Research

Abstract:

How can one motivate field staff to meet activity goals on time? Can introducing competition within groups motivate workers to meet goals faster than simply setting targets for workers? We conducted an experiment that assigned temporary field workers for a mobile app registration project into two treatment groups: field workers pursuing individual goals versus competing for a shared group-goal. We measure whether field workers reached their goal, the time to reach the goal, and the number of registered users per field worker. Our model suggests that field workers complete tasks more quickly with in-group competitive targets compared to individual targets. In line with this prediction, we observed that in-group competition led to an increased number of registrations and faster target achievement. Although the effects do not significantly vary by gender, the competition treatment proved more effective for employed individuals, those with less experience, and those with higher ability.

Abstract:

Using weekly price data from 97 Nigerian markets, we examine how seasonal harvest timing shapes price dynamics for staple grains using a dyadic panel design. Our analysis reveals that markets operating in the same harvest phase experience faster price convergence, while asynchronous seasonal conditions slow adjustments—particularly for local rice and cowpea. In contrast, imported long-grain rice shows stable price behavior throughout the year. These results highlight the critical influence of seasonal cycles on market integration and offer fresh insights for food security strategies.

Abstract:

Market integration is critical for food security in developing economies facing socio-political instability. Using weekly price data from 97 Nigerian markets, this study investigates how violent conflict influences trade dynamics between market pairs. Results reveal that frequent violent events have limited short-term effects on price transmission, and changes in conflict intensity do not significantly disrupt price adjustments. Markets with stronger trade connections demonstrate greater resilience by leveraging alternative trade routes. These findings highlight the role of market connectivity in maintaining trade efficiency, suggesting policies that enhance market networks can strengthen resilience and improve food security.

Abstract:

This study examines the unintended labor market and demographic consequences of China’s 2012 Female Labor Protection Policy (FLP), which aimed to strengthen workplace protections through extended maternity leave, standardized allowances, job restrictions, and employer penalties. Using a triple-difference strategy and China Family Panel Studies (CFPS) data, we isolate FLP's effects from concurrent family planning policies. Our findings reveal that while FLP sought to enhance workplace protections, it led to wage declines for women, no significant effect on labor force participation, and no observable impact on fertility rates. Wage reductions extended beyond childbearing-age women, disproportionately affecting older female workers. These results highlight how labor protections, when introduced alongside fertility policies, can inadvertently create wage penalties and spillover effects beyond targeted groups, offering new insights into the intersection of workplace regulations and demographic shifts.

Abstract:

Mitigating the ripple effects of shocks in a production network hinges on identifying a few critical sectors that shape the entire system’s response. In my study, I model trade as an interconnected input–output network and linearize its dynamics to derive a matrix that captures cascading disturbances. By leveraging concepts from network controllability analysis, I employ a novel method to pinpoint key nodes using a bipartite representation and maximum matching techniques. My findings reveal that these pivotal nodes tend to avoid high-degree, highly connected sectors; instead, they are often found in peripheral or upstream industries—such as specialized input-supplying sectors with few substitutes—that exert disproportionate influence on overall network stability. Building on these insights, I develop an optimal intervention framework to design the most efficient policy measures that stabilize the network by directly targeting these critical sectors. This tractable, policy-oriented framework provides new insights into mitigating systemic risk in an increasingly interconnected economy.

Abstract:

As natural disasters increasingly disrupt international trade, a key question is what makes a country's export resilient. A prominent hypothesis suggests that economic complexity—a measure of a country's productive capabilities—enhances stability, yet its role in buffering trade against large, sudden shocks remains empirically unsettled. This paper develops a unified framework to test this relationship, linking disaster shocks to countries' economic structures and positions in global value chains. Using a panel of bilateral, product-level exports, I first estimate average effects with a PPML gravity model and then introduce a novel resilience metric from a double-hurdle survival model, which captures the probability that a trade flow survives a shock above a critical threshold. To address the endogeneity of economic complexity, I use an instrument based on the average complexity of structural peers. Three results emerge. First, aggregate economic complexity by itself is a misleading predictor of resilience once its channels are disentangled. Second, upstream sectors experience larger export contractions. Third, resilience is driven by product sophistication rather than the breadth of the export basket: diversification without advanced capabilities fails to buffer major shocks. By disentangling the components of complexity, the paper explains why some economies withstand shocks while others suffer trade collapse and points to policies focused on upgrading product sophistication and managing upstream vulnerabilities.

Abstract:

Fluctuations in economic growth in foreign countries affect the U.S. economy, primarily through trade. We present a simple network model of trade and growth that formally represents the mechanisms through which demand shocks in other countries affect economic activities in the US. The key model prediction is that as the US trades more with emerging markets, whose economic volatility is higher on average, US employment volatility too will increase. The model predictions are estimated using US trade data and sector-level aggregate economic data from other countries over the past two decades.