Knowledge that Transforms

We show that, depending on how the impact of omitted variables is measured, it can be substantially easier for omitted variables to flip coefficient signs than to drive them to zero. This behavior occurs with “Oster's delta” (Oster 2019a), a widely reported robustness measure. Consequently, any time this measure is large—suggesting omitted variables may be unimportant—a much smaller value reverses the sign of the parameter of interest. We propose a modified measure of robustness to address this concern. We illustrate our results in four empirical applications and two meta-analyses. We implement our methods in the companion Stata module “regsensitivity.”

We propose a novel identification strategy to isolate exogenous immigration shocks across US counties, by interacting quasi-random variations in the composition of ancestry across counties with the contemporaneous inflow of migrants from different countries. We show a positive causal impact of immigration on local innovation and wages at the five-year horizon. The positive dynamic impact of immigration on innovation and wages dominates the short-run negative impact of increased labor supply. A structural estimation of a model of endogenous growth and migrations suggests the increased immigration to the United States since 1965 may have increased innovation and wages by 5 percent.

What is the optimal response of a resource exporter when a price cap is imposed on its main export? This paper develops a dynamic framework incorporating stochastic prices, financial frictions, and market power to study this novel tool of statecraft. With the right design, a price cap can incentivize increased extraction, stabilizing prices in the global market. But the stabilizing effects diminish when there is leakage outside the cap. Consequently, weak enforcement of the policy worsens the trade-off faced by the sanctioning policymaker. We provide a systematic approach to setting and enforcing an optimal cap level in these circumstances.

We study the welfare impacts of 96 climate-related tax and spending policies. We extend and apply the marginal value of public funds (MVPF) framework, most notably providing a new method for incorporating learning-by-doing spillovers. We find subsidies for the production of clean energy (such as wind production tax credits) have higher MVPFs than all other subsidies in our sample, including EV subsidies. Conservation nudges have large MVPFs when targeting regions with dirty grids. Fuel taxes and cap-and-trade policies are highly efficient means of raising revenue. We also construct traditional cost-per-ton estimates and compare and contrast the lessons they provide.

Using linked employer-employee data from Brazil, we document a significant gender pay gap, which is largely attributed to women working at lower-paying employers. To interpret this fact, we develop an equilibrium search model with endogenous firm pay, amenities, and hiring. We provide a constructive proof of identification of all model parameters. The estimated model suggests that amenities are important for both men and women, and that compensating differentials account for half of the gender pay gap. Equal treatment policies partly close gender gaps but are not output- or welfare-improving.

We construct a public atlas of mean outcomes in adulthood by childhood census tract. Outcomes vary sharply across neighborhoods: For children whose parents earn $27,000, the standard deviation of mean household income in adulthood is $10,420 across tracts within counties. Only half the variation in outcomes is explained by traditional measures of neighborhood opportunity like poverty rates. Experimental and quasi-experimental estimates indicate 60 percent of the variation in outcomes across neighborhoods is driven by causal effects. We demonstrate how our statistics can be applied to better target policies to improve low-opportunity areas and help families move to affordable high-opportunity areas.

We construct a dynamic model of child development where forward-looking parents and children jointly take actions to increase the child’s cognitive and noncognitive skills within a Markov perfect equilibrium framework. In addition to time and money investments in their child, parents also choose whether to use explicit incentives to increase the child’s self-investment, which may reduce the child’s future intrinsic motivation to invest by reducing the child’s discount factor. We use the estimated model parameters to show that the use of extrinsic motivation has large costs in terms of the child’s future incentives to invest in themselves.

An informed seller designs a dynamic mechanism to sell an experience good. The seller has partial information about the product match, which affects the buyer's private consumption experience. We characterize equilibrium mechanisms of this dynamic informed principal problem. The belief gap between the informed seller and the uninformed buyer, coupled with the buyer's learning, gives rise to mechanisms that provide the skeptical buyer with limited access to the product and an option to upgrade if the buyer is swayed by a good experience. Depending on the seller's screening technology, this takes the form of free/discounted trials or tiered pricing, which are prevalent in digital markets. In contrast to static environments, having consumer data can reduce sellers' revenue in equilibrium, as they fine-tune the dynamic design with their data forecasting the buyer's learning process.

We study the macroeconomic implications of asymmetric information in capital markets.We build a quantitative capital-accumulation model in which capital is traded in illiquid markets, with sellers having more information about capital quality than buyers.Asymmetric information distorts the terms of trade for sellers of high-quality capital, who list higher prices and are willing to accept lower trading probabilities to signal their type.Led by the model's predictions, we measure the distortions from asymmetric information by studying the relationship between listed prices and trading probabilities in a unique dataset of individual capital units listed for trade.By combining the empirical measurement with the model, we show that information asymmetries can play a quantitatively large role during economic crises when the degree of asymmetric information deteriorates.