RESERVE BANK OF MALAWI

FINANCIAL SECTOR TECHNICAL ASSISTANCE PROJECT (FSTAP)

MALAWI: BASELINE FINANCIAL LITERACY AND CONSUMER

PROTECTION HOUSEHOLD SURVEY

FINAL REPORT

Ephraim W. Chirwa

Peter M. Mvula

August 2014

Wadonda Consult Ltd Room 317/309 MPC Building

PO Box 669, Zomba

Malawi

Tel-Fax: (265) 01 527 399

Tel : (265) 01 527 736

Mobile: (265) 0888 839 296 / 0888 827 933

Email: wacoafrica@wadonda.com

Web: http://www.wadonda.com WACOWACOWACOWACOL

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Table of Contents

List of Tables ....................................................................................................................................................................... iii List of Figures ..................................................................................................................................................................... iv

List of Abbreviations ........................................................................................................................................................ vi Executive Summary ........................................................................................................................................................ vii 1. Introduction ............................................................................................................................................................... 1

1.1 Background and Context............................................................................................................................. 1

1.2 Importance of Financial Literacy and Consumer Protection .......................................................... 2

1.3 Financial Literacy and Socio-Economic Status .................................................................................... 3

1.4 Objectives of the Survey .............................................................................................................................. 4

1.5 Survey Methodology ..................................................................................................................................... 5

1.5.1 Sample Design ............................................................................................................................................ 5

1.5.2 Selection of Households and Individual Respondents ................................................................ 5

1.5.3 Data Collection Method .......................................................................................................................... 6

1.5.4 Methods of Data Analysis ....................................................................................................................... 7

1.3.4.1 Stratification of the Sample and Weights ............................................................................... 7

1.3.4.2 Methods of Analysis ........................................................................................................................ 8

2. Households and Respondents Characteristics .............................................................................................. 9

2.1 Households Characteristics ........................................................................................................................ 9

2.1.1 Gender of Household Heads ................................................................................................................. 9

2.1.2 Marital Status of Household Heads ..................................................................................................... 9

2.1.3 Literacy and Education of Household Heads ................................................................................ 10

2.2 Characteristics of Respondents ............................................................................................................... 11

2.2.1 Gender and Marital Status .................................................................................................................... 11

2.2.2 Literacy and Education Levels............................................................................................................. 12

2.2.3 Main Socio-Economic Status ............................................................................................................... 13

2.2.4 Participation in Household Financial Decisions ........................................................................... 13

3. Incomes and Economic Activities in Malawi ................................................................................................ 15

3.1 Understanding Personal Incomes .......................................................................................................... 15

3.1.1 Sources of Incomes ................................................................................................................................. 15

3.1.2 Seasonality in Personal Incomes and Estimated Incomes ........................................................ 16

3.1.3 Remittances ............................................................................................................................................... 17

3.2 Understanding Household Incomes ..................................................................................................... 18

3.2.1 Sources of Household Incomes .......................................................................................................... 18

3.2.2 Seasonality in Household Incomes and Estimated Incomes ................................................... 20

3.3 Self-Assessment of Financial Position ................................................................................................... 20

3.4 Understanding Sources of Financial Advice ....................................................................................... 21

4. Financial Literacy in Malawi ............................................................................................................................... 23

4.1 Understanding Financial Concepts ....................................................................................................... 23

4.2 Understanding Mobile Money and Agency Banking ...................................................................... 32

4.2.1 Access to Mobile Phones ...................................................................................................................... 32

4.2.2 Use of Mobile Phones for Financial Transactions ........................................................................ 32

4.3 Determinants of Financial Literacy ........................................................................................................ 35

5. Knowledge of Financial Services and Products in Malawi ...................................................................... 41

5.1 Possession of Financial Services and Products .................................................................................. 41

5.2 Choices and Decisions about Financial Services and Products ................................................... 43

5.3 Financial Consumer Protection ............................................................................................................... 46

5.4 Financial Information and its Sources ................................................................................................... 50

5.5 Assessment of Financial Services............................................................................................................ 51

5.6 Factors Associated with Access to Financial Services ..................................................................... 56

6. Money Management Practices in Malawi ..................................................................................................... 61

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6.1 Budgeting and Planning ............................................................................................................................ 61

6.2 Savings Behaviour ........................................................................................................................................ 64

6.3 Adequacy of Money for Basic Needs ..................................................................................................... 68

6.4 Debts and Debt Management ................................................................................................................. 70

6.5 General Money Management .................................................................................................................. 73

6.6 Determinants of Budgeting and Savings Behaviour ....................................................................... 77

7. Financial Planning Practices in Malawi .......................................................................................................... 84

7.1 Planning for Expected Events .................................................................................................................. 84

7.2 Planning for Unexpected Events ............................................................................................................ 85

7.3 Planning for Older Age ............................................................................................................................... 89

7.3.1 Planning for Older Age for the “Under 60 Year Olds” ................................................................. 89

7.3.2 Managing Life for the “Above 60 Year Olds” ................................................................................. 92

7.3.3 Knowledge about Pensions ................................................................................................................. 93

7.4 Planning for Children’s Future ................................................................................................................. 96

7.5 General Planning .......................................................................................................................................... 97

7.6 Determinants of Financial Planning for Older Age .......................................................................... 99

8. Main Findings and Recommendations ....................................................................................................... 102

8.1 Main Findings ............................................................................................................................................. 102

8.2 Recommendations .................................................................................................................................... 110

8.2.1 Financial Education Programmes and Strategies ..................................................................... 110

8.2.2 Monitoring and Evaluation ............................................................................................................... 111

9. References ............................................................................................................................................................. 113

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List of Tables Table 1: Stratification of the Sample ........................................................................................................................... 5

Table 2: Content of the Questionnaire and Logical Path to Conduct Interview ......................................... 7

Table 3: Marital Status of Household Heads (%) ................................................................................................... 10

Table 4: Literacy and Education Levels of Household Head (%) ..................................................................... 10

Table 5: Marital Status of Respondents.................................................................................................................... 12

Table 6: Highest Level of Schooling by Population Segments ........................................................................ 13

Table 7: Main Socio-Economic Status of Respondents ...................................................................................... 13

Table 8: Participation in Financial Decision Making by Population Segments (%) .................................. 14

Table 9: Personal Income Sources in Past 12 Months (%) ................................................................................. 15

Table 10: Main Source of Personal Income ............................................................................................................. 16

Table 11: Proportion with Seasonal Personal Income ........................................................................................ 16

Table 12: Proportion with Daily/Weekly/Monthly Personal Income Variations (%) ................................ 17

Table 13: Proportion with Estimated Average Monthly Personal Income (%) .......................................... 17

Table 14: Frequency of Provision of Income or Help In-kind (%) ................................................................... 18

Table 15: Sources of Household Income in Past 12 Months (%) ..................................................................... 19

Table 16: Main Source of Household Income (%) ................................................................................................ 19

Table 17: Proportion with Estimated Average Monthly Household Income Groups(%) ....................... 20

Table 18: Proportion that Get Information or Advice for Important Financial Decision ........................ 21

Table 19: Sources of Financial Advice (%) ............................................................................................................... 22

Table 20: Key Financial Literacy Questions in the Survey ................................................................................. 24

Table 21: Proportion with Correct Answers to Financial Literacy Questions (%) ..................................... 25

Table 22: Proportion with Correct Answers by Socio-Economic Groups (%) ............................................. 26

Table 23: Distribution of Financial Literacy Index by Population Groups ................................................... 26

Table 24: Distribution of Financial Literacy Index by Socio-Economic Groups ......................................... 27

Table 25: Proportion of Adults who Saved Money as a Child (%) .................................................................. 28

Table 26: Proportion of Adults with Knowledge of Financial Terms (%) ..................................................... 29

Table 27: Self-Assessment of Time Preferences (%) ............................................................................................ 30

Table 28: Self-Assessment of Behavioural Traits (%) ........................................................................................... 31

Table 29: Proportion of Adults Owning/Using Mobile Phones (%) ............................................................... 32

Table 30: Knowledge of Use of Mobile Phones for Financial Services (%) .................................................. 32

Table 31: Use of Mobile Phones for Financial Services ....................................................................................... 33

Table 32: Use/Willingness to Use Alternative Places for Financial Services (%) ........................................ 35

Table 33: Probit Regression Marginal Effects – Financial Literacy by Type................................................. 37

Table 34: Ordinary Least Squares Regression on Financial Literacy Index ................................................. 39

Table 35: Current Possession of Financial Products and Services (%) .......................................................... 42

Table 36: Proportion Possessing Financial Products and Services (%) ......................................................... 43

Table 37: First Mentioned Products and Services Chosen by Respondent (%) ......................................... 44

Table 38: How Adults Got Information about Financial Product (%) ............................................................ 45

Table 39: Proportion of Adults Checking Terms and Conditions about Financial Product (%) ........... 46

Table 40: Proportion of Adults Experiencing Conflict with Financial Service Provider (%) .................. 47

Table 41: Use of Media as Sources of Information (%) ....................................................................................... 50

Table 42: Frequency of Talking about Financial Institution and Services (%) ............................................ 51

Table 43: Proportion with Revealed Demand for Bank Loan (%) ................................................................... 54

Table 44: Perceptions on Different Types of Financial Service Providers (%) ............................................ 55

Table 45: Probit Regression Marginal Effects – Participation in Financial Market Segments............... 58

Table 46: Probit Regression Marginal Effects – Bank Account and Bank Loan Potential Demand .... 60

Table 47: Proportion Budgeting and Planning Use of Money (%) ................................................................. 62

Table 48: Proportion Saving and Frequency of Saving (%) .............................................................................. 64

Table 49: Proportion of Adults Running Short of Money (%) .......................................................................... 68

Table 50: Proportion of Adults Borrowing Money to Buy Food and Basics (%) ........................................ 70

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Table 51: Proportion of Adults Borrowing Money to Pay Debts (%) ............................................................. 72

Table 52: Proportion of Adults Who Have to Repay Borrowed Money (%) ................................................ 72

Table 53: Percent of Respondents with Debt Level Relative to Income (%) ............................................... 73

Table 54: Proportion of Adults Who Know Amount of Money Spent Last Week (%) .............................. 74

Table 55: Proportion of Adults Who Know Amount of Money Available (%) ............................................ 74

Table 56: Overall Self-Assessment of Money Management (%) ..................................................................... 75

Table 57: Overall Self-Assessment of Purchasing Behaviour (%) .................................................................... 76

Table 58: Proportion of Adults with Confidence in Managing Money/Finances (%) .............................. 76

Table 59: Probit Regression Marginal Effects – Planning Use of Money ...................................................... 79

Table 60: Probit Regression Marginal Effects – Savings Behaviour ............................................................... 80

Table 61: Probit Regression Marginal Effects – Current Debt Obligations ................................................. 81

Table 62: Probit Regression Marginal Effects – Very Confident in Money Management ...................... 82

Table 63: Expected Major Expenditures and Ability to Pay (%) ...................................................................... 85

Table 64: Worries about Ability to Pay for Expected Expenditure or Bill (%) ............................................. 85

Table 65: Planning for Unexpected Events and Readiness (%) ....................................................................... 86

Table 66: Persons Responsible for Planning for Major Expected and Unexpected Expenses (%) ...... 88

Table 67: Solutions to Unexpected Drop in Income (%) .................................................................................... 89

Table 68: Proportion with Plans for Meeting Household Expenses in Old Age (%) ................................. 90

Table 69: Proportion with Plan for Meeting Household Expenses in Old Age Already in Place (%) .. 91

Table 70: Whether Sources Would Provide Enough Money to cover Expenses in Full (%) .................. 91

Table 71: Receipt of Pension and Contribution to Pension (%) ...................................................................... 92

Table 72: Sources of Money to Cover Expenses in Old Age for Over 60 Year Olds (%) .......................... 93

Table 73: Mean of Number Children and Economically Dependent Children .......................................... 96

Table 74: Nature of Planning for the Children’s Future (%) .............................................................................. 97

Table 75: Proportion that Plan Ahead for the Future (%) .................................................................................. 99

Table 76: Probit Regression Marginal Effects – Planning for Older Age ................................................... 100

Table 77: Monitoring and Evaluation Indicators ............................................................................................... 112

List of Figures Figure 1: Age Structure of Baseline Sample and National Population ........................................................... 6

Figure 2: Headship of Sample Households .............................................................................................................. 9

Figure 3: Gender of Survey Respondents (%) ........................................................................................................ 11

Figure 4: Literacy of Respondents by Population Segments ........................................................................... 12

Figure 5: Household Self-Assessment of Financial Status compared to a Year Ago (%) ....................... 20

Figure 6: Household Self-Assessment of Financial Status Looking at a Year Ahead (%) ....................... 21

Figure 7: Proportion Very Likely to Use Mobile Phones for Financial Services (%) .................................. 34

Figure 8: Proportion Searching for Information from a range of Sources (%) ........................................... 44

Figure 9: Nature of Searching for Information from a Range of Sources (%) ............................................. 45

Figure 10: Actions taken to Resolve Conflict with Service Provider (%) ...................................................... 48

Figure 11: Why No Actions Taken to Resolve Conflict with Service Provider (%) ..................................... 48

Figure 12: Actions Expected to Resolve Conflict with Service Provider (%) ............................................... 49

Figure 13: Knowledge about Key Consumer Protection Institutions (%) .................................................... 50

Figure 14: Proportion with Revealed Demand for Bank Accounts (%) ......................................................... 52

Figure 15: Proportion with Revealed Demand for Banks Account by Socio-Economic Status (%) .... 53

Figure 16: Motivating Factors for Opening Bank Account (%) ........................................................................ 54

Figure 17: Motivating Factors for Taking a Bank Loan (%) ................................................................................ 55

Figure 18: Proportion Experiencing Problems in Using Financial Services (%) ......................................... 56

Figure 19: Proportion Planning Use of Money by Socio-economic Groups (%) ....................................... 63

Figure 20: Proportion that Save some Money by Socio-economic Groups (%) ........................................ 65

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Figure 21: Uses of Left-over Money (%) ................................................................................................................... 66

Figure 22: Methods of Savings (%) ............................................................................................................................ 67

Figure 23: Reasons for Choosing Savings Method (%) ....................................................................................... 68

Figure 24: Main Reasons for Running Short of Money for Food and Necessities (%) ............................. 69

Figure 25: Coping Mechanisms when Running Short of Money for Food and Necessities (%) .......... 70

Figure 26: Proportion that Ever Borrow Money by Socio-economic Groups (%) ..................................... 71

Figure 27: Ability to Borrow More for adults that had to Repay any Money (%) ...................................... 73

Figure 28: Proportion Very Confident in Managing Money by Socio-economic Groups (%) .............. 77

Figure 29: Measures taken to Prepare for Unexpected Expenses (%) .......................................................... 87

Figure 30: Whether one was Worried about the Meeting the Unexpected Expenses (%) .................... 87

Figure 31: Incidence of Unexpected Drop in Income (%) ................................................................................. 88

Figure 32: Extent of Worry at being unable to Meet Household Expenses in Old Age (%) .................. 92

Figure 33: Knowledge of Pensions (%) ..................................................................................................................... 94

Figure 34: Knowledge of the Operations of a Typical Pension (%) ................................................................ 94

Figure 35: Knowledge of the National Pension Scheme in Malawi (%) ....................................................... 95

Figure 36: Knowledge about the Operation of the New Pension Scheme (%) ......................................... 96

Figure 37: Proportion that ‘Try to Save for the Future’ (%) ............................................................................... 97

Figure 38: Proportion that ‘Try to Save Some Money Regularly, even if it is only a Little’ (%) ............ 98

Figure 39: ‘Always Try to Have Some Provision for Emergencies’ (%) .......................................................... 98

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List of Abbreviations ATMs Auto Teller Machines CAMA Consumer Association of Malawi CFTC Competition and Fair Trading Commission EAs Enumeration Areas FINCA Foundation for International Credit Assistance FSTAP Financial Services Technical Assistance Project GOM Government of Malawi MARDEF Malawi Rural Development Fund MFIs Microfinance Institutions MRFC Malawi Rural Finance Company NSO National Statistical Office RBM Reserve Bank of Malawi ROSCAs Rotating Savings and Credit Associations SACCO Savings and Credit Cooperative Organisation SMS Short Message Service VSLAs Village Savings and Loan Associations

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Executive Summary Introduction Although Malawi has undergone through financial sector reforms since the early 1980s, the proportion of the population with access to formal financial services remains low and a significant proportion rely on the informal financial sector. In addition to problems of access to financial services, there is a gap in knowledge of the extent to which adult Malawians are financially literate and knowledgeable about financial products and consumer protection in Malawi. Through the Financial Services Technical Assistant Program (FSTAP), the Reserve Bank of Malawi commissioned a baseline survey in the second half of 2013 to form a basis for interventions in financial literacy in Malawi. The main objective of the baseline survey was to obtain information on knowledge of financial management and services as a basis for designing appropriate interventions for improving financial literacy and consumer protection in Malawi. The baseline survey covered a randomly selected national representative sample of 4,999 households throughout Malawi across four strata including urban – cities, urban –district towns, peri-urban and rural areas. Face-to-face interviews were conducted using a structured questionnaire administered to one randomly selected adult member above the age of 17 years old (from 15 years where there were no adult members of the household above 18 years). The socio-economic profile of households included in the baseline survey is consistent with the national population in terms of the population age structure, save minor difference in some selected features. The literacy rate is 71% among household heads and 67% among adult respondents. Most of the respondents have the highest completed level of education as primary school (standards 1 – 8) representing 57.9% of respondents. Most of the respondents are decision-makers in household finances as they contribute to the household budget (93%) and participate in the household decision about money (94%). Incomes and Economic Activities Most households in Malawi have fragile incomes and tend to rely more on unstable sources,

and the situation is consistent with previous findings of low incomes and high incidence of

poverty in Malawi. This is mainly due to the fact that self-employment is the most common economic activity and most important source of income among adult Malawians both at individual and household levels. Formal and informal employment was reported by only 9.3% of adult Malawians while only 0.3% of adult Malawians are actively looking for employment. There is high instability in incomes with 93% of adult Malawians reported that their incomes are seasonal and the seasonal variations occur regardless of times of they get most incomes or when they get the least incomes. About 67% of adult Malawians have personal incomes averaging less than MK10 000 per month while 48% of households reported receiving average monthly household incomes of less than MK10 000, although the proportions are much higher in rural areas compared to urban areas. These low levels of formal employment imply that most of the income among Malawians comes from unstable sources with consequences on people’s ability to save and invest in productive activities. There is limited recourse to advice from financial providers such as banks, microfinance

organisations, insurance providers, ROSCAs or someone in a savings club. In terms of getting information or advice when making important financial decisions, 55% strongly agreed that they always get information or advice, regardless of the population segments. The main source of financial advice is their spouse or partner as reported by 45% of adult Malawians, followed by a friend (40%) and a parent or grandparent (19%).

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Financial Literacy The levels of financial literacy vary considerably and depend on the financial concept and

terms known by consumers, but financial illiteracy cuts across population segments and

across formal education levels. Using the seven indicators of financial literacy relating to simple division, inflation, simple interest rate, compound interest rates, absolute and percentage discounts, risk and risk diversification, the most correct answers were on simple division (82%), followed by absolute and percentage discount (64%) and compound interest rate (54%). However, combining the scores, only 1% of respondents gave correct answers to all 7 questions, 27% got 5 – 6 questions right and 21% got only 1 – 2 questions right. The mean financial literacy is 4 correct answers representing 57% average score. Some of the adult Malawians with tertiary education and in formal employment got some of the questions on financial literacy wrong. The experience of saving money as a child, mainly saving the money in the money box at

home regardless of whether they are in urban – cities or rural areas, is positively associated

with financial literacy. About 55% of adult Malawians saved money as a child and this tends to be associated with financial literacy and higher saving behaviour. In addition, having a bank account, medium to long term planning and formal levels of education are positively associated with levels of financial literacy. The knowledge of financial terms such as interest rate, insurance, shares, stock exchange,

inflation and devaluation is low, and the non-existence of equivalent local language terms

(except for interest rate) made matters worse. The interest rate is mostly known what it means by 43%, insurance and shares are known by 28% each, stock exchange is only known by 6%, inflation is known by 7% and devaluation is known by 14% of respondents. There are, however, urban – rural biases in knowledge of these concepts with much higher levels in the urban areas compared to rural areas. There is moderate access to mobile phones although ownership of mobile phones remains

low, but the opportunities for use of mobile phones for financial transactions are huge. Access to mobile phone is at 56% although only 36% own a mobile phone. There is urban – rural bias in mobile phone ownership with 71% of those living in urban – cities compared to only 29% of those living in rural areas owning a mobile phone. Most adults (more than 75%) have knowledge of use of mobile phones for financial services such as receiving/transferring money, paying bills, buying airtime and Me2U. Although most respondents have actually used mobile phones to buy air time and sending airtime (Me2U), a high proportion of respondents are very likely to use a mobile phone for receiving money (73%), transferring money (79%) and paying bills (65%). There is high potential demand for alternative places for accessing financial services other

than banking halls of financial institutions. Most would also welcome the use of alternative places for accessing financial services, most popular being large agro-input dealers (96%), bank branch (81%) and local supermarkets (80%). Some of these alternative places are much closer to customers particularly for the rural population for which a large proportion remain without access to financial services. Knowledge of Financial Services and Products Knowledge of financial products and services, holding of formal financial services and

products, and knowledge about financial consumer protection remain limited in Malawi and

the situation is acute in rural areas. Most adults do not have information about financial

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products and services and have limited information about financial consumer protection agencies and how to resolve conflicts with financial service providers. There is low holding of formal financial sector products and services in Malawi, with only 17% and 6% having products and services in the formal and semi-formal financial services compared to 53% in the informal sector and 34% without any financial product and service. There are urban – rural differences with a higher proportion of urban city populations (47%) using formal products and services than rural populations (10%). Only 15.4% of adult Malawians held bank savings/deposit account in 2013 while 25% of

adult Malawians have informal savings accounts in ROSCAs and VSLAs. The holding of formal savings and current accounts has marginally declined between 2008 and 2013, suggesting a net closure of accounts. The potential demand for bank accounts remain low, including those with accounts and those intending to open one in future, at 29% of adult Malawians. However, the availability of financial services may be key since 61% among urban – city populations compared to 22% among rural populations with bank accounts or intending to open one. Other key socio-economic factors that increase the probability of having a bank account are financial literacy, incomes, gender (male head or male respondent), age of respondent (inverted u-shape), education and formal employment. The motivating factors for opening a savings account include interest rates, bank charges and the bank’s reputation mentioned by at least 25% of respondents. The demand for bank loans is even lower as only 8% of respondents indicated that they have a bank loan or intending to take one, with bank’s reputation and credit interest rates being the main considerations. In choosing financial products and services, most respondents search for information from a

range of sources and are pro-active by approaching the service providers. However, most learn about financial products and services from friends and family (58%), followed by service providers from which 36% learnt about the products. This implies that targeting financial education to specific groups may have contagion effects as friends and families that attend such training are likely to pass the knowledge to others within communities. Most adult Malawians have limited information about consumer protection agencies,

procedures for reporting problems experienced in the course of accessing financial services,

and resort to complain to traditional and community leadership when they are in conflict

with financial service providers. Only 74% have heard about the Reserve Bank of Malawi, 13% have heard of the Reserve Bank of Malawi Division of Consumer Protection and 47% have heard about the Consumer Association of Malawi. It is also apparent that most consumers are not aware of procedures for seeking redress with appropriate authorities whenever they are in conflict with financial service providers. The informality of many financial services may also play a part in this gap in knowledge. Although only 8% of adults have had conflicts with financial service providers, most did nothing about it and those that acted opted to stop using the service and approached the service providers through community elders. Approaching service providers through community elders, stopping using service, approaching the police and by discussing informally are the most common actions that respondents would take in the future if faced with a situation of conflict with a service provider. The proportion that did not take action after experiencing conflict with service providers indicated that they are not aware of government agencies that can be approached for help. In designing consumer financial education programmes, the use of the radio has the

potential to reach out to a greater proportion of Malawians. The survey revealed that 62% use the radio as a source of information. Newspapers, though not replacing radio, would be useful in urban areas such as cities and district towns. Modern media facilities such as internet and SMS

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seem to be less effective vehicle for financial education as 3.8% and 3.9% regularly use such facilities, respectively. There are mixed perceptions about five service providers (banks, other lending and MFIs,

community groups, katapila and insurance companies) on the quality of services. Community groups score highly with respect to getting things done easily, quick service, providing information that is easy to understand and reasonable charges. Katapila is known for lending too easily and getting borrowers into problems and taking property away property when borrowers fail to repay the loan. The main problems experience by consumers using financial services are mainly related to long time to withdraw money from the bank and ATMs not working when people want to withdraw money. Money Management Capabilities Most adult Malawians, 91%, plan use of money when they receive it and 47% of those that

plan use of money do so always and 79% indicated that they keep their plans. The likelihood of planning increases with improvements in financial wellbeing, seasonality of income and education levels. Although, a large proportion of those that plan indicated that they keep the plan, it is not known to what extent these plans are documented by the household. The proportion of adult Malawians that has some money left over after paying for food and

basic necessities is high, 76%, but only 18% save on a regular basis. The incidence of saving is lowest in the rural areas, 75% and 16% save on a regular basis. The main reason for saving some money is to keep it for future food and other necessities needs as revealed by 75% of adult Malawians. Other reasons include keeping money for unforeseen expenditures (53%), spending money of self or buying non-essential items (51%) and to invest the money in business or farming (49%). Savings behaviour is positively associated with the level of financial literacy, the level of income, improvement in financial wellbeing, seasonality of income, marital status (monogamy or polygamy), upper primary and lower secondary education, self-employment and savings experience as a child. The results underscore the importance of developing a savings culture from childhood as one way of promoting future savings behaviour. Most adult Malawians keep their money at home (81%), saving at a bank (20%), at an

informal savings and credit group (14%) and at informal saving group (chipereganyu) (10%). Other methods mentioned by less than 8% of adult Malawians include saving through keeping livestock, using someone else for safe keeping and saving through stocks for business. The methods of savings that appeals most are simple to use, convenient to get to, safe from temptations to use the money and safe and trustworthy. The baseline survey has therefore established that most savings are kept outside the formal financial system. While a high proportion plan and save, 90% run short of money to cover expenses for food

and other basic needs and 70% have ever used debt to finance basis necessities. They run short of money because they feel that their incomes are insufficient or income fluctuates or it is unreliable and indeed many borrow from family and friends (63%) or go for ganyu work (61%). However, the proportion of adult Malawians that borrow to pay debts is lower, only 18% and most borrow sometimes rather than regularly. With respect to current debt obligations, a third of adult Malawians (38% among urban –city adults) have to repay borrowed money. Most adult Malawians with debts contract debts that are typically less than or equal to their monthly income, but 21% contracted debts that were more than their monthly income. Most adult Malawians revealed that they are disciplined in managing their money, learning

from mistakes others make and being conscious buyers of unnecessary things and consider

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affordability. About 79% of adults revealed that they are ‘very disciplined’ in managing their money while 67% learn from the mistakes that others make in managing their money. Malawians are also conscious buyers of unnecessary things before buying food and basic necessities and most never buy unnecessary things when they know they cannot afford them. More than half of adult Malawians (56%) revealed that they are very confident in money management, and such confidence is high among the middle age group (35 – 59), increases with level of formal education and increases with formality of employment. Financial Planning Capabilities There are several aspects of financial planning that were central to the study particularly focusing on planning for expected and unexpected expenses, planning for old age and planning for children. Generally, there is limited planning for old age in Malawi and this may be driven by the low income levels. Most households are desperate on how they are going to meet planned and unexpected expenses and very few have thought on a pension as a plan for old age. The following are the main findings on financial planning in Malawi: There is limited planning for expected and unexpected expenses, with most adult

Malawians being unable to cover such expenses equivalent to their monthly income in full. Although 74% of adults were expecting a major expense or bill equivalent to their monthly income, 59% of these would not be able to cover such expenses or to pay for such a bill in full. And 45% of adult Malawians are desperate and had done nothing to enable them cover such expected expenses in full without resorting to borrowing. Similarly, 87% of adult Malawians cannot cover unexpected expenses in full the following day without borrowing money that they would pay back and 78% are doing nothing to prepare for such an eventuality. This is consistent with problem of insufficient or irregular incomes that most people feel they have to manage their lives properly. It is not surprising that most people are very worried on how they will cover expected or unexpected expenses with fragile incomes, with many respondents and their households (86%) experiencing a drop in income in the past 12 months. Most adult Malawians are challenged on the concept of planning for old age among those

under the age of 60 years and only 11.4% have savings plans for old age. The most popular plan for old age is to sell or rent out non-financial assets such as land, house and livestock (40%), followed by business (37%) and always working (31%). About a third of respondents have no plans at all and only less than 3% have pension plans. Similarly, for adults over 60 years old, the main ways of covering expenses are to always work, business income, selling or renting out non-financial assets and financial help or support from family. The probability of having a plan for old age significantly increases with levels of financial literacy, income levels, improvements in financial wellbeing, seasonality of income, male headship of households, age of respondents, highest levels of education (from secondary) and nature of employment. People’s knowledge about pensions vary, with 42% of adult Malawians not having heard

about pensions and 41% having heard about them and understanding meaning of pensions. A higher proportion of adults in urban –cities (58%) compared to 38% among adults in the rural areas. Only 11% of those that have heard about pension and know what they mean, believe that both the employer and employee contribute for the employee’s retirement. The knowledge that both the employer and employee contribute money for the employee’s retirement is even low among those with tertiary education (38%) and with upper secondary education (12%), and among those in formal sector employment (14%) but surpassed by those in informal sector employment (14%).

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The National Pension Scheme is not very much known by adult Malawians that have ever

heard of pensions and understand them, only 10% know about it and only 50% of these

know that it is mandatory for employers to participate. The proportions that have heard about the National Pension Scheme is also with respect to education and nature of employment, with the highest proportion in these groups being 27% among those with tertiary education and the highest proportion of 26% among formal sector employees, respectively. Recommendations The low levels of financial literacy across the population segments and across different

levels of education in Malawi justify the development of a comprehensive financial

education programme on various issues of money and financial management. Such programmes in the context of Malawi should not only focus on the financially excluded population, but the financially included as well as their financial literacy seem to be wanting as well. This will require utilizing various delivery channels for financial education to reach out large proportions of the Malawian population. Given the general low literacy levels in Malawi, it is therefore important for any financial

education programme to develop local language terms for some of the financial terms and

concepts. Most of the financial terms and concepts do not have local language equivalent terms and are not easily translated into local languages without describing what they mean. Financial education programmes should be developed in English and main local languages

in Malawi. Although the bulk of the population has less than secondary education level, the survey has shown that there are pockets among the educated from secondary to tertiary levels that have poor understanding of financial concepts and financial terms. The use of mass media complemented by other media channels may be recommended as

channels of for delivering financial education. In Malawi, most households have access to a radio. Development of radio programmes such radio drama and discussion forums and having specific times for airing the programmes and providing contact numbers after broadcast may be useful interventions. The increase in the number of local radio stations and TV broadcasters offer additional opportunities for harnessing the potential of media to deliver financial education, including soap opera on TV. TV programmes may prove useful for targeting the high income groups and working class in urban areas. The Reserve Bank of Malawi should increase its visibility in championing financial consumer

protection and in articulating the financial grievance reporting procedures. There should be public awareness of consumer protection institutions and the procedures for approaching them. This should include the establishment of walk in or phone-in centres (hotline numbers) for consumers to register their complaints about financial services and also get help on how to resolve some of the conflicts. Multiple stakeholders should be used in the delivery of financial education programmes in

Malawi given the diversity of gaps in financial literacy and financial capability. This should include consumer protection agencies, financial service providers, non-governmental programmes civil society organisations and farmer organisations. These can target specific groups such as secondary and college students, workers and micro-entrepreneurs. Some of the civil society organisations that may be targeted to deliver financial education include

• Consumer Association of Malawi • Economic Association of Malawi • Malawi Economic Justice Network

xiii

• Society of Accountants in Malawi • Malawi Microfinance Network • Bankers Association of Malawi • Malawi Congress of Trade Unions • Employers Consultative Association of Malawi

Financial education programmes should be integrated into some of the development

programmes in Malawi that offer cash incomes to the poor. For example, the scaling-up of the social cash transfer provides a huge opportunity for improving financial literacy if financial education can be integrated. Similarly, public works programmes that are implemented by the Malawi Government through the Local Development Fund and GOM-EU provide avenues for reaching out to rural citizens on financial education. Where such programmes are utilized financial education should not be delivered to intended beneficiaries only but also other households in communities where these projects are implemented. In the medium to long-term, there is need to revisit the education curriculum in primary and

secondary schools so that basic financial skills and financial literacy are introduced in some

of the life skill courses.

1

1. Introduction 1.1 Background and Context Since the early 1980s, Malawi has gone through several structural reforms at macro and sectoral levels including reforms in the financial sector with varying successes (Chirwa and Mlachila, 2004). However, despite these reforms, the Malawi economy remains fragile with erratic economic growth and high poverty levels. Over the past three decades, the economy has at times achieved macroeconomic stability, but this has hardly been sustained. In more recent times, a period of nearly six consecutive years from 2006characterized good macroeconomic and fiscal policies, culminating in a more stable macroeconomic environment. But the macroeconomic picture changed in 2011 when there began a period of unstable exchange rate, high interest rates and high inflation. Agriculture remains the main source of economic growth and livelihoods in Malawi, contributing almost 40% of GDP and generating over 90% of foreign exchange earnings. This main source of economic growth is dominated by the smallholder sector, using rain-fed cultivation, where a high proportion of output is produced to meet subsistence needs. The incidence of poverty in Malawi remains high, estimated at 50.7% of people living below the poverty line in 2011 (NSO, 2012). Malawi has one of the lowest per capita GNI of $280 in the world. It is estimated that 24.5% of Malawians are ultra-poor, who struggle to meet basic food needs (NSO, 2012). The situation is exasperated by high levels of illiteracy, the national literacy rate for persons over the age of 15 years being 65.4%, and limited employment opportunities. The financial sector reforms have increased the number of players and number of products in Malawi. However, the level of financial inclusion in the country remains low. Most of the formal financial institutions are mostly in the urban areas, leaving rural areas mostly underserved. Granted that about 90% of the population lives in the rural areas, it should not be surprising that a large proportion of the population have no access to formal financial services. In 2010, it was estimated that only 19% of individuals in Malawi have/use to formal banking services; that 7% had experience with the non-bank financial institutions, and that19% had experience with the informal sector (FinScope, 2008; World Bank, 2010). There are several reasons that can be attributed to low access to financial services and they include low income levels, distance to banking and financial facilities which increases transaction costs relative to income levels. This low access to financial services has implications for economic development. For example, NSO (2012) finds that of the 20% households that operate non-farm enterprises only 4.4% and 1.4% obtained a non-agricultural loan from bank or other institution in the urban and rural areas, respectively. Similarly, of the 8% of households that obtained a loan, the proportion of borrowers from banks were 33% in the urban areas compared to 6% in the rural areas. Other factors such as infrastructure are also critical in explaining the urban-rural disparities in access to financial services in Malawi. For example, most of the roads are only passable in the dry season. However, access to telecommunication services is improving although the rural areas still lag behind. National Statistical Office (2012) finds that about 73% of households in urban areas have access to a mobile phone compared to 29% in the rural areas. This is a major improvement from the situation in 2004 when the statistics were 18% for urban areas against 0.8% for rural areas. Although the extent of financial exclusion is documented in Malawi, there is a gap in knowledge about the level of financial literacy and how socio-economic factors affect financial literacy and how, in turn, financial literacy may affect planning, management and use of incomes and wealth. For this reason, the Reserve Bank of Malawi under the Financial Services Technical Assistance Project (FSTAP) commissioned a nation-wide baseline survey of adults from 15 years in order to assess the level of financial literacy in Malawi. The FSTAP includes a component on financial consumer protection and financial literacy, which will support the Government’s efforts to increase

2

public trust in, and usage of, the financial sector by strengthening the legal and regulatory framework for financial consumer protection; enhancing the institutional arrangements for consumer protection in all financial services; and, by promoting financial literacy initiatives that will help the average person understand the risks and rewards of accessing and using financial products (World Bank, 2011). The baseline survey covered 4,999 households randomly selected from four strata reflecting different income levels, nation-wide. The main objective of the baseline survey was to obtain information on knowledge of financial management and services among households to enable the authority to measure the success of any intervention that might be put in place to increase the levels of financial literacy and consumer protection in Malawi. The baseline survey gathered information from adult members of the households about their money management, financial planning, usage of financial products and services, levels of financial literacy and sources of income and earnings for households or their own account. The baseline survey was conducted between July and November 2013. As noted by Garcia et al (2013) evidence about the level of financial literacy is necessary for countries to design and implement efficient programmes in financial education. 1.2 Importance of Financial Literacy and Consumer Protection Financial literacy as one’s ability to understand own finances and to make informed decisions about using and spending money, plays important roles in financial decision-making at personal and household level (Lewis and Messy, 2012). More broadly, World Bank et al (2009) defines financial literacy as a “combination of consumers’/investors’ understanding of financial products and concepts and their ability and confidence to appreciate financial risks and opportunities, to make informed choices, to know where to go for help, and to take other effective actions to improve their financial well-being”. Atkinson and Messy (2012) note that a financial literate person should have knowledge about key financial concepts and ability to apply numeracy skills in financial situations. More recently, literature suggests that financial literacy is a component of financial capability. Financial capability is defined as the internal capacity to act in one’s best financial interest, given socioeconomic and environmental conditions (World Bank, 2013). It constitutes financial knowledge (financial literacy), attitudes, skills, and behaviour of consumers with respect to understanding, selecting and using financial services, and the ability to access financial services that fit their needs. It is argued that financial knowledge can affect a range of financial behaviours such as wealth accumulation, stock market participation, portfolio diversification, participation and asset allocation, retirement plans, indebtedness and responsible financial behaviour (Monticone, 2010; Jappelli, 2010). Financial literacy can also help prepare households and individuals for tough times (such as economic crises) by promoting mitigation strategies through accumulation and diversification of assets and hedging themselves against risks (World Bank et al., 2009). Literature also suggests that financial literacy reinforces timely payment of bills and limits the levels of indebtedness that enables credit access in tight markets. Financial literacy also helps to improve the efficiency and quality of financial services through demand for better products and services by consumers, in the course, reducing the service provider’s information advantages (World Bank et al, 2009). This in turn can also foster competition among service providers as they attract customers to their products and services. Jappelli (2010) argues that “lack of financial literacy may create more favourable conditions for deceitful financial practices and unfair competition in financial markets, and be a serious impediment to effective financial intermediation”. Financial literacy can also promote stability of the financial and economic system thereby promoting economic growth and development (Shambare and Rugimbana, 2012; World Bank et al, 2009).

3

While the case for financial literacy has been made more strongly in the developed and emerging markets, there is greater realisation that financial education is also critical in the developing countries where the extent of financial exclusion is high. As Shambare and Rugimbana (2012) argue, the global financial crisis has meant that financial literacy is important not only to individuals but also to policy makers and financial institutions. Most of the studies on financial literacy have therefore been conducted in the developed countries (see reviews in World Bank et al., 2009) although the evidence from the developing countries is emerging. There is also increasing interest in financial literacy and financial education in Africa as illustrated by studies in Kenya, Uganda and South Africa (World Bank et al, 2012; Bank of Uganda and GIZ, 2011; Shambare and Rugimbana, 2012). Financial literacy is generally measured by peoples’ knowledge on interest rates and its calculation, knowledge on inflation and time value of money and their understanding of the concept of risks (Xu and Zia, 2012; Garcia et al, 2013; de Bassa Scheresberg, 2013).Xu and Zia (2012) provide the global evidence on the levels of financial literacy. Generally, the international evidence on financial literacy show that a large proportion of adults knows very little about financial matters with many individuals being unfamiliar with basic concepts on interest rates, insurance, shares and debt (Jappelli, 2010). World Bank et al (2009) review of empirical evidence on importance of financial literacy reveals that most consumers in the developed countries perform poorly in financial literacy tests, although they tend to overstate their skills, and do not practice basic financial skills (such as budgeting and savings or retirement planning). In a study conducted in the USA, only 34% of young adult respondents could correctly answer all three financial literacy questions (de Bassa Scheresberg, 2013). Beal and Delpachitra (2003) find that only 28% of Australian University students answered correct all five questions on basic indicators of financial literacy. Lusardi et al (2010) find that among young adults in USA, only 27% knew about inflation and risk diversification and could do simple interest rate calculations. Although there is scanty evidence on financial literacy in the developing countries, there is indicative evidence that developing countries tend to have lower levels of financial literacy. For instance, Garcia et al (2013) note that about 50% of the population in selected Latin American countries understood the concept of interest rates and its computation. In South Africa about 60% of people in household surveys did not understand the concept of interest while in Zambia about 67% were unfamiliar with basic financial products including auto teller machines and debit cards (World Bank et al, 2009). Shambare and Rugimbana (2012) find that even among the educated students in South Africa, the level of financial literacy was still moderate. Xu and Zia (2012) also note that financial literacy levels are generally low even in high income countries; they are much lower in low income countries. 1.3 Financial Literacy and Socio-Economic Status There are several factors that can be associated with the level of financial literacy. In Australia, low levels of financial literacy were found among individuals with lower education levels, lower incomes, unemployed, lower savings levels, those that are single and those on the extreme ends of adult age groups (Roy Morgan Research, 2003). Similarly, de Bassa Scheresberg (2013) finds that young adults in the USA lacked basic financial knowledge particularly among women, minorities, and lower-income or less-educated individuals. Xu and Zia (2012) in a review of international evidence also show that financial literacy is affected by level of education, level of income and wealth, age, gender, geographic and ethnic disparities, retirement planning and level of sophistication in investment behaviour. Fonseca et al (2012) find that females had lower levels of financial literacy than males, but these differences were not due to differences between their characteristics but by differences in coefficients or how literacy is produced. Lusardi et al (2010) find that college educated male student whose parents had stocks and retirement savings were

4

more likely to know about risk diversification than females with high school education from poor parents. Monticone (2010) using a regression model on Italian data finds that wealth is associated with small but positive effect on financial knowledge. Nicolini et al (2013) present a cross country comparison of factors affecting financial literacy in the USA, Canada, the UK and Italy and find significant differences across countries in levels of financial literacy and factors that explain such levels. Other studies have focused on the role of financial literacy on financial management behaviour of consumers. In the USA, de Bassa Scheresberg (2013) uses high-cost borrowing, precautionary savings, and planning for retirement as financial behaviour indicators and finds financial literacy to be a significant explanatory variable negatively related to high-cost borrowing and positively related to savings and retirement planning regardless of model specification. van Rooij et al (2011) find that financial literacy positively affects retirement planning in the Netherlands and the causality is from financial literacy to planning and not the other way round. The other body of evidence focuses on the impacts of financial education on financial literacy and financial behaviour. Using a randomized control trial, Collins (2013) finds that financial education led to improvements in self-reported financial behaviour but without measurable effects on saving and credit. Xu and Zia (2012) provide a summary of some impact evaluations of business literacy training programmes in developing countries, with most studies reporting improvements in financial behaviour but limited impacts on outcomes such as revenues and profits. 1.4 Objectives of the Survey The main objective of the survey was to obtain information on knowledge of financial management and services among households to enable the authority to measure the success of any intervention that might be put in place to increase the level of financial literacy and consumer protection in Malawi. Using different population segments, this baseline report aims at

• Assessing money and debt management practices and factors affecting money management

• Assessing the extent to which households plan for expected and unexpected events, and

future obligations

• Assessing the level of knowledge and use of financial services and products among households

• Assessing the level of financial numeracy and financial literacy and socio-economic factors

associated with financial literacy

• Understanding the sources of income and economic activities for the households and individuals

• Identifying and outlining policy options and interventions that are likely to increase the level of financial literacy and consumer protection in Malawi.

5

1.5 Survey Methodology 1.5.1 Sample Design The sample for the baseline survey was based on the 2008 Population Census data and projected population data obtained from the National Statistical Office (NSO). Two stage stratification sampling was used in the survey. In the first stage, in each stratum, the sample number of Enumeration Areas was randomly drawn using STATA. In the second stage, 20 households from each selected Enumeration Area were randomly selected from a list of households from the household listing exercise. Using the NSO sampling frame, each district was stratified into Enumeration Areas (EAs). The EAs have on average 335 households. In order for the sample to include households from different income groups, the population was clustered into four residential areas (strata): (1) urban-city areas, (2) urban-district town areas, (3) peri-urban areas, (4) rural areas. These strata account for 13%, 3%, 4% and 80% of the population, respectively. In the case of Malawi, these 4strata also provide a fair differentiation of households in terms of wealth and access to financial services. This stratification also implied that the number of districts included in the sample was random and the distribution of enumeration areas per district was also random and only known after the random selection of EAs in each stratum. In each EA the target sample was 20 households. Table 1 presents the distribution of the sample Enumeration Areas by stratum and the actual number of households interviewed. With a planned sample of 5,000 households, this entailed a sample of 250 EAs, constituting 33, 7, 10 and 200 EAs from urban-city, urban-district town, peri-urban and rural areas, respectively. The baseline survey yielded a randomly drawn sample of 4,999 households from all the districts in Malawi, except for Rumphi and Likoma in which none of the EAs were sampled at the design stage.

Table 1: Stratification of the Sample

Description of Stratum

2013 Projected

Population

2013 Projected

Households Number

of EAs Sample No EAs

Sample Number of

HHs

Actual Number of

HHs

Urban-cities 2,015,377

446,686

1,055 33 600 599

Urban-district towns 440,246

96,478

314 7 140 140

Peri-urban 620,515

134,356

577 10 200 200

Rural 12,100,000

2,666,389

10,576 200 4,000 4,000

Total

15,176,139

3,343,909

12,522 250 5,000 4,999

1.5.2 Selection of Households and Individual Respondents In each sample EA a household-listing exercise was conducted based on the NSO maps and using a Household Listing Form. Boundaries of the EAs were verified with the help of local leaders. After verification of the boundaries, each EA was portioned into smaller areas for listing purposes and listed households were marked to signify that they have been enumerated in the baseline survey. The listing forms for each EA were consolidated and the households were numbered from 1 to N. Households for interviews were selected randomly using Interval sampling.

6

The baseline survey used a face-to-face interview. In each selected household, one adult member whose age was above 18 years on the last birthday was randomly selected for interviews using a specially designed Kish table using a matrix of last two digits of the household identification and the number of eligible households (those 18 years and above). Households were visited three times in cases the randomly selected household was not available and the Kish table was used to select the replacement household member on the third visit. The household roster information was obtained from any adult member, but the rest of the interview was conducted with a randomly selected household. The random selection of household yielded a population structure that closely resembles the population structure in the national census conducted in 2008. Figure 1 shows the age structure of the population from the sample households in the baseline survey 2013 and the national population census of 2008. The population distributions are similar indicating how closely the sample households in the financial literacy baseline survey reflect the structure of the national population. However, in the baseline financial literacy survey the 5 – 9 years group dominates while the 0 – 4 years group accounts for the highest proportion of the population. The adult population structure, from 15 years old upwards, in the baseline financial literacy survey is very similar to the adult population structure of the national population census which shows a youthful population.

Figure 1: Age Structure of Baseline Sample and National Population

Source: Financial Literacy Baseline Survey 2013 and NSO (2008) 1.5.3 Data Collection Method The data was collected from a randomly selected member of the household using a semi-structured questionnaire. The survey asked questions to household members responsible for the household’s budget or their own personal spending. In order to measure financial literacy, the survey asked respondents about their behaviour, attitudes, motivations and knowledge with respect to financial issues. The questions span from objective information from the household such as day-to-day money management and usage of financial products, to hypothetical questions that measure the financial skills of household members. Table 2 presents the structure of the questionnaire and approach to the sections with the objectives of each section.

3000 2000 1000 0 1000 2000 3000

0 - 4

5 - 910-14

15-19

20-24

25-29

30-34

35-39

40-44

45-49

50-54

55-59

60-64

65-69

70-74

75-7980-84

85-89

90-94

95+

Financial Literacy Baseline 2013

Female Male

2000000 1000000 0 1000000 2000000

0 - 4

5 - 9

10-14

15-19

20-24

25-29

30-34

35-39

40-44

45-49

50-54

55-59

60-64

65-6970-74

75-79

80-84

85-89

90-94

95+

Malawi Population Census 2008

Female Male

7

Table 2: Content of the Questionnaire and Logical Path to Conduct Interview

Steps Section Part Type of respondent (Who

answered to the questions in

the section)

Objectives

1 B Money

Management

Respondent as identified by

section A

− Respondent answering for himself/herself AND his/her household

OR

− Respondent answering as an individual only

To understand how people manage

their day-to-day money (planning

spending, spending on food and

necessary items, keeping track of

spending, borrowing, general money

management)

2 C Financial

planning

To understand whether people plan for

future expenditures (known

expenditures, unexpected expenditures

or emergencies, old age, for their

children)

3 D

Financial

Services and

Products Details

Respondent as identified by

section A but answering

according to what is

mentioned in the question

To understand how people choose

financial products, whether they check

the features, terms and conditions

before buying financial products,

whether they look for information

before buying products and whether

they seek advice or information before

making financial decisions.

4 E Financial

Literacy

To capture underlying motivations that

influence the way people behave with

money and financial issues and with life

in general.

5 F

Household

Income

Estimation

To obtain information on the variations

in income that the individual

respondent and his/her household faces.

6 G Concluding

Questions

To understand

− whether the respondent seeks information or advice before making decisions and,

− whether the respondent would like to have more information about general aspects of money management and if so, what type of information.

1.5.4 Methods of Data Analysis

1.3.4.1 Stratification of the Sample and Weights

The sample is stratified into four categories that represent different income wealth levels by residence in Malawi: urban-cities, urban-district towns, peri-urban and rural areas. Two sampling weights were computed (1) household sample weight (2) individual member weight. Firstly, for

8

each interviewed household, the sample weights in each stratum were calculated as the inverse of the product of the probability of selecting enumeration areas and the probability of selecting households (using the number of households listed in each EA) in each enumeration area. Secondly, the individual household adult member weight was obtained by multiplying the household weight by the reciprocal of the probability of selecting an adult member in the household. 1.3.4.2 Methods of Analysis

Two approaches are adopted in the analysis of the baseline data on financial literacy and consumer protection. First, using the four stratifications of the data, statistical analysis is used to generate average proportions of the target variables of analysis. This provides a comparative analysis of the extent of financial literacy across income groups defined by the geographic location of respondents. The statistical analysis uses tests of differences between means and cross-correlations between variables, pie-charts and graphs. Secondly, econometric models are used to explain relationships between financial skills and socio-economic characteristics of households and respondents. This enables the isolation of factors that are important in explaining the extent of financial literacy in multivariate analysis. Literature suggests several variants of such econometric models and how financial literacy indicators explain some of the planning behaviour in addition to socio-economic or demographic factors. For instance, using multivariate analysis, Clark et al (2012) and van Rooij et al (2011, 2012) focus on the role of financial literacy on retirement plans while Sevim et al (2012) study the link between financial literacy and borrowing behaviour. Xu and Zia (2012) review some of the studies that attempt to establish links between financial literacy and socio-economic variables of respondents or households.

9

2. Households and Respondents Characteristics 2.1 Households Characteristics This section reviews the characteristics of the households that can help explain some of the financial behaviours that may be obtained in analysis of the financial literacy of the Malawian population. The average household size of the sample households is 4.8 persons, slightly higher than the average household size of 4.6 persons as per the 2008 population census (NSO, 2008). 2.1.1 Gender of Household Heads Globally, 76.1 per cent of the households that were sampled in this study were headed by males and 23.9 per cent were headed by females (Figure 2). There were strata differences though in that there were a lot more male-headed households in urban-district centres (87.3%) and cities (86.5%) than in per-urban areas (80.8%) and rural areas (73.9%). Thus, the proportion of female-headed households was a lot higher in rural areas than in urban areas.

Figure 2: Headship of Sample Households

Source: Financial Literacy Baseline Survey 2013

2.1.2 Marital Status of Household Heads Overall, 67.2% of household heads are married and in a monogamous relationship, 5.4% are married in a polygamous relationship and 1.7% are married but in informal union (Table 3). The results also show that 8% of household heads are divorced and 11.1% are widowed. There are, however, some variations of marital status by population segments. There is a higher proportion of married-monogamous in urban-cities (77.1%) but the proportion declines to 65.2% in the rural areas. Rural areas have proportionately more household heads that are divorced compared to residents of urban-cities.

86.5 87.3

80.8

73.9 76.1

13.5 12.7

19.221.6

23.9

0

10

20

30

40

50

60

70

80

90

100

Urban - cities Urban -district towns

Peri - urban Rural Malawi

Pe

rce

nt

Male Female

10

Table 3: Marital Status of Household Heads (%)

Indicators Urban - cities

Urban – district towns

Peri - urban

Rural Malawi

Married monogamous Married polygamous Informal union Divorced Separated Widowed Never married

N

77.10 2.04 0.37 4.22 3.82 4.84 7.62 659

76.89 2.73 1.00 1.42 2.53 8.45 6.98 140

70.54 1.84 2.58 9.06 4.92 6.39 4.68 200

65.19 6.20 1.90 8.74 4.31

12.31 1.35 4,000

67.19 5.41 1.73 7.99 4.22

11.05 2.41 4,999

Source: Financial Literacy Baseline Survey 2013 2.1.3 Literacy and Education of Household Heads The literacy levels among household heads are consistent with national figures for adult population, although higher in the baseline survey. It is shown in Table 4 that, overall, in the baseline survey 70.9% of household heads can read or write in English or Chichewa or Chitumbuka while the national average is 65.4% (NSO, 2012). The literacy rate in urban-cities is highest at 94.3% and declines consistently to 66.6% in the rural areas. In terms of the highest level of education attained by the household head, overall 17.8% of household heads had never attended school or did some primary school, and this is higher in the rural areas (20.9%) declines in the urban areas to 2.2% in the cities. Primary education is the dominant highest level of education among household heads with 29.6% and 28.7% completing lower primary and upper primary education, respectively. Less than a quarter of household heads (23.9%) had their highest level of education from secondary school to tertiary education. However, there are differences by population segments with urban areas having a higher proportion of household heads with secondary and tertiary education while rural areas have a higher proportion of household heads with no education and primary education. Table 4: Literacy and Education Levels of Household Head (%) Indicators Urban -

cities Urban –

district towns Peri -

urban Rural Malawi

Can Read or Write?

Yes No

N

94.26

5.74 659

84.20 15.80 140

79.80 20.20 200

66.55 33.45 4,000

70.92 29.09 4,999

Highest Level of Education

Some or no primary Primary (Std1-5) Primary (Std6-8) Secondary (Form 1-2) Secondary (Form 3-4) Tertiary (college or university)

N

2.21 9.92

22.72 17.56 30.20 17.38 659

6.94

17.85 31.52 14.66 23.19

5.82 140

10.11 19.24 22.25 12.98 19.90 15.53 200

20.90 33.43 29.80

7.27 7.14 1.46 4,000

17.80 29.56 28.70

8.96 10.90

4.08 4,999

Source: Financial Literacy Baseline Survey 2013

11

2.2 Characteristics of Respondents The questionnaire in the baseline survey was administered to a randomly selected adult member of each sampled household as noted above. It is therefore important to examine the characteristics of the respondents which can help in understanding financial literacy and financial behaviour in Malawi. Some of these characteristics are used in the multivariate analysis to explain variations in various aspects of financial management, financial planning and financial literacy. 2.2.1 Gender and Marital Status Much as the household headship was dominated by males, regardless of where the household resided, interviews were mostly held with women. Figure 3 shows that, overall, 59.1 per cent of the interviews were held with women and the proportions are highest in urban district towns (64%) and cities (61.6%). This is likely to be the case because in most cases in urban centres and cities most men are away either in formal employment or in some form of informal employment including self-employment.

Figure 3: Gender of Survey Respondents (%)

Source: Financial Literacy Baseline Survey 2013

Regarding the marital status of the respondents, most of them (67%) were married monogamously (Table 5). Examination of the residential location reveals that there were more monogamously married respondents amongst urban-district towns (73.2%) and peri-urban towns (72.3%). The proportion of unmarried respondents was highest among respondents in cities (18%), followed by respondents in urban-district towns (17.6%), and the lowest was amongst rural respondents at 7.2 per cent. There were more divorced respondents though in the rural strata (6.3%) and in polygamous marriages (5.8%) than respondents in the other three strata.

38.436.0

42.3 41.4 40.9

61.664.0

57.7 58.6 59.1

0

10

20

30

40

50

60

70

Urban - cities Urban - district towns

Peri - urban Rural Malawi

Pe

rce

nt

Male Female

12

Table 5: Marital Status of Respondents

Marital status Urban - cities Urban – district towns

Peri - urban Rural Malawi

Married monogamous 68.3 72.3 72.3 66.2 67.0 Married polygamous 1.4 0.7 1.9 5.8 4.9 Informal union 0.3 1.1 1.9 2.0 1.7 Divorced 3.8 0.9 4.7 6.3 5.7 Separated 4.4 2.1 2.8 3.7 3.7 Widowed 3.9 5.2 4.5 8.7 7.8 Never married 18.0 17.6 12.0 7.2 9.2

N 659 140 200 4,000 4,999

Source: Financial Literacy Baseline Survey 2013 2.2.2 Literacy and Education Levels Among the demographic characteristics that the survey investigated was whether the respondents could read and write English, Chichewa or Tumbuka and results show that in Malawi as a whole, 67.1 per cent of the respondents reported that they could read and write (Figure 4). The highest literacy levels were reported in cities (87.4%), followed by urban-district towns (82.1%) and the lowest proportion was in rural areas (62.3%).

Figure 4: Literacy of Respondents by Population Segments

Source: Financial Literacy Baseline Survey 2013

In terms of the highest level of education, survey results show that the majority did primary education with 30.5% doing lower primary level and 27.4% having gone up to higher primary level (Table 6). Close to 20% of the respondents just had some primary education or none at all. Only 3.4% had gone to college or university, and 10.4% had gone up to upper secondary school (forms 3 or 4). Examining the different population segments shows that there were more people that had done lower and upper secondary school in cities, urban-district towns and per-urban areas than in rural areas. On the other hand, there were more people that had been either to college or university in cities and peri-urban centres than in the other two strata. This pattern has also been observed with respect to heads of households.

87.482.1 79.5

62.367.1

12.617.9 20.5

37.732.9

0

10

20

30

40

50

60

70

80

90

100

Urban - cities Urban - district towns

Peri - urban Rural Malawi

Pe

rce

nt

Can read and write English, Chichewa or Tumbuka

Cannot read and write English, Chichewa or Tumbuka

13

Table 6: Highest Level of Schooling by Population Segments Highest level of schooling Urban - cities Urban – district

towns Peri– urban Rural Malawi

Some or no primary Primary (St. 1-5) Primary (St. 6-8) Secondary (1-2) Secondary (3-4) Tertiary (college or university)

5.3 14.7 24.2 16.0 25.6 14.3

9.0 15.4 37.3 16.2 18.9

3.2

10.1 23.6 21.2 15.4 19.4 10.3

22.2 34.2 27.9

7.7 6.9 1.2

19.0 30.5 27.4

9.4 10.4

3.4

Source: Financial Literacy Baseline Survey 2013 2.2.3 Main Socio-Economic Status The majority of the respondents in this study (75.8%) were self-employed (Table 7). Self-employment in this case included working on own farm or merely being an unpaid family worker. This proportion though is highest among rural respondents (81.5%) and lowest amongst city respondents (50.7%). There were a lot more respondents in formal employment in peri-urban areas (18%) and cities (12.4%) than in rural areas (2.7%) and urban district towns (4.5%). Employment in the informal sector was highest in cities (11.8%) and lowest in peri-urban areas (2.2%). Table 7: Main Socio-Economic Status of Respondents Main status in last four weeks Urban -

cities Urban –

district towns Peri -

urban Rural Malawi

Employed, formal employment Employed, informal sector Self-employed (incl. own farm,

unpaid family worker Looking for work Waiting for busy season Studying Retired Sick/person with a disability Housewife/house-work/caring for

household member N

12.4 11.8 50.7

1.0 0.0 5.0 0.9 0.0

14.4

659

4.5 5.7

61.7

0.0 0.0 2.9 4.9 0.2

19.2

140

18.0 2.2

60.6

0.0 0.0 3.9 1.1 0.0

10.8

200

2.7 3.4

81.5

0.3 0.2 1.6 0.0 1.1 6.0

4,000

4.8 4.5

75.8

0.3 0.2 2.2 0.4 0.9 7.7

4,999

Source: Financial Literacy Baseline Survey 2013 2.2.4 Participation in Household Financial Decisions One of the sections in this study aimed at finding out if at all respondents contributed to the budget of the household that they belonged to, and Table 8 shows that the majority (92.6%) indicated that they did. Across strata, the highest proportion was amongst respondents from rural areas (93.9%) and the lowest was amongst respondents from cities (84%). The pattern is the same when one considers respondents’ participation in households’ decision making regarding money. A slightly higher proportion of respondents in rural areas (94.5%) were involved in household monetary decision than of respondents from cities (89.4%). Table 8 also shows that a good proportion of respondents (84.1%) were mainly responsible for personal spending. In this regard, differences across strata were not that pronounced.

14

Table 8: Participation in Financial Decision Making by Population Segments (%) Variable Urban -

cities Urban –

district towns Peri - urban Rural Malawi

Contribution to household

budget

Yes No

84.0 16.0

84.6 15.4

89.0 11.0

93.9 6.1

92.6 7.9

Participation in household

decisions about money

Yes No

89.4 10.6

88.9 11.1

93.9 6.1

94.5 5.5

93.6 6.4

Person mainly or partly

responsible for own personal

spending

Yes mainly Yes partly No

82.3 17.0

0.7

85.3 13.7

1.0

84.8 15.2

0.0

84.3 14.7

1.0

84.1 15.0

0.9

N 659 140 200 4,000 4,999

Source: Financial Literacy Baseline Survey 2013

15

3. Incomes and Economic Activities in Malawi

3.1 Understanding Personal Incomes 3.1.1 Sources of Incomes Most respondents in the survey (87.4%) indicated self-employment, work in own business or farm as a source of income for them (Table 9). The proportion was highest in rural areas (90.0%) and lowest in cities (70.7%). The next source mentioned by many people was ganyu (58.4%) and again, the highest proportion was among people from rural areas (65.5%) and lowest in cities (26.7%). Ganyu was followed by sale of crops or livestock (36.8%), with the rural areas again having the highest proportion of 41.3 percent and cities lowest with 11.8 per cent. Forth came help from family/friends/community living in Malawi (35%), and this time around the highest was in cities (45.7%) and the lowest in rural areas (32.5%). Table 9: Personal Income Sources in Past 12 Months (%) Income sources in the past 12 months Urban -

cities Urban –

district towns

Peri - urban

Rural Malawi

Self-employment, work in own business or farm Informal work in private sector Formal work in private sector Work in the public sector/government Ganyu

Pension or other government transfer Help from family/friends/community living in Malawi Help from family/friends/community living abroad Sales of livestock, crops, etc. Subletting land or housing Income from interest on savings or returns on other

investments or financial products No personal income at all

N

70.7 15.8 10.6

4.3 26.7

1.3 45.7

9.0 11.8 11.3

7.4

1.0 659

80.9 3.0 4.6 6.1

38.8 2.6

42.3 8.2

30.5 1.3

11.9

- 140

80.0 1.9 6.4

13.2 40.4

2.1 42.2

4.7 35.2

9.9 4.8

0.5 200

90.9 4.1 1.6 1.8

65.5 0.9

32.5 4.5

41.3 2.2 5.3

0.3

4,000

87.4 5.5 3.1 2.9

58.4 1.0

35.0 5.2

36.8 3.7 5.8

0.4

4,999

Source: Financial Literacy Baseline Survey 2013 Regarding which source of income was considered most important, the majority (75.2%) singled out self-employment, working in own business or farm (Table 10). The highest proportion was in rural areas (80.3%) and the lowest in cities (55.3%). Ganyu came second at 6.9% and help from family/friends/community living in Malawi, came third at 5.8%.

16

Table 10: Main Source of Personal Income Sources of Income Urban -

cities Urban –

district towns

Peri - urban

Rural Malawi

Self-employment, work in own business or farm Informal work in private sector Formal work in private sector Work in the public sector/government Ganyu

Pension or other government transfer Help from family/friends/community living in Malawi Help from family/friends/community living abroad Sales of livestock, crops, etc. Subletting land or housing Income from interest on savings, or returns on other

investments or financial products N

55.3 10.9

7.7 3.4 4.9 0.3

12.2 1.3 0.3 1.7 0.1

563

65.7 2.2 1.3 3.5 2.5 0.7

13.7 0.5 3.0 0.9 6.1

140

52.7 2.9 5.0

12.2 9.6 0.8 9.3

0 3.5 1.0

-

200

80.3 2.0 1.2 1.0 7.3 0.2 4.2 0.3 2.6 0.1 0.1

3,996

75.2 3.2 2.2 2.0 6.9 0.3 5.8 0.4 2.4 0.4 0.3

4,995

Source: Financial Literacy Baseline Survey 2013 3.1.2 Seasonality in Personal Incomes and Estimated Incomes Respondents were then asked whether their income varied at different times of the year and what nature of variation it was. The results are summarised in Table 11 below. The majority of the respondents (93.8%) indicated that their income did vary in a year with more people (95.1%) in rural areas indicating thus than in cities (86.1%). A follow-up question was whether income varied when they got the most income or not, and 97 per cent of the people indicated that income varied when they got the most income. The same applied when questioned whether income varied when they got the least income. Table 11: Proportion with Seasonal Personal Income Variable Urban –

cities Urban –

district towns Peri -

urban Rural Malawi

Whether income varies by season or not

Yes No Don’t know Refused

N

86.1 12.9

0.9 0.1 659

91.9

8.1 - -

140

94.4

5.6 - -

199

95.1

4.6 0.2 0.2

3,996

93.8

5.9 0.2 0.2

4,994

Whether income varies when they get the

most income

Income steady Income varies

N

5.4 94.5 569

0.3 99.7 130

2.6 96.4 183

2.8 97.2 3,809

3.0 97.0 4,691

Whether income varies when they get the

least income

Income steady Income varies

N

3.8 96.2 569

0.3 99.7 130

6.1 93.9 183

2.5 97.4 3,809

2.8 97.2 4,691

Source: Financial Literacy Baseline Survey 2013

About 6.2% of the sample respondents indicated that their income does not vary seasonally or refused to answer or did not know. These were asked if their income varied day-by-day, week-by-week or month-by-month. Table 12 shows that about half the respondents (49.3%) said their income was steady, while 44.6 per cent indicated that their income varied, with 0.2% not knowing, and 5.9% refusing to answer the question.

17

Table 12: Proportion with Daily/Weekly/Monthly Personal Income Variations (%) Variable Urban –

cities Urban –

district towns Peri -

urban Rural Malawi

Income steady Income varies Don’t know Refused

N

69.47 29.41

- 1.12 83

63.36 12.41

- 24.23

10

65.92 34.08

- -

16

37.87 54.69

0.34 7.10 179

49.33 44.55

0.21 5.91 290

Source: Financial Literacy Baseline Survey 2013 When asked to estimate their average monthly income from all sources, 31.8% of the sample indicated that they get more than MK10,000, while 30.9% indicated that they get more than MK1,000 but less than MK4,000, and 29.2 per cent that they get more than MK4,000 but less than MK10,000 (Table 13). The more-than-MK1,000-but-less-than-MK4,000 has the highest proportion in rural areas, so too the more-than-MK4,000-but-less-than-MK10,000. The more-than-MK10,000 has the highest proportion in cites (70.7%), followed by in peri-urban (51%), and then in urban-district town (47.8%); and the rural areas have the lowest proportion (23.4%). Table 13: Proportion with Estimated Average Monthly Personal Income (%) Income in an average month Urban -

cities Urban –

district towns Peri -

urban Rural Malawi

More than zero and less than MK 1,000 More than MK1,000 but less than MK 4,000 More than MK 4,000 but less than MK 10,000 More than MK 10,000 Don’t know Refused

N

0.8 12.2 15.2 70.7

0.9 0.1 569

5.3 18.8 27.2 47.8

0.2 0.8 140

5.9 20.3 23.6 51.0

- 0.2 199

8.2 35.2 31.9 23.4

0.9 0.3

3,996

7.0 30.9 29.2 31.8

0.9 0.3

4,994

Source: Financial Literacy Baseline Survey 2013 3.1.3 Remittances Related to incomes was the issue of whether respondents did give money to somebody outside their household, and Table 14 indicates that a good proportion of respondents (64.9%) did so with the highest proportion being urban-district centres (78.4%) and lowest in rural areas (61.8%). Items or things given out included cash (62.9%) which was predominant in cities (91%) and lower in rural areas (56.8%). Help in kind (85.6%) was higher than cash though and the highest was in peri-urban areas (89.5%) and lowest in cities (68.1%). The majority of the respondents (69.5%) indicated that the provision of remittances was not done frequently and 77.2% indicated that remittances were given out occasionally.

18

Table 14: Frequency of Provision of Income or Help In-kind (%) Variable Urban -

cities Urban –

district towns Peri -

urban Rural Malawi

Remit Money/Help In-kind

Yes No

N

76.5 23.3 659

78.4 21.6 140

75.0

25 199

61.8

38 3,997

64.9 34.9 4,495

Kind of Help Provided

Cash gifts Help in kind, e.g. food, children’s clothing,

household items, etc. Loans

N

91.0 68.1

1.2 519

66.1 82.9

1.3 112

66.4 89.5

1.7 148

56.8 88.9

1.9

2,479

62.9 85.6

1.7

3,258

Money/help Provided Frequently?

Yes No

N

39.8 60.2 519

41.8 58.2 112

42.4 57.6 148

35.1 64.9 2,479

36.5 69.5 3,258

Money/Help Provided Occasionally or

Regularly?

Occasionally Regularly

N

68.9 31.1 519

80.5 19.4 112

70.9 29.1 148

79.2 20.6 2,479

77.2 22.6 3,258

Source: Financial Literacy Baseline Survey 2013 3.2 Understanding Household Incomes This section reviews incomes for households that had more than one member. For the sample, 84.4% of respondents indicated there are additional members of the household who receive income in addition to the respondents. These respondents were asked to talk about the incomes for their household.1 3.2.1 Sources of Household Incomes For households that had more than one member, the sources of income were more or less the same. What really varied were the proportions of households that were mentioning the source. Just as in the case of the respondent’s income above, at the household level (Table 15) most households got income from self-employment, working in own business or farm (93.8%, up from 87.4% for respondents), ganyu (65.3%, up from 58.4%), sale of livestock and crops (43.7%, up from 36.8%) and help from family and friends living in Malawi (35.2%, up from 35%). Ganyu is a more prevalent source of income in the rural areas, providing income to 71.7% of rural households compared to only 35.9% of urban-city households.

1The post-survey household weights, rather than the individual respondent weights, are used in this section.

19

Table 15: Sources of Household Income in Past 12 Months (%) Income Sources Urban -

cities Urban –

district towns

Peri - urban

Rural Malawi

Self-employment, work in own business or farm Informal work in private sector Formal work in private sector Work in the public sector/government Ganyu

Pension or other government transfer Help from family/friends/comm. living in Malawi Help from family/friends/community living abroad Sales of livestock, crops, etc. Subletting land or housing Income from interest on savings, or returns on other

investments or financial products Other specified

N

85.24 32.78 24.09

8.61 35.87

2.70 46.09

9.91 18.69 13.01

9.95

0.60 526

89.54 16.34

8.33 14.22 46.86

1.81 47.69

6.66 36.57

1.57 14.41

3.84 116

84.11 9.68

14.22 21.96 48.65

1.94 39.67

6.99 42.19

8.96 8.11

1.69 157

95.88 7.78 3.07 3.11

71.69 0.96

32.60 4.33

47.96 3.38 6.36

0.54 2,995

93.78 11.22

6.36 5.12

65.29 1.25

35.15 5.22

43.70 4.75 7.18

0.72 3,794

Source: Financial Literacy Baseline Survey 2013 The same applies to the source of income that was considered to be the main source; the majority of the households (77.6%, up from 75.2%) singled out self-employment, working in own business or farm (Table 16). Work in informal sector in terms of household income though came second at 6.6%, and the highest was in cities (20.8%) and lowest was in rural areas (4.2%). Ganyu is the third most important source as reported by at 3.8% of households, with cities recording 3.7% and rural areas 5.5%. Although, a high proportion indicated that ganyu is one source of income in their household, very few consider it the main source of income. The fourth most important source is formal work in the private sector mainly for 4.4% of households, but this is the third most important source in the cities (17.7%) with only 2% of rural household indicating it as the main source of income. Table 16: Main Source of Household Income (%) Income Sources Urban -

cities Urban –

district towns

Peri - urban

Rural Malawi

Self-employment, work in own business or farm Informal work in private sector Formal work in private sector Work in the public sector/government Ganyu

Pension or other government transfer Help from family/friends/comm. living in Malawi Help from family/friends/community living abroad Sales of livestock, crops, etc. Subletting land or housing Income from interest on savings, or returns on other

investments or financial products Other specified

N

49.83 20.75 17.68

5.93 3.86 0.24 0.38 0.67

- 0.38

-

- 526

64.65 10.80

5.38 11.50

3.23 0.20 0.37

- 2.33

-

- 116

54.97 6.94

10.12 19.89

3.69 1.38 1.53

- -

0.67 -

- 157

83.83 4.21 1.98 1.55 5.05 0.09 0.78 0.29 1.72 0.08 0.10

0.10 2,995

77.58 6.59 4.40 3.36 4.77 0.11 0.74 0.31 1.53 0.14 0.08

0.12 3,794

Source: Financial Literacy Baseline Survey 2013

20

3.2.2 Seasonality in Household Incomes and Estimated Incomes With regard to household income variation, the levels are the same as at the individual level with 95 per cent indicating that household incomes varied by season. This variation was regardless of when they got the most income or least, and most households reported that their incomes were not steady. Table 17 reports the estimated household incomes. Estimated average household monthly income from all sources shows that 50.4 per cent of households (up from 31.8 per cent on respondents average) get more than MK10,000, while 31.7 per cent, up from 29.2 per cent indicated that they get more than MK4,000 but less than MK10,000. Those getting less than MK1,000 but less than MK4,000 dropped from 30.9 per cent to 15.5 per cent. Table 17: Proportion with Estimated Average Monthly Household Income Groups(%) Income Levels Urban -

cities Urban –

district towns

Peri - urban

Rural Malawi

More than zero and less than MK 1,000 More than MK1,000 but less than MK 4,000 More than MK 4,000 but less than MK 10,000 More than MK 10,000 Don’t Know

N

- 1.6 6.8

90.0 1.7 526

- 6.3

12.1 81.5

- 116

- 9.4

21.6 68.8

- 157

1.3 18.6 37.6 41.0

1.4 2,995

1.0 15.5 31.7 50.4

1.3 3,794

Source: Financial Literacy Baseline Survey 2013 3.3 Self-Assessment of Financial Position One of the aims of the study was to get a feel of how people assessed themselves in terms of their financial standing. Figures 5 and 6 give a picture of this self-assessment. Figure 5 shows that a third of the respondents at the time of the survey indicated that they and their households were better off financially than they had been in the year before, but 51.8% indicated that they felt that they were worse off and only 16.1% indicated that they were just about the same. The worse off were highest in rural areas (54.5%) and lowest in cities (38.8%). The better off were highest in cities (42.4%) and lowest in rural areas (29.2%).

Figure 5: Household Self-Assessment of Financial Status compared to a Year Ago (%)

Source: Financial Literacy Baseline Survey 2013

42.4

37.6

41.1

29.2

31.8

38.8

48.844.5

54.551.8

18.5

13.6 14.515.9 16.1

0

10

20

30

40

50

60

Urban - cities Urban - district

towns

Peri - urban Rural Malawi

Pe

rce

nt

Better off Worse off Just about the same

21

People are a bit more optimistic though regarding their financial outlook ahead. Figure 6 shows that 64.9% of the respondents felt that they and their households would be better off financially a year from the time of the survey compared to the position at the time of the survey. Cities had a much higher proportion of respondents (67.2%) that indicated that their financial status would be better in the year ahead, and rural areas had the lowest proportion (52.5%). Globally though, 21.8% of the respondents indicated that they did not know with a much higher percentage in rural areas (22.8%) and lowest in cities (16.5%).

Figure 6: Household Self-Assessment of Financial Status Looking at a Year Ahead (%)

Source: Financial Literacy Baseline Survey 2013

3.4 Understanding Sources of Financial Advice

The baseline survey also sought to understand the extent to which people get information or advice when they are faced with an important financial decision to make. A statement, “I always get information or advice when I have an important financial decision to make” was read to respondents and asked to state the extent this statement described them. Table 18 shows 55.1%strongly agreed that this statement represented them while 18% strongly disagreed. The proportion strongly agreeing was highest in urban-district towns (67.9%) and lowest in cities (52.1%). On the other hand, the proportion strongly disagreeing was highest in rural areas (18.8%) and lowest in urban-district towns (9.5%). Table 18: Proportion that Get Information or Advice for Important Financial Decision Extent – Agree/Disagree Urban -

cities Urban –

district towns

Peri - urban

Rural Malawi

Strongly agree Agree to some extent Disagree to some extent Strongly disagree

N

52.1 28.6

4.5 16.6 659

67.9 11.3 11.3

9.5 140

62.8 19.7

2.4 15.1 200

54.5 22.7

3.8 18.8 4,000

55.1 22.7

4.1 18.0 4,999

Source: Financial Literacy Baseline Survey 2013

67.2

58.4 59.1

52.254.9

5.6

9.9 9.411.2 10.4

10.4 12.4 9.7 13.5 12.9

16.5 19.3 21.9 22.8 21.8

0

20

40

60

80

100

120

Urban - cities Urban - district towns

Peri - urban Rural Malawi

Pe

rce

nt

Better off Worse off Just about the same Don’t Know

22

People in need of advice went to various sources but as Table 19 shows, the most predominant ones included: a spouse/partner (44.7%), a friend (39.8%), a parent or grandparent (19.4%) and someone else in the household besides a spouse/child/parent/grandparent (15.3%). A sizeable proportion (16.8%) indicated that they did not go anywhere for advice and relied on themselves. The highest proportion of people that did not go anywhere was in rural areas (17.8%) and lowest in urban-district towns (9.1%). Suffice to say that very few people went to financial institutions to get financial advice. Table 19: Sources of Financial Advice (%) Sources of financial advice Urban -

cities Urban –

district towns

Peri - urban

Rural Malawi

Someone in a bank Someone at your workplace or your employer A traditional leader Someone you trust in your community (e.g. a teacher) Someone at the District Commissioner’s Office Your spouse/partner One of your children A parent or grandparent Someone else in your family besides

spouse/child/parent/grandparent A friend Someone in a savings club Someone in a ROSCA/chipereganyu An insurance provider A microfinance organization A katapila operator Do not go anywhere to get advice - I rely on myself

2.3 5.5 0.2 1.9 0.9

47.0 4.1

15.6 17.3

43.8

1.4 3.8 0.1 2.1 0.8

15.0

3.6 0

0.5 0.2

0 48.3

6.2 27.7 22.2

46.8

2.2 2.9

0 0 0

9.1

2.2 3.6 0.4 4.8 0.9

53.7 3.0

17.5 20.2

43.7

3.3 3.6

0 2.1

0 11.4

1.0 0.9 3.3 5.0 0.2

43.6 6.2

19.8 14.4

86.6

3.1 5.3

0 1.2 0.2

17.8

1.3 1.6 2.7 4.4 0.3

44.7 5.8

19.4 15.3

39.8

2.8 5.0

0 1.3 0.2

16.8

Source: Financial Literacy Baseline Survey 2013

23

4. Financial Literacy in Malawi Financial literacy is important for one’s capability to make informed decisions on financial matters. With increasing sophistication of the financial system and the relative power of financial providers, acquisition of knowledge by consumers can offer protection against abuse of consumer rights. The main objectives of the questions on financial literacy are to capture underlying motivations that influence the way people behave with money and financial issues and with life in general. It has been noted above that financial literacy among citizens does affect a lot of financial behaviours such as wealth accumulation, participation in various financial markets, management of risk through diversification, planning for the future, and does help in making informed decisions about financial matters. The major issues in financial literacy are numeracy and understanding of financial terms and concepts, understanding peoples’ planning horizons, and their use of mobile money and agency banking. Using econometric analysis, factors that are associated with financial literacy are also investigated particularly their knowledge on interest rate, inflation, risk diversification and overall financial literacy index. 4.1 Understanding Financial Concepts Literature suggests standard questions for assessing citizen’s understanding of financial matters, but the number of questions and issues depends on the level of sophistication of financial systems in different countries. In the developed countries, the number of indicators to measure financial literacy tends to be larger than what can be asked in developing countries where formal financial markets are thin and where most financial transactions are informal. In the case of the baseline survey in Malawi, seven indicators have been selected for computation of the financial literacy index. These questions test the respondent’s knowledge and ability to do basic financial calculations such as division, concept of inflation, simple and compound interests, differences between absolute and percentage discounts, risk and risk diversification. Table 20 presents a summary of the financial knowledge tested, the questions that were asked and the response options. The response options were read out to respondents, except for questions where they were supposed to give the value. The correct answers to these seven questions are the basis for constructing a financial literacy index which has a minimum value of zero if the respondent got none of the questions correct (financially illiterate), and a maximum value of 7 obtained when a respondent gives correct answers to all the 7 questions (highly literate). Although these questions represent concepts at different levels of comprehension, the financial literacy index is not weighted and provides an indicator of the degree of financial literacy. Five groups are also formed to represent different levels of financial literacy: zero score, 1 – 2 score, 3 – 4 score, 5 – 6 score and 7 score groups. The analysis is first based on the individual questions that form the financial literacy index and followed by the analysis of the financial literacy index and its categorization.

24

Table 20: Key Financial Literacy Questions in the Survey

Knowledge Questions in the Survey Response Options in the Survey Division 1. Imagine that five brothers are given a gift of

MK1,000. If the brothers have to share the money equally how much does each one get?

MK |___|___|___|___|

Inflation 2. Now imagine that the brothers have to wait for one year to get their share of the MK1,000 and inflation stays at 5 percent. In one year’s time will they be able to buy:

1. More with their share of the money than they could today?

2. The same amount? 3. Less than they could buy today? 4. It depends on the types of things

that they want to buy Simple Interest 3. Suppose you put MK100 into a savings

account with a guaranteed interest rate of 2% per year. You don’t make any further payments into this account, you don’t withdraw any money, and no additional fees are assessed. How much would be in the account at the end of the first year, once the interest payment is made?

MK |___|___|___|___|

Compound Interest

4. And how much would be in the account at the end of five years? Would it be:

1. More than MK110 2. Exactly MK110 3. Less than MK110 4. Or is it impossible to tell from the

answer given Absolute and Percentage Discounts

5. Let’s assume that you saw a radio of the same model on sale in two different shops. The initial retail price of it was MK1000. One shop offered a discount of MK150, while the other one offered a 10% discount. Which one is a better deal– a discount of MK150 or 10%?

1. A discount of MK150 2. They are the same 3. A 10% discount

Risk 6. Which of the following statements best describes the primary purpose of insurance products?

1. To accumulate savings 2. To protect against risk 3. To make payments or send money 4. Other (specify)

Risk Diversification

7. Suppose you have money to invest. Is it safer to buy shares of just one company or to buy shares of many companies?

1. Invest in the shares of one company

2. Invest in the shares of many companies

Source: Financial Literacy Baseline Survey 2013 Table 21 shows the proportion of adults who are literate on various aspects of financial literacy. Overall, the concept that is known most is simple division, with 82.5% of adult Malawians with knowledge on how to divide money equally among individuals. The least known concept is the computation of simple interest rate, with only 19.1% providing the correct figure for the future value of money. The concept of risk diversification is also known by only 37.9% of adult Malawians. About 64.3% of adult Malawians provided the correct answer to the question on discount and 54% of adult Malawians provided the right answer on the question of compound interest rate. However, caution may be exercised for these high scores on discount and compound interest rates given the low proportion that gave the correct amount in the simple interest rate question. 2

2 Although this cannot be verified from the data, the correct responses on discount and compound questions were the first options to be mentioned to the respondent and this may have resulted in respondents guessing the correct answer.

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Table 21: Proportion with Correct Answers to Financial Literacy Questions (%)

Financial Knowledge Urban - cities

Urban – district towns

Peri– urban

Rural Malawi

Division Inflation Simple interest Compound interest Absolute/percent discount Risk Risk diversification

N

91.24 65.35 32.45 54.07 64.47 71.03 43.72 659

89.19 60.11 17.53 66.79 65.37 58.98 39.64 140

86.98 55.66 20.68 56.27 60.46 58.36 36.57 200

80.44 55.97 16.90 53.25 64.12 38.89 36.91 4,000

82.46 57.31 19.11 53.98 64.03 44.69 37.87 4,999

Source: Financial Literacy Baseline Survey 2013 There are regional variations in the responses to the questions, and the rural areas have the least proportions in six of the seven indicators, with the exception of the absolute and percentage question where the lowest proportion is obtained among the peri-urban population. In contrast, the urban population has the highest proportions in 5 of the seven indicators of financial literacy, with the exception of compound interest rates and discount questions where the highest proportions are obtained in district towns’ population. Generally, this suggests that there is an urban bias in financial literacy in Malawi. Table 22 shows proportions of adults that provided the correct answer to specific financial literacy questions by socio-economic characteristics. With respect to gender of respondents, in all the seven questions, the proportions with the correct responses are higher among male adults than they are among female adults, although the differences are not substantial with the exception of the concept of risk. In terms of the highest level of education, while the proportions with correct answers increase with the level of education for most indicators, this does not seem to be the case with respect to compound interest. For instance, 45.2% of adults with tertiary education compared to 65.5% of adults with lower secondary education. This suggests that among the educated, there are still high proportions of adults that did not provide correct answers to the financial literacy questions. With respect to the nature of employment, there is also a positive relationship between formalization of employment and financial literacy. For all the financial literacy questions, the highest proportions that provided correct responses are among adults employed in the formal sector, generally followed by those employed in the informal sector. Nonetheless, the computation of simple interest rate was also difficult for even those in formal employment; only 39.4% of adults in formal employment gave a correct answer to the simple interest rate question and 49.3% got the question on risk diversification right.

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Table 22: Proportion with Correct Answers by Socio-Economic Groups (%)

Indicator Division Inflation Simple Interest

Compound Interest

Discount Risk Risk Diversification

Gender

Male Female

87.76 78.80

59.49 55.80

22.89 16.49

55.53 52.91

63.05 64.71

58.18 35.37

42.16 34.90

Education

None/some primary Primary (1-5) Primary (6-8) Secondary (1-2) Secondary (3-4) Tertiary

67.76 80.63 85.07 89.37 90.45 96.04

52.25 53.86 57.65 61.98 61.72 73.15

8.84

16.13 17.34 22.19 30.10 50.00

51.23 48.75 56.51 65.50 59.40 45.21

67.64 62.50 63.92 60.96 64.55 65.93

26.30 35.55 41.69 56.35 73.15 90.46

34.83 35.66 36.42 38.54 43.31 55.50

Employment

Employed - Formal Employed - Informal Self-employed Unemployed

91.40 85.93 82.09 80.42

70.71 58.10 56.00 59.40

39.40 23.99 17.49 19.31

60.12 51.52 53.84 53.47

69.48 66.72 64.41 59.49

79.94 56.64 41.75 44.71

49.30 44.91 36.79 37.55

Source: Financial Literacy Baseline Survey 2013 Table 23 shows the mean financial literacy index and its distribution by population segments. Overall, the mean financial literacy index among adult Malawians is 3.6, implying that, on average, adults get 50% of the financial literacy questions. The highest score of 4.2 is obtained among the urban population and the lowest score of 3.5 is obtained among the rural populations, confirming the urban-rural bias observed above. The lower panel of the table shows the distribution financial literacy index, with a score of zero implying financial illiteracy and a score of 7 implying highly financial literate. With the exception of the urban population, most of the adult Malawians had scores of 3 – 4 questions; they provided the correct answers for 3 – 4 questions out of the 7 financial literacy questions. Overall, the proportion of adult Malawians that can be described as financially illiterate is 2.1% while 21.4% can be described to have low financial literacy. The proportion of adults that can be described as highly literate (with a maximum score of 7) is only 1.1% and 27.2% of adults are above average financial literacy levels. This implies that only 28.3% of adult Malawians have above average financial literacy and got more than 4 of the 7 financial literacy questions correct. Table 23: Distribution of Financial Literacy Index by Population Groups

Financial Literacy Index Urban - cities

Urban – district towns

Peri– urban

Rural Malawi

Financial Literacy Index (Mean) 4.2 4.0 3.7

3.5

3.6

Financial Literacy Index Group (%)

0 (Illiterate) 1 – 2 (low literacy) 3 - 4 5 -6 7 (Highly literate)

N

0.48

13.86 38.92 44.18

2.55 659

0.00

15.08 49.71 31.29

3.92 140

2.19

21.07 41.13 34.70

0.91 200

2.48

22.96 50.06 23.70

0.80 4,000

2.12

21.41 48.17 27.15

1.14 4,999

Source: Financial Literacy Baseline Survey 2013 Table 24 presents the mean financial literacy index and its distribution by various socio-economic groups. With respect to age of the respondents, lower financial literacy is observed among adults that are more than 49 years old, with the lowest level of 2.8 being among the elderly (above 64 years old) with the peak of 3.9 observed among the 35-39 age group. The peak for each age group appears to be a financial literacy index of 3 – 4 correct answers. The age groups above 54 years old

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have the highest proportions with financially illiterate adults, with 8.8% of the adults above 64 years old being financially illiterate. With respect to gender of respondents, male respondents scored 3.9 while female respondents scored 3.4, suggesting a gender bias in financial knowledge. There are also proportionately more female respondents who are financially illiterate (2.8%) than their male counterparts (1.2%) and less female respondents that are highly financial literate (0.6%) than their male counterparts (1.9%). Table 24: Distribution of Financial Literacy Index by Socio-Economic Groups

Indicator Mean Financial Literacy Score (% of adults) Zero 1 - 2 3 – 4 5 - 6 7

Age Group

16-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65+

3.6 3.8 3.7 3.9 3.8 3.6 3.5 3.5 3.3 2.8

1.87 0.47 1.83 0.58 1.43 1.47 1.26 3.54 3.48 8.76

21.94 17.68 19.30 16.92 15.91 20.78 21.81 23.62 27.36 38.12

47.79 52.75 47.25 49.86 50.54 49.94 51.36 45.16 47.07 36.28

27.76 28.21 29.34 30.21 31.74 26.42 25.13 27.68 20.26 16.21

0.63 0.90 2.28 2.42 0.38 1.38 0.44 0.00 1.83 0.63

Gender of Respondent

Male Female

3.9 3.4

1.21 2.76

16.70 24.67

46.07 49.62

34.16 22.30

1.86 0.64

Education of Respondent

None/some primary Primary (1-5) Primary (6-8) Secondary (1-2) Secondary (3-4) Tertiary

3.1

3.3

3.6

3.9

4.2

4.8

4.36 2.85 1.53 0.31 0.93 0.00

27.92 25.76 20.99 16.27 12.61

6.57

52.90 49.06 49.94 48.66 41.70 30.77

14.62 21.92 27.26 32.13 41.34 57.12

0.20 0.40 0.29 2.64 3.42 5.54

Nature of Employment

Employed - Formal Employed - Informal Self-employed Unemployed

4.6

3.9

3.5

3.5

0.00 0.86 2.35 2.04

7.43

19.64 22.17 22.58

35.92 40.17 48.90 50.85

51.12 39.23 25.59 23.73

5.53 0.11 0.99 0.80

Source: Financial Literacy Baseline Survey 2013 There are also differences in financial literacy based on the highest education achieved by the respondents and there is a consistent positive relationship between the level of education and financial literacy. The average score on financial literacy among adults with no education or some primary education is 3.1 but rises steadily to 4.8 among adults with tertiary education. Although most adults with tertiary education have scores above 4, only 5.5% of adults with tertiary education provided correct answers to all seven questions in the index, suggesting that financial education is needed among adult Malawians regardless of the highest level of education attained by respondents. Table 25 shows proportion of adults who saved some money as children and where they saved such money. Overall, 49.9% of adult Malawians reported that they saved money as children. The differences between population segments are not substantial, with the highest proportion of 54.4% amongst adults in district towns and lowest of 49.2% amongst adults in the rural areas. Among those reporting that they saved as a child, saving money in box at home was the most popular method as reported by 66.6% of adults who had saved money as a child. About 30% of adults who saved money as children saved with parents or family members and only 1.6% had

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experience with a financial institution as a child. Similarly, there is little variation across the population segments in the method used to save money as a child. Childhood savings behaviour may be positively associated with financial literacy. The average financial literacy score for adults who saved money as a child is 3.74 compared to the financial literacy index of 3.45 among adults who never saved some money as children. The two-group mean-comparison t-test produced a t-statistic of 7.5 which is statistically significant at the 1% level. Table 25: Proportion of Adults who Saved Money as a Child (%)

Financial Literacy Index Urban - cities

Urban – district towns

Peri– urban

Rural Malawi

Saved Money as a Child?

Yes No Don't Know Refused

N

52.20 47.52

0.28 -

659

54.38 45.62

- -

140

50.41 48.08

1.51 -

200

49.21 50.54

0.15 0.10 4,000

49.86 49.84

0.19 0.12 4,999

Where was Money Saved?

Financial Institution Home in a box With parent/family member Other Don’t Know Refused

N

2.42

68.07 28.91

- -

0.60 363

6.53

67.25 26.22

- - -

75

4.95

62.56 28.96

3.53 - -

106

1.02

66.59 30.79

1.54 0.05

- 1,960

1.62

66.62 30.27

1.37 0.04 0.08 2,504

Source: Financial Literacy Baseline Survey 2013 The baseline survey also sought to determine the level of knowledge of typical financial terms among adult Malawians. Respondents were asked whether they have heard of the term and whether they know what it means. These financial terms include ‘interest rate’, ‘insurance’, ‘shares’, ‘stock exchange’,’ inflation’ and ‘devaluation’. Most of these terms were difficult to translate in local languages as there are no similar or equivalent terms. This meant that with exception of ‘interest rate’, these terms were retained as English terms but pronounced as local language words during the interviews. Table 26 shows the extent to which financial terms have been heard or not and whether people know what they mean. The terms that were mostly unheard were ‘inflation’ by 78.2% of adults, followed by ‘stock exchange’ (74. 5%) and ‘devaluation’ (64.6%). Surprisingly, ‘devaluation’ and ‘inflation’ have been topical issues with respect to macroeconomic stability yet are concepts that have never been heard by adult Malawians.

The term that has mostly been heard is ‘interest rate’ (this is also a term that has a local language equivalent). Only 24.9% of adult Malawians have never heard the term ‘interest rate’. There is, however, a sizeable proportion of adults who have heard the term ‘interest rate’ but they do not know what it means (31.6%) while only 43.1% of adults have heard and know its meaning. Amongst all the terms, ‘interest rate’ is the concept which has the highest proportion of adults who know its meaning. ‘Shares’ is the second most widely heard term. Only about 29% of adult Malawians have heard and know what ‘insurance’ and ‘shares’ mean. While a high proportion of adults have heard of ‘shares’, only 25.3% have heard about the ‘stock exchange’ (with only 7.5% knowing what a stock exchange means. Only 21.7% of adult Malawians have heard the term ‘inflation’ but only 7.1% know its meaning. Similarly, although 35.2% have heard the term ‘devaluation’ only 14.4% of adult Malawians know the meaning of ‘devaluation’. This analysis shows that the knowledge of basic financial terms in Malawi is limited.

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Table 26: Proportion of Adults with Knowledge of Financial Terms (%)

Indicator Urban - cities

Urban – district towns

Peri - urban

Rural Malawi

Interest Rate

Never heard of this Heard, but do not know what it means Know what this means Refused

11.00 27.06 61.75

0.19

12.26 23.51 64.23

-

18.71 25.82 55.47

-

28.17 33.07 38.72

0.04

24.93 31.60 43.41

0.06 Insurance

Never heard of this Heard, but do not know what it means Know what this means Refused

12.11 31.67 56.03

0.19

21.43 38.28 40.29

-

25.55 21.57 52.87

-

40.61 37.04 22.18

0.17

35.52 35.63 28.69

0.16 Shares

Never heard of this Heard, but do not know what it means Know what this means Refused

13.38 41.44 44.99

0.19

14.10 35.04 50.86

-

25.15 31.42 43.43

-

32.53 43.14 24.25

0.09

29.04 42.06 28.80

0.09 Stock Exchange

Never heard of this Heard, but do not know what it means Know what this means Refused

47.92 27.41 24.48

0.19

66.22 13.60 20.18

-

55.67 28.31 16.02

-

80.37 15.81

3.63 0.19

74.48 17.84

7.51 0.17

Inflation

Never heard of this Heard, but do not know what it means Know what this means Refused

54.43 22.20 23.18

0.19

69.96 14.92 15.12

-

61.38 20.20 18.42

-

83.46 12.92

3.44 0.18

78.16 14.55

7.13 0.16

Devaluation

Never heard of this Heard, but do not know what it means Know what this means Refused

34.74 25.11 39.95

0.19

55.21 21.35 23.19

0.25

51.30 15.98 32.72

-

70.80 20.47

8.63 0.10

64.64 20.88 14.37

0.11

N 659 140 200 4,000 4,999

Source: Financial Literacy Baseline Survey 2013 With respect to places of residence, the data show that full knowledge of financial terms vary across population segments. For instance, there is an urban bias in terms of the proportions that have heard and know the meaning of ‘interest rates’, above 60% in cities and district towns and only 38.7% of adults living in the rural areas. This is also true for the rest of the terms, with the gap being wider between urban areas and rural areas. For example, 40% of adults in cities compared to 8.6% of adults in rural areas have heard and know the meaning of ‘devaluation’. Respondents were asked to assess their time preference on day-to-day decision by agreeing or disagreeing to different statements. Table 27 presents the time preferences of adult Malawians by population segments. Overall, 41.8% and 32.4% of adult Malawians strongly disagree and strongly agree that they ‘only focus on the short term’, respectively. Similarly, more adult Malawians strongly disagree (44.2%) than strongly agree (30.6%) with the statement that they ‘live more for present day than tomorrow’. In terms of whether adults believe that ‘the future will take care of itself’, 46.9% strongly disagree, 28.4% strongly agree and 13.8% agree to some extent. Across the three statements, short-termism is much lower in the cities but few differences exist between populations in district towns, peri-urban and rural areas. These results show that most adult Malawians tend to make decisions over the short term and are less likely to plan over a long term. Hence, they are unlikely to make long-term financial decisions.

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Table 27: Self-Assessment of Time Preferences (%)

Statements Urban - cities

Urban – district towns

Peri - urban

Rural Malawi

“I only focus on the short term”

Strongly agree Agree to some extent Disagree to some extent Strongly disagree Don't Know Refused

26.35 12.90 11.82 48.75

- 0.19

27.40 10.77 12.85 48.99

- -

32.32

7.00 4.02

56.65 - -

33.57 15.87 11.03 39.42

0.10 0.02

32.36 14.87 10.85 41.80

0.08 0.04

“I live more for present day than for

tomorrow”

Strongly agree Agree to some extent Disagree to some extent Strongly disagree Don't Know Refused

22.41 10.00 13.07 54.07

- 0.45

33.22 11.38 11.02 43.48

0.90 -

30.96 8.78 4.21

56.04 - -

31.81 14.59 11.60 41.91

0.05 0.03

30.61 13.60 11.41 44.23

0.07 0.08

“The future will take care of itself”

Strongly agree Agree to some extent Disagree to some extent Strongly disagree Don't Know Refused

21.08 12.02 12.70 54.02

- 0.19

24.09 12.62 14.82 48.48

- -

28.53

9.75 4.13

57.59 - -

29.72 14.44 10.79 44.98

0.05 0.02

28.35 13.83 10.85 46.89

0.04 0.04

N 659 140 200 4,000 4,999

Source: Financial Literacy Baseline Survey 2013 Table 28 presents the self-assessment of behavioural traits of adult Malawians by population segments. Overall, it appears that 61.8% of adult Malawians strongly disagree that they do things without giving them thought and 77.8% strongly disagree that they act impulsively. Similarly, 60.8% of adult Malawians strongly disagree that they say things before they have thought them through. There are also urban-rural biases in these behavioural traits, with higher proportions disagreeing in the cities than in the rural areas. Thus, these negative traits are less likely to be found in most adult Malawians and it can be concluded that most may be careful and thoughtful individuals in life and in dealing with financial matters. Adult Malawians were also asked about positive traits – ‘always looking for opportunities’, ‘having aspirations’ and ‘working hard on what they do’. Overall, more than 80% of adults strongly agree that they always look for opportunities for improving their situation (84%), they have many aspirations (84.9%) and they always work hard to be among the best at what they do (87.9%). There are very little variations with respect to cities, district towns, peri-urban and rural populations.

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Table 28: Self-Assessment of Behavioural Traits (%)

Statements Urban - cities

Urban – district towns

Peri - urban

Rural Malawi

I do things without giving them much

thought

Strongly agree Agree to some extent Disagree to some extent Strongly disagree Don't Know Refused

7.19 16.08 11.40 65.13

- 0.19

8.45 9.43 8.83

71.49 -

1.79

13.65 10.75

8.09 67.52

- -

11.89 14.87 12.67 60.49

0.07 0.02

11.25 14.63 12.15 61.82

0.05 0.10

I am impulsive

Strongly agree Agree to some extent Disagree to some extent Strongly disagree Don't Know Refused

3.02 6.25 4.65

85.74 0.16 0.19

4.55 4.87 6.13

84.45 - -

3.21 4.89 8.27

83.63 - -

5.89 7.48

10.51 75.83

0.07 0.22

5.34 7.10 9.49

77.79 0.08 0.20

I say things before I have thought

them through

Strongly agree Agree to some extent Disagree to some extent Strongly disagree Don't Know Refused

6.80

19.33 12.72 60.86

- 0.28

5.01 6.31

17.32 71.37

- -

12.09 10.08

9.21 68.02

0.61 -

11.44 16.07 12.37 59.85

0.11 0.15

10.65 15.85 12.44 60.79

0.12 0.16

I always look out for opportunities for

improving my situation

Strongly agree Agree to some extent Disagree to some extent Strongly disagree Refused

83.87 12.09

1.78 2.07 0.19

86.02 8.62 2.67 2.69

-

87.88 9.53 0.98 1.61

-

83.64 12.85

1.70 1.72 0.09

83.96 12.44

1.71 1.80 0.09

I have many aspirations

Strongly agree Agree to some extent Disagree to some extent Strongly disagree Refused

86.47

9.02 1.59 2.73 0.19

82.30 10.25

1.70 5.76

-

84.91

9.11 1.59 4.39

-

84.73

9.96 2.39 2.89 0.02

84.87

9.81 2.23 3.05 0.04

I always work hard to be among the

best at what I do

Strongly agree Agree to some extent Disagree to some extent Strongly disagree Refused

88.94 8.17 1.30 1.40 0.19

94.61 2.70

- 2.69

-

89.53 7.97 1.51 0.99

-

87.27 9.85 1.34 1.43 0.11

87.86 9.29 1.29 1.45 0.11

N 659 140 200 4,000 4,999

Source: Financial Literacy Baseline Survey 2013

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4.2 Understanding Mobile Money and Agency Banking 4.2.1 Access to Mobile Phones Ownership of mobile phones in Malawi has seen exponential growth in the past decade. For instance, NSO (2012) finds that only 3% of households in Malawi owned a mobile phone in 2005 but this increased to 36.3% of households in 2012 (11% among the poorest 20% and 62.5% amongst the richest 20%). Table 29 shows the proportion of adults that own a mobile phone or have access to a mobile phone in Malawi. Overall, 36.4% of adult Malawians own a mobile phone with an additional 20% of adults not owning but having access to a mobile phone. The urban-rural bias is apparent in the ownership of mobile phones. In cities, 70.8% of adults have a mobile phone (88.8% overall access to mobile phone) while in the rural areas only 28.7% of adults (49.3% overall access) own a mobile phone. The difference in mobile phone ownership in district towns and peri-urban areas is minor. The penetration of mobile phones is good and it offers more opportunities for access to financial information and services. Table 29: Proportion of Adults Owning/Using Mobile Phones (%) Variable Urban -

cities Urban –

district towns Peri -

urban Rural Malawi

Yes, own mobile phone Yes, have use of mobile phone No Don't Know Refused

N

70.81 18.00 11.19

- -

659

52.79 20.49 26.72

- -

140

56.77 15.65 27.58

- -

200

28.73 20.58 50.61

0.06 0.02 4,000

36.38 20.00 43.56

0.04 0.02 4,999

Source: Financial Literacy Baseline Survey 2013 4.2.2 Use of Mobile Phones for Financial Transactions The level of knowledge on the use of mobile phones for financial services among adults with access to a mobile phone is high. Table 30 shows the proportion of adults who have heard of being able to use a mobile phone to conduct financial transactions. Overall, more than 80% of adults have heard using a mobile phone to receive money, transfer money, pay bills, buy airtime and send airtime (Me2U). Nonetheless, Me2U and buying airtime are the most common services associated with use of mobile phones. Respondents also mentioned other services, which were mainly bank account alert services, and checking balances in bank accounts, but this was mentioned by only 1.6% of adult Malawians. The differences in knowledge between population segments are not substantial especially for airtime buying and Me2U services. Table 30: Knowledge of Use of Mobile Phones for Financial Services (%)

Use Urban - cities

Urban – district towns

Peri - urban

Rural Malawi

Receive money Transfer money Pay bills Buy airtime Me2U (sending airtime) Other (mainly bank account alerts)

N

90.39 94.41 93.24 98.69 99.25

2.14 578

82.36 83.14 85.82 92.58 99.61

4.21 100

86.26 86.03 83.25 97.38 99.26

0.86 135

76.96 79.21 72.40 90.96 96.31

1.35 1,905

80.51 82.90 77.93 93.00 97.24

1.61 2,718

Source: Financial Literacy Baseline Survey 2013 Further analysis among adults with access to mobile phones reveals that very few have actually used mobile phones to access financial services, with the exception of airtime buying and Me2U

33

services. Overall, Table 31 shows that only 3.9%, 4.1% and2.6% of adult Malawians have used a mobile phone to receive money, transfer money and pay bills, respectively. The proportion that has used mobile phones to receive money is highest in the district towns and peri-urban areas compared to urban and rural areas. Me2U services are the financial services mostly used by those that have access to mobile phones – 52.1% of adult Malawians with access to mobile phones use the phone for Me2U service. The mean number of times the mobile phone is used to access financial services in a month is relatively small – about 5 times for money receipt, bill payment and Me2U services; 3 times for money transfer services, 12 times for airtime purchase services and 6 times for other financial services. Table 31: Use of Mobile Phones for Financial Services

Use Urban - cities

Urban – district towns

Peri - urban

Rural Malawi

Used Mobile Phone in ... (%)

Receive money Transfer money Pay bills Buy airtime Me2U (sending airtime) Other (bank account alerts)

3.54 7.71 5.40

41.17 64.47

6.71

11.93

8.06 6.98

30.35 60.27 58.06

6.18 5.03 5.74

39.36 61.62

0.00

3.16 2.44 0.87

36.55 46.86 24.16

3.86 4.08 2.60

37.45 52.08 22.73

Mean Number of Times Used /Month*

Receive money Transfer money Pay bills Buy airtime Me2U (sending airtime) Other (bank account alerts)

2.1 2.8 2.4

16.4 5.9

24.8

3.8 4.9 2.4

11.5 7.3 4.0

1.1 2.3 2.5

15.7 5.9

-

6.2 2.9

15.0 10.5

4.5 5.1

4.5 3.0 5.0

12.3 5.2 6.1

Note: * These average figures may be affected by outlier observations due to low number of adults using such services.

Source: Financial Literacy Baseline Survey 2013 Figure 7 shows the potential demand for use of mobile phones in particular financial services among adult Malawians with access to a mobile phone. Using the four financial services (receiving money, transfer money, pay bills, buy airtime), overall the demand ranges from 64.6% for bill payment to 90% for buying airtime as very likely financial services for which the mobile phone would be used. In addition, 73.9% and 79.1% of Malawians with mobile phones are very likely to use mobile phones for receiving money and transferring money, respectively. More generally, urban-cities tend to have high potential demand for use of mobile phones for accessing financial services, with more than 84% of adult Malawians with mobile phones being very likely to use mobile phones for such services. The lowest figures seem to be among residents of peri-urban areas although the demand is expressed by at least 57% of the adult population. Although the proportion that uses mobile phones for financial services in rural areas is low, a high proportion of adult Malawians with phones is very likely to use a mobile phone for accessing financial services.

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Figure 7: Proportion Very Likely to Use Mobile Phones for Financial Services (%)

Source: Financial Literacy Baseline Survey 2013

There are other organisations or business establishments that could be used as points for accessing financial services rather than banks in Malawi. However, their usefulness depends on how potential users perceive them and the potential demand that exists for such service points. These organisations include large agro-input dealer shops, fuel stations, supermarkets, dealers at the market, microfinance or SACCO office, bank branch or other bank outlets and ATM. Overall, 74.7% of adult Malawians are willing to use other places rather than banks to access financial services (Table 32). The proportions increase as you move from cities to rural areas where banking facilities are non-existent. Large agro-input dealers are the most popular organisations as potential points for accessing financial services, with 96.3% of adult Malawians willing to access financial services at input dealer shops. Use of the fuel station as access points for financial services is least and is only confirmed by 65% of those that indicated used of alternative places, although the proportions are higher in urban areas (where fuel stations are many) than in rural areas where such facilities are limited. Local supermarkets and microfinance/SACCO office are also places that provide opportune points for accessing financial services.

84.4

72.5

67.1

71.673.9

89.0

81.3

67.3

77.2 79.1

84.6

70.5

57.659.0

64.6

95.091.2

80.2

89.4 90.0

0

10

20

30

40

50

60

70

80

90

100

Urban - cities Urban - district towns

Peri - urban Rural Malawi

Pe

rce

nt

Receive Money Transfer Money Pay Bills Buy Airtime

35

Table 32: Use/Willingness to Use Alternative Places for Financial Services (%)

Use Urban - cities

Urban – district towns

Peri - urban

Rural Malawi

Use/Willing to Use Alternative Place

Yes

66.63

79.07

74.25

75.86

74.71 Alternative Places

Large Agro-Input Dealer Fuel Station Local Supermarket Dealer at the market MFI/SACCO office Bank branch or other bank outlet ATM Other

N

91.64 84.99 79.95 62.97 77.12 93.14 88.61

0.39 459

96.81 81.43 86.89 73.74 82.05 94.03 88.10

1.91 106

97.92 69.49 79.77 65.01 83.51 93.03 84.40

2.57 152

96.75 61.25 80.18 69.70 76.46 78.44 64.68

1.51 3,008

96.25 65.13 80.38 68.85 77.09 81.43 69.27

1.45 3,725

Source: Financial Literacy Baseline Survey 2013 4.3 Determinants of Financial Literacy This section explores the link between indicators of financial literacy and socio-economic characteristics of respondents. The following model is estimated: ���� = � + �� + ��� + ���� + ��� + �� + � (1) where FLI is a vector of financial literacy indices, RFT is a vector of respondents financial and behavioural traits, HHW is a vector of household wealth and welfare indicators, HHC is a vector of household characteristics, REC is a vector of respondent characteristics, X is a vector of other control variables, and μ is the error term. Four indicators of financial literacy are used as dependent variables. Firstly, financial knowledge of simple interest rate, defined as a dummy equal to 1 if the respondent provided a correct answer to the interest rate calculation question; otherwise it is equal to zero. Secondly, knowledge about inflation, defined as a dummy equal to 1 if the respondent provided a correct answer to the inflation question; otherwise it is equal to zero. Thirdly, knowledge about risk diversification, defined as a dummy equal to 1 if the respondent provided a correct answer to the risk diversification question; otherwise it is equal to zero. Fourthly, is the financial literacy index (Fonseca et al, 2012; Lusardi et al, 2010)–measured as an index of number of correct answers to basic financial literacy questions: basic division, simple interest rate, compound interest rate, inflation, discounts, risk and risk diversification. This index ranges from 0 to 7. Various socio-economic variables and financial literacy indicators are used as explanatory variables to explain various money management behaviours. The first group is the RFT vector which includes having or intention to open a bank account, having or intention to obtain a bank loan, whether saved money as a child and short-term behaviour traits. The short-term traits are captured by a dummy equal to 1 if the respondent strongly agreed with any one of the three statements that cared less about the future (“I only focus on the short term” or “I live more for the present day than for tomorrow” or “The future will take care of itself”), otherwise it is equal to zero. The intentions to have a bank account, to take a bank loan and having saved money as a child are also defined as dummy variables. The second group relates to indicators of financial literacy – the financial literacy index (Fonseca et al, 2012; Lusardi et al, 2010). This is measured as an index of number of correct answers to basic financial literacy questions: basic division, simple interest rate, compound interest rate, inflation,

36

discounts, risk and risk diversification. Although these questions are at different levels of difficulty, the higher the number of correct answers, the more financial literate are the consumers. The third group relates to three indicators of incomes and welfare – income, financial wellbeing, and seasonality of income. Income is measured by estimated income per month in thousands of Malawi Kwacha. Wellbeing is measured by a dummy equal to 1 if the respondent revealed that household financial wellbeing was better than it was a year ago. Seasonality is captured by a dummy equal to 1 if it was revealed that the income for the household was seasonal. The fourth group of variables relates to household characteristics – gender of household head and household size. Gender of household head is measured as a dummy equal to 1 if male-headed household and equal to zero if female-headed households. The household size is the number of persons in the household. The fifth group includes respondent’s characteristics – age, age squared, gender, marital status, highest education and nature of employment. Age is measured in number of year and gender as a dummy equal to 1 for male respondents (zero for female respondents). Marital status is measured by three dummy variables capturing type of marriage – monogamous, polygamous and informal union, with the unmarried categories taking a value of zero. Highest level of education is measured by dummy variables for lower primary (1-5), upper primary (6-8), junior secondary (1-2), senior secondary (3-4) and tertiary, with no or some primary being the base category. The nature of employment is measured by four dummy variables – employed in formal sector, employed in informal sector, self-employed and unemployed, with unemployed being a base category in the models. The sixth group includes other control variables such as dummies for population segments (rural being the base category) and whether the respondent was responsible for both household and personal spending. Table 33 presents results probit regression results on likelihood of having the correct financial knowledge on interest rates, inflation and risk diversification in Malawi. All the three models are validated by the statistically significant Chi-squared test statistic at the 1% level. The socio-economic characteristics explain between 2% in the risk diversification model and 10% in the interest rate model of the variation in the dependent variable. This low explanatory power is consistent with similar models in the literature (see for instance, Lusardi et al, 2010). First, the behaviour traits variables seem to be important correlates in the interest rate and inflation models. In the inflation model, having a bank account or having intentions to open a bank account raises probability of having correct knowledge about interest rate by 3.3% points compared to those that do not have the intention to open a bank account. However, there is no significant relationship between correct knowledge about interest rates and having or intentions to take a bank loan. Savings behaviour from childhood increases the probability of having the correct knowledge about interest rate by 6.8% points. Thinking and making decision within the short-term time horizon and caring less about the future reduces the probability of correct knowledge about interest rate by 9% points. Since the concept of interest rates is more associated with savings from the point of view of consumers, those that do not care about the future are unlikely to save and invest time to understand how to calculate simple interest. In the inflation model, opening a bank account and saving behaviour from childhood are positively associated with correct knowledge about inflation while bank loan and short-termism are negatively associated with correct knowledge about inflation. Short-termism is also negatively associated with correct knowledge about the concept of risk diversification.

37

Table 33: Probit Regression Marginal Effects – Financial Literacy by Type

Variables Interest Rate Inflation Risk Diversification

dF/dx z dF/dx z dF/dx z Have/intend to open bank account (0/1) Have/intend to take bank loan (0/1) Saved money as a child (0/1) Short-term horizon (0/1) Monthly income (K’000) Better-off financially than a year ago (0/1) Household size Male respondent (0/1) Married respondent – monogamous (0/1) Married respondent – polygamous (0/1) Married respondent – informal union (0/1) Age of respondent (years) Age-squared of respondent (years) Primary (1-5) education (0/1) Primary (6-8) education (0/1) Secondary (1-2) education (0/1) Secondary (3-4) education (0/1) Tertiary education (0/1) Employed – formal sector (0/1) Employed – informal sector (0/1) Self-employed (0/1) Urban – cities (0/1) Urban – district towns (0/1) Peri-urban (0/1)

0.0330 -0.0207 0.0677

-0.0904 0.0001 0.0336

-0.0049 0.0066

-0.0172 -0.0619 0.2982 0.0073

-0.0001 0.0985 0.1125 0.1475 0.2416 0.4174

-0.0233 0.0012 0.0033 0.0231

-0.0383 -0.0114

2.11b -1.01 5.67a

-7.63a 1.34

2.53a -1.69c

0.51 -1.22

-2.48b 4.64a 3.24a

-3.32a 4.49a 4.70a 4.22a 6.21a 6.62a -0.81 0.04 0.18 1.17

-1.11 -0.43

0.0830 -0.0780 0.0744

-0.1114 0.0000 0.0081

-0.0012 -0.0010 -0.0292 -0.0642 0.1572 0.0118

-0.0001 0.0071 0.0349 0.0345 0.0285 0.0265 0.0155

-0.0676 -0.0318 0.0209

-0.0289 -0.0348

3.98a -2.38b 4.70a

-6.98a 0.08 0.46

-0.31 -0.06 -1.59 -1.63 3.11a 4.36a

-4.76a 0.31 1.41 1.03 0.80 0.43 0.31

-1.51 -1.30 0.77

-0.54 -0.88

0.0216 -0.0257 -0.0174 -0.0481 0.0002

-0.0003 -0.0001 0.0605 0.0043 0.0405

-0.0378 -0.0006 0.0000

-0.0526 -0.0510 -0.0359 0.0228 0.2221

-0.0302 0.0452 0.0073 0.0142 0.0027

-0.0415

1.05 -0.86 -1.12

-3.07a 1.20

-0.02 -0.02 3.56a 0.24 1.04

-0.67 -0.25 -0.51

-2.37b -2.13b -1.11 0.65

3.76a -0.66 1.04 0.30 0.54 0.05

-1.15 Number of observations Wald chi-squared Prob> chi-squared Pseudo R-squared

4922 342.6 0.000

0.0969

4922 168.43

0.000 0.0307

4922 109.57

0.000 0.0203

Note: For dummy variables dF/dx is for discrete change of dummy variable from 0 to 1. Superscripts a, b and c represent statistically significant at 1%, 5% and 10% levels, respectively.

Secondly, the role of household wealth and household size in financial education is limited, although incomes are positively associated with financial knowledge about interest rates, inflation and diversification. Households who indicated that they were better-off financially than they were a year ago were 3.4% points more likely to have the correct knowledge of interest rates than were those whose condition did not change or were worse-off. The results also show that respondents from larger households are less likely to have the correct knowledge about interest rates. Thirdly, a number of respondents’ characteristics have significant positive association with correct interest rate knowledge but less so with respect to correct inflation and risk diversification knowledge. Focusing on the interest rate model, respondents in polygamous marriages are more likely to have incorrect knowledge while those married in informal union are more likely to have correct knowledge than were respondents who are single. The age of respondent has an inverted u-shape relationship with the probability of answering the interest rate question correctly, with the probability beginning to drop at the age of 36.5 years. Formal education plays a significant role in the probability of providing the correct answer to the interest question with all the marginal effects being statistically significant at the 1% level. The higher the level of education, the larger the rise in the probability of answering the interest rate question correctly compared to those with no education – from 9.9% points in lower primary education to 41.7% points among those in tertiary education. This therefore suggests that education is an important determinant of financial

38

literacy. The nature of employment and the area of residence for the respondents do not play an important role in the probability of answering the interest rate question correctly. With regard to correct answer to the inflation question, the only respondent’s characteristics that seem to play significant roles are marital status and age. Compared to respondents whose marital status is single, respondents married in informal unions were more likely to provide the correct answer on inflation with a marginal probability of 15.7% points. Similar to the case of interest rates, there is an inverted u-shape relationship between the probability of a correct answer on inflation and age, with the probability beginning to decline at the age of 59 years. In the model about the correct knowledge of inflation, there is no evidence of significant relationship between probability of answering the inflation question correctly and education level, nature of employment and area of residence. Turning to the knowledge on risk diversification, the results show that gender and education levels of respondents play significant roles in determining the probability of answering correctly the question on risk diversification. In terms of gender, the probability that the answer on risk diversification is correct is higher for male respondents by 6.1% points than for female respondents. This suggests that females were significantly less financially literate with regard to the concept of diversification than were their male counterparts. Education levels play some inconsistent roles with primary education being negatively associated and tertiary education being positively associated with the probability of answering the risk diversification question correctly. Primary education compared to no education reduces the probability of answering the risk diversification question correctly by about 5% points while tertiary education raises the probability by 22.2% points. The results also show that the nature of employment and the area of residence do not play significant roles in the probability of answering the diversification question correctly. Table 34 presents ordinary least squares regression results of the factors associated with the financial literacy index which is the sum of correct answers from the seven questions related to financial literacy. Model 1 excludes respondents’ financial and behavioural traits while model 2 includes these traits. Overall, model 1 and 2 explain 16% and 20% of the variation in the financial literacy index, respectively. The F-statistics also show that the null hypothesis that all coefficients except the constant are zero is rejected at the 1% significance level. The inclusion of financial and behavioural traits in model 2 makes the income variable statistically insignificant, otherwise the significance of the other variables remain unchanged. Focusing on interpretation of results in model 2, three out of four behavioural traits are found to be statistically significant at the 1% level. The results show that having a bank account or having the intention to open a bank account makes a difference in the extent of financial literacy. The mean financial index for respondents with intention to open a bank account is 0.43 scores higher than the mean financial index of adults that do not intend to open a bank account. Owning a bank account or intending to open a bank account compels respondents to search information on financial issues, thereby improving their understanding of financial terms. However, this is not true in the case of taking a bank loan or intending to take a bank loan. Respondent who saved some money as a child have the mean financial index which is 0.15 scores higher than the mean scores for adults that did not save as a child, and the coefficient is statistically significant at the 1% level. This suggests that introducing children to manage their own savings improves financial literacy in adult life – hence such adults are more likely to learn more about the financial system and products. The mean financial index for people that care less for the future is 0.44 scores lower than the mean financial index of people that care more for the future in their everyday life. Hence, short-termism traits in human behaviour are not conducive to acquiring financial education.

39

Table 34: Ordinary Least Squares Regression on Financial Literacy Index

Variables Model 1 Model 2 coeff. T coeff. t

Have/intend to open bank account (0/1) Have/intend to take bank loan (0/1) Saved money as a child (0/1) Short-term horizon (0/1) Monthly income (K’000) Better-off financially than a year ago (0/1) Household size Male respondent (0/1) Married respondent – monogamous (0/1) Married respondent – polygamous (0/1) Married respondent – informal union (0/1) Age of respondent (years) Age-squared of respondent (years) Primary (1-5) education (0/1) Primary (6-8) education (0/1) Secondary (1-2) education (0/1) Secondary (3-4) education (0/1) Tertiary education (0/1) Employed – formal sector (0/1) Employed – informal sector (0/1) Self-employed (0/1) Urban – cities (0/1) Urban – district towns (0/1) Peri-urban (0/1) Constant

- - - -

0.0009 0.1870 0.0257 0.3190 0.0005

-0.1416 0.5577 0.0492

-0.0006 0.0691 0.3614 0.7500 0.9996 1.2900 0.1710

-0.0395 0.0916 0.2770 0.1635

-0.0090 1.9729

- - - -

1.82c 3.90a 2.41b 6.89a 0.01

-1.33 3.51a 6.72a

-8.07a 1.08

5.32a 8.31a

10.37a 8.43a 1.38

-0.33 1.47

3.78a 1.19

-0.08 12.31a

0.4260 -0.1131 0.1476

-0.4415 0.0005 0.1328 0.0229 0.2568

-0.0327 -0.2042 0.6594 0.0458

-0.0006 0.0492 0.2810 0.5845 0.7875 0.9422 0.0743

-0.0221 0.0850 0.2030 0.1104

-0.0212 2.2404

7.55a -1.36 3.47a

-10.25a 1.01

2.82a 2.21b 5.59a -0.66

-1.97b 4.02a 6.40a

-7.84a 0.77

4.14a 6.51a 8.21a 6.18a 0.61

-0.19 1.38

2.84a 0.80

-0.20 13.85a

Number of observations F- statistic Prob>F R-squared

4922 41.15 0.000

0.1597

4922 44.73 0.000

0.1970 Note: For dummy variables dF/dx is for discrete change of dummy variable from 0 to 1. Superscripts a, b and

c represent statistically significant at 1%, 5% and 10% levels, respectively. With respect to household characteristics, households that had witnessed improvement in their financial welfare and household size are positively associated with higher financial literacy scores. Households that were better-off financial than they were a year ago have a mean financial index score that is 0.13 scores higher than the financial index of households that experienced financial stagnation or were worse-off financially. Thus, although incomes do not play a significant role, increases in financial position (increases in incomes) are positively associated with financial knowledge. This may be due to the fact that increased incomes provide opportunities for savings and investments, as a result such households may be looking for information on how to utilize excess incomes. With respect to respondents’ socio-economic characteristics, the results show that gender, marital status, education and place of residence are associated with the number of correct answers to financial literacy questions. There is evidence of gender bias in levels of financial literacy, with the mean financial index for male respondents being 0.25 points higher than the mean financial index for female respondents. In terms of marital status, respondents in polygamous marriage have mean financial index scores lower by 0.20 points compared to respondents that are single. However, the average financial index scores for respondents that are married through informal union are 0.66 points higher than the average for respondents that are single. The age of the

40

respondent has an inverted u-shape relationship with financial literacy score, with the score starting to decline at 38 years of age. The level of formal education plays an important role in financial literacy, with the coefficients being statistically significant at the 1% level from upper primary to tertiary education and the coefficients are increasing with the level of education. Compared to no education, respondents whose highest education is upper primary school have mean financial index scores that are 0.28 scores higher while respondents whose highest level of education is tertiary have mean financial index scores that are 0.94 scores higher. This suggests that years of schooling matter in the acquisition of financial knowledge. There is, however, no statistically significant relationship between the level of financial literacy and the nature of employment. In terms of population segments, the results show that respondents in urban–cities have mean financial literacy scores that are 0.20 points higher than the average scores among residents of rural areas. The coefficient of urban-cities is statistically significant at the 1 percent level. This may be attributed to the many sources of information about financial information and services in urban-cities compared to rural areas.

41

5. Knowledge of Financial Services and Products in Malawi Literature suggests that most consumers in developing countries have little knowledge about the services and products offered by financial service providers, leading to high levels of financial exclusion. It is important therefore to know the degree to which products and services offered in the financial sector are known by customers. The main objectives of questions on financial services and products are to understand how people choose financial products, whether they check the features, terms and conditions before buying financial products, whether they look for information before buying products and whether they seek advice or information before making financial decisions. In addition, financial consumer protection is increasingly becoming important with the sophistication of the financial sector and increasing market power of financial service providers. The baseline survey also investigates whether consumers have come into conflict with financial providers, the steps taken to resolve such conflicts and the extent to which people in Malawi are aware of various institutions that provide financial consumer protection. Some of the decisions can be affected by the level of financial literacy and socio-economic factors. Multivariate regression analysis is therefore used to investigate socio-economic factors associated with likelihood of participation in formal, semi-formal and informal financial systems, likelihood of having a savings account and a bank loan. 5.1 Possession of Financial Services and Products The concentration of formal financial service providers in high income areas such as cities and district towns has implications on the use of financial products and services in Malawi. OPM and Kadale Consultants (2009) find that 55% of adults are excluded from access to financial services, with the formal sector only servicing 26% of adult Malawians in terms of holding or using financial products and services. The baseline survey asked a different question, on whether adult Malawians currently have financial products in different segments of the market compared to 5 years ago. Table 35 shows the proportion of adult Malawians that have current financial products and services in formal, semi-formal and informal market segmentation by population segments. There are adult Malawians that have no financial products and services in more than one segment. For instance, 1.2% of adults had products in both formal and semi-formal markets, 9.9% had products in formal and informal markets, 3.4% of adults had products in both semi-formal and informal markets and 0.9% had products in all three markets. Overall, 16.9% of adult Malawians had at least one product or service from the formal financial sector, 5.6% held at least one product from the semi-formal sector and 52.8% had at least one product/service from the informal financial sector. The baseline survey reveals that 34.2% of adults Malawians had no financial product and service at the time of the survey. The proportion of adults without financial products and services is highest among those living in the rural areas (38%), followed by those living in the district towns and lowest in the cities (18.5%). Interestingly, the proportion with products and services from the informal sector is highest among city dwellers at 59.7% although they also have the highest proportion with products from the formal financial sector.

42

Table 35: Current Possession of Financial Products and Services (%)

Products and Services Urban - cities

Urban – district towns

Peri - urban

Rural Malawi

Formal products and services Semi-formal products and services Informal products and services No financial products and services

N

46.90 3.26

59.74 18.48 659

33.71 8.18

56.24 24.45 140

34.54 5.18

52.28 23.21 200

10.22 5.86

51.55 37.95 4,000

16.97 5.58

52.81 34.24 4,999

Note: The percentage columns do not add to 100% due to multiple accesses of products and services across market segments.

Source: Financial Literacy Baseline Survey 2013 Table 36 presents specific products and services that adult Malawians currently have and those that they have had in the past 5 years, whether they currently have them or not. The most dominant current product/service from the formal sector is savings and deposit account, with 15.2% of adult Malawians with access. If current accounts are included and netting out multiple account holding, the baseline survey shows that only 15.4% of adult Malawians have bank accounts.3 Compared to 5 years ago, the data shows a marginal decline in both savings/deposit accounts and in current accounts, showing that possession of bank accounts has declined among the adult Malawians. Differences by population segments are apparent with only 8.6% of adults in rural areas having formal savings and deposit accounts compared to 44.7% of adults in the cities. These differences are partly due to supply side factors such as location of the financial service providers, particularly banks. Mortgages and current/checking accounts appear to be city products with virtually none held by rural dwellers. Although the number of microfinance institutions (MFIs) has increased in the past 2 decades, the proportion of adults holding products and services in MFIs is not high. Nonetheless, the data shows that such services are available in district towns, peri-urban and rural areas. The role the informal financial sector plays in Malawi is a significant one, not only in the rural areas (with limited supply of financial service providers) but also in the urban areas. City dwellers have the highest proportion with informal credit compared to other areas. Overall, almost a third of adult Malawians use informal credit and 24.9% use informal savings products such as Rotating Savings and Credit Associations (ROSCAs) and Village Savings and Loan Associations (VSLAs). In the past 5 years, the lower panel of Table 40 shows that as much as 59.9% of adults nationally and 67.9% among city dwellers have had informal credit and 29.7% have had savings in the informal sector. Most worrying is the fact that the proportion of adults with no financial products and services has increased in the past 5 years from 20.4% to 34.2%.

3 This figure is not comparable to the 19% of adults that were banked (which includes ownership of products or use of banking products or services) in 2009 (OPM and Kadale Consultants, 2009).

43

Table 36: Proportion Possessing Financial Products and Services (%)

Products and Services Urban - cities

Urban – district towns

Peri - urban

Rural Malawi

Have Now

Investments Pensions Health/life/income insurance Mortgages Formal credit General insurance Formal savings/deposit account Current/checking account Money transfer services Semi-formal credit (MFIs) Semi-formal savings (MFIs) Informal credit (katapila/friends) Informal savings (ROSCAs, VSLAs) Informal insurance None

N

3.75 8.82 5.85 0.29 3.30 4.94

44.71 4.66 4.06 0.18 1.91

42.33 23.13 11.46 18.48 659

0.23 6.85 0.61 0.00 0.45 0.38

33.55 0.23 4.36 3.49 5.93

31.38 36.93 12.59 24.45 140

3.62 8.95 5.86 0.00 2.82 3.53

29.29 3.45 3.80 2.24 3.42

29.21 23.88 12.09 23.21 200

0.80 1.11 0.14 0.00 0.21 0.13 8.61 0.10 0.96 2.43 4.50

30.52 24.76 14.22 37.95 4,000

1.30 2.70 1.17 0.04 0.74 0.93

15.16 0.85 1.62 2.42 4.18

32.02 24.94 13.70 34.24 4,999

Have had in past 5 years

Investments Pensions Health/life/income insurance Mortgages Formal credit General insurance Formal savings/deposit account Current/checking account Money transfer services Semi-formal credit (MFIs) Semi-formal savings (MFIs) Informal credit (katapila/friends) Informal savings (ROSCAs, VSLAs) Informal insurance None

N

4.04 9.40 6.77 0.46 5.75 5.07

47.82 5.03 4.59 4.44 2.15

67.87 29.27 12.17 10.95 659

0.23 6.85 0.61 0.00 0.45 0.61

39.81 0.23 4.36 5.14 7.19

66.39 42.68 13.17 10.84 140

4.12 8.95 6.73 0.29 3.59 3.53

30.36 3.76 4.35 6.97 3.42

55.76 28.32 13.43 12.84 200

0.91 1.18 0.14 0.05 0.43 0.13 9.67 0.17 1.17 4.84 5.21

58.59 29.31 15.81 22.82 4,000

1.45 2.82 1.33 0.12 1.27 0.95

16.67 0.97 1.88 4.90 4.80

59.92 29.73 15.13 20.38 4,999

Source: Financial Literacy Baseline Survey 2013 5.2 Choices and Decisions about Financial Services and Products

Respondents were asked about the products and services that were specifically chosen by them. For the first product/service that was mentioned, questions were asked about their choices. Table 37 presents the distribution of the first product mentioned by adults that were chosen by respondents. Reflective of access to financial products and services above, the typical products that were mentioned first as being chosen by respondents are formal savings/deposits (15.8%), informal credit (47%) and informal savings (23.7%). Investments, health/life/income insurance, mortgages, general insurance, current account and money transfers were not first products or services mentioned in the district towns while money transfers were not mentioned in the peri-urban areas.

44

Table 37: First Mentioned Products and Services Chosen by Respondent (%)

Products & Services Urban - cities

Urban – district towns

Peri - urban

Rural Malawi

Investments Pensions Health/life/income insurance Mortgages Formal credit General insurance Formal savings/deposit account Current/checking account Money transfer services Semi-formal credit (MFIs) Semi-formal savings (MFIs) Informal credit (katapila/friends) Informal savings (ROSCA, VSLAs) Informal insurance

N

2.33 0.66 1.85 0.26 1.82 1.05

35.76 1.06 0.81 1.63 0.33

33.74 16.72

1.98 518

- 0.29

- -

2.20 -

35.88 - -

3.22 0.86

29.24 26.05

2.25 113

1.49 1.84 1.45 0.37 1.15 0.80

30.34 1.57

- 1.84 2.73

38.87 17.14

0.41 162

0.60 0.09 0.11 0.03 0.31 0.09 8.99 0.17 0.39 3.75 3.91

51.06 25.41

5.10 2,727

0.87 0.27 0.43 0.08 0.65 0.27

15.08 0.37 0.41 3.32 3.21

47.04 23.73

4.28 3,520

Source: Financial Literacy Baseline Survey 2013 Respondents who made choices about the product by themselves were asked whether they searched for information from a range of sources before they got the product. Figure 8shows the proportion of adults that searched or not searched for information from a range of sources. Overall, 69.1% of adults that made the choice of the product by themselves searched for information from different sources before choosing the product or service. There are variations by population segments, with the highest proportion searching for information among residents of district towns (78.6%) and the lowest among residents of rural areas (68.6%). Most adult Malawians, therefore make decisions about financial products and services after considering several sources of information about the products.

Figure 8: Proportion Searching for Information from a range of Sources (%)

Source: Financial Literacy Baseline Survey 2013

Among those that searched for information from a range of sources, questions were asked about who approached them and from where they learnt about the product/service (Table 38). Overall, 87.6% of adult Malawians searching for information about the products from a range of sources

70.278.6

66.8 68.6 69.1

29.821.4

33.2 31.4 30.9

0

20

40

60

80

100

120

Urban - cities Urban - district towns

Peri - urban Rural Malawi

Pe

rce

nt

Yes No

45

approach the service providers for information while only 12.4% are approached by the service provider. There are no substantial variations across the population segments. The most common sources about the product are family or friends, accounting for 58.4% among those that searched information from a range of sources. This is followed by the service provider, accounting for 35.6% of adults searching for information about the product. Family or friends are the main sources of information about the product in cities, peri-urban and rural areas while residents of district towns learn about the product mostly from the service providers. Employers and advertisements in the media seem to play a limited role. Table 38: How Adults Got Information about Financial Product (%)

Indicators Urban - cities

Urban – district towns

Peri - urban

Rural Malawi

Who approached who

I approached the provider The provider

N

89.86 10.14 370

96.36

3.64 89

88.99 11.01 117

86.56 13.44 1,879

87.62 12.38 2,455

Where they learn about the product

Service provider Family or friends Employer Advertisement in media Other

N

20.85 68.72

5.13 5.30

- 370

45.13 39.68

7.25 7.93

- 89

41.64 46.23

4.70 7.43

- 117

37.45 58.32

0.72 3.07 0.45 1,879

35.60 58.36

1.87 3.85 0.34 2,455

Source: Financial Literacy Baseline Survey 2013 Figure 9 shows the proportions that searched for alternative products and to what extent they searched for the financial product they had chosen. Overall, 52% of adults that chose products themselves also considered alternatives and 57.1% searched until they found the best product for their needs. Searching for alternative products was highest among residents of district towns and lowest among rural residents. Similarly, the proportion searching until they got the best product is highest among district town residents, followed by city residents and lowest among rural residents.

Figure 9: Nature of Searching for Information from a Range of Sources (%)

Source: Financial Literacy Baseline Survey 2013

58.2

70.0

54.349.8 52.0

64.1

70.5

55.9 55.257.1

0

10

20

30

40

50

60

70

80

Urban - cities Urban - district towns

Peri - urban Rural Malawi

Pe

rce

nt

Considered Alternatives Searched until Found Best Product

46

Table 39 shows the proportion of adults who chose the product themselves and whether they checked the terms and conditions of the product prior to getting the product. Overall, 79.2% of adult Malawians that chose products on their own also checked terms and conditions before obtaining the product and 88.2% of these did so carefully. There are, however, no major differences across population segments in terms of checking terms and conditions and the extent of scrutinizing the terms and conditions. Table 39: Proportion of Adults Checking Terms and Conditions about Financial Product (%)

Variable Urban - cities

Urban – district towns

Peri - urban

Rural Malawi

Checked Terms and Conditions?

Yes No

N

81.81 18.19 518

78.05 21.95 113

85.53 14.47 161

78.37 21.63 2,725

79.24 20.76 3,517

To what extent?

Carefully Roughly Refused

N

89.77 10.23

- 422

94.27

5.73 -

85

89.82 10.18

- 142

87.41 12.37

0.21 2,124

88.17 11.66

0.17 2,773

Source: Financial Literacy Baseline Survey 2013 5.3 Financial Consumer Protection The need for financial consumer protection arises due to asymmetry of information between financial service providers and consumers and due to high concentration of markets in many segments of the financial sector. Although the central banks provide overall protection, in form of deposit protection, through their regulatory and supervisory responsibilities, in developing countries some of these regulations only apply to the formal segment of the informal system. Malawi has several laws that aim at protecting consumers against business malpractices, although the focus is on general goods and services, rather than specific to the financial sector. First, there is the Consumer Protection Act of 2003 which aims at protecting the rights of consumers; addressing the interests and needs of consumers; establishing a Consumer Protection Council, and providing effective redress mechanisms for consumer claims. Second is the Competition and Fair Trade Act of 2003 whose main aim is to encourage competition and prohibit anti-competitive trade practices and behaviour, and to protect consumer welfare. Under this Act, the Malawi Competition and Fair Trading Commission was established as a body to handle complaints about uncompetitive and unfair trading practices. The baseline survey also sought to establish the extent to which problems that consumers experience with service providers tend to be resolved while seeking consumers’ perceptions on consumer protection issues in Malawi. Apart from public institutions, the Consumer Association of Malawi (CAMA) established in 1994 as a non-governmental organisation, also offers consumer protection services. CAMA’s mandate is to “promote and protect consumer interests through policy advocacy and lobbying, conducting public awareness and education programmes and carrying out research on various cross-cutting issues which have direct or indirect bearing on the consumer”4. As noted by World Bank (2011), consumers in Malawi do not have adequate mechanisms for handling complaints against financial service providers partly due to absence of procedures for handling disputes within financial institutions or outside the financial system. In addition to its regulatory and supervisory role, the Reserve Bank of Malawi established a Consumer Protection Division specifically to promote consumer welfare and protect consumers against malpractices in

4 See http://www.cama.mw

47

the financial sector. There are also other state institutions such as other government departments, the judiciary and the Police that can also handle consumer complaints about the quality of services in the financial sector. Nonetheless, the use of these various channels resolving conflicts in the financial sector may be hampered by consumer awareness. The baseline survey therefore sought to understand how consumers have dealt with conflicts with financial service providers and what they would do in case of a conflict with a financial service provider. Table 40 shows the proportion of adult Malawians that have ever had a conflict with a financial service provider. Overall, only 8% of adults have had a conflict with a financial service provider. The proportion of adults experiencing a conflict is much higher in the peri-urban and cities than in the rural areas. As observed above, peri-urban and cities have the highest proportion of adults with access to formal financial products and services, and these conflicts are likely to arise with formal service providers. It is also noted that most of the adults that experienced conflicts with the financial service providers also reported that they did something to resolve it. Table 40: Proportion of Adults Experiencing Conflict with Financial Service Provider (%)

Indicators Urban - cities

Urban – district towns

Peri - urban

Rural Malawi

Experienced conflict?

Yes No Refused

N

15.06 84.94

- 659

9.12

90.88 -

140

15.45 84.55

- 200

6.3

93.63 0.07 4,000

7.98

91.97 0.06 4,999

Did something about it?

Yes No Refused

N

90.16

9.84 -

90

72.35 27.65

- 12

81.32 18.68

- 29

81.82

17.5 0.69 249

83.41 16.16

0.43 380

Source: Financial Literacy Baseline Survey 2013 Figure 10 shows the proportion that took action to resolve the conflict and the nature of action taken. The most dominant approach taken to resolve conflicts was to stop using the service reported by 35.2% of adults, followed by approaching service providers through community leaders (21.1%), approaching the service providers through friends and family (19%) and submitting a formal grievance to the company that sold the product. The limited use of formal institutions such Reserve Bank of Malawi and its Consumer Protection Division, judiciary and Ministry of Finance and the high proportion that just stops using the service indicate widespread problems of public awareness of how consumers can go about resolving conflict with the financial service provider.

48

Figure 10: Actions taken to Resolve Conflict with Service Provider (%)

Source: Financial Literacy Baseline Survey 2013

About 16.2% of adults that experienced a conflict with a financial service provider did not take any action at all and as Figure 11 shows most of them (36.2%) were not aware of government agencies that can be approached for help. There is also a perception that law does not adequately protect consumers in Malawi, with 19.1% of adults that did not take action believing that the laws are not effective. The consumers also feel that the financial service providers are just too powerful and do not have strong countervailing power when they experience a conflict. This is reflective of the structure of the financial system in Malawi where different segments of the financial sector have few players dominated by one or two providers.

Figure 11: Why No Actions Taken to Resolve Conflict with Service Provider (%)

Source: Financial Literacy Baseline Survey 2013

0.0

0.0

0.0

0.1

0.3

0.4

1.6

4.3

8.2

12.9

16.8

19.0

21.1

35.3

0.00 10.00 20.00 30.00 40.00

Submitted a claim to the RBM Consumer Protection Division

Submitted a claim to the Ministry of Finance

Approached the media (newspaper, radio, or TV station)

Submitted a claim to the Reserve Bank of Malawi (generally)

Submitted a claim to other government authority

Approached the commercial and/or magistrates court

Approached a consumer organization

Approached the police

Other

Made an informal complaint to employees of the company

Submitted a formal grievance to the company which sold me the product

Approached the service provider through friends and family

Approached the service provider through community elders

Stopped using the service before the contract expired

Percent

The law does not

adequately protect

consumers, 19.1

Government authorities do not

work

properly, 3.0

Financial

organizations are

too powerful, 13.8

I am not aware of government

agencies that I

can approach for help, 36.2

Other, 22.4

49

The question of action for resolving conflict with the financial service provider was also asked to adults that have not had experience of a conflict and Figure 12 shows what they could have done if they were to be in conflict with a service provider. Nearly a third would have approached the service provider through community leaders, 27.7% would have stopped using the service, 27.1% would have approached the police and 26.7% would have had informal discussion with the service providers. There is notable absence in the top 6 actions of the Reserve Bank, RBM Consumer Protection Division and Ministry of Finance. The police and a consumer organization perform much better than public institutions that are providing oversight over financial service providers. These figures just confirm the lack of awareness of consumers on how they can resolve conflicts with financial service providers. Among both those that experience conflict and took action and the ones that did not experience a conflict, it seems there is more trust in community leaders as channels for resolving conflicts with financial service providers.

Figure 12: Actions Expected to Resolve Conflict with Service Provider (%)

Source: Financial Literacy Baseline Survey 2013

Figure 13 shows the awareness of adult Malawians about the key consumer protection institutions, Reserve Bank of Malawi (RBM), RBM Division of Consumer Protection and Consumer Association of Malawi (CAMA). Respondents were asked whether they have heard of any of these three institutions. The Reserve Bank of Malawi is the institution that adults have heard most (74.2%), followed by the Consumer Association of Malawi (46.7%) and RBM – Division of Consumer Protection is least known (12.5%). For Reserve Bank of Malawi and CAMA, more adults in the cities know these institutions than those (adults) in the rural areas. The more urbanized the areas, the higher the proportion of adults that know RBM and CAMA. Surprisingly, the proportion that has heard of RBM Division of Consumer Protection is highest among peri-urban dwellers at 18.7% compared those in the cities at 15.7%. The low proportion of adults who have heard about the RBM Division of Consumer Protection coupled with lack of awareness of resolving conflicts in the financial sector, implies that as a new institution in financial consumer protection, the division has a massive task of creating awareness about its existence and the role it can play in promoting consumer rights in the financial sector.

0.2

0.2

0.3

0.4

0.5

1.1

1.8

2.9

3.1

3.3

4.3

5.1

10.8

11.1

14.6

26.7

27.1

27.7

30.6

0.00 5.00 10.00 15.00 20.00 25.00 30.00 35.00

Submit a claim to the RBM Consumer Protection Division

Refused

Submit a claim to the Ministry of Finance

Approach the media

Submit a claim to the Reserve Bank of Malawi (generally)

Submit a claim to other government authority

Other (specify here):

Formally, through a system for redress (unspecified)

Don't Know

Do nothing

Approach a consumer organization

Make an informal complaint to employees of the company

Approach the service provider through friends and family

Approach the commercial and/or magistrates court

Submit a formal grievance to the company which sold me the product

Informally, by directly discussing (unspecified)

Approach the police

Stop using the service before the contract expired

Approach the service provider through community elders

Percent

50

Figure 13: Knowledge about Key Consumer Protection Institutions (%)

Source: Financial Literacy Baseline Survey 2013

5.4 Financial Information and its Sources There are several channels through which citizens can get information on financial products and services. These channels can also be useful in guiding programmes on financial education through understanding of the current habits of the adult population. Table 41 presents the proportion of adults on their current use of alternative channels of information by assessing the extent to which they are in the habit of using different media sources. Overall, the radio seems to be the dominant media for information as 61.8% of Malawian adults regularly listen to the radio. The proportion of ‘listen to the radio’ is highest at 75.2% among city residents and falls in low income areas to 59.2% in rural areas. NSO (2012) finds that ownership of radio is highly correlated with wealth, and 60.6% of households and 42.8% of households in the urban and rural areas own a radio, respectively. The second most important channel across population segments is TV with 14.6% of adult Malawians indicating that they regularly watch TV, although the difference between cities and rural areas is substantial. Table 41: Use of Media as Sources of Information (%)

Statement Urban - cities

Urban – district towns

Peri - urban

Rural Malawi

"I regularly read a national newspaper." "I regularly listen to the radio." "I regularly watch TV." "I regularly use the internet." "I regularly use SMS as a source of

information on financial services." N

28.98 75.23 49.32 16.97 10.42

659

24.79 72.48 27.55 11.33

9.97

140

19.95 61.02 30.43

9.11 8.74

200

6.16 59.21

7.36 0.97 2.19

4,000

10.43 61.83 14.61

3.79 3.85

4,999

Source: Financial Literacy Baseline Survey 2013 Although there has been increased penetration of mobile phones in Malawi in recent times from 18% in 2005 to 73% in 2011 in urban areas and from 0.9% to 29.5% during the same period in rural areas (NSO, 2012), the use of SMS on mobile phones as a source of financial information is limited.

90.5

85.381.6

70.674.2

15.713.3

18.7

11.6 12.5

69.9

60.7

56.0

41.6

46.7

0

10

20

30

40

50

60

70

80

90

100

Urban - cities Urban - district towns

Peri - urban Rural Malawi

Pe

rce

nt

Reserve Bank of Malawi

RBM Division of Consumer Protection

Consumer Association of Malawi

51

Overall, only 3.9% of adult Malawians indicated that they regularly use SMS as a source of information on financial service and the proportion declines as one moves from the cities (10.4%) to rural areas (2.1%). So even in the urban areas where the ownership of mobile phone is quite high, the use of such devices for financial information is dismal. Financial knowledge and information can also be acquired through conversation with relatives, colleagues and friends. Table 42 shows how frequent adult Malawians talk about financial institutions and services with their families and friends. The proportion of households that talk about financial institutions and services daily is only 6.8% of adult Malawians. The highest proportion is observed in district towns (21%) and the lowest proportion is observed among city residents (5.8%). It appears Malawians talk less frequently about financial institutions and services, with the highest proportion of 30% of adults talking once a month or less often. There are also significant proportions of adults that never talk about financial institutions and services, about 22.6% of adult Malawians, with the lowest proportion of 5.3% among residents of district towns.

Table 42: Frequency of Talking about Financial Institution and Services (%)

Statement Urban - cities

Urban – district towns

Peri - urban

Rural Malawi

Daily Few times a week Few times a month Once a month or less often Never Refused

N

5.84 24.11 19.70 35.81 14.52

0.02 659

21.00 27.18 22.39 24.16

5.27 -

140

6.78 12.9

20.53 36.94 22.84

- 200

6.32 20.06

20.1 28.81 24.66

0.05 4,000

6.8 20.48 20.15 29.95 22.58

0.04 4,999

Source: Financial Literacy Baseline Survey 2013 5.5 Assessment of Financial Services Holding of formal financial products and services in Malawi remains low as observed above, with only 15.4% of adult Malawians in 2013 having savings/deposit and current accounts. This issue is investigated further by looking at the revealed demand for such service in terms of the proportion of adults that have a bank account or are considering opening one. This means that these figures overstate the actual proportion of households that have bank accounts; they give a sense of the potential demand for banking services. Figure 14 shows the proportion of adults with or considering opening a bank account in Malawi. Overall, 28.7% of adult Malawians have a bank account or are considering opening one. Although this includes intention to open a bank account it compares favourably with the proportion that has formal savings and current account products. There is a relationship between population segments and the revealed demand for bank accounts, possibly influenced by the availability of banking services and relatively higher incomes in the cities compared to other areas. In the urban-cities, 60.8% of adults have a bank account or are considering having one compared to rural areas where banking facilities are limited with only 21.1% of adults having bank accounts or intending to have one. Although, banks have recently been expanding to district towns, the proportion with bank accounts or considering bank accounts in district towns is marginally less than that observed in peri-urban areas. Nonetheless, it can be argued that most of those that have bank accounts in peri-urban and rural areas are accessing banking facilities mostly located in district towns.

52

Figure 14: Proportion with Revealed Demand for Bank Accounts (%)

Source: Financial Literacy Baseline Survey 2013

The revealed demand for bank accounts is explored further by looking at the socio-economic characteristics of adult Malawians as presented in Figure 15. First, with respect to age of respondents, high revealed demand is observed among the 30-34 years age group (36.5%), followed by the 55-59 years age group (33.2%) while the least proportion is among the over-65-year-old groups. Thus, those that are in retirement age are unlikely to hold bank accounts or consider opening a bank account. Secondly, in terms of gender, adults from female-headed households and female respondents are less likely to have a bank account or consider opening one. Thirdly, there is a clear pattern of the relationship between education and the revealed demand for a bank account with the proportion of having/wanting a bank account rising exponentially from 9.9% among adults with no education/some primary education to 89.7% among adults with tertiary education. Finally, there is a similar pattern with respect to the nature of employment, with the proportion having/wanting a bank account decreasing from 84.3% among adults in formal employment to 24.9% among adults in self-employment and 26.2% among adults who are unemployed.

60.8

44.145.9

21.7

28.7

0

10

20

30

40

50

60

70

Urban - cities Urban - district towns

Peri - urban Rural Malawi

Pe

rce

nt

53

Figure 15: Proportion with Revealed Demand for Banks Account by Socio-Economic Status (%)

Source: Financial Literacy Baseline Survey 2013

Figure 16 shows most important factors that adult Malawians having/wanting a bank account mentioned as motivating factors. The most important factor considered by 36.5% of adult Malawians relates to interest rates and costs, followed by bank charges (30.7%), bank’s reputation (29.1%), having enough money to put in the bank (22.3%) and bank requirements for opening an account (such as identification cards) (20.2%). The two most important factors relate to the net benefits from holding accounts. This implies that as long as the spread between savings and credit interest rates remain high as they are in Malawi (Chirwa and Mlachila, 2004), most adults with low incomes are unlikely to open bank accounts. Data from various commercial banks following interest rates adjustments in March 2013 shows that the average spread between savings interest rates and the base lending rates is 26%, with the base lending rates being as much as 4.5 times the savings interest rate. This high spread offers little incentives for adults to hold bank accounts in Malawi. Distance to banking offices and minimum balance requirements do not seem to be major factors as only 15.6% and 14.3% of adults indicated that would be one of their most important factors, respectively.

25.0

31.6

36.5

33.1

28.4 29.0 29.9

33.2

20.0

14.6

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

40.0

Perc

en

t

a) Age of Respondent

31.7

15.6

37.5

22.6

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

40.0

Pe

rce

nt

b) Gender

9.9

18.2

27.1

37.1

53.5

89.7

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0

Pe

rce

nt

c) Education of Respondent84.3

41.7

24.9 26.3

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

Pe

rce

nt

d) Employment

54

Figure 16: Motivating Factors for Opening Bank Account (%)

Source: Financial Literacy Baseline Survey 2013

The revealed demand for bank loans is even much lower than the revealed demand for a bank account. Table 43 shows that only 7.6% of adult Malawians have a bank loan or are considering taking out a bank loan. There are differences between population segments with 12.7% of adults in cities and 5.2% of adults in district towns having/wanting a bank loan. Table 43: Proportion with Revealed Demand for Bank Loan (%)

Variable Urban - cities

Urban – district towns

Peri - urban

Rural Malawi

Yes No

N

12.74 87.26 659

5.15 94.84 140

12.36 87.64 200

6.63 93.37 4,000

7.64 92.36 4,999

Source: Financial Literacy Baseline Survey 2013 Figure 17 shows that among the 7.6% of adults that had a bank loan or are considering taking a bank loan, the two most important factors for taking a loan are the bank’s reputation (38.7%) and credit interest rates (35.4%). This is followed by the fact that the individual has a bank account with the bank already (20.8%) and the courtesy of the bank staff (18.5%). Insurance requirements and collateral requirements were important considerations for 15.4% and 12.4% of adults, respectively. Similar to the factors important for opening a bank account, proximity to a bank office is not among the most important factors in considering taking a loan. The factors under ‘other’ mentioned by 9.3% of adults include help in starting a business and in business finances and period of loan repayment.

2.3

3.5

7.4

7.5

14.3

15.6

16.4

20.2

22.3

29.1

30.7

36.5

0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0

Any additional informal payments

Waiting time in line and length of approval procedures

Other

Gifts and advertising campaigns

Bank's minimum required balance

Proximity to the bank office

The way the bank's personnel treat you

Bank requirements for one to open up an account

Whether I have enough money to put in the bank

Bank's reputation

Bank charges

Savings and credit interest rate and costs

Percent

55

Figure 17: Motivating Factors for Taking a Bank Loan (%)

Source: Financial Literacy Baseline Survey 2013

Table 44 shows evaluation of various financial service providers, in terms of the proportion that agreed with different statements about the quality and types of services. First, with respect to ‘things done with financial service providers being easy’, community groups scored highest with 58.8% of adults, followed by banks with 40.7%, and the least being insurance companies. Secondly, with respect to efficiency of services, community groups again had the highest proportion of 55.1% of adults agreeing that ‘it is quick to get service’, followed by the banks at 41.5%, and insurance companies are least. Thirdly, banks have the highest proportion of 53.2% of treating customers with respect, followed by community groups, and insurance companies are least. Table 44: Perceptions on Different Types of Financial Service Providers (%)

Statement Banks Other Lending

& MFIs

Community Groups

Katapila Insurance Companies

"Getting things done with them is easy" "It is quick to get service" "They treat you with respect" "The information they give is easy to

understand" "They are for rich people & not for poor

people" "The charges are reasonable" "They lend too easily and get you into

problems" "They take your property if you do not pay

your loan" N

40.67 41.53 53.23 44.53

39.31

37.27 19.21

29.28

4,999

22.87 23.06 28.84 25.72

13.56

19.65 43.40

54.98

4,999

58.80 55.08 52.48 53.45

5.63

54.12 36.17

47.97

4,999

21.09 30.69 16.06 18.41

8.69

6.73

80.15

82.83

4,999

10.50 10.04 14.82 13.15

34.42

8.06 7.09

12.16

4,999

Source: Financial Literacy Baseline Survey 2013 Fourthly, in terms of ease to understand the information provided, community groups are rated highly followed by banks, with insurance companies and katapila being on the lower end. Fifthly,

4.0

5.6

5.8

9.3

12.4

14.1

15.4

18.5

20.8

35.4

38.7

0 5 10 15 20 25 30 35 40 45

Waiting time in line and length of approval procedures

Proximity to the bank office

Gifts and advertising campaigns

Other

Collateral requirements

Bank's minimum balance/deposit requirement

Insurance requirements

The way the bank's personnel treat you

That I already have an account with them

Credit interest rates

Bank's reputation

Percent

56

a high proportion of adults feel that banks and insurance companies are ‘for the rich people and not poor people’ and less feel so for community groups and katapila. Sixthly, community groups and banks emerge as reasonable with respect to charges imposed on customers while katapila and insurance companies are considered less reasonable in respect to that. Seventhly, katapila is characterized as ‘lending too easily and get you into problems’ as revealed by 80.2% of adults, followed by other lending organizations and MFIs (43.4%) and community groups (36.7%). Finally, katapila was also reported by a large proportion (82.8% of adults) that ‘they take your property if you do not repay the loan’, followed by MFIs and community groups, while only 29.3% of adults expressed such sentiment regarding banks.

Figure 18 reports whether adults personally experienced problems when using financial services and shows that the most common problem cited is waiting long time to withdraw money from the bank, mentioned by 14% of adults. This is followed by problems with Auto Teller Machines (ATMs) when people want to draw money (12.8%) and hidden or unexplained charges when withdrawing money from the bank. About 4.9% of adults indicated that they have been fraudulently approached by someone claiming to be a microfinance lender.

Figure 18: Proportion Experiencing Problems in Using Financial Services (%)

Source: Financial Literacy Baseline Survey 2013

5.6 Factors Associated with Access to Financial Services This section investigates the relationship between financial access variables and socio-economic characteristics of adult Malawians using the following equation: ���� = � + ���� + ��� + ���� + ��� + �� + � (2) where FAI is a vector of financial access indicators, FLI is a vector of financial literacy indicators, HHW is a vector of household wealth and welfare indicators, HHC is a vector of household characteristics, REC is a vector of respondent characteristics, X is a vector of other control variables, and μ is the error term. The independent variables are as defined under equation (1) above.

0.6

1.4

4.9

7.8

12.8

14.0

0 2 4 6 8 10 12 14 16

Any other type of problem

Difficulty obtaining any type of insurance payout after filing a claim

Been fraudulently approached by someone claiming to be a microfinance lender

Hidden or unexplained charges when withdrawing money from the bank

The ATM isn't working when you need to withdraw money

Waiting a long time to withdraw money from the bank

Percent

57

Several indicators of access to financial services are constructed as dichotomous dependent variables. The first group has three indicators that focus of the likelihood of participating in each of the following financial market segments: formal, semi-formal and informal financial markets. Participation in formal financial market is defined as a dummy equal to 1 if the respondent held any financial product or service in the formal financial system (stock market, banks, non-bank and insurance), otherwise it is equal to zero. Similarly, participation in the semi-formal market is captured by a dummy equal to 1 if the respondent held financial products and services in the semi-formal sector (such as MFIs), and participation in the informal financial sector is captured by a dummy equal to 1 if the respondent held products/services from the informal sector (such as katapita, ROSCAs, VSLAs) and zero otherwise. As observed above, some of the respondents participate in all three segments but the models are estimated separately. The second group of indicators relate to the revealed demand for bank accounts and bank loans. The revealed demand for bank loans is defined as a dummy equal to 1 if the respondent has a bank account or is considering opening one; otherwise it is equal to zero. Similarly, revealed demand for loans is defined as a dummy equal to 1 if the respondent has a bank loan or is considering taking one; otherwise it is equal to zero. These two variables capture both effective demand (those already with bank accounts) and the potential demand (those willing to open bank accounts or willing to take bank loans but do not currently have these). The explanatory variables include financial literacy index, household income and financial wellbeing, gender of household head, household size, age of respondent, marital status of respondent, highest level of education of respondent, nature of employment and population segments as defined under equation (1) above. Table 45 presents marginal effects from regression analysis of the probability of participating in different financial segments. All the models are valid based on the Chi-squared tests at the 1 percent significance level, rejecting the null hypothesis that all the parameter coefficients are equal to zero. However, the formal market model has more explanatory power than the other two markets. First, does financial literacy help? The evidence shows that participation in the formal and semi-formal markets is positively associated with financial literacy; the more financially literate the adult respondent is, the higher the probability of participation in these markets. Financial literacy, however, does not matter in participation in the informal market. Comparatively, an additional correct answer to financial literacy questions leads to an increase of 1.7% and 0.9% in the probability of participating in the formal and semi-formal markets, respectively. This suggests that financial education programmes are likely to improve the proportion of adults that can hold financial products and services in the formal financial sector, ceteris paribus. Income variables also play an important role, particularly in the formal and semi-formal sector. The results show that the households’ monthly income is positively associated with participation in the financial markets but the marginal effects are only statistically significant in the semi-formal market model at the 5% level of significance. The marginal effects show that an extra MK1 000 in monthly income increases the probability of participating in semi-formal markets by 0.01%. More important though are the changes in the financial position of households compared to a year ago, particularly statistically significant for formal and semi-formal markets. The marginal effects suggest that the probability of participation increases by 3.5% in the formal market for households that experience an improvement in financial welfare. Seasonality of income only plays a weakly positive significant role in informal market – suggesting that respondents whose household income is seasonal are likely to participate in the informal markets with a marginal effect of 7.9% increase in probability of participation. The gender of the head of the household and the size of the household does not play an important role in the formal market but play varying roles in the semi-formal and informal markets.

58

In the semi-formal market, the larger the household, the more unlikely the respondent is to participate in the market, with an extra member reducing the probability of participation by 0.4%. In the informal market model, respondents from male-headed households are unlikely to participate in informal markets compared to those from female-headed households, with probability falling by 0.5%. Similarly, the gender of respondent is only statistically significant in the informal market model and the odds are in favour of male respondents with probability falling by 9.3%. Respondents from large households are more likely to participate in informal financial markets, with an extra member increasing probability by 0.7%. Table 45: Probit Regression Marginal Effects – Participation in Financial Market Segments

Variables Formal Semi-formal Informal dF/dx Z dF/dx z dF/dx z

Financial literacy index Monthly income (K’000) Better-off financially than a year ago (0/1) Seasonal income (0/1) Male headed household (0/1) Household size Male respondent (0/1) Married respondent – monogamous (0/1) Married respondent – polygamous (0/1) Married respondent – informal union (0/1) Age of respondent (years) Age-squared of respondent (years) Primary (1-5) education (0/1) Primary (6-8) education (0/1) Secondary (1-2) education (0/1) Secondary (3-4) education (0/1) Tertiary education (0/1) Employed – formal sector (0/1) Employed – informal sector (0/1) Self-employed (0/1) Urban – cities (0/1) Urban – district towns (0/1) Peri-urban (0/1)

0.0170 0.0007 0.0348

-0.0494 0.0329 0.0007

-0.0065 0.0169

-0.0100 -0.0291 0.0088

-0.0001 0.0358 0.1289 0.2298 0.3703 0.6396 0.2766

-0.0065 -0.0069 0.1316 0.1349 0.0577

4.40a 1.47

2.95a -1.62 2.00 0.28

-0.58 1.05

-0.38 -0.90 4.59a

-3.53a 1.75c 5.06a 5.46a 8.03a 9.76a 5.13a -0.26 -0.45 5.29a 3.01a 1.98b

0.0091 0.0001 0.0138 0.0169 0.0137

-0.0037 -0.0122 -0.0109 -0.0009 -0.0102 0.0017 0.0000

-0.0156 -0.0070 -0.0003 -0.0087 -0.0180 0.1296 0.0200 0.0338

-0.0368 0.0150

-0.0187

3.59a 2.04b 1.77c 1.21 1.25

-2.12b -1.64 -0.93 -0.05 -0.49 1.38

-1.49 -1.74c -0.71 -0.02 -0.66 -1.04 2.96a 0.75

3.88a -5.32a

0.61 -1.46

0.0080 0.0000 0.0163 0.0785

-0.0539 0.0070

-0.0640 0.0934 0.0828 0.0383 0.0081

-0.0001 0.0357 0.1251 0.1130 0.0810

-0.0675 0.1293 0.1233 0.0606 0.0635 0.0367 0.0066

1.40 0.00 0.92

1.91c -1.86c 1.74c

-3.39a 3.57a 2.04b 0.61

2.96a -3.63a

1.54 5.10a 3.43a 2.31b -1.12 2.86a 2.96a 2.41b 2.36b 0.69 0.17

Number of observations Wald chi-squared Prob> chi-squared Pseudo R-squared

4922 751.97

0.000 0.3291

4922 81.57 0.000

0.0370

4922 169.99

0.000 0.0295

Note: For dummy variables dF/dx is for discrete change of dummy variable from 0 to 1. Superscripts a, b and c represent statistically significant at 1%, 5% and 10% levels, respectively.

Marital status variables are only statistically significant in the informal market model. Married respondents, whether monogamous or polygamous, are likely to participate in informal financial markets compared to respondents that are not married. The marginal effects are modest with the probability of participating in informal financial markets increasing by 9.3% and 8.3% for married-monogamous and married-polygamous, respectively. Otherwise, marital status does not play a statistically significant role in adult’s participation in formal and semi-formal financial sectors. The age of the respondent has inverted u-shape effects on the probability of participating in the formal and informal market but the marginal effects on the probability of participation are minor. Education is positively associated with participation in the formal and informal market. In the formal market all the education marginal effects are positive and statistically significant at the 1 percent level from upper primary education. More interesting is the increase in the marginal

59

effects in terms of ‘the higher the level of education’ compared to ‘no education’. For instance, having lower primary school education increases the probability by 3.6% compared to having tertiary education where the probability of participating in the formal financial system increases by 64%. The opposite anecdote is evident in the informal market in which the positive marginal effects of education falls as the education level increases, with tertiary education being negatively associated with informal market participation. The nature of employment has varying effects. In the formal market, only the marginal effects of formal sector employment are statistically significant at the 1 percent level. The marginal effects show that switching from being unemployed to being employed in the formal sector increases the probability of participating in the formal financial sector by 27.7%. This high marginal effect is likely to be a result of the fact that a majority of formal sector employees are paid their salaries through the formal banking systems and tend to have no alternative but open a bank account. For semi-formal and informal markets, formal employment and self-employment are both positively associated with participation in these markets but the marginal effects range from 3.6% to 12.9%. The residential status also matters, with city residents being more likely to participate in formal financial markets and informal market, but less likely to participate in semi-formal markets. The probability of participating in formal financial markets increases by 13.2% and that of participating in informal markets (increases) by 6.4%, much lower than for formal markets; and it falls by 3.7% in the semi-formal market. Residing in district towns and peri-urban areas is only statistically significant in the formal market model, with probability increasing by 13.5% and 5.8%, respectively. District towns and peri-urban residential status does not affect participation in the semi-formal and informal markets. Table 46 reports marginal effects of socio-economic characteristics of adult respondents on the revealed demand for bank accounts and bank loans. Both models are validated by the statistically significant Wald Chi-squared at the 1% level. The revealed demand for bank accounts is positively associated with the financial literacy index, and the marginal effects are statistically significant at the 1% level. The probability of revealing the demand for bank accounts increases by 4.2% for any additional correct answer to the financial literacy questions. Among the household income variables, monthly household incomes and households whose financial position was better-off were more likely to have respondents that revealed demand for a bank account, with marginal effects on probability at 0.4% and 5.4%, respectively. Household size and age of respondent are also positively associated with probability of revealing loan demand and the marginal effects are statistically significant. Education also plays an important role with all education marginal effects being positive associated with revealed demand for bank accounts and being statistically significant at the 1% level. There is also an increasing trend of the marginal effects from 12% increase in the probability of revealed demand in switching from no education to lower primary school education to 66.2% increase in probability in switching from no education to tertiary education. Revealed demand for bank accounts is also higher among those in formal employment than in those who are unemployed. Switching from unemployment to formal employment increases the probability of revealing demand for a bank account by 25.5%. The probability of revealing demand for a bank account also significantly increases among city and district town residents compared to rural residents.

60

Table 46: Probit Regression Marginal Effects – Bank Account and Bank Loan Potential Demand

Variables Bank Account Bank Loan dF/dx z dF/dx Z

Financial literacy index Monthly income (K’000) Better-off financially than a year ago (0/1) Seasonal income (0/1) Male headed household (0/1) Household size Male respondent (0/1) Married respondent – monogamous (0/1) Married respondent – polygamous (0/1) Married respondent – informal union (0/1) Age of respondent (years) Age-squared of respondent (years) Primary (1-5) education (0/1) Primary (6-8) education (0/1) Secondary (1-2) education (0/1) Secondary (3-4) education (0/1) Tertiary education (0/1) Employed – formal sector (0/1) Employed – informal sector (0/1) Self-employed (0/1) Urban – cities (0/1) Urban – district towns (0/1) Peri-urban (0/1)

0.0416 0.0043 0.0535 0.0413 0.0587

-0.0039 0.0537 0.0157 0.0178 0.0129 0.0131

-0.0001 0.1196 0.1942 0.2920 0.3537 0.6624 0.2550 0.0330 0.0197 0.1402 0.0928 0.0440

7.44a 7.56a 3.17a 1.13

2.16b -1.02 2.95a 0.63 0.42 0.21

4.50a -4.24a 4.45a 6.68a 7.24a 8.73a

12.94a 4.26a 0.76 0.81

4.95a 1.71c 1.06

0.0029 0.0001 0.0183 0.0060 0.0127

-0.0026 0.0290 0.0052 0.0030 0.0022 0.0075

-0.0001 0.0120 0.0317 0.0683 0.0609 0.0407 0.0389

-0.0178 -0.0080 0.0142

-0.0318 0.0250

1.10 2.10b 2.27b 0.38 0.97

-1.49 3.21a 0.43 0.15 0.07

5.05a -5.04a

0.91 2.08b 2.73a 2.55b 1.23 1.57

-1.24 -0.66 1.15

-2.94a 1.37

Number of observations Wald chi-squared Prob> chi-squared Pseudo R-squared

4922 753.45

0.000 0.2557

4922 182.58

0.000 0.0815

Note: For dummy variables dF/dx is for discrete change of dummy variable from 0 to 1. Superscripts a, b and c represent statistically significant at 1%, 5% and 10% levels, respectively.

With respect to revealed demand for a bank loan, the evidence suggests that financial literacy does not play a statistically significant role. The role of income is marginal, with a MK1 000 increase in monthly household income leading to only 0.01% increase in probability of revealing demand for a bank loan while being better-off financially leading to 1.8% increase in probability. Male respondents are likely to reveal demand for a bank loan compared to female respondents, while age also plays a statistically significant role. The impact of education on revealed demand for a bank loan is variable with upper primary education and secondary education being statistically significant at 5% level. The marginal effects on the probability of revealing demand for a bank loan ranges from 3.2% among upper primary school educated respondents to 6.8% among lower secondary school educated respondents. The revealed demand for a bank loan also diminishes if adults live in district towns compared to those that live in rural areas.

61

6. Money Management Practices in Malawi

Money management covers aspects of budgeting, savings behaviour, debt levels and management of debt. The main objective of the questions in money management is to understand how people manage their day-to-day money such as planning spending, spending on food and necessary items, keeping track of spending, borrowing, general money management. The respondents were answering the questions on financial planning for themselves and their households or for themselves as individuals. Overall, 92.2% of adult Malawians answered for both their household and personal spending and 7.8% of respondents answered for their personal spending. The analysis also investigates the association between key money management behaviours and socio-economic characteristics and the role played by financial literacy. 6.1 Budgeting and Planning Budgeting and planning is one of the financial skills necessary for prudent spending of resources and can help ensuring that consumers do not spend beyond their means. The baseline survey asked respondents about the extent to which they plan the use of money in a typical year, the frequency of planning, the nature of spending plans and the extent to which they abide by the plans. Table 47 shows the extent of budgeting and planning among consumers in Malawi and in different population segments. Overall, the survey reveals that 91.4% of adult Malawians plan the use of money when they receive money. The differences between population segments are not substantial, although the highest proportion of adult respondents that plan are in urban-district towns (96.1%) and the lowest are in the rural areas (90.9%). However, of those who plan the use of money, only 46.9% of adult Malawians always plan when they receive money, with the highest proportion of 60.4% observed among respondents in peri-urban areas. There is also high incidence among adult Malawians to abide by their financial plan, with 78.9% of those that plan their use of money following their plan. The highest proportion of keeping to the plan is observed among adults in district towns (94.5%). However, the extent to which adult Malawians always keep to the plan is low, with only 43% always keeping to the plan compared to 56.7% who sometimes keep to the plan.

62

Table 47: Proportion Budgeting and Planning Use of Money (%)

Indicators Urban - cities

Urban – district towns

Peri - urban

Rural Malawi

Planning Use of Money

Yes No Don't Know Refused

N

93.24

6.76 - -

659

96.12

3.88 - -

140

92.75

7.25 - -

200

90.85

9.12 0.03 0.01 4,000

91.44

8.54 0.01 0.01 4,999

Frequency of Planning

Always Sometimes

N

55.37 44.63 617

47.97 52.03 135

60.36 39.64 185

44.53 55.47 3,628

46.87 53.13 4,565

Nature of Planning

Exactly Rough plan Don't Know

N

50.90 49.10

- 617

61.56 38.44

- 135

56.46 43.54

- 185

46.86 53.13

0.01 3,628

48.42 51.57

0.01 4,565

Whether Keep to the Plan

Yes No

N

78.32 21.68 617

94.52

5.48 135

77.34 22.66 185

77.96 22.04 3,628

78.60 21.40 4,565

Frequency of Keeping to Plan

Always Sometimes Don't Know Refused

N

52.22 47.78

- -

483

44.22 53.87

- 1.91 125

54.13 45.87

- -

146

40.78 58.99

0.06 0.17 2,858

43.08 56.65

0.04 0.22 3,612

Source: Financial Literacy Baseline Survey 2013 The survey revealed that among adults responsible for household spending and those responsible for their own personal spending, 91.9% and 86.1%, respectively, plan for use of money they receive. Figure 19 shows the proportion of adult Malawians that plan the use of the money received by socio-economic groups of respondents. Panel (a) shows differences in planning for use of money depending on the age group of the respondents, showing an inverted u-shape with those over 64 years. There are also gender differences in terms of head of households, with 92.7% of respondents coming from male-headed households compared to 85.9% of respondents coming from female-headed households (Panel (b)). The differences based on gender of respondents are, however, not substantial.

63

Figure 19: Proportion Planning Use of Money by Socio-economic Groups (%)

Source: Financial Literacy Baseline Survey 2013

Panel (c) shows differences in planning for use money with respect to highest levels of education, with the proportion of those that plan increasing with the level of education especially between no schooling and upper primary. The differences in planning among adults with upper primary and higher levels of education are not substantial. Panel (d) shows that planning is associated with the nature of employment. Planning for use of money is highest among adults in formal employment (95.4%) compared to adults who are unemployed (85.1%).

93.0 93.8 91.6 92.6 95.0 95.9 92.688.7 85.1

77.9

0.0

20.0

40.0

60.0

80.0

100.0

120.0

Pe

rce

nt

a) Age of Respondent

92.71

85.86

92.57

90.66

82.0

84.0

86.0

88.0

90.0

92.0

94.0

Pe

rce

nt

b) Gender

86.1

89.5

93.5 93.6

95.5 95.3

80.0

82.0

84.0

86.0

88.0

90.0

92.0

94.0

96.0

98.0

Pe

rce

nt

c) Education of Respondent96.4

92.5 92.3

85.1

78.0

80.0

82.0

84.0

86.0

88.0

90.0

92.0

94.0

96.0

98.0

Pe

rce

nt

d) Employment

64

6.2 Savings Behaviour One of the problems of low income countries such as Malawi is that the savings rates are low, leading to problems in private investments. The baseline survey sought to establish the extent to which adult Malawians are able to save, i.e. whether they ever have any money left over after paying for food and other basic necessities. Table 48 shows the extent of savings by different population segments. Overall, 76.2% of adult Malawians indicated that they have some money left after paying for basic needs, although only 18.1% of these had regular savings. The lowest savings rates are experienced among rural adults, with the smallest proportion of saving regularly. Table 48: Proportion Saving and Frequency of Saving (%)

Indicators Urban - cities

Urban – district towns

Peri - urban

Rural Malawi

Saves Some Money

Yes No Don't Know

N

81.14 18.66

0.2 659

83.24 16.76

- 140

84.86 15.14

- 200

74.54 25.46

- 4,000

76.21 23.76

0.03 4,999

Frequency of Savings

Regularly Sometimes Don't Know Refused

N

27.09 72.91

- -

530

25.92 74.08

- -

120

25.59 73.46

0.21 0.73 171

15.57 84.23

0.02 0.17 2,959

18.10 81.70

0.03 0.17 3,780

Source: Financial Literacy Baseline Survey 2013 Figure 20 shows the proportion that saves some money after spending on basic necessities by socio-economic groups. There is a higher proportion saving among young adults compared to that among the elderly. The 25-34 years age groups have the highest proportions of adults that save some money but the proportion that saves some money declines consistently from the 35-39 years age group, with only 65.6% of the over-64-year olds saving some moneys after paying for basic needs. A higher proportion of adult males tend to save more compared to the proportion of adult females. With respect to highest education level education, there is an increasing trend in the proportion of adults saving as the number of years of schooling increases from 66.8% among those with no education to 88.4% among those with tertiary education. An interesting picture emerges with respect to the nature of employment, with the proportion saving being high among those in formal employment and those unemployed and lowest among those in informal employment.

65

Figure 20: Proportion that Save some Money by Socio-economic Groups (%)

Source: Financial Literacy Baseline Survey 2013 Figure 21 shows what adult Malawians do with the money that is left over after paying for food and other basic necessities. The most important use of the left over money is to save/keep for future food and basic necessities requirements (74.6%) and followed by save/keep for unforeseen expenditures (52.9%). The next two uses are spending on buying non-essential items and investing money in business or farming. Only 27.2% of those that had left over money kept the money to meet known major expenditures such as buying farm inputs or paying farm workers. There is also a non-negligible proportion (14.9%) that sent money to family members and provided help to others (remittances). Saving money for children’s education is not a common saving behaviour as only 10% of adults revealed doing so with the left over money. Similarly, not many adults save money for their own or spouse’s education.

75.980.9 80.7 79.4 79.0

73.4 71.6 70.7 68.965.6

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

Perc

en

t

a) Age of Respondent

78.3

67.1

80.673.2

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

Pe

rce

nt

b) Gender

66.872.5

77.682.2

85.9 88.4

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0

Pe

rce

nt

c) Education of Respondent

86.4

72.0

77.1

85.1

60.0

65.0

70.0

75.0

80.0

85.0

90.0

Pe

rce

nt

d) Employment

66

Figure 21: Uses of Left-over Money (%)

Source: Financial Literacy Baseline Survey 2013 The most typical method for keeping money left over after paying for basic necessities for adults that saved or kept some money is to keep cash at home or a secret hiding place practised by 74.6% of adults that saved money (Figure 22). Only 19.9% of adults who saved kept the savings at a bank (own account or other members account)5, and 14.3% saved at an informal savings and credit group. The low proportion that saves at a bank and another finance organisation reflects the supply-side constraints in the formal banking industry. Although in recent times the formal banking system is reaching out to district towns and peri-urban areas, the proportion of adults that save at formal financial institutions is low (20.8%).

5 This is more than 15.4% of adults with bank accounts as observed above because it includes bank accounts of other members of the household since this question was about household expenses and savings.

0.6

0.7

1.2

3.5

3.6

6.0

7.9

10.2

14.9

27.2

48.6

51.4

52.9

74.6

0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0

Keep money for own/spouse's education

Invest money in fixed assets

Repay debts

Others

Lend it to others

Keep money to cover fluctuations in income

Give some money to my church/mosque

Keep money for children's education

Send to family members and provide help to others

Keep money for a known major expenditure

Invest money in business or farming

Spend money on self/ buying non-essentials

Keep money for unforeseen expenditure

Keep money for future food and other necessities

Percent

67

Figure 22: Methods of Savings (%)

Source: Financial Literacy Baseline Survey 2013 Figure 23 presents the most popular reasons why adults that saved money chose different methods of saving. The most popular reason for the saving method is the simplicity in the use of the method to make and utilize savings, a major consideration among 37.5% of adult respondents that saved some money. This is followed closely by convenience to get to the place where savings are made as revealed by 36.6% of adults who saved some money. The other important characteristics of the methods of savings are safety from temptation of spending the money and trustworthy of the savings method. Most of the ‘other’ reasons provided relate to ‘too little money to save’. Although, OPM and Kadale Consultants (2009) did not find a large proportion that mentioned convenience as one of the problems with use of banking services, this baseline survey suggests that simplicity and proximity or nearness to banking services may be key drivers of the choice of the method of savings.

0.0

0.0

0.0

0.4

0.4

0.9

4.0

6.6

6.9

7.3

10.2

14.3

19.9

81.1

0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0

Savings through Treasury bills or bonds

Savings through shares/stock market

Savings with employer

Others

Savings with membership organization

Savings at another finance organization (eg SACCO)

Savings through advance buying of inputs

Savings through keeping stocks for business

Someone else for safe keeping

Savings through keeping livestock

Membership to informal savings group (chipereganyu)

Membership of informal savings and credit group G

Savings at a bank

Keep cash at home

Percent

68

Figure 23: Reasons for Choosing Savings Method (%)

Source: Financial Literacy Baseline Survey 2013

6.3 Adequacy of Money for Basic Needs The baseline survey also explored the adequacy of money among households and individuals to meet the basic food and necessities requirements. Table 49 shows the extent of the problem of inadequacy of money to meet basic food and necessity items among adults by population segments. Overall, 90% of adult Malawians run short of money to meet basic food and necessities requirements, with about 26.8% of these running short of money regularly. This is not surprising given the high poverty incidence in Malawi (NSO, 2012). The situation seems to be worse in rural areas than in urban areas, although lower proportions are evident among adults in urban-district towns. Table 49: Proportion of Adults Running Short of Money (%)

Indicators Urban - cities

Urban – district towns

Peri - urban

Rural Malawi

Run Short of Money?

Yes No Don't Know

N

82.7 17.3

- 659

80.41 19.59

- 140

86.15 13.85

- 200

91.83

8.14 0.02 4,000

89.97 10.01

0.02 4,999

Frequency of Running Short

Regularly Sometimes Don't Know Refused

N

17.3 82.5

- 0.2 552

10.02 89.98

- -

115

21.83 78.17

- -

173

29.14 70.53

0.03 0.3

3,675

26.79 72.92

0.03 0.26 4,515

Source: Financial Literacy Baseline Survey 2013 The main reason most of the adult Malawians run short of money for food and basic necessities is that 64.8% have insufficient or low incomes (Figure 24). This is followed by 39.3% of adults who

0.2

2.3

6.6

6.7

6.9

7.1

7.6

9.4

9.9

26.6

27.0

36.6

37.5

0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0

They understand you

It is convenient to pay in

The service is very good

Others

Safe from relatives/others that want to use it

Savings are hidden from others

It is convenient to withdraw from

It does not cost much to use

It gives the best rate of interest

It is safe or trustworthy

Safe from temptation to spend it

It is convenient to get to

It is simple to use

Percent

69

also attributed inadequacy in money due to fluctuating or unreliable income sources, while 33.6% reported that their problem of money is due to increased cost of food and necessities. The forth important factor is losses in business, reported by 26% of adult respondents. Overspending and failure to plan were reported by just 5% of adults, these low figures are consistent with the high incidence of planning observed above. The problem of insufficient/low income was reported by 52.4%,67.2%, 66.6% and 58.4% of adults in formal employment, informal employment, self-employment and no employment, respectively.

Figure 24: Main Reasons for Running Short of Money for Food and Necessities (%)

Source: Financial Literacy Baseline Survey 2013 Given the high incidence among adult Malawians in running out of money for food and other basic needs, respondents were asked what they do when they run short of money for basic necessities. Figure 25 shows that 63.1% resorted to borrowing from family and friends while 61.1% engaged in ganyu labour to fill the finance gap. The third and fourth most popular strategies reported by 19.2% and 18.7% are distress sale of household assets or livestock and cash gifts from family or friends, respectively. Ganyu labour is a typical coping mechanism for many households, particularly in rural Malawi.

1.4

1.9

2.8

5.0

5.1

7.9

10.0

10.6

10.8

26.0

33.6

39.3

64.8

0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0

Need to repay debt

Others (mainly poor harvest)

Looking for work

Failure to plan ahead/budget

Overspending

Have to provide financial help to others

Unexpected expenses/events

Unable to work

Expected expenses

Business losses

Increased cost of food and necessities

Fluctuating/unreliable income

Insufficient/low income

Percent

70

Figure 25: Coping Mechanisms when Running Short of Money for Food and Necessities (%)

Source: Financial Literacy Baseline Survey 2013 6.4 Debts and Debt Management In an environment where income is insufficient for a large proportion of the population, the debt burden can be worrisome. Overall, 70.2% of adult Malawians ever use credit or borrow money to buy food or pay for basic necessities because they had run short of money (Table 50). There is high incidence of borrowing money to purchase food and other basic necessities in the urban areas compared to peri-urban and rural areas, although in the rural areas people tend to borrow more regularly than in the urban and peri-urban areas. Table 50: Proportion of Adults Borrowing Money to Buy Food and Basics (%)

Indicators Urban - cities

Urban – district towns

Peri - urban

Rural Malawi

Ever Borrow Money?

Yes No

N

73.46 26.54 659

71.41 28.59 140

66.49 33.51 200

69.86 30.14 4,000

70.21 29.79 4,999

Frequency of Borrowing

Regularly Sometimes Refused

N

6.2

93.73 0.06 490

2.73

97.27 -

105

3.15

96.85 -

142

7.64

92.23 0.14 2,786

7.06

92.83 0.12 3,523

Source: Financial Literacy Baseline Survey 2013 The analysis of incidence of borrowing money to buy food and basic necessities by socio-economic groups show an inverted u-shape trend with respect to age of the respondent (Figure 26). There is also high incidence of borrowing among respondents from male-headed (71.6%) compared to respondents living in female-headed households (64.3%), suggesting some risk

0.5

1.0

1.6

2.0

3.6

4.0

4.7

6.8

8.6

9.8

13.8

18.7

19.2

61.1

63.1

0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0

Borrow from bank/use credit card/go into overdraft

Spend less on non-essentials (e.g. spending on G

Borrow from employer/salary advance

Borrow from a local moneylender (e.g. katapila)

Other (mainly selling produce)

Buy on credit (informally) from shops

Go without expensive food items such as meat

Spend less on essentials/ necessary items (e.g. food)

Borrow from a community social fund or informal G

Find extra work/work extra hours

Use savings

Cash gifts from family or friends

Sell assets such as household items or livestock

Ganyu

Borrow from family, friend or work colleague

Percent

71

averse behaviour among female-headed households in contracting debt to support food consumption. However, there are no major differences in terms of the gender of the respondents.

Figure 26: Proportion that Ever Borrow Money by Socio-economic Groups (%)

Source: Financial Literacy Baseline Survey 2013 The relationship between contracting debt for food consumption is not clear cut in terms of education, although the highest proportion is observed amongst respondents whose highest level of schooling is upper secondary school. With respect to nature of employment of adult Malawians, those in formal and informal employment are more likely to borrow money to finance food and other basic necessities than are those unemployed. Only 18.5% of adult Malawians borrow money to pay for debts, with a slightly higher proportion among those living in cities (Table 51). Of those that borrow to bay back debts, a majority do so sometimes, with only 9.4% borrowing money regularly to pay debts. Generally, this shows that the behaviour of borrowing money to pay debts in Malawi is not typical, and if it exists, it is not routine.

68.0

76.672.9 72.3

74.9 76.4

69.465.1 66.9

52.0

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

Pe

rce

nt

a) Age of Respondent

71.6

64.3

70.2 70.2

60.0

62.0

64.0

66.0

68.0

70.0

72.0

74.0

Pe

rce

nt

b) Gender

61.1

68.8

61.1

71.776.9

71.6

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

Pe

rce

nt

c) Education of Respondent

74.079.2

70.9

62.6

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

Pe

rce

nt

d) Employment

72

Table 51: Proportion of Adults Borrowing Money to Pay Debts (%) Indicators Urban -

cities Urban –

district towns

Peri - urban

Rural Malawi

Ever Borrow to Pay Debts?

Yes No Don’t Know

N

19.44 80.56

- 659

13.58 86.42

- 140

13.98 86.02

- 200

18.8

81.17 0.03 4,000

18.46 81.51

0.03 4,999

Frequency of Borrowing

Regularly Sometimes Refused

N

6.58

93.02 0.39 129

-

100.00 -

20

11.73 88.27

- 35

10.03 89.97

- 755

9.36

90.59 0.05 939

Source: Financial Literacy Baseline Survey 2013 Table 52 shows the proportion of adults that have to repay any money that they have borrowed (current debt obligations) by population segments. Overall, 33.0% of adult Malawians have debt obligations. There are differences depending on population segments; with the highest proportion (38.6%) having debt obligations observed among those living in urban areas (cities and district towns) and the lowest observed among those living in rural areas (31.7%). Although the proportion that borrows to purchase food and basic necessities is high, the proportion with current debt obligations is much lower.

Table 52: Proportion of Adults Who Have to Repay Borrowed Money (%)

Indicators Urban - cities

Urban – district towns

Peri - urban

Rural Malawi

Repay Borrowed Money?

Yes No Don’t Know Refused

N

38.4 61.6

- -

659

38.56 61.44

- -

140

36.34 63.23

0.43 -

200

31.69 68.23

0.06 0.02 4,000

33.03 66.89

0.07 0.01 4,999

Source: Financial Literacy Baseline Survey 2013 About a third of adult Malawians had some kind of debt. The respondents in the baseline survey were asked to state the level of their total debt at the time of the survey and how the debt compared with their monthly income. Table 53 shows that 78.5% of respondents that had some kind of debt had a debt of less than or equal to their monthly income, followed by those whose debts was less than or equal to their annual income, but more than one month’s worth of income (19%). Very few people had debts total more than their annual income, only 2%.

73

Table 53: Percent of Respondents with Debt Level Relative to Income (%) Current Total Debt Urban -

cities Urban –

district towns Peri -

urban Rural Malawi

Less than or equal to monthly income Less than or equal to annual income,

but more than one month’s worth of income

More than annual income Don’t Know Refused

N

76.51 20.51

2.98 - -

259

84.8 13.49

- 0.59 1.12

53

85.34 12.38

1.61 -

0.67 79

78.1 19.46

1.88 0.30 0.26

1,283

78.54 18.98

1.95 0.25 0.28

1,674

Source: Financial Literacy Baseline Survey 2013

The baseline survey also sought to establish the ability to borrow among adults with debt obligations as a self-assessed indicator of borrowing behaviour. Good debt management requires borrowing money for which one can afford to repay without difficulties. Figure 27 shows that about 47.3% of adults in Malawi borrow up to a set limit for which they can afford and 44.2% could afford to borrow more if they wanted. Only 7.8% of adults could borrow more than they could afford, suggesting that Malawians are cautious borrowers and tend to borrow within manageable levels.

Figure 27: Ability to Borrow More for adults that had to Repay any Money (%)

Source: Financial Literacy Baseline Survey 2013 6.5 General Money Management This section explores the general knowledge on money management and the respondents’ own assessment of how they manage their moneys. Most adult Malawians (73.6%) know the amount of money that they personally spent a week before the survey and there are minor differences (Table 54). The proportion that knows exactly how much money they spent in the last week before the survey is also high, as much as 68.9% of adult Malawians that reported that they knew how much

0.08

0.66

7.78

44.21

47.27

0 5 10 15 20 25 30 35 40 45 50

Don't Know

Refused

Could have borrowed more than afford

Could afford to borrow more if wanted

Could have borrowed to our limit

Percent

74

money they had spent. The highest proportion of who exactly knew the amount was higher in district towns, followed by those in the rural areas. Table 54: Proportion of Adults Who Know Amount of Money Spent Last Week (%) Indicators Urban -

cities Urban –

district towns

Peri - urban

Rural Malawi

Know Money Spent Last Week?

Yes No Don’t Know Refused

N

77.30 22.50

0.20 -

659

85.54 14.46

- -

140

77.22 22.78

- -

200

72.24 27.42

0.19 0.14 4,000

73.61 26.10

0.18 0.11 4,999

To What Extent?

Exact Roughly Don’t Know Refused

N

65.48 34.14

0.38 -

524

71.53 28.47

- -

113

64.31 35.69

- -

155

69.68 30.28

- 0.05 2,923

68.91 31.00

0.05 0.03 3,715

Source: Financial Literacy Baseline Survey 2013 Respondents were also asked whether they knew how much money was available for them and their household for day-to-day spending at the time of the survey. Table 55 shows that 71.7% of adult Malawians knew the amount of money available. The proportion was higher in the district towns at 85.1% and lowest among rural respondents at 69.5%. Most of those that reported that they knew the amount of money available also knew exactly how much money was available, with minor differences across population segments. Table 55: Proportion of Adults Who Know Amount of Money Available (%)

Indicators Urban - cities

Urban – district towns

Peri - urban

Rural Malawi

Money Availability Known?

Yes No Don’t Know Refused

N

81.14 18.52

0.17 0.17 659

85.14 14.86

- -

140

72.94 26.42

- 0.64 200

69.52 30.15

0.28 0.05 4,000

71.74 27.93

0.24 0.1

4,999

To What Extent?

Exact Roughly Don’t Know Refused

N

75.15 24.85

- -

553

75.34 24.66

- -

113

70.67 29.33

- -

145

72.66 26.99

0.13 0.22 2,799

73.04

26.7 0.1

0.17 3,613

Source: Financial Literacy Baseline Survey 2013 Table 56 presents self-assessment by respondents of their money management ability across population segments. Two statements were posed to them to agree or disagree on how disciplined they are in managing money or whether they learn from other people’s mistakes. Overall, the baseline survey shows that 79.1% of adult Malawians agreed strongly that they are more disciplined in managing money. Interestingly, the proportion that agreed strongly that they are disciplined is lowest among the urban-cities population and highest among the district town populations. At the same time, most Malawians agree strongly to the statement that they learn

75

from the mistakes of other people in managing their money, about 65.8%, with rural people learning less from others. Table 56: Overall Self-Assessment of Money Management (%) Indicators Urban -

cities Urban –

district towns

Peri– urban Rural Malawi

“I am very disciplined in managing

money”

Strongly agree Agree to some extent Disagree to some extent Strongly disagree Don’t Know

N

77.38 18.33

1.92 2.29 0.09 659

86.38 11.32

1.47 0.83

- 140

81.72 14.77

1.48 1.39 0.63 200

78.87 16.75

2.76 1.54 0.08 4,000

79.09 16.67

2.54 1.6 0.1

4,999

“I learn from mistakes others make

in managing their money”

Strongly agree Agree to some extent Disagree to some extent Strongly disagree Don’t Know Refused

N

73.97 14.96

3.43 7

0.64 -

659

81.69 13.44

1.32 3.54

- -

140

73.1 16.7 2.22 7.97

- -

200

64.5 17.85

6.2 11.24

0.09 0.12 4,000

66.75 17.27

5.47 10.26

0.15 0.09 4,999

Source: Financial Literacy Baseline Survey 2013 Table 57 presents the proportion of respondents with respect to their purchasing behaviour by population segments. The baseline survey reveals that only17% of adult Malawians regularly or sometimes buy unnecessary things before buying food and other basic necessities, with 36.8% doing so rarely and 46.2% never engaging in such behaviour. There seems to be differences across population segments, with lower proportions of never buying unnecessary items reported among those resident in cities, and higher proportions among those in the rural areas. On the question whether people buy unnecessary things even when they cannot afford them, Table 19 shows that this happens from regularly to rarely among 35.5% of respondents while 64.4% never engage in such behaviour. As is the case with the question of buying unnecessary items before food, the proportion of those that never buy unnecessary items even when they cannot afford is higher in peri-urban and rural areas than among those living in cities and district towns. These figures suggest that Malawians are more prudent in their purchasing behaviour. These self-assessments are consistent with a high proportion of Malawians that plan their use of money as observed above.

76

Table 57: Overall Self-Assessment of Purchasing Behaviour (%)

Indicators Urban - cities

Urban – district towns

Peri - urban

Rural Malawi

Buying unnecessary things before

buying food & necessities

Regularly Sometimes Rarely Never Don’t Know Refused

N

6.79 15.04 40.68 37.49

- -

659

1.00 20.55 35.35 43.10

- -

140

6.53 12.12 31.55 49.80

- -

200

2.29 13.63 36.52 47.51

0.03 0.02 4,000

3.03 13.98 36.77 46.18

0.02 0.02 4,999

Buying unnecessary things even

when you can't afford them

Regularly Sometimes Rarely Never Don’t Know Refused

N

1.69 7.12

33.30 57.78

- 0.11 659

2.04 9.59

27.24 61.12

- -

140

- 3.47

27.08 69.45

- -

200

0.78 8.47

25.28 65.35

0.09 0.02 4,000

0.90 8.09

26.47 64.43

0.07 0.03 4,999

Source: Financial Literacy Baseline Survey 2013 Table 58 shows the proportion of adult Malawians with different levels of confidence in their ability to manage their money or finances by population segments. Overall, 55.8% of adults reported that they were very confident in their ability to manage their money or finances. The level of confidence was highest among those living in district towns (66.4%) and peri-urban areas (64.1%) and lowest among those living in four major cities (53.4%). The proportion not at all confident in their ability to manage finances is highest in the rural areas (2.5%) and lowest in peri-urban areas (0.1%). Table 58: Proportion of Adults with Confidence in Managing Money/Finances (%)

Indicators Urban - cities

Urban – district towns

Peri - urban

Rural Malawi

Very confident Somewhat confident Not at all confident Don’t Know Refused

N

53.39 45.85

0.69 -

0.07 659

66.40 33.32

0.29 - -

140

64.16 35.45

0.14 -

0.24 200

55.19 42.06

2.47 0.02 0.25 4,000

55.80 41.92

2.05 0.02 0.22 4,999

Source: Financial Literacy Baseline Survey 2013 Figure 28 shows a somewhat inverted u-shape relationship between age and being very confident in the ability to manage finances, with those more than 59 years old recording a below 50% ‘very confident’ level and the 16-24 year olds recording 51.7%. There are also clear differences in terms of gender of respondents, with 61.7% of male adults compared to 51.7% of female adults feeling very confident in their ability to manage their finances. The highest level of schooling is also positively related to the extent of being very confident in the ability to manage their finances. Similarly, a higher proportion of adults in formal employment are very confident than adults who are unemployed in their ability in managing their finances.

77

Figure 28: Proportion Very Confident in Managing Money by Socio-economic Groups (%)

Source: Financial Literacy Baseline Survey 2013

6.6 Determinants of Budgeting and Savings Behaviour Multivariate analysis is employed to explore the factors that influence the various behavioural aspects in the management of money and finances. The multivariate analysis seeks to determine factors that are associated with the probability of money management behaviour occurring among adult Malawians. Owing to the binary (latent) nature of the dependent variables, probit regression models are used with appropriate weights and marginal effects are obtained for the probability of the event occurring. The following is the general specification of the model ���� = � + ���� + ��� + ���� + ��� + �� + � (3) where MMI is a vector of money management behavioural indicators, FLI is a vector of financial literacy indicators, HHW is a vector of household wealth and welfare indicators, HHC is a vector of household characteristics, REC is a vector of respondent characteristics, X is a vector of other control variables, and μ is the error term. Four indicators of money management behaviour are developed as dependent variables in the multivariate regression analysis. First, is planning behaviour which is captured by the incidence of planning. The incidence of planning is measured by a dummy variable equal to 1 if the respondent plans how to use money; otherwise it is equal to zero. Second, is likelihood of maintaining savings which is measured by a dummy variable equal to 1 if the respondent saved some money left after spending on food and other basic necessities; otherwise it is equal to zero. Third, is the incidence of debt obligations which is measured by a dummy equal to 1 if the respondents reported that they currently have to repay any money that they had borrowed, otherwise it is equal to zero. Fourth, is the indicator of overall confidence in the ability to manage money or finance and is

51.7

56.2 57.7

62.1

56.358.8

62.0 61.1

48.2 47.4

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

Pe

rce

nt

a) Age of Respondent

56.4

53.3

61.7

51.7

46.0

48.0

50.0

52.0

54.0

56.0

58.0

60.0

62.0

64.0

Perc

en

t

b) Gender

50.854.6 54.8

61.8 60.064.6

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

Pe

rce

nt

c) Education of Respondent

69.1

54.9 56.4

48.7

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

Pe

rce

nt

d) Employment

78

measured as a dummy equal to 1 if the respondent revealed very high confidence in money management. The explanatory variables include financial literacy index, household income and financial wellbeing, gender of household head, household size, age of respondent, marital status of respondent, highest level of education of respondent, nature of employment and population segments as defined under equation (1) above. In the model for planning we also control for whether the respondent was answering for personal and household spending with a dummy equal to 1, zero if answering for personal spending. Table 59 presents marginal effects from a probit regression model on the factors associated with incidence of planning the use of money by adult Malawians. Model 1excludes the financial literacy index while Model 2 includes the financial literacy index. The results show that planning the use of money is not statistically associated with degree of financial literacy. The level of income is not associated with planning the use of money, but those households whose financial position was better off than a year ago and those whose income was seasonal were more likely to plan the use of money. Seasonality in income increases the probability of planning the use of money by 5.2% while improving financial wellbeing increases the probability of planning money use by 2.9%. The other factor that is significantly associated with planning use of money is education, particularly from upper primary to senior secondary education compared with no education. While upper primary education increases the probability of planning use of money by 3.3%, the impact of secondary education is higher with probability increasing by at least 5.45%. The nature of employment also plays a part, with marginal effects being between 7.3% for self-employment and 3.9% for those employed in the informal sector. Confirming earlier observations, adults living in urban-district towns are more likely to plan for the use of money than those in the rural areas.

79

Table 59: Probit Regression Marginal Effects – Planning Use of Money

Variables Model 1 Model 2 dF/dx z dF/dx Z

Financial literacy index Monthly income (K’000) Better-off financially than a year ago (0/1) Seasonal income (0/1) Male-headed household (0/1) Household size Male respondent (0/1) Married respondent – monogamous (0/1) Married respondent – polygamous (0/1) Married respondent – informal union (0/1) Age of respondent (years) Age-squared of respondent (years) Primary (1-5) education (0/1) Primary (6-8) education (0/1) Secondary (1-2) education (0/1) Secondary (3-4) education (0/1) Tertiary education (0/1) Employed – formal sector (0/1) Employed – informal sector (0/1) Self-employed (0/1) Household spending (0/1) Urban-cities (0/1) Urban-district towns (0/1) Peri-urban (0/1)

- 0.0001 0.0293 0.0521 0.0302 0.0045 0.0000

-0.0138 -0.0075 -0.0192 0.0002 0.0000 0.0194 0.0327 0.0549 0.0544 0.0325 0.0553 0.0393 0.0729 0.0685

-0.0035 0.0406

-0.0120

- 0.50

3.43a 1.86c 1.70c 2.15c 0.00

-0.99 -0.30 -0.45 0.14

-1.29 1.92c 3.11a 5.81a 5.29a 1.39

4.48a 2.94a 4.50a 2.18b -0.23 2.17b -0.49

0.0015 0.0001 0.0291 0.0519 0.0299 0.0045

-0.0004 -0.0137 -0.0070 -0.0202 0.0001 0.0000 0.0193 0.0322 0.0543 0.0537 0.0311 0.0551 0.0392 0.0726 0.0687

-0.0041 0.0405

-0.0122

0.50 0.49

3.39a 1.86c 1.69c 2.13b -0.04 -0.98 -0.29 -0.47 0.09

-1.21 1.91c 3.05a 5.68a 5.09a 1.29

4.45a 2.93a 4.50a 2.18b -0.27 2.16b -0.50

Number of observations Wald chi-squared Prob> chi-squared Pseudo R-squared

4921 187.43 0.0000 0.0827

4921 187.74 0.0000 0.0828

Note: For dummy variables dF/dx is for discrete change of dummy variable from 0 to 1. Superscripts a, b and c represents statistically significant at 1%, 5% and 10% levels, respectively.

Table 60 presents marginal effects from probit regression model on the probability of making savings from the money left over after buying food and other necessary items. Introduction of the financial literacy index changes the significance of senior secondary school and tertiary education effects although the relationship remains positive. Focusing on Model 2, the results show that people with higher scores on literacy are more likely to save, and an additional score on basic financial literacy questions leads to a 2.1% increase in the probability that the household will save some money. All the income indicators are statistically significant at the 1% level. Nonetheless, the marginal effects of monthly income is substantial, with an increase in income by MK1 000 only leading to 0.2% increase in the probability of savings. More importantly households that revealed that they were better-off financially than a year ago were more likely to save, and improvements in financial position (from no change and worse off) leads to 9% increase in the probability of saving some money. The results also suggest that households whose income is seasonal are more likely to same money for future use possibly supporting the future consumption smoothing argument. The impact is substantial, with seasonality of income increasing the probability of savings by 14.5%. Household size is inversely related to the probability of saving some money and the results show that an extra member of the household decreases the probability of savings by 0.7%.

Compared to respondents that are unmarried, married monogamous/polygamous respondents are more likely to save but married – informal union respondents are less likely to save some money for future use. The results suggests that being married in an informal union reduces the

80

probability of savings by 16.8%, this may be due to lack of long-term commitments to such types of marriages. Table 60: Probit Regression Marginal Effects – Savings Behaviour Variables Model 1 Model 2

dF/dx z dF/dx Z Financial literacy index Monthly income (K’000) Better-off financially than a year ago (0/1) Seasonal income (0/1) Male-headed household (0/1) Household size Male respondent (0/1) Married respondent – monogamous (0/1) Married respondent – polygamous (0/1) Married respondent – informal union (0/1) Age of respondent (years) Age-squared of respondent (years) Primary (1-5) education (0/1) Primary (6-8) education (0/1) Secondary (1-2) education (0/1) Secondary (3-4) education (0/1) Tertiary education (0/1) Employed – formal sector (0/1) Employed – informal sector (0/1) Self-employed (0/1) Saved as a child (0/1) Urban-cities (0/1) Urban-district towns (0/1) Peri-urban (0/1)

- 0.0016 0.0892 0.1443

-0.0087 -0.0066 0.0236 0.0883 0.1008

-0.1539 0.0039

-0.0001 0.0278 0.0434 0.0836 0.0558 0.0843 0.0559 0.0042 0.0643 0.0853

-0.0155 0.0604 0.0566

- 2.78a 5.86a 3.48a -0.34

-1.92c 1.41

3.63a 3.38a

-2.52b 1.69

-2.14b 1.43

2.07b 3.18a 1.97b 1.70c 1.34 0.11

2.81a 6.14a -0.59 1.42

1.71c

0.0211 0.0016 0.0865 0.1453

-0.0100 -0.0071 0.0175 0.0896 0.1038

-0.1678 0.0029 0.0000 0.0269 0.0367 0.0719 0.0375 0.0624 0.0518 0.0039 0.0621 0.0815

-0.0216 0.0577 0.0571

4.23a 2.71a 5.66a 3.51a -0.39

-2.07b 1.04

3.67a 3.50a

-2.71a 1.25

-1.60 1.39

1.74c 2.64a 1.27 1.17 1.22 0.10

2.73a 5.86a -0.81 1.35

1.72c Number of observations Wald chi-squared Prob> chi-squared Pseudo R-squared

4922 256.2 0.000

0.0639

4922 272.12

0.000 0.0674

Note: For dummy variables dF/dx is for discrete change of dummy variable from 0 to 1. Superscripts a, b and c represent statistically significant at 1%, 5% and 10% levels, respectively.

Although all education variables are positively associated with savings behaviour, only upper primary school and junior secondary school marginal effects are statistically significant with a peak at junior secondary school level (increasing probability by 7.2%). With respect to the nature of employment, compared to the unemployed, the only statistically significant marginal effect is found among self-employed adult respondents and leads to a 6.2% increase in the probability of savings. There is also evidence that childhood savings behaviour is positively associated with savings behaviour of adults with the marginal effects being statistically significant at the 1% level. This suggests that saving as a child increased the probability of savings by 8.2%. The probability of savings is higher in peri-urban areas than in rural areas while it is lower in urban-cities than in rural areas. As noted above, about a third of adult Malawians had current debts that they were expecting to pay. Table 61 presents marginal effects of factors associated with current debt obligations. As can be seen from the results, inclusion of the financial literacy index does not change the significance and signs of other variables, except for monthly income. Financial literacy is positively associated with the probability of having a current debt obligation but the impact is to raise the probability by 1.9%. Respondents from households with higher monthly incomes and those that were better-off financially are unlikely to have current debts although the marginal effects are small 0.02% for

81

income, and 3.4% for being financially better-off. The results, however, show that seasonality of household income increases the probability of having current debt obligations by 7.1% and the coefficient is statistically significant at the 5% level. Such respondents may be borrowing to smooth their consumption in periods of low income. The evidence also suggests that male-headed households are less likely to have current debt obligations; hence female-headed households are more likely to have debt obligations. Male respondents were also unlikely to have current debt obligations compared to female respondents. Table 61: Probit Regression Marginal Effects – Current Debt Obligations

Variables Model 1 Model 2 dF/dx z dF/dx Z

Financial literacy index Monthly income (K’000) Better-off financially than a year ago (0/1) Seasonal income (0/1) Male-headed household (0/1) Household size Male respondent (0/1) Married respondent – monogamous (0/1) Married respondent – polygamous (0/1) Married respondent – informal union (0/1) Age of respondent (years) Age-squared of respondent (years) Primary (1-5) education (0/1) Primary (6-8) education (0/1) Secondary (1-2) education (0/1) Secondary (3-4) education (0/1) Tertiary education (0/1) Employed – formal sector (0/1) Employed – informal sector (0/1) Self-employed (0/1) Urban-cities (0/1) Urban-district towns (0/1) Peri-urban (0/1)

- -0.0002 -0.0309 0.0676

-0.0919 0.0051

-0.0603 0.0716 0.0827 0.2068 0.0089

-0.0001 0.0331 0.1106 0.1485 0.0878 0.0769 0.2344 0.1264 0.0510 0.0407 0.0857 0.0419

- -1.59

-1.91c 1.89c

-3.18a 1.37

-3.50a 2.94a 2.01c 3.28a 3.31a

-4.24a 1.46

4.45a 4.29a 2.45a 1.30

4.89a 2.80a 2.19c 1.57 1.60 1.09

0.0187 -0.0002 -0.0343 0.0705

-0.0939 0.0047

-0.0658 0.0727 0.0862 0.1971 0.0079

-0.0001 0.0320 0.1041 0.1340 0.0689 0.0522 0.2317 0.1278 0.0495 0.0354 0.0827 0.0423

3.48a -1.71c -2.11b 1.99b

-3.25a 1.27

-3.80a 3.00a 2.10b 3.11a 2.94a

-3.81a 1.41

4.18a 3.85a 1.91c 0.89

4.81a 2.83a 2.13b 1.37 1.55 1.10

Number of observations Wald chi-squared Prob> chi-squared Pseudo R-squared

4922 177.48

0.000 0.0344

4922 191.22

0.000 0.0367

Note: For dummy variables dF/dx is for discrete change of dummy variable from 0 to 1. Superscripts a, b and c represent statistically significant at 1%, 5% and 10% levels, respectively.

Compared to unmarried respondents, married respondents were more likely to have debt obligations. The highest impact is with respect to marriage by informal union which raises the probability of having current debt by 19.7% almost double the effects of other categories of marriage. There is a significant inverted u-shape relationship between age of respondents and having current debt obligations. The highest level of education is also positively associated with current debt, but only upper primary school and secondary education are statistically significant and their marginal effects being higher than other education categories. Adults in employment are more likely to report having current debt obligations than the unemployed adults. The marginal effects show that being in formal employment increases the probability of having current debt obligation by 23.2% while being in self-employment only increases the probability of debt obligation by only 5%. There are no statistical differences in probability of having current debt obligation between population segments.

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Factors associated with self-assessment of people’s confidence in their ability to manage their money or finances are evaluated based on the marginal effects presented in Table 62. The model slightly improves with the inclusion of the financial literacy index, and the signs and significance of marginal effects do not change. The results show that adults who are financially literate are more likely to reveal that they are very confident in their ability to manage their money. An additional correct answer to financial literacy questions increases the probability of revealing high confidence in managing money by 3.1%. Table 62: Probit Regression Marginal Effects – Very Confident in Money Management

Variables Model 1 Model 2 dF/dx z dF/dx Z

Financial literacy index Monthly income (K’000) Better-off financially than a year ago (0/1) Seasonal income (0/1) Male-headed household (0/1) Household size Male respondent (0/1) Married respondent – monogamous (0/1) Married respondent – polygamous (0/1) Married respondent – informal union (0/1) Age of respondent (years) Age-squared of respondent (years) Primary (1-5) education (0/1) Primary (6-8) education (0/1) Secondary (1-2) education (0/1) Secondary (3-4) education (0/1) Tertiary education (0/1) Employed – formal sector (0/1) Employed – informal sector (0/1) Self-employed (0/1) Urban-– cities (0/1) Urban-– district towns (0/1) Peri-urban (0/1)

- 0.0005 0.0655

-0.0222 -0.0579 0.0003 0.0975 0.0217 0.0430 0.0702 0.0084

-0.0001 0.0016 0.0380 0.0207 0.0527 0.1475 0.0758

-0.0109 0.0621

-0.0685 0.1011 0.0375

- 2.28b 3.78a -0.54

-2.02b 0.08

5.37a 0.82 1.04 1.18

3.17a -3.40a

0.07 1.55 0.62 1.53

2.67a 1.63

-0.25 2.51b

-2.53b 1.97c 0.96

0.0308 0.0004 0.0600

-0.0201 -0.0606 -0.0004 0.0888 0.0235 0.0489 0.0562 0.0069

-0.0001 -0.0003 0.0272

-0.0018 0.0231 0.1155 0.0716

-0.0098 0.0592

-0.0770 0.0963 0.0387

5.41a 2.13b 3.45a -0.49

-2.12b -0.10 4.86a 0.89 1.18 0.93

2.59a -2.70a -0.01 1.10

-0.05 0.65

2.00b 1.54

-0.22 2.38b

-2.82a 1.87c 1.00

Number of observations Wald chi-squared Prob> chi-squared Pseudo R-squared

4922 133.48

0.000 0.0243

4922 166.25

0.000 0.0294

Note: For dummy variables dF/dx is for discrete change of dummy variable from 0 to 1. Superscripts a, b and c represent statistically significant at 1%, 5% and 10% levels, respectively.

Of the income and wealth indicators, only monthly incomes and improvements in financial position are positively associated with high confidence in money management, leading to increase in probability by 0.04% and 0.6%, respectively. Respondents from male-headed households were more unlikely to reveal high confidence in money management than those from female-headed households. However, male respondents were more likely to reveal high confidence in money management than female respondents. The results imply that a male respondent from a male-headed household increases the probability of revealing high confidence in money management by 4% compared to female respondent from a female-headed household. The marital status of the respondent does not statistically affect the level of confidence in the ability to manage money or finances. The age of the respondent is positively related to the probability of being very confident in money management but up to a certain limit after which age is negatively associated with the level of confidence in financial management. Formal education also plays a positive role, but only tertiary education is associated with ‘very high

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confidence’ in financial management. Tertiary education compared to no education raises the probability of being very confident in the ability to manage finances by 11.5%. This is the factor that has the highest positive marginal effect in the self-assessed confidence in the management of finances. In terms of the nature of employment, adults that are self-employed are more likely to be very confident in managing their money, with probability increasing by 5.5% compared with the unemployed. It is likely that this confidence is reinforced by their experience in managing their self-employment activities. Adults living in urban-cities are less likely to be very confident in financial management compared to those residing in rural areas.

84

7. Financial Planning Practices in Malawi

The main objective of the questions in financial planning is to understand whether people plan for future expenditures including major expected expenditures, unexpected expenditures or emergencies, planning for old age and planning for the future of the children. The respondents were answering the questions on financial planning for themselves and their households or for themselves as individuals. As noted in the previous section only 7.8% of the respondents answered as individuals. The key issues investigated include how they deal with situations requiring money in unexpected events, whether and how they plan for their retirement age for adults less than 60 years old and how adults above 60 years are managing to make ends meet. Econometric analysis is used to investigate the association between likelihood of planning for old age and socio-economic characteristics and the role played by financial literacy. 7.1 Planning for Expected Events

Participants to the study were then asked to state whether or not they expected to have a major expense or bill amounting to at least the size of their monthly income. Table 63 indicates that the majority of the respondents (74%) expected some kind of expenditure or bill of the magnitude of their monthly income. Across stratum, more people in the urban-district towns (88.2%) than those in rural areas (72.9%) anticipated that level of debt or bill. Asked about the ability to pay in full if the debt or bill was to be paid the following day, the majority of the respondents (59.4%) said that they would not be able to make it and the proportion is highest amongst respondents from urban-district towns (69.2%) and lowest among respondents in cities (57.7%). When it came to doing something to make sure that they would be able to pay the expected expenditure in full without borrowing money that they had to pay back, again, the majority (45.4%) indicated that they had done nothing, and differences between the four strata of residence were not that pronounced. Suffice to say that in both instances, ability to pay the following day and doing something about the debt, there were a good proportion of people (24.9% and 29.3%, respectively) that did not know whether they would be able to pay or not or whether they had done anything or not.

85

Table 63: Expected Major Expenditures and Ability to Pay (%) Variable Urban -

cities Urban –

district towns Peri - urban Rural Malawi

Expecting a major expenditure or

bill in next 12 months

Yes No Don’t Know

N

74.5 25.3

0.1 659

88.2 11.8

- 140

79.8 20.2

- 200

72.9 26.7

0.3 4,000

74.0 25.7

0.3 4,999

Ability to pay in full if expense

was to be met tomorrow

Yes No Don’t Know Refused

N

17.0 57.7 25.3

- 491

19.3 69.2 11.5

- 123

15.9 63.8 20.2

- 160

14.0 58.9 25.7

1.3 2,916

14.7 59.4 24.9

1.0 3,699

If anything done to make sure

they pay the expected expense

Yes No Don’t Know Refused

N

22.1 47.4 30.5

- 491

35.5 50.3 14.3

- 123

33.4 42.6 24.1

- 160

23.0 45.4 30.4

1.5 2,916

23.8 45.4 29.3

1.2 3,699

Source: Financial Literacy Baseline Survey 2013

Last but not least, respondents in this section were asked the level of worry that they had in paying up the expense in full. Table 64 shows that only 13.8 per cent of the respondents were not worried at all, but 32.1 per cent were very worried and another 27.8 per cent were just a bit worried. Amongst those that were not worried at all the greatest proportion was among respondents from peri-urban areas (23%) and the lowest was among respondents from rural areas (12.7%). Table 64: Worries about Ability to Pay for Expected Expenditure or Bill (%) Variable Urban -

cities Urban –

district towns Peri - urban Rural Malawi

Not worried at all A bit worried Very worried Don’t Know Refused

N

16.9 30.7 27.0 25.3

- 491

12.8 46.3 28.3 12.5

- 123

23.0 25.6 31.2 20.2

- 160

12.7 26.6 33.1 26.2

1.3 2,916

13.8 27.8 32.1 25.3

1.0 3,699

Source: Financial Literacy Baseline Survey 2013 7.2 Planning for Unexpected Events The baseline survey sought how households plan for unexpected expenditures. These unexpected expenditures may include unexpected bills, unexpected replacement of household materials, unexpected home repairs, unexpected medical costs or funerals. Table 65 summarises the issues. Respondents were asked if they would be able to pay in full unexpected expenses that would come upon them the following day without borrowing money that they would have to pay back. The majority (87.2%) indicated that they would not be in a position to do so. The highest proportion that indicated that they would be able to do so was among respondents from urban-district towns (22.5%) which was way above the national proportion of 12.8 per cent. The lowest was amongst respondents from rural areas (12%).

86

Regarding the preparedness to be able to cover an unexpected expense, the majority (78%) indicated that they had not done anything to make sure that they could cover such an expense. When it comes to thinking of doing something to make sure they cover such unexpected expense, the majority (64.5%) indicated that they had not thought of anything and 35.4 per cent indicated that they had. Of those that had, the biggest proportion was among respondents from cities and the lowest was among respondents from rural areas (32.4%). Table 65: Planning for Unexpected Events and Readiness (%) Variable Urban -

cities Urban –

district towns Peri - urban Rural Malawi

Could cover an unexpected

expense in full without borrowing

money

Yes No Don’t Know

N

14.3 85.4

0.3 659

22.5 77.5

- 140

14.5 85.5

- 200

12.0 80.0

- 4,000

12.8 87.2

- 4,999

Something done to make sure

they pay the unexpected expense

without borrowing money to

repay later

Yes No Don’t Know Refused

21.3 78.4

0.3 -

22.7 77.3

- -

21.1 78.9

- -

21.9 77.9

0.1 0.2

21.8 78.0

0.1 0.1

Thought about doing something

cover unexpected expenses

without borrowing

Yes No Don’t Know Refused

46.1 53.6

- -

36.9 58.6

- 4.5

45.0 55.0

- -

32.4 67.0

0.1 -

35.4 64.5

- 0.1

Source: Financial Literacy Baseline Survey 2013 Respondents were then asked what they had done or thought of doing to prepare for the unexpected expenses. Figure 29 shows that the majority of the respondents (77/1%), had accumulated some savings that they would use in the event of some unexpected expenses. With regard to population segments, the highest proportion of respondents with accumulated savings was reported among urban-district town population (100%) and the lowest was among the rural population (72.3%). Reliance on support from family and friends was another avenue that people banked their hopes on in the event of some unexpected expenses (11.5%). Reliance on family and friends was highest among peri-urban populations (17.4%) and lowest among the district town population, while among the rural population only 11.3%. Other specified ways including thinking about starting a business, keeping livestock and selling livestock were reported by 27.2% of adult Malawians.

87

Figure 29: Measures taken to Prepare for Unexpected Expenses (%)

Source: Financial Literacy Baseline Survey 2013

On the unexpected expenditures respondents were asked whether or not they were worried about meeting them. Figure 30 shows that overall, only 11.2 per cent were not worried at all, with the rural areas having the lowest proportion of those not worried at all (10.1%), and the cities having the highest proportion (16.7%). Otherwise, overall, 57.6 per cent were very worried and 31.2 per cent were a bit worried. The highest proportion of respondents that were very worried was amongst those from rural areas (59.6%) and the lowest proportion was amongst respondents from urban-district towns (47%).

Figure 30: Whether one was Worried about the Meeting the Unexpected Expenses (%)

Source: Financial Literacy Baseline Survey 2013

Respondents from urban-district towns, peri-urban and rural areas were largely responsible for planning for major expected and unexpected expenses (Table 66). For the rural areas, these were followed by a joint planning by the respondent and husband/wife/partner (27.2%) and then planning mainly by the respondent’s husband/wife/partner (21.7%). For respondents in the city

1.0

1.4

2.3

11.5

27.2

77.1

0 10 20 30 40 50 60 70 80 90

Buy formal insurance

Contribute to informal insurance fund

Rely on employer support

Repy on support from family and friends

Other specified

Accumulate savings

Percent

16.7

12.615.5

10.1 11.2

35.6

40.4

28.330.3 31.2

48.2 47.0

56.2

59.657.6

0

10

20

30

40

50

60

70

Urban - cities Urban - district towns

Peri - urban Rural Malawi

Pe

rce

nt

Not worried at all A bit worried Very worried

88

though, the majority (33.2%) planned jointly with husband/wife/partner, followed by planning by the respondent only (29.7%). Table 66: Persons Responsible for Planning for Major Expected and Unexpected Expenses (%) Person Urban -

cities Urban –

district towns Peri-urban Rural Malawi

Mainly respondent 29.7 37.2 38.4 39.8 35.4 Mainly respondent’s

husband/wife/partner 19.4 18.5 28.0 21.7 21.6

Respondent and husband/wife/partner jointly

33.2 33.0 24.6 27.2 28.0

Respondent and someone else in the household jointly

10.0 5.2 5.0 5.5 5.0

Mainly someone else in the household

7.1 6.2 3.0 5.3 5.4

Nobody at all - - - 0.4 0.3 Don’t know - - 1.0 - - Refused to answer 0.6 - - 0.1 0.1

Source: Financial Literacy Baseline Survey 2013 The respondents were also asked if at all they had in the 12 months before the interview experienced any drop in their monthly income. Figure 31 shows that 85.4 per cent of the respondents had experienced a drop and the largest proportion was among respondents from rural areas (86.4%), with the peri-urban sample having the lowest proportion (77.7%).

Figure 31: Incidence of Unexpected Drop in Income (%)

Source: Financial Literacy Baseline Survey 2013

The majority of respondents (57%) that had experienced some kind of drop in income did ganyu and 49.9 per cent borrowed money from family members, relatives and friend (Table 67). The use of ganyu was more predominant in the rural areas (63.7%) and lowest in cities (24.1%). The third most popular method was to cut down on expenses and save (25.1%), followed by selling some of their goods (20.3%) and then spending savings that they had (14%). Distress selling was common in households from rural areas (22.9%) and peri-urban areas (20.9%), while as drawing down on savings was high in urban-district towns (24.2%), cities (22.3%), peri-urban centres (20.9%) and lowest in rural areas (11.9%).

81.6 82.777.7

86.4 85.5

18.2 17.3 22.317.3

14.5

0

20

40

60

80

100

120

Urban - cities Urban -district towns

Peri - urban Rural Malawi

Pe

rce

nt

Yes No

89

Table 67: Solutions to Unexpected Drop in Income (%) How ends were met Urban -

cities Urban –

district towns Peri - urban Rural Malawi

Cut down expenses and saved 43.9 28.0 35.0 21.5 25.1 Borrowed money from family,

relatives and friends 56.4 56.8 44.9 48.8 49.9

Bought on credit from shops 5.3 6.4 6.2 5.5 5.5 Borrowed from non-banking

financial institutions 1.3 7.4 5.9 4.1 3.9

Sold some of their goods 5.9 11.0 20.9 22.9 20.3 Spent their savings 22.3 24.2 20.9 11.9 14.0 Worked extra hours or did

additional jobs 10.4 6.8 12.8 8.8 9.1

Did ganyu 24.1 40.7 39.5 63.7 57.0 Borrowed from a bank 1.1 1.0 1.1 0.6 0.7 Relied on employer support 2.9 2.0 2.7 0.8 1.2 Relied on employer insurance 0 0 2.2 0.1 0.1 Relied on chipereganyu 2.4 2.1 0 2.5 1.4

Source: Financial Literacy Baseline Survey 2013 7.3 Planning for Older Age Planning for old age was investigated at two levels: respondents under 60 years of age and respondents over 60 years (of age). For respondents under the age of 60, it is important to understand how they are planning how they are going to manage their expenses when they get to over 60 years old while for those already in the 60-years-and-above age group understanding how they are managing life can generate important lessons. 7.3.1 Planning for Older Age for the “Under 60 Year Olds” Overall, 87.9% of adult respondents were under the age of 60 years. These people were asked plans that they had for meeting expenses in old age and Table 68 shows that nationally, people have recourse to: selling or renting out non-financial assets (39.6%), income from business (36.5%), income from working (30.6%) and using their savings or other financial assets (11.4%). Savings and other financial assets and business are more pronounced in cities and peri-urban areas whereas selling or renting non-financial assets are more pronounced in urban-district town and rural areas. A third of the adults under the age of 60 years (33.3%) had no plan at all.

90

Table 68: Proportion with Plans for Meeting Household Expenses in Old Age (%) Nature of Plans Urban -

cities Urban – district

towns Peri - urban Rural Malawi

Financial help/support or help in kind from family, village or clan

Savings or other financial assets Own pension from the government

payable to everyone Own pension provided by your

employer Other own pension (not covered in

code 3 and 4 above) Pension in the name of other

household member Insurance Selling or renting out non-financial

assets (land, house, livestock) Inheritance Business (income from or selling) Will always work (employed or self-

employed) or farm Other None at all

N

7.10

18.26 6.07

3.90

0.26

0.67

2.84

36.14

1.28 49.14 20.77

2.01

32.85 631

11.51

11.26 4.98

0.95

-

-

0.83 54.29

0.75

38.33 26.03

0.17

24.64 127

5.12

15.85 7.61

5.18

1.29

0.62

3.36

41.18

1.58 39.86 26.69

0.26

24.72 181

8.85

9.86 0.67

0.57

0.05

0.26

0.15

39.39

0.61 33.96 32.89

1.59

34.36 3,430

8.51

11.38 1.93

1.19

0.14

0.32

0.72

39.58

0.76 36.52 30.64

1.53

33.29 4,369

Source: Financial Literacy Baseline Survey 2013 Table 69 shows the proportion of respondents under the age of 60 years who had things already in place to make sure that they could cover their household expenses in their old age. Overall, high on the list (25.8%), indicated that they will always work or farm, followed by business (21.2%) and then selling or renting out non-financial assets (19.4%). Employment or working on farm is highest in rural areas, while business is highest in cities and selling or renting out non-financial assets is highest in urban-district towns.

91

Table 69: Proportion with Plan for Meeting Household Expenses in Old Age Already in Place (%) Nature of Plans Urban -

cities Urban – district

towns Peri - urban Rural Malawi

Financial help/support or help in kind from family, village or clan

Savings or other financial assets Own pension from the government

payable to everyone Own pension provided by your

employer Other own pension (not covered in

code 3 and 4 above) Pension in the name of other

household member Insurance Selling or renting out non-financial

assets (land, house, livestock) Inheritance Business (income from or selling) Will always work (employed or self-

employed) or farm Other specified None at all

N

2.49

11.45 4.54

2.66

-

0.34

2.75 12.92

0.34

31.71 13.69

1.60

14.49 631

0.16

6.92 4.35

0.32

-

-

- 22.33

-

26.26 16.76

-

25.00 127

0.38

7.30 4.75

2.25

0.67

-

1.94 16.10

-

21.57 17.25

0.26

25.06 181

2.14

3.56 0.45

0.39

0.04

0.06

0.06

20.60 0.40

19.07 28.97

0.70

12.96 3,430

2.02

4.97 1.38

0.79

0.07

0.09

0.53

19.37 0.35

21.20 25.81

0.78

14.24 4,369

Source: Financial Literacy Baseline Survey 2013 Among the respondents under the age of 60 years that had retirement plans, 61.1% of respondents indicated that the sources which they had would provide money to cover the expenses in full while 34.7% indicated that the plans would not adequately cover expenses (Table 70). With respect to population segments, the highest proportion of those whose plans are adequate is among the urban-district town population and the least is among the peri-urban population. Table 70: Whether Sources Would Provide Enough Money to cover Expenses in Full (%) Response Urban -

cities Urban –

district towns Peri - urban Rural Malawi

Yes No Don’t Know Refused

N

65.63 28.72

0.65 5.00 361

76.88 15.56

7.56 -

76

52.52 45.09

2.39 -

95

59.99 36.26

1.60 2.16 1,922

61.11 34.78

1.44 2.67 2,454

Source: Financial Literacy Baseline Survey 2013 Asked if they were worried to cover household expenses in old age, the majority (46.5%) reported that they were very worried (Figure 32). Only 18.4 per cent indicated that they were not worried at all and 24.6 per cent indicate that they were a bit worried. Some (0.4%) indicated that they did not know whether to worry or not. The respondents that were very worried were from rural areas where close to half (49.2%) indicated that they were very worried compared to 34.6 per cent among respondents from urban-district towns.

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Figure 32: Extent of Worry at being unable to Meet Household Expenses in Old Age (%)

Source: Financial Literacy Baseline Survey 2013

The bulk of our respondents aged below 60 years (99.1%) were not receiving any pension be it from government, through employer or from both sources (Table 71). This is regardless of whether one lives in urban centres or not. It is also evident that very few people were contributing to a pension of some sort. Table 71: Receipt of Pension and Contribution to Pension (%) Variable Urban -

cities Urban –

district towns Peri–urban Rural Malawi

Receipt of Pension

Yes – from the government Yes – through employer Yes – both government &employer No (Don’t know) (Refused)

0.4 0.6

- 98.8

0 02

3.1 0.3

- 96.2

0.4 0

2.0 0.3

- 97.7

0 0

0.2 0.2

- 99.4

01 0.1

0.4 0.3

- 99.1

0.1 0.1

Contribution to Pension

Yes – from the government Yes – through employer Yes – both government & employer No (Don’t know) (Refused)

3.1 5.3 1.5

90.0 - -

-

0.5 0.4

99.0 - -

8.4 2.5 1.4

87.6 - -

0.9 0.4 0.1

98.3 0.2 0.1

1.6 1.2 0.3

96.7 0.1 0.1

Source: Financial Literacy Baseline Survey 2013 7.3.2 Managing Life for the “Above 60 Year Olds” Only 12.1% of the respondents were above 60 years of age. The majority of respondents aged over 60 years (56.1%) indicated that they will get the money to cover household expenses in old age from employment or farming (Table 72). The proportion reporting this was highest in peri-urban areas (63.8%) and lowest in cities (33.1%). This is followed by income from business (31.3%) and then income from selling or renting out non-financial assets. While as for the below 60 year olds, business was also number two, in this group selling or renting out non-financial assets and working/farming have reversed positions.

28.5

19.417.6 16.6

33.8

45.3

39.4

33.9

37.0 34.641.2

49.2

0

10

20

30

40

50

60

Urban - cities Urban - district towns

Peri - urban Rural

Pe

rce

nt

Not worried at all A bit worried Very worried

93

Table 72: Sources of Money to Cover Expenses in Old Age for Over 60 Year Olds (%) Sources of Money Urban -

cities Urban –

district towns

Peri - urban

Rural Malawi

Financial help/support or help in kind from family, village or clan

38.4 21.5 9.9 26.9 27.0

Savings or other financial assets 16.6 2.4 3.5 3.6 4.3 Own pension from the government payable to

everyone 8.1 23.0 3.5 1.5 2.5

Own pension provided by your employer - - 11.8 0.3 0.6 Other own pension (not covered in code 3 and 4

above) - 4.6 - - 0.1

Pension in the name of other household member 7.2 - - - 0.4 Insurance 7.0 - - - 0.4 Selling or renting out non-financial assets (land,

house, livestock, valuables) 44.7 40.4 18.0 27.7 28.8

Inheritance - - - 0.5 0.4 Business (income from or selling) 33.1 44.4 39.8 30.5 31.3 Will always work (employed or self-employed) or

farm 32.3 40.9 63.8 57.9 56.1

None at all - - 0.7 10.9 9.8 N 27 13 19 566 625

Source: Financial Literacy Baseline Survey 2013 While in the less-than-60-year age group nearly two thirds of the respondents indicated that the sources would provide enough money to cover the expenses, the reverse is true in the older than 60-years age group. A majority (62.7%) indicated that the sources would not provide enough money. The highest proportion was in peri-urban areas (79%) and the lowest was in urban-district towns (28.8%). Similar to the status of the under 60 year age group, the majority of the over 60s as well (97.1%) did not receive any pension and 99.6 per cent did not contribute to any pension. 7.3.3 Knowledge about Pensions All respondents were asked about their knowledge about pensions. Figure33gives an indication of the extent of knowledge about pensions among respondents from the various strata. It shows that 24.2 per cent of the respondents had not heard about pensions and the largest proportion was among respondents from rural areas (26.9%) and lowest in the city (10.7%) and urban-district town (10.9%). Close to 40% had heard about pensions but they did not understand what they were. The highest proportion was among those from urban-district towns (40%) and lowest in peri-urban centres (31.4%) and cities (31.5%). Only 40.7% indicated that they had heard of pensions and understood what they were, with cities (57.8%) having the highest proportion and rural areas (37.5%), lowest proportion.

94

Figure 33: Knowledge of Pensions (%)

Source: Financial Literacy Baseline Survey 2013

Respondents that had heard and understood what pensions are were asked to choose between statements that best described how a typical pension works. Figure 34 shows that the majority of respondents (69.5%) chose the statement that ‘my employer contributes money for my retirement’. The highest proportion was amongst respondents from rural areas and the lowest was among adults from urban-district towns. A much small proportion (17.8%) went for the statement that indicated that one contributes money for his/her own retirement. Overall, only 10.7% of those that have heard about pensions indicated that both their employer and themselves contribute towards their retirement, which is the correct understanding of how a typical pension works. These results show that adult Malawians have imperfect understanding of how a typical pension works.

Figure 34: Knowledge of the Operations of a Typical Pension (%)

Source: Financial Literacy Baseline Survey 2013

57.8

49.146.1

37.540.7

31.5

40.0

31.435.4

39.4

10.7 10.9

22.5

26.924.2

0

10

20

30

40

50

60

70

Urban - cities Urban - district towns

Peri - urban Rural Malawi

Pe

rce

nt

Yes, and I understand what they areYes, but I don’t understand what they areNo, I have not

57.5

52.3

67.1

73.3

69.5

22.5

28.4

17.0 16.217.8

18.9 8.8 15.9 8.6 10.70

10

20

30

40

50

60

70

80

Urban - cities Urban - district towns

Peri - urban Rural Malawi

Pe

rce

nt

My employer contributes money for my retirement

I contribute money for my own retirement

Both my employer and myself contribute money for my retirement

95

The knowledge that both the employer and employee contribute money for the employee’s retirement is even low among those with tertiary education (38%) and with upper secondary education (12%), and among those in formal sector employment (14%) but surpassed by those in informal sector employment (14%). With regard to plans to introduce a national pension scheme in Malawi, 89.5% of the respondents (of 1,926 respondents) who understood pensions had not heard about the plan to introduce a national pension scheme in Malawi (Figure 35). Only 10% of those with knowledge about pensions have heard of such plans. The highest proportion of those that had heard about it was in urban-district towns (15.1%), followed by those in peri-urban areas (13.9%) and then cities (11%). The lowest was in the rural population at 9.3%. In terms of highest education of respondents, 7.2% with no education, 5.9% with lower primary education, 10% with standard 6-8 education, 9.7% with form 1 – 2 education, 14.3% with form 3 – 4 education and 27.3% with tertiary education have heard about the National Pension Scheme. There are also low proportions with respect to nature of employment, 26.1% among formal employees, 11.4% among informal employees, 9.1% among self-employed and 9% among unemployed.

Figure 35: Knowledge of the National Pension Scheme in Malawi (%)

Source: Financial Literacy Baseline Survey 2013

Close to half the respondents (49.7%) that had heard about the national scheme indicated that it would be mandatory for the employees to participate while 39.6% indicated that it was not mandatory (Figure 36). A smaller proportion (10.2%) indicated that they did not know and the largest proportion that did not know was among respondents from rural areas (13.4%) and the lowest was from cities (2.3%). The results show that a relatively higher proportion of respondents that have heard about the national pension scheme, have the correct view that it is mandatory for employers to participate. It is also evident from the data that the highest proportion with the correct characterisation of the pension scheme is among respondents in urban-cities (62.5%) and the lowest proportion is among the respondents in the rural areas (37.2%).

11.0 15.1 13.99.3 10.0

98.083.8 86.1

90.2 89.5

0

20

40

60

80

100

120

Urban - cities Urban - district towns

Peri - urban Rural Malawi

Pe

rce

nt

Yes No Don't Know Refused

96

Figure 36: Knowledge about the Operation of the New Pension Scheme (%)

Source: Financial Literacy Baseline Survey 2013

7.4 Planning for Children’s Future In this baseline survey, respondents were also asked some questions on planning for the future of their children. The survey sought to find out the number of children that respondents had and then the number of children that were economically dependent on them. About 87% of the sample respondents had children. Table 73 shows that the mean number of children that respondents had was 4 but an average of 3 children were economically dependent on them. The mean number of children per respondent (among those who had children) is lower in urban-cities (3.1) than that among those living in the rural areas (4 children). Similarly, the mean number of children that are economically dependent on the respondent is lower in the urban areas than it is in other population segments. Table 73: Mean of Number Children and Economically Dependent Children Sample strata

N

Average number of children Average number of child-economic dependents

Mean Std. Deviation Mean Std. Deviation Urban-cities Urban-district towns Peri-urban Rural Malawi

533

107

169

3,561

4,370

3.14 3.89 3.62 3.99 3.87

2.01 2.39 1.98 2.32 2.29

2.59 3.31 2.96 2.83 2.82

1.74 1.93 1.92 1.95 1.93

Source: Financial Literacy Baseline Survey 2013 Adults who had children that were economically dependent on them were asked if they were in any way planning for the future of the children. Table 74 shows that the majority of respondents (79.3%) were planning for the future of their children by providing them with education. This was followed by those who invested in land or buildings with the aim of passing them on to their children (21.6%), and then investing in business to pass on to children (15.6%) and then those saving money to pass on to their children (14.7%). Investing in land and building was highest in peri-urban areas (32.9%) and saving to pass on to children was highest in cities (18.3%).

35.0

20.9 21.5

48.439.6

62.7

68.6 66.6

37.249.7

2.310.6 11.9 13.5 10.2

0

20

40

60

80

100

120

Urban - cities Urban - district towns

Peri - urban Rural Malawi

Pe

rce

nt

Voluntary for employers to participate

Mandatory for employers to participate

Don't Know

97

Table 74: Nature of Planning for the Children’s Future (%) Nature of Plans Urban -

cities Urban –

district towns

Peri - urban

Rural Malawi

Providing your child/children with an education Saving money to pass on to your child/children Investing money to pass on to your

child/children Investing in land and buildings to pass on to your

child/children Investing in a business to pass on to your

child/children Investing in insurance (e.g. group life cover) for

your children Other specified None of these things

N

73.87 18.27

9.24

28.94

16.94

4.64

1.33 2.14 622

76.22 17.78

5.15

25.96

11.37

1.73

2.27 0.80 128

74.58 17.07

8.59

32.68

16.76

6.91

- 6.88 178

80.68 13.81

6.07

19.33

15.45

0.77

2.54 4.60 3,505

79.29 14.73

6.59

21.55

15.57

1.64

2.24 4.24 4,433

Source: Financial Literacy Baseline Survey 2013 7.5 General Planning To assess the general preparedness for expenses, respondents were first asked the extent to which they agreed with three statements and the following three charts give the results. Figure 37 displays results for the statement: “I try to save money for the future”. Overall, 41% of the respondents indicated that this statement represented them very well and 24% indicated that it did not represent them at all. Variation across strata shows that the largest proportion that felt that the sentence did not represent them was from rural areas (24%) and the lowest was in peri-urban areas (18.5%).

Figure 37: Proportion that ‘Try to Save for the Future’ (%)

Source: Financial Literacy Baseline Survey 2013

Figure 38 shows that only 43.6% of the respondents felt that the statement “I try to save some money regularly, even if it is only a little” described them personally and the highest proportion was among people from peri-urban areas (52%) and lowest was in rural areas (42.1%).

45.246.6 46.5

39.841.0

34.4

30.6

35.0 34.1 34.0

20.522.8

18.5

26.124.0

0

5

10

15

20

25

30

35

40

45

50

Urban - cities Urban - district towns

Peri - urban Rural Malawi

Pe

rce

nt

Yes – very well Yes – to some extent No

98

Figure 38: Proportion that ‘Try to Save Some Money Regularly, even if it is only a Little’ (%)

Source: Financial Literacy Baseline Survey 2013

In Figure 39, fewer people 29.6% felt they were represented very well with the statement “I always try to have some provision for emergencies or unexpected expenses”. In this regard, the highest proportion was in urban-district towns (39.1%), then cities (34.3%) and then peri-urban areas (33%) with the rural areas being the lowest at 28.1%.

Figure 39: ‘Always Try to Have Some Provision for Emergencies’ (%)

Source: Financial Literacy Baseline Survey 2013

Respondents were also asked how far ahead they usually planned for their future and Table 75 gives the results. Most people in the sample either planned daily but less than a week (25.5%), or weekly but less than once (27.3%), or one month but less than 6 months (28.2%). Very few people planned 6 months but less one year (6.2%), one year but less than 2 years (7.6%), and two years but

49.6

44.8

52

42.143.6

35.7

40.4

34.4 35.1 35.3

14.7 14.8 13.8

22.821.0

0

10

20

30

40

50

60

Urban - cities Urban - district towns

Peri - urban Rural Malawi

Pe

rce

nt

Yes – very well Yes – to some extent No

34.3

39.1

33.0

28.129.6

37.3

27.0

36.9

31.8 32.6

28.4

33.936.1

40.1

37.8

0

5

10

15

20

25

30

35

40

45

Urban - cities Urban - district towns

Peri - urban Rural Malawi

Pe

rce

nt

Yes – very well Yes – to some extent No

99

less than five years (0.6%). In general therefore, there is not too much planning into the far distant future. Table 75: Proportion that Plan Ahead for the Future (%) Planning Horizon Urban –

cities Urban –

district towns Peri -

urban Rural Malawi

Daily/less than a week Weekly/less than one a month One month but less than six months Six months but less than one year One year but less than two years Two years but less than five years Five years but less than ten years Ten or more years ahead Does not plan for the future at all

21.5 31.2 34.4

5.1 5.5 0.4 0.3 0.3 1.3

32 31.1 20.8

6.9 6.8

- 0.6 0.5 1.4

30.2 22.2 35.2

2.8 5.2 0.5 1.7 0.9 1.3

25.6 26.8 27.1

6.6 8.1 0.6 0.4 0.5 3.8

25.5 27.3 28.2

6.2 7.6 0.6 0.5 0.5 3.3

Source: Financial Literacy Baseline Survey 2013 7.6 Determinants of Financial Planning for Older Age

This section explores the factors that are associated with the probability of having a retirement plan for older age. The specification used by van Rooij et al (2011, 2012) is adapted in which financial literacy indices and socio-economic characteristics are used to explain likelihood of having a retirement plan. The following is the specification of the model ���� = � + ���� + ��� + ���� + ��� + �� + � (3) where POA is an indicator of whether the respondent has plans of money management behavioural indicators, FLI is a vector of financial literacy indicators, HHW is a vector of household wealth and welfare indicators, HHC is a vector of household characteristics, REC is a vector of respondent characteristics, X is a vector of other control variables, and μ is the error term. The dependent variable, retirement plan, comes from a question asked to respondents “What

plans do you personally have for meeting your/your households expenses in your old age?” Thirteen options (including ‘none’) were provided without reading them out. The options included savings, support from family, pension, insurance, renting out assets, inheritance, business and always working or farming. In this case having a retirement plan is measured by a dummy variable that takes the value 1 if the respondent has a retirement plan for older age (choose at least one of the 12 options) and 0 if she/he had no plan or had not thought about it. The model is run on a subsample of respondents that are less than 60 years old. The explanatory variables include financial literacy index, household income and financial wellbeing, gender of household head, household size, age of respondent, marital status of respondent, highest level of education of respondent, nature of employment and population segments as defined under equation (1) above. Table 76 presents probit regression results of the likelihood of having a retirement plan for older age for respondents under the age of 60 years. The inclusion of the financial literacy index variable slightly improves the explanatory power of the model but does not change the significance of the other variables. Model 2, which is the focus of interpretation, explains 7.2% of the variations in the probability of having a retirement plan for older age. Financial literacy positively correlates with the probability of having a retirement plan and the marginal effects are statistically significant at the 1% level. This suggests that the probability of having a retirement plan increases by 2.9% points for an additional correct answer on the financial literacy questions.

100

The current level of income also plays a significant role although the magnitude of the marginal effects is small indicating that an additional K1 000 to household income increases the probability of planning for old age by 0.05% points. Households whose financial position was better-off than it was a year ago had higher probability of having a retirement plan by 4.2% points than households that experienced no change or were worse-off financially. Seasonality of income seems to have a larger effect on planning, with seasonality in incomes raising the probability of having a retirement plan for old age by 20.4% points. The results also show that respondents from male-headed households are more likely to have retirement plan than respondents from female-headed households, differing in probability by 6.1% points. This bias is also reinforced by the gender of the respondents in which the probability of having a retirement plan increases by 6.6% points for male respondents compared to female respondents. The implication is that the probability of having the retirement plan increases by 12.7% points for male respondents coming from male-headed households compared to female respondents and those that come from female-headed households. Gender is therefore an important predictor of the likelihood of having a retirement plan.

Table 76: Probit Regression Marginal Effects – Planning for Older Age

Variables Model 1 Model 2 dF/dx z dF/dx z

Financial literacy index Monthly income (K’000) Better-off financially than a year ago (0/1) Seasonal income (0/1) Male-headed household (0/1) Household size Male respondent (0/1) Married respondent – monogamous (0/1) Married respondent – polygamous (0/1) Married respondent – informal union (0/1) Age of respondent (years) Age-squared of respondent (years) Primary (1-5) education (0/1) Primary (6-8) education (0/1) Secondary (1-2) education (0/1) Secondary (3-4) education (0/1) Tertiary education (0/1) Employed – formal sector (0/1) Employed – informal sector (0/1) Self-employed (0/1) Urban – cities (0/1) Urban – district towns (0/1) Peri-urban (0/1)

- 0.0006 0.0461 0.1983 0.0624 0.0021 0.0741 0.0048

-0.0100 -0.0026 0.0208

-0.0002 -0.0080 0.0263 0.1193 0.1288 0.2141 0.2053

-0.0176 0.1240

-0.0195 0.0690 0.0400

- 1.90c 2.67a 4.16a 2.02b 0.52

4.10a 0.18

-0.24 -0.04 4.01a

-2.83a -0.32 1.04

4.04a 4.39a 5.48a 6.37a -0.40 4.68a -0.71 1.33 1.02

0.0285 0.0005 0.0423 0.2042 0.0605 0.0019 0.0662 0.0079

-0.0033 -0.0160 0.0193

-0.0002 -0.0098 0.0169 0.1031 0.1062 0.1930 0.2047

-0.0160 0.1218

-0.0255 0.0646 0.0387

4.87a 1.75c 2.44b 4.30a 1.94c 0.45

3.63a 0.29

-0.08 -0.26 3.73a

-2.56a -0.39 0.67

3.36a 3.44a 4.45a 6.41a -0.36 4.62a -0.93 1.22 0.98

Number of observations Wald chi-squared Prob> chi-squared Pseudo R-squared

4310 300.55

0.000 0.0668

4310 321.05

0.000 0.0719

Note: For dummy variables dF/dx is for discrete change of dummy variable from 0 to 1. Superscripts a, b and c represent statistically significant at 1%, 5% and 10% levels, respectively.

There is no statistically significant association between probability of having a retirement plan and marital status of the respondents. As is the case with earlier models, there is an inverted u-shape relationship between the age of the respondent and the probability of having a retirement plan. The probability of having a retirement plan increases as the age increases but begins to fall at the age of 48 years.

101

Formal education plays a very important role in the probability that respondents have a retirement plan both in terms of the statistical significance and the magnitudes of the marginal effects. However, the formal education effects begin with secondary education and the increase in the probability range from 10.3% points among respondents whose highest education is junior secondary school to 19.3% points among respondents whose highest education is tertiary. The nature of employment matters, with statistically significant marginal effects at 1% level with respect to formal sector employment and self-employment. The probability of having a retirement plan increases by 20.5% points and 12.2% points for respondents employed in the formal sector and self-employed compared to the unemployed, respectively. Although not statistically significant, informal sector employment is negatively correlated with the probability of having a retirement plan. There is no statistically significant evidence of urban-rural differences in having a retirement plan.

102

8. Main Findings and Recommendations Financial inclusion, consumer protection and financial education are important ingredients of a well-functioning financial system. Many studies in developing countries have shown that large proportion of the population operate outside the formal financial system; they know little about the products in the formal financial sector and are financially illiterate. As a way of addressing these issues, financial education programmes and institutionalization of consumer protection in the financial sector are being promoted in order to expand financial inclusion and encourage better management of personal and household resources. In Malawi, earlier studies find that more than half of adult Malawians are excluded from the financial system. However, there were gaps in knowledge with regard to the level of financial literacy and awareness about financial consumer protection in Malawi and how financial literacy affects the financial decisions and the behaviour of financial decision-makers at household and personal levels. In order to create better interventions to improve financial inclusion, this baseline survey of financial literacy and consumer protection was conducted in the second half of 2013. The objective of the baseline survey was to obtain information on knowledge of financial management and services as a basis for designing appropriate interventions for improving financial literacy and consumer protection in Malawi. The baseline survey covered a randomly selected national representative sample of 4,999 households throughout Malawi across four strata including urban-cities, urban-district towns, peri-urban and rural areas. Face-to-face interviews were conducted using a structured questionnaire administered to one randomly selected adult member above the age of 17 years (from 15 years where there were no adult members of the household above 18 years). 8.1 Main Findings Socio-economic characteristics The socio-economic profile of households included in the baseline survey is consistent with the national population in terms of the population age structure, save minor differences in some selected features. The following are the main findings in terms of the characterisation of Malawian households:

• Although most of the households are male-headed (76.1%), 59.1% of the respondents are females. Most of the household heads are married and in a monogamous relationship and 11% were widowed.

• The literacy rate is 71% among household heads and 67% among adult respondents. Most of the households heads and respondents have the highest completed level of education as primary school (standards 1 – 8) representing 58% of households and 57.9% of respondents, respectively.

• It is also evident from the study that the main activities for most respondents is self-employment (76%) and as high as 82% in the rural areas. Formal and informal employment was reported by only 9.3% of adult Malawians while only 0.3% of adult Malawians are actively looking for employment.

• Most of the respondents are decision-makers in household finances as they contribute to the household budget (93%), participate in the household decision about money (94%) and are mainly responsible for own personal spending (84%).

103

Incomes and Economic Activities Most households in Malawi have fragile incomes and tend to rely more on unstable sources, and the situation is consistent with previous findings of low incomes and high incidence of poverty in Malawi. The baseline survey has shown that self-employment is the most common economic activity among adult Malawians both at individual and household levels. The following are the main findings:

• Overall, self-employment (business or farm) is the main source of income for 75% of adult Malawians and 78% of Malawian households. The highest proportions are among the rural populations (80% of respondents and 84% of households) and lowest in urban-cities as reported by 50% of urban-city households. Formal work in government and the private sectors is the main source of income for only 4% of adult Malawians. These low levels of formal employment imply that most of the income among Malawians comes from unstable sources with consequences on people’s ability to save and invest in productive activities.

• There is high instability in incomes with 93% of adult Malawians reported that their

incomes are seasonal and the seasonal variations occur regardless of times of year when they get most incomes or when they get the least incomes. About 67% of adult Malawians have personal incomes averaging less than MK10,000 per month while 48% of households reported receiving average monthly household incomes of less than MK10,000, although the proportions are much higher in rural areas than in the urban areas.

• The self-assessment of people’s current financial position compared to a year ago shows

that only 32% of Malawian households revealed that there were better off financially while 52% revealed that their financial position got worse. The rural areas are relatively worse than the urban areas. However, looking ahead, 55% of households believe that their financial position will improve, although 22% of households do not know of their future prospects.

• In terms of getting information or advice when making important financial decisions, 55% strongly agreed that they always get information or advice, regardless of the population segments. The main source of financial advice is their spouse or partner as reported by 45% of adult Malawians, followed by a friend (40%) and a parent or grandparent (19%). There is limited recourse to advice from financial providers such as banks, microfinance organisations, insurance providers, ROSCAs or someone in a savings club.

Financial Literacy The levels of financial literacy vary considerably and depend on the financial concept and terms known by consumers. Nonetheless, there are high levels of financial illiteracy across population segments and across formal education levels, suggesting that a national financial education programme is a necessary intervention. This derives from the following findings:

• Using the seven questions relating to simple division, inflation, simple interest rate, compound interest rates, absolute and percentage discounts, risk and risk diversification, the most correct answers were on simple division (82%), followed by absolute and percentage discount (64%) and compound interest rate (54%). However, combining the scores, only 1% of respondents gave correct answers to all the 7 questions, 27% got 5 – 6

104

questions right and 21% got only 1 – 2 questions right. The mean financial literacy is 4 correct answers representing 57% average score.

• About half of adult Malawians report that they saved money as a child and they mainly saved the money in the money box at home, regardless of whether they are in urban-cities or rural areas.

• Knowledge of financial terms such as interest rate, insurance, shares, stock exchange, inflation and devaluation is low, and the non-existence of equivalent local language terms (except for interest rate) made matters worse. What interest rate means is mostly known by 43%, insurance and shares are known by 28% each, stock exchange is only known by 6%, inflation is known by 7% and devaluation is known by 14% of respondents. There are, however, urban-rural biases in knowledge of these concepts with much higher levels in the urban areas than in the rural areas.

• Less than 50% of adult Malawians strongly disagree with statements that ‘they focus on the short-term’, ‘live more for present day than tomorrow’ and ‘the future will take care of itself’. There are however non-trivial proportions that strongly agree with these statements as high as 32% in agreeing that ‘they focus on the short-term’. On the positive aspects of life, most do things after giving much thought, say things after thinking through them, they always look for opportunities, have aspirations and always work hard.

• Access to mobile phone is at 56% although only 36% own a mobile phone. There is urban-rural bias in mobile phone ownership with 71% of those living in urban-cities compared to only 29% of those living in rural areas owning a mobile phone. The baseline survey also finds that most people (more than 75%) have knowledge of use of mobile phones for financial services such as receiving/transferring money, paying bills, buying airtime and Me2U. Nonetheless, most respondents have actually used mobile phones to buy air time and sending airtime (Me2U). But a high proportion of respondents are very likely to use a mobile phone for receiving money (73%), transferring money (79%) and paying bills (65%).

• Most would also welcome the use of alternative places for accessing financial services, most popular being large agro-input dealers (96%), bank branch (81%) and local supermarkets (80%). Some of these alternative places are much closer to customers particularly for the rural population for which a large proportion remain without access to financial services.

• With respect to factors associated with financial literacy, there are variations in the factors depending on the financial concept. However, with respect to the financial literacy index, the positive drivers include having a bank account, saving money as a child, medium to long term planning horizon, improving financial wellbeing, being a male respondent, age of respondent (inverted u-shape), education (from standard 6 upwards) and being resident in urban-city areas. More significantly is the role played by savings as a child underscoring the importance of developing a saving culture at a younger age. Formal education also plays important roles in both significance and magnitudes of effects.

Financial Services and Products Holding of formal financial services and products remains limited in Malawi and the situation is acute in rural areas. Most adults do not have information about financial products and services and have limited information about financial consumer protection agencies and how to resolve

105

conflicts with financial service providers. The following main issues emerge from the baseline survey:

• There is low possession of formal financial sector products and services in Malawi, with only 17% and 6% having products and services in the formal and semi-formal financial services compared to 53% in the informal sector and 34% without any financial product and service. There are urban-rural differences with a higher proportion of urban city populations (47%) having formal products and services than rural populations (10%). In the formal sector the most common product and service is savings/deposit account held by 15% of adult Malawians compared to 25% who have informal savings accounts in ROSCAs and VSLs.

• In choosing financial products and services, most respondents search for information from a range of sources and are proactive by approaching the service providers. However, most learn about financial products and services from friends and family (58%), followed by service providers from which 36% learnt about the products. This implies that targeting financial education to specific groups may have contagion effects as friends and families that attend such training are likely to pass the knowledge to others within communities.

• The proportion of respondents that have had conflicts with financial service providers is small, but still most did nothing about it and those that acted opted to stop using the service and approached the service providers through community elders. Approaching service providers through community elders, stopping using service, approaching the police and by discussing informally are the most common actions that respondents would take in the future if faced with a situation of conflict with a service provider. The proportion that did not take action after experiencing conflict with service providers indicated that they are not aware of government agencies that can be approached for help.

• Only 74% have heard about the Reserve Bank of Malawi, 13% have heard of the Reserve Bank of Malawi Division of Consumer Protection and 47% have heard about the Consumer Association of Malawi. It is also apparent that most consumers are not aware of procedures for seeking redress with appropriate authorities whenever they are in conflict with financial service providers. The informality of many financial services may also play a part in this gap in knowledge.

• In designing consumer financial education programmes, the use of the radio has the potential to reach out to a greater proportion of Malawians as currently 62% use the radio as a source of information while newspapers, though not replacing radio, would be useful in urban areas such as cities and district towns. Modern media facilities such as the internet and SMS seem to be less effective vehicle for financial education.

• The potential demand for bank accounts remain low, including those with accounts and those intending to open one in future, at 29% of adult Malawians. However, the availability of financial services may be key since 61% among urban-city populations compared to 22% among rural populations with bank accounts or intending to open one. Other key socio-economic factors that increase the probability of having a bank account are financial literacy, incomes, gender (male head or male respondent), age of respondent (inverted u-shape), education and formal employment. The motivating factors for opening a savings account include interest rates, bank charges and the bank’s reputation mentioned by at least 25% of respondents.

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• The demand for bank loans is even lower as only 8% of respondents indicated that they have a bank loan or intending to take one, with bank’s reputation and credit interest rates being the main considerations.

• There are mixed perceptions about five service providers (banks, other lending and MFIs, community groups, katapila and insurance companies) on the quality of services. Community groups score highly with respect to getting things done easily, quick service, providing information that is easy to understand and reasonable charges. Katapila is known for lending too easily and getting borrowers into problems and confiscating property when borrowers fail to repay the loan. The main problems experienced by consumers using financial services are related to long time to withdraw money from the bank and ATMs not working when people want to withdraw money.

Money Management Overall, the money management practices in Malawi are encouraging as reflected in the high proportion of adult Malawians that plan the use of money, that save some money, that know how much they spend, how much money they have and the discipline in managing money. However, the confidence in managing money is moderate and that there is high incidence of borrowing to support food and basic necessities. In addition, although a majority save some money, the savings are mainly made outside the formal financial system. The following are the main findings on money management practices in Malawi:

• A high proportion, 91%, of adult Malawians plan use of money when they receive it and 47% of those that plan use of money do so always and 79% indicated that they keep their plans. There are minor differences in planning use of money in urban-cities, urban-district towns, peri-urban and rural areas, except the urban district towns that have significantly higher likelihood of planning than rural areas.

• The factors that are positively associated with the likelihood of planning include improvements in financial wellbeing, seasonality of income, highest education of respondents, and being in self-employment. Respondents from larger households and respondents married in informal unions were unlikely to plan the use of their money. The level of financial literacy does not significantly affect the likelihood of planning the use of money, so is the gender of the household head and gender of respondents. Although, a large proportion of those that plan indicated that they keep the plan, it is not known to what extent these plans are documented by the household.

• One aspect of good money management is the ability to save some money after paying for food and basic goods and services. The proportion of adult Malawians that has some money left over after paying for food and basic necessities is high, 76%, but only 18% save on a regular basis. The incidence of saving is lowest in the rural areas, 75% with 16% of these saving on a regular basis. The main reason for saving some money is to keep it for future food and other necessities needs as revealed by 75% of adult Malawians. This is followed by keeping money for unforeseen expenditures (53%), spending money of self or buying non-essential items (51%) and to invest the money in business or farming (49%).

• Savings behaviour is positively associated with the level of financial literacy, the level of income, improvement in financial wellbeing, seasonality of income, marital status (monogamy or polygamy), upper primary and lower secondary education, self-employment and savings experience as a child. Similar to planning, household size and informal union marriages are negatively associated with likelihood of savings. The results

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underscore the importance of developing a savings culture from childhood as one way of promoting future savings behaviour.

• The typical ways of keeping such money include keeping cash at home (81%), saving at a bank (20%), at an informal savings and credit group (14%) and at informal saving group (chipereganyu) (10%). Other methods mentioned by less than 8% of adult Malawians include saving through keeping livestock, using someone else for safe keeping and saving through stocks for business. The methods of savings that appeals most are simple to use, convenient to get to, safe from temptations to use the money and safe and trustworthy. The baseline survey has therefore established that most savings are kept outside the formal financial system.

• A high proportion of adult Malawians (90%) run short of money to cover expenses for food and other basic needs and 70% have ever used debt to finance basic necessities. They run short of money because they feel that their incomes are insufficient or income fluctuates or it is unreliable, and indeed many borrow from family and friends (63%) or go for ganyu work (61%). However, the proportion of adult Malawians that borrow to pay debts is lower, only 18% and most borrow sometimes rather than regularly. With respect to current debt obligations, a third of adult Malawians (38% among urban-city adults) have to repay borrowed money. Overall, the most adult Malawians with debts contract debts that are typically less than or equal to their monthly income, but 21% contracted debts that were more than their monthly income.

• The incidence of current debts is higher among households with lower incomes, those with worsening financial position, female-headed households and female respondents, married respondents, respondents with upper primary to upper secondary education, employed (formal or informal) and self-employed). There is also evidence that respondents with higher financial literacy also tend to have higher likelihood of debt – this may be due to higher ability to manage such debts. Age of respondent has an inverted u-shape relationship with current debt obligation.

• A majority of adult Malawians (74%) know the amount of money they spent in the previous week, with most knowing exactly how much they spent (69%). Similarly, a majority of adult Malawians (72%) know the amount of money that was available for them and their households with 73% knowing the exact amount.

• Most adult Malawians (79%) revealed that they are ‘very disciplined’ in managing their money while 67% learn from the mistakes that others make in managing their money. They are also conscious buyers of unnecessary things before buying food and basic necessities and most never buy unnecessary things when they know they cannot afford them. More than half of adult Malawians (56%) revealed that they are very confident in money management, and such confidence is high among the middle age group (35 – 59), increases with level of formal education and increases with formality of employment.

• Key characteristics that are associated with higher levels of confidence in money management include financial literacy levels, monthly incomes, improvement in financial wellbeing, age of respondent (inverted u-shape), tertiary education and self-employment. Respondents from male-headed households were more unlikely to be very confident in money management than those from female-headed households but male respondents were more likely to be very confident than were female respondents. The adult population

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in urban-cities were less likely while populations in district towns were more likely to be confident in money management than were rural populations.

Financial Planning There are several aspects of financial planning that were central to the study particularly focusing on planning for expected and unexpected expenses, planning for old age and planning for children. Generally, there is limited planning for old age in Malawi and this may be driven by the low income levels. Most households are desperate on how they are going to meet planned and unexpected expenses and very few have thought on a pension as a plan for old age. The following are the main findings on financial planning in Malawi:

• A majority of the respondents (74%) are expecting a major expense or bill equivalent to their monthly income, no wonder about 59% of these would not be able cover such expenses or to pay for such a bill in full. Furthermore, a significant proportion (45%) is desperate and had done nothing to enable them to cover such expected expenses in full without resorting to borrowing. Similarly, 87% of adult Malawians cannot cover unexpected expenses in full the following day without borrowing money that they would use to pay back, and a majority (78%) are doing nothing to prepare for such an eventuality. This is consistent with problem of insufficient or irregular incomes that most people feel they need to have to manage their lives properly.

• Most people are therefore very worried on how they will cover expected or unexpected expenses with fragile incomes, with many respondents and their households (86%) experiencing a drop in income in the past 12 months. Most will resort to ganyu work (57%), particularly in the rural areas (64%), to survive if they experience unexpected drop in incomes. This is followed by half who would resort to borrowing money from family, friends and relatives.

• The concept of planning for old age is most problematic among Malawians under the age of 60 years. The most popular plan for old age is to sell or rent out non-financial assets such as land, house and livestock (40%), followed by business (37%) and always working (31%). About a third of respondents have no plans at all and only less than 3% have pension plans.

• Multivariate analysis shows that the probability of having a plan for old age significantly increases with levels of financial literacy, income levels, improvements in financial wellbeing, seasonality of income, male headship of households, age of respondents (inverted u-shape relationship), highest levels of education (from secondary), being a male respondent, being a formal sector employee and if the respondent is self-employed

• For respondents over 60 years old, the main ways of covering expenses is to always work, business income, selling or renting out non-financial assets, and financial help or support from family.

• People’s knowledge about pensions vary, but overall 42% of adult Malawians have not heard about pensions and 41% have heard about them and understand what they mean. A higher proportion of adults in urban-cities (58%) compared to 38% among adults in the rural areas have heard about pensions. Only 11% of those that have heard about pension and know what they mean, believe that both the employer and employee contribute for the employee’s retirement. The knowledge that both the employer and employee

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contribute money for the employee’s retirement is even low among those with tertiary education (38%) and with upper secondary education (12%), and among those in formal sector employment (14%) but surpassed by those in informal sector employment (14%).

• The National Pension Scheme is not very much known by adult Malawians that have ever heard of pensions and understand them, only 10% know about it and only 50% know that it is mandatory for employers to participate. The proportions that have heard about the National Pension Scheme is also with respect to education and nature of employment, with the highest proportion in these groups being 27% among those with tertiary education and the highest proportion of 26% among formal sector employees, respectively.

• About 87% of the sample respondents have children, with the mean number of children being around 4 of which 3 children are economically dependent on the respondent. Provision of education to children is the most common plan for children future as articulated by 79% of respondents with children, followed by investing in land and buildings to pass to children (22%). Saving money to pass to children is a plan for children’s future only among 15% of respondents with children. About a quarter of the respondents do not try to save for the future, 21% do not try to save same money regularly even if it is only little and 38% do not try to have provision for emergencies.

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8.2 Recommendations 8.2.1 Financial Education Programmes and Strategies The low levels of financial literacy across the population segments and across different levels of education in Malawi justify the development of a comprehensive financial education programme on various issues of money and financial management. Such programmes in the context of Malawi should focus not only on the financially excluded population, but also on the financially included population since their financial literacy seems to be wanting as well. This will require utilizing various delivery channels for financial education to reach out large proportions of the Malawian population. The following issues and strategies may be considered in the development of national financial education programmes:

• Financial terms and concepts are not easily translated into local languages. Given the general literacy levels in Malawi, it is therefore important for any financial education programme to develop local language terms for some of the financial terms and concepts.

• Financial education programmes should be developed in English and main local languages in Malawi. The baseline has shown that there are pockets of people among the educated from secondary to tertiary levels that have poor understanding of financial concepts and financial terms.

• The use of mass media complemented by other media channels may be recommended as channels for delivering financial education. In Malawi, most households have access to a radio. Development of radio programmes such radio drama and discussion forums and having specific times for airing the programmes and providing contact numbers after broadcast may be useful interventions. The increase in the number of local radio stations and TV broadcasters offer additional opportunities for harnessing the potential of media to deliver financial education, including soap opera on TV. Television programmes may prove useful for targeting the high income groups and working class in urban areas.

• The Reserve Bank of Malawi should increase its visibility in championing financial consumer protection. There should be public awareness of consumer protection institutions and the procedures for approaching them. This should include the establishment of walk-in or phone-in centres (hotline numbers) for consumers to register their complaints about financial services and also get help on how to resolve some of the conflicts.

• It is important to use multiple stakeholders to deliver financial education programmes in Malawi given the diversity of gaps in financial literacy. This should include consumer protection agencies, financial service providers, non-governmental programmes, civil society organisations and farmer organisations. Some of the civil society organisations that may be targeted to deliver financial education include Consumer Association of Malawi, Economic Association of Malawi, Malawi Economic Justice Network, Society of Accountants in Malawi, Malawi Microfinance Network, Bankers Association of Malawi, Malawi Congress of Trade Unions and Employers Consultative Association of Malawi. These can target specific groups such as secondary and college students, workers and micro-entrepreneurs.

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• It may also be important to integrate financial education programmes in some of the development programmes in Malawi that offer cash incomes. For example, the scaling-up of the social cash transfer provides a huge opportunity for improving financial literacy if financial education can be integrated. Similarly, public works programmes that are implemented by the Malawi Government through the Local Development Fund and GOM-EU provide avenues for reaching out to rural citizens on financial education. Where such programmes are utilized financial education should not be delivered to intended beneficiaries only but also other households in communities where these projects are implemented.

• In the medium to long-term, there is a need to revisit the education curriculum in primary and secondary schools so that basic financial skills and financial literacy are introduced in some of the life skills courses.

8.2.2 Monitoring and Evaluation The various interventions that will be put in place to improve financial inclusion and financial literacy will need to be monitored in the long term. Some of the issues that financial education may tackle will require behavioural changes which may take a long time. The baseline survey has been undertaken prior to the implementation of a national programme of financial education. There is a need for subsequent periodic national surveys on financial literacy and consumer protection that will determine the impacts of the various interventions that will be put in place to improve financial literacy and consumer protection in Malawi. Table 77 suggests 31 indicators that should be monitored after implementation of financial education and financial inclusion programmes. These indicators are grouped into financial literacy, financial education, financial consumer protection, products and services, money management and financial planning. The table describes each of the indicators with the baseline figure reported. This is a short list aimed at capturing progress on various interventions that may be put in place in order to improve financial literacy and financial consumer protection in Malawi.

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Table 77: Monitoring and Evaluation Indicators

Variable Indicator Description Baseline 2013

1) Financial Literacy 1) Division % correct answer 82.5%

2) Inflation % correct answer 57.1% 3) Simple interest rate % correct answer 19.1% 4) Compound Interest rate % correct answer 54.0% 5) Discount % correct answer 65.0% 6) Risk % correct answer 44.7% 7) Risk diversification % correct answer 37.9% 8) Financial Literacy Index % with 5 – 7 correct answers 28.3% 9) Knowledge - Interest rate % that know what it means 43.4% 10) Knowledge - Insurance % that know what it means 28.7% 11) Knowledge - Shares % that know what it means 28.8% 12) Knowledge - Stock

Exchange % that know what it means 7.5%

13) Knowledge - inflation % that know what it means 7.1% 14) Knowledge - Devaluation % that know what it means 14.4%

2) Financial Education 15) Programme Participation for specific interventions

% who have participated in financial education interventions

0.0%

16) Programme Listenership for specific interventions

%listened to different programmes

0.0%

3) Financial Consumer Protection

17) RBM Financial Protection % who have heard of RBM DCP 74.2% 18) Consumer Association % who have heard of CAMA 12.5% 19) Consumer Protection

Procedures % indicating approaching consumer protection institutions

46.7%

4) Financial Products and Services

20) Access to formal financial services

% with products and services in the formal sector

17.0%

21) Access to semi-formal financial services

% with products and services in the semi-formal sector

5.6%

22) No access to financial products and services

% without access to any financial services

34.2%

23) Bank accounts % with savings and deposit bank account

15.4%

5) Money Management

24) Saving some money % saving some money after basis expenses

76.2%

25) Place of saving money % saving some money at a bank 19.9% 26) Self-confidence in money

management % very confident in money management

55.8%

6) Financial Planning 27) Savings plans for old age % with savings and financial assets plans for old age

11.4%

28) Pension plan for old age % with own pension plans for old age

1.9%

29) Knowledge of pensions % who understand what pensions are

40.7%

30) Knowledge of the National Pension Scheme

% who have heard about the National Pension Scheme

10.0%

31) Knowledge of operation of National Pension Scheme

% that heard and have correct knowledge how the National Pension Scheme operates

49.7%

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