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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

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Foreign aid the poverty problem

FOREIGN AID & THE POVERTY PROBLEM

WARWICK ECONOMICS SUMMER SCHOOL International Development

Dr. Mani

July 2014


Lectures outline
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
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
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
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)



Aid flows
Aid Flows

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


Optimists rationale for aid
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
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
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
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
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
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
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
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
    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
    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
    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
    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
    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
    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
    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
    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
    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))