This overview describes the development of methods for empirical research in the field of labor economics during the past four decades. This period is characterized by the use of micro data to answer policy relevant research question. Prominent in the literature is the search for exogenous...

This chapter reviews the existing empirical evidence on how social insurance affects health. Social insurance encompasses programs primarily designed to insure against health risks, such as health insurance, sick leave insurance, accident insurance, long-term care insurance and disability...

This survey is devoted to the statistical analysis of duration models and point processes. The first section introduces specific concepts and definitions for single-spell duration models. Section two is devoted to the presentation of conditional duration models which incorporate the effects of...

This paper develops the method of local instrumental variables for models with multiple, unordered treatments when treatment choice is determined by a nonparametric version of the multinomial choice model. Responses to interventions are permitted to be heterogeneous in a general way and agents...

Traditional instrumental variable estimators do not generally estimate effects for the treated population but for the unobserved population of compliers. They do identify effects for the treated when there is one-sided perfect non-compliance. However, this property is lost when covariates are...

This paper reviews some of the most popular policy evaluation methods in empirical microeconomics: social experiments, natural experiments, matching, instrumental variables, discontinuity design, and control functions. It discusses identification of traditionally used average parameters and more...

A large part of the recent literature on program evaluation has focused on estimation of the average effect of the treatment under assumptions of unconfoundedness or ignorability following the seminal work by Rubin (1974) and Rosenbaum and Rubin (1983). In many cases however, researchers are...

The Wooldridge method is based on a simple and novel strategy to deal with the initial values problem in the nonlinear dynamic random-effects panel data models. This characteristic of the method makes it very attractive in empirical applications. However, its finite sample performance is not...

This paper assesses the effectiveness of unconfoundedness-based estimators of mean effects for multiple or multivalued treatments in eliminating biases arising from nonrandom treatment assignment. We evaluate these multiple treatment estimators by simultaneously equalizing average outcomes among...

Estimation of average treatment effects under unconfoundedness or exogenous treatment assignment is often hampered by lack of overlap in the covariate distributions. This lack of overlap can lead to imprecise estimates and can make commonly used estimators sensitive to the choice of...