A Primer for Unit Root Testing

Author:   K. Patterson
Publisher:   Palgrave USA
ISBN:  

9781403902054


Pages:   277
Publication Date:   17 March 2010
Format:   Paperback
Availability:   In Print   Availability explained
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A Primer for Unit Root Testing


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Overview

An analysis of economic time series is almost impossible without a detailed knowledge of concepts such as non stationarity, integration and unit roots, yet the literature on these topics is immense. This text gives an authoritative overview of the literature providing direction and guidance. It also provides detailed examples to show how the techniques can be applied in practical situations and the pitfalls to avoid.

Full Product Details

Author:   K. Patterson
Publisher:   Palgrave USA
Imprint:   Palgrave Macmillan
Dimensions:   Width: 14.00cm , Height: 1.70cm , Length: 21.60cm
Weight:   0.389kg
ISBN:  

9781403902054


ISBN 10:   1403902054
Pages:   277
Publication Date:   17 March 2010
Audience:   College/higher education ,  Professional and scholarly ,  Professional and scholarly ,  Postgraduate, Research & Scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

Table of Contents

List of Figures Symbols and Abbreviations Preface An Introduction to Probability and Random Variables Time Series Concepts Dependence Convergence An Introduction to Random Walks Brownian motion: Basic Concepts Brownian Motion: Differentiation and Integration Some Examples of Unit root Tests Glossary References

Reviews

'I would like to congratulate you on writing what I consider to be the most accessible and helpful book on the subject of Time Series Analysis.' - Professor Abdul Ghaffar Mughal, Central Asian Academy, Tashkent, Uzbekistan


Author Information

KERRY PATTERSON is Professor of Economics at the University of Reading. His research interests include Time Series Econometrics and Macroeconomics.

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