This volume in the series Advanced Texts in Econometrics explains recent theoretical developments in the econometric modelling of relationships between different statistical series. Clive Granger and Timo Ter�svirta illustrate ways of using dynamic, multivariate analysis techniques to provide models of nonlinear relationships between variables. They pay particular attention to the case of a single dependent variable modelled by a few explanatory variables and the lagged dependent variable in nonlinear form. They also discuss the division of nonlinear relationships into parametric and nonparametric models. The developments detailed in this book will be useful to econometricians who need to construct or use models of nonlinear, dynamic, multivariate relationships, such as an investment or production function.

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.

About the Author

Clive W. J. Granger is at Centre for Econometric Analysis, California. Timo Ter�svirta is at Research Institute of the Finnish Economy.

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