Analysis of Microdata [Hardcover]

The availability of microdata has increased rapidly over the last decades, and standard statistical and econometric software packages for data analysis include ever more sophisticated modeling options. The goal of this book, now initssecondedition,istofamiliarizethereaderwithawiderangeofcommonly used models, and thereby to enable her/him to become a critical consumer of current empirical research, and to properly conduct own empirical analyses. The book can be used as a textbook for an advanced undergraduate, a Masters or a ?rst-year Ph.D. course on the topic of microdata analysis. In economicsandrelateddisciplines,suchacourseistypicallyo?eredaftera?rst course on the linear regression model. Alternatively, the book can also serve as a supplementary text to applied ?eld courses, such as those dealing with empirical analyses in labor, health or education. Finally, it might provide a useful reference for graduate students, researchers and practitioners who encounter microdata in their work. The focus of the book is on regression-type models in the context of large cross-section samples where the dependent variable is qualitative or discrete, or where the sample is not randomly drawn from the population of interest, due to censoring or truncation of the dependent variable. While our ba- groundisineconomics,andweoccasionallyrefertoproblemsandapplications fromempiricaleconomics,themodelsdiscussedinthisbookshouldbeequally relevant wherever microdata are used, inside the social sciences, including for example quantitative political science and sociology, as well as outside.

This second edition introduces regression models for qualitative and discrete dependent variables, to sample selection models, and to event history models, all in the context of maximum likelihood estimation. It presents a number of commonly used models.