analyzing the nonlinear relationship between financial development and economic growth in iran: a combined approach using principal component analysis and copula models

The connection between financial development and economic growth remains a highly discussed and critical issue in economic research. this study examines iran's economy from 1990 to 2023 by developing a composite financial development index, which incorporates metrics such as the ratio of private sector credit and broad money supply (m2) to gross domestic product (gdp). principal component analysis (pca) was employed to create the composite index, and copula modeling was utilized to examine nonlinear relationships among variables. furthermore, kendall, spearman, and pearson correlation coefficients were computed to evaluate the strength and nature of these relationships. the findings suggest no robust or statistically significant link between financial development and economic growth in iran. the results, derived from an innovative integration of pca and copula modeling over the 1990–2023 period, highlight a lack of structural interdependence between financial development and economic growth in iran. this study stands out from previous work due to its emphasis on nonlinear relationships and iran's distinctive bank-centric financial system under economic sanctions. the analysis suggests that financial resources, primarily allocated to non-productive sectors, have not made a significant contribution to economic growth. to address this, targeted reforms in the banking sector are recommended to improve credit allocation to productive industries and enhance regulatory oversight to curb the inflationary impact of liquidity expansion, aligning with the study's findings of structural inefficiencies.