Abstract

The undesirable effect of poor exchange rate policy on economic growth has been firmly established in the literature using various parametric methods of econometric techniques. However, less is known about the prioritization of the exchange rate as a determinant of economic growth using a nonparametric approach. Thus, this study introduced machining learning approach (feature selection, particle swarm optimization—PSO, and genetic algorithm—GA techniques) to evaluate the relative primacy of the exchange rate for sustainable economic growth in Germany, South Africa, and Slovakia using Rodrik model with time series data from 1990 to 2016. The study reveals that GDP per capita is the most crucial variable for economic growth in Germany and South Africa whereas, in Slovakia, the real exchange rate takes precedence over all other determinants of economic growth. That is, exchange rate takes precedence over other factors as a determinant of economic growth in an economy (Slovakia) with the high rate of trade openness while income per capita is the most important determinant of economic growth in economies (Germany and South Africa) with a relatively lower rate of trade openness. This partly supports Rodrik’s conclusion. We, therefore, recommend that highly opened economies should focus on viable exchange rate policies, such as undervaluation of currency to enhance sustained economic growth. On the other hand, relatively less open economies should focus on policies that improve income per capita rather than exchange rate policies.

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