Published May 1994
by Springer .
Written in English
|Contributions||Baldev Raj (Editor)|
|The Physical Object|
|Number of Pages||250|
This text presents modern developments in time series analysis and focuses on their application to economic problems. The book first introduces the fundamental concept of a stationary time series and the basic properties of covariance, investigating the structure and estimation of autoregressive-moving average (ARMA) models and their relations to the covariance by: This text presents modern developments in time series analysis and focuses on their application to economic : Springer International Publishing. Faculty Books; Cowles Library; Cowles Foundation Paper Series; Submission Guidelines. New Developments in Time Series Econometrics. October , Program Chair: Peter C. B. Phillips. SATURDAY: “Econometric Analysis of Evolutionary Time Series. Part of the Studies in Empirical Economics book series (STUDEMP) Abstract. Empirical data in economics are typically non-experimental, especially in finance and macroeconomics where researchers usually rely on time series gathered by official agencies or other investigators. New Developments in Time Series Econometrics: An Overview. In Author: Jean-Marie Dufour, Baldev Raj.
Buy New Developments in Time Series Econometrics by Jean-Marie Dufour, Baldev Raj from Waterstones today! Click and Collect from your local Waterstones . This book contains eleven articles which provide empirical applications as well as theoretical extensions of some of the most exciting recent developments in time-series econometrics. The papers are grouped around three broad themes: (I) the modeling of multivariate times series; (II) the analysis of structural change; (III) seasonality and fractional integration. Since these themes are. This book provides a broad, mature, and systematic introduction to current financial econometric models and their applications to modeling and prediction of financial time series data. It utilizes real-world examples and real financial data throughout the book to apply the models and methods described. Abstract A framework is proposed for interpreting recent developments in time series econometrics, emphasizing the problems of linking economics and statistics.
In this book, the authors reject the theorem-proof approach as much as possible, and emphasize the practical application of econometrics. Readers learn about structural breaks by replicating papers by Perron, Zivot and Andrews. Students and practitioners will find the book useful. Applied Econometric Time Series, 4th Edition demonstrates modern techniques for developing models capable of forecasting, interpreting, and testing hypotheses concerning economic data. In this text, Dr. Walter Enders commits to using a “learn-by-doing” approach to help readers master time-series analysis efficiently and effectively. First is a development based upon the Wold decomposition theorem and the autocorrelations of a time series and second shows how the spectral distribution function of a stationary time series can be derived from the representation of such a process in terms of random variables defined in the frequency domain rather than in the time domain. Bruce Hansen (University of Wisconsin) Time Series Econometrics January 7 / Autoregressive Models Useful for understanding dynamics Illustration: U.S. quarterly real GDP growth rates, post-war GDP t = () + () GDP t 1 + () GDP t 2 () GDP t 3 +be t.