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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 1 - 10 of 21

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Mark Esposito
Vol. 10, Issue 3
Governments around the globe are in a high-stakes race to develop cutting-edge AI systems. But how exactly are they using the technology for their own operations, and what might…
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Raffaella Sadun
Vol. 121, Issue 45, Pages e2412205121
A country’s national income broadly depends on the quantity and quality of workers and capital. But how well these factors are managed within and between firms may be a key…
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Rembrand Koning
Working Paper No. 25-023
Generative AI has the potential to transform productivity and reduce inequality, but only if adopted broadly. In this paper, we show that recently identified gender gaps in…
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Bruno S. Sergi
This paper provides theoretical and methodological underpinnings for optimal investment decisions in the oil & gas industry. In doing so, this paper investigates how to…
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David Yang
Working Paper No. 32193
Global innovation and entrepreneurship has traditionally been dominated by a handful of high-income countries, especially the US. This paper investigates the international…
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Bruno S. Sergi
This book elaborates on the modern experience and prospects and the development of recommendations for sustainable development of the agrarian economy based on digital…
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Raffaella Sadun
Vol. 101, Issue 5, Pages 56-65
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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…
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Jane Kim
Vol. 26, Issue 8, Pages 1217-1224
Objectives: Model-based cost-effectiveness analyses can inform decisions about screening guidelines by quantifying consequences of alternative algorithms. Although actual…