Synopses & Reviews
This volume expands and develops the analyses and concepts put forward in Unit Root Tests in Time Series: Volume One, providing a comprehensive and clear way into the techniques of unit root testing. Patterson provides an awareness of the pitfalls and extensions to nonstandard cases, giving guidance to the practitioner and enabling the reader to understand the complex theoretical aspects of unit root tests.
Crucial issues such as Nonstationarity caused by a unit root are discussed, and explanation is combined with examples, showing theory at work with real economic issues such as the prices of assets and measures of economic activity.
Review
Synopsis
Testing for a unit root is now an essential part of time series analysis. Thisvolume provides a critical overview and assessment of tests for a unit root in time series, developing the concepts necessary to understand the key theoretical and practical models in unit root testing.
Synopsis
Testing for a Unit Root is now an essential part of time series analysis but the literature on the topic is so large that knowing where to start is difficult even for the specialist. This book provides a way into the techniques of unit root testing, explaining the pitfalls and nonstandard cases, using practical examples and simulation analysis.
About the Author
KERRY PATTERSON is professor of Econometrics at the University of Reading, UK. He has established an international reputation in Econometrics and has published over 50 articles in leading journals, including the Journal of the Royal Statistical Society, the Review of Economics and Statistics, and the Economic Journal and the International Journal of Forecasting. He is co-editor, with Terence Mills, of the Palgrave Handbook of Econometrics, Volumes 1 and 2, author of Unit Root Tests in Time Series, Volume 1, and author of A Primer for Unit Root Testing.
Table of Contents
Introduction
Functional Form and Nonparametric Tests for a Unit Root
Fractional Integration
Semi-parametric Estimation of the Long Memory Parameter
Smooth Transition Nonlinear Models
Threshold Autoregressions
Structural Breaks in AR Models
Structural Breaks with Unknown Break Dates
Conditional Heteroscedasticity and Unit Root Tests