The role of financial development in poverty reduction in Iran using the Principal Component Analysis Method (PCA)

The purpose of this paper is to explain the relationship between financial development and poverty in Iran. Considering the existence of different indicators in the financial development literature, in order to introduce a combination of the variables for financial development, the Principal component analysis (PCA) method was used. This method takes into account most of the dimensions of financial development to construct a composite index. The Poverty Index (SST) was also used as a poverty indicator. In order to test the relationship between the variables, the Autoregressive Distributed Lag model (ARDL) was used. After the second-rate financial development index was introduced, the non-linear effects of the relationship between financial development and poverty were evaluated for the period of 1395-1368. The results indicated that the financial development variable had a negative and significant effect on poverty. In other words, improving the financial situation would lead to poverty reduction in the society. The coefficient of the second power index was negative and significant, indicating that there is a reverse U relation in the case of the financial development and poverty in Iran.