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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 11 - 20 of 32

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Jaya Wen
Vol. 38, Pages 101-122
This paper investigates the effect of Phase 2 of the Golden Tax Project on the value-added tax (VAT) in China. The reform introduced computer-generated invoices and electronic…
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Winnie Yip
Vol. 220
The COVID-19 pandemic has accelerated the adoption of telemedicine worldwide. Understanding how demand for telemedicine services expands during and after the pandemic is important…
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Winnie Yip
The burden of sexually transmitted infections (STIs) continues to increase in developing countries like China, but the access to STI care is often limited. The emergence of direct…
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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
Purpose: This paper investigated whether a bank’s popularity and depositors' fear of Google search volume could affect bank deposits and credit. Design/methodology/approach: The…
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Winnie Yip
Vol. 234
Online health care marketplaces have emerged with the adoption of telemedicine during the COVID-19 pandemic. Despite its readily available information on price and quality, we…
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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…