An Evaluation of the Degree of Financial Inclusion attained throughthe SHG Bank Linkage Program (SBLP) a Unique Model of

Microfinance Based Poverty Intervention in IndiaPaul Jose P1*

Vasanthakumari P2

1St. Thomas College, Thrissur, Kerala, India2. NSS College, Ottappalam, Kerala, India

Abstract

Microfinance is the developmental intervention devised after the failure of the directed credit programs world over. In India microfinance was adapted into the unique program of linking Self Help Groups of poor women to banks in the year 1992. It is visualized that the linkage of the poor women through SHGs with the formal financial institutions will also promote financial inclusion at the macro level, while providing a platform for encouraging entrepreneurial activities, and thus eradicating poverty. It has been twenty two years since the SBLP was adopted at the national level,and the program has witnessed exponential growth along the length and breadth of the country. The objective of the present paper is to assess how far the program has been successful in enhancing the level of financial inclusion in the economy. And, it also intends to devise a framework for making successful assessment of the objective. The paper concludes, after fitting a simple regression equation between two specially designed indices to measure the degree of financial inclusion and the level of SBLP in each state in India, that only less than one quarter of the financial inclusion level attained is explained by the program of SBLP and that any program to enhance financial inclusion has necessarily to be context specific, especially in a country like India which nests diverse interests and standards in every conceivable sphere of life.

Key Words: Financial Inclusion, Microfinance, SBLP, SHG

*Alappatt Palatingal House, Sweet Bazar Road, Irinjalakuda, Kerala, India, PIN 680121. Tel: 9496347172. Fax: 91480 2825708. E mail: jose_paul09@yahoo.co.in

1. Introduction

The failure of the interventions based on directed and subsidized credit aimed at dealing with poverty led to the emergence of a novel tool in the later decades of the last century, andsoon became the buzzword among the planners Microfinance. It was in Bangladesh where Microfinance was first tested on a large scale under the leadership of the Nobel Laureate Mohummad Unus. Soon the term Microfinance became familiar throughout the world as a trustworthy tool of poverty eradicationintervention in developing as well as developed world. Microfinance is essentially a scheme of granting small time loans coupled with other financial services like micro savings and micro insurance based on a hitherto unheard scheme of group liability of the poor especially poor women with the ultimate aim of enabling them to financing profitable entrepreneurial activities, which would eventually lead them out of poverty. Group Liability, which is the most important feature of microfinance, involves the coming together of women from homogeneous background into small groups with the common aim of fetching loans for supporting entrepreneurial activities from financing institutions based on the non collateral personal guarantee they provide on behalf of one another. Probably the driving force behind the implementation of the program of microfinance on a phenomenal scale supported by Government as well as private agencies like NGOs throughout developing world is the distinct understanding that savings and credit accessibility to the poor from formal sources can, as stated by Brar (2004), strengthen the links between financial inclusion, financial development, economic growth, and thus poverty alleviation. It is well established that financial exclusion results in non accessibility and non availability of funds from formal sources, which, in turn, will lead to dependence of, especially the poor, on high cost credit from informal sources such as moneylenders. Such dependence aggravates thelivelihood circumstances of the poor and drastically reduces the chances of getting out of

the quagmire of debt trap. It is against the backdrop of this possibility that the emergence of microfinance is to be viewed. The method of granting microfinance soon found many adaptations throughout low income and marginalized communities in Asia, Africa and America.

In India also an adaptation of microfinance intervention emerged; the SHG model whichensures access for the poor women to formal financial institutions step by step. At first, a group of 15 to 20 women from homogenous background form themselves into Self Help Groups self help in the sense that they come together to find ways to solve their financial and non financial problems which regularly meet and accumulate savings. At the second stage, they, preferably after a period of smooth functioning for six months, become eligible for formal linkage with a banking institution. Now the groups can open savings accounts and acquire the status of Savings Linkage. Finally, SHGs become eligible for microloans, which may run up to several multiples of the savings of the group. The loans are granted on the non collateral security generated by the mutual personal guarantee extended by one another.The SHGs, when granted microloans acquire the status of Credit Linkage with the bank. With the credit linkage, two objectives are met.First, it helps bring the hitherto unbanked poor within the coverage of financial inclusion and,secondly, provides finance for bringing up income generating activities and thus acquiring a decent and respectable living for the poor.Thus, the program of Linking SHGs with Banking Institutions - more popularly known as SHG Bank Linkage Program (here in after referred to as SBLP) widen the net of financial inclusion along with providing opportunities for the poor to improve their livelihood opportunities.

1.1 Progress of SBLP

SBLP, which commenced as a pilot program in India in the year 1992 with a linkage of 255 SHGs, has grown exponentially and provided

opportunity of access to regular savings and banking facilities to about 95.1 million households through 7.32 million SHGs and mobilized a savings of a whopping Rs.82.17 billion when the program completed 21 years in 2013. It is estimated that on an average only about 30% of the savings of the groups are reflected in the savings accounts, for only the balance after giving internal loans to members comes to banks as deposits. Of the households having access to banking facilities through the program, about 57.87 million are provided with credit facilities of a total of Rs.393.75 billion. Thus goes the growth of the SBLP, which is described as the largest microfinance program in the world (National Bank for Agriculture and Rural Development [NABARD], 2011).Apart from the exponential growth of the program, the other prominent feature displayed during the course of the progress of SBLP is its rather unusual concentration in the southern region of the country in terms of all the parameters of growth like the number of SHGssavings linked, savings mobilized and loans granted. For example, 55.46 percent of the total savings linked SHGs and 61.85 percent of the savings generated through SHGs in the year 2013 are from the southern region of the country, while the claim of the region in the credit linkage in terms of number of SHGs credit linked and loans granted is 69.35 percent and 84.35 respectively. And, another interesting element of the progress of the program is that the southern region claims the highest amount of average loan per SHGs. In 2013, the average loan outstanding per SHG in the southern region was Rs. 2.05 lakh whereas the Central Region, which comes next, had only Rs. 1.08 lakh as loans outstanding. And, it is time that an enquiry into the extent to which the program has contributed in achieving its major objective financial inclusion through the SBLP was undertaken.

2. Literature

Most of the literature on microfinance centers on the outcomes of the impact studies undertaken in various countries at the

participant level, which either argue for the positive impacts on the participants like reduction in: vulnerability (Zaman, 2000), incidence of poverty (Khandker, 2001),inequality (Beck, Demirguc-Kunt & Levine,2004) and gender based household violence (Schuler, Hashemi & Badal 1998) and increase in: business turnover and employment (Afrane, 2002), household income (Remenyi & Quinones, 2000) economic and social status (Schuler & Hashemi, 1994) and bargaining power of the participants in various spheres of life ( Cheston & Kuhn, 2002; Murray, Leonard & Kondo, 2007) or the negative impacts like:increase in debt burden (Rahman, 1999),encouraging unequal social structures based on hierarchies and inequalities in rural communities rather than challenging them (Wright, 2006), and benefiting the wealthier rather than the poorer (Coleman, 2006; Takahashi & Tsukada, 2010). Still very rare is to find literature on the macro economic impact of microfinance. Certain aspects like the impact of macro economic growth on the performance of Microfinance Institutions (Ahlin, Lin &Maio, 2011), impact of the intervention on the poverty reduction at the macro level (Imai,Gaiha, Thappa & Anim, 2012) and the impact on reduction of income equality and enhancing the welfare, (Cuong, Bigman, Berg & Vu,2007; Kai & Hamori, 2009) have been examined from a macro economic perspective in various countries. In India also studies are mainly centered on the benefits or drawbacks of microfinance program led by the SBLP. For example, Puhazhendi and Satyasai (2000),Todd (2001) and Chavan and Ramakumar (2002), were all praise for the positive impactsthe program generated on the participants along the length and breadth of the country, while some other studies brought out the negative aspects like the negative assortative matching among the members (Aniket, 2006) andperpetration of the conventional subordinate gender related roles of women in the household(Garikipati, 2008). Apart from the micro level impact studies, the impact of SBLP in themacro perspective in India is brought out mainly through two types of outputs: one is the

regular reports on the working of the program of microfinance in the country and the yearly State of the Sector Reports; and the other belongs to the attempts made by some to underpin the highly skewed spread of SBLP on the varying degrees of financial inclusion attained by the states in the country, e.g.,Sangwan (2008). However, both the attempts suffered from methodological weakness in as much as that the tools applied by them were insufficient to capture the influence of SBLP on the level of financial inclusion to the full extent. 3. Significance and Objective

Yet, there has been no worthwhile attempt to underpin the relationship between the microfinance intervention SBLP and the level of financial Inclusion in various states of India. India, being the country with the largest coverage of microfinance in the world, any proven pattern of outcome generated here can be the guiding light in future elsewhere. The purpose of the present paper is to fill this gap, and it is justified well considering the objective of SBLP which falls within the broad framework of microfinance intervention, i e., to promote financial inclusion while providing finance to undertake Income Generating Activities to support the livelihood requirements of the poor, especially women.And, this paper also aims to provide a framework for establishing the relation between a microfinance program and the level of financial inclusion in a country.

4. Framework for analysis

Constitutionally, India is a Union of 28 States and 7 Union Territories, and it lies to the north of the equator between 84' and 376' north latitude and 687' and 9725' east longitude.The system of governance is a federal form with a Union Government for the whole of Indian Union and 28 State Governments and 7 Union Territories (UTs) with separately identified functional domains for the Union Government and the other entities as per the

Seventh Schedule of the Constitution, which, in addition, highlights the critical role envisaged for State Governments in fulfilling the aspirations set out in the Directive Principles of State Policy. A Union Territory, except the two of Pondicherry and the National Capital Territory (NCT) of Delhi, is a special type of administrative division which is ruled directly by the Union Government. The UTs of Pondicherry and NCT of Delhi have elected legislatures headed by Chief Ministers.Generally, it is the domain of the State Governments to frame policies for the eradication of poverty in the States, and various State Governments have framed policies founded in Microfinance with a view to rooting out poverty. In the present analytical framework the UTs have been excluded for two reasons: it is found that considering the UTs at par with the States will cause a bias in the results of the analysis for the special status of UTs has enabled them to acquire a very higher status with regard several indicators selected for the analysis like the number of bank branches per 1000 square kilometers as compared to the other States, which will play exceptionally down the status of the other reasonably well performing states also.The framework for analysis involves two steps: The first step involves the designing of two indices for measuring the level of Financial Inclusion (Index of Financial Inclusion IFI) and the level of spread of SBLP (Index of SBLP - ISBLP) in the states in Indiarespectively. The former is constructed to measure the Financial Inclusion status of each State of the country over a period of five years from 2008 to 2012, whereas the latter is for measuring the level of attainment in the SHG Bank Linkage Program over the same period.SHG Bank Linkage Program is viewed as a vehicle for improving the financial access, especially of the poor; therefore, it is rightly presumed that there is great likelihood that SBLP has enhanced the inclusionary levels of the States. As the second step, a simple regression line is conceived with the Index of financial Inclusion as the dependent variable and the Index of SBLP as the independent

variable so that the extent of financial inclusion attained through SBLP can be determined with the outcomes of the equation.

4.1 Step I: Design of the two Indices (IFI and ISBLP)

The Index of Financial Inclusion (IFI) is the result of an attempt to develop a comprehensive measure of the status of Financial Inclusion in the states of India. The design involves the identification of dimensions and indicators of financial inclusion and devising of the tool of IFI. Multitudes of dimensions and indicators leading to measuring financial inclusion have been identified for cross country studies (World Bank 2014). It is not the dimensions, but the identification and proper measurement of indicators that poses problem in assessing the level of financial inclusion. Generally, level of financial inclusion is measured from the perspective of two dimensions: Dimension of Access to banking facilities and Dimension of Usage of banking facilities (Classens 2006). Dimension of Access is measured by the sub dimensions such as Geographical Penetration(GP), Demographic Penetration (DP) of Banking Facilities and Banking Penetration(BP). The Geographical Penetration (GP) of banking facilities as measured by the number of Bank Offices per 1000 Km2 is included in the computation of the Index of Financial Inclusion because measurement of the extent of inclusion in an economy necessarily involves the dimension of the number of banking facilities per unit of geographical area. Kempson, Whyley, Caskey and Collard (2004) have proved that the greater the distance from a bank branch the greater the chances for financial exclusion. Demirguc- Kunt and Klapper (2012) state that distance from a bank is much greater a barrier in rural areas.Kendall, Mylenko and Ponce (2010) also havemade use of bank branch density (both relative to population and geographic area) as a measure of the physical availability of the facilities. Demographic Penetration (DP) isjustified because easy availability of the

banking services to the people is an important measure of the level of financial inclusion. It is gauged by number of bank offices (per 1000 population). Banking Penetration (BP) is measured by the number of Deposit Accounts per lakh of population, and it is necessary for determining the level of acceptance of the facilities among the people. The number of Deposit Accounts includes all types of accounts Fixed, Current and Savings because possessing an account irrespective of the type brings the people into contact with a banking institution and can be broadly regarded as included. Only deposit accounts and not credit accounts have been considered for computing the Banking Penetration because when a person is sanctioned a loan, a savings account is opened in his name and the loan is transferred to the savings account which can be withdrawn in convenient sums; and no one walks away with the loan amount other than through an account in his/her name. It means each and every credit account will have an equal number of Savings accounts; therefore, counting Credit Accounts in the dimension of Banking Penetration will result in double counting the number of Accounts to the extent of Credit Accounts. Banking Usage (BU) is measured by the volume of credit and deposit as proportion of Gross State Domestic Product (GSDP) of each state. The use of the Dimension Banking Usage in the measurement of Financial Inclusion is justified on account of the fact that even in highly banked societies people with bank accounts may not be actively making use of the facilities offered (Kempson, Whyley, Caskey and Collard 2004). This fact makes measuring the actual use of the credit and deposit facilities offered by banks necessary to study the level of financial inclusion. 4.1.1 The Tool of IFI: The Index of Financial Inclusion (IFI) employed in the present paper is not the first attempt of its kind. It was Sarma (2008), who first attempted to develop an Index to measure the level of the Inclusionary trends in an economy in the global context, drawing heavily on the Human Development Index (HDI) which was part of the intellectual effort

led by the late Pakistani economist Mahbub ul Haq, who together with a group of scholars including Amartya Sen, the famous Indian Nobel laureate for Economics, incorporated the ranking system according to HDI in the Human Development Reports. Sarma incorporated the modifications suggested by Nathan, Mishra and Reddy (2008), who introduced an alternative approach for computing HDI at the final stage. Sarmas Index of Financial Inclusion is a composite of three sub dimensions: Banking Penetration (Dimension 1); Availability of Banking Services (Dimension 2) and Usage (Dimension 3), whereas the present one involves one more dimension Demographic Penetration. The other point of difference with Sarmas IFI is that the present Index of Financial Inclusion is the simple arithmetic mean of the four selected sub dimensional indices, whereas, Sarmas Index is computed according to the modifications suggested by Nathan et. al. (2008).

The Index of Financial Inclusion (IFI) is finally arrived at as follows in two steps. First, an index is calculated for each of the four sub dimensions explained above by dividing the difference between the actual value and the minimum value of the indicator for each dimension by the range concerned. This step helps in holding the value of each dimension between 0 and 1.

For the 28 states in India, Individual Dimensions of Composite Index of Financial Inclusion of stateth :

d (1) mMmA

,

}BU,BP,DP,GP{ , and

stateofdimensionofvalueactualA th

, statesofdimensionofvalueMaximumM

statesofdimensionofvalueminimumm

And, in the second step, the composite Index of the four sub dimensional indices is computed in the following manner:

BU,BP,DP,GP

d (2) ,41StateofIFI

4

1

th

4.1.2 The tool of ISBLP

The second step in the analysis is the formulation of an Index of SBLP (ISBLP). It is well known that there exist wide variationsbetween Indian states as regards the extent of spread of the program. As a result of which, the financial inclusion level achieved by various states will by all probability be different,therefore, any technique to rate the spread of SBLP must reflect certain distinctive characteristics of various Indian states like thepropensity of the members of SHGs to save and invest (because SHGs are formed basically with the imperative of generating internal savings); the boldness to undertake more debts,which necessarily reflects the low degree of risk aversion (because the objective of SBLP is to enable the poor to undertake entrepreneurial activities financed by the microcredit so that they will get rid of poverty) and the spread of SHGs throughout the diverse states in terms of the absolute number of SHGs (because it is the influence of state wise distribution of SHGs that is considered ultimately). Three distinct sub dimensional indices have been identified to reflect the above three imperatives: Index of Propensity to Save and Invest proxied by Average Savings per Member of SHGs for Each State (AS), Index of Entrepreneurial Competence (EC) proxied by average outstanding loan per SHG of each State during the period under study and Index of Penetration of SBLP (PS) proxied by the number of SHGs per thousand of population.

And, the ISBLP is computed exactly in the same manner as that of IFI in two stages. In the first stage, an index is calculated for the each of the three sub dimensions by dividing the difference between the actual value and the minimum value of the indicators selected for each dimension by the range concerned. For the 28 states in India, Individual Dimensions of Composite Index of SBLP of stateth :

(3) mMmA

d

}PS,EC,AS{ And

stateofdimensionofvalueactualA th

and , statesofdimensionofvalueMaximumM

statesofdimensionofvalueminimumm

And the composite index of SBLP is arrived at as follows:

PS,EC,AS

dState (4)31ofSBLPofIndex

3

1

th

5. Data and reasons for the Limitations in the Study

The study is solely based on the secondary data retrieved from various sources like Registrar General and Census Commissioner (2006) for the details on the population of India for various years, Planning Commission (2013) for the Gross State Domestic Product at current prices and various Reports of NABARD. The study period is limited to five years from 2008 to 2012 on account two reasons: first, the data regarding the various dimensions of SBLP recognized for this paper are available from NABARD only from 2008, and secondly, the details of the number of accounts, amount of

deposits and credit retrieved from Basic Statistical Reports of RBI are available only up to the end of 2012 at the time of drafting this paper. It is stated earlier in this paper that the Union Territories (UTs) have been excluded from considering for the analysis. Yet, the variables relating Pondicherry a UT which is culturally, geographically and linguistically closer to one of the major Southern States -Tamil Nadu - is added back to the corresponding figures of Tamil Nadu in the computation of indices and subsequent analysis, because, for the first two years such as 2008 and 2009, the secondary data figures of SBLP for the state of Tamil Nadu are inclusive of the figures for the UT of Pondicherry. And,for the three subsequent years, the NABARD started publishing separate details for Pondicherry. However, in order to maintain uniformity of data for the three subsequent years also, the data of Pondicherry are added back to Tamil Nadu for all the indices. Besides, certain estimations regarding the number of members of SHGs have also made for lack of details.

6. Results

Table no. 1 exhibits the details of the computations of IFI and ISBLP. The pattern of behavior of the two indices reveals certain interesting points. Goa claims the highest Index of Financial Inclusion, whereas the other states including the states of the Southern Region which are famous for the exorbitantly high concentration of SBLP do not come near the first ranking state of Goa in respect of IFI ranking. These rather contradicting features of the behavior of the two indices led to the further enquiry into the dynamics of the relation between SBLP and level of financial inclusion attained by the participating states. Acorrelation analysis between the IFI and the ISBLP for the years under study revealed that there exists a non - zero significant correlation,

Table No. 1 Showing IFI and ISBLP

State

IFI SBLP

2008

2009

2010

2011

2012

2008

2009

2010

2011

2012

Northern RegionHaryana 0.29 0.28 0.30 0.29 0.33 0.37 0.37 0.53 0.50 0.34Himachal Pradesh 0.30 0.29 0.30 0.26 0.32 0.17 0.28 0.26 0.30 0.32Jammu & Kashmir 0.22 0.19 0.20 0.16 0.21 0.36 0.24 0.48 0.12 0.19Punjab 0.45 0.43 0.45 0.43 0.48 0.27 0.22 0.25 0.22 0.30Rajasthan 0.14 0.12 0.12 0.10 0.11 0.11 0.22 0.19 0.16 0.20North Eastern RegionArunachal Pradesh 0.12 0.10 0.10 0.08 0.09 0.10 0.20 0.15 0.12 0.24Assam 0.13 0.10 0.11 0.10 0.11 0.13 0.22 0.29 0.21 0.26Manipur 0.03 0.01 0.01 0.01 0.01 0.10 0.08 0.16 0.40 0.10Meghalaya 0.14 0.12 0.13 0.11 0.14 0.17 0.17 0.17 0.13 0.16Mizoram 0.13 0.11 0.12 0.09 0.12 0.31 0.30 0.46 0.14 0.65Nagaland 0.04 0.02 0.02 0.04 0.03 0.18 0.42 0.14 0.16 0.23Tripura 0.14 0.13 0.14 0.13 0.15 0.19 0.34 0.41 0.34 0.53Eastern RegionBihar 0.15 0.15 0.15 0.14 0.14 0.17 0.23 0.23 0.11 0.17Jharkand 0.15 0.15 0.15 0.14 0.16 0.08 0.20 0.19 0.26 0.23Orissa 0.14 0.14 0.15 0.14 0.17 0.25 0.39 0.38 0.34 0.42Sikkim 0.23 0.23 0.19 0.17 0.20 0.21 0.46 0.14 0.17 0.21West Bengal 0.27 0.27 0.28 0.27 0.29 0.16 0.49 0.22 0.29 0.26Central RegionChatisgarh 0.07 0.10 0.11 0.10 0.12 0.20 0.22 0.19 0.18 0.21Madhya Pradesh 0.34 0.09 0.11 0.10 0.12 0.13 0.20 0.21 0.19 0.26Uttar Pradesh 0.21 0.19 0.20 0.19 0.21 0.19 0.26 0.24 0.22 0.33Uttarakhand 0.31 0.27 0.25 0.22 0.28 0.36 0.44 0.38 0.26 0.48Western RegionGoa 0.85 0.84 0.85 0.84 0.86 0.48 0.35 0.59 0.26 0.39Gujarat 0.22 0.20 0.21 0.18 0.21 0.21 0.20 0.28 0.15 0.17Maharashtra 0.42 0.41 0.41 0.40 0.43 0.15 0.35 0.21 0.24 0.34Southern RegionAndhra Pradesh 0.25 0.24 0.26 0.24 0.28 0.44 0.63 0.60 0.53 0.70Karnataka 0.35 0.34 0.36 0.32 0.21 0.40 0.42 0.41 0.46 0.69Kerala 0.52 0.50 0.51 0.49 0.43 0.26 0.50 0.36 0.47 0.62Tamil Nadu & Pondicherry 0.35 0.35 0.36 0.33 0.39 0.60 0.73 0.50 0.43 0.50

therefore, it is decided to run the regression between IFI (dependent variable) and ISBLB

(Independent Variable). The regression results are given in table no.2.

Table No. 2. showing year wise Regression Equations

year Regression Line R2 P Value2008 SBLPIFI 069808.0 0.28 0.003

2009 SBLP..IFI 45300799 0.15 0.039

2010 SBLP..IFI 63300398 0.27 0.004

2011 SBLP..IFI 46600956 0.12 0.072

2012 SBLP..IFI 57500607 0.23 0.010

7. Conclusion and DiscussionThe table no.2 shows that, except for 2008 and 2010, only less than a quarter of the financial inclusion level attained is explained by the program of SBLP. The year 2011 has witnessed an exceptionally low contribution of SBLP towards financial inclusion, probablybecause of the microfinance crisis in the year 2010 which had serious repercussions in India also. Microfinance program is recognized as amedium of poverty reduction by first bringing the poor under the net of financial inclusion. Itis only logical to assume that a program like SBLP will massively contribute to enhancing financial inclusion in the country. But, the results here show that microfinance program promoted by SBLP in a country like India cannot be the only solution for financial inclusion related issues; rather the results here testify to that any program to enhance financial inclusion has necessarily to be context specific. Depending solely upon a single program like SBLP need not deliver the intended results.And, in a country like India, where a vast majority is outside the net of financial inclusion, coupling other programs with microfinance interventions only will bring out desired level of total inclusion.

Acknowledgements: The authors thankfully remember the suggestions made by Dr. Antony P. L who playfully hold out that social science people seldom understand Math. The first

author, under no circumstances, will share the errors

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