Omitted Variable Tests and Dynamic Specification An Application to Demand Homogeneity

This book deals with the omitted variable tests for a multivariate time-series regression model. What are the consequences of testing for the omission of a variable when the model is dynamically misspecified? What is the small sample bias of the omitted variable test when the model dynamics is correctly specificfied? The answers to these questions are proposed in this book. As an empirical illustration, the analysis is applied to the homogeneity test of a demand system. I particularly thank Professor Dr. Philippe J. Deschamps who draw my attention on this subject and who made very helpful comments and sugges tions. Additionally, I would like to thank Professor Dr. Reiner Wolff for his comments especially on the chapter dealing with consumer theory. Special thanks go to Maria Jose Redondo, who read this book several times and for the inspiring discussions with her. I would also like to thank Dr. Ali Vak ili (always ready to answer any questions in mathematics), Prof. Dr. Hans Wolf gang Brachinger, Curzio De Gottardi, Peter Mantsch, Dr. Paul-Andre Monney, Dr. Uwe Steinhauser, Leon Stroeks and Dr. Peter Windlin. Frances Angell improved the English of this work. The research for this book had been financially suppürted by the Univer site de Fribourg (Switzerland). Finally, I appreciated the support from Springer-Verlag and I thank Dr.

Product details

• Authors: Björn Schmolck
• Publisher: Springer, Berlin
• Content: Book
• Product form: Paperback / Softback
• Publication date: 01.01.2000
• Subject: Social sciences, law, business > Business > Economics
• EAN: 9783540673583
• ISBN: 978-3-540-67358-3
• Pages: 144
• Illustrations: X, 144 p. 17 illus.
• Height (packing): 23.5 cm
• Weight (packing): 220 g
• Series: Lecture Notes in Economics and Mathematical Systems > Vol.488; Lecture Notes in Economics and Mathematical Systems > 488
• Subjects: Mikroökonomie, Wahrscheinlichkeitsrechnung und Statistik, Ökonometrie und Wirtschaftsstatistik, Correlation, Variance, Likelihood, Estimator, MonteCarloSimulation, Covariancematrix, Multivariateregression, Dynamicspecification, RobustWaldtest, Omittedvariabletest, Homogeneitytest