Elements of Time Series Econometrics

An Applied Approach

Evzen Kocenda and Alexander Cerný

Evzen Kocenda and Alexander Cerný

Distributed for Karolinum Press, Charles University

228 pages | 6 x 8
Paper $15.00 ISBN: 9788024613703 Published October 2007 Not for sale in the Czech Republic and the Slovak Republic

This book presents the numerous tools for the econometric analysis of time series. The text is designed with emphasis on the practical application of theoretical tools. Accordingly, material is presented in a way that is easy to understand. In many cases, intuitive explanation and understanding of the studied phenomena are offered. Essential concepts are illustrated by clear-cut examples. The attention of readers is drawn to numerous applied works where the use of specific techniques is best illustrated. Such applications are chiefly connected with issues of recent economic transition and European integration. The outlined style of presentation makes the book also a rich source of references.

 

The text is divided into four major sections. The first section, "The Nature of Time Series," gives an introduction to time series analysis. The second section, "Difference Equations," describes briefly the theory of difference equations, with an emphasis on results that are important for time series econometrics. The third section, "Univariate Time Series," presents the methods commonly used in univariate time series analysis, the analysis of time series of one single variable. The fourth section, "Multiple Time Series," deals with time series models of multiple interrelated variables. Appendices contain an introduction to simulation techniques and statistical tables.

Contents

INTRODUCTION

 

1.THE NATURE OF TIME SERIES

1.1 Description of Time Series

1.2 White Noise

1.3 Stationarity

1.4 Transformations of Time Series

1.5 Trend, Seasonal, and Irregular Patterns

1.6 ARMA Models of Time Series

1.7 Stylized Facts about Time Series

 

2. DIFFERENCE EQUATIONS

2.1 Linear Difference Equations

2.2 Lag Operator

2.3 The Solution of Difference Equations

2.4 Stability Conditions

2.5 Stability and Stationarity

 

3. UNIVARIATETIME SERIES

3.1 Estimation of an ARMA Model

3.2 Trend in Time Series

3.3 Seasonality in Time Series

3.4 Unit Roots.

3.5 Unit Roots and Structural Change

3.6 Detecting a Structural Change

3.7 Conditional Heteroskedasticity and Non-Linear Structure

 

4. MULTIPLETIME SERIES

4.1 VAR Models

4.2 Granger Causality

4.3 Cointegration and Error Correction Models

4.4 Unit Root Tests in Panel Data

 

REFERENCES

 

APPENDIX A: MONTE CARLO SIMULATIONS

 

APPENDIX B: STATISTICAL TABLES

 

INDEX

For more information, or to order this book, please visit http://www.press.uchicago.edu
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