Knowledge that Transforms

This paper studies the role of job displacement in the household bankruptcy decision. Using an event-study methodology, I find that NLSY respondents are over three times more likely to file for bankruptcy immediately following a job loss. Using county-level data, I find similar magnitudes in the aggregate, with significant effects lasting two to three years. The results suggest that unemployment spells can have significant long-term consequences on households’ credit market outcomes.

This paper studies the effects of violent crime on market prices and size using plant-level panel data in Colombia. To estimate causal effects, I exploit reductions in violence driven by increases in security expenditures during Álvaro Uribe’s presidency; these resulted in greater violence reductions in municipalities that voted for him in the 2002 elections as he was looking for reelection. I find that firms that face higher violence also face lower output and input prices. Output prices fall more than the prices of inputs, which drives firms to reduce production, and some firms exit the market. Workers see reductions in their real income.

We document how imperfect information generates heterogeneous effects in information treatments with personalized high-frequency feedback and peer comparisons. In our field experiment in retail electricity, we find that high- and low-energy users symmetrically underestimate and overestimate their relative energy use pretreatment. Responses to personalized feedback, however, are asymmetric. Households that overestimate their relative use and low users both respond by consuming more. These boomerang effects provide evidence that peer-comparison information programs, even those coupled with normative comparisons, are not guaranteed to lead to increases in prosocial behavior.

In models with potentially weak identification, researchers often decide whether to report a robust confidence set based on an initial assessment of model identification. Two-step procedures of this sort can generate large coverage distortions for reported confidence sets, and existing procedures for controlling these distortions are quite limited. This paper introduces a generally applicable approach to detecting weak identification and constructing two-step confidence sets in GMM. This approach controls coverage distortions under weak identification and indicates strong identification, with probability tending to 1 when the model is well identified.

West Bengal potato farmers cannot directly access wholesale markets and do not knowwholesale prices. Local middlemen earn large margins; pass-through from wholesale to farmgate prices is negligible. When we informed farmers in randomly chosen villages about wholesale prices, average farmgate sales and prices were unaffected, but pass-through to farmgate prices increased. These results can be explained by a model where farmers bargain ex post with village middlemen, with the outside option of selling to middlemen outside the village. They are inconsistent with standard oligopolistic models of pass-through, search frictions, or risk-sharing contracts.

I use daily prices collected from online retailers in five countries to study the impact of measurement bias on three common price stickiness statistics. Relative to previous results, I find that online prices have longer durations, with fewer price changes close to 0, and hazard functions that initially increase over time. I show that time-averaging and imputed prices in scanner and CPI data can fully explain the differences with the literature. I then report summary statistics for the duration and size of price changes using scraped data collected from 181 retailers in 31 countries.

Using employee-employer matched data, I analyze the impact of a low-wage trade shock on manufacturing workers in a high-wage country, Denmark, and how they adjust to the shock over a decade. I derive causal effects by exploiting the dismantling of the Multifiber Arrangement quotas on products from China upon its WTO accession as a quasi-natural experiment and use within-industry, within-occupation heterogeneity in workers’ exposure to this shock. I find significant negative long-run effects on earnings and employment trajectories and identify job instability in the service sector as a main adjustment friction, concentrated among workers with manufacturing-specific education and occupation. The results establish the importance of specific human capital in trade adjustment and provide evidence of skill upgrading as workers rebuild lost human capital through education.

We conduct a disaggregated empirical analysis of civil conflict at the subnational level in Africa over 1997 to 2011 using a new gridded data set. We construct an original measure of agriculture-relevant weather shocks exploiting within-year variation in weather and in crop growing season and spatial variation in crop cover. Temporal and spatial spillovers in conflict are addressed through spatial econometric techniques. Negative shocks occurring during the growing season of local crops affect conflict incidence persistently, and local conflict spills over to neighboring cells. We use our estimates to trace the dynamic response to shocks and predict how future warming may affect violence.

This paper analyzes "attribute-based regulations," in which regulatory compliance depends upon some secondary attribute that is not the intended target of the regulation. For example, in many countries, fuel-economy standards mandate that vehicles have a certain fuel economy, but heavier or larger vehicles are allowed to meet a lower standard. Such policies create perverse incentives to distort the attribute upon which compliance depends. We develop a theoretical framework to predict how actors will respond to attribute-based regulations and to characterize the welfare implications of these responses. To test our theoretical predictions, we exploit quasi-experimental variation in Japanese fuel economy regulations, under which fuel-economy targets are downward-sloping step functions of vehicle weight. Our bunching analysis reveals large distortions to vehicle weight induced by the policy. We then leverage panel data on vehicle redesigns to empirically investigate the welfare implications of attribute-basing, including both potential benefits and likely costs.

We study the effect of birth order on personality using Swedish population data. Earlier-born men are more emotionally stable, persistent, socially outgoing, willing to assume responsibility, and able to take initiative than later borns. Firstborn children aremore likely to bemanagers and to be in occupations requiring leadership ability, social ability, and Big Five personality traits.We find a significant role for the sex composition within the family. When investigating possible mechanisms, we find that negative effects of birth order are driven by postnatal environmental factors. We also find evidence of lower parental human capital investments in later-born children.