An Introduction to Classical Econometric Theory

An Introduction to Classical Econometric Theory

4.33 (3 ratings by Goodreads)
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Description

This book is designed to fill the gap between introductory undergraduate texts and advanced texts for graduate students. Its comprehensive coverage ensures that readers understand both the 'how' and the 'why' of econometrics, as it explains not only the mathematical techniques for econometric problem-solving but also the mathematical foundations of the discipline. Developed with careful pedagogical methodology throughout, the text makes full use of empirical examples and includes appendices providing 'ready reference' and refresher courses on basic mathematics, as well as further material for the more advanced student.show more

Product details

  • Hardback | 976 pages
  • 194 x 254 x 62mm | 1,919.97g
  • Oxford University Press Inc
  • New York, United States
  • English
  • numerous line figures
  • 0195111648
  • 9780195111644
  • 1,297,509

Review quote

Ruud's book is very original, innovative and clear * Recensioni e Segnalazioni Bibliografiche * Very advanced textbook which covers all aspects of classical econometric theory * Josef Forsterer, University of Linz * Excellent exposition, great clarity; coherency * Luc Bauwens, University of Lourain * Book gives a deep insight into the foundation of modern econometrics * Dr Hannes Winner, University of Innsbruck * A useful book that provides all the necessary mathematical tools for graduate students to analyse data obtained from repeatable experiments. * Aslib Book Guide, Vol.65, Aug. 2000. * It is an excellent text with very few weaknesses and I strongly recommend it. * R Blundell, University College London *show more

Table of contents

1. The Least-Squares Linear Fit ; 2. The Geometry of Least Squares ; 3. Partitioned Fit ; 4. Restricted Least Squares ; 5. Overview of Ordinary Least Squares ; 6. Linear Unbiased Estimation ; 7. Variances and Covariances ; 8. Variances and Covariances of Ordinary Least Squares ; 9. Efficient Estimation ; 10. Normal Distribution Theory ; 11. Hypothesis Testing ; 12. Overview of Linear Regression ; 13. Nonnormal Disbribution Theory ; 14. Maximum Likelihood Estimation ; 15. Maximum Likelihood Asymptotic Distribution Theory ; 16. Maximul Likelihood Computation ; 17. Maximum Likelihood Statistical Inference ; 18. Heteroskedasticity ; 19. Serial Correlation ; 20. Instrumental Variables Estimation ; 21. The Generalized Method of Moments ; 22. Generalized Method of Moments Hypothesis Tests ; 23. Overview ; 24. Panel Data Models ; 25. Autoregressive Moving-Average Time Series Models ; 26. Simultaneous Equations ; 27. Discrete Dependent Variables ; 28. Censored and Truncated Variables ; 29. Overview ; APPENDICES ; BIBLIOGRAPHY ; INDEXshow more

Review Text

It is an excellent text with very few weaknesses and I strongly recommend it. R Blundell, University College Londonshow more

Rating details

3 ratings
4.33 out of 5 stars
5 33% (1)
4 67% (2)
3 0% (0)
2 0% (0)
1 0% (0)
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