What Works in Development?: Thinking Big and Thinking Small - Softcover

Softcover

ISBN 10: 0815702825 ISBN 13: 9780815702825

Verlag: Brookings Institution Press, 2009

Inhaltsangabe

" What Works in Development? brings together leading experts to address one of the most basic yet vexing issues in development: what do we really know about what works— and what doesn't—in fighting global poverty? The contributors, including many of the world's most respected economic development analysts, focus on the ongoing debate over which paths to development truly maximize results. Should we emphasize a big-picture approach—focusing on the role of institutions, macroeconomic policies, growth strategies, and other country-level factors? Or is a more grassroots approach the way to go, with the focus on particular microeconomic interventions such as conditional cash transfers, bed nets, and other microlevel improvements in service delivery on the ground? The book attempts to find a consensus on which approach is likely to be more effective. Contributors include Nana Ashraf (Harvard Business School), Abhijit Banerjee (MIT), Nancy Birdsall (Center for Global Development), Anne Case (Princeton University), Jessica Cohen (Brookings),William Easterly (NYU and Brookings),Alaka Halla (Innovations for Poverty Action), Ricardo Hausman (Harvard University), Simon Johnson (MIT), Peter Klenow (Stanford University), Michael Kremer (Harvard), Ross Levine (Brown University), Sendhil Mullainathan (Harvard), Ben Olken (MIT), Lant Pritchett (Harvard), Martin Ravallion (World Bank), Dani Rodrik (Harvard), Paul Romer (Stanford University), and DavidWeil (Brown)."

Über diesen Titel

Über die Autorin bzw. den Autor

Jessica Cohen is a development economic research fellow with the Global Economy and Development program at the Brookings Institution. William Easterly, professor of economics at New York University and a nonresident senior fellow at the Brookings Institution, is the author of The White Man's Burden:Why theWest's Efforts to Aid the Rest Have Done So Much Ill and So Little Good (Penguin, 2006).

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What Works in Development?

Thinking Big and Thinking Small

Brookings Institution Press

Copyright © 2009 Brookings Institution Press
All right reserved.
ISBN: 978-0-8157-0282-5

Chapter One

Introduction: Thinking Big versus Thinking Small

JESSICA COHEN AND WILLIAM EASTERLY

The starting point for the contributions to this volume, and the conference for which they were prepared, is that there is no consensus on "what works" for growth and development. The ultimate goal of development research-a plausible demonstration of what has worked in the past and what might work in the future-remains elusive. As Martin Ravallion points out in his comment on chapter 2, we are beyond "policy rules" such as the Washington Consensus, and "thinking big" on development and growth is in crisis. The "big" triggers for economic growth have not been shown to work, either because they in fact did not work or because it was impossible to demonstrate their impact persuasively.

As a result, many in development have turned to "thinking small." For the most part-but not exclusively-the focus has shifted from macro- to micropolicy questions. This type of research commonly seeks the most effective method for delivering public goods such as education and vaccines. A growing methodology for analyzing micropolicy questions is randomized controlled trials (also known as Randomized Evaluations, REs). Much of this volume is about the merits and drawbacks of REs in elucidating what works in development. The specific arguments-we say more on them later in this chapter-revolve around several nagging questions. What kind of development policy research yields "hard" evidence? Are some types of evidence "harder" than others? Is there a trade-off between the scope of the questions researchers ask and the quality of the evidence they generate? What questions and what quality of evidence matter most for development policy and aid effectiveness? In exploring these issues, it is essential to first ask how the crisis in thinking big transpired and whether thinking small is indeed a solution.

The Collapse of "Thinking Big"

The failure of thinking big-elsewhere described as "the panaceas that failed"-has been widely acknowledged. Many would agree with Arnold Harberger that "there aren't too many policies that we can say with certainty ... affect growth." Some, like those behind the Barcelona Development Agenda, would go even further: "There is no single set of policies that can be guaranteed to ignite sustained growth." Even the universally revered dean of growth theory, Robert Solow, believes that "in real life it is very hard to move the permanent growth rate; and when it happens ... the source can be a bit mysterious even after the fact."

Where did this pessimism come from? As both Abhijit Banerjee, and William Easterly in his comment on Banerjeee, discuss later in the volume, several contributing factors readily come to mind: despite concerted attempts, macroeconomists were unable to deliver higher growth; the credibility of the growth regression literature waned; extremely volatile growth rates could not be explained; and growth analysis neglected to do enough long-run regressions.

The Failure of Big Pushes to Raise Growth

Three unsuccessful pushes are particularly notable:

1. The early big push in foreign aid (especially in the most aid-intensive continent, Africa).

2. Structural adjustment (also known as the Washington Consensus) in the 1980s and 1990s.

3. "Shock therapy" in the former Communist countries.

All of these episodes are far from natural experiments, of course, with adverse selection posing a severe problem for the interpretation of policy impact. However, all three had such poor outcomes that the counterfactual-that growth would have been even worse without the macroeconomic intervention-was hardly plausible.

The Failure of the Growth Regression Literature

The pessimism surrounding big pushes intensified as the credibility of the cross-country growth literature declined, with its endless claims for some new "key to growth" (regularly found to be "significant") and probably well-deserved reputation for rampant data mining. As the Easterly comment on Banerjee notes, the number of variables claimed to be significant right-hand-side (RHS) determinants approached 145, which is probably an undercount. Having a long list of possible controls to play with, researchers found it easy enough to arrive at significant results, and using the abundant heuristic biases that make it possible to see patterns in randomness, convinced themselves that the significant results were from the "right" specification, and that the others (usually unreported) were from the "wrong" ones.

The growth literature was also criticized for its inability to address causality. In the absence of clear evidence that growth outcomes can be attributed to specific levers, development research has severely limited utility for policy. This deficiency was probably due to the infeasibility of instrumenting for multiple RHS variables. Any such attempts usually relied on the Arellano-Bond or Arellano-Bover dynamic panel techniques, which (essentially using lagged RHS variables as instruments) became a kind of magical machine churning out causal econometric results. Unfortunately, the identifying assumptions were so implausible as to leave most outside observers unconvinced. This left the causality question unresolved.

Not to overstate the inevitability of the collapse of growth knowledge, neither data mining nor causality was a completely hopeless cause in aggregate regressions. Data mining can be held in check with a well-known methodology: estimating slight variants of the original specification that are as plausible as the original; or, better yet, adding new data that were unavailable at the time of the original estimation to the exact specification. As far as causality was concerned, occasionally there would be a reasonably plausible instrument for a RHS variable of particular interest.

Both remedies can be explored in the hotly debated literature on the effect of aid on growth. Since it is hard for researchers to hold themselves aloof from the strong vested interests in and political biases for or against aid, there was enormous scope for data mining in aid and growth regressions. One very simple test of data mining is to add new data that were not available at the time of the original regression specification and see if the results still hold. The famous result of Craig Burnside and David Dollar that "aid raises growth in a good policy environment" did not pass this test.

As for causality, one promising instrument for aid was population size, because of the quirk that the aid donor bureaucracy does not fully increase aid dollars one for one with recipient population size. Log of population is thus an excellent predictor of aid/gross domestic product (GDP), thankfully unrelated to the economic motivations for aid, and has been used in many studies. Another original strategy for identifying the impact of aid on growth has been to instrument aid from the Organization of Petroleum Exporting Countries (OPEC) to their poor Muslim allies with the interaction between oil price and a Muslim dummy variable. This approach uncovered a short-term effect of aid on output, but also a zero effect on medium-term growth. The generalizability problems of such identification strategies are much like those of REs. Does small-population-induced aid have the same effect as other aid? Does intra-Muslim aid have the same effect as aid from the United...

Details zur Ausgabe

• Verlag: Brookings Institution Press
• Erscheinungsdatum: 2009
• Sprache: Englisch
• ISBN 10: 0815702825
• ISBN 13: 9780815702825
• Einband: Taschenbuch
• Anzahl der Seiten: 257
• Herausgeber: Cohen Jessica
• Kontakt zum Hersteller: Nicht verfügbar
• Verantwortliche Person: gpsr@libri.de; gpsr@libri.de; ; Friedensallee 273; Hamburg; 22763; Deutschland