The Impact of Private Sector Credit on Self-Employment in Iran: A Hybrid Approach of Artificial Intelligence with Spatial Model

Self-employment plays an important role in the iranian economy and understanding the factors that influence it is of great importance. the aim of this study was to investigate the repercussions of private sector credit on self-employment in iran. artificial intelligence techniques such as artificial neural networks, deep neural networks and machine learning algorithms were used to identify non- linear relationships and complex patterns in the data. spatial econometric models such as sar, sem and sdm were also used to account for spatial dependencies between provinces and to examine the spatial spillover effects of utilization for the period 1990-2023 at the provincial level of the country. the results indicate a negative and significant relationship between the ratio of microfinance to gross domestic product (gdp) and the self-employment rate. the negative coefficients of economic openness index and capital formation rate also indicate their negative impact on self-employment. in contrast, the total factor productivity and education expenditure variables have a positive and significant effect on the self-employment rate. the results of the spatial models also show the interdependence of the self-employment rate in the different regions of the country. although microfinance was expected to increase self-employment, this study found a negative relationship between the two, which could be due to inefficiencies in the provision of microfinance and its insufficient focus on the creation of sustainable and productive jobs. greater economic openness and higher capital formation rates also have a negative impact on self-employment, as they increase foreign competition and encourage investment in larger sectors of the economy. on the flip side, improvements in total factor productivity and investment in education form the basis for the growth of self-employment. the results of the spatial models also underline the importance of considering spatial spillover effects and dependencies when formulating measures to promote employment and entrepreneurship.