Measurement of seat belt and air bag effectiveness is complicated by the fact that systematic data are collected only for crashes in which a fatality occurs. These data suffer from sample selection since seat belt and air bag usage influences survival rates which in turn determine whether a...

Measuring the relative likelihood of fatal crash involvement for different types of drivers would seem to require information on both the number of fatal crashes by driver type and the fraction of drivers on the road falling into each category. In this paper, however, we present a methodology...

Because data are collected for only fatal crashes, it is difficult to accurately measure seat belt and air bag effectiveness. The use of safety devices influences survival rates which in turn determine whether a crash is included in the sample, leading to sample selection bias. We propose a...

We present a methodology for measuring the risks posed by drinking drivers that relies solely on readily available data on fatal crashes. The key to our identification strategy is a hidden richness inherent in two-car crashes. Drivers with alcohol in their blood are seven times more likely to...

In certain auction, search, and related models, the boundary of the support of the observed data depends on some of the parameters of interest. For such nonregular models, standard asymptotic distribution theory does not apply. Previous work has focused on characterizing the nonstandard limiting...

We provide an argument for the limitation of Edgeworth expansions to many commonly used statistics in the weak instrument framework. However, we show that Edgeworth expansions hold for approximately similar tests regardless of the identification conditions. Finally, we consider simulation...

In certain auction, search, and related models, the boundary of the support of the observed data depends on some of the parameters of interest. For such nonregular models, standard asymptotic distribution theory does not apply. Previous work has focused on characterizing the nonstandard limiting...

It is well-known that size-adjustments based on Edgeworth expansions for the t-statistic perform poorly when instruments are weakly correlated with the endogenous explanatory variable. This paper shows, however, that the lack of Edgeworth expansions and bootstrap validity are not tied to the...

This paper develops asymptotic optimality theory for statistical treatment rules in smooth parametric and semiparametric models. Manski (2000, 2002, 2004) and Dehejia (2005) have argued that the problem of choosing treatments to maximize social welfare is distinct from the point estimation and...