Semiparametric Methods in Econometrics (Lecture Notes in Statistics (131))

Many econometric models contain unknown functions as well as finite- dimensional parameters. Examples of such unknown functions are the distribution function of an unobserved random variable or a transformation of an observed variable. Econometric methods for estimating population parameters in the presence of unknown functions are called "semiparametric." During the past 15 years, much research has been carried out on semiparametric econometric models that are relevant to empirical economics. This book synthesizes the results that have been achieved for five important classes of models. The book is aimed at graduate students in econometrics and statistics as well as professionals who are not experts in semiparametic methods. The usefulness of the methods will be illustrated with applications that use real data. This book presents the main ideas underlying a variety of semiparametric methods in a way that will be accessible to graduate students and applied researchers who are familiar with econometrics theory at the level taught in graduate-level courses in leading universities. The book emphasizes ideas instead of technical details and provides as intuitive an exposition as possible. There are empirical examples that illustrate the methods that are presented and examples without data of applied problems in which semiparametric methods can be useful. Front Matter....Pages i-x Introduction....Pages 1-3 Single-Index Models....Pages 5-53 Binary Response Models....Pages 55-102 Deconvolution Problems....Pages 103-139 Transformation Models....Pages 141-178 Back Matter....Pages 179-206