Modelling nonlinear economic relationships

Author(s)

Bibliographic Information

Modelling nonlinear economic relationships

Clive W.J. Granger and Timo Teräsvirta

（Advanced texts in econometrics）

Oxford University Press, c1993

  • : pbk

Available at  / 55 libraries

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Note

Bibliography: p. [168]-179

Includes index

Description and Table of Contents

Description

This volume explains recent theoretical developments in the econometric modelling of relationships between different statistical series. The statistical techniques explored analyse relationships between different variables, over time, such as the relationship between variables in a macroeconomy. Examples from Professor Terasvirta's empirical work are given. Professors Granger and Terasvirta 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 will be of use to econometricians wishing to construct and use models of nonlinear, dynamic, multivariate relationships, such as an 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. Granger and Terasvirta also discuss the division of these nonlinear relationships into parametric and nonparametric models.

Table of Contents

  • Basic concepts
  • general models and tools for analysis
  • nonlinear models in economic theory
  • particular nonlinear multivariate models
  • long memory models
  • linearity testing
  • building nonlinear models
  • forecasting, aggression and non-symmetry
  • applications
  • strategies for nonlinear modelling.

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