AID, GROWTH AND DEVELOPMENTFor or Against Official Development Assistance

Finn TarpUNU-WIDER and University of Copenhagen

UNU-ONY Event:

Conference Room 6, Temporary North Lawn Building,

UN Headquarters, New York 19 April 2010

Part I

INTRODUCTION AND MOTIVATION

Introduction (1)• The effectiveness of aid contentious: Not really

surprising • First, aid is given and received for many reasons:

Two basic approaches: – unselfish (promote ”a better world”) (includes needs vs merit/potential

issues) and selfish (strategic political, commercial and other interests)

• Second, “Does aid work” has many interpretations, for example:

Does aid improve human development (ex. HDI, save human lives, improve nutrition, promote food security)?

Does aid reduce poverty and inequality (ex. Headcounts, Gini, regional imbalances)?

Does aid promote ‘good policies’ (ex. CPIA)? Does aid promote democracy, freedom of speech and political

rights?

Introduction (2)

• Third, assume agreement on purpose: ”The how” remains open

• Many reasons for disagreement (Kanbur):– Different perceptions of market structure and power

(causal relationships)– Different levels of aggregation– Different time horizons

Principal Question of Interest in What Follows

Does foreign aid boost economic growth on average in developing countries?

Debated both in the academic and popular literature.“The notion that aid can alleviate systemic poverty, and has

done so, is a myth. Millions in Africa are poorer today because of aid; misery and poverty have not ended but

have increased.”

(Dambisa Moyo, 2009)

“A reasonable estimate is that over the last thirty years [aid] has added around one percentage point to the annual

growth rate of the bottom billion.”

(Paul Collier, 2007)

Objections to Pursuing the Issue

This isn’t a relevant question– Economic growth is not the objective– Foreign aid is too heterogeneous– Averages are not interesting

And recognize upfront methodological challenges:– Poor quality data across the board– Growth is a highly complex, non-linear process– Long delays between receipt of aid and onset of

economic growth (e.g., health, education)– Endogenous allocation of aid (good performers

graduate, poor performers remain or receive even more)

BUT …..

– My view: Profound dangers involved if the economics profession and more broadly social sciences fenced off the question (leave the field open to unhelpful rhetoric)

= Humility is required, BUT….lessons from 4 generations spanning >40 years merit attention

Part II

HISTORICAL BACKGROUND

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General Trends in Foreign Aid • The early years (>1945) – the Marshall plan: its

success fuelled optimistic expectations• The golden age (from early 1960s)• Stabilization and structural adjustment (early

1980s) (-> conditionality)

• Aid fatigue (from the late 1980s –> selectivity)• Monterey/Gleneagles G-8, the Paris declaration

and the Accra agenda for action (country ownership is key): A new beginning?

How Much Aid is Actually out There?

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Mozambique (28.6%)

Tanzania (13.2%)Bolivia (8.7%)

Vietnam (4.3%)

Bolivia (82.2$)Mozambique (61.9$)

Tanzania (34.7$)Vietnam (18.2$)

0.0

2.0

4.0

6.0

8D

ensity

0 20 40 60 80

Aid in % of GNIMode: 1.8%Median: 3.2%Iqr: 11.6%pointMin: -0.3%Max: 73.3%

Aid per capita, US$Mode: 17.9$Median: 31.5$Iqr: 65.9$Min: -20.6$Max: 1781.3$

Note: Kernel density using Gaussian kernel. The hight of the graph reflectsthe (weighted) average number of observations in an interval around the midpoint.Source: World Bank (2007)

Figure 2.2: Density of average annual (1996-2005)ODA shares

Changing Global Context

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020

40

60

80

10

0

1970 1975 1980 1985 1990 1995 2000 2005Year

RemittancesFDITradeGNI

Aid

Note: All variables are expressed as an index equal to one in 1970 and constructed from seriesof constant 2000 prices in US$.FDI is constructed from net FDI inflows and trade is based on the sum of exports and imports.Source: World Bank (2007)

Figure 2.3: Macroeconomic indicators in aidreceiving countries

Part III

EMPIRICAL LITERATURE:Four Generations

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What Does “does aid work?” Mean?: An Economist Perspective

• High income per capita associated with good standards of living – a lot of variation around means, but ….

• How to get high income? One avenue is:– Savings -> Investment -> Growth

• “Does aid work” often means:– Does aid increase savings?– Does aid increase investment?– Does aid increase growth?

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What is the Problem?

• How to measure the true impact of aid?• Targets versus actual outcomes• Before-and-after• The need for a counterfactual

– With-and-without– It is difficult and controversial! Economists use

different (often statistical) methods to try to deal with this

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Micro-evidence

• Cost-benefit analysis (old)• Many projects showed respectable rates of

private, economic and social return• Different projects had different returns (and

variation across countries and time), but overall it seemed aid works …

Turning to Early Macro: The Harrod-Domar Macro Model of Saving, Investment and Growth

Growth Constant* Investment / GDP

Investment Gross Domestic Saving + Foreign Saving

Ig

Y

I S A FY Y Y Y

• This simple model leads to the “financing gap” model: Aid fills a gap to reach desired growth

• Aid => S one-to-one, so Aid => I one-to-one, and Aid => Growth is predictable and sizeable (Aid = 10% of GDP might give an additional 5% growth)

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Aid and Growth: 1970s and 1980s

• Early optimism – Papanek’s articles using simple cross-country regressions

• But increasing disappointment with traditional Harrod-Domar (and Solow) model

• Aid may work at micro – but its impact not only is smaller than predicted (for many reasons) – it also somehow ‘evaporates’ on its way to the macro level (the micro-macro paradox)

• Eventually widespread perception of failure – reported in influential “so-called” summary studies…by Mosley, Anne Krueger, Howard White etc

• But what did cross-country research (first and second generation) actually show? No impact?

First and Second Generation: Hansen and Tarp (2000)

• 131 ”early” (simple) cross-country regression studies…..– Several studies showed aid associated with decreased

savings BUT only one study (and one regression) (Gupta & Islam, 1983) shows impact is greater than the aid – so net savings effect positive

– Aid increases investment! Not a single study contradicts

– Only one study (and one regression) (Mosley, 1987) shows negative impact on growth (and the insignificant studies overwhelmingly dominated by one study with misspecified model…)

• Aid seems to work – on average – in simple first and second generation studies

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Aid and Growth: Third Generation – the 1990s

• New data: panel data• New theory (introducing economic policy and

institutions directly)• Taking account of the endogeneity of aid• Taking non-linearity serious• New econometric methods (GMM)

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Third Generation – Panel Data Cross-country Regressions

• Aid is down the rathole (Boone, 1994)– [t]he lack of robustness of the aid variable in

the regression . . . shows that aid does not create, nor correlate with, those underlying factors which cause growth

– This empirical evidence supports Friedman’s (1958) forecast that the ‘new’ aid programs would not lead to economic development

• But Boone soon started fading….

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Aid and Growth: Third Generation – Burnside-Dollar

• Burnside-Dollar: aid works– But only in good policy countries

• Burnside-Dollar cutting the Gordian knot introducing an aid x policy interaction term in the statistical analysis

• Note underlying development paradigm and key policy implication

• Hansen and Tarp (2001) showed there is a more convincing story: aid works but with diminishing returns– The interaction term – aid x policy – looses out to

aid squared!• New data, new doubts!

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3rd Generation: Summing-up (Tarp, SEPR)

• A substantial number of 3rd generation studies• General consensus: aid does seem to work • But: disagreement about the particular

circumstances + aid less decisive than originally thought – Inherent problems or too small?

• Robustness an issue, methodological choices matter + remember ‘iron law of econometrics’:– With ‘noisy’ data, a ‘dirty’ dependent variable, and weak

proxies results biased towards zero– Weak instruments will give weak conclusions!!

• My take: Don’t allocate aid selectively according to simple macro rules

An Emerging Pessimistic 4th Generation

• Leading example is Rajan and Subramanian 2008– Supply side instruments for aid motivated by

skepticism of GMM statistical methods– Long horizon cross-section– No systematic effect of aid– This conclusion seems to hold for:

• Different types of aid• Alternative time periods

Micro-macro Paradox Revived?

• Insights of non-macro empirical research– Largely positive results from rigorous field

experiments– World Bank project evaluations broadly

encouraging http://www.worldbank.org/ieg/arde09/index.html

– Evidence of improvements in meso-level outcomes , particularly social indicators (e.g., Easterly, 2009)

• Some authors link these to aid

What Should We Expect?

• Aim of empirics is to falsify a prior

• Theoretical prior from growth theory = modest– Rajan and Subramanian (2008): 10% Aid/GDP

→ 1% increase in per capita growth rate

• Time dimension is important due to long run aspects of growth process– Education & health (Ashraf et al. 2008;

Acemoglu & Johnson 2007)

Arndt-Jones-Tarp (2009)http://www.wider.unu.edu/publications/working-papers/discussion-papers/2009/en_GB/dp2009-05/

• Start from Rajan-Subramanian (same data and instrument)– Retain focus on long-run cross-section

• Employ insights from programme evaluation:(1) Develop a new treatment/control estimator(2) Strengthen the growth equation specification(3) Improve the instrumentation strategy

• Quick review of results:– Cannot reject the theoretical prior (β = 0.1) (10% aid

gives 1% additional growth)– Generally do reject a “no impact” hypothesis (β = 0)– No micro-macro paradox!

Part IV

CONCLUDING DISCUSSION

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The Impact on Aid of Economic Crisis

• The average banking crisis reduces output per capita by 10% – and the loss is not restored within 7 years of the crisis onset

• The target for aid expressed as a percentage of economic size (0.7% of GNI)

• To maintain the past VOLUME of aid, aid will have to rise faster as a % of total spending

• Is this likely under business as usual scenarios? No

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Source: OECD-DAC Online Data Base

Net ODA as Percentage of Donor GNI in 2008

ODA/GNI

Many donors remain far from achieving the UN goal

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Note: ODA Disbursement is expressed in current prices(Millions of USD). Data for 2008 is preliminary.

Source: OECD-DAC Online Data Base

Net ODA Disbursement and ODA/GNI (% Change Between 2005 and 2008 )

Net ODA Disbursement (% Change) ODA/GNI (% Change)

The ODA/GNI ratio fell for 12 out of 22 DAC donors before the crisis 30

Gleneagles G8 Summit

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Source: OECD-DAC Online Data Base

Net ODA Disbursement to Africa Constant Prices(1981-2007)

Netting out debt relief ODA to Africa has not risen in real terms since the late 1980s

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Should We Worry?

• Aid’s critics would say NO (some even say growth will rise if aid is eliminated, others say aid has no effect)

• Weight of empirical evidence: Aid’s aggegate impact conforms to priors from modern growth theory (i.e. 10% aid/GNI gives 1% additional growth)

• So would appear present financial climate (where private flows have fallen dramatically) not a good time to experiment with Dambisa Moyo’s proposal to kill aid

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Conclusion• There is a problem out there! • It is morally right to do something about it• Aid an established tool – and limited other

options – at least for the time being• Plenty of micro evidence aid works• On many macro issues we lack definitive

answers • But, empirical macro evidence mounting – and

generally favorable to aid: 4 generations during more than 40 years!

• To get more impact make aid work better • Should we scale up as well?

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Conclusion

• Scaling up: Moyo says NO!! – Sachs says YES!!• Four generations suggest aid does work: while

little to suggest a highly potent driver – on average – very little to suggest aid has done macro-economic harm and many indications of some impact (alongside what one would expect)

• This does not per se prove significant scaling up would work – so balanced implication is: scale up where-ever possible

• From economics to politics: the need is there but is scaling up politically feasible? If so, how, under which circumstances?