A. Colin Cameron is Professor of Economics atthe University of California, Davis. He currently serves as Director of that university's Center on Quantitative Social Science Research. He is coauthor with Pravin Trivedi of Regression Analysis of Count Data. Pravin K. Trivedi is John H. Rudy Professor of Economics at Indiana University at Bloomington. He is on the editorial boards ofthe Econometrics Journal and the Journal of Applied Econometrics.
Microeconometrics. Methods and Applications
Par : ,Formats :
- Nombre de pages1056
- FormatGrand Format
- PrésentationRelié
- Poids1.83 kg
- Dimensions18,2 cm × 26,1 cm × 4,1 cm
- ISBN0-521-84805-9
- EAN9780521848053
- Date de parution01/05/2005
- ÉditeurCambridge University Press
Résumé
This book provides a comprehensive treatment of microeconometrics, the analysis ofindividual-level data on the economic behaviorof individuals orfirms using regression methods applied to cross section and panel data. The book is oriented to the practitioner. A good understanding of the linear regression model with matrix algebra is assumed. The text can be used for Ph.D. courses in microeconometrics, in applied econometrics, or in data-oriented microeconomics sub-disciplines ; and as a reference work for graduate students and applied researchers who wish to fill in gaps in their tool kit.
Distinguishing features include emphasis on nonlinear models and robust inference, as well as chapter-length treatments of GMM estimation, nonparametric regression, simulation-based estimation, bootstrap methods, Bayesian methods, stratified and clustered samples, treatment evaluation, measurement error, and missing data. The book makes frequent use of empirical illustrations, many based on seven large and rich data sets.
Distinguishing features include emphasis on nonlinear models and robust inference, as well as chapter-length treatments of GMM estimation, nonparametric regression, simulation-based estimation, bootstrap methods, Bayesian methods, stratified and clustered samples, treatment evaluation, measurement error, and missing data. The book makes frequent use of empirical illustrations, many based on seven large and rich data sets.