Associate Professor, Economics Department, University of Isfahan, Iran
Ph.D candidate of economics, Alzahra University of Tehran, Iran
One of the most important applications of economic growth models is for regional economic growth. In regional growth studies, it is necessary to consider spatial effects because of spatial dependence among the growth rates of regions. This research investigates the impact between net migration and its spatial lag on regional growth, based on the neoclassical (Solow) growth model. The used model in the study is the Dynamic Panel Data (DPD) which has been specified as a Spatial Durbin Model (SDM) and estimated by the spatial generalized method of moments (SGMM). The specified model has been tested for the 30 provinces of Iran in the period of 2006-16. The estimated results show that the time-lagged dependent variable had a positive and highly significant effect on income per capita. The impact of initial income per capita on growth is negative, and the convergence hypothesis is thus accepted. That is, poor provinces grow faster than the rich. The income per capita and growth are positively related to net migration rate. Expectedly, the new coming people to a province would increase income per capita and growth. The estimated coefficient of the spatial lag of the dependent variable is statistically significant and demonstrates spatial dependence in income as well as economic growth among the provinces of Iran. Every province’s growth rate was positively impacted by the economic growth of its neighbors. However, net migration has no spatial effect on income per capita and growth. In other words, the regional economic growth has not been influenced by migration to neighboring provinces.
Keywords: Neoclassical growth model, convergence, migration, spatial Durbin model, spatial generalized method of moments.
JEL classification: O47, C23, R23