Fr. 179.00

Unit Root Tests in Time Series - Extensions and Developments

English · Hardback

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Informationen zum Autor KERRY PATTERSON 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 , 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 . Klappentext 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. Zusammenfassung 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. Inhaltsverzeichnis 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

List 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

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