FOREIGN AID & THE POVERTY PROBLEM

FOREIGN AID & THE POVERTY PROBLEM WARWICK ECONOMICS SUMMER SCHOOL International Development Dr. Mani July 2014

LECTURES OUTLINE • Lecture 1: Introduction – Foreign Aid & the Poverty Problem • Lecture 2: Poverty & Nutrition; Intra-Household Resource Allocation • Lecture 3: Gender Issues: Missing Women & (Other) Crimes + Health • Lecture 4: Health + Behavioral Approach to Poverty

Lecture 1 Outline • Poverty Trends & Aid Flows • Aid Optimists versus Aid Pessimists • Evidence: Foreign Aid & Growth • Foreign Aid in Practice • Aid Goals & Conditionality • Effectiveness of Aid Organizations • New Approaches to Foreign Aid & Development

The Poverty Problem • GNP per capita at current exchange rates in 2007 in Switzerland was 59880. GNP per capita at PPP in 2007 was $45850 in the US. • What was it in the poorest country? • 61.2% of the population in Mali in the 2001 lived on less than $1.25 a day at 2005 PPP prices. • 30% of the children under 5 in Mali in 2000-2007 had measurable signs of malnutrition (44% in India, 0 in Sweden). • Under 5 mortality rate in Mali was 217/1000 in 2006 (270 in Sierra Leone, 4 in Norway) • Life expectancy at birth for males was 52 years in Mali (41 years in Sierra Leone, 79 in Sweden)

Preventable problems • In 2005, 865 million people lived under a dollar a day at Purchasing power parity: they have the purchasing power of 1 1993 dollar. What does this mean? • 27 million children every year do not get the essential vaccinations • 6.5 millon children die every year before their first birthday, mainly of diseases that could have been prevented. • Half of school-aged children in India cannot read a very easy paragraph (even though most are in school)

Changes in Poverty over Time

Aid Flows Official Foreign Aid to LDCs (2006) = $103.6 billion !

Optimists rationale for aid Poverty Trap: A situation where • To the left of the intersection, low income today lowers income tomorrow… • …the opposite is true to the right of the intersection • Under what conditions could the income generation process look like this? • Savings? • Returns to Education? • New Technology adoption? • Rationale for aid: A one-time large injection of funds can jump-start prosperity

Pessimists’ Rationale Against Aid • Why? • Income/resources can be accumulated gradually. • Big injections of money at low income levels will not alter the long term income level that can be reached. • Hence less rationale for aid.

Aid Optimists vs. Pessimists • Optimists: Jeffrey Sachs, Paul Collier, Bill Gates • Pessimists: William Easterly, DambisaMoyo • How do we reconcile these different points of view? Which one is true? What evidence should we consider to arrive at a conclusion? • One Conventional Measure: Growth Rates of Countries • Why Growth Rates? • Countries with high growth rates also seem to be very effective at Poverty Reduction (i.e. Growth and Poverty Reduction seem to be highly correlated) • Even the elasticity of Poverty Reduction wrt Growth rates does not seem to go down in countries with higher growth rates.

Foreign Aid & Growth • Evidence: Burnside and Dollar (AER,2000) • Finding: “We find that aid has a positive impact on growth in developing countries with good fiscal, monetary and trade policies but has little effect in the presence of poor policies” • Basic Specification: where g=growth rate of per capita income in country i at time t, y=per capita income, a=(aid receipts)/GDP, p=vector of policies (fiscal, monetary & trade) and z=vector of other exogenous variables that may affect growth and aid • Basic Idea: If policies affect growth, and lump sum aid has a positive effect on growth, then policies should affect the effectiveness of aid for growth as well.

Robustness of BD(2000) findings:1 Source: Burnside and Dollar(2000) Source: Easterly, Levine & Roodman (2003) • Scatter plot of unexplained portion of economic growth against unexplained portion of interaction between aid and policy where.. • Unexplained portion of growth and aid*policy is the error term obtained by regressing the variable on all other RHS variables in BD(2000)) • Small changes in definitions of “Aid”, “Policy” and the set of countries makes results change – so BD findings of aid & good policies not very robust

Aid Agencies: Defining Goals • Peculiar Incentive problem of Aid Agencies: • Spending one group of people’s money on another group of people.. • ..where the beneficiaries have little voice on how the money is spent • Goals: “Development”, “Poverty Reduction” or “Growth”, but.. • Over the short run, many factors other than aid affect growth. • Growth rates move quite slowly • How do you measure this goal concretely? • If it is unrealistic to expect aid to affect growth over the short run, aid agencies have little incentive to set targets in terms of growth rates…and • …not surprising that they choose more observable measures – i.e. aid disbursements.

Aid Agencies’ Goals -- 2 • Question: How can aid agencies ensure that these dollar target based disbursements result in effective aid? • Accounting for how Aid Money is spent • Imposing Conditions on Loans before they are granted (Conditionality): • Reward Good performance and Punish Poor performance • Reward self-motivated reformers more than countries on whom reform is imposed • Evaluating the effects of loans after they are completed.

Conditionality in Practice • Conditions attached to Aid about (low) budget deficits & inflation, non-interference in market pricing, privatization & Trade openness • Some Success Stories… • Mauritius, 1980-1994 – 4.3% growth in pci (7 adjustment loans) • Thailand (same period) – 5.3% per capita growth • Peru – did not first perform, but in the 1990s went from -2.6% growth (1980-90) to +2.6% per capita income growth(1990-94) • BUT not much punishment for countries that fail ! • Conditionality fails in practice if conditions imposed are not ‘Time Consistent’ • i.e., it is not in the best interest of the donor/aid agency to carry out a threat or promise that was initially designed to influence the recipient govt.’s actions (“Samaritan’s Dilemma”)

Conditionality in Practice -- 2 • “Over the past few years Kenya has performed a curious mating ritual with its aid donors. The steps are: one, Kenya wins its yearly pledges of foreign aid. Two, the government begins to misbehave, backtracking on economic reform and behaving in an authoritarian manner. Three, a new meeting of donor countries looms with exasperated foreign governments preparing their sharp rebukes. Four, Kenya pulls a placatory rabbit out of the hat. Five, the donors are mollified and the aid is pledged. The whole dance starts again.” ---- (The Economist, 1995)

Ex-post Evaluation of Projects • WB reviews only 5% of its loans after three to ten years following the last disbursement (Meltzer Commission, 2000) • Besides, evaluation uses reports from the very people who implemented the project! • World Bank surveys of borrowing governments since the mid-1990s on how the bank has performed from the governments’ point of view not made public (Wade, 2001).

Aid Agency Effectiveness Easterly-Pfutze, Journal of Economic Perspectives (2008) evaluate Aid agencies (23 Bilateral & 17Multilateral) on criteria below: • Transparency of operations: • What the money is spent on, which sector, how much to NGOs etc. • 4 Dimensions of Best practice: (measuring extent to which aid) • Specialization: is not fragmented among too many donors, too many countries, and too many sectors for each donor. • Selectivity: avoids corrupt autocrats and goes to the poorest countries. • Ineffective aid channels: is tied to political objectives or consists of food aid or technical assistance. • Overhead costs : an agency’s (administrative costs: amount of aid it gives) & aid per employee

Findings • Transparency: The data are terrible! Aid agencies are typically not transparent about their operating costs and about how they spend the aid money • IDA & multilateral development banks the best, UN agencies the worst! • Fragmentation: Too high – the probability that two random aid $s will • Be from the same donor = only 9.6% • Go to the same country, from any given donor = only 4.6% • Go to the same sector = only 8.6% (only 3 sectors got more than 10%) • i.e. Too many claimants, too many causes • Selectivity • Too much money to corrupt autocrats, too little to the poorest countries – and its not because poverty is highly correlated with corruption • Ineffective Aid Channels: • Mean shares: Tied aid (21%), food aid (4%), and technical assistance(24%) • Overhead costs: • Mean = 9% (OH costs/ODA), UN agencies the worst, multilateral donors bad

Correlations between Aid Practices • More specialization  Moreaid to corrupt states, less aid to the poorest countries • More specialization Lower overhead costs • Less food aid, tied aid  Less aid to corrupt states, more aid to the poorest countries • More transparency  Lower overhead

Aid Success Stories • Spectacular Success Stories: • Brazil Land Reform, Rural Electrification & Water Supply Program (2001) • South Korea, Taiwan • Eradication of Small pox • Near Eradication of River blindness • Family Planning, Life Expectancy & Lower Infant Mortality • Green Revolution in Asia

Why Growth May Not be the Right Outcome Measure • Foreign Aid Giving is based on Assumptions that do not seem to hold in practice: • That Foreign Aid should spur Investment • Investment should spur Growth • Countries with high Growth do have faster rates of Poverty Reduction, but this need not be a causal effect of Growth on Poverty Reduction. Why? • Reducing Poverty may foster Growth… • …Which may reduce poverty even further • Growth without Poverty Reduction may not be sustainable (for political and other reasons), so that countries that grow over time may be the ones that also focus on reducing poverty. • Considerable variation in Poverty Reduction rates across countries with high growth rates.

New Approaches: Thinking “Micro” • Set targets in terms of specific outcomes rather than growth rates or expenditures • E.g. Gates Foundation evaluates outcome in terms of number of children vaccinated, student achievement, use of toilets etc. • Identify specific programs/policies that work and why the do • Randomized Control Trials: Systematic, Scientific Evaluation of Programs to assess which programs really work and put money there • Idea taken from Drug Trials • Treatment Group vs. (otherwise identical) ‘Control’ Group • Compare outcomes across both groups to determine effectiveness of intervention. (Addresses Selection and OVB Issues in evaluation) • E.g. Treating Intestinal Worm infection in Kenya

New Approaches 2: Giving Directly • Give directly to Individuals rather than through Governments – Loans, (Un)conditional Cash Transfers (UCT/CCT) • Examples: Give Directly (UCTs), Kiva Foundation (Loans) • Give Directly Model • Identify poor households based on whether they have a Thatched Roof via Satellite images • Use Mpesa (“Mobile money”) to transfer money to eligible candidates -- $1000 per candidate • Evidence suggests that these Unconditional transfers are effective in increasing household assets and business/agricultural income as well as food security (not alcohol or tobacco consumption!), while lowering domestic violence and improving mental health (Haushofer and Shapiro(2013))

FOREIGN AID & THE POVERTY PROBLEM