In collaboration with Payame Noor University and Iranian Geography and Urban Planning Association

Document Type : Research Paper

Authors

1 Professor, Department of Economics, payame Noor University, Tehran, Iran

2 Associate Professor, Department of Economics, Payame Noor University, Tehran, Iran

3 Ph.D. Student in Economics, payame Noor University, Tehran, Iran

10.30473/psp.2024.68877.2693

Abstract

In recent years, researchers have analyzed migration flows using several experimental methods. This research has considered economic factors (per capita GDP, unemployment rate, and poverty intensity) and environmental factors (drought index (CI)) affecting internal migration in 31 provinces of Iran during 2011-2016. The results of descriptive statistics are displayed in the ArcMap software. Moreover, considering that the location dimension has been confirmed in statistical data on internal migration and explanatory variables based on Moran's I test and in spatial models according to rho and lambda statistics, after testing different spatial models, the SEM spatial model was chosen to examine the research model. For this purpose, GeoDa and Stata software were used. The results of the spatial regression of the cross-sectional data showed that the economic indicators of GDP per capita, unemployment, and poverty intensity have a statistically significant effect on net migration in the provinces of the country. Unemployment and poverty have a negative effect, and income (gross domestic product per capita) positively affects net migration in the provinces. These results are consistent with the economic motives proposed in neoclassical theories and relative deprivation theory in internal migration. Additionally, increasing CI (avoidance of drought) as an environmental factor has positively and significantly affected net migration in the provinces. By combining this result with descriptive statistics, it can be stated that migration is one of several potential strategies for households to deal with environmental changes (drought).

Keywords

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