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The Harvard Center for International Development is home to faculty affiliates from each school at Harvard University, working across sectors in developing nations around the world.

Faculty research is published in a wide range of academic and policy venues and can be found through the feed and filters below. Select faculty research papers are highlighted in our Faculty Research Insights series on our blog, CID Voices.

CID working papers published by Harvard faculty, graduate students, and research fellows prior to 2024 can be found here

Showing results 71 - 80 of 281

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David Bloom
Vol. 8, Issue 1
Recent research has documented a wide range of health, economic, and social benefits conferred by vaccination, beyond the direct reductions in morbidity, mortality, and future…
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Michael Woolcock
Working Paper No. 10051
Responding effectively and with professional integrity to the many challenges of public administration requires recognizing that access to more and better quantitative data is…
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Dani Rodrik
Working Paper No. 2023-07
In the context of a shift towards longer-term, public-value-oriented economic thinking, there is a real opportunity to reimagine the contracts that structure public-private…
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Rifat A. Atun
Vol. 11, Issue 10, Pages 1576-1586
Background: The global burden of diabetes is rising rapidly, yet there is little evidence on individual-level diabetes prevention activities undertaken by health systems in low-…
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Vincent Pons
Vol. 15, Issue 4, Pages 177–217
Candidates’ placements in polls or past elections can be powerful coordination devices for both parties and voters. Using a regression discontinuity design in French elections, we…
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Raffaella Sadun
Vol. 101, Issue 5, Pages 56-65
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Awa Ambra Seck
Between 1830 and 1962, six million Africans living under colonial rule served in the French army. Most were deployed internationally to maintain order or fight French wars. After…
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Joseph Henrich
Large language models (LLMs) have recently made vast advances in both generating and analyzing textual data. Technical reports often compare LLMs’ outputs with “human” performance…