Knowledge that Transforms

Abstract We show that teachers’ value added (VA) depends on the VA of the teachers who preceded them. To do so, we use administrative data from North Carolina and find that a one-standard deviation increase in last grade’s mean teacher VA causes a 0.08σ decrease in teacher VA. Controlling for prior teacher assignment eliminates this bias. Under a benchmark policy that releases teachers in the bottom 5% of the VA distribution, 32% of teachers are incorrectly released using traditional techniques. Our results highlight the importance of incorporating dynamic features of education production into the estimation of teacher quality.

Abstract Close elections are important for many reasons, including that consequent election disputes can weaken democratic legitimacy and risk political violence. We quantify the probability of close outcomes in U.S. presidential races with novel applications of empirical election models from several sources. We show that razor-thin margins are very likely under the Electoral College (EC). And we establish that the EC causes this closeness: It would not occur under any plausibly comparable popular vote system. The tendency of the EC to generate close elections is found today and throughout U.S. presidential voting history.

Abstract This paper studies imperfectly perceived private information in insurance markets when contracts endogenously respond. Equilibrium contracts, pooling, and welfare depend on the joint distribution of risk and misperception. In the Health and Retirement Study (HRS), I show that misperceptions typically covary with (medical, long-term care, disability, and mortality) risk type: high types underperceive their risk and low types overperceive. I develop a general model and algorithm to estimate the equilibrium contracts, pooling, and welfare impact of misperceptions that is applicable in many settings. I offer suggestive evidence from U.S. annuity markets that contracts are distorted due to misperceptions, with welfare likely increasing.

Abstract We empirically assess whether hindsight bias affects citizens’ evaluation of their political actors. Using an incentivized elicitation technique, we demonstrate that people systematically misremember their past policy preferences regarding how to best fight the COVID-19 pandemic. At the peak of the first wave in the United States, the average respondent mistakenly believed that they supported significantly stricter restrictions at the onset of the first wave than they actually did. Exogenous variation in the extent of hindsight bias, induced through a randomized survey experiment, indicates that hindsight bias has a negative causal impact on the change in trust in government.

Abstract Using panel data on a 20% random sample of Canadian taxpayers, we study behavioral responses to the cancellation of a lifetime capital gains exemption that resulted in increased capital gains taxation for some individuals. We show that the exemption did not change the number of taxpayers reporting positive capital gains, and thus unlikely resulted in increased participation in capital markets. Furthermore, our results suggest that the cancellation increased the long-run capital gains realizations of tax filers with more unused exemption room but had a small, statistically insignificant impact on the capital gains realizations of those with little unused exemption room.

Abstract We investigate whether participants in the patent system are sensitive to information quality by examining how they treat inaccurate information. We use a novel approach to identify patents with inaccurate information: patent-paper pairs where the paper has been retracted and the corresponding patent contains the retracted material. Despite containing inaccurate information, we find that these patents are prosecuted and maintained by many applicants, are not rejected by examiners, and continue to be cited by some downstream readers after retraction. Insensitivity to inaccurate information may lead to erroneous decisions during examination and has implications for patent quality, disclosure, and knowledge flows.

Abstract Using Chicago police data, we train a machine learning model to predict the risk of being shot in the next 18 months. Out-of-sample accuracy is strikingly high. A central concern with using police data is “baking in” bias, or overestimating risk for groups likelier to interact with police conditional on behavior. Our predictions, however, accurately recover risk across demographic groups. Legal, ethical, and practical barriers should prevent using victimization predictions to target law enforcement. But using them to target social services could increase both the potential for interventions to reduce shootings and the available statistical power to detect those reductions.

Abstract This paper explores whether and why a maternal child penalty to earnings would emerge even without changes in employment and hours worked. Using a matched event study design, we trace monthly changes in determinants of wages (job performance, human capital accumulation, and promotions). Data come from a usefully unusual setting with required multiyear employment and detailed personnel data: the US Marine Corps. Mothers’ job performance initially declines, and gaps in promotion grow through 24 months postbirth. Fathers’ physical fitness performance drops somewhat but recovers. These patterns lead mothers to earn relatively lower wages, even absent changes in employment postbirth.

Abstract This paper investigates the returns to health care provision during the mortality transition. We construct a new panel data set covering German municipalities from 1928 to 1936. The endogeneity of health care supply is addressed by using the expulsion of Jewish physicians from statutory health insurance as exogenous variation in regional physician supply. Increases in the supply of physicians reduce infant mortality and mortality from common childhood diseases. Using a semiparametric control function approach, we find diminishing marginal returns to health care provision. The results are consistent with historical trends in infant mortality over the twentieth century.

Abstract This paper estimates the returns to human capital accumulation during the first era of mega-firms in the United States by linking employees at General Electric—a canonical enterprise associated with the “visible hand” of managerial hierarchies—to the 1940 census. I find large returns to higher education through seniority in the hierarchy, span of control, earnings, and selection into management training, using the proximity of land-grant colleges and historical universities to birth states for identification. The findings highlight the human capital determinants of the managerial revolution at a prominent firm, driven by earlier public investments in the U.S. education system.