Document Type : Science - Research
Authors
1 1. Professor of Economics, Department of Economics, payame Noor University, Tehran, Iran
2 2. Associate Professor of Economics, Department of Economics, payame Noor University, Tehran, Iran
3 3. Ph.D. Student. in Economics, Department of Economics, payame Noor University, Tehran, Iran
Abstract
Migration, usually refers to permanent or long-term changes in the place of residence. This study aims to investigate the spatial analysis of internal migration in Iranian provinces during 2011-2016 with an emphasis on economic and environmental factors. For this purpose, the economic factors per capita GDP, unemployment rate, poverty severity along with the environmental factor of (CO2) emissions were identified in the regression model. First, location (space and distance) was significant in internal migration data according to the Moran test at 95% level. Then, based on the variance inconsistency test and the rho-correlation statistical in the spatial lag model were confirmed. Therefore, spatial regression analysis was performed based on the spatial lag model. The results of spatial regression showed that the economic indicators per capita GDP, unemployment and poverty severity had a statistically significant effect on the net migration rate in the provinces. Unemployment and poverty severity had a negative effect and income had a positive effect on the net migration rate in the provinces. But CO2 emissions were positively correlated with the dependent variable.As greenhouse gas emissions of CO2 increase, so does air pollution. While one might expect that net migration and CO2 emissions would have a negative relationship, the descriptive statistics of net migration and average CO2 emissions show that, except for Khuzestan province, provinces with high CO2 emissions have also attracted more immigrants.This suggests that the CO2 emission index reflects the positive effects of industrialization in the provinces rather than the negative effects of air pollution.
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