This book is intended for a two-semester, graduate-level course and is paced to admit more extensive treatment of areas of specific interest to the instructor and students. It is assumed that the reader of the book will have had an econometric methods course. In the final section of each chapter we have provided a guide to further readings that briefly lists and describes useful related works in the area. The exercises provided with each chapter are a blend of proofs and results that replace or extend many of those in the text. Applications are included in the exercises as well. We believe strongly that students must grapple with applied econometric techniques. Of course, this means the development of an appropriate dexterity with computers and relevant software as a requirement for serious students in econometrics.
Inhaltsverzeichnis
Contents: Introduction.- Fundamental Methodology: Review of Ordinary Least Squares and Generalized Least Squares. Point Estimation and Tests of Hypotheses in Small Samples. Large Sample Point Estimation and Tests of Hypotheses. Stochastic Regressors. Use of Prior Information. Preliminary Test and Stein-Rule Estimators.- Violations of Basic Assumptions: Feasible Generalized Least Squares Estimation. Heteroscedasticity. Autocorrelation. Lagged Dependent Variables and Autocorrelation. Unobservable Variables.- Special Topics: Multicollinearity. Varying Coefficient Models. Models That Combine Time-Series and Cross-Section Data. The Analysis of Models with Qualitative or Censored Dependent Variables. Distributed Lags. Uncertainty in Model Specification and Selection.- Simultaneous Equations Models: Introduction to Simultaneous Equations Models. Identification. Limited Information Estimation. Full Information Estimation. Reduced Form Estimation and Prediction in Simultaneous Equations Models. Properties of Dynamic Simultaneous Equations Models.- Frontiers: Special Topics in Simultaneous Equations.- Appendix: Estimation and Inference in Nonlinear Statistical Models.- Index.
