Authors
Abstract
Globalization, the process of considerable increase in international trade, global exchanges and markets’ integration as a fundamental characteristic, are emerging inevitably. Investigating the way in which this process affects economic variables, can be a guidance of decision making for policy makers. Considering structural economic differences between urban and rural societies in Iran and using 1350-1386 Iran’s economy dataset, first we compared the efficiency of VAR and VEC models with artificial neural network (ANN) approach in forecasting measure of income distribution inequality of urban societies and finally the best model (ANN) has used as an out-of-sample forecasting tool in different designed scenarios from 1387 to 1395. Choosing ANN model, decrease in urban societies’ income inequality during globalization process, is the main result.
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