Inference in Cointegrated VAR Models

Alessandra Canepa

ISBN 10: 3838314697 / ISBN 13: 9783838314693

Published by LAP LAMBERT Academic Publishing Mai 2010, 2010

About this Item

This item is printed on demand - Print on Demand Titel. Neuware -Obtaining reliable inference procedures is one of the main challenges of econometric research. Test statistics are usually based on applications of the central limit theorem. However, in order to work well the first order asymptotic approximation requires that the asymptotic distribution is an accurate approximation to the finite sample distribution. When dealing with time series models, this is not generally the case. In this book we investigate the small sample performance of various bootstrap based inference procedures when applied to vector autoregressive models. Special attention is given to Johansen's maximum likelihood method for conducting inference on cointegrated VAR models. Throughout the book, empirical applications are provided to illustrate the bootstrap method and its applications. The analysis should provide some guidance to practitioners in doubt about which inference procedure to use when dealing with cointegrated VAR models.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 172 pp. Englisch.

Seller Inventory # 9783838314693

Bibliographic Details

• Title: Inference in Cointegrated VAR Models
• Publisher: LAP LAMBERT Academic Publishing Mai 2010
• Publication Date: 2010
• Language: English
• ISBN 10: 3838314697
• ISBN 13: 9783838314693
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 11D millimeters 220 millimeters width by 150 millimeters height by 11 millimeters depth
• Weight: 274 grams

About this title

Synopsis

Obtaining reliable inference procedures is one of the main challenges of econometric research. Test statistics are usually based on applications of the central limit theorem. However, in order to work well the first order asymptotic approximation requires that the asymptotic distribution is an accurate approximation to the finite sample distribution. When dealing with time series models, this is not generally the case. In this book we investigate the small sample performance of various bootstrap based inference procedures when applied to vector autoregressive models. Special attention is given to Johansen’s maximum likelihood method for conducting inference on cointegrated VAR models. Throughout the book, empirical applications are provided to illustrate the bootstrap method and its applications. The analysis should provide some guidance to practitioners in doubt about which inference procedure to use when dealing with cointegrated VAR models.

About the Author

Alessandra Canepa is Lecturer at Brunel University, London. She obtained her PhD in Economics from Southampton University in 2003.