Applied Econometric Times Series (Wiley Series in Probability and Statistics) - Hardcover

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About the Author: Walter Enders is Professor and Lee Bidgood Chair of Economics and Finance at the University of Alabama. He received his doctorate in economics from Columbia University. His current research focuses on the development and application of time-series models to areas in economics and finance, including documenting the cyclic and shifting nature of terrorist attacks in response to defensive counteractions. Dr. Enders has published numerous research articles in such journals as the Review of Economics and Statistics, Quarterly Journal of Economics, and the Journal of International Economics. He has also published articles in the American Economic Review, the Journal of Business and Economic Statistics, and the American Political Science Review.

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Accessible & Modern Techniques for Time-Series Analysis

Assuming only a basic understanding of multiple regression analysis, this classic introduction to time-series analysis shows how to develop models capable of forecasting, interpreting, and testing hypotheses concerning economic data using modern techniques. Numerous real-world examples from fields ranging from agricultural economics to transnational terrorism further illustrate the various techniques.

This new edition reflects both sound structure and recent advances in time-series econometrics, such as out-of-sample forecasting techniques, nonlinear time-series models, Monte Carlo analysis, and bootstrapping.

Features:

• New discussion of parameter instability and structural breaks including tests for endogenous breaks.
• New coverage of developments in cointegration tests and in unit root tests.
• Improved discussions on out-of-sample forecasting methods and multivariate GARCH models.
• Numerous illustrations of key concepts and detailed example using real-world data.
• Step-by-step approach to time-series estimation.
• Additional questions and empirical exercises that enable students to practice the techniques covered in the test. Data sets are available on the text s companion Web site.
• Emphasizes difference equations as the foundation of all time-series models.