- Inbunden (Hardback)
- Antal sidor
- Cambridge University Press
- Trivedi, Pravin K.
- 17 b/w illus. 56 tables
- Series Number 53 Regression Analysis of Count Data
- 241 x 158 x 38 mm
- Antal komponenter
- 9:B&W 6 x 9 in or 229 x 152 mm Case Laminate on Creme w/Gloss Lam
- 929 g
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Regression Analysis of Count Data
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Fler böcker av A Colin Cameron
A Colin Cameron
This book provides the most comprehensive treatment to date of microeconometrics, the analysis of individual-level data on the economic behavior of individuals or firms using regression methods for cross section and panel data. The book is oriente...
Microeconometrics Using Stata
A Colin Cameron, Pravin K Trivedi
A complete and up-to-date survey of microeconometric methods available in Stata, Microeconometrics Using Stata, Revised Edition is an outstanding introduction to microeconometrics and how to execute microeconometric research using Stata. It covers...
Bloggat om Regression Analysis of Count Data
A. Colin Cameron is Professor of Economics at the University of California, Davis. His research and teaching interests span a range of topics in microeconometrics. He is a past director of the Center on Quantitative Social Science at the University of California, Davis and is currently an associate editor of the Stata Journal. He is coauthor (with Pravin K. Trivedi) of the first edition of Regression Analysis of Count Data (Cambridge, 1998) and of Microeconometrics: Methods and Applications (Cambridge, 2005). Pravin K. Trivedi is Distinguished Professor and J. H. Rudy Professor of Economics at Indiana University, Bloomington. His research and teaching interests are in microeconometrics and health economics. He served as co-editor of the Econometrics Journal from 2000 to 2007 and has been on the board of Journal of Applied Econometrics since 1988. He is coauthor (with A. Colin Cameron) of the first edition of Regression Analysis of Count Data (Cambridge, 1998) and of Microeconometrics: Methods and Applications (Cambridge, 2005).
1. Introduction; 2. Model specification and estimation; 3. Basic count regression; 4. Generalized count regression; 5. Model evaluation and testing; 6. Empirical illustrations; 7. Time series data; 8. Multivariate data; 9. Longitudinal data; 10. Endogenous regressors and selection; 11. Flexible methods for counts; 12. Bayesian methods for counts; 13. Measurement errors.