Knowledge that Transforms

Local opinion leaders may play a key role in easing information frictions associated with technology adoption. This paper analyzes the influence of physician investigators who lead clinical trials for new cancer drugs. By comparing diffusion patterns across 21 new cancer drugs, we separate correlated regional demand for new technology from information spillovers. Patients in the lead investigator's region are initially 36% more likely to receive the new drug, but utilization converges within four years. We also find that superstar physician authors, measured by trial role or citation history, have broader influence than less prominent authors.

We estimate the first cross-sectional index of transaction-based land values for every U.S. metropolitan area. The index accounts for geographic selection and incorporates novel shrinkage methods using a prior belief based on urban economic theory. Land values at the city center increase with city size, as do land-value gradients; both are highly variable across cities. Urban land values are estimated at more than two times GDP in 2006. These estimates are higher and less volatile than estimates from residual (total - structure) methods. Five urban agglomerations account for 48% of all urban land value in the United States.

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.

We investigate determinants of driving speed in large U.S. cities. We first estimate city-level supply functions for travel in an econometric framework where the supply and demand for travel are explicit. These estimations allow us to calculate an index of driving speed and to rank cities by driving speed. Our data suggest that a congestion tax of about 3.5 cents per kilometer yields welfare gains of about $30 billion per year, that centralized cities are slower, that cities with ring roads are faster, and that the provision of automobile travel in cities is subject to decreasing returns to scale.

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.