Report No. 443 14 - A 0

ANGOLA Investment Climate Assessment

October 2007

Regional Program for Enterprise Development (RPED) Finance and Private Sector (AFTFP) Afiica Region

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TABLE OF CONTENTS

LISTING OF BOXES. FIGURES AND TABLES ................................................................... m ......................................................................................................... ACKNOWLEDGEMENTS V ........................................................................................................... EXECUTIVE SUMMARY 1

INTRODUCT'ION ......................................................................................................................... 5 ........................................................................................... Objective and Rational of the Report 6

....................... 1 SOCIAL CONTEXT AND MACROECONOMIC BACKGROUND 11 ................................................................................... 1 . 1 Socio-geographic Characteristics 11

1.2 Policy choices and structural changes ............................................................................ 15 1.3 The Economic Outlook: Oil Is Well That Ends Well ..................................................... 17

.............................................................................. 2 THE BUSINESS ENVIRONMENT 22 ............................................................................ 2.1 Formal Sector: Perceived Constmints 22

...................................................................................................................... 2.2 Electricity 2 6 .................................................................................................. 2.3 Corruption and Crime 2 8 .................................................................................................. 2.4 Regulatory Eramework 32

............................................................................ 2.5 Transportation and Other Constrai$s 34 3 MICRO FIRMS ............................................................................................................... 37

3.1 Constraints to Business .................................................................................................. 37 ..................................................... 3.2 Comparison between formal sector and micro firms 42

4 FACTOR MARKETS: FINANCIAL SECTOR, LABOR AND LAND MARKET ......................................................................................................................... 45

4.1 The Financing of Firms in Angola ................................................................................. 45 4.2 The Formal Labor Market in Angola ............................................................................. 50 4.3 Land Market ................................................................................................................. -57

5 MANUFACTURING AND FIRM'S PRODUCTIVITY ............................................. 60 5.1 Labor Productivity and Labor Cost ................................................................................ 60 5.2 Total Factor Productivity and Investment Climate Determinants .................................. 63

6 SYNTHESIS OF RESULTS AND POLICY RECOMMENDATIONS ..................... 66 .................................................................................................. 6.1 Constraints to Business 66

6.2 Financial Market .........A. ................................................................................................ 66 ................................................................................................................... 6.3 Productivity 67

6.4 Policy Recommendations .............................................................................................. 67 ........... ANNEX A: TECHNICAL APPENDIX FOR PRODUCTIVITY cALcULA~~ONS 76

LISTING OF BOXES, FIGURES AND TABLES

Boxes:

1 What is an Investment Climate Assasment?

Page

12

Listing of Figures:

Oil Dependency for Selected Countries Evolution of Angola's Real GDP Per Capita, 1960-2004 Angola: Real GDP growth (1990-2006) Progress in Macroeconomic Indicators curbing Inflation Tradable and Nontradable Inflation Rates

2.1 Top 6 Major or Very Severe Constraints as Reported by All Formal Sector Finns in Percentages 2.2 Costs of Security and Theft - International Comparisons 3.1 Percentage of Firms Reporhng Major or Very Severe Constraints (Top 6 Constraints for Forrid

Sector) - Formal Sector versus Micro Firms 3.2 Indmx-2 Costs - Formal Sector versus Micro Finns 5.1 Labor Productivity - International Comparison 5.2 Labor Cost per Employee (U.S. Dollars) - Manufacturing Sector 5.3 Unit Labor Cost - International Comparison - 5.4 Capital per Employee - International Comparison 5.5 Total Factor Productivity - International Comparison

L i g of Tables:

Sample Descriphon Basic Poverty and Social Indicators Composition of GDP by Sector, 1966-2004 Major or Very Severe Cons@ahts as Reported by All Formal Sector Firms in Percentages Major or Very Severe Constraints as Reported by Manufacturing Sector Firms in Percentages Major or Very Severe Constraints as Reported by Finns - Comparison Across Countries Indirect Costs - Manufacturing Sector Indirect Costs - Manufacturing Sector - Comparison across Countries I n h c t Costs - All Formal Sectors infrastructure Indicators - All Formal Sectors Inhstructure Indicators - Comparison across Countries Common Percc@on Index - 2007 Perception of Govenunent and Regulations - All Formal Sectors Court System - All Formal Sectors Security Services and Security Expenditure - Comparison across Countries - Manufacturing

Sector Regulatory Burden - All Formal Sectors Regulatory Burden - Comparison across Countries Licensing Process Licensing Process - Comparison across Countries Starting a Business Licenses Inventory Holdings of Most important Input - Manufacturing and All Sectors Percentage of Inputs Delivered by Road - Manufacturing Sector Origin of Inputs - Manufacturing Sector Customs - Manufacturing Sector - Comparison across Countries Trading Across Borders

Major or Very Severe Constraints as Reported by Micro F m s in Percentages Indirect Costs - Micro Firms hhstmcture Indicators - Micro Finns Perception of Govenunent and Regulat~ons - Micro Firms Court System - Micro Firms Security Services and Security Expenditure - Micro Firms LicensinglRegistration - Micro Firms Percentage of Firms Reporting Major or Very Severe Obstacles to Registering a Business - Micro Films Regulatory Burden - Micro Firms Licensing Process - Micro Firms Regulatory Burden - Formal Sector versus Micro Firms Perception of Govenunent and Regulations - Farmal Sector versus Micro F h s Mastructure Perceptions - Formal vs Micro Firms Sources of Short-term Finance in the Formal Sector Sources of Long-term Finance in the Formal Sector Sources of Finance - Formal Sector versus Micro Finns Sources of Short-term Financing - Comparison with other Countries Sources of Long-term Financing - Comparison with other Counties Access to Credit in the Formal Sector Access to Credit - Comparison with other Countries Collateral - Formal Sector versus Micro F h s Collateral - Comparison with other Countries Cost of debt and duration - Comparison across Counties Reasons for Not Applying for Loans - Formal Sector Loan ApplicationlRejection Labor Regulations Employment: Full-time Permanent Workforce - All Formal Sectors Employment: Full-time SeasonalRemporary Workforce - A1 I Formal Sectors Description of Workforce - Manufacturing Sector Unionized Workforce - Manufacturing Sector Average Educational Attainment of Production Workers - Manufacturing Sector Average Educational Attainment of Production Workers - Comparison across Countries - Manufactunng Sector Firms offering Training - Manufacturing Sector Firms offering Training - Manufacturing Sector - Comparison across countries Absenteeism - All Formal Sectors HIV Prevention Activities - All Formal Sectors Determinants of Earnings - Manufacturing Sector Labor Productivity (US Dollars) - Manufacturing Labor Costs per Employee (US Dollars) -Manufacturing Production Function Estimates Total Factor Productivity Extended Production Function Estimates Effects of Access to Finance Effects of Electricity Effects of Business Licenses Effects of Crime Effects of Cormphon Effects of Transportation

ACKNOWLEDGEMENTS

This report was pqared by a team lead by Giuseppe Iarossi (AFTPS) and comprising of Francisco Galrao Carneiro (OPCCE), Ricardo Gonplves (AFTPS), Sofia Silva (AFTPS), and Tania Olivein (AFTPS). David Shiferaw (AFTPS) provided invaluable research assistance. Olivier J. Lambert (AFTFS), Thomas Muller (AFTFS), Abdelmoula M. Ghzala (AFITR), and Stephan KL. von Klaudy (FEU) contributed to the policy recommendations. Comments and suggestions were received by Maria Margarida Baessa Mendes (AFMAO), Alberta Chueca Mora (AFMAO), Gilberto de Barros (AFTPS), Vjgayanti Desai (CSMPF), James Habyarirnana (AFTPS), Melanie Mbuyi (AFTPS), Joyce Msuya (CAFSC), Christopher Porter (AFMAO), Manju Shah (AFTPS), Dileep Wagle (AFTPS), and the participants to the concept note review and ICA review sessions. The authors are also grateful for comments received at the workshops held in Luanda in July 2007 by representatives from the Govenunent of Angola, The Catholic University, private large companies, SMEs, and the donor community, including Tharaldsen Paul Sverre (Norway Embassy). Official peer reviewers were Jose Guilherme Reis (LCSPF), Babatunde Onitri (CAFSS), Joyce Msuya (CAFSC), and Septime Martin (Aliican Development Bank). We are grateful to USAID for contributing to the cost of data collection.

EXECUTIVE SUMMARY

Since the peace accords of 2002, Angola has witnessed a surge in gross domestic product. The growth rate of real GDP increased fiom 3.4% in 2003, to 15% in 2006 due in large part to the increases in oil production and revenue. Increased oil production fiom new oil fields is expected to push Angola's GDP growth rate to approximately 30% in 2007.

Angola's macroeconomic stabilization efforts have been commendably successful. Following the adoption of the September 2003 stabilization program, Angola's annual price inflation has consistently fallen fiom its 2002 level of 100%. In 2005, Angola's 12 month consumer price inflation was 18.5%. In addition, significant increases in oil revenues have allowed for a government budget surplus of about 7% of GDP in 2005.

The lack of linkages, however, between the capital and technology intensive oil sector and the rest of the economy has meant that non-oil sectors have not experienced equivalent growth. Moreover, Angola's heavy dependence on the oil-sector, which contributed to over 91.92% of exports in 2004 and over 80% of the state budget, and the dramatic increase in Angola's real effective exchange rate', has nnpeded the development of Angola's manufacturing sector.

Despite the favorable outlook in terms of mineral wealth, the Angolan economy will not enter a path of sustainable shared growth without some necessary structural reforms. Because of the long civil war and of the effects of the strong dependence on oil and diamond revenues, the private sector has not evolved outside of the mineral sectors and the quality of the country's institutions remains low. The combination of this state of affairs creates constraints to private sector development and for the diversification of the economy.

Angola's Investment Climate Assessment (ICA) looks in detail at factors constraining the private sector, such as the effective hctioning of the product markets, financial market, infrastructure services, and the country's legal, regulatory, and institutional environment. The ICA also provides the analytical framework to identi@ reform priority by linking constraints to h level costs and.productivity.

The Angola ICA report is largely based on results from a survey of 310 firms in the non-oil private sector, representing a population of 839 firms in the manufacturing and services industry in Angola.' The sample included small medium and large f m s located in Luanda, Benguela and Huambo. The survey also included 115 micro-hs. As benchmarks, the survey utilizes comparator countries and comparator country-groupings. The comparator countries include: Algeria, Democratic Republic of Congo (DRC), South Africa, and Namibia, while comparator country-groups include: low income, Sub-Saharan Africa, and resource-rich countries.

Key Investment Climate Constraints

Access to credit is viewed as one of the most significant constraints in Angola with over half of surveyed firms reporting it as a major or very severe constraint. Small and medium-sized

' IMF estimates point to an over 40% increase in Angola's real effective exchange rate for the two years ending 2005

Source: INE 2003 census.

firms, and firms located outside of Luanda reported access to credit to be particularly constraining. Retained earnings constitute the main source of working capital and long-term finance of firms in Angola. The banking sector accounts for only 1 % and 4% of a typical h ' s total short-term and long-term financing needs respectively. Firms in Angola rely more on internal b d s and less on banks than firms in Sub-Saharan Afiica. Similarly, only 2% of firms in Angola have an overdraft, compared to and average of 35% in the continent.

Cost of finance is not a problem for Angola's firms. Interest rates and collateral requirements are comparatively attractive in Angola compared to the other countries. Collateral requirements and interest rates on loans are more favorable in Angola than in the DRC, South Afiica, Algeria, Namibia, and the country-group comparators. However with about 79% of loan applications in Angola rejected, the problem of access to credit is related to availability and not cost of credit.

The complexity of the application process and unacceptability of collateral are the principal reasons for low banking penetration in Angola. Over 80% of firms in Angola do not apply for a loan. One third of them do no apply because the application process is considered too complex. Similarly of those that applied for a loan over one third was rejected because the collateral provided was considered unacceptable by the bank.

Electricity is the main driver of indirect costs and affects the manufacturing sector more than other sectors. Almost half of the firms consider availability of energy a major bottleneck. Urnliability of electricity costs on average 4.6% of sales to a typical Angolan firm. In Angola 84% of all firms experienced power outages, on average 8 times per month. Electricity-related indirect costs affect more heavily large firms (9.8% of total sales), domestic h s (4.8% of total sales) and firms based in Luanda (4.9% of total sales). Generaton, a costly alternative, thus, are owned by almost 70% of h s and provide approximately 3 1% of electricity needs.

Manufacturing fulns and firms outside of ~uanda contend transportation to be a signif~cant constraint to business. Manufacturing firms in Angola lose 2.1% of their production in transit, a percentage higher than in all comparator countries (except Algeria). In addition, with imports representing 40% of manufacturing sector inputs, the average number of days to clear custom is 28 days comparatively the highest than in Sub-Saharan Afiica,. Moreover, for firms outside of Luanda limited access to roads is problematic.

Corruption is considered a signif~cant bottleneck by fvms In Angola. Close to 40% of them view corruption as a major constraint, particularly large h s . Moreover, 40% of large firms report informal payments or gifts to be common '%I get things done". Corruption appears to be problematic within the court system as almost 90% of firms believe it to be unfair, partial, and corrupted. Furthermore ICA results indicate that only 23% of firms agree with the statement that laws are consistently and predictably interpreted. In the manufacturing sector, firms in Angola incur indirect costs due to corruption for 3.4% of sales, which is lower than Algeria (7.9%) and DRC (5.1%), but greater than low income (3.1%), Sub-Saharan Africa (2.5%), and resource-rich countries (1.9%). Angola's low ranking of 147 out of 169 in Transparency International's 2007 Corruption Perception Index confirms the ICA's results.

Although demonstrating a positive trend since 2000, Angola's regulatory environment remains problematic for business. On average close to 8% of senior management time is spent with government regulations. Although comparable with other countries in the region, this burden

falls disproportionately on large (14.6%) and foreign (10.2%) firms, as well as firms in the retail sector (12.9%). Business licensing and permits are reported as major or very severe constraints by a greater proportion of firms in Angola than low income, Sub-Saharan Africa, and resource-rich comparator-groups of countries. In the Doing Business indicators of 2008, Angola is ranked in the last decile in regulatory quality. Although the establishment of the Guichet Unico has improved Angola's performances on regulatory requirements to begin a business, the costs needed to start a business in Angola are higher than all comparator countries (except the DRC) and country-group averages.

Obtaining licenses is still a lengthy process for some firms in Angola. Construction-related permits necessitate more than 3 months for large firms, but only 27 days for small finns. In addition, obtaining an import license takes on average 23 days for small firms, but requires 2 months for large firms. The time and costs needed to build a warehouse in Angola are the highest in the continent (with the exception of DRC regarding costs).

These constraints have a direct impact on costs and productivity of Angolan firms. Value added per worker in manufacturing enterprises in Angola is relatively high at around $5,000. Angola performs better than most comparator countries except South Aliica, Namibia, Swaziland, and Botswana. On the other hand, Angola has high labor cost, at approximately $3,000 second only to Namibia and South Africa. The share of value added represented by labor cost in Angola is the highest in all comparator countries. Addressing the major constraints faced by firms in Angola will improve their productivity. Electricity, bribes, security and theft account for up to 10-1 2% of sales lost in 2006. Labor productivity and total factor productivity will increase by 6-8% if access to credit is improved, electricity is more reliable, or corruption is reduced. Similarly our survey data shows that sirnpliflmg the regulatory environment can have an even higher impact on firm productivity.

Recommendations:

1. Electricity

Improve the monitoring and regulation of the electricity system. Review options for private participation in management contmcts and investments. Separate generation, transmission and distribution. Ensure operability of independent regulator responsible for price setting. Increase energy generation.

2. Credit

Enhance credit information infrastructure. Upgrade corporate registries, collateral registries, and public record systems. Facilitate the establishment of private credit bureaus. Reform collateral law and improve court efficiency. Strengthen accounting framework, enhance disclosure requirement.

3. Corruption & Regulation

Declare political will to fight corruption, make resources available and establish an Anti Corruption Agency. Increase effectiveness of GUE by reducing the cost of starting a business. Reduce costs to execute notary deeds. Reduce time required to obtain

Commercial Operations Permits and the registration with the Registry of Companies. Build up capacity for the Voluntary Arbitration Law. Shorten time to obtain licenses fiom the Provincial Governor and real estate registry. Reduce sot of inspections. Establish information system in the judiciary.

INTRODUCTION

Successive armed conflicts, which lasted almost three decades after independence, have devastated Angola and its economy. However, since the peace accord of April 2002, Angolans have begun a transition toward national reconciliation and lasting peace. For the Government of Angola (GoA), one of the main challenges ahead is to reconstruct the economy and reunite society after a war that has left its most visible marks on the millions of displaced that are returning to their areas of origin and demobilized former combatants that will need to be reintegrated into society. Peace in Angola has come hand in hand with a surge in GNI~ per capita over the past years: per capita GNI rose from USD 470 in 2001 to about USD 1,980 in 2006, primarily as a result of increased oil production and revenue. Even though the national income is currently above the average level in Sub-Saharan Africa, Angola was nonetheless ranked 16 1 st out of 177 countries in the UN Human Development Index (HDI) of 2 ~ 6 . ~ This underscores the magnitude of Angola's challenges in the social sphere.

Over the period between 1990 and 2001, GDP growth exhibited an irregular pattem that is largely explained by fluctuations in domestic oil production and its international market price. In 2002 growth peaked at 13 percent, thanks largely to the peace agreement and to strong growth in oil production. Growth, however, slowed in 2003, but surged by 11.2 percent in 2004, largely reflecting, once again, developments in the oil sector. Because of few linkages between the capital and technology intensive oil sector and the rest of the economy, non-oil sectors have not shown such growth rates. The economy's dependence on oil is further demonstrated by the fact that it contributed to nearly 50% of all GDP in 2004, whereas services contributed 32% and manufacturing just 4.2%. Additionally, oil accounted for 91.92% of exports in 2004 and contributions of the oil sector to the state budget exceeded 80 percent.

Angola is one of Africa's most resource-rich countries. It is Sub-Saharan Africa's second largest producer of oil and the world's fourth largest producer of diamonds, with over 12% market share. In addition, Ahgola is endowed with other minerals, plenty of water for hydroelectric power and irrigation, vast fertile lands, and abundant timber and marine resources.

The capital-intensive oil sector, mainly located offshore, accounts for about 50 percent of GDP. The formal non-oil economy is dominated by trade and commerce and non-tradable services. The agricultural sector's contribution to GDP rose from 8 percent in 2004 to 10 percent in 2006, but it is still far from the 24 percent levels of 1991. Much of the explanation for the rise in food production has been the return of displaced people after the war. The informal sector has become extremely important mainly due to the disruption caused by the civil war. It is estimated that almost 70 percent of existing jobs are in the informal sector.

3 Gross National Income (GNI) pzr capita using the A t h method ( c a n t US$).

4 The UN ednmes that 154 out of 1,000 infane die in their fnst year of life compared with 91 for Sub-Saharan African as a whole and 41 percent

of all children under five are chronicaUy malnourished The Survey on the Family Aggregate about Revenues and Expendihrres O R ) underbken in

2000-2001, revealed that the poverty incidence was 68 percent of the population wih 28 percent of individuals in extreme poverty situation or destitute.

Rural povelty has been estimated at 94 percent (ECF', 2003).

The GoA has been taking stock of the current situation and released in 2004 the final version of The Estratkgia de Combate a Pobreza (ECP), Angola's Poverty Reduction Strategy Program. The ECP is in its final stages of revision and finalization. It states as its major objective the need to consolidate "pace and national unity through the improvement of life conditions of the Angolan citizens, those that are more vulnerable, by motivating them to actively participate in the social economic development process". For this, the GoA is determined to 'reduce the incidence of poverty by half by 20 15 from its 2000-2001 level of 68 percent and acknowledges that although support from other donors is needed, private sector participation is essential.

The World Bank's Interim Strategy Note (ISN) of February 2005 was set to support the government's program for 2005-2006' and emphasized the need to encourage the Private Sector's role through a stronger publiclprivate dialogue h e w o r k and a more propitious operatin % environment for the private sector. The World Bank's ISN of May 2007 reinforced this need , whilst at the same time recognizing that there has been progress: "[the GoA] ... has adopted legislation to streamline the regulatory framework and clan@ land rights and has improved customs procedures (reducing the average paperwork processing time from 25 days in 2000 to 5 in 2006). It has also taken steps to improve access to financial services, including microfinance, by allowing new entrants into the market. Investments in infrastructure, including roads, railways, and electricity generation and transmission will also improve the investment climate."

The Regional Program on Enterprise Development (RPED) of the World Bank Africa Private Sector Group agreed to conduct an Investment Climate Assessment (ICA) in Angola

Objective and Rational of the Report

Work to improve the investment climate is recognized as a key pillar of World Bank Group work to promote economic growth and poverty alleviation in developing count~ies.~ The main focus of Investment Climate Assessments (ICAs) is on microeconomic and structural dimensions of a nation's business environment, viewed in an international perspective (See Box 1). To this end, ICAs look in detail at factors constraining the effective functioning of product markets, financial and non-financial factor markets, and infrastructure services, including in particular weaknesses in an economy's legal, regulatory and institutional h e w o r k . ICAs also provide the tools and

5 The World Bank's Interim Sbategy Note 0 of February 2005 was set to supprt the government's program for 2005-2006 arcund three pillars

i) enhancing transparent governance and intensifying capacity develop en^ ii) providing basic senices (especially for retumeg, excombatanis, and

other vulnerable groups) and rehabilifation of emergency -, and iii) supporting brondhsed equimble growth, W a U y through

impmvemenis in the e n v h m m t for private sector growth.

6 The World Bank's Interim Strategy Note of May 2007 is organued around three pillars: (a) strengthening public sector management and

government institutional capcity, @) supponh.lg the rebuilding of critical inhastructure and h e improvement of service delivery for poverty reduction,

and (c) promoting growth of nonmineral sectors.

7'The cen!nl challenge in reaping greater benefiis h m globaJization lies in improving the investment climate - that is, in providing sound regulation

of indusm, imludimg the promotion of w m p o n ; in overcoming bureaucratic delay and ineficiency; in fighting cormpion; and in improving the

quality of hhtnctums. While the investment climate is clearly important for large, formal sector firms, it is just as important - if not more so - for

small and medium enterprises (SMEs), the informal sector, agricultuml productivity, and the generation of off-firm employment Fore these reasons, the

invesrment climate itself is a key issue for poverty reduction." Nicholas Stem, Chief Economisf March 22,200 1.

analytical b e w o r k to identify reform priorities in a country's investment climate, by linking constraints to firm-level costs and productivity. The main objective of this report is to develop a better understanding of the investment climate constraints that limit the growth and competitiveness of Angolan firms. In particular, the report seeks to measure in a standardized way the investment climate conditions in Angola, to provide comparisons of these conditions with those prevailing in other countries and regions, and to identify the features of the investment climate that matter most for competitiveness and growth. While we recognize that issues related to macroeconomic and political stability are crucial for constituting a good investment climate, the focus of this report is on microeconomic issues. Indeed, the importance of political economy and macroeconomic issues is now well understood, and they have been addressed at length in other World Bank reports.*

BOX 1: What is an Investment Climate Assessment?

Investment climate assessments systematically analyze the conditions for private investments and enterprise growth in a country, d r a ~ g on the experience of local firms to pinpoint the areas where reform is most needed to improve the private sector's productivity and competitiveness. By providing a practical foundation for policy recommendations and involving local partners throughout the process, the assessments are designed to give greater impetus to policy reforms that can speed the private sector's growth.

Produced by the World Bank Group in close partnership with a public or private institution in each country, the investment climate assessments are based on a survey of private enterprises designed to capture firms' experience in a range of areas - financing, governance, regulation, tax policy, labor relations, conflict resolution, hbastructure services, technology, and training, among others. All these are areas where difficulties can add substantially to the costs of doing business. The survey attempts to quantify firms' costs related to the investment climate bottlenecks. Using a standard methodology, the assessments then compares the survey findings with those in similar countries to evaluate how the country's private sector is competing.

The findings of the survey, combined with relevant information from other sources, provide a practical basis for identifjmg the most important areas for reform aimed at improving the investment climate. The findings and policy recommendations emerging from the assessments are discussed extensively with the private sector and other stakeholders in the country. This broad dissemination of the findings is aimed at engaging not only policymakers but also business leaders, investors, nongovernmental organizations, and the donor community in shaping the national private sector development strategy, forging consensus on the priorities for reform of the investment climate, and laying the groundwork for concrete responses to the problems identified.

Source: World Bank (2003), Improving the Investment Climate in Bangladesh.

See World Bank (2006a), "Angola Country Economic Memorandum" (CEM); and World Bank (2002b) ''Cowmy Rocurement Assessment R q f l (CPAR)

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The Investment Climate Survey Questionnaire

Two survey instruments were used. The first one is the standard RPEDACA questionnaire for the formal sector which is composed of three parts:

The first part is designed for general managers or business owners and deals with the internal structure of businesses and the investment climate within which they operate, including bureaucratic obstacles and infrastructure constraints;

The second part deals with finance, production and markets and provides information on business performance as well as human resources and labor market issues.

The last part includes a small questionnaire for a sample of up to 10 workers per business. This data facilitates an understanding of the interaction between firm peifonnance/business climate and labor market outcomes.

A second survey instrument was used for gathering data fiom micro firms (firms with less than 5 full-time employees). Given the characteristics of the sample, it is a lighter version of the standard ICA questionnaire, mainly looking at investment climate data and a basic set of financial data.

The Investment Climate Sample

The World Bank Enterprise Survey in Angola targeted establishments located in Luanda, Benguela, and Huambo in the following industries:

1. Manufacturing: Food and Beverages 2. Manufacturing: Garment 3. -Manufacturing: Other Manufacturing 4. Retail Trade 5. Rest of the universe, including:

Construction Wholesale trade Hotels, bars and restaurants Transportation, storage and communications Computer related activities

The survey also sampled a selection of micro establishments (establishments with less than five full-time permanent paid employees) from the targeted universe, without stratification by industry.

The total sample size was 425 as described in table 1.1. The population fi-ame for establishments with five or more full-time paid permanent employees consisted in a population of 839 establishments. A list of manufacturing establishments in Luanda was obtained from the INE (National Statistical Office), but no suitable lists of establishments could be sourced for the other two strata, or for any strata in Benguela and Huambo. Therefore a list of establishments was compiled in the field by walking through the industrial and commercial zones of each of the target

cities, and identifying establishments likely to have five or more employees. The resulting list was combined with the manufacturing list for Luanda to yield the sample frame.

Table 1.1 : Sample Description

Size Ownership Location

Sector Total Small Medium Large Foreign Domestic Luanda Outside*

Economy 425 367 53 5 67 358 348 77

Manufacturing 2 15 178 32 5 18 197 177 38

Micro-firms 115 10 105 98 17

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* Benguela and Huarnbo

Finally, the micro establishment stratum covers all establishments of the targeted categories of economic activity with less than 5 employees. For many reasons including the small size of establishments, their expected high rate of turnovers, the high level of "informality" of establishments in many activities and consequently the difficulty to obtain trustworthy information from official sources, an aerial sampling approach to estimate the population of establishments and select the sample in this stratum for all regions of the survey.

Structure of the Report

Section 1 provides the social context and macroeconomic aspects of Angola. Section 2 deals with formal firms' perception of the economic environment they operate in. We analyze the results of the ICA survey and other countries' ICA surveys (the comparator countries are Democratic Republic of Congo (DRC), Algeria, South Africa and ~ a m i b i a ) ~ in order to (i) identify and compare indirect costs of doing business in Angola, (ii) identi@ and compare firms' perception of the main constraints to business, (iii) identify and compare government-driven constraints, (iv) quantify and compare the impact of corruption and crime on firms' operations and (v) identify and compare infrastructure-driven constraints.

Section 3 follows the same structure of section 2, but deals mainly with the micro firms. In particular, not only does it focus on points (i) to (v) (see above), but it also compares formal sector firms with micro firms in Angola.

9 The selection of Algeria, d~ Democratic Republic of Congo @RC) and Namhia as comparator cwmies is based on the that they are each

resource-rich, and at varying levels of development. In addition, DRC and Namibia are neighboring and possible cornpentor countries. Cornparism

with SubSaharan African avenges are made where data is available.

Section 4 analyzes factor markets, namely labor, finance and land. It relies mostly on ICA survey data (Angola and comparator countries) in order to better understand the hctioning of each market and the main constraints associated with it.

Section 5 looks at labor and capital productivity of manufacturing h s in Angola and quantifies Total Factor Productivity (TFP). It also analyzes the impact of the various constraints to business on TFP and labor productivity.

Finally, section 6 contains a synthesis of the main results and our policy recommendations.

1 SOCIAL CONTEXT AND MACROECONOMIC BACKGROUND

1.1 Socio-geographic Characteristics

The Republic of Angola is, after the Democratic Republic of Congo and Sudan, the third largest nation south of the Sahara. It has an area of 1,276,700 sq. km (including the 7,270 sq. km of the oil-rich Cabinda enclave) and is the largest Portuguese speaking African country.

The country's relative climatic diversity represents an advantage and hints at huge potential for agricultural development. Angola's location in the intertropical and subtropical zones of the Southern hemisphere, its proximity to the sea and the cold Benguela stream, and its topographical characteristics are the factors which create two distinct climate regions with two seasons: the dry and cool season (from June to September) and the hot and humid season (from October to May). The northern region from Cabinda to Ambriz has a humid tropical climate with heavy rainfall, while the region from Luanda to Namibe (Mqamedes) has a moderate tropical climate, with the rainfall reduced on the coast by the Benguela wind stream. The southern strip between the plateau and Namibia has a desert climate, given the proximity to the Kalahari, with irregular rainfall between 600 and 1000 mm. annually. Temperatures average 23 degrees C in the north and the coastal areas, and 19 degrees C in the interior. The relative climatic diversity, due to variations of altitudes across the country, allows for the growth of crops from both tropical and relatively more temperate zones.

The vast and diverse territory hosts a large concealed economic potential. Among the abundant natural resources there is plenty of water that provides for hydroelectric power plants and irrigation; amid mineral resources there are abundant oil, diamonds, iron, quartz, ornamental stones and phosphates. In the Cabinda region, very dense forests predominate (Maiombe forests) with economically important timbers such as black wood, ebony, African sandalwood, and ironwood. With a coastline of 1,650 km, Angola's waters are rich in fish, mollusks, and crustaceans. The main petroleum basins under exploration are located near the coast of Cabinda and Zaire provinces. The main diamond producing area is located in the Lunda Norte province. Unfortunately, due to the nonexistence of proper and comprehensive geological surveys, the whole mineral potential ofAngola is, to this date, vastly unknown.1°

The Angolan population is young and growing rapidly. Recent population figures are difficult to obtain due to the lack of a full national census. A limited census was carried out in the province of Luanda in 1983, which was extended to the provinces of Cabinda, Namibe and Zaire in 1984. War-related problems made it impossible to carry out a national census. In 1980, according to official estimates, the population reached 7.7 million. Though data is scanty, the population was projected to grow at an annual rate of 2.9% during the 1980s and 1990s, reaching about 13 million in 2003. Estimates by the US Census Bureau suggest that in 2000 some 6.5 million people or about 62% of the Angolan population were under the age of 24 and that by 2025 that segment of the population would be of approximately 10.8 million people, or around 60% of the population.

- -

10 See Amijo and Costa (1 997) and Alves da Rocha (2001) for a detailed description ofAngola's nahnal r e s o w endowmenb.

1 1.

Population density (8.6 inhabitants per IGr?) is low and ethno-linguistic groups are geographically separated. The most populous provinces are Huambo, Luanda, Bie, Malange, and Huila, which together account for more than half of the total population. About threequarters of the population come h m three ethno-linguistic groups: the Ovimbundu (37%) in the Central plateau region, the Kimbundu (25%) living in a belt extending h m Luanda to the East, and the Bakongo (13%) in the Northwest. In addition, mesti~os (Angolans of mixed European and African family origins) amount to about 2%, with a small population of whites, mainly ethnic Portuguese. Portuguese is both the official language and predominant language, spoken in the homes of about two-thirds of the population, and as a secondary language by many more.

The existing social indicators are low and represent a huge challenge to the government and development partners alike. According to both the 2001 Household Income and Expenditure survey (IDR) and the 2002 Multiple Industry Cluster Survey (MICS), approximately 70% of the population lives on less than 2 dollars a day and the majority of the Angolans lack access to basic healthcare. About one in four Angolan children die before their fifth birthday, !N% of whom perish due to malaria, diarrhea or respiratory tract infections, the maternal mortality rate (at 1,800 per 100,000 births) is one of the highest in SSA, and three in five people do not have access to safe water or sanitation. The HIVIAIDS prevalence rate is, according to official statistics, relatively low, affecting an estimated 3.7% of adults.' ' However, lack of adequate statistical information and a limited number of surveillance centers suggest that the true prevalence rate may be much higher. In terms of education, primary school enrollment is very low at 56%, and suffers from late entries into school and high repetition and drop out rates. Some 33% of the adult population is currently illiterate, though in rural areas this climbs to as many as 50% (see Table 1.2). Table 1.2: Basic Poverty and Social Indicators

General living conditions are far from ideal, even for the middle class, but they are especially dire for the poor. The long period of civil war destroyed much of the infrastructure. Most Angolans, even in urban areas, do not have reliable access to safe water - only 20% in urban

lpo~ulation (million) 1 14.7 1 1 Pouulation S2O vears 1 60% 1 l~oGlation below ~overtv line 1 68% 1 l ~ i f e expectancy at birth 1 42.4 1

1 I UNAIDS, Report an Global Aids Epidmic, 2006 Low estimates are 1.9% and high estimates are 9.4%.

Under-five mortality (per I000 live births) HWAIDS prevelance Population who know where to get an HIV test Population correctly stating 3 main ways to avoid HIV infection Adult illiteracy rate - Maternal mortality rate Net primary school attendance rate (1-4th grade) HDI rank (out of 177 countries) GDVcapita rank (out of 177 countries) Gini coefficient (income, 1995) Gini coefficient (income, 2001)

250 3.90% 23% 17% 33% 1800 5 6% 161 128 0.54 0.62

Source: IDR (200011); UNICEF (2003); UNAIDS (2004); UNDP (2005)

areas outside of Luanda have access to it, according to the MICS data. Again the inequality is stark12 In Luanda, virtually no one in the two lowest asset quintiles reported access to safe water, while 40% in the highest quintile reported access. For example, in the comuna of Hoji ya Henda, population of 580,000 people, only about 15% of the people are connected to piped water while the rest of the population relies on 18 public water points, 14 of which are functioning. Electricity also is primarily available to the rich, most of who rely on generators given the poorly hctioning infrastructure and fkquent power outages. In Luanda, 82% of the highest quintile reported having electricity, but no one in the bottom 60% reported having any.

Public delivery of social services is also skewed in favor of the urban rich. For example, in urban areas in 2002, 50% of women reported receiving some form of trained pregnancy assistance, and this percentage dropped to 40% in the bottom quintile. However, only 24% in rural areas reported receiving this assistance, with just 16% in the poorest 20% of the population. An estimated 17% of (surviving) children under the age of 5 had not received any childhood vaccinations at all in 2002. Access to education is poor as well. Only 44% of rural children of primary school age (grades 14)

, are reported to be

Figure 1 .I Oil Dependency for Selected Countries

Oil revenues/Total revenues

-A -..A Angola

u Gabon -- I Tobaaa . -.

Algeria Mexico Norway Venezuela

in school, and 60% of urban children. This is partly because about one third of children start school 1-2 years late, either because the walk to schools is long, the family cannot

Oil expoMotal expo* (%) -

2 0

0

as poor so parents 1 do not value the

child's education

Cameroon

, I I I I

very highly, or the parents simply want to keep the children at home for an extra year. Of those who start, only 46% complete primary school and enroll in fifth grade.

afford the fees, children are heeded to work at home, school

0 20 40 60 80 100

The war caused the demise of the rural economy and the subsequent sharp rise in urbanization due to the amval of rural refugees. More than 1 million lost their lives during the civil war, 3 million fled to the cities and 400,000 crossed the borders into neighboring countries. Upwards of 45% of

quality is viewed

12 According to a recent survey conducted by Development Workshop m Luanda, about 30% of the interviewed households did not have access to

basic mhtmchm (e.g pipedlsafe water and electricity), as well as to basic services such as health and education in the vicmity. About 56% have

access to some level of inlkWmXm and senices. Only 13% have access to a relatively high provision of in6astructure and services (Devebpment

Workshop, 2003: 44).

the population became concentrated in urban areas, with more than half of them in Luanda (Adauta de Sousa, 2003). Furthermore, the current population growth at 2.9% per annum has almost doubled the population since 1980, which is now estimated at 14.7 million. Cross- continental transportation links, which served landlocked neighbors as well as the domestic economy, have atrophied. Infrastructure has also deteriorated in the cities, partly because of warfare and partly because inefficiencies in most pamtatal companies and price control policies depress public utility revenues, which hi1 to recover costs in most services. An estimated $4 billion may be required just to restore the road and bridge network, without which little rural activity is feasible.

Until 1975, the country was known as an agricultural producer, not an oil exporter. It was the world's fourth-largest exporter of coffee and one of the largest exporters of staple foods in sub- Saharan Afiica-exporting more than 400,000 metric tons of maize annually. These grain exports were produced almost exclusively by smallholders using traditional technologies. Oil had not yet achieved the high production levels of the 1980s and thereafter. Today, the economy is heavily dependent on oil, a capital-intensive -tor with few linkages to other parts of the economy and little impact on employment. After 1973, the structure of the economy changed substantially as the mining and service sectors increased their share of GDP (Table 1.3). To this date, the Angolan economy remains heavily dependent on the oil sector, which represents nearly 92% of total exports and close to 80% of total government revenues - one of the highest dependency rates in Afiica and elsewhere (see Figure 1.1).

Table 1 3 Composition of GDP by Sector, 1966 - 2004

1%6 1970 1987 19% 2084

Agriculture, Forestry and Fishery 14.2 9.0 12.6 7.0 9.1

Industry 22.2 29.6 57.5 67.8 58.1

Mining 6.3 10.7 51.0 61.2 49.8

Manufacturing 8.7 10.7 3.7 3.4 4.2

Electricity and water 0.9 0.9 0.3 0.0 0.0

Construction 6.3 7.3 2.5 3.1 4.0

Transport and communications 6.3 5.9 2.7 0 0

Commerce 34.0 30.3 7.2 15.0 15.4

Sources: IV Plano de Fornento 1974-1 979, Angola; P d Estatistico, 1988-1 99 1 ; "Angola:

"An hhuductory Review." The World Bank, January 1991; data provided by Angolan authorities to IMF and WB.

1.2 Policy choices and structural changes

The economy has experienced a great deal of ups and downs in its growth path during the last four decades. From 1960 to 1973, GDP per capita at 1996 international prices grew steadily, but collapsed by more than 35% after independence (see Figure 1.2). The period between 1974 and 1976 and the events associated with the fight for independence had a profound impact on Angola's economy insofar as skilled labor fled the country and organhtional capacity diminished. From 1975 to 1997, the economy suffered several shocks, the biggest of them being the restart of the war at the end of 1992 which caused another major drop of roughly 39% in GDP per capita in 1993. In addition, changes in oil prices provoked economic contractions during that period and GDP per capita declined at an average rate of 2% per annum. From 1997 to 2004, GDP per capita grew at an average rate of 4.2% per annum with the biggest increase observed in 2002 (about 13%). In mid-2002 gradualist economic policies were adopted and by 2004 the government managed to bring inflation down and to some extent improve ttansparency in the oil and fiscal sectors. Currently, the level of GDP per capita stands at US$ 1,784, which is still half of the level observed in 1973.

Figure 1.2 Evolution of Angola's Real GDP Per Capita, 1960 - 2004

After independence, Angola embarked on a system of centralized economic and political management that only in the mid-1980s started to be reviewed. The transition to a market economy took impetus with an ambitious refom program introduced in 1987 that aimed at stabilizing the economy, securing fiscal discipline, encouraging the development of the private sector, and abandoning the system of administered prices. Progress on this agenda has been sluggish and only after the early 2000s, aided by the fortuitous role played by growing oil revenues, the government succeeded in curbing inflation and achieving an incipient macroeconomic stability. In the face of a favorable external outlook, the government now has the opportunity to consolidate the country's transition to a market economy.

Real GDP Per Capita (19602004) $US

4000 - 3500 -

3000 - 2500 - 2060 - 1500 - I000 -

500 -

#- /-",

#+- Cbilwariwiak~[end 1992) a a ailpraJlrtbnafsdedbjwar

\

--

1986 0 7 ' 1 1 1 " " ' 1 1 " " 1 1 1 1 " ' 1 1 " " ' 1 1 " " " 1 1 r 1 ~ ~ ~ I

s s b b s o % ~ s e o % b b a @ ~ % b b a o l ,p 9 'p 4 6$ 8 $7 & 4 .$% p \4 @,.$ 8 ,** ,$P %@ '$++

- GDP per capna at anert irt'l pnas - -GDP per cspita at 96 ~rt ' l prices

The reforms ranged from budgetary discipline to rescheduling of the external debt and adjustments to the planning system. At the beginning of 1989, the authorities approved a "Program of Economic Recovery" (Programa de Renrperaqo Econbmica -PRE) oriented to the two main objectives of starting the process of macroeconomic adjustment and of promoting the rapid recovery of production. The PRE initiated the implementation of the economic reforms announced in the Program for Economic and Financial Restructuring (Programa de Saneamento Econ6mico e Financeiro - SEF), which included the following: (1) the reduction of the budget deficit of the state budget; (2) the adoption of new solutions to finance the budget deficit; (3) the restructuring of the financial situation of public enterprises; (4) the reform of domestic credit policies; (5) the rescheduling of external debts; (6) adjustments of controlled prices; and (7) adjustments in the exchange rate.

On the structural side, the reforms aimed at increasing the role of the private sector and at gradually reducing the importance of the state in the economy, On matters concerned with structural reforms to increase the efficiency of the productive system, the SEF envisaged a more important role for the private sector, more autonomy for public enterprises, a revision of the law on foreign investment and improvements in the planning system. The SEF explicitly admitted that smaller public enterprises should be transferred to the private sector and that state ownership should remain concentrated largely in key enterprises with strategic roles. As regards improvements in the planning system, the SEF envisaged achieving better coordination between the Annual Plans, the State Budget, and the Foreign Exchange Budget, and more decentralization of planning activities h m the Planning Ministry to the planning organizations at regional levels.

Despite the appropriate focus, the reforms did not yield the expected results. Government efforts to implement the SEF and the PRE proved unsuccessfbl and between 1989 and 2000 some 12 different macroeconomic stabilization programs were introduced with equally hstrating results. On average, there were 1.2 programs per year and each of the programs lasted for a period of 10.6 months. Throughout this period, the main obstacles to the lasting and effective stabilization of the economy continued to be the lack of fiscal discipline, the excessive centralization in the planning system and the resulting bureaucratization of the economy, and the inefficieicy of the state in promoting the growth of productivity. Fiscal deficits remained high during the 1990s making it difficult for the authorities to reduce inflation, the oil economy remained the main source of state revenues without productive links with the other sectors af'the economy, and the priorities of the war continued to condition government expenditures, which focused primarily on consumption and military expenditures and neglected social and development spending (notably on health, education, and infrastructure).

More recently, the government's economic policy has yielded positive results, but sustainability will demand further reforms. With the implementation of a more rigorous monetary policy, the restriction of monetary financing of the budget deficit since 2002, and the implementation of an active exchange rate policy since September 2003, inflation has been significantly reduced. However, the outlook is subject to sigdicant risks, which must be addressed by government actions. Most importantly, in an uncertain environment for oil production and prices, public expenditure growth needs to be set in a medium-term context to avoid the boom and bust cycles that have undermined stability and development in other oil-producing countries. The following paragraphs highlight progress obtained so far and the tensions that will need to be managed to complete the transition to a market economy and to a viable democracy.

1.3 The Economic Outlook: Oil Is Well That Ends Well

The macroeconomic framework for 2007 is highly favorable. In our estimates, total government revenues are expected to remain at a level close to 38% of GDP until 2007. On the expenditure side, spending is estimated to decline from 38.5% of GDP in 2004 to 35.7% of GDP in 2005.13 In the pursuit of long-term fiscal sustainability, spending should gradually decline in 2006 and 2007 as a share of GDP.]~ Such gradual decline in public spending as a share of GDP is not politically unrealistic insofar as real GDP is estimated to have grown by 20% in 2005 and to grow by an average 24% in 2006-2007 supported by strong performance in the oil sector and steady recovery of the non-oil economy.

Figure 1.3: Angola: Real GDP growth 1990-2006

,, The figures are based on information as of March 2006 and reflect the macroeconomic tiamework agreed between the authorities and the Fund

during the 2006 Article N cons&ons.

The economic outlook in Angola has been transformed by the peace agreement of 2002 and by positive developments in the oil sector. With the end of violent conflict and the return of more than 4 million IDPs to their original communities since 2002, agricultural production has picked up and the non-oil economy has shown signs of a vigorous recovery in Angola. Although official and detailed data on the non-mineral economy is scant, the lively and vibrant informal economy

14 In the draft 2006 budget recently finalized by the Government, the authorities are projecting a fiscal deficit of 6.9% of GDP in 2006 and an annual

inflation rate of 10°'. The fiscal n u m h in our rnaroeconomic fiamework are different 6om those presented by the Government in the 2006 budget

because our h a t e s use higher oil prices for 2006 (S56kmel) than those used by the Government in their 2006 budget ($45hmel).

30%

20%

,ox

0%

-lo%

-20%

-30% A n g o l a I SSA -LOW Income

that is now seen in the streets of Luanda is a visible leading indicator of strong economic performance. There have also been encouraging signs of recovery in public services, construction, and infrastructure rehabilitation. Oil production, which currently accounts for 55% of GDP, is expected to double to 2 million barrels per day by 2007. Largely as a result of increasing oil production combined with rising international oil prices, real GDP is estimated to have grown by 20% in 2005, while the economy outside the mineral sectors is estimated to have grown at an annual rate of roughly 10% over the last 3 years. Current projections indicate that GDP is expected to grow by 15% in real terms in 2006 and by 30% in 2007, one of the highest growth rates in the world (see figure 1.3).

Figure 1.4: Progress in Macroeconomic Indicators

&'wok 011 Produdlon - M u a l (2001-2041) and Angola: External Debt a8 s Share of GDP ProJadrd (2005-07)

lee8 reee 2000 2001 2002 2ooa 1004 Z D O I ~ ~ Q ~ ~ Z O ( Y ~ O O S Z ~ O O ~ ~

Angols: NonQll F I8ul Deflclt a8 a Share of NonQll Angola: Nreke-Month Growth Rates of GDP Monetary Indlutors

t W 0 2001 2002 2003 2004 ZOO0 ZOO1 2002 ZOO3 2004

I m M3 Reserve Money

There have been commendable successes towards macroeconomic stabilization, but there should be a stronger emphasis on the continuing deficiencies in policy design and implementation. Figure 1.4 shows progress on a number of macroeconomic variables since the year 2000, including oil production. The stabilization obtained so far, however, needs to be strengthened with improved coordination of the fiscal policy with monetary and exchange rate policies. These policies need to spell out a consistent strategy to absorb the upcoming oil windfall without inhiiiting growth outside the mineral sectors. To avoid the boom and bust cycles that have undermined stability and development in some other oil-producing countries, new public spending in the future should be set in a medium-term context. In addition, the authorities should consider the adoption of a monetary anchor, with the responsibilities for executing monetary policy defined by the Central Bank in order to guarantee a downward trend in inflation even in the face of an external shock

The root cause of past inflationary episodes in Angola was the monetization of its fiscal deficits. Angola's main source of fiscal revenue is the taxation of the oil sector, including the state-owned oil company Sonangol. As a result, fiscal revenues have been excessively vulnerable to international crude oil price volatility and have not always been able to keep pace with expenditures. The insufficient control of public spending, including notably large extra budgetary expenditures and the sizeable operational deficit of Banco Nacional de Angola (BNA), have induced large increases in base money. Additionally, in the past, favored interest groups, including Sonangol, have used arbitrage and other tactics to benefit fiom high inflation, for exam le, by delaying payments in domestic currency for oil and other sales received in hard currency.' Until 2002, this combination of affairs had actually created positive incentives for high inflation.I6

More recently, government's efforts to reduce inflation have been successful. Between 1999 and the peace agreement of 2002, annual consumer price inflation fell from around 300% to around 100% (see Figure 1.5). Following the adoption of a stabilization program in Figure 1.5: Curbing InRaUon

September 2003, inflation fell sharply again and by December 2004 the 12- month inflation rate had declined to 3 1%. The improvement was largely due to the government's avoidance of money creation for deficit finance purposes together with smaller fiscal deficits in 2003 and 2004 (that dropped from 6.5% of GDP in 2003 to 1.5% of GDP in 2004, on a commitment basis) and an estimated fiscal surplus of

An#ob: Yoar on Yoar Inllailon R.ir

L w 6.8% of GDP in 2005. Since 2003, 1 % [ f f f ~ g # f ~ f $ f ~ g g f ~ g $ government spending has been s 6 s a s 6 k k k 6 k o k I s a

increasingly funded by &sources obtained through direct sales of foreign exchange in excess of $2 billion in 2003 and 2004, respectively, which has increased Angola's external liabilities.17 The non-oil fiscal deficit as a share of non-oil GDP has also declined substantially since 2000 from around 130% to close to 63% in 2005. In 2005, the cumulative rate of inflation dropped to 18.5% and the projection for 2006 is of an annual rate of 10%. Monetary aggregates have been kept under control contributing to lower inflation.

15 A detailed discwion of public finance management issues can be found m the Bank's PEMFAR report, published m February 2005 (see World

Bank, 2005).

16 From a political economy point of view, a centralized economic system tfiat hens b a d on conbulling marken enmurages the development of a

wealthy elite which tends to create mechanisms to guarantee the appmpriation of profits vrespectrve of exchange rate and price swing so they are

largely indifferent to macroeconomic shocks and the need to stabilize the economy. In fact, the wealthy can lose h m economic r e f m to the extent that

comwtive markets and bansparent public finances shrink the scope f a rent extraction. Some commenmrs argue that this was actually one of the

reasons beyond the war situation that could be used to explain why refom s!alled through the 1990s (Aguilar, 2001).

17 A detailed descnpt~on of the kinds and magnitudes of intervention in the foreign exchange market m Angola is available in the 2004 Angola

Economic Report published by the Center of Shdies and Scientific Investigation of the Catholic University of Angola - see CEIC (2004).

There are F'igure 1.6: lkadable and Nontradable inflation consequences associated with the current policy to combat inflation. First, removal of excess liquidity from

rates

expansion permitting a decline in the rate of inflation. Second, the use of foreign exchange for the purpose of mopping up liquidity contributes to stabilizing .the exchange rate. Third, keeping the exchange rate stable implies a corresponding constancy in the prices of imported goods, eliminating inflationary pressures fiom this source. Finally, avoiding a policy that requires an immediate fiscal

circulation reduces the inflationary pressures deriving fi0m money

immediate i d visible success in economic management. These effects combined may help the government to build the necessary political capital for the future, when expenditures will invariably have to be cut down.

lnflatlon Rates, January 2003 July 2005 (Annual percentage change)

adjusbn&t in favor of one which ' , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , I

Achieving sustainable inflationary stability is also essential to harness the growth of the non-oil economy. It is a well established fact that the inflation component of market-oriented reform policies should be expected to be growth-enhancing. In the case of Angola, this is particularly relevant for the non-oil economy, given the insulation of the oil-economy due to its enclave nature. This is so because high rates of inflation can be expected to reduce economic growth through a variety of mechanisms which can influence both the rate of capital accumulation and the rate of growth of total factor productivity. One of such mechanisms is that high inflation means unstable

_ inflation and volatile relative prices, which reduces the information content of price signals and distorts the efficiency of resource allocation thus harming the growth of total factor productivity over extended periods. Furthermore, governments that tolerate high inflation have lost macroeconomic control, and this circumstance is likely to deter domestic investment in physical capital."

yields price stability, while postponing

Beyond the fiscal sphere, there are important concerns associated with the virtual stabilization of the nominal exchange rate that the current policy has generated. As noted above, exchange rate stability may be seen as a beneficial consequence of this policy by working as a major factor limiting price increases of tradable goods. However, the growth of the monetary aggregates in

1 I . 1 { H i f f . f

18 Barn (1997) presents cross-wlmby evidence on the negative relationship between inflation and growth for a sample of 100 munbies with annual

observations on macmeumomic data for the period 1960-90. His & hding is that, other thing equal, a IO?? increase in the rate of idation

reduces long-nm growth by about 0.025% per year.

cuts in expenditures, generates an O t ~ n a g a h

Angola, while slowing, has been faster than would be consistent with the achievement of the inflation objective, with the consequence that the real exchange rate has appreciated significantly. The implication of this is that the policy has been much less effective in reducing the inflation of the non-tradables (see Figure 1.6). In addition, the scaling up of public spending is likely to exert pressure on the domestic price level. To counter this effect and to keep the declining trend in inflation, the authorities should resort to both sales of foreign currency and new issues of government bonds to help mop up excess liquidity. In this context, an appreciation of the nominal exchange rate should not be resisted as it will contribute to reducing inflation.

2 THE BUSINESS ENVIRONMENT

2.1 Formal Sector: Perceived Constraints

Firms were asked to class@ various constraints of their business environment Table 2.1 contains the percentage of firms perceiving each constraint as major or very severe. Approximately half of the firms perceive access to credit and electricity as important constraints to their operation; crime, corruption and business licensing also belong to the group of most important obstacles to business operation (since over one third of firms identified them as major constraints). Transportation, identified by 27% of firms, is also a relevant constraint.

These perceptions vary across firms. Access to finance appears to affect smaU and medium firms more significantIy than large firms. Domestic firms and firms located outside Luanda also perceive it to be more of a problem than foreign firms or firms located in Luanda. By contrast, electricity appears to be more of a problem for large firms and for finns in the manufacturing sector. Crime and corruption appear to be more significant constraints for large firms and for firms located in Luanda. Transportation is identified as a major problem for firms located outside Luanda.

Table 2.1: Major or Very Severe Constraints as Reported by All Formal Sector Firms in Percentages

Changing our focus to the manufacturing sector, Table 2.2 contains the percentage of firms which classified each constraint as major or very severe. A higher share of firms (over 60%) perceive access to credit and electricity as the two most important constraints to their operation. Similarly, business licensing, crime and corruption are important obstacles identified by over one third of manufacturing firms.

Canstraint

Acmss to finance (aMihbilityand msl)

Elecbicity

Qime, theff and disorder

CoMpbm

Business licensing and Pm&

Transpatation

~ ~ d ~ d ~ ~ m in in(am, wa Access to land

Tax rates

w - a n i c instability

Customs and Trade Regulations

Inadequably educated wCfkfcrce

Tax adrrinisbaiion

Funclioning of Ute carrts

Wlcal instability

Labor R6g~laS0ns

Telecarmudcations

TOTAL

Source: ICA Survey

55%

48%

37%

36%

33%

27%

27%

23%

23%

22Y.

21%

21%

18%

14%

14%

12%

7%

Rrmslze

Small Med. Large

56% 52% 40?4

43% 58% 100%

39% 17% 60%

38% 20% 60%

35% 20% 60%

26% 29% 80%

28% 17% 20%

24% 19% 20%

23% 20% 60%

23% 15% 40%

22% 15% 60%

23% 6% 20%

19% 11% 20%

16% 4% 40%

15% 4% 0%

14% 2% 0%

7% 8% 20%

35% 59%

41% 47%

37% 37%

43% 35%

31% 34%

25% 28%

22% 27%

31% 22%

13% 25%

16% 23%

22% 21%

15% 22%

13% 19%

10% 15%

7% 15%

6% 13%

9% 7%

m w i p

F o r m Dom.

Laation

Luanda OLndde LuanB

indusby

Manuf. - Rst Food andManUf'

- Garments Omer RBtail me

universe

Table 2.2: Major or Very Severe Constraints as Reported by Manufacturing Sector Firms in Percentages

Constraint

Business licensing and Permits

Crime, theft and disorder

Practices of competitors in inform. sector

Transportation

l ~ a x rates

Macmeconomic instability

Inadequately educated workforce

l~ccess to land

Tax administration

Customs and Trade Regulations

Functioning of the courts

Political instability

Labor Regulations

1 TOTAL

63%

I F i n size - 1 Ownership I Small Med. Large Forelgn Dom

66% 52% 40% 49% 65%

60% 69% 100% 72% 61%

41% 30% 60% 44% 39%

43% 19% 60% 23% 41%

37% 26% 60% 28% 36%

36% 16% 20% 17% 34%

31% 25% 80% 34% 31%

Location

Luanda :Ut::

Source: ICA Survey

Figure 2.1 focuses on the perceptions contained in Table 2.1 across locations. Here we can see clearly that the perception of obstacles in Luanda is different fiom that outside Luanda. Access to credit, electricity, and transportation are more important constraints for firms located outside Luanda than for firms in Luanda. By contrast, crime and corruption are a significant constraint for firms located in Luanda.

Figure 2.1: Top 6 Major or Very Severe Constraints as Reported by All Formal Sector Firms in Percentages

60%

50% a Outside Luanda

40%

30%

20%

10%

0%

Source: ICA Survey

In a comparison across countries (Table 2.3), we can see that, as in Angola, access to credit is even more of a constraint in Algeria, DRC and Namibia - respectively 66%, 64% and 100% of h s report it to be a serious problem. Angola perfoms better than low income countries, sub-Saharan Afiica countries or resource rich countries, where over 75% of h s consider it to be a major bottleneck to their business.

Electricity, on the other hand, appears to be more of a constraint only in DRC, where 77% of firms report it to be a serious problem. In Algeria, South Africa and Namibia it is perceived to be less of a problem than in Angola.

Similarly, crime and licensing seem to be more of a problem for h s in Angola than in the rest of the continent. While corruption in Angola is worse than in South Africa, Namibia, and the DRC, it is within the regional average.

Table 2.3: Major or Very Severe Constraints as Reported by Firms - Comparison Across Countries

Consbaint

Access to finance (availability and cost)

Electriaty

Crime, theft and disorder

Cormption

Business licensing and Permits

Transportation

Practices d canpetiton in infam. sedu

Access to bnd

Tax rates

Mauoeconwnic inslability

Customs and Trade Regulations

I Inadequately educated wakforce I l ~ a x adminisbation 1 Functioning d the c w r k

Political inslability

Labor Regulations

I~elemmmunications

Source: ICA Surveys

Low income SubSaharan Resource b n n s /Africa ImunMi

55%

46%

37%

38%

33%

27%

27%

23%

23%

22%

21%

21%

18%

14%

14%

12%

7%

These perceived constraints have a direct impact on indirect costs. In Table 2.4 we have estimated a number of indirect costs for manufacturing h s in Angola. We can see that the manufacturing sector has to bear indirect costs which amount to some 11% of its total sales.lg Of these, electricity (production lost due to power outages) is the main component (5.2% of total sales), although bribes (3.4% of sales) are also relevant.

66%

15%

NIA

39%

32%

NIA

62%

41%

47%

42%

35%

29%

39%

NIA

NIA

17%

19%

19 Care mwt be be when i n t q d n g this value as it may double count the& therefore, this d u e should be seen as an uppa limit to indirect

costs.

Table 2.4: Indirect Costs - Manufacturing Sector Firm size ( Ownership

Indirect costs as % sales TOTAL Small Med. Large Foreign Domestic

Electricity 5.2 4.9 6.3 9.6 3.7 5.4

Breakage or spoilage in transit 1.4 1.1 2.9 1.1

Theft while in transit I 0.7 I 0.8 0.2

I~hef t . robbery or arson 1 0.4 1 0.4 0.3 0.0 1 0.1 0.4

Location I

In comparison to other countries, we can see fiom Table 2.5 that Angola performs better than Algeria and the Democratic Republic of Congo, where such indirect costs amount to 17.1% and 14% of sales respectively. However South Africa and Namibia report much lower indirect costs (2.7% and 4.7% respectively). Low income and Sub-Saharan African countries report levels of indirect costs higher than Angola, whilst h s in resource rich countries appear to face similar levels of indirect costs (1 0.1 % of sales).

Total indirect costs 11.2

Table 2.5: Indirect Costs - Manufacturing Sector - Comparison across Countries

Indirect costs as % sales

Source: ICA Survey 10.8 12.9 12.6

Alaria D. R, Congo South Africa Namibia LOW income Sub-Saharan Resource lich 1 LulgO'a I I I I IcnunU. f r i ICouMis 1

12.5 11.0

I~mduction lost while in transit 1 2.1 1 2.4 1 1.0 1 0.8 1 1.0 1 1.5 1 1.4 1 1.3 1

12.7 2.6

Electricrty

Bribes

In all comparators, electricity is one of the main drivers of indirect costs (and the main driver for all comparators except Algeria and Namibia). In conclusion, the analysis of the indirect costs appears to confirm the perception that electricity is a significant problem for Angolan firms.

5.2

3.4

Theft, robbery or arson

Total indirect costs

It is interesting to note that these indirect costs affect different types of firms differently (Table 2.4). Electricity and bribes are more of a problem for domestic firms (5.4% and 3.7% of total sales respectively) and firms based in Luanda (5.6% and 4.2% of total sales respectively). Electricity affects large firms to a significant extent (9.8% of total sales), whereas bribes and crime affect mostly small firms (3.5% and 0.4% of total sales respectively).

When looking at aIl formal sectors, the main conclusion does not change significantly (see Table 2.6)." Total indirect costs amount to 8.3% of total sales, with electricity alone accounting for over half of that total (4.6% of total sales). Large firms (1 1.4% of sales) face higher indirect costs than smalVmedium firms.

5.3

7.9

Source: ICA Surveys

0.4

11.2

20 Note that Table 2.6 does not include breakage, spoilage or thefl while in transit

7.4

5.1

1.6

17.1

0.9

0.3

0.5

14.0

1.2

1.7

0.6

2.7

9.9

3.1

0.8

4.7

8.7

2.5

1 .O

15.5

5.8

1 .9

1 .O

13.6

1.1

10.1

Electricity related indirect costs afflict large firms (9.8% of total sales), domestic firms (4.8% of total sales) and firms based in Luanda (4.9% of total sales). The manufacturing sector is more affected than the other sectors.

2.2 Electricity

Table 2.6: Indirect Costs -All Formal Sectors

Looking in more detail at electricity, there are several dimensions one can analyse. In Angola 84% of all firms experienced power outages, on average 8 times per month (Table 2.7). Large firms experience power outages more frequently (16 times per month) but with a lower duration (8 hours). Firms based in Luanda are relatively less affected by this problem and the manufacturing sector is more affected than the others. This confirms why electricity is perceived to be less of problem for firms based in Luanda and more of a problem for firms in the manufacturing sector - see Table 2.1.

Indirect costs as %sales

Elecblcily

Bribes

Theft, robbery w arson

Total indirecl costs

To correct for this problem, 68% of firms have their own generators. We would expect a higher percentage of generator ownership where the problem is perceived to be more important: indeed, over 90% of firms from outside Luanda have a generator. These generators produce an average of 31% of the total electricity needs. Large firms rely more on their generators (49% of total electricity) than small and medium firms (28% and 43% respectively).

Additionally, obtaining an electrical connection is a time consuming process: on average, firms have to wait 60 days- to obtain one. Firms from outside Luanda have to wait a great deal more - on average 182 days.

Source: ICA Survey

T O T N

4.6

3.3

0.5

6.3

F l n size

Small Med. Large

4.5 4.6 9.8

3.4 2.4 1.6

0.5 0.5 0.0

8.4 7.5 114

Ownership

Foreign Dom.

3.1 4.8

3.3 3.2

0.8 0.4

7.3 8.5

Location

Luanda Outside Luanda

4.9 2.2

4.1 0.0

0.5 0.3

9.5 2.5

lndusby Manuf. - Rest Food and - ' Retail me beYerages Garments Other univen

4.7 5.7 5.5 4.2 3.0

2.6 4.3 3.8 4.4 1.8

0.6 0.5 0.3 0.7 0.6

7.8 10.5 9.5 9.3 5.3

Table 2.7: Infrastructure Indicators - AU Formal Sectors

lTwe I Quality measure

% firms experienced p e r outages

Frequency of power wbges (time per month)

Duration of power outages (harm)

Eledriaty Pmduction lost (% annual sales) I I I 1% finns mth a generata

% eledtiaty coming fmm owl I generata

Number of days lo obbln electrica mneclion

Source: ICA Survey

-

TOTAL

- 84

8

21

4.6

68

31

60 -

I Firm sue

Small Med. Largc

85 78 100

7 8 16

21 23 8

4.5 4.6 9.8

65 84 80

28 43 49

46 202 7

Foreign Dan

Location

Gutsidt Luanda Luanda

Industry danuf. Rest :ood Manuf. - Manuf. - Retail the ~ n d Garments Other I V

universe

89 87 81 87 82

8 8 9 6 8

30 17 26 13 14

4.7 5.7 5.5 4.2 3.0

89 71 55 NIA NIA

33 23 31 NIA NIA

99 45 64 25 40

In comparison to other countries (Table 2.8), only in the Democratic Republic of Congo do more firms experience power outages (96%) than in Angola. When analysing total outage duration (Erequency of outages multiplied by its average duration), Angolan firms report a longer period (80 days) without electricity over a year. Firms in DRC have more frequent power outages (19 times per month) than in Angola, but they last for less longer (4 hours on average).

Overall, the number of days of production lost because of electricity problems is significantly higher in Angola than in comparator countries, although the indirect cost it generates for firms in Angola is lower than in those countries. This may be explained by the higher penetration of own generators in Angola (68% of h s in Angola have a generator), which account for a larger share of total electricity needs (compared to other countries) and this may reduce the impact of power outages on the day-to-day operation of firms. However, care must be taken with this line of thought because it is costlier to use a generator to produce electricity, which naturally translates into higher direct costs for firms.

Our main conclusion is that even with such a high penetration of generators (compared to other countries), electricity remains a serious constraint to business.

Table 2.8: Infrastructure Indicators - Comparison across Countries

2.3 Corruption and Crime

TW

~l&"ty

Corruption is perceived to be a serious constraint by firms. Approximately 36% of firms recognize it to be a major or very severe constraint, and this p e p t i o n appears to be more common among large firms and firms located in Luanda (Table 2.1) .

That corruption is one of the major bottlenecks in Angola is confirmed by other sources. Transparency International's Corruption Perceptions Index (CPI) attempts to quantify the degree of corruption as seen by business people and country analysts, and ranges between 10 @ghly clean) and 0 @ghly corrupt). Table2.9 shows that Angola is near the bottom of the ranking, with a score of 2.2 in 2007. Within our comparators, only the Dern. Rep. of Congo performs worse.

Source: ICA Sweys

Quality measure

% firms expiend power outages

Total outage duration (days)

Production lost (% annual sales)

% firms with own generator

% electricity coming from own generator

Number of days to obtain electrical connection

Table 2.9: Conuption Perceptions index - 2007

I DRC 168 1.9 1 Source: Transparency International

Angola

84

80

4.6

68

3 1

60

Nevertheless, since the end of the civil war Angola has recorded some improvements on political stability and control of cormption. More recently the World Bank Governance Indicators for 2006 have shown Angola as one of the top reformers in these 2 areas.

Whilst positive results have been achieved recently, Table 2.6 shows that corruption still entails a significant indirect cost for firms of approximately 3.3% of sales. Whereas firms located outside Luanda support lower indirect costs because of bribes (and this may help explain why cormption

Algeria

68

14

5.3

29

22

100

21 This apparent strange resdt is probably due to the fact that this question is perceived by managers outside Luanda as more threatening than those in Luanda. As a matter of fact informal discussions with local experts have pointed out that this result is counterintuitive.

D. R Congo

96

36

6.9

42

19

27

South Aiiica

NIA

1.0

0.9

9

17

6

Namibia

NIA

0.1

1.4

7

1

10

JAW income countries

NIA

11.5

9.1

41

14

50

Sub-Saharan Africa

NIA

8.4

8.2

36

11

42

Resource rich countries

NIA

4.6

5.8

30

9

45

is perceived to be less of a problem for those firms), large firms also appear to face lower i n h t costs. This result implies that the amount of bribe genemlly requested is a fixed amount not dependent on the volume of activity of the firm.

From an international perspective, corruption is more of a problem in Algeria and DRC, where the cost of bribes is higher than in Angola (Table 2.5). Nevertheless with an estimated cost of over 3% of sales, corruption remains a key bottleneck to firms in Angola.

Looking in more detail at corruption, Table 2.10 shows that only 23% of firms believe that government officials have a consistent and predictable interpretation of the law. This uncertainty may be closely linked to corruption. Furthermore some 24% of firms report informal payments or gifts to be common to "get things done" regarding customs, taxes, licenses, regulations, etc, whilst only 7% know in advance the amount of payment needed. Informal payments are perceived to be a more serious problem for large and domestic firms, as well as for firms based in Luanda. When a government contract is at stake, firms expect to have to pay some 4.5% of its value in such informal gifts or payments to secure it.

Table 2.10: Perception of Government and Regulations -All Formal Sectors

I Of conh3ct "lye paidl 4 1 4.3 5.5 10.0 1 4.7. 4.5 I 5.6 TI 1 1 to secure contract 6.1 4.8 6.3

% firms who agree with statement

Consistent and predictable interpretation of h e law

lnfumal commonplace

Advance knowledge of i n f m a l paymentlgift

Percen'ageafannualsalesspent on informal payments/gifts

I I I I I I I Source: ICA Survey

The court system is another institution where corruption may be a problem. Table 2.1 1 shows that firms have a relatively low confidence in it. Almost 90% of firms believe the system to be unfair, partial and corrupted whilst only 50% believe it to be able to enforce its decisions. Clearly, the problem appears to be not so much at the postdecision stage, but at the predecision stage, with 80% of firms considering the process slow, 70% expensive, partial and corrupted. This conclusion is reinforced by the fact that whilst 4% of firms had payment disputes in the past two years, only 49% of such disputes were taken to court.

TOTAL

23.4

23.8

7.0

3.3

Firm size

Small Med. Large

23.3 24.4 20.0

24.1 19.4 40.0

6.6 6.3 40.0

3.4 2.4 1.6

Ownership

F a e n Dom

30.4 22.2

16.6 25.0

12.1 6.2

3.3 3.2

Location

Wanda :$: 28.3 0.0

28.8 0.0

8.5 0.0

4.1 0.0

Industry

Manuf. - Rest of ;: and Z:knbs E:f' - Retail h e universe

15.5 23.0 26.0 27.3 22.0

18.3 45.9 30.0 20.7 16.3

8.4 11.5 4.9 7.5 7.7

2.6 4.3 3.8 4.4 1.8

Table 2.11 : Court System -All Formal Sectors

I I Firm size I Ownership ( Location I Industry

I I I I I I I Source: ICA Survey

aaraMtica System

Fair,imparUalanduncompted

Quick

Affordable

Able to enforce decisions

Percentage d firms with paymentd'mputesinthepast2 years seffled by third parties

Crime was also reported to be a serious constmint to business (see Table 2.1). Almost 40% of firms complained about this problem. From an international perspective, more Angolan firms complain about crime than firms in South Africa, where this is a well known problem.

Apart fiom the ICA data, there is little available evidence on the overall crime rates in An ola. According to the Interpol (2000), the incidence of crime is 71.52 per 100,000 inhabitants2'. In comparison, South Africa's is 8,176 per 100,000 inhabitants (Intepl (200l))~~, ranking consistently in the world top crime rankings, especially on violent crime.

TOTAL

31.7

21.5

28.5

48.8

3.9

When we look at more objective indicators of crime, the picture is quite different. Although many firms complain only 18% of them experienced losses as a result of theft, robbery, vandalism or arson, whilst in DRC and Namibia such losses were experienced by 26% and 35% of firms respectively. South Africa has a higher incidence of crime: 52% of manufacturing firms experienced losses due to it.

The impact of crime on the costs of production in Angola is not as high as in other countries. Theft, vandalism or arson generates indirect costs totalling 0.5% of sales, lower than most countries in the region (Table 2.5).

Small W. Lam

31.5 34.620.0

21.7 20.4 20.0

29.5 22.2 20.0

49.1 47.8 40.0

2.5 9.3 40.0

Similar results are obtained if we look at the share of f m s that employ security services. Fewer h s in Angola's manufacturing sector pay for security services (Table 2.12). At the same time average security costs (as a percentage of annual sales) are similar to DRC and particularly South Africa (where crime incidence is high).

22 Available h m http:llw.justicemitiative.orplregidafridanpla .

23 Available h h t t p : l l w . j u s t i c e m M v e . ~ d a ~ c a / ~ ~ ~ ~ c a / s a d h a ~ ~ o .

F a i ~ n D m ,

50.7 28.4

32.5 19.8

38.2 28.8

52.2 48.2

8.7 3.1

Luanda Fz:: 38.0 1.6

25.7 1.6

34.2 1.5

58.7 1.5

4.4 1.2

Manuf. - Lo and rJkb- EF - Retail Rest Of me^ universe

29.5 17.2 28.4 33.0 41.2

16.9 5.7 21.9 19.8 30.6

25.3 0.0 29.2 28.5 37.4

37.9 51.6 58.4 42.6 48.8

1.4 5.7 3.3 4.7 5.8

Table 2.12: Security Services and Security Expenditure - Comparison across Countries - Manufacturing Sector

Finally, if we sum together the cost due to theft and the costs of security services, we see that Angola perfoms as well as other countries in the region and evei better that the region average (Figure 2.2). This leads us to conclude that although crime has some cost implications for Angolan firms, it is not a major constraint.

Figure 2.2: Costs of Security and Theft - International Comparisons

4 0 1- --- ----

Industry

Manuf. - Rest of Food and Manuf.

- Manuf. - bev.

Garments Other Retail the universe

56 29 32 57 61

1.9 0.8 1 .O 3.0 1.7

Angola D. R. Congo South Africa Low income SSA SSA Resource rich counbies

Source: ICA Survey

Percentage Of fins that paid for securitv

Seculity as % annual sales

Source: ICA Survey

Ownership

Foreign Dom.

72 44

2.7 1.6

Location

Outside Luanda Luanda

49 41

1.8 1.4

TOTAL

48

1.7

F i n ske

Small Med. Large

45 68 60

1.7 1.9 0.8

2.4 Regulatory Framework

Over the past few years Angola has registered a position and noticeable evolution on regulatory quality. The governance indicators developed by the World Bank clearly show that Angola has moved up fiom the lowest levels since 2000. Although the evolution in regulatory quality has been positive, more needs to be done since Angola still remains among then Sub-Saharan African countries with the lowest score. This confirms h ' s perceptions of business licensing and the overall regulatory burden as a significant constraint (Table 2.1).

Table 2.13 shows that on average close to 8% of senior management time is spent dealing with government regulations. This burden falls disproportionately on large (14.6%) and foreign (10.2%) firms, as well as h s based in Luanda (8.4%). The retail sector is the most affected (12.9%). On average, close to 68% of all firms were visited by officials each year, on average 5 times. Large firms rank high in both coverage (100%) and frequency (7 visits), whereas small h s rank low in both (63% in coverage and 5 visits). Outside Luanda, coverage is high (98%), but frequency is lower (3 visits).

Table 2.13: Regulatory Burden - All Formal Sectors

On the indicator of regulatory burden Angola performs similarly to our comparator countries, with the exception of Namibia (Table 2.14).

Table 2.14: Regulatory Burden - Comparison across Countries

Quality measure

% senior management time spent with regulations

% firmsvisiled by officials

N u m b e r o f i n s ~ v i s ' t s Jlast 12 months

Quality measure countries Africa

% senior management time spent 7,7 with regulations

Source: ICA Survey

Source: ICA Survey

Ownership

Foreign O m .

10.2 7.3

83.4 64.9

4.7 5.3

Regarding the licensing process, Table 2.15 shows that obtaining licenses is a slow process: it takes 24 days to obtain an import or operating license, whilst a construction-related permit takes some 42 days. The process of obtaining licenses is much slower in Luanda and (with the exception of import licenses) it is faster for small firms.

TOTAL

7.7

67.6

5.2

Firm size

Small Med Large

7.7 7.4 14.6

62.9 96.2 100.0

4.7 7.1 7.2

Location

Luanda ::t:z 8.4 4.7

61.1 98.3

5.9 3.0

lndusby

Manuf. - Lo and Ee:ni tE: - RetaL! Rest Of the untvene

5.6 3.9 6.6 12.9 6.9

74.7 42.6 58.6 66.1 83.7

4.9 3.1 5.0 4.7 6.2

Table 2.15: Licensing Process

Number of day. to obtain:

Source: ICA Survey

Construction-related permit

An import license

An operating license -

An international comparison (Table 2.16) shows that it is common in Angola to wait long to obtain licenses, even though the wait in Angola is a bit better than the regional averages. Nevertheless Angola performs worse than high performance countries such as South Afiica and Namibia on all types of license.

TOTAL

Table 2.16: Licensing Process - Comparison across Countries

42.1

23.9

24.1

Firm size

Small Med. Large

Starting a business in Angola was a lengthy (124 days are necessary) and costly process (Table 2.1 7). Only the DRC fares worse than Angola (155 days), whilst Algeria, South Africa and Namibia appear to have a speedier and less costly business start-up process. Both the time needed and the costs of starting a business in Angola are higher than the Sub-Saharan Afkica average. This estimates however in based on 2005 data. In response to this problem the government has established a new office, the Guichet &co that is supposed to speed up the registration of firms. And the next Doing Business will show that Angola has improved its performance on this indicator.

27.0 93.4 105.0

25.1 19.9 8.0

22.9 24.3 64.0

Number of days to obtain:

Construction-related permit

An import license

An operating license

Table 2.17: Starting a Business

Ownenhip

Foreign Dom.

39.2 42.8

30.5 21.1

34.5 21.5

Source: ICA Survey

Angola

42.1

23.9

24.1

1 Duration (day.) 1 124 1 24 1 155

Loqation

Outside Luanda Luanda

Number of procedures

1 cost (X of income per capha) 1 486.7 1 21.5 1 481.1 1 6.9 1 18.0 1 1628

Industry

pz:f. - Manuf. - Manuf. - and

Garments Other Retail the unlverse

57.4 7.5

26.7 8.5

40.1 8.6

D. R. Congo

23.6

12.3

23.7

I Min. capital (% of income per capita) ) 74.1 1 46.0 177.3 0.0 0.0 209.9

Source: World Bank Doing Business Indicators 2006

41.3 75.0 81.2 21.3 32.6

15.3 20.0 16.5 23.5 32.3

18.5 8.0 19.6 23.5 31.8

Angda

13

South Ahica

8.6

7.0

5.0

Algeria D. R. Congo

Namibia

21.4

19.5

9.3

Swth Africa

Low income countries

58.7

28.0

15.7

14

Namibia

13 9 10

Sub-Saharan Africa

54.3

24.7

15.2

SubSaharan Africa

Resource rich countries

51.5

16.9

24.2

Nevertheless if we look at procedures, time, and costs to build a warehouse (Table 2.18), both time (326 days) and costs are much higher in Angola than in the comparator countries (with the exception of DRC regarding costs). The sub-Saharan AiXca average (230 days) is lower, as is the cost associated with the licensing process.

Table 2.1 8: Licenses

Time (days) I 326 I 244 I 306 1 174 I 105 I 230 1 Number of procedures

This leads us to conclude that business licensing remains a problem in Angola.

Angola

15

Cost (% of income per capita)

2.5 'Ransportation and Other Constraints

Transportation emerged fiom Table 2.1 as an important constraint to business, particularly for firms located outside Luanda. From Table 2.4 and Table 2.5, manufacturing firms in Angola lose 2.1% of their sales in transit (breakage, spoilage or theft), more than in all comparators (except Algeria). Strangely, firms located outside Luanda report very low transportation indirect costs, although they perceive transportation to be a significant constmint.

Algeria

25

Source: World Bank Doing Business Indicators 2006 1239.2

Table 2.19: Inventory Holdings of Most Important Input - Manufacturine and All Sectors

58.9

outside holding large inventories, Average number of days TOTAL Small Medium Large Foreign Domestic Luanda Luanda which is inefficient. Table Manufacturing 2.19 shows that on

average manufacturing AII Sectors firms hold approximately

14 days of production of

D. R. Congo

14

-

their most important input. Large firms and foreign firms hold on average more (20 and 2 1.6 days respectively). The retail sector holds on average more inputs (20 days of production) than the other sectors

South Africa

17

Namibia

I I

2281.9

The smooth operation along the supply chain requires easy transportation of goods between firms. As we can see in Table 2.20, only 3 1 % of manufacturing firms have their inputs delivered by mad. Whilst not explicitly asked, we presume that other means of transportation are commonly used, possibly railways, air or maritime transport. In particular, we observe that no firms outside Luanda have their inputs delivered by road. This explains why they perceive transportation to be a significant constraint (Table 2. l), but report no indirect costs of transportation (Table 2.4).

SubSaharan Africa

18

Supply chain problems often result in firms Finn size

33.5

Ownership

134.9 1024.5

Table 2.20 Percentage of Firms with Inputs Delivered by Road - Manufacturing Sector

Table 2.21 complements the results shown in Table 2.20 Some 40% of inputs are of foreign origin, with large firms (80%), foreign firms (67%) and firms manufacturing garments (58%) using a higher proportion of foreign inputs.

Given the high proportion of foreign inputs used for production, the good functioning of the customs agencies is essential in the supply chain. Only 20% of firms import directly and it takes approximately 28 days for incoming inputs to clear customs.

Industry

Manuf. - Rest of

t:;:ints- !::lf-" Retail the universe

24 40 33 NIA NIA

Table 2.21: Origin of Inputs - Manufacturing Sector

Source: ICA Survey

Percentage of firms with inputs delivered by road

I I I F i m ~ size I Ownership I Location I Industry I

Ownership

Foreign Dom.

12 33

Location

Luanda ;::$: 37

TOTAL

3,

Percentage of inputs o 1 40 1 3 1 68 80 ( 67 38 1 41 36 1 47 58 34 NIA NIA I

Firm size

Small Med. Large

35 20

Percentage Of inputs Of domestic origin

Source: ICA Survey

In comparison to other countries, the number of days needed to clear customs is clearly high. From Table 2.22 we can see that D.R. Congo (13 days), South Africa (7 days) and Namibia (3 days) have a speedier process for imports to clear customs. All country group comparators perform better than Angola in this respect aswell.

TOTAL

60

Table 2.22: Customs - Manufacturing Sector - Comparison across Countries - I Angola 1 Alge"a I D. R. Congo 1 South Africa 1 Namibia I ~ n b i ~ ~ m e l ~ ~ ~ i ~ b n n l , " , " , " $ ~ , "

Small Med. Large

66 32 20

I ~ v e . A of days to clear customs (imports) I 28 1 22.9 1 12.8 1 6.7 1 3.4 1 15.4 1 12.4 1 10.2 1 Source: ICA Surveys

Fonign Dom.

33 62

Whilst time needed to clear customs is one important variable, other aspects are also relevant. Table 2.23 contains some Doing Business indicators for the comparator countries regarding trading across borders. In Angola, importing is costly, time consuming and bureaucracy-ridden

Luanda :u\y:: 59 64

Manuf. - [:tra;;~ ~ ~ ~ ~ n U - ~ ~ ~ f ' :Y:- Retail the universe

53 42 66 NIA NIA

when compared to Algeria, South Africa and Namibia. Angola compares well to DRC, but in terms of cost and time for imports it ranks worse than the sub-Saharan Afiica average. A similar picture emerges when analysing exports, although the number of documents necessary for exporting is lower than in the other comparator countries, with the exception of South Afiica.

Documents fw export (number)

Time for export (dap)

Cost to export (US$ per container)

Documents fw import (number)

Time for import (dap)

Cost to impat (US$ per container)

Table 2.23: 'Ikading across Borders

I . .

I I I

Source: World Bank Doing Business Indicators 2006

Namibia Angola Sub-Saharan Africa Algeria D. R. M n ~ o

Therefore, transportation is indeed a problem in Angola, which generates indirect costs for h s . In addition, although customs is not perceived to be a significant constraint (Table 2. I), objective indicators show that it may indeed constitute a serious constraint for business, in particular, for the manufacturing sector which imports 40% of its inputs. For h s located outside Luanda, which perceive transportation constraints as more significant, it probably generates lower indirect costs because other means of tmnsportation are used.

South Africa

3 MICRO FIRMS

3.1 Constraints to Business

The main constraints identified by micro firmsz4 are electricity, access to credit, transportation, access to land, corruption and business licensing (Table 3.1). With the exception of access to land, all other constraints are also among the most important for the formal sector (although transportation is particularly relevant for firms located outside Luanda). As in the formal sector, location is a key factor in the perception of constraints: almost all k s outside Luanda identify access to credit as a major or very severe constraint, whilst access to land is a problem only for firms in Luanda.

Table 3.1 : Major or Very Severe Constraints as Reported by Micro Firms in Percentages

Constraint

Electricity

Access to finance (availability and cost)

Transportation

Access to land

Corruption

Business licensing and Permits

Crime, theft and disorder

Customs and Trade Regulations

Practices of competitors in inform. sector

Macroeconomic instability

Tax rates

Tax administration

Inadequately educated workforce

(~olitical instability I l~unctioning of the courts I ILabor Regulations

Source: ICA Survey

TOTAL

Ownership Location Industry

Outside Manuf. - Foreign Dom. Luanda Lwnda Food and Manuf.

- Manuf. - I Ibev. Garments Other Retail

Rest (

the universe

74%

The impact of some of these constraints on micro firms' costs is higher than for formal firms. The breakdown of indirect costs amounts to approximately 10.6% of total sales (Table 3.2). Electricity (5%) and corruption (bribes) (3%) are the two main causes of such costs. Firms located in Luanda are particularly affected (1 1.6% of sales), whilst firms outside Luanda have comparatively lower indirect costs (2.9% of sales).

24 Micm firms are firms wiB less than 5 Ill-time emplo~es.

Table 3.2: Indirect Costs - Micro Firms

1 Thel bile in lansit 1 0.8 1 0.2 0.9 1 0.9 0.1 1 1.5 0.0 0.4 1.3 0.1 1

Indirect costs as % sales

Electricity

Bribes

Breakage or spoilage in transit

Looking first at electricity, (Table 3.3), 90% of firms experienced power outages, on average 11 times per month, each lasting on average 15 hours. As a result, a significant proportion of firms own their own or share generators (50% of firms), which account for 43% of their total electricity needs.

TOTAL

4.0

3.1

0.4

1 Theft. robbery or arson

Total indirect costs

Table 3.3: Infrastructure Indicators - Micro Firms

Quality measure

Ownership

Foreign Dom.

2.4 5.1

0.2 3.4

0.2 0.5

Source: ICA Survey

1.4

10.6

TOTAL

Location

Outsae Luanda Luanda

5.2 2.4

3.5 0.2

0.5 0.2

1.5 1.3

4.5 11.2

Electricity Production lost (% annual sales) 1 4.8

Industry

Manuf. - Food and Manuf. - Manuf. - Rest of beverages Garments Other Retail the

universe

9.6 1.0 4.0 4.4 5.6

0.0 0.0 5.0 3.0 3.3

0.0 0.0 1.3 0.5 0.0

% firms experienced power outages

Frequency of power outages (times per month)

Duration of power outages (hours)

1 % firms with own generator ( 50

1.5 0.0

11.6 2.9

90

l, 15

0.0 0.0 0.1 1.3 2.2

11.1 1.0 10.7 10.5 11.2

Ownership

Foreign Dom

% electricity coming from own generator Number of days to obtain elecbical connection 52

Regarding corruption, Table 3.4 shows that close to 90% of firms believe that government officials do not interpret consis&ntly and predictably the law, whilst some 26% of firms report informal payments or gifts to be common to "get things done" regarding customs, taxes, licenses, regulations, etc. The perception of firms in Luanda is more favourable than that of firms outside Luanda, where almost all firms believe that officials do not interpret the law consistently and that informal payments are necessay to get things done.

Luanda Outside Luanda

Source: ICA Survey

Overall, firms spend on average 3.1% of their annual sales on informal gifts or payments. Also, when a government contract is at stake, firms expect to have to pay some 5.9% of its value in informal gifts or payments to secure it.

Manuf. - Food and Manuf. - Manuf. - Rest

Garments Other Retail the universe

Table 3.4: Perception of Government and Regulations - Micro Firms

Consistem and pedimble/ 13.2 1 20.0 12.5 1 14.3 4.8 1 0.0 0.0 7.6 18.2 intelpretation of the law

8.9 1

- -

% firms who agree with statement

Informal p"menwginj 25.8 1 10.0 27.4 1 28.6 4.8 1 0.0 0.0 38.1 26.8 commonplace

23.8 1

TOTAL

Advance knowledge of informal paymentlgift

Percentage of contract value paid to becure contract

I 5.1 I 7.4 5.7 1 6.6 0.5 1 1.9

Ownership

Foreign Dom.

Percentage of annual sales spent on informal

I I I I I I

Source: ICA Survey

,4.1

Similarly to the results of the formal sector, the perceptions of the court system are not very favourable: the great majority (60% to 70%) of micro firms think the court system is unfair, partial, corrupted, and not affordable. Firms in Luanda have the system in higher regard than do firms outside Luanda, although none of them have used the courts recently.

Location

Outside Luanda Luanda

pvmentslaifts 3.1

Industry

Manuf. - Food Manuf. - Manuf. - Rest o and bev, Garments Other Retail the

universe

0.0 15.5

Crime does not appear as a top 5 constraint for micro firms. Nevertheless it generates indirect costs totalling 1.4% of sales (Table 3.2). In addition direct costs (security services) associated with crime are in the order of 1.3% of sales (Table 3.6).

0.2 3.4

Table 3.5: Court System - Micro Firms

15.3 4.8 0.0 0.0 22.9 14.8 11.9

3.5 0.2

Characteristics of the court system

Fair, impartial and uncorrupted Quick Affordable Able to enforce decisions Percentage of firms with payment disputes in the past 2 years settled by third parties

0.0 0.0 5.0 3.0 3.3

Source: ICA Survey

Location

Luanda ~~~~~~ 31.6 4.8 27.6 4.8 48.0 4.8 58.2 4.8

5.1 0.0

Industry

Manuf. - Rest of and z:zLnt; E:kf' - Retail the

universe

61.9 76.4 15.3 23.4 35.6 61.9 76.4 45.8 18.2 20.8 61.9 76.4 53.4 37.1 44.5 61.9 76.4 61.0 49.1 50.5

0.0 0.0 7.6 3.4 5.9

TOTAL

28.5 24.9 42.9

51.9

4.5

Ownership

Foreign Dom.

30.0 28.4 40.0 23.4 70.0 40.2 80.0 49.2

0.0 5.0

One interesting result fiom the perceptions of micro firms is the fact that business licensing is also. identified as a significant constraint. The vast majority of micro h s in Angola have gone through some sort of licensinglregistration process: 87% have an approved or registered company name; 92% have a commercial registration; 91 % have an operatinggeneral license and 88% have a tax identification number (Table 3.7). Therefore, it is legitimate for these firms to perceive business licensing as a constraint because most of them have gone through a licensing process. However, this result suggests that defining the informal sector in Angola based on the number of full-time employees may not be entirely appropriate (see Henley et al. (2006)'~).

Table 3.6: Security Services and Security Expenditure - Micro Firms

Percentage of firms that paid for security services

Security wst as % annual sales

Source: ICA Survey

Table 3.7: LicensingDtegistration - Micro Firms

Indeed, we can see from Table 3.8 that micro h s iden@ time to complete the registration process as the most significant obstacle to obtaining a license, and this is particularly relevant for h s located in Luanda.

Source: ICA Survey

TOTAL

33

Percentage of f i n s with

Appmvedlregistered company name

Commercial regisbation

OperaSng/bade/generaI license

Tax identification number

25 Henley, A., Arabsheibani, G R and Cameim, F. (2006), "On defining and measuring the i n f d sector", World B d Policy Research Working

Paper 3866.

Ownership

Foreign Dam,

50 32

2.3 1.2

TOTAL

87

92

91

88

Location

Luanda Outside Luanda

38 0

1.5 0.0

Mership

Foreign Dorn.

90 87

100 91

100 90

100 87

Industry

Rest of Manuf. - Food Manuf. - Manuf. - Retail the and bev. Garments Other

univem

0 0 23 48 18

0.0 0.0 0.7 1.8 0.9

Location

Luanda ~~~~~ 86 100

91 100

90 100

87 100

indusby

,","tEv: Food zzLni Manuf. - Other Retail Of the universe

69 62 54 95 91

69 62 85 97 91

69 62 77 95 94

69 62 62 93 94

Table 3.8: Percentage of Firms Reporting Major or Very Severe Obstacles to Registering a Business - Micro Firms

Ownership

Minimum capital requirements

Financial cost of completing registration

Location

Obstacle

Time to complete regismtion

IAdministrative burden of complying with tax laws I 17% I 20% 17% I 19% O% I 1 Other administrative burdens 1 16% 1 20% 16% I 18%

I

TOTAL

28%

Difficulty of getting necessary information 14% 0% 16%

Financial tax burden after regisbation 1 12% 1 20% ::z 1 13% 5%

Foreign Dom.

10% 30%

Looking at more detail at the overall regulatory framework, Table 3.9 shows that on average 8% of senior management time is spent with government regulations. Moreover, on average close to 83% of all firms were visited by officials an average of 8 times each year. This is similar pattern to formal sector firms - see Table 3.11.

Luanda Outside Luanda

32% 5%

I Strict labor market rules

Table 3.9: Regulatory Burden - Micro Firms

Source: ICA Survey

5%

Quality measure

% senior management time spent with regulations

% firms visited by officials

Obtaining licenses is a lengher process for micro firms (Table 3.10): it takes some 80 days to obtain a construction-related permit and 64 days to obtain an import license. This is particularly so for firms in Luanda.

10% 4%

Number of inspection visits (last 12 months)

5% 0%

TOTAL

8.2

82.9

Source: ICA Survey

7.5

Ownership

Foreign Dam,

8.8 8.2

90.0 82.2

10.4 7.2

Location

Luanda Outside Luanda

8.9 2.9

80.6 100.0

Industry

Manuf. - Food Manuf. - Manuf. - Rest of

and bev. Garments Other Retail the universe

1.9 3.1 8.9 9.3 7.3

38.1 23.6 84.7 89.7 79.2

8.2 3.2 5.5 3.0 15.9 7.5 4.2

Table 3.10: Licensing Process - Micro Firms

Location

~~onst~ct ionrelated pt'd 1 80.1 1 1041 7.0 I NIA NIA NIA 90.0 60.4 1

Industry I Number of days to obtain:

1 h import license 1 642 1 72.9 7.7 1 7.0 NIA NIA 67.6 64.3 1

TOTAL

3.2 Comparison between formal sector and micro b s

An operating license

As we can see from Figure 3.1, there are minor differences between firms in the formal sector and micro h s in the identification of their main constraints: the top 6 constraints of formal firms are also main constraints for micro firms, with the only exception of access to land.

Luanda Outside Luanda

Figure 3.1: Percentage of Firms Reporting Major or Very Severe Constraints (Top 6 Constraints for Formal Sector) - Formal Sector versus Micro Firms

BOY. ,--- - --- ----

Manuf. - Rest of Food and - -

Garments Other Retail the universe

Source: ICA Survey

34.4

Source: ICA Survey

On the other hand, indirect costs are slightly higher for micro firms, especially because of theft, robbery or arson (Figure 3.2).

42.1 8.6 8.0 8.0 20.4 28.5 47.8

Figure 3.2: Indirect Costs -Formal Sector versus Micro Firms

Eiectllcity Bllbes Wll, mbbgl w amon Tdal indirect ccsls

Source: ICA Survey

Micro finns face a somewhat similar regulatory burden, except for visits by official (Table 3.11).

Table 3.11 : Regulatory Burden - Formal Sector versus Micro Firms

Quality measure Formal Micro

% senior management time spent with regulations I 7.7

% firms visited by officials

The percentage of annual sales spent on giWinforma1 payments is the same for micro firms and firms in the formal sector (Table 3.12). While government officials are held a bit in higher regard

. in the formal sector where 23% of firms believe officials to have a consistent and predictable interpretation of the law, compared to only 13% among micro firms.

Number of inspection visits (last 12 months)

Table 3.12: Perception of Government and Regulations - Formal Sector versus Micro Firms

5.2 7.5

1 % firms who agree with statement

Source: ICA Survey

1 Formal Micro 1 Consistent and predictable interpretation of the law

Informal paymentslgifts commonplace

Advance knowledge of informal paymentlgift

23.4 13.2

23.8 25.8

7.0 14.1

Percentage of annual sales spent on informal paymentslgifts

Percentage of contract value paid to secure contract

3.3 3.1

4.5 5.9

Source: ICA Survey

Regarding infrastructure (Table 3.13) again micro firms and firms in the formal sector are equally affected by power outages. The most significant difference is that more firms in the formal sector have generators (68% versus 50% among micro firms), but these are more important for micro firms (generators are responsible for 43% of electricity needs of micro firms, compared to 3 1 % in the formal sector).

I % firms experienced power outages

Table 3.13: Infrastructure Perceptions - Formal Sector versus Micro Firms

1% electricity coming from om generator

Formal Miuo Type

Electricity

Number of days to obtain electrical connection Source: ICA Survey

Quality measure

Frequency of power outages (times per month)

Duration of power outages (hours) Production lost (% annual sales)

% firms with own generator

4 FACTOR MARKETS: FINANCIAL SECTOR, LABOR AND LAND MARKET

4.1 The Financing of Firms in Angola

As we have seen in chapter 2, access to finance is a major constraint to business in Angola. Thus, this section analyses firms' access to finance in detail, along with labour market and land.

In order to operate, firms need short-term and long-term finance. In Angola, the main sources of working capital are firms' own retained earnings (8 1 %), with trade credit (1 1%) emerging as the second largest source of finance (Table 4.1). The banking sector accounts for a meagre 1% of total short-term financing needs. Firms outside Luanda rely even more on internal funds (94%).

A similar pattern is observed for long-term finance (Table 4.2). Retained earnings are the main source of finance (89%), with a slightly more important role of the banking sector (4%). The firms' reliance on the banking sector for their long-term finance depends sigmficantly on their size. Large firms rely on the banking sector for 25% of their long-term finance, while small firms rely on the banking sector for only 4% of their long-term finance.

Table 4.1:. Sources of Short-term Finance in the Formal Sector

Table 4.2: Sources of Long-term Finance in the Formal Sector

l ndustry

Rest of - Manuf. - Ynuf . - and bev, Garments Other universe

78.1 82.8 80.2 85.9 81.2

1.0 0.0 1.0 0.5 2.8

14.5 5.5 10.9 6.5 13.2

6.4 11.8 8.0 7.2 2.8

I s s l s d ~ ~ d s b t 1 0.1 1 0.1 0.0 0.0 1 0.9 00 1 0.1 0.0 0.0 0.0 0.0 0.0 0.6 1 1

Source: ICA Survey

Source: ICA Survey

% short-term financing from

Internal funddRetained earning

Borrowedfmmbanksandatherfinancial institutions

Purchases On suppliers and advances frwn customers

BorrOWedfrmfami~ylfriendsandother informal sources

%kf@lmfirmi~fran

Irhm;l fmWFWAnedeaTirgs

fran ad i f l m

Rnfrases fran alas ad &atx3franastarers

f3mJm-J fran f;rrilyTrimk ad other i ~ s c u n e s

Ownership

Foreign Dom.

75.3 82.5

2.8 1.0

14.6 10.1

7.3 6.5

TOTAL

81.4

1.2

10.7

8.7

Location

Outside Luanda Lwnda

78.8 93.8

0.8 3.3

12.4 2.9

8.1 0.0

T O T A s r e l l

885

51

12

80

Firm size

Small Med. Large

83.2 68.8 83.0

0.9 3.4 0.0

8.5 26.0 15.0

7.3 2.5 2.0

90.5 826 68.8

4.0 6 1 250

a7 26 6.3

53 9.9 0.0

~ ~ F a e i ~ h L u a 7 d a ~ F o o d

75.3 90.5

159 34

4.4 0.7

5.0 61

87.9 91.1

4.0 9.3

1.5 0.0

7.4 0.0

FlBst d atsidSw.-w. -w.-

ad bev. uiwse

828 91.7 91.4 E 3 84.9

4.8 0.0 1.9 4.7 13.1

20 0.0 1.8 0.0 0.0

126 83 5.8 0.0 1.4

A comparison between the sources of finance of the formal sector and of micro firms shows that they have a similar pattern, both for short and long term finance (Table 4.3).

Table 4.3: Sources of Finance - Formal Sector versus Micro Firms

%financing from

Ilntemal hmnddRetained earnings 1 81.4 83.0 1 1 . 5

Shwt-term

Formal Micro

Long-term

Formal Micro

)Borrowed from familyfiriends and other informal sources 1 6.7 2.8 1 6.0 2.4 1

Borrowed from banks and other financial institutions

Purchases on credit from suppliers and advances from customers

Source: ICA Survey

In comparison with other countries (Table 4.4 and Table 4.9, firms in Angola have to rely more on their own resources (81% for short- term and 89% for

1.2 2.6

11.5

long-term capital) than do finns in Algeria (74% and 73% respectively), South Africa (66% and 58% respectively) and Namibia (60% and 74% respectively). Only DRC shows a similar pattern to Angola. In most countries the role of the banking sector as a source of finance is more important than in Angola. A comparison with country groups yields a similar conclusion.

5.1 8.5

1.2 0.0

Table 4.4: Sources of Short-term Financing - Comparison with Other Countries

source: ICA Surveys

% short-tern financing from

Internal funddRetained earnings

BomMed from banks and other financial institutions Purchases on credit fmm suppliers and advances from customers B o m d from familylfriends and other informal swrces

Issued new equityldebt

South Africa

66

17

12

4 -

1

Angda

81

11

0

Namibia

67

6

24

3

0

Algeria

74

11

9

6

0 -

D. R. h g o

81

3

15

1

0

countries

72

10

12

6

1

Sub-Saharan Africa

70

11

14

6

1

Resource rich countries

77

8

10

5

2

Table 4.5: Sources of Long-Term Financing - Comparison with Other Countries

Internal fundrnetained earnings 1 88 Bolrowed from banks and Othe financial institutions

Bormwed from famllylfriends end other informal sources

Algeria

Issued new equityldebt 0

Looking at this issue in more detail, Table 4.6 shows that only 1.6% of firms in Angola have an overdraft facility and only 4.1% have loans. F h s outside Luanda report having no overdraft facilities, which may explain why they perceive access to credit as the most significant constraint to business (see Table 2.1). As one would normally expect, the percentage of large firms with loans (60%) is larger than that of small (3%) or medium firms (8%).

D, R,

85

6

3

5

Source: ICA Surveys

Table 4.6: Access to Credit in the Formal Sector

I 1 I Finn *u I Ormership Location I Industry I

South Africa

58

33

1

8

Namibia

74

20

2

4

%firms with

Overdrafts

From an international perspective firms in all other countries have better access to credit than firms in Angola (Table 4.7). In Algeria, 39% have an overdraft facility and 53% have loans; in DRC, the closest to Angola, 5% of firms have overdraft facilities and 6% loans. Country group comparators highlight a much greater reliance on overdraft facilities everywhere other than in Angola.

Lines of credit 1 loans

Table 4.7: Access to Credit - Comparison with other Countries

LOW income countries

73

17

2

7

TOTAL

1.6

Source: ICA Survey

4.1

Sub-Saharan Africa

71

22

2

7

Small Med. Large

1.3 4.2 0.0

% firms with

Overdrafts

The lack of loans from banks to firms implies that firms rely little on banks as sources of finance, which confirms that access to finance is indeed an important constraint, especially for small and medium firms.

Resource rich countries

76

18

1

6

2.8 7.6 60.0

Lines of credit 1 loans

Foreign Dom.

4.4 1.2

Angola

1.6

9.5 3.2

1 Note: For South Afiica, and country group comparators, lines of credit are included in overdrafts. Source: ICA Survey - Angola, Algeria, D. R. Congo and South Africa

4.1

Luanda Outside Luanda

2.0 0.0

38.6

Manuf. - Rest of Food and - - beverages Garments Other Retail Me

universe

2.8 0.0 0.8 2.8 1 .O

3.1 8.8

52.9

2.8 0.0 4.1 2.8 7.9

D, R, Congo

5.0

5.9

Sourn Africa

68.0

39.3

Namibia

26.8

NIA

LOW income countries

30.2

NIA

SubSaharan Africa

35.0

NIA I NIA 1

Resource rich covnhies

27.4

Requiring collateral for loans is a widespread practice in Angola (see Table 4.8). In the formal sector, 93% of h s report it to have been demanded for their loans, whilst all micro f i m had to provide it. The value of the collateral, as a percentage of the amount borrowed, is larger for micro firms (1 13% of the loan) than for firms in formal sectors (99.6%). The most frequently given type of collateral in the formal sector is accounts receivable or inventories (42% of firms have given this type of collateral), whilst for micro firms it is personal assets (36% of firms have given this type of collateral).

Table 4.8: Collateral -Formal Sector versus Micro Firms

I Formal 1 1% firms whose loans required collateral 1 93.4 ( 100.0

Value of collateral required (% loan)

Land, buildings

Type of collateral Machinery and equipment including movables required (% of firms with affirmative Accounts receivable and inventories answers)

Personal assets of owner (house, etc.)

Such collateral requirements are very different in Angola (compared to other countries). As we can see fiom Table 4.9, collateral is more frequently demanded in Angola (93% of cases) than in Algeria (82%), the DRC (go%), South Afiica (69%) or Namibia (74%). However, its value (as a percentage of the amount borrowed) is lower than in these countries. The same is true when we look at comparator country groups.

99.6

24.7

Other

Table 4.9: Collateral - Comparison with other Countries

113.1

28.8

18.3

41.6

30.7

31.6

11.0

35.8

Source: ICA Survey 7.4

Source: ICA Surveys

0.0

% Rrms Aose loans required cdlatera

Value ol mllateral required (% loan)

One reason which may help to explain the low reliance of Angola's firms on the banking sector may be the cost of debt - the interest rate. Avmge interest rates in the formal sector are approximately 6% for overdrafts, 9% for lines of credit and 8% for loans. With inflation (consumer prices) running at around 13% in 2 0 0 6 ~ ~ , this results in a negative real interest rate. The cost of debt cannot be a convincing explanatory factor for the low reliance on banks for financing

26 NF, Data and Statistics - 23% in 2005 and 12.9% in 2006 (inflation - wnsumer prices).

4s

Note: For South Africa, the values in the table refer to loans payable in more than one year

93.4

99.6

Algeria

82.4

184.6

A,rica

68.9

132.8

D, R.

90.0

134.2

Namibia

72.8

182.2

Sub-Saharan Africa

77.9

' 161.0

LOW income countries

81.9

171.5

Resource rich countries

78.1

173.3

purposes by Angola's firms since the cost of bank credit is lower in Angola than in all comparator countries. (Table 4. lo),

Table 4.10: Cost of Debt and Duration - Comparison across Countries

Sowce: ICA Surveys

Our conjecture is confirmed by Table 4.11: the main reason why Angola's firms (formal sector) do not apply for loans is related to the complexity of the application process (cited as the main reason by some 30% of firms). Other factors which are cited as reasons for not applying include, in descending order of importance, having sufficient capital and thus not needing a loan (19% of firms), the perception that the loan application would not be approved (18% of firms) and only thereafter high interest rates (1 6%). Small firms are particularly affected by the complexity of loan applications.

Table 4.11: Reasons for Not Applying for Loans - Formal Sector

Note: For South Afiica, the values in the table refer to loans payable in more than one year

Sub-Saharan Africa

15.3

43.2

Resource rich countries

15.0

47.4

Namibia

12.4

66.1

Low income cwnbies

17.4

34.5

Algeria

11.3

25.3

D. R. Congo

11.5

35.2

Line of credit 1 loan

Average annual interest rate

Duration (months)

% firms citing as main reason for not applying for loans:

South Africa

11.0

70.0

Angola

8.5

48.6

No need for a loan - establishment has sufficient capital

Application procedures for loans or line of credit are complex

Interest rates are not favorable

Collateral requirements for loans or line of credit are unattainable

Size of loan and maturity are insufficient

Did not think it would be approved

Concrete results of loan applications confirm the perception that collateral requirements and the complexity of application process are the 2 main reasons for a low banking penetration in Angola.

Firm size

Small Med. Large

1 Other

TOTAL

14.2 33.6 50.0

34.7 18.1 0.0

16.8 22.8 0.0

7.1 2.3 0.0

5.4 10.6 0.0

19.2 4.5 0.0

18.9

29.7

16.2

8.4

5.4

18.4

Sowce: ICA Survey

2.7 8.1 50.0 3.0

Close to 79% of loan applications in the formal sector are rejected, 46% because of unacceptable collateral or co-signers and 23% because of incomplete applications (Table 4.12).

Table 4.12: Loan Application/Rejection

% firms applying for loansllines of credit

Problems with credit historylreport 1 Reasons for reiection

% rejected applications

Collateral or cosigners unacceptable

Insufficient profitability

of loansllines of -&edit Incompleteness of loan application

16.9

I Concerns about level of debt already incurred I 1 O 0 I

15.5

78.8

46.0

7.5

I Other 1 5.9 1 0.0 1

78.7

55.9

14.7

I I I I

Source: ICA Survey

Overall, access to credit is clearly an important constraint for Angolan firms, especially small and medium sized firms. Looking at its two dimensions - availability and cost - the ICA data leads us to conclude that cost of debt is not the main explanatory factor for this finding. The problem is related to the requirements demanded by banks, such as the acceptability of collakraVco-signers and the loan application itself.

4.2 The Formal Labor Market in Angola

Labor regulations appear to be one of the least important constraints for firms in Angola (see Table 2.1). In fact, 96% of firms in the formal sector and 96% of micro firms report that labor regulations did not affect their decisions to hire or fire workers.

In a comparison across countries using Doing Business indicators (Table 4.13), we can see that labor regulations are less stringent in Angola than in the other comparator countries (except Namibia), particularly regarding the hiring of workers. The Difficulty of Hiring indexz7 is lower in Angola than in Algeria, the DRC and South Africa, and it is also lower than the sub-Saharan f i c a average. The hiring cost (8% of salary) refers to the non-wage labor cost and measures all social security payments. It is lower than the sub-Saharan Afica average (1 3%), but higher than in DRC (6%) and South Africa (2%).

27 Each index varies from 0 to 100, with higher values indicating more rigidity.

5 0

However, both the rigidity of hours' index and the difficulty of firing index have relatively high values. When combined into the Rigidity of Employment Index (an average of the difficulty of hiring index, the rigidity of hours' index and the difficulty of firing index) we see that Angola has relatively rigid labor market regulations, with only the DRC having a higher value for this index. Despite this, firms in Angola do not put labour regulations among their top concerns of the business environment (see Table 2.1).

Table 4.13: Labor Regulations

I I Angda I Algeria D. R. Congo

Dniiulty of Hiring Index

Rigidity of Hwrs Index

DKiuity of Firing Index

Rigidty of Employment Index

Hiring cost (% of salary)

Firing costs (weeks of wages)

South Ahlca Namibia

Source: World Bank Doing Business Indicators 2006

33

80

80

64

8.0

58.5

Sub-Saharan Africa

44

60

30

45

27.5

17.0

Small firms account for the majority of total employment in Angola's formal sector firms - approximately 61% of the total. Medium firms account for 27% and large firms for 11%. Since 2002, the majority of h s have added workers - 57% of small firms and 80% of large firms. Thus, an average firm in Angola now has 14.3 workers compared with 13.3 in 2002 (see Table 4.14). This growth in the number of employees is clearly more felt for firms based in Luanda.

Table 4.14: Employment: Full-time Permanent Workforce - AU Formal Sectors

I I I Flm size 1 Ormershlp I Location I Industry

I I rnvt -

Rest c Small Med Large Foreign D m , Luanda :u:yz ;ecm;;t p:;n~ EE: - Retail the

universe

I Employment per firm - 2006 ( 14.3 1 10.2 31.0 122.01 19 1 13.5 1 14.5 13.5 1 17.4 8 6 17.0 10.5 128

I Employment per firm - 2002 1 13.3 1 8 6 240 108.4 20.2 12.3 1 13.4 13.1 1 14.9 6.8 16.5 10.2 112

Full-time seasonal or temporary employment is, by comparison, not very common. As we can see from Table 4.15, the average h in Angola employs 2 full-time temporary workers, 13% of which are female. Foreign firms rely more on that type of workers, employing on average 4.4 workers. Firms in the retail sector also rely relatively more on temporary full-time workers (4.6 workers on average).

Percentage of firms adding workers

Source: ICA Survey

511.2 56.5 63.8 80.0 63.3 57.5 69.2 27.5 57 7 68.6 66.4 41 9 56.9

The workfo~e in the manufacturing sector consists mostly of production workers (79% of the total), 14% of which are female and 8 1 % of which are skilled. The female share of the production workforce is more significant in the manufacturing of garments (51% of the total). The female share of non-production workers is larger than that of production workers, and this is true for the various firm sizes or sector of activity (see Table 4.16).

Table 4.15: Employment: Full-time SeasonabTemporary Workforce - All Formal Sectors

Table 4.16: Description of Workforce - Manufacturing Sector

Employment perfirm

% female workers

TOTAL T -

% of non-production workers

Source: ICA Survey

TOTAL

2.0

13

% female non-production workers

% production workers

Firm size

Small Med Large

2.0 2.4 1.0

12 33 2

% female production workers

% skilled production workers

Ownership

Foreign D m .

4.4 1.6

28 10

Source: ICA Survey

Firm sue

Small Med. Large

Location

Luanda :z: 2.5 0.0

13 NIA

1 Ownership I Location I Industry

Industry

Manuf. - Rest of

Fttm;;d :z gtf' - Retail the universe

1.4 I .4 1.2 4.6 1.2

8 1 5 15 33

Food and Manuf. - Manuf.

beverages Garments Other

Most of the workforce in the manufacturing sector is not unionized. From Table 4.17, we can see that only 7% of the workforce is unionized, mainly in medium and large firms and in firms located in Luanda.

Table 4.17: Unionized Workforce - Manufacturing Sector

Firm size

From Table 2.1 (all formal sectors) and Table 2.2 (manufacturing sector) we also fmd that the workforce education is not perceived to constitute a significant constmint. We look deeper into this issue in Table 4.18, which shows the average educational attainment in terms of years of education of a typical production worker in the manufacturing sector. More than half of the firms (81%) report their typical production worker to have between 7 and 12 years of education. Roughly this

Percentage of unionized workforce

Ownership

Source: 1CA Survey

TOTAL

6.8

Location Industry

Small Med. Large

2.6 25.8 45.0

Foreign Dom.

6.8 6.8

Luanda

7.2 4.9

Manuf. - Food and !:zLn,- !E: - beverages

9.8 0.3 6.3

may correspond to complete secondary schooling and some university training. One third of the firms have a workforce with only primary education completed. Only 14% of firms say that their typical production worker has 3 or fewer years of education (incomplete primary schooling).

Interestingly, firms outside Luanda clearly report that their typical production worker has fewer years of education than the average: more firms report fewer than 3 years of education (26% compared to the 14% average), 4-6 years (52% compared to the 33% average) and 7-12 years (1 9% compared to the 48% average). Despite this, firms outside Luanda perceive an inadequately educated workforce to be less of a problem than firms located in Luanda (see Table 2.2). This may be related to the type of firm and its particular needs in terms of worker's education: firms located outside Luanda may require a less skilled worldbrce, which explains why they perceive education not to be a significant constraint. By contrast, firms in Luanda may require a more skilled worldbrce which, in 31% of Luanda's firms (the percentage of firms which consider an inadequately educated workforce to be a major or very severe constraint), they cannot find.

Table 4.18: Average educational attainment of production workers - Manufacturing Sector F i n size I ownership I Location I Industry I

0-3 years of education

In a comparison with other countries, presented in Table 4.19, we see that the educational level of workers in Angola is considerably lower than that of all comparators (with the exception of Algeria): workers in Angola are more likely to have fewer than 6 years of education than in all country and group comparators. Additionally, the percentage of workers with more than 13 years of education of Angola is much lower than in all country and group comparators.

4-6 years of education 7-12 years of education > I3 years of education

Table 4.19: Average educational attainment of production workers - Comparison across Countries - Manufacturing Sector

TOTAL

14.1

Source: ICA Survey

32.6 48.3

1.9

Source: ICA Surveys

Small Med. La-rge

13.1 22.3 0.0

<6 years of education 6-12 years of education > 13 years of education

The question one must ask is why do firms in Angola not complain more vehemently about an inadequately educated workforce (fiom Table 2.1, only 21% believe this to be a major or very severe constraint). One possibility is that the production process of most firms does not require such skills. This would occur if firms have adapted their production technologies to the level of education of the workforce. Another possibility is that firms compensate such low levels of education with training programmes.

33.1 28.4 40.0

48.8 43.0 60.0 2.3 0.0 0.0

Foreign Dom.

11.7 14.3

Note: For Algeria, the values in the table refer to qualified workers

Angola

47 48 2

33.4 32.5

49.4 48.2 0.0 2.1

Luanda Outside Luanda

11.8 26.1

Algeria

58 32 10

Manuf. -

Food and Eztn& 0":; - beverages

15.5 0.0 15.6

28.8 52.4

53.9 19.3 2.3 0.0

28.8 25.4 35.8

47.6 68.8 45.4

1.4 5.7 1.6

D. R. Congo

38 52 11

South Africa

10 78 12

Namibia

NIA NIA NIA

Low income countries

11 78 13

Sub- Saharan Africa

10 72 12

Resource rich countries

15 70 15

Training is often a complement for education, which could help explain why workforce education is not identified as a significant constraint Table 4.20 shows that 19% of manufacturing firms have offered training to their employees, mostly production workers. Foreign firms are more likely to offer employee training than domestic ones, and the larger the firm is, the more likely it is to offer training to its employees. Although very few firms outside Luanda identify an inadequately educated workforce to be a major or very severe constraint to business (see Table 2.1 and Table 2.2), 25% offer training to their workers (compared to 18% of firms in Luanda). Such training is particularly targeted at production workers.

Table 4.20: Firms Offering 'kaining - Manufacturing Sector

Source: ICA Survey

% of h s offering training

% production workers receiving baining

% non-production workers receiving baining

In an international comparison (Table 4.21), we see that firms in Angola offer training less frequently than in all other comparators (with the exception of D.R. Congo). However, when we look at who receives training, production workers in Angola receive training to a larger extent than those comparators.

Table 4.21 : Firms Offering 'kaining - Manufacturing Sector - Comparison across Countries

TOTAL

19

53

12

1 % productlm workers receking training 1 61 1 tVA I 63 I 45 I 48 I 7 1 22 1 19 I

F i n she

Small Med. large

14 37 80

44 74 46

7 26 11

YO of firms offwng training

Source: ICA Survey

Ownership

Foreign Don.

50 . 17

61 50

33 7

Angola

19

% nm-production workers receiring training

This analysis lends some support to the conjecture that despite the relatively low level of education of the workforce, firms might perceive this not to constitute a problem if training were indeed a complement of education.

Absenteeism is a problem in Angola. As we can see from Table 4.22, 44% of firms report high absenteeism due to sickness and 26% due to HIVIAIDS. The results obtained through the employee questionnaire show that 19% of workers have been sick during the last 30 days, on average missing 4.3 days of work. They also show that 63% of workers see HIVIAIDS as a big concern.

~ocatic-n

Luanda Ez:i 18 25

40 100

13 9

12

lndusby

Manuf. - [;oo&and pzki g$'

ges

17 17 21

86 35 40

22 0 10

Algeria

32

0. R. Conga

11

NIA

South Afrlca

64

Namibia

44

37

rich camtries

31

cwntries

35

Sub-Saharan Africa

40

47 69 21 27 22

Table 4.23 shows that firms are concerned with HTV: 61% of firms have helped spread I-lW prevention messages. However, a much lower percentage has undertaken other important activities, such as h e condom distribution or anonymous I-lW testing.

Table 4.22: Absenteeism - AU Formal Sectors

In order to ascertain the determinants of wages, we have estimated four basic wage equations using Ordinary Least Squares (OLS) (see Table 4.24). Such regressions allow us to quantify marginal returns to education or experience, as well as other worker (e.g. gender) andlor firm characteristics (e.g. firm size).28

Table.4.23: H l V Prevention Activities - AU Formal Sectors

In the first model, we attempt to explain wage levels as a hc t ion of years of education (schooling), years of past experience, gender and the number of hours worked per week. In the second model, we introduce an additional explanatory variable: whether the worker has undergone - formal training in the past.

Source: ICA Survey

Ormenhip

Foreign Drm

36 46

19 11

21 27

4 4 0 0 9 3 5 1 0 0

Firm size

Small Med Large

44 45 40

13 10 20

25 28 40

% reminD high absenteeism due to

Om sickness

Familyffriends sickness

HIVIAIDS

Familyffriends HIVIAIDS

28 We have excluded 5 observations frmn the sample: 2 because of extremely low reported salaries and 3 because of exmmely high reported

salaries.

TOTAL

44

12

26

Of which undertook:

HIV prevention messages

Free condom distribution

Anonymous HIV testing

Location

Luanda E:!:

33 100

15 0

10 100

Source: ICA Survey

Firm size

Small Med. Large

61 62 80

30 39 20

5 10 0

TOTAL

61

31

6

Industry

Manuf. - Rest of Lcm;i E$ - Retail lhe univefse

51 48 39 44 47

7 0 11 18 17

35 20 19 26 30

1 0 4 8 2

Ownership

Foreign Dom.

56 62

36 30

10 5

Location

Outside Luanda Luanda

54 98

31 33

7 0

The third model introduces other possible firm-specific explanatory factors, namely firm size and whether the firm is foreign-owned. Finally, in the fourth model we control for industry.29

Table 4.24: Determinants of Earnings - Manufacturing Sector

I Dependent variable: Log annual wages

Std. error Experience

Std. error I Female

Std. error

Log (hourslweek) Std. error 0.159 "* 0.158 "' 0.157 *** 0.157 no

Past training 0.276 0.260 Std. error 0.063 "* 0.060 "* 0.059 ***

Constant 2.872 3.21 3 2.743 2.360 0.635 " 0.641 "' 0.645 "'

(***) Statistically different from 0 at a 1% significance level

I Std. error Firm size (large)

Std. error Foreign

Std. error Sector: manufacturing - other

Std. error Observations

(**) Statistically different from 0 at a 5% significance level (*) Statistically different from 0 at a 10% significance level Source: ICA Survey

0.064 "* 0.070 0.721 0.659

0.133 *** 0.133 "* 0.450 0.438

0.083 "' 0.082 "' 0.214

0.065 "' 484 484 466 466

In all models, education appears with clearly positive marginal rates of return: every additional year of education increases a worker's salary by 2.3 - 3.7% (across models). Assuming all other factors are constant, a female worker typically receives a salary which is 12.2 - 17.8% lower than that of a male worker. Experience appears to be a significant explanatory variable in models 1 and 2, but once firm-specific characteristics are controlled for, its coefficient is no longer statistically different from zero.

Training yields high returns to workers: those who have undergone formal training courses in the past have salaries which are 26 - 27% higher than those who did not.

29 Several h e r specifications were tested using union membership, years of work in the firm (tenure), Ill-time worker soitus, whether the worker is

currently receiving training and iirm location, whose coefficiena are not significantly different lium zero, i.e. appear not to explain salary levels. Often

schooling or experience pment decreasing marginal returns, i.e. contribute less to salary increases as tfieir level also increases. This was tested by

huducing bah variables squared in the re-ion, but k i r coe5ciena were not statistically diffmt fium 0. Other sector dwmnies were also tested,

b u ~ theircoe5ciena were not statistically difirent fium 0.

Firm size appears to be an important explanatory factor of wages, particularly if a firm is large. If this is the case, salaries are some 66 - 72% higher than in small firms. The same result is true for foreign firms, which (assuming everythmg else to be constant) pay salaries that are 44 - 45% higher than in domestic firms.

These results may help explain why the level of education of the workforce is not perceived to be a significant constraint. Indeed, training appears to be a good substitute for education: in terms of salary, workers who have undertaken training courses in the past have a salary which is higher than those who have not. In addition, such training courses are equivalent, in terms of salary, to an additional seven years of education, which is substantial (average education is 8.2 years).

4.3 Land Market

Overall, access to land is not perceived as a top constraint to business in the ICA survey. In fact, micro firms rank it fourth (after electricity, access to finance and transportation), while firms from the formal sector rank it eighth, as shown in tables 2.1 and 3.1. However, one of the main reasons access to land is currently not regarded as a major problem is that f m s - as well as the general population - tend to consider the land they occupy as their property. Therefore, it is highly probable that access to land will be regarded as a serious constraint to business in the near future, as firms become more aware of the potential impact of recent legislation on land rights.

The Angolan legal system is derived fiom the Portuguese colonial system, adapted after independence. The Law No. 2030 of 1948 was the basis for land law. The new Constitution of 1975, on the other hand, established the overall right of the state to all land, which could be transferred based on its use. The Law 2 1 C of 1992 regulated the concession of land for agricultural use, on the basis of surface land use rights. Also in 1992, the Decree 46A gave the Provincial Government the right to concession, including in urban areas.

In 2002, the process of creating a new Land Law began, and a first draft was finalized in July that year. The Law (Lei de Terras - Law No. 9 of 2004) was finally published in November 2004. It is worth stressing out the difficulties involved and the length of the process of creating legislation regarding an issue as essential to economic development and stability as are land rights.

It must be noted, however, that the actual land occupancy and use have little resemblance to what is established in the legal framework: In fact, the findings of a field research undertaken in the peri-urban areas of Luanda showed that 43% of respondents had no awareness of the legal concept of land rights, and only 13% had a reasonable awareness of land rights issues (Development Workshop, 2005).

Since independence, Angola's population distribution has changed dramatically. As living and security conditions deteriorated, in particular during the civil war, there was a clear exodus fiom inland towards the main urban areas. In Luanda, in particular, there has been an exponential population growth since independence, not for demographic changes, but due to voluntary and forced migrations from other parts of the country. There were two periods when this trend was most obvious. These were immediately after independence, and when civil war reached its peak. There are no official numbers for the 1970s and 1980s but, between 1995 and 2000, it is estimated that the population in Luanda increased from 2,070,000 - with an overall average growth rate

estimated at 6.7% per annum - to 3,150,000 - with a growth rate estimated at 8.23% per annum (Development Workshop, 2003). And the tendency is for this growth to continue, even today.

As an emergency measure, during the last thlrty years land has been allocated extensively in peri- urban areas, as inner areas were already occupied. While pen-urban areas grew rapidly, the legal, administrative and technical capacity of the state was severely affected. In addition, due to war, the national cadastre was taken over by the Ministry of Defence, whose main priority was naturally not urban development and, as a result, the cadastre became completely out of date.

The Constitution defines that land formally belongs to the state, with the exception of a limited number of entities which had full freehold land rights before independence and did not lose them since then, namely through abandonment, confiscation or nationalisation. The new Land Law confirms it, namely by stressing out in its 6th article the point that acquisition of land by usucapiCo (i.e. the right to occupy land by virtue of a factual occupation for a given period of time) is illegal. This decision was taken despite strong pressure fiom the various economic agents involved for the state to recognise that, after thirty years of informal occupation, a legal h e w o r k should be developed to provide the residents the right to be where they are.

In Luanda, some formal market-related activity does exist: after venfylng actual occupation, the cadastre is checked (despite being completely out of date) and, if it contains a previous land registry, there needs to be a public announcement to confirm that is has been abandoned or if there are still legitimate rights (Development Workshop, 2003). Even so, as state supply of land has been virtually non-existent, the large majority of urban dwellers have accessed land through informal mechanisms. However, given the conditions in which it happened - often involving local administrative institutions - and the time elapsed since then, most of them consider they have valid rights to the land. In fact, an active informal market is in place, the most common mechanism being the purchase of land with witnessed purchase documents, and such land occupations and constructions therefore do have some legitimacy. As a result, Development Workshop (2005) observed that, in Luanda, around 80% of those interviewed had occupied their land through informal mechanisms, while 86% felt secure of their land. On the other hand, if we look at the results from the ICA survey, we can see that, in Luanda, around 66% of firms from the formal sector and 46% of micro firms believe they own the land they are occupying.

There are serious limitations on what the government can do in moving to formal rights in the short term. However, there needs to be a distinction between land rights and land titles and, in order to gradually evolve to the latter, it is necessary to emphasise the former (Development Workshop, 2005).

At present, firms can only legally register the land if they acquire it from the state or from someone with full freehold land rights. This may explain, for instance, why land is not often used as collateral in loans. On the other hand, if we look at the results from the ICA survey in greater detail, we can see that foreign firms fiom the formal sector already consider access to land to be their fifth constraint to business, after conuption, electricity, crime, theft and disorder and access to finance. This is not surprising, as the Land Law determines, in its 35th article, that only Angolan individuals can buy land from the state. This means that foreign firms can only obtain property rights by acquiring already privately-owned land, which is rather scarce, as we have seen.

Even today, at a time of peace, it is unlikely that a substantial part of the urban population - and firms, in particular - will move back to rural areas, as they wish to enjoy the benefits of proximity to other productive units, labour market. and commercial opportunity, especially until transportation difficulties, identified as a major constraint for finns located outside Luanda, are overcome. This will create further pressure on the land market (both formal and informal), prices will continue to rise, and conflict over occupation rights is likely to increase. Therefore, the land occupation regularisation process must be a priority.

5 MANUFACTURING AND FIRM'S PRODUCTMTY

Before establishing the effects of investment climate constraints on firm's productivity it is important to grasp Angola's position both internationally, by comparing with relevant countries, and nationally, by investigating differences across a number of firm's characteristics. For the international comparisons we use median values for Sub Saharan countries where Investment Climate surveys have been camed out recently. The aggregate values by income levels and resource abundance exclude South M c a , because not all variables for comparison are readily available. Nevertheless we also report the closest results for South M c a separately so we have a fuller picture for comparison in the region.

5.1 Labor Productivity and Labor Cost

Labor productivity is measured as value added per em loyee. From Figure 5.1, we can see that 3 r Angolan firms perform better than other resource rich countries in sub-Saharan Africa, but are

still well below other lower middle income countries in the region, particularly Namibia and South Afiica. As it is recognized, productivity in South ~ f r i c a ~ ' is considerably higher than in the rest of Sub-Saharan Afiica. Labor productivity in Angola, however, compares favourably with countries such as Tanzania, Rwanda, and the Democratic Republic of Congo.

Figure 5.1: Labor Productivity - International Comparison

1 Value Added per Worker Labor productivity in the Angolan manufacturing sector is higher in foreign owned firms (see Table 5 . 1 ) ~ ~ . We can also see that firms established in Luanda are more productive than those in the other sampled cities (Benguela and Huambo) .

30 The set of resource rich counmes includes Angola, BOB- DRC, Namibia and Uganda The lower middle income group contains Angola,

Namibia and Swaziland

3 1 See South A6ica: an Assessmt of the Investmat Climate (2006). World Bank

32 Median value.

Table 5.1 Labor Productivity (US Dollars) - Manufacturing

Next we turn to investigating the labor costs. We measure them as the total costs of workforce divided by the total number of employees (including both full time and temporary workers). Figure 5.2 shows that labor costs in Angola are high in the region, being only below South Africa and Namibia.

Figure 5.2: Labor Cost per Employee - International Comparison

Labor Cost per Worker

Firms in Luanda

Source: ICA Survey Note: The fmt row in the table refm to the mean and the second value to the median.

Location

Luanda Other

9045 5046 5627 4470

Value added per worker

2o05

Industry

Manuf. - Food and - - beverages

Garments Other

5780 5169 10336 4894 5144 5557

F i n size

Small Med. Large

8652 6584 8393 5355 5148 8168

TOTAL

8339 5436

1 I Table 5.2 the labor

in Angolan manufacturing firms does not vary considerably across the different dimensions used in this analysis.

Ownership

Foreign Dom.

9502 8232 7224 5144

I a @ ~ " 9 *a 9. (pa +QO +* . * * '@ & P a* @ GQ $ p 8 . 4 5 * c p p P I * a P 5 + * 1 * p @ 8 6 B @ P G o @ @+eq. 4 @ # \6 & *+ d V \+ * nV

1 4d6$.+ ** %s* & + . 5 B0 &&* %O*

9 eC 5*9 4 I 8' I G

3 3 Median value

face the highest labor costs of the regions sampled, but as we can see in

Table 5.2 Labor Costs per Employee (US Dollars) - Manufacturing

Note: The first row in the table refen to the mean and the second value to the median.

2005

A better way to understand the weight of labor costs in firms' operations is to study their unit labor costs, that is, look at total cost of manpower as a

Figure 5 3 Unit Labor Costs - International Comparison proportion of value added.

Unit Labor cost This indicator is quite useful for international com~arisons as it does not

above those reported in the DRC, but well below many other countries

Source: ICA Survey

TOTAL

3377 2740

Figure 5.4: Capital per Employee - International Comparison

depend on national currency units and is, therefore, not subject to exchange rate movements. It is clear from Figure 5.3 that Angolan firms face the highest labor costs in the region. This is expected in countries that rely heavily on labor intensive production methods. As a matter of fact the levels of capital intensity in Angola are

in the region (Figure 5.4).

F i n size

Small Med. Large

3470 2806 3720 2747 2687 2740

I Capital per Worker . .

Ownership

Foreign Dom.

4267 3296 2687 2751

Location

Luanda Other

3553 2561 2762 2627

Industry

Manuf. - Food andManUf' - beverages Garments Other

2928 3018 3701 2653 2922 2751

5.2 Total Factor Productivity and Investment Climate Determinants

We now look at total factor productivity, which is the productivity of h s after both capital and labor have been taken into account. Figure 5.5 shows total factor productivity (TFP) across countries as a proportion of TFP in South Africa. Angolan firms' perform rather well in terms of TFP. They perform at 40% of the productivity of South African f m s . Angola appears in a better position than most Sub Saharan African countries. Figure 5.5: Total Factor Productivity - International Comparison

Using the methodology o,: --

described in Annex A we 0.8

estimate a Cobb-Douglas 0.7 0.6

production function for 0,5

Angolan manufacturing firms. 0.4 0.3 We proxy capital by the ,,

product of average capacity 0.1

utilization and the book value O

of machinery and equipment, and measure labor by the total number of employees in the establishment. Results are reported in Table 5.3.

We find that capital elasticity is almost four times lower than labor elasticity. We tested for constant returns to scale in production and we cannot reject the hypothesis that the sum of those elasticities of inputs is equal to one. Therefore, there is strong evidence of constant returns to scale in production in the sampled firms. This means that the size of firms is not immediately a predictor of productivity. We see also see that if a firm is new (less than 5 years in operation) it has higher

Table 5.3 Production Function Estimates value added. Firms in the food and beverages sector generate

Firms in Luanda are more productive than firms located in the rest of the country. Foreign owned firms are more productive. These results corroborate the initial findings of labor productivity. (Table 5.4) The only counterintuitive result relates to the influence of firm size, as we find that medium sized firms have the highest average TFP. However, this could be due to the fact that

I Coef. SE P-value Labor 1 0.778 ("') 0.073 0.000

-

the number of large firms in the sample is very low.

lower value added.

(***) Statistically different 6orn 0 at a 1% significance level Source: ICA Survey

Capital Age of Firm Manager's Education Manager's Experience Food Garments Constant Observations R squared Test CRS: F stat

Prob>F

0.193(^**) 0.022 0.000 0.234 (***) 0.089 0.008

-0.1 36 0.099 0.167 0.070 0.086 0.413

-0.258 ("') 0.085 0.003 -0.145 0.132 0.272

10.0071 (***) 0.392 0.000 159

0.486 0.16

0.685

Table 5.4 Total Factor Pmductivity - -

source: IU\ survey

Average Median

We established in section 2 that fims perceive electricity, access to finance, corruption, business licensing, and transportation as serious constraints affecting Angolan h s . We now attempt to

Table 5 5 Extended Production Function Estimates

TOTAL

1.321

- - 0.941

F i n size

Small Medium Large

1.322 1.404 0.876

Labor

0.942 1.300 0.840

Capital Access to Finance Finance PV Electricitv

Business Licenses Constrction Permit I 0.227 0.216 0.295 / 0.266 0.216 0.221 I

Ownership

Faeign Domestitic

1.417 1.312

Model 1 Coef. SE P-value

0.846("') 0.123 0.000

Power 0;tagee PV

1.300 0.917

Model 2 Coef. SE P-value

0.825("') 0.123 0.000 0 .196y) 0.024 0.000

-0.143 0.228 0.529 -0.037r) 0.018 0.040

- , PV 1 - 0 . 0 6 6 ~ ) 0.024 0.006 ( - 0 . 0 7 4 ~ ) 0.024 0.002 Crime. Then and Disorder I I

Location

Luanda Other

1.438 0.940

0.192('") 0.024 0.000

-0.158 0.228 0.489 -0.032(.) 0.018 0.078

-0.081("') 0.022 0.000 -0.012 0.016 0.438

Operation License PV Corruption Informal Payments Pavments to Officials

Crime 0.280(") 0.127 0.028 PV -0.028 0.024 0.245

industry

Manuf. - Food and -Manuf' - Garments Other

1.185 1.145 1.440 1.077 0.859

-0.192("') 0.053 0.000 4.005 0.016 0.758

Transportation B ma kage 0.010 0.019 0.616

-0.002 0.021 0.939

0.958 1.045 0.921

-0.687("*) 0.264 0.010 -0.027 0.024 0.256

0.017 0.012 0.157 -0.001 0.010 0.915

Generator r

-0.633(") 0.263 0.017 -0.010 0.023 0.655

0.008 0.012 0.497 0.000 0.010 0.991

Garments Age of Firm Foreign Ownership Medium Size Large Size Luanda

I R squared 0.590 1 0.589 1 (***) Statistically different from 0 at a 1% significance level (**) Statistically different from 0 at a 5% significance level (*) Statistically different from 0 at a 10% significance level Source: ICA Survey

Constant 110.324(***) 0.498 0.000 110.695("') 0.519 0.000

34 These measures are expkined in detail below and in Anm A.

Observations

quantifj~ the &pact of each of these

159 1 159

investment climate factors on measures of productivity. We estimate an extended production hnction

specification including both objective measures34 of each constraint and the fims perception of such constraints (denoted pv3'). Two models are estimated: in model 1 we test the

statistical significance of objective measures of each constraint as well as firms' perceptions; in model 2, we use the average of the objective measure of the constraint by location and sector of the h s to address

endogeneity concerns. Table 5.5

35 PV is an indicator based on the mking of the peneption of the three most serious obstacles. For each finR the most serious oktacle was given a

weight of 3, the second most serious a wight of 2 and the third most seriow a weight of 1.

reports the results.

Access to finance is measured by a dummy variable that takes the value of one if the firm has an overdraft or bank loan. Here and for the remainder of this section, PV represents the correspondent perception of the firm as this being a major or very severe obstacle to business. We see that only the perception variable has a negative impact on productivity. However, it is important to remember at this point that the penetration of access to bank finance is very low in the sampled h s . Overall less than 3% of h s have access to any form of bank finance making it very difficult to find any strong effects. Firms that perceive access to finance as a major constraint are 4% less productive.

Problems with electricity are measured by the natural logarithm of hours of power outages per month. There is a strong negative impact of these problems on productivity. We can see that these a decrease of 1 % in the number of hours of production lost due to power outages leads to an 8% increase in TFP. It is apparent that even the high usage of private generators does not mitigate the losses in productivity caused by a deficient electricity supply network

Business licenses and permits were also identified as a serious constraint by firms. To measure this, we include binary variables that assume the value of one if it takes over 28 days to obtain a construction pennit and an operational license. We find that the delay in obtaining operational license has a significant and negative effect on total factor productivity: h s which have to wait a long time (more than 28 days) to obtain an operational license show a level of productivity which is more than half of the firms that do not wait that long to obtain the licence.

Corruption problems are approximated by percentage of total sales spent in informal payments to get things done and by percentage of sales paid to officials to secure government contracts. The effects of such variables are weak This may reflect the fact that the proxies used do not hlly capture the corruption problem faced by h s . However the perception of corruption as a problem is significantly correlated with TFP in both models labor productivity. Firms that consider corruption as a major problem are 7% less productive.

Finally problems with transportation are proxied by proportion of value of shipments lost due to breakage or theft while in transit. As with corruption, it is the perception variable that has a consistent negative impact on productivity. Firms complaining about transportation are approximately 10% less productive.

The productivity analysis provided above shows that reforms on improving the access to credit, securing a reliable supply of electricity, accelerating the business licensing process, increasing transparency, and improving transport links will have positive effects on firm productivity in Angola.

6 SYNTHESIS OF RESULTS AND POLICY RECOMMENDATIONS

6.1 Constraints to Business

Indirect costs in Angola are relatively high: approximately 10% of total sales in the manufacturing sector and 8% for all sectors. Micro firms face slightly higher indirect costs, totalling 12% of sales. In the formal sector, electricity is the main driver of such costs.

Firms in the formal sector have identified the following constraints to business: access to credit, electricity, crime, corruption, and business licensing. Transportation is an important constraint for h s located outside Luanda. Micro firms have identified broadly the same constraints to business (with different orders of importance), with one exception: access to land appears in their top five concerns. In comparison with other countries, h s in Angola and the DRC have broadly similar main concerns (electricity and access to finance), but in the latter, macroeconomic constraints are very important whilst in Angola they are not.

In terms of infrastructure, electricity-related problems are mostly due to power outage duration and frequency. Generators, a costly alternative, become thus necessary for firms to operate, and provide some 3 1 % of total electricity needs. In comparison with the DRC, Algeria, South Africa, Namibia and comparator country groups, such outages are more pronounced in Angola.

Business licensing in Angola is a time consuming process: a consfmction permit takes some 42 days and an operating license 24 days. This is both worrying in absolute and relative terms, as firms in the DRC, Algeria, South Africa and Namibia have generally speedier and less costly business licensing processes.

Conuption is also a serious constraint, with firms' perceptions being that government officials do not have a consistent interpretation of the law, Overall, firms make informal payments worth some 3.3% of total yearly sales.

6.2 Financial Market

Despite strong growth of credit to the private sector in the past three years, the depth of the Angolan financial sector is still very shallow with 11.1% MUGDP (compared to an average 27% in low-income countries). Access to finance as a constraint is mirrored by very low financial sector intermediation with private sector credit accounting for only 8% of GDP in 2006 (compared to an average of 23% in low-income countries).

Angolan firms rely essentially on internal funds to finance themselves, with borrowing (e.g. fiom banks) accounting for only 5% of total long term financing needs. Regarding working capital needs, borrowing is even less common. In comparison with other countries, the role of the banking sector as a source of finance is less pronounced in Angola. This constraint is confirmed by the fact that a very small percentage (less than 4%) of firms has overdraft facilities, lines of credit or loans from banks, clearly lower than in DRC, Algeria, South Africa, Namibia and compamtor country- groups.

Lack of access to finance coincides with high liquidity in the banking sector and the banking system as a whole fails to intermediate growing deposits into credit. Net credit as share of deposits

declined to 38% in 2005. The Angolan financial sector remains highly dollarized with 44% of total banking sector credit and 52% of deposits denominated in foreign currency.

Based on sound macroeconomic policies interest rates have been declining significantly (along with inflation) and cost of debt does not appear to be a critical factor limiting firm's access to finance. On the contrary, high access thresholds as documented by complex credit application procedures and high collateral requirements are stated to be the main reasons limiting access to finance by firms.

6.3 Productivity

Firms in Luanda have higher levels of labor productivity than in the rest of the sampled cities even though they face higher labor costs. Labor costs average 54% of value added revealing the prevalence of a labor intensive manufacturing sector. Angolan firms use low levels of capital per employee. To complete the picture about productivity in the surveyed firms, estimates of Total Factor Productivity reveal that foreign owned firms are the most productive.

Investment climate constraints identified as the most serious by the interviewed establishments tend to have a negative impact on productivity, The food and beverages, and garment sectors are less productive than the reference one (other manufacturing firms). Moreover, foreign owned firms and the ones located in Luanda are more productive than domestic firms and those located outside of Luanda respectively.

The evidence on the effects of business climate constraints on productivity shows that reforms on improving the access to finance, improving electricity inliastructure, speeding up the business licensing process, on increasing transparency and improving transport links will have positive effects on productivity.

6.4 Policy Recommendations

6.4.1 Finance

A lot of progress has been made in improving Angola's payments systems over the last few years. Nevertheless increasing financial depths will require improving the lending environment and encouraging banks and non-banks to expand financing to the private sector. Rather than providing credit banks in Angola prefer to charge fees fiom transactions, to provide short-term trade financing and to invest in high-yield government bonds. Consequently, the development of Angola's private sector is constrained by Angola's financial environment. - Improving the lending environment will be crucial to encourage credit expansion and at the same time avoid undue accumulation of risk in the financial system. Financial institutions in Angola are reluctant to expand credit given their limited ability to identify borrowers with good credit risk (lack of accounting frameworks, market information and credit information) and the ability to enforce contracts and secure collateral (inefficient creditor rights and enforcement, lack of secured lending frameworks and collateral registries). In addition, sustainable financial sector development will require strengthening of bank and corporate governance frameworks and a robust risk-based supervisory framework.

While low financial sector development and lack of access to finance impedes growth in general, low financial sector intermediation capacity poses a particular problem in Angola given the rapid growth of oil revenues in the country. Enhancing the capacity of the financial sector to intermediate funds into productive investment will be crucial for creating absorptive capacity and managing the risk of Dutch Disease'. Financial sector development could be a driver on non-oil growth in the private sector. However, credit expansion and investments require 'bankable' projects and financial sector reform should not be seen separate fiom general investment climate reform.

The Angolan Governrnent has provided a hmework for future financial sector reform with the passing of the New Law on Financial Institutions and the Securities and Exchange Law in 2005. The authorities have identified a broad range of policy areas to address current constraints to access to finance, including:

o Human Resource Capacity and skiis Development in the financial sector o Business Registration and identification systems o Credit Registries and Collateral Registries o Creditor Rights and Enforcement o Long-Term finance, including real estate and mortgage finance o Deposit Insurance Systems o Microfinance o Diagnostic Work on interest rate spreads and Monetary Policy implications

A concerted effort by the various Government agencies and development partners to implement reform in the identified priority areas will key to address constraints to access to finance.

The BNA initiative on expanding access to credit contains a significant number of relevant policy actions targeted in particular at constraints in the lending environment and financial sector capacity.

Short - tern recommendations:

1. Enhance credit information inhstructure. The existing public credit registry has very limited coverage and primarily serves supervision puposes. The recent WB/FIRST/IFC review of credit information infrastructure in Angola has found a broad consensus among banks and regulatory authorities for expanding its functionality under the supervision of the BNA and upgrading the system based on existing international best practice applications. In the short-run, an efficient solution could be to outsource operation, but not ownership, of the registry to an experienced international credit bureau operator on behalf of the BNA. Later, with a growing credit market, the entry of private credit bureau operators (potentially on shared platforms within SADC) should be enabled and encouraged.

2. Upgrade coporate registries, collateral registries and public record systems. ?he scope of financial information &structure should include efficient access to corporate information, registries of secured lending charges and court records etc.

3. Computerize property registration process, simplify taxes and fees, and make optional the involvement of notaries so as to improve property registration. Efficient land registries and

the ability to easily perfect and transfer land titles are an important vehicle to provide property owners with access to collateralized financing. On average property registration in Angola requires 369 days compared to the regional average of 1 14 days. The lengthmess of Angola's property registration process, i.e. more than three times the regional average, is principally a result of the 300 days required to receive definitive registration h m the Real Estate Registry. Backlog and paper-based records necessitate that all history of transactions relevant to the property must be checked every time.

4. Clarify the property rights in the new land law in order to reduce codhion and help identify sources of collateral.

5. Review standards and codes on creditor rights and insolvency regimes, including the enforcement of property rights and the efficiency of commercial court procedures and the establishment of alternative dispute resolution mechanisms.

Long -term recommendations:

1. Conduct the planned FSAP. The Financial Sector Assessment Program (FSAP) will provide an appropriate framework for more detailed diagnostics on financial sector constraints with a view to enhance access to finance and increase financial sector intermediation capacity. The FSAP should also provide guidance on addressing issues arising from the linkages between financial sector capacity and the degrees of fixedom of monetary policy.

2. Conduct a detailed household survey on access to finance to identify constraints for households and micro-enterprises in low-income segments of the population.

3. Notwithstanding the objectives to establish a national ID system and expanding the use of corporate tax IDS, introduce a financial ID system based on biometric. Various experiments based on biometric financial IDS in the region, in particular Uganda, have shown some promise in establishing the basis for credit information and know-your- customer procedures in an environment with high degrees of informality and incomplete public records infr-astructure.

4. Strengthen the accounting framework, enhance disclosure requirements and build capacity of the accounting and auditing profession. Good accounting information and reliable audits are the basis for sound bank risk assessments and the expansion of cash-flow based lending technology. In addition to the planned training and certification program for accountants and auditors, a review of accounting and auditing standards could ensure that international best practice are recognized.

5. Foster asset based lending practices. Review secured lending and leasing frameworks - including the supporting infrastructure like movable collateral registries - and implementation of international best practice in order to promote diversification of bank lending technologies and emergence of non-bank financial providers especially in support of SMEs and rural non-farm private sector development.

6. Promote the application of innovative products and technology to expand access to finance. Capacity building for banks and microfinance institutions in the use of different lending technologies secured lending, leasing, mortgage finance and in the longer run the promotion of new products such as warehouse receipts or weather insurance are likely to have high impact on financial depths.

6.4.2 Infrastructure

Electricity

The Angolan Government's objective of providing sustainable and reliable electricity supply is documented in the "Development Strategy of Angola's Private Sector" approved in September 2002. The strategy aims to increase access to electricity from 20% in 2001 to 36% by 201 1, and to increase electricity generation by 7.4% per annum between 2006 and 201 1. In addition, the government is committed to the reduction of regional asymmetries in access to electricity. This commitment is congruent with our survey results where 79% of firms outside of Luanda deemed electricity as a constraint compared to 59% of the firms in Luanda (See Table 2.2).

In the long-term the government intends on creating a national electricity transmission system that connects all regions to one integrated grid. In addition, a national fund for the electricity sector to widen access was foreseen in the 1996 electricity law. A range of measures including levies on electricity or petroleum products, state budget, and grants or loans h m international institutions were seen as financing sources for the fund. In October 2002, proposals for activating the fund were submitted to the government. The hnd exists only in concept. Levies on electricity or petroleum products need National Assembly's approval. There is recognition, however, that even when the National Fund is operating it would be wholly inadequate to finance needed investments in the sector, and, therefore, private financing will be required.

The lack of financial stability of ED EL^^ and E N E ~ ~ and the considerable accumulated debts among parastatals and between these companies are problematic. Combining losses and non- collection suggests that only 45% of the electricity that EDEL receives from ENE is paid for with the other 55% stolen, lost as heat in the transmission or distribution lines, or sold but not paid for. In addition, the tariff structures are not reflective of costs with costs being historically set below long-run marginal costs.38 Technical and non-technical losses totaling 36% in the EDEL system are very high.-Many of the non-technical losses are due to inefficient billing and settlement systems, illegal connections, and the lack of proper metering systems. These financial problems have resulted in EDEL and E m ' s reliance on direct government subsidies, which are restricted to distribution activities. As a result, the expansion of electricity supply has been limited.

Short-term Recommendations:

1. Unbundle the financial structure of ENE into generation, transmission, and distribution activities and introduce cost-reflective tariffs, which would necessitate a gradual increasing of tariffs.

36 EDEL is the disbibutive company responsible for the elecbicity supply in Luanda province.

37 ENE is mpomible for electricity genedon, mrnission, and disbibution in the main citics of the 15 provinces outside of Luanda. k is nsponsible

for Angola's e ldc i ty genedon.

38 See World Bank Report "F'rivate Solutions for InkMmchm in Angola" page 43. Authors indicate that long-nm marginal cost is said to be

US$O.l IkWh. They are however unable to idRltifY the basis for this calculation.

2. Improve the monitoring and regulation to ensure more efficient billing and settlement systems, reduction of illegal connections, and proper metering systems.

3. Amend the legal and institutional framework to allow private operators to play an important role in restoring and expanding supply to consumers in the small or not-so-small isolated networks.

4. Review options for private sector participation in management contracts. With respect to ENE and EDEL activities good rewards to strong private management can be obtained by outsourcing metering and resource collection services. This approach could be applied to a range of services including construction, maintenance, and manufacture or treatment of electricity poles.

5. Review options for private sector participation in investment. This can be done through the build own operate (BOO), build operate transfer (BOT) contracts for power plants, or a number of variants of BOO and BOT.

Long-term Recommendations:

1. ENE should prepare, publish and regularly update an electrification plan. Private operator should be contracted to provide support services to private and municipal rural electricity operators. A simpler system for licensing of off-grid or small-scale electricity schemes should be introduced.

2. Achieve physical and managerial separation of generation, transmission, and distribution. This will help facilitate the future objective of creating separate and autonomous enterprises for each business fimction.

3. Ensure full operability and independence of regulator. The regulator should be responsible in the setting of electricity prices. This is important in reassuring the private sector that prices will be allowed to cover reasonable costs and earn a reasonable rate of return.

4. Move away from uniform tariffs, which imply that a consumer connected to the ENE grid in isolated areas, pays prices that are a fraction of the production cost in those areas, while those without an ENE connection must pay very high prices for electricity produced from small diesel generating sets. A policy of nonuniform tariffs would allow private developers and ENE to operate supply systems in rural areas with much reduced or no dependence on the state for operating subsidies.

5. Implement private sector participation in management contracts and investments (through BOO, BOT or variants of the &o).

6.4.3 Regulatory Environment

The government of Angola has recently been engaging in a number of legislative and administrative initiatives in an attempt to address obstacles to the establishment and operation of new businesses in Angola. In August 2003, the Guiche Unico de Empresas (GUE), a public service agency comprising delegations of all services or government bodies involved in authorizing business start-ups was set up. In April 2004, a new Company Law took effect that consolidated rules related to incorporation of commercial companies in Angola, which was previously spread out amongst several laws. Although too early to see the full impact of such measures, Angola has already slightly improved in its ranking in the Doing Business Indicators. There is, however, a need to fUrther increase the efficacy of the GUE, and reduce the related costs.

Short-term Recommendations:

1. Increase effectiveness of the GUE by reducing the cost to start-up a business. 2. Reduce costs to execute the notary deed of incorporation, provisional registration with

registry of companies, and obtainment of the Commercial Operations Permit. 3. Reduce time required to obtain the Commercial Operations Permit and the two-step

registration with the Registry of Companies from the current 40 and 30 days respectively.

Closing a business in Angola is a costly and timely endeavor. The time required to go through insolvency in Angola is approximately 6 years, compared to the Sub-Saharan Afiica average of 3 years. In addition, the recovery rate is 11 cents per dollar, compared to the Sub-Sahara Afiican average of 17 cents per dollar. These obstacles to closing unviable businesses result in the continuation of these loss-making businesses and the subsequent inability to reallocate assets and human capital to more productive uses.

In spite of the fact that Angola has bankruptcy laws, they are almost never used. In developing countries, however, it is often the case that debts are settled outside of the legal insolvency procedures. This is one reason why the recently enacted Voluntary Arbitration Law (VAL), which provides a legal M e w o r k for the resolution of non-judicial disputes, is important. It is, however, necessary to build up the legislative and administrative regulatory capacities for foreclosures over the long-term.

Short-term Recommendations:

4. Build up the administrative capacity for the recently enacted Voluntary Arbitration Law through the recruitment and training of arbitrators and staff.

5. Encourage the involvement of creditors in the foreclosure process.

Long-term Recommendations:

1. Enact the necessary laws and build up administrative capacities for foreclosures through the recruitment and training ofjudges and staff.

Contract enforcement in Angola necessitates 46 procedures compared with the Sub-Sahara African regional average of 40. In addition, the time to enforce a contract is 1,011 days compared with the regional average of @I3 days. To reach a judgment it takes 1 year and 4 months (485 days) on average, and to enforce that judgment it takes almost the same amount of time (440 days).The high number of procedures and time required for a contract's enforcement underscore incapacities and inefficiencies inherent in the legal and judicial system.

The Voluntary Arbitration Law is useful in providing an alternate mechanism to the court system as a form of dispute settlement. In addition, the establishments of information systems for caseload and judicial statistics will help reduce judgment periods. The US Department of Commerce's Commercial Law Development Program, for example, improved criminal case management in Angola's Luanda Province by instituting a computerized case tracking system. In addition, there is a need for the further simplification of the procedures in commercial disputes. A modification of the structure of the judiciary to allow for small claims and specialized commercial courts is

necessary. Finally, the simplification and clarification of laws and regulations would result in the freeing up of court-resources for more relevant "dispute settlement" activities.

Short-term Recommendations:

6. Establish information systems for caseload and judicial statistics. 7. Further simplify the procedures in commercial disputes. 8. Simplify and clarify laws and regulations

Licensing a warehouse in Angola requires 14 procedures, takes 337 days, and costs 1 1 10% of per- capita income. The Sub-Sahara African average requires 18 procedures, takes 262 days, and costs 2550% of per-capita income. The request for the license from the Provincial Governor takes 180 days to complete and the registration of the building with the real estate registry takes 90 days. As a result, efforts to hasten the response time of Angola's government bureaucracy and computerization of registry process ought to enable a faster tumaround time. In terms of costs, obtaining power connections and the hiring of the inspection firm comprise 63% and 36% respectively of total "warehouse" licensing costs. Consequently, improvements in electricity infrastructures ought to help diminish the costs of licensing a warehouse.

Short-term Recommendations:

9. Shorten the time to obtain a license from the Provincial Governor 10. Shorten the time to obtain a license from the real estate registry 1 1. Reduce the costs of inspection by increasing competition and reduce the fees for electrical

connections. 12. Computerize registry process

6.4.4 Corruption

Angola remains one of the countries in the world were corruption is most pervasive. Angola ranks 147 out of 169 countries in the Transparency International's Corruption Perception Index. Objective data from the ICA shows that firms in Angola have to pay close to 4% of the contract value in bribes in order to obtain government contracts. Corruption is most problematic for large firms and h s in Luanda. Tackling corruption is not an easy or a short process. It requires political will, popular support, and necessary resources.

Short-term Recommendations:

1. Clearly and unequivocally declare political will to fight corruption at the very top level. 2. Allocate necessary resources to the fight: assign 0.5% of national budget permanently to

this fight

Long-term Recommendations:

1. Establish an Anti Corruption Agency. Recruit investigators and staff and define a clear mandate.

2. Develop an anti corruption campaign to build popular support.

Foster isset based lendmg prrtdlcg and review l&g and k m g 6ameworks

vate pamcrpatlon In

environment for Reduce IX& to execute the notary deed of business -4 m m p w o n , ~ O V I S I ~ l e m o n Hlth

regdry of cornparues and obtamment of the Commercial Operat~cms Penn~t Reduce tune required to obtm the Conunernal wens P m t and the twostep regisbahon

High cost to close a business Burdensome time and number of prwdures.

High costs of licensing Lengthy time quired

Lengthy time quired to reach judgment and enforce a contract.

High costs on doing business.

Recently enacted Volunkary Arbitration Law (VAL)

Improved criminal case - p e n t in Angola's Luanda Rovince instiaaed Voluntaq Arbitration Law usell in providing an alternate mechanism to the court system as a foml of dispute settlement

Some improvements in regulatory quality noted, however, conuption is still asignificant pmblem in Angola.

with the Registry of Companies. . Build up the administrative capacity for the VOIW& Arbitration Law through th recruitment and training of arbibatm and staff. Encourage the involvement of creditors in the

Shorten the time to attain a l i h m the Rovincial Govmor Shortenthethetoobtainalicense h m t h e real estate regisby Compderize registry pmcess Reduce costs of inspection by i n m i n g competition and mime fees for electrical connections

Establish information s y s m for caseload and judicial statistics. Further simplify the procedures in commercial disputes. SiilifLand clarify laws and qditions

Clearly and unequivocally declare political will to fight comqtion at the very top level Allocate necessary resources to the fight assign 0.5% of national budget permanently to this fight

I Enaa the necessary laws and build up adminktdve capacities for foreclosures through the mmibnent and bain'ig of judges and s M .

Establish an Anti Comption Agency. Recruit investigators and staff and define a clear mandate. Develop an anti cormption campaign to build popular suppon

ANNEX A: TECHNICAL APPENDIX FOR PRODUCTIVITY CALCULATIONS

We follow the methods proposed by Escribano and Guasch (2005)~~' Productivity is estimated by fitting the following Cobb-Douglas production function:

where VAi is value added for fum i; Li is the total cost of labor; Ki is the capital stock; 'i is a vector of firm-level control variables and includes a dummy variable for the age of the firm (1 if less than 5 years old; 0 otherwise), a dummy variable that assumes the value of one if the manager has some higher education, and a dummy that assumes the unit value if the manager has more than 5 years of experience; F and G are industry dummies for food and garments sectors.

Total Factor Productivity (TFP) is constructed as the estimate of ',, the part of value added not explained by labor or capital, after controlling for industry's fixed effects and addressing endogeneiy concerns by the inclusion of averages by location and sector instead of the firm responses4 .

The impact of the investment climate variables identified in our earlier analysis on TFP can be estimated through the following equation using weighted ordinary least squares4' :

Where TFf: is the total factor productivity (in log) for firm i; ICi is a vector of the investment

climate variables; FCi is a vector of h - l e v e l characteristics such as size, export orientation, location and ownership status, and the ownahip of a generator. As an alternative to this two step procedure, we also estimated extended Cobb-Douglas production functions proposed by Escribano and Guasch, using investment climate constraint perceptions to control for endogeneity of inputs:

39 E s c n h o and Guasch (2005), Assessing the J n p c t of the lnvesbnent Climate on Productivity Using Firm-Level Data: Methodology and

the Cases of Guatemala, Honduras, and Nicsuagua, World Bank Policy Research Working Paper 3621.

40 Due to the homogeneity in the sample it is only p s i b l e to include one of these avenge variables at a tim. The choice of miable to include

was detemdned by highest improvement in the gocdness of fit

41 Unweighted regressions with robust stmdard errors were also computed with results that are qualitatively identical to the ones reported here.

Where IC,. includes investment climate perceptions reported by the firms, whch are considered not to determine the use of inputs. The variables used have already been described in the main text. Below we report the full results of the effects of investment climate constraints on TFP and labor productivity. As already mentioned the location of the firm in the capital has a significant positive effect on productivity. There is some weaker evidence that older firms are more productive.

Table A1 Effects of Access to Finance

Finance*

TFP Model 1 TFP Model 2 Coef. SE P-value Coef. SE P-value

PV I -0.011 0.016 0.5141 -0.011 0.016 0.498 Food I 0.002 0.086 0.9801 -0.024 0.133 0.859 Garments Age of Firm Foreign Ownership Medium Size Large Size Luanda Constant 1 -0.182 0.106 0.0871 -0.167 0.119 0.161 R squared I 0.0471 0.047 Source: ICA Survey

Table A2 Effects of Electricity

Labor Productivi -1

Garments Age of Firm Foreign Ownership Medium Size Large Size Luanda

Electricity

TFP Model 1 Coef. SE P-value

Constant 1 -0.069 0.127 0.5901 0.430 0.186 0.0211 8.493 0.143 0.000~ R squared

TFP Model 2 Coef. SE P-value

0.0761 0.1031 0.092

Labor Productivity Coef. SE P-value

Source: ICA Survey

Table A3 Effects of Business Licenses

PV Food

Business Licenses Constrction Permit$ Operation License

Garments Age of Firm Foreign Ownership Medium Size Large Size Luanda Constant ( -0.278 0.096 0.004( -0.393 0.112 0.001 ( 8.405 0.108 0.000 R squared 0.071 1 0.0781 0.087 Source: ICA Survey

TFP Model 1 Coef . SE P-value

0.240 0.211 0.257 -0.561 0.266 0.035

Table A4 Effects of Crime

TFP Model 2 Coef. SE P-value

-8.119 4.089 0.048 -0.517 0.262 0.050

Labor Productivity Coef. SE P-value

0.126 0.238 0.597 -0.702 0.299 0.019

Crime, Theft and Disorder Security3 Crime PV Food Garments Age of Firm Foreign Ownership Medium Size Large Size Luanda

Table A5 Effects of Corruption

Constant 1 -0.203 0.091 0.0261 -0.293 0.093 0.0021 8.489 0.102 0.000

TFP Model 1 - TFP Model 2 I Labor Productivity I Coef. SE P-value 1 Coef. SE P-value I Coef. SE P-value

TFP Model 1 Coef. SE P-value

0.1 18 0.083 0.157 0.334 0.120 0.006

-0.038 0.019 0.048 -0.082 0.088 0.353 0.006 0.125 0.963

-0.200 0.093 0.032 0.173 0.145 0.235 0.057 0.131 0.665

-0.393 0.241 0.104 0.372 0.113 0.001

R squared 0.0861 0.1lOl 0.095

PV ( -0.053 0.019 0.005) -0.051 0.019 0.007) -0.077 0.021 0.000 Food 1 -0.028 0.087 0.7501 0.040 0.094 0.6731 -0.265 0.096 0.006

TFP Model 2 Coef. SE P-value

2.159 0.653 0.001 0.338 0.117 0.004

-0.035 0.019 0.064 -0.766 0.232 0.001 0.000 0.123 0.999

-0.221 0.092 0.016 0.141 0.143 0.326 0.058 0.127 0.650

-0.370 0.237 0.120 -0.243 0.223 0.277

Source: ICA Survey

Corruption Informal Payments Pavments to Officials3

Labor Productivity Coef. SE P-value

0.093 0.093 0.323 0.215 0.135 0.114

-0.064 0.021 0.003 -0.289 0.100 0.004 -0.245 0.141 0.083 0.034 0.105 0.747 0.266 0.164 0.106 0.052 0.148 0.724

-0.442 0.272 0.105 0.311 0.128 0.015

Source: ICA Survey

0.008 0.012 0.521 0.002 0.009 0.851

Garments Age of Firm Foreign Ownership Medium Size Large Size Luanda Constant R squared

0.009 0.008 0.238 -0.271 0.154 0.079

0.041 0.127 0.744 -0.177 0.095 0.062 0.159 0.146 0.276 0.091 0.130 0.483

-0.450 0.258 0.082 0.433 0.113 0.000

-0.198 0.092 0.031 0.067

0.005 0.013 0.688 0.004 0.010 0.731

0.519 0.299 0.083 -0.169 0.093 0.071 0.168 0.145 0.248 0.097 0.129 0.455

-0.441 0.242 0.070 1.835 0.804 0.023

-0.274 0.101 0.007 0.076

-0.194 0.142 0.172 0.067 0.106 0.526 0.228 0.162 0.161 0.085 0.145 0.556

-0.522 0.288 0.071 0.355 0.126 0.005 8.499 0.102 0.000

0.099

Table A6 Effects of Transportation

Breakage ITheft

Transportation

PVS Food Garments Age of Firm Foreign Ownership Medium Size Large Size Luanda

TFP Model 1 Coef. SE P-value

Source: ICA Survey

TFP Model 2 Coef. SE P-value

Constant 1 -0.105 0.097 0.2771 0.711 0.216 0.0011 8.564 0.108 0.000

Labor Productivity Coef. SE P-value

R squared 0.077) 0.1081 0.102