Difference in differences methods have become very popular in applied work. This paper provides a new method for inference in these models when there are a small number of policy changes. This situation occurs in many implementations of these estimators. Identification of the key parameter...

This paper uses the marginal treatment effect (MTE) to unify the nonparametric literature on treatment effects with the econometric literature on structural estimation using a nonparametric analog of a policy invariant parameter; to generate a variety of treatment effects from a common...

There are two broad classes of models used to address the econometric problems caused by skewness in data commonly encountered in health care applications: (1) transformation to deal with skewness (e.g., OLS on ln(y)); and (2) alternative weighting approaches based on exponential conditional...

This paper examines non-response in a large government survey. The response rate for the American Time Use Survey (ATUS) has been below 60 percent for the first two years of its existence, raising questions about whether the results can be generalized to the target population. The paper begins...

This paper uses Wald's concept of the risk of a statistical decision function to address the question: How should sample data on treatment response be used to guide treatment choices in a heterogeneous population? Statistical treatment rules (STRs) are statistical decision functions that map...

In recent years, considerable attention has been devoted to the development of statistical methods for the analysis of uncertainty in cost-effectiveness analysis, with a focus on situations in which the analyst has patient-level data on the costs and health effects of alternative interventions....

Econometric analyses of treatment response commonly use instrumental variable (IV) assumptions to identify treatment effects. Yet the credibility of IV assumptions is often a matter of considerable disagreement, with much debate about whether some covariate is or is not a "valid instrument" in...

This paper examines the validity of overidentification tests and exogeneity tests in the presence of grouped data. We find that even a small intra-group correlation, when instruments do not vary within groups, may generate a substantial bias in the standard overidentification tests described in...

We propose methods for evaluating density forecasts. We focus primarily on methods" that are applicable regardless of the particular user's loss function. We illustrate the methods" with a detailed simulation example, and then we present an application to density forecasting of" daily stock...

A central problem in applied empirical work is to separate out the patterns in the data that are due to poor production of the data, such as e.g. non-response and measurement errors, from the patterns attributable to the economic phenomena studied. This paper interprets this inference problem as...