Knowledge that Transforms

Governments have used vouchers to spend billions of dollars on private education; much of this has gone to religiously affiliated schools. We explore the possibility that vouchers could alter the financial outcomes of religious organizations that are operating schools and thus have an impact on the spiritual, moral, and social fabric of communities. Using a data set of Catholic parish finances from Milwaukee, we show that vouchers are a dominant source of funding for many churches. Vouchers appear to offer financial stability for congregations as voucher expansion prevents church closures and mergers. However, voucher expansion causes significant declines in church donations and church revenue from noneducational sources.

Survey nonresponse has risen in recent years, which has increased the share of imputed and underreported values found on commonly used data sets. While this trend has been well documented for earnings, the growth in nonresponse to government transfers questions has received far less attention. We demonstrate analytically that the underreporting and imputation of transfer benefits can lead to program impact estimates that are substantially overstated when using instrumental variables methods to correct for endogeneity or measurement error in benefit amounts. We document the importance of failing to account for these issues using two empirical examples.

We propose to use economic theories to construct shrinkage estimators that perform well when the theories' empirical implications are approximately correct but perform no worse than unrestricted estimators when the theories' implications do not hold. We implement this construction in various settings, including labor demand and wage inequality, and estimation of consumer demand. We provide asymptotic and finite sample characterizations of the behavior of the proposed estimators. Our approach is an alternative to the use of theory as something to be tested or to be imposed on estimates. Our approach complements uses of theory for identification and extrapolation.

How high is unemployment? How low is labor force participation? Is obesity more prevalent among men? How large are household expenditures? We study the sources of the relevant official statistics—the Current Population Survey, the Behavioral Risk Factor Surveillance System, and the Consumer Expenditure Survey—and find that the answers depend on whether we look at easy- or at difficult-to-reach respondents, measured by the number of call and visit attempts made by interviewers. A challenge to the (conditionally-)random-nonresponse assumption, these findings empirically substantiate the theoretical warning against making population-wide estimates from surveys with low response rates.

This study examines the effect of chain store entry on drug quality and prices in India. In contrast to prevailing mom-and-pop pharmacies, chains exploit scale economies in distribution and signaling to offer high-quality drugs at lower cost. We show that chain entry leads to a 5% improvement in drug quality and a 2% decrease in prices at incumbent retailers. Effects are larger for locally distributed drug brands but do not depend on consumer SES. Our findings suggest that in markets with asymmetric information, organizational technologies such as chains can play an important role translating market expansion into higher quality.

We build on the intuitive (static) modeling framework of Rosen (1974) and specify a simple, forward-looking model of location choice. We use this model, along with a series of graphs, to describe the potential biases associated with the static model and relate these biases to the time series of the amenity of interest. We then derive an adjustment factor that allows the potentially biased static estimates to be converted into forwardlooking estimates. Finally, we illustrate these concepts with two empirical applications: the marginal willingness to pay to avoid violent crime and the marginal willingness to pay to avoid air pollution.

Teamwork pervades modern production, yet teamwork can make individual roles difficult to ascertain. The Matthew effect suggests that communities reward eminent team members for great outcomes at the expense of less eminent team members. We study this phenomenon in reverse, investigating credit sharing after damaging events. Our context is article retractions in the sciences. We find that retractions impose little citation penalty on the prior work of eminent coauthors, but less eminent coauthors experience substantial citation declines, especially when teamed with eminent authors. These findings suggest a reverse Matthew effect for team-produced negative events. A Bayesian model provides a candidate interpretation.

Using novel data from the Berea Panel Study, we show that the beauty wage premium for college graduates exists only in jobs where attractiveness is plausibly a productive characteristic. A large premium exists in jobs with substantial amounts of interpersonal interaction but not in jobs that require working with information. This finding is inconsistent with employer taste-based discrimination, which would favor attractive workers in all jobs. Unique task data address concerns that measurement error in the importance of interpersonal tasks may bias empirical work toward finding employer discrimination. Our conclusions are in stark contrast to the findings of existing research.

The basic New Keynesian model predicts that positive supply shocks are less expansionary at the zero lower bound (ZLB) compared to periods of active monetary policy. We test this prediction empirically using Fernald's (2014) utilization-adjusted total factor productivity series, which we take as a measure of exogenous productivity. In contrast to the predictions of the model, positive productivity shocks are estimated to be more expansionary at the ZLB compared to normal times. We find that there is no significant difference in the response of expected inflation to a productivity shock at the ZLB compared to normal times.

We provide evidence of a violation of the informativeness principle whereby lucky successes are overly rewarded. We isolate a quasi-experimental situation where the success of an agent is as good as random. To do so, we use high-quality data on football (soccer) matches and select shots on goal that landed on the goal posts. Using nonscoring shots, taken from a similar location on the pitch, as counterfactuals to scoring shots, we estimate the causal effect of a lucky success (goal) on the evaluation of the player's performance. We find clear evidence that luck is overly influencing managers' decisions and evaluators' ratings. Our results suggest that this phenomenon is likely to be widespread in economic organizations.