AID, GROWTH AND DEVELOPMENT For or Against Official Development Assistance

1. AID, GROWTH AND DEVELOPMENTFor or Against Official Development Assistance Finn Tarp UNU-WIDER and University of Copenhagen UNU-ONY Event: Conference Room 6, Temporary North Lawn Building, UN Headquarters, New York 19 April 2010

2. Part I INTRODUCTION AND MOTIVATION

3. Introduction (1) • The effectiveness of aidcontentious: Not reallysurprising • First, aid is given and received for manyreasons: Twobasicapproaches: • unselfish (promote ”a betterworld”) (includesneedsvs merit/potential issues) and selfish (strategicpolitical, commercial and otherinterests) • 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?

4. 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

5. 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.” (DambisaMoyo, 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)

6. 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)

7. 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

8. Part II HISTORICAL BACKGROUND

9. 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?

10. How Much Aid is Actually out There?

11. Changing Global Context

12. Part III EMPIRICAL LITERATURE: Four Generations

13. 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?

14. 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

15. 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 …

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

17. 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?

18. 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

19. 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)

20. 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….

21. 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!

22. 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

23. 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

24. 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

25. 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)

26. 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!

27. Part IV CONCLUDING DISCUSSION

28. 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

29. Many donors remain far from achieving the UN goal

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

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

32. 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

33. 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?

34. 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?