Co-integration, error correction, and the econometric analysis of non-stationary data
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|Banerjee A., et al.|
Описание:This book is wide-ranging in its account of literature on cointegration and the modelling of integrated processes (those which accumulate the effects of past shocks). Data series which display integrated behavior are common in economics, although techniques appropriate to analyzing such data are relatively new, with few existing expositions of the literature. This book explores relationships among integrated data series and their use in dynamic econometric modelling. The concepts of cointegration and error-correction models are fundamental components of the modelling strategy. This area of time series econometrics has grown in importance over the past decade and is of interest to both econometric theorists and applied econometricians. By explaining the important concepts informally and presenting them formally, the book bridges the gap between purely descriptive and purely theoretical accounts of the literature. The work describes the asymptotic theory of integrated processes and uses the tools provided by this theory to develop the distributions of estimators and test statistics. It emphasizes practical modelling advice and the use of techniques for systems estimation. A knowledge of econometrics, statistics, and matrix algebra at the level of a final-year undergraduate or first-year undergraduate course in econometrics is sufficient for most of the book. Other mathematical tools are described as they occur.
About the Series
Advanced Texts in Econometrics is a distinguished and rapidly expanding series in which leading econometricians assess recent developments in such areas as stochastic probability, panel and time series data analysis, modeling, and cointegration. In both hardback and affordable paperback, each volume explains the nature and applicability of a topic in greater depth than possible in introductory textbooks or single journal articles. Each definitive work is formatted to be as accessible and convenient for those who are not familiar with the detailed primary literature.