John Chipman

Advanced Econometric Theory (eBook, ePUB)

• Format: ePub

Produktbeschreibung

When learning econometrics, what better way than to be taught by one of its masters. In this significant new volume, John Chipman, the eminence grise of econometrics, presents his classic lectures in econometric theory.

Starting with the linear regression model, least squares, Gauss-Markov theory and the first principals of econometrics, this book guides the introductory student to an advanced stage of ability. The text covers multicollinearity and reduced-rank estimation, the treatment of linear restrictions and minimax estimation. Also included are chapters on the autocorrelation of residuals and simultaneous-equation estimation. By the end of the text, students will have a solid grounding in econometrics.

Despite the frequent complexity of the subject matter, Chipman's clear explanations, concise prose and sharp analysis make this book stand out from others in the field. With mathematical rigor sharpened by a lifetime of econometric analysis, this significant volume is sure to become a seminal and indispensable text in this area.

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Produktdetails

• Verlag: Taylor & Francis eBooks
• Seitenzahl: 408
• Erscheinungstermin: 1. März 2013
• Englisch
• ISBN-13: 9781134340446
• Artikelnr.: 38445702

Autorenporträt

John S. Chipman is Regents' Professor of Economics Emeritus at the University of Minnesota. He taught in the areas of Econometrics, International Trade, and Welfare Economics. His is currently involved in theoretical and econometric research into international trade and the history of utility theory. He has published a number of key journal articles and his paper - Homothetic Preferences and Aggregation - is one of the most significant papers in economic theory ever published.

Inhaltsangabe

Preface 1. Multivariate Analysis and the Linear Regression Model 2. Least
Squares and Gauss
Markov Theory 3. Multicollinearity and Reduced
Rank Estimation 4. The treatment of Linear Restrictions 5. Stein Estimation 6. Autocorrelations of Residuals
1 7. Autocorrelations of Residuals
2 8. Simultaneous Equations 9. Solutions to the Exercises

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Preface 1. Multivariate Analysis and the Linear Regression Model 2. Least-Squares and Gauss-Markov Theory 3. Multicollinearity and Reduced-Rank Estimation 4. The treatment of Linear Restrictions 5. Stein Estimation 6. Autocorrelations of Residuals-1 7. Autocorrelations of Residuals-2 8. Simultaneous Equations 9. Solutions to the Exercises