Research

Working Papers

• "Reassessing China's Rural Reforms: The View from Outer Space"

  with Oliver Kim

  We study one of the central reforms in China’s economic miracle, the Household Responsibility System (HRS), which decollectivized agriculture starting in 1978. The HRS is commonly seen as having significantly boosted agricultural productivity—but this conclusion rests on unreliable official data. We use historical satellite imagery to generate new measurements of grain yield, independent of official Chinese statistics. Using two separate empirical designs that exploit the staggered rollout of the HRS across provinces and counties, we find no causal evidence that areas that adopted the HRS sooner experienced faster grain yield growth. These results challenge our conventional understanding of decollectivization, land reform, and the origins of the Chinese miracle.

Published

• "Will Wealth Weaken Weather Wars? AEA: Papers and Proceedings, 2024

  with Marshall Burke, Solomon Hsiang, and Edward Miguel

  Abstract: This study estimates the moderating impact of economic development on climate-conflict linkages during 1989–2019 in Africa, the world region that in recent decades has experienced the most armed conflict. We build a spatially disaggregated dataset that merges multiple decades of georeferenced data on climate shocks and conflict events with both local- and national-level measures of economic development to help shed light on the relative importance of local opportunity costs versus state capacity. We find that higher national GDP per capita greatly dampens the conflict risk associated with higher temperatures, suggesting that enhanced state capacity is a key factor.

• "Survey of open science practices and attitudes in the social sciences" Nature Communications, 2023

  with Rebecca Littman, Garret Christensen, Elizabeth Levy Paluck, Nicholas Swanson, Zenan Wang, Edward Miguel, David Birke, and John-Henry Pezzuto

  Abstract: Open science practices such as posting data or code and pre-registering analyses are increasingly prescribed and debated in the applied sciences, but the actual popularity and lifetime usage of these practices remain unknown. This study provides an assessment of attitudes toward, use of, and perceived norms regarding open science practices from a sample of authors published in top-10 (most-cited) journals and PhD students in top-20 ranked North American departments from four major social science disciplines: economics, political science, psychology, and sociology. We observe largely favorable private attitudes toward widespread lifetime usage (meaning that a researcher has used a particular practice at least once) of open science practices. As of 2020, nearly 90% of scholars had ever used at least one such practice. Support for posting data or code online is higher (88% overall support and nearly at the ceiling in some fields) than support for pre-registration (58% overall). With respect to norms, there is evidence that the scholars in our sample appear to underestimate the use of open science practices in their field. We also document that the reported lifetime prevalence of open science practices increased from 49% in 2010 to 87% a decade later.

• "Incorporating High-Frequency Weather Data into Consumption Expenditure Predictions" NeurIPS ML4D 2021

  with Anders Christensen and Simón Ramírez Amaya

  Recent efforts have been very successful in accurately mapping welfare in data-sparse regions of the world using satellite imagery and other non-traditional data sources. However, the literature to date has focused on predicting a particular class of welfare measures, asset indices, which are relatively insensitive to short-term fluctuations in well-being. We suggest that predicting more volatile welfare measures, such as consumption expenditure, substantially benefits from the incorporation of data sources with high temporal resolution. By incorporating daily weather data into training and prediction, we improve consumption prediction accuracy significantly compared to models that only utilize satellite imagery

• "Marketing and Technology Adoption and Diffusion" Applied Economics: Perspectives and Policy, 2020

  with Amir Heiman and David Zilberman

  Applied economists have investigated individual adoption choices as wellas diffusion (aggregate adoption). The emphasis, however, has been on adopters’ behavior and risk associated with production and markets. Marketing also considersbroader aspects and marketers develop tools to address risk related to thefit of a product, its performance, and its reliability. This paper expands the economic literature onadoption by analyzing and assessing the implications of the choice of marketing tools,like money-back guarantees, demonstrations, and others, by marketers. The analysisis based on the threshold model of diffusion, which recognizes heterogeneity and dynamics. We provide evidence and examples from agriculture.

Work in Progress

• "How Large are the Environmental Benefits of Sustainable Agriculture? Evidence from Mexico" with Bram Govaerts

• "Predicting Maize Yields at Large Scale using Remote Sensing" with James E. Sayre and Kangogo Sogomo

• "Conflict and Agricultural Land Abandonment in Africa"