Econometric Methods with Applications in Business and Economics / Edition 1

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Applied work in business and economics often require a solid understanding of econometric methods to support decision making. This book provides this, encouraging an active engagement with these methods by means of examples and exercises, so that the student develops a working understanding and hands-on experience with current day econometrics.
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Product Details

  • ISBN-13: 9780199268016
  • Publisher: Oxford University Press
  • Publication date: 6/28/2004
  • Edition description: New Edition
  • Edition number: 1
  • Pages: 816
  • Sales rank: 1,217,017
  • Product dimensions: 9.80 (w) x 7.50 (h) x 1.90 (d)

Meet the Author

Christiaan Heij is Associate Professor at the Econometric Institute of the Erasmus University in Rotterdam and specialises in econometrics and statistics. Paul de Boer is Assistant Professor at the Econometric Institute of the Erasmus University in Rotterdam and specialises in econometrics and statistics. Philip Hans Franses is Professor of Applied Econometrics and Professor of Marketing Research, both at the Erasmus University Rotterdam. He has published in leading international journals on applied econometrics, time series analysis, empirical finance, and marketing research. He is the (co-)author of various books published by Oxford University Press and Cambridge University Press.
Teun Kloek is Professor Emeritus of Econometrics at Erasmus University Rotterdam. He has published in leading international journals on econometric theory, applied econometrics and quantitative economics. Herman K. van Dijk is Professor of Econometrics and director of the Econometric Institute of the Erasmus University in Rotterdam. His fields of research are Bayesian Inference and Decision Analysis in Econometrics, Computational Economics, Stochastic Trends and Cycles in Time Series Econometrics and Income Distributions.

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Table of Contents

1. Review of Statistics
2. Simple Regression
3. Multiple Regression
4. Nonlinear Methods
5. Diagnostic Tests and Model Adjustments
6. Qualitative and Limited Dependent Variables
7. Time Series and Dynamic Models
Appendix A: Matrix Methods
Appendix B: Data Sets

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