Policy selectivity forgone: Debt and Donor

behavior in AfricaNancy Birdsall, Stijn Claessens, Ishac

Diwan

Nelly Maell, Marton Bandoli

Africa

Sub-Saharan Africa

OverviewIntroductionDevelopment assistance and debt

accumulation in AfricaData, trends and raw statisticsHypothesis, empirical analysis,

major findingsConclusion

IntroductionAid and development aid business

Two major findings

First Aid is more effective when the recipient

country’s policy and institutional

environment satisfies some minimal criteria.

SecondAid and debt relief

have not been targeted particularly toward

countries with adequate policies and institutions (Burnside

and Dollar 2000)

Research question

Will the official program of debt reduction affect future donor behavior and they will loose their willingness to direct aid to its best uses or it will just invite the another

round of business as usual?

Debt accumulation in AfricaDebt $350 billion dollarsGDP for the region was negative over the last two

decades (- 2% in the 1980s, - 1% in the 1990s)GDP per capita was lower in 2000 than in 196040% of the 600 million people lived less than $1 a

day in 2000 (World Bank 2000)Growing stock of debt – from $60 billion in 1980 to

$230 billion in 2000Growing debt service – from $6 billion a year in

1980s to $11 billion in 1990s

Debt problems in Africa

1 problem

•The total disbursements in the form of new loans and grants have always exceeded countries’ actual debt service.

2 problem

•The proportion of total debt owed to the IMF, World Bank and other multilaterals has been constantly growing as bilateral donors switched from loans to grants and increasingly forgave outright portions of debt owed them.

The rising debt levels and the increase in the share of the multilaterals meant that by the mid 1990s the donors and creditors – not the indebted countries – were caught in a debt trap. (Claessens and others 1997)

Arrears to the multilaterals would have meant the reduction of future lending.

Arrears would make visible the failure of the past aid transfers.

As a result aid flows started to respond more to debt stocks, less to policy and poverty.

Data and analysis of donor behaviorOver 1977-199837 Sub-Saharan countries with

all necessary dataFrom 37 countries – 29 are

HIPC and the 8 Non-HIPCAll data is from World Bank’s

GDF statistics

HIPC – high indebted poor countries

DataNet transfers - amount of net movement of real resources to the country from official sources on account of debt or grants.

NT = G + NB – (P+R) = G + NB – TDS

NT = net transfersG = grantsNB = new debt disbursementsP = principal repayment on existing debtR = interest payment on existing debtTDS = total debt service paid

Analysis of donor and creditor behavior

3 subgroups of indebtedness:Low debt country

Country’s debt to GDP ratio is less than 62,8%High debt country, low multilateral regime

Country’s total debt to GDP ratio is more than 62,8%The share of multilateral debt in total debt is less

than 41,2%High debt, high multilateral regime

Country’s total debt to GDP ratio is more than 63,8%Share of the multilateral debt in total debt is more

than 41.2%

Creditor and donor selectivity: Empirical analysis

High net transfers

High debt

High povert

yGood policy

High lending in the past high debt stock nowdaysIndependent of the quality of domestic policy, poverty

level, institutional capacity to productively absorb flows barrier to selectivity in lending

Creditor and donor selectivity

•Disadvantage•it may be influenced by

incentives to affect the lending behavior of the World Bank

•actual CPIA is available only to the public at the country level in more aggregated form

•Advantage•including not only criteria

releated to public policy effort, but also those related to institutional capacity and governance

Country Policy and

Institutional Assessment

(CPIA)

Burnside and Dollar (2000): based on publicly available datas

The index weights three variables: budget surplus as a share of GDP, rate of inflation, degree of openess of the economy

CPIA < 3 bad policy countries CPIA =>3 good policy countries46% bad policy countries, 54% good policy

countries

CPIA

Differences in net transfers between bad and good policy countries

Other country characteristics1. Degree of indebtednessCharacteristics: colonial ties, strategic interest

of donors, openess of the economy, policy stance

2. Degree of povertyHigh multilateral debt countries are much

poorer than low debt countries; $320 per capita vs. $980 per capita

3. Size of economy

• NTij: Net transfer for country in year is scaled to GDP

• PVTDSGDP: Present Value measure of all future scheduled debt service payments relative to GDP

• GDPCAP: GDP per capita• LNPOP: Population size• CPIA: Country Policy Institutional

Assessment

Regression resultsNet transfers are positively related to debt

stocksHight debt stocks more net transfers

higher debt stocksLarge multilateral debts, donor have allowed

poor policy to continue in these countries and actually provided more resources to accomodate larger macro-imbalances

OLS and Alternative Policy variable

Donors and creditors behaivor

ResultsNet transfers were positive over two decades

in Sub-Saharan countriesMore indebted countries received more net

transfers.Donors are selective for country policies in

low debt countries but not so in high multilateral debt countries.

Findings suggest that donors should be selective for country policies –invest less to countries with poor policy.

Additional resources to good policy countries will help to enhance their growth and lead to poverty reduction.

Donors can make the necessary break with past practice – increase their contribution to the huge development challenges in Africa.

Better donor behavior – more effective development assistance in the long rung, convince the public in donor countries to maintain and raise development assistance budgets.