Information about Sub-Saharan Africa África subsahariana
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Appendix 5Business and Economic Environment

Author(s):
Catherine Pattillo, Anne Gulde, Kevin Carey, Smita Wagh, and Jakob Christensen
Published Date:
August 2006
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Information about Sub-Saharan Africa África subsahariana
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This appendix gives further background on the legal and economic environment in which financial sectors in sub-Saharan Africa operate.

  • Poor legal and institutional frameworks create a difficult operating environment for banks. The World Bank’s Doing Business indicators show legal framework and credit information indices that are lower than in comparator countries. The coverage of credit registries is also lower (Table A8).
  • Better legal and institutional environments are associated with a higher share of private credit to GDP in SSA. The indices for the extent of credit information and the legal rights of creditors are strongly correlated with the private loan share (Table A9).
  • Bank lending is also constrained by property rights systems that are weaker than in other regions. Doing Business surveys indicate that the costs of enforcing contracts, collecting debts, and registering property are significantly higher in SSA than in comparator groups (Figure A4).
  • Private enterprises in SSA identify access to credit and the cost of financing as key obstacles to firm growth. For companies included in a World Bank survey, the share of companies in SSA identifying financial sector problems as a serious growth constraint—over half—was much higher than for firms surveyed in the rest of the world (Figure A5).
Table A8.Sub-Saharan Africa and Comparator Groups: Doing Business Legal and Credit Indicators(Values in 2005)
OtherOther
Sub-SaharanLower-IncomeSub-SaharanLow-Income
Africa(excluding SSA)Low-Income(excluding SSA)
Credit-conducive legal rights index4.34.64.44.4
Credit information index1.52.11.41.4
Public credit registry coverage
(percent of adults)0.83.10.80.8
Private credit bureau coverage
(percent of adults)3.76.90.20.2
Source: World Bank, Doing Business 2005 data set.Note:The legal rights index ranges from 0 to 10; higher scores indicate that collateral and bankruptcy laws are better designed to expand access to credit. The credit information index ranges from 0 to 6; higher values indicate that more credit information is available from either a public registry or a private bureau to facilitate lending decisions. Both coverage variables reflect the number of borrowers covered by registry or bureau as a percentage of the adult population.
Source: World Bank, Doing Business 2005 data set.Note:The legal rights index ranges from 0 to 10; higher scores indicate that collateral and bankruptcy laws are better designed to expand access to credit. The credit information index ranges from 0 to 6; higher values indicate that more credit information is available from either a public registry or a private bureau to facilitate lending decisions. Both coverage variables reflect the number of borrowers covered by registry or bureau as a percentage of the adult population.
Table A9.Sub-Saharan Africa: Doing Business Indicators and the Private Loan Share
Sub-Saharan Africa

Regressions
Sub-Saharan Africa

Low-Income Regressions
Dependent variable: private loan share of GDP
Legal rights index0.02(0.18)0.01(0.56)0.01*(0.06)0.02*(0.03)
Credit information index0.03*(0.06)0.01(0.86)0.01(0.80)0.00(0.95)
Interest rate spread-0.01(0.12)-0.01*(0.05)-0.01*(0.04)-0.01*(0.02)
GDP per capita0.11(0.01)0.03(0.26)
R-squared0.260.540.250.29
Sources: World Bank, Doing Business 2005 data set; IMF, International Financial Statistics, and World Economic Outlook.Note: Significance levels are in parentheses. Coefficients significant at l0 percent or better are indicated by *.
Sources: World Bank, Doing Business 2005 data set; IMF, International Financial Statistics, and World Economic Outlook.Note: Significance levels are in parentheses. Coefficients significant at l0 percent or better are indicated by *.

Figure A4.Sub-Saharan Africa and Comparator Groups: Doing Business Costs of Debt and Contract Enforcement and Property Registration

Source: World Bank, Doing Business database, 2006.

  • Banks in SSA have a higher propensity to allocate deposits to claims on the government than banks elsewhere. In addition, they have mobilized deposits at a slower rate than banks in comparator groups. From the second half of the 1990s to 2004, while claims on the government grew faster than claims on the private sector in SSA, the pattern is strongly reversed in other LICs. In addition, reserves and foreign assets account for more of asset growth in low-income SSA than claims on the private sector (Figure A6).

Figure A5.Sub-Saharan Africa: Obstacles to Growth of Private Enterprises

(Percent of companies indicating an obstacle as a serious constraint to growth of business)

Source: World Bank, Investment Climate Surveys, 2005.

  • Financial sector reforms have been incorporated into IMF-supported program conditionalities. On average in SSA, while the number of financial sector conditions per program has not increased as sharply in SSA as in the rest of the world, the share of “harder” types of conditionalities (prior actions and performance criteria) have risen more than in other groups. As in the rest of the world, compliance with financial sector conditionality declined over 1995–2003 (Figures A7, A8, A9).

Figure A6.Sub-Saharan Africa and Comparator Groups: Funding Sources and Uses

(Percentage change from previous four-year period)

Source: IMF, International Finance Statistics.

  • A key feature of the environment for the conduct of monetary policy is a country’s choice of nominal anchor. The movement of most SSA countries outside the CFA zone and the rand Common Monetary Area from an exchange rate anchor to a monetary anchor has been associated with successful stabilization of inflation in most countries (Table A10).

Figure A7.Financial Sector Conditionality Compliance in IMF-Supported Programs in SSA and All Countries, 1995–2003

(Proportion of program measures implemented as scheduled)

Figure A8.Financial Sector Conditionality Hardness in IMF-Supported Programs in SSA and All Countries, 1995–2003

(Share of prior actions and performance criteria in total program measures)

Figure A9.Financial Sector Conditionality Intensity in IMF-Supported Programs in SSA and All Countries, 1995–2003

(Number of conditions per program year)
Table A10.Sub-Saharan Africa: The Choice of Anchor for Inflation
Number of Countries
Description198019851990199520002004
Exchange rate anchorFrench franc/euro [CFA Zone]141414141414
South African rand [CMA]223333
U.S. dollar1544633
Portuguese escudo001000
Spanish peseta100000
Pound sterling110000
SDR1172100
Other currency composites25910323
Monetary anchorDefined monetary aggregate target3000076
Other5710171214
Of which: IMF-supported program4107
Inflation anchorInflation targeting framework000011
As percent of total non-CFA non-CMA countries
U.S. dollar181415221211
Portuguese escudo004000
Spanish peseta400000
Pound sterling440000
SDR39257400
Other currency composites18323711811
Exchange rate anchor837563372022
Monetary aggregate target00002822
Other182537634852
Of which: 1MF-supported program4026
Money-based anchor182537637674
Inflation anchor1nflation targeting framework000044
Source: IMF, Annual Report on Exchange Arrangements and Exchange Restrictions (2004).

Seychelles, Guinea, and Eritrea.

Botswana, Comoros (euro), and Cape Verde (euro).

Includes countries targeting either broad or reserve money.

Programs typically defined in terms of NIR floor and NDA ceiling.

Source: IMF, Annual Report on Exchange Arrangements and Exchange Restrictions (2004).

Seychelles, Guinea, and Eritrea.

Botswana, Comoros (euro), and Cape Verde (euro).

Includes countries targeting either broad or reserve money.

Programs typically defined in terms of NIR floor and NDA ceiling.

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