Glenn Ellison’s research while affiliated with Massachusetts Institute of Technology and other places

We describe the structure and use of epidemiology models of disease transmission, with an emphasis on the susceptible/infected/recovered (SIR) model. We discuss high-profile forecasts of cases and deaths that have been based on these models, what went wrong with the early forecasts, and how they have adapted to the current COVID pandemic. We also offer three distinct areas where economists would be well positioned to contribute to or inform this epidemiology literature: modeling heterogeneity of susceptible populations in various dimensions, accommodating endogeneity of the parameters governing disease spread, and helping to understand the importance of political economy issues in disease suppression.

Does academic economic research produce material of general scientific value, or do academic economists write only for peers? Is economics scholarship uniquely insular? We address these questions by quantifying interactions between economics and other disciplines. Changes in the influence of economic scholarship are measured here by the frequency with which other disciplines cite papers in economics journals. We document a clear rise in the extramural influence of economic research, while also showing that economics is increasingly likely to reference other social sciences. A breakdown of extramural citations by economics fields shows broad field influence. Differentiating between theoretical and empirical papers classified using machine learning, we see that much of the rise in economics’ extramural influence reflects growth in citations to empirical work. This growth parallels an increase in the share of empirical cites within economics. At the same time, some disciplines that primarily cite economic theory have also recently increased citations of economics scholarship. ( JEL A11, A14)

Technologies, especially the Internet, have transformed how consumers search for products and prices. Price search has become cheap and easy and, therefore, ubiquitous, for many products. Just as technologies have made price search easier, however, they have increased incentives that firms have to obfuscate, or make price search harder. In this article, we focus on these actions that firms take and their effects on market participants. We discuss empirical evidence on this phenomenon, as well as its welfare impacts in the context of theories of search and obfuscation. Finally, we offer a framework for thinking about policy interventions based on this welfare analysis and outline some of the challenges facing policymakers.

We examine the evolution of economics research using a machine-learning-based classification of publications into fields and styles. The changing field distribution of publications would not seem to favor empirical papers. But economics' empirical shift is a within-field phenomenon; even fields that traditionally emphasize theory have gotten more empirical. Empirical work has also come to be more cited than theoretical work. The citation shift is sharpened when citations are weighted by journal importance. Regression analyses of citations per paper show empirical publications reaching citation parity with theoretical publications around 2000. Within fields and journals, however, empirical work is now cited more.

This paper uses data from the American Mathematics Competitions to examine the rates at which different high schools produce high-achieving math students. There are large differences in the frequency with which students from seemingly similar schools reach high achievement levels. The distribution of unexplained school effects includes a thick tail of schools that produce many more high- achieving students than is typical. Several additional analyses suggest that the differences are not primarily due to unobserved differences in student characteristics. The differences are persistent across time, suggesting that differences in the effectiveness of educational programs are not primarily due to direct peer effects.

Evolutionary models in which N players are repeatedly matched to play a game have "fast convergence" to a set A if the models both reach A quickly and leave A slowly, where "quickly" and "slowly" refer to whether the expected hitting and exit times remain bounded when N tends to infinity. We provide simple and general Lyapunov criteria which are sufficient for reaching quickly and leaving slowly. We use these criteria to determine aspects of learning models that promote fast convergence.

This article develops a model with endogenously coarse rules. A principal hires an agent to take an action. The principal knows the optimal state-contingent action, but cannot communicate it perfectly due to communication constraints. The principal can use previously realized states as examples to define rules of varying breadth. We analyze how rules are chosen under several assumptions about how rules can be amended. We explore the inefficiencies that arise and how they depend on the ability to refine rules, the principal’s time horizon and patience, and other factors. Our model exhibits path dependence in that the efficacy of rule development depends on the sequence of realizations of the state. We interpret this as providing a foundation for persistent performance differences between similar organizations and explore the role of different delegation structures in ameliorating the effects of bounded communication. (JEL D23, K40, D83)

This paper explores differences in the frequency with which students from different schools reach high levels of math achievement. Data from the American Mathematics Competitions is used to produce counts of high-scoring students from more than two thousand public, coeducational, non-magnet, non-charter U.S. high schools. High-achieving students are found to be very far from evenly distributed. There are strong demographic predictors of high achievement. There are also large differences among seemingly similar schools. The unobserved heterogeneity across schools includes a thick tail of schools that produce many more high-achieving students than the average school. Gender-related differences and other breakdowns are also discussed.