Non-linearities in inflation-growth nexus in the SADC region : a panel smooth transition regression approach

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Authors

Seleteng, Monaheng
Bittencourt, Manoel
Van Eyden, Renee

Journal Title

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Volume Title

Publisher

Elsevier

Abstract

The main objective of central banks around the world is the achievement and maintenance of price stability, which actually creates an environment conducive for faster economic growth. Therefore, it is important for policy makers to understand the relationship between inflation and economic growth in order to make sound policies. If inflation is detrimental to economic growth, then policy makers should aim for low rates of inflation. This leads to a question; how low should the inflation rate be? Previous research in the non-linearities of the inflation–growth relationship has found that a positive relationship exists when the inflation rate is low and a negative relationship when the inflation rate is high. This implies the existence of a threshold level of inflation at which the sign switches. In this paper we use panel data for the period 1980– 2008 to examine the inflation–growth nexus in the Southern African Development Community (SADC) region and to endogenously determine the threshold level of inflation. To deal with problems of endogeneity and heterogeneity, the paper uses the Panel Smooth Transition Regression (PSTR) method developed by González et al. (2005) to examine the non-linearities in the inflation–growth nexus. This technique further estimates the smoothness of the transition from a low inflation to a high inflation regime. The findings reveal a threshold level of 18.9%, above which inflation is detrimental to economic growth in the SADC region.

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Keywords

Economic growth, Inflation, Threshold level, Non-linearities, PSTR model, Southern African Development Community (SADC), Panel Smooth Transition Regression (PSTR)

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Citation

Seleteng, M., Bittencourt, M & Van Eyden, R 2013, 'Non-linearities in inflation-growth nexus in the SADC region : a panel smooth transition regression approach', Economic Modelling, vol. 30, pp. 149-156.