Suchergebnisse

The estimation of the effects of treatments endogenous variables representing everything from individual participation in a training program to national participation in a World Bank loan program has occupied much of the theoretical and applied econometric research literatures in recent years. This volume brings together a diverse collection of papers on this important topic by leaders in the field from around the world. Some of the papers offer new theoretical contributions on various estimation techniques and others provide timely empirical applications illustrating the benefits of these and other methods.All of the papers share two common themes. First, as different estimators estimate different treatment effect parameters, it is vital to know what you are estimating and to know to whom the estimate applies. Second, as different estimators require different identification assumptions, it is crucial to understand the assumptions underlying each estimator. In empirical applications, the researcher must also make the case that the assumptions hold based on the available data and the institutional context. The theoretical contributions range over a variety of different estimators drawn from both statistics and econometrics, including matching and other non-parametric methods, panel methods, instrumental variables, methods based on hazard rate models and principal stratification, and they draw upon both the Bayesian and classical statistical traditions.The empirical contributions focus mainly on the evaluation of active labor market programs in Europe and the United States, but also examine of the effect of parenthood on wages and of the number of children on child health.It contains both theoretical and emperical contributions. It includes examples from both Europe and the US

This collection of methodological developments and applications of simulation-based methods were presented at a workshop at Louisiana State University in November, 2009. Topics include: extensions of the GHK simulator; maximum-simulated likelihood; composite marginal likelihood; and modelling and forecasting volatility in a bayesian approach.

Aims to annually publish original scholarly econometrics papers on designated topics with the intention of expanding the use of developed and emerging econometric techniques by disseminating ideas on the theory and practice of econometrics throughout the empirical economic, business and social science literature.

This volume focuses on recent developments in the use of structural econometric models in empirical economics. The first part looks at recent developments in the estimation of dynamic discrete choice models. The second part looks at recent advances in the area empirical matching models.