This study uses machine learning (feature selection, particle swarm optimization-PSO, and genetic algorithm-GA) to assess the relative importance of exchange rates for sustainable economic growth in Germany, South Africa, and Slovakia, using Rodrik's model and time-series data (1990-2016). The findings indicate that GDP per capita is most crucial for Germany and South Africa, while the real exchange rate is paramount in Slovakia. This suggests that highly open economies (like Slovakia) should prioritize exchange rate policies, while less open economies should focus on income per capita.
Publisher
Palgrave Communications
Published On
May 05, 2020
Authors
Mehdi Seraj, Pejman Bahramian, Abdulkareem Alhassan, Rasool Dehghanzadeh Shahabad
Tags
exchange rates
sustainable growth
machine learning
GDP per capita
real exchange rate
economic policies
international economics
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