Original Research

A macroeconomic model for South Africa: A non-linear econometric modelling approach

Marinda Pretorius, Ilse Botha
Journal of Economic and Financial Sciences | Vol 1, No 1 | a379 | DOI: https://doi.org/10.4102/jef.v1i1.379 | © 2018 Marinda Pretorius, Ilse Botha | This work is licensed under CC Attribution 4.0
Submitted: 02 July 2018 | Published: 30 April 2007

About the author(s)

Marinda Pretorius, University of Johannesburg, South Africa
Ilse Botha, University of Johannesburg, South Africa

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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.

Keywords

Non-linearity; emerging market; STAR; constant coefficients; linear specifications

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