Investigating Credit Risk Assessment Using Indicators Affecting the Relationship between Financial Development and Economic Growth - Markov Switching Approach

Currently, due to economic fluctuations in Iran, the investment return of banks in Iran has undergone a major transformation. One of the major challenges facing bank investors is effectively allocating their money to projects and accurately assessing credit risk. Various factors affect the credit risk of banks. In this paper, the effective variables on credit risk estimation are examined and then the effect of credit risk on investment return performance is determined. For this purpose, three hypotheses were determined and the annual data of the member companies of the Tehran Stock Exchange in the period 2001-2021 were used to test the hypothesis. The study method has two stages, so that in the first stage, the Markov switching method is used to select variables affecting credit risk and for this purpose, the relationship between important indicators such as financial development and economic growth. Then, in the second stage, the important and effective variables selected in the first stage are used to estimate the credit risk and its impact on investment returns. Findings from the study showed that variables such as interest rate, inflation, ratio of domestic credit to private sector and exchange rate have a significant and positive effect on credit risk and variables such as foreign direct investment and annual real GDP growth have negative and significant effect on credit risk and credit risk has a negative and significant effect on investment returns.