Abstract

Econometric models are often made up of assumptions that never truly match reality. One of the most challenged requirements is that the coefficients of econometric models remain constant over time, in the sense that it is assumed that the future will be similar to the past. If the assumption of constant coefficients is not satisfied, any conclusions reached from normal (constant coefficient) models will be biased. Another, very closely related, contested assumption is that the functional form (usually linear) of a model remains unchanged over time. The theory of linearity has long been the centre of all econometric model-building. According to Teräsvirta (1994), if linear estimates were not successful in practice, they would have been forsaken long ago, and this has certainly not been the case. Quite the opposite has been experienced: some very influential ideas based on the linear relationships between variables, like cointegration analysis, have been established. Nonetheless, there are definite situations in which linear models are unable to grasp the underlying economic theory of the data accurately. This article addresses the problem of non-linearity by applying smooth transition autoregressive (STAR) specifications to an existing simultaneous macroeconomic model of the South African economy. The results support the view that non-linear models provide better forecasts than linear specifications of equations.

Highlights

  • Econometric models are often made up of assumptions that never truly match reality

  • The linear specification was represented by a multivariate ordinary least squares model

  • The non-linear specification was symbolized by combining multivariate ordinary least square specifications as well as smooth transition autoregressive (STAR) specifications

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Summary

Introduction

Econometric models are often made up of assumptions that never truly match reality. One of the most challenged assumptions is that the functional form (usually linear) of a macroeconomic model stays the same over time, in the sense that it is assumed that the future will be similar to the past. If the assumption of linearity is not satisfied, any conclusions obtained from normal (linear) models will be biased. The theory of linearity has long been the centre of all econometric model-building. According to Teräsvirta (1994), if linear estimates were not successful in practice they would have been forsaken long ago, and this has certainly not been the case. There are definite situations in which linear models are unable to grasp the underlying economic theory of the data accurately

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