Knowledge that Transforms

Macroeconomic outcomes depend on the distribution of markups across firms and over time, making firm‐level markup estimates key for macroeconomic analysis. Methods to obtain these estimates require data on the prices that firms charge. Firm‐level data with wide coverage, however, primarily come from financial statements, which lack information on prices. We use an analytical framework to show that trends in markups over time or the dispersion of markups across firms can still be well‐measured with such data. Measuring the average level of the markup does require pricing data, and we propose a consistent estimator for such settings. We validate the analytical results using simulations of a quantitative macroeconomic model and offer supporting evidence from firm‐level administrative production and pricing data. Our analysis supports the use of financial data to measure trends in aggregate markups.

Governments use their countries' economic strength from financial and trade relationships to achieve geopolitical and economic goals. We provide a model of the sources of geoeconomic power and how it is wielded. The source of this power is the ability of a hegemonic country to coordinate threats across disparate economic relationships as a means of enforcement on foreign entities. The hegemon wields this power to demand costly actions out of the targeted entities, including mark‐ups, import restrictions, tariffs, and political concessions. The hegemon uses its power to change targeted entities' activities to manipulate the global equilibrium in its favor and increase its power. A sector is strategic either in helping the hegemon form threats or in manipulating the world equilibrium via input‐output amplification. The hegemon acts a global enforcer, thus adding value to the world economy, but destroys value by distorting the equilibrium in its favor.

We study reputation formation where a long‐run player repeatedly observes private signals and takes actions. Short‐run players observe the long‐run player's past actions but not her past signals. The long‐run player can thus develop a reputation for playing a distribution over actions, but not necessarily for playing a particular mapping from signals to actions. Nonetheless, we show that the long‐run player can secure her Stackelberg payoff if distinct commitment types are statistically distinguishable and the Stackelberg strategy is confound‐defeating . This property holds if and only if the Stackelberg strategy is the unique solution to an optimal transport problem. If the long‐run player's payoff is supermodular in one‐dimensional signals and actions, she secures the Stackelberg payoff if and only if the Stackelberg strategy is monotone. Applications include deterrence, delegation, signaling, and persuasion. Our results extend to the case where distinct commitment types may be indistinguishable, but the Stackelberg type is salient under the prior.

Transparency versus opacity is an important dimension of college admission policy. Colleges may gain useful information from a holistic review of applicants' materials, but in doing so may contribute to uncertainty that discourages potential applicants with poor information. This paper investigates the impacts of admissions transparency in the context of Texas' Top Ten Percent Plan, using survey and administrative data from Texas and a model of college applications, admissions, enrollment, grades, and persistence. I estimate that two thirds of the plan's 9.1 point impact on top‐decile students' probability of attending a flagship university was due to information rather than mechanical effects. Students induced to enroll are more likely to come from low‐income high schools, and academically outperform the students that they displace. These effects would be larger if complemented by financial‐aid information, and are driven by transparency, not misalignment between the rules used for automatic and discretionary admissions.