
Econometrics
Franco Peracchi(Author)
Wiley (Publisher)
Published on 7. December 2000
Book
Hardback
XXII, 680 pages
978-0-471-98764-2 (ISBN)
Description
In Econometrics the author has provided a text that bridges the gap between classical econometrics (with an emphasis on linear methods such as OLS, GLS and instrumental variables) and some of the key research areas of the last few years, including sampling problems, nonparametric methods and panel data analysis. Designed for advanced undergraduates and postgraduate students of the subject, Econometrics provides rigorous, yet accessible, coverage of the subject.
Key features include:
* A unified approach to statistical estimation emphasising the analogy (or bootstrap) principle
* An introduction to bootstrap and jackknife methods for assessing the accuracy of an estimator
* Detailed discussion of nonparametric methods for estimating density and regression of functions
* Emphasis on diagnostic procedures and on prediction criteria for evaluating the results fo statistical analysis
* An introduction to linear exponential family and generalized linear models
* A thorough discussion of robustness in statistical sense
More details
Product info
gebunden
Edition
1. Auflage
Language
English
Place of publication
New York
United States
Target group
College/higher education
Professional and scholarly
Product notice
sewn/stitched
Cloth over boards
Dimensions
Height: 240 mm
Width: 161 mm
Thickness: 42 mm
Weight
1211 gr
ISBN-13
978-0-471-98764-2 (9780471987642)
Schweitzer Classification
Person
Franco Peracchi is a Professor of Econometrics at Tor Vergata University in Rome. he received an MSc in Econometrics from the London School of Economics in 1983 and a PhD in Economics from Princeton University in 1987. His research interests include econometric theory and methods, nonparametric and robust statistical methods, and labour economics. His work has been published in leading econometric and statistical journals.
Content
Preface.
Notation.
Regression Models.
Sampling.
Time Series.
Point Estimation.
Statistical Accuracy and Hypothesis Testing.
The Classical Linear Model: Estimation.
Violations of the Ideal Conditions for OLS.
Diagnostics Based on the OLS Estimates.
The Classical Linear Model: Hypothesis Testing.
Asymptotic Properties of Least Squares Methods.
The Instrumental Variables Method.
Linear Models for Panel Data.
Linear Simultaneous Equation Models.
Nonparametric Methods.
M-Estimators.
Adaptive and Robust Regression Estimators.
Models for Discrete Responses.
Models for Truncated and Censored Data.
References.
Appendix A: Review of Linear Algebra.
Appendix B: Methods of Numerical Maximization.
Appendix C: Review of Probability.
Appendix D: Elements of Asymptotic Theory.
Index.