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Cited by 308

The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.

The Power and Pitfalls of Experiments in Development Economics: Some Non‐random Reflections

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Barrett, Christopher B., Carter, Michael R.·2010·Applied Economic Perspectives and Policy

Abstract

Impact evaluation based on randomized controlled trials (RCTs) offers a powerful tool that has fundamentally reshaped development economics by offering novel solutions to long‐standing problems of weak causal identification. Nonetheless, RCTs suffer important and underappreciated pitfalls, some of which are intrinsic to the method when applied to economic problems, others that are the result of methodological boosterism. Among the pitfalls are ethical dilemmas, uncontrollable treatments that result in a ‘faux exogeneity,’ distortion of the research agenda, and a tendency to estimate interventions' abstract efficacy rather than their effectiveness in practice. We illustrate these points through the literature on smallholder capital access and productivity growth. Ultimately, we argue for a methodological pluralism that recognizes all identification strategies' limitations.

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Metadata

Authors
Barrett, C. B., & Carter, M. R.
Venue
Applied Economic Perspectives and Policy
Publisher
Wiley
Published
2010-12
Volume
32
Issue
4
Pages
515-548
ISSN
  • 2040-5790 (ISSN-L)
  • 2040-5804
OpenAlex
W2021675608
Cited by
308
References
7
FWCI
15.08
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: The Power and Pitfalls of Experiments in Development Economics: Some Non‐random Reflections. https://app.cochat.ai/papers/10.1093/aepp/ppq023
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Barrett, C. B., & Carter, M. R. (2010). The Power and Pitfalls of Experiments in Development Economics: Some Non‐random Reflections. Applied Economic Perspectives and Policy. https://doi.org/10.1093/aepp/ppq023

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.