The impact of bank credit uptake on income inequality in inflationary periods: The case of Türki̇ye

Abstract

This study analyzes the impact of regional credit utilization on income inequality during inflationary periods, using NUTS-2-level macroeconomic, financial, social welfare, and income distribution indicators for Türkiye covering the period 2014–2023. The study consists of two phases. In the first phase, I estimate a heterogeneous-effects pooled OLS model to examine whether the effect of inflation on income inequality varies across regions, and the results provide evidence of regional heterogeneity. In the second phase, I estimate panel fixed-effects models with interaction terms to examine how regional credit use relates to income inequality across pre-shock and post-shock periods, using 2020 as the reference year. I include credit-type shares and total deposits (as a percentage of GDP) and their interactions with the post-shock dummy. To illustrate different aspects of income inequality, I used the Gini coefficient, the P80/P20 ratio, and the total income shares received by different income groups as dependent variables; economic growth, the share of the trade deficit in GDP, years of education, population, and unemployment served as control variables. In continuation of the second part, I estimated dynamic models using the System GMM method by adding lags to the models established with the panel fixed effects method, and I compared the outputs obtained from the two methods. As for the results, both methods suggest that institutional credit usage increased income inequality in the post-shock period by increasing the share of the upper income group and decreasing the share of the middle-income group. On the other hand, the fact that the impact of personal financing loan and consumer credit card usage in the post-shock period was not found in the estimated outputs using the panel fixed effects method but was significant with the System GMM indicates that the credit variables are more suitable for a dynamic structure, thus supporting the use of the System GMM. While personal financing loans, similar to institutional loans, supported the upper class in the post-shock period, increasing the Gini and P80/P20 ratios (and thus income inequality), the effect of personal credit cards was the opposite. The fact that credit card usage, also in normal times, statistically significantly but inversely favored the upper income group demonstrates the modifying effect of the inflation shock. These findings are noteworthy because they show that the negative impacts of inflationary policies on income distribution can be mitigated through selective credit incentives.