Research
Working Paper
I study the impact of partisan leaders on traffic stop policing behaviors in North Carolina. Using a difference-in-differences design that exploits sheriff turnovers, I find that offices with a Democrat-to-Republican sheriff turnover rather than a Democrat-to-Democrat sheriff transition have an increase of black drivers’ share in traffic stops by 3.2 percentage points, a 13.5% increase compared to baseline. Decomposing the changes in black driver's share along two dimensions: stop purposes and officers, I find that the increase is driven by changes within safety stops instead of investigation stops, and driven by changes in incumbent officers' tendency to stop black drivers. The increase in racial disparities is not accompanied by an increase in unconditional hit rates. Overall, the results suggest that partisan leadership, a crucial feature of the US criminal justice system, plays an important role in shaping racial disparities in frontline policing.
Publications
Curriculum and National Identity: Evidence from the 1997 Curriculum Reform in Taiwan (with Ming-Jen Lin and Tzu-Ting Yang | Journal of Development Economics, 2023) [final draft]
This paper examines the causal effects of textbook content on individuals' national identity, by exploiting a curriculum reform that introduced a new perspective on Taiwan's history for students entering junior high school after September 1997. Using a repeated nationally representative survey and a regression discontinuity design, we show that students exposed to the new textbooks were more likely to hold exclusive Taiwanese identity rather than dual identity (i.e. Taiwanese and Chinese). The effect was greater for academic track students and those living in neighborhoods where fewer people identify as Taiwanese. In addition, our results suggest that the new curriculum had little impact on people's political preferences related to Taiwan independence. Finally, we find that the probability of reporting as Taiwanese among old textbook readers converges with that of people reading new textbooks in the long run since the perspectives of old textbooks are in conflict with the recent social trends.
Work in Progress
The Impact of Partisan Politics on Personnel Composition: Evidence from North Carolina's Sheriffs' Offices (with Samuel Krumholz)
We study the impact of partisan leaders on the political composition of law enforcement agencies in the United States using elected sheriffs in North Carolina as a case study. Using a difference-in-differences design, we find that offices shifting from a Democrat to Republican sheriff experience a 9 percentage point (27\%) decrease in the Democratic share of Sheriff deputies relative to counties experiencing a Democrat to Democrat turnover. This change is driven both by existing Democratic deputies disproportionately changing their party registration and an increase in the share of Republican deputies among the entrants. Overall, we provide new evidence that leaders can shape the personnel's political composition not just by hiring but by inducing party switches.
Electoral Cycles of Informal Taxation and Welfare Benefit Provision: Evidence from Indonesia Villages
This paper studies the impact of electoral incentives on frontline public finance arrangements. I examine in Indonesian villages electoral cycles of informal tax collection and rice subsidy provision. In the election year, lower-expenditure households pay less informal taxes, and average households receive more subsidized rice. As a result, village heads make the informal tax system more progressive and reduce overall leakage in the subsidy program right before the village head elections. The results suggest that electoral incentives faced by local agents are important in shaping the local public finance system.
Disparate Impact of Social Safety Net Inclusion on Internal Migrants in Indonesia
Discussion of targeting the poor mostly focuses on the performance of specific methods on the general population, while the performance across groups are rarely examined. This project examines the performance of the proxy-means-testing (PMT) algorithms across internal migrants and locals in Indonesia. Using the same household expenditure sample and household characteristic variables, I reproduce the PMT algorithm adopted by Indonesian central government. I find that conditional on the same true household expenditure level, the PMT algorithm over-predicts internal migrants expenditure comparing to locals. Zooming in to the poor households the central government aims to target, whose expenditure lies in the bottom 25% of the population, the PMT algorithm's over-prediction results in an 8 percentage points increase of exclusion error for migrants than locals. Preliminary analysis indicates that among the PMT variables, household head education and occupation, and residential neighborhood characteristics contribute the most to the over-prediction bias. Future steps will explore whether local labor and residential markets function differently for locals and migrants and how these differences contribute to the PMT algorithm biases.
Does Better Targeting the Poor Increase Long-term Education Attainment? Evidence from Indonesia's Unified Targeting System (with Sudarno Sumarto and Achmad Tohari)
Decentralizing Development: Structural Transformation Effects of Indonesia's Village Fund (with Holt Dwyer)
The Impact of Algorithmic Tools on Sentencing: Evidence from New Zealand
The Impact of Algorithmic Tools on Accident Injury Categorization: Evidence from New Zealand