This specific ISBN edition is currently not available.View all copies of this ISBN edition:
This volume explains recent theoretical developments in the econometric modelling of relationships between different statistical series. The statistical techniques explored analyze relationships between different variables over time, such as the relationship between variables in a macroeconomy. Examples from Professor Terasvirta's empirical work are given. The authors are leading exponents of techniques of dynamic, multivariate analysis. They illustrate in this volume exploratory ways of using such techniques to provide models of nonlinear relationships between variables. This is an extension of previous work on linear relationships, and on univariate models. These developments should be of use to econometricians wishing to construct and use models of nonlinear, dynamic, multivariate relationships, such as investment function or a production function. Particular attention is paid to the case of a single dependent variable modelled by a few explanatory variables and the lagged dependent variable in nonlinear form. The book concentrates on stochastic series, since the existence of unexpected shocks strongly suggests that economic variables are stochastic. It also discusses the division of these nonlinear relationships into parametric and nonparametric models.
"synopsis" may belong to another edition of this title.
Clive W. J. Granger is at Centre for Econometric Analysis, California. Timo Terasvirta is at Research Institute of the Finnish Economy.Review:
"A good introductory text on this topic, and should be accessible to graduate students and professional economists, even those with just a basic background in econometrics and time series analysis."--The Southern Economic Journal
"About this title" may belong to another edition of this title.
Book Description Oxford University Press, 1993. Hardcover. Condition: New. Never used!. Seller Inventory # P110198773196