An Introduction to Classical Econometric Theory

Hardcover | March 1, 2000

byPaul A. Ruud

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In An Introduction to Classical Econometric Theory Paul A. Ruud shows the practical value of an intuitive approach to econometrics. Students learn not only why but how things work. Through geometry, seemingly distinct ideas are presented as the result of one common principle, makingeconometrics more than mere recipes or special tricks. In doing this, the author relies on such concepts as the linear vector space, orthogonality, and distance. Parts I and II introduce the ordinary least squares fitting method and the classical linear regression model, separately rather thansimultaneously as in other texts. Part III contains generalizations of the classical linear regression model and Part IV develops the latent variable models that distinguish econometrics from statistics. To motivate formal results in a chapter, the author begins with substantive empirical examples.Main results are followed by illustrative special cases; technical proofs appear toward the end of each chapter. Intended for a graduate audience, An Introduction to Classical Econometric Theory fills the gap between introductory and more advanced texts. It is the most conceptually complete text forgraduate econometrics courses and will play a vital role in graduate instruction.

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In An Introduction to Classical Econometric Theory Paul A. Ruud shows the practical value of an intuitive approach to econometrics. Students learn not only why but how things work. Through geometry, seemingly distinct ideas are presented as the result of one common principle, makingeconometrics more than mere recipes or special tricks....

Paul A. Ruud is at University of California, Berkeley.

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Format:HardcoverPublished:March 1, 2000Publisher:Oxford University PressLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:0195111648

ISBN - 13:9780195111644

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Table of Contents

IntroductionI. Ordinary Least Squares1. The Least Squares Linear Fit2. The Geometry of Least Squares3. Partitioned Fit4. Restricted Least Squares5. Overview ofc Ordinary Least SquaresII. Linear Regression6. Linear Unbiased Estimation7. Variances and Covariances8. Variances and Covariances of OLS9. Efficient Estimation10. Normal Distribution Theory11. Hypothesis Testing12. Overview of Linear RegressionIII. Generalizations of the Linear Model13. Non-Normal Distribution Theory14. Maximum Likelihood Estimation15. ML Asymptotics16. ML Computation17. ML Statistical Inference18. Heteroskedasticity19. Serial Correlation20. IV Estimation21. The Generalized Method of Moments22. GMM Hypothesis Tests23. OverviewIV. Latent Variable Models24. Panel Data Models25. ARMA Time Series Models26. Simultaneous Equations27. Discrete Dependent Variables28. Censored and Truncated Variables29. OverviewV. AppendicesA. Abbreviations and AcronymsB. NotationC. Linear Algebra and Matrix TheoryD. ProbabilityE. Classical StudiesF. Noncentral DistributionsG. Multivariate DifferentiationH. Characteristic Functions

Editorial Reviews

"This textbook is rigorous yet accessible. I believe it is destined to become the standard against which all other econometrics textbooks will be measured. Superb!"--Dr. James J. Jozefowicz, Indiana University of Pennsylvania