Knowledge that Transforms

We study the impact of misreported treatment status on the estimation of causal treatment effects, focusing on applications where no additional information or repeated measurements are available. We first characterize the bias introduced by misclassification on the average treatment effect on the treated (ATT) under a conditional independence assumption, in both a binary and a multiple-treatment setting. We find that the bias of matching-type estimators computed from misclassified data cannot in general be signed. We subsequently provide easily implementable methods to bound the ATT of interest semiparametrically, in particular allowing for very general forms of impact heterogeneity and of the no-treatment outcome equations, as well as for some dependence of the misreporting probabilities on individual characteristics. The empirical problem that motivates our paper is the estimation of the wage returns to a number of educational qualifications in the United Kingdom, allowing for misreporting in attainment. We investigate the sensitivity of the raw estimates to the presence of misclassification and explore the identification power of plausible restrictions on the nature and extent of misclassification. We show that the resulting bounds are sometimes wide but generally point to reasonable ranges of positive values for average returns to schooling among the schooled. For the range of educational qualifications considered, we further show that the claim sometimes made that measurement error bias roughly cancels out selection bias is not supported. More generally, our results show that under relatively mild restrictions, we can obtain strong conclusions regarding our questions of interest.

School desegregation might have induced unintended behavioral responses of white families as well as state and local governments. This paper examines these responses and is the first to study the effects of desegregation on the finances of school districts. Desegregation induced white flight from blacker to whiter public school districts and to private schools, but the local property tax base and local revenue were not adversely affected. The state legislature directed significant new funding to districts where whites were particularly affected by desegregation. Desegregation therefore appears to have achieved its intended goal of improving resources available in schools that blacks attended.

Consumption risk sharing among U.S. states increases in booms and decreases in recessions. These business cycle fluctuations in interstate risk sharing are driven mainly by states in which small businesses account for a large share of income or employment. State-level banking deregulation during the 1980s loosened the dependence of interstate risk sharing on the business cycle, mainly through its impact on states with many small firms. Our results establish a major benefit from bank deregulation: small firms' access to credit and, with it, interstate risk sharing have improved mainly when it is most urgently needed: in nationwide economic downturns.

Theory suggests that a firm facing competition will raise prices as consumer preferences become more diverse, and with high enough diversity, a duopolist under product differentiation may price higher than a monopolist. Focusing on the price for cable modem Internet access, with or without DSL competition, and using the standard deviation of education attainment as a proxy for preference diversity, we find empirical support for these results. In markets where cable competes with DSL, the cable Internet price increases with preference diversity. Moreover, the cable Internet price under DSL competition can exceed that without competition when preferences are sufficiently diverse. © 2011 The President and Fellows of Harvard College and the Massachusetts Institute of Technology.

U.S. firms' stock return volatility rose fivefold from 1971 through 2000 and then reverted to near 1971 levels by 2006. This was driven mainly by a rise and fall in the firm-specific, rather than systematic, component of volatility. Firm-level total factor productivity growth volatility exhibited a similar pattern. We hypothesize that firm heterogeneity, reflected in firm-specific volatility, rises as a new general purpose technology (GPT) propagates across the economy and then ebbs once the GPT is widespread. Measuring GPT adoption by information technology capital intensity, we find robust cross-industry empirical evidence supporting the hypothesis.

In this paper we provide new evidence on the impact on the U.S. CPI of the appearance and growth of new types of product outlets. Our CPI food microdata permit a more detailed categorization of outlet types than in previous studies, and we can adjust for numerous differences in item characteristics. We also examine the effects of changes in outlet mix not only across outlet categories but also within those categories. In our sample, we find that the upward impact on price from increased item quality has offset most, but not all, of the downward impact of lower-priced outlets.

We use panel data from the U.S. Health and Retirement Study, 1992–2002, to estimate the effect of self-assessed health limitations on the active labor market participation of older men. Self-assessments of health are likely to be endogenous to labor supply due to justification bias and individual-specific heterogeneity in subjective evaluations. We address both concerns. We propose a semiparametric binary choice procedure that incorporates nonadditive correlated individual-specific effects. Our estimation strategy identifies and estimates the average partial effects of health and functioning on labor market participation. The results indicate that poor health plays a major role in labor market exit decisions.

I look for divisions to clusters among academic departments in three disciplines: economics, mathematics, and comparative literature. I define clusters as subsets of departments with unexpectedly little hiring across the cluster lines. The division within economics is by far the strongest, is consistent with anecdotal evidence about “freshwater” and “saltwater” schools of thought and has been stable over time. There is also a significant division within comparative literature, but the hiring patterns among top mathematics departments are consistent with random matching.

We examine the effect of more than 3,400 gun shows using data from Gun and Knife Show Calendar and vital statistics data from California and Texas. Considering the one month following each show and a surrounding area ranging from 80 to 2,000 square miles, we find no evidence that gun shows increase either gun homicides or suicides. The similarity of our estimates for California and Texas suggests that the much tighter California gun show regulations do not substantially reduce the number of firearms-related deaths in that state. Using incident-level crime data for Houston, Texas, we also find no evidence of an effect on other crime categories.