Seasonality in Regression

Svend Hylleberg, Karl Shell

• Publisher: Academic Press
• Year: 2014
• Print ISBN: 9780123634559
• eBook ISBN: 9781483277745
• Topic: Economics
• Subtopic: Business General
• Index: Economics

Seasonality in Regression presents the problems of seasonality in economic regression models. This book discusses the procedures that may have application in practical econometric work. Organized into eight chapters, this book begins with an overview of the tremendous increase in the computational capabilities made by the development of the electronic computer that has profound implications for the way seasonality is handled by economists. This text then examines some seasonal models and their characteristics. Other chapters consider the most frequently applied evaluation criteria and appraise the values in the applications. This book discusses as well the frequency domain estimators and provides insight into problems of estimating the disturbance–covariance matrix through the use of the disturbance spectrum. The final chapter deals with the main objective of the treatment of personality to formulate and estimate econometric models. This book is a valuable resource for economists and econometricians who have knowledge of econometrics at an advanced undergraduate or graduate level.

Table of contents

• Front Cover
• Seasonality in Regression
• Copyright Page
• Table of Contents
• Preface
• Chapter 1. Introduction and Historical Perspective
• Chapter 2. The Definition of Seasonality
• Chapter 3. Evaluation Criteria for Seasonal Adjustment Procedures
• Chapter 4. The Errors-in-Variables Model
• Chapter 5. The Errors-in-Variables Model: Application of Officially Adjusted Series
• Chapter 6. The Time-Varying Parameter Model
• Chapter 7. The Integrated Econometric Time-Series Procedure
• Chapter 8. Conclusions
• Appendix A: Other Officially Applied Seasonal Adjustment Methods: A Survey
• Appendix B: The Autocovariance Generating Functions of ARMA Models
• Appendix C: A Tool Kit for the Formulation of Univariate and Multivariate Time-Series Models
• Appendix D: A Collection of Time Series Used in the Applications
• References
• Index