Investigating the Nonlinear Effectiveness of Monetary Policy in Iran with the Emergence of Innovative Activities in the Banking Sector
Keywords:
Principal Component Analysis, Information Technology, Banking Sector, Monetary Policy, Innovation EmergenceAbstract
Objective: This study examines how the emergence of banking innovations enhances the nonlinear effectiveness of monetary policy in Iran.
Methodology: This applied, descriptive–analytical study employs panel data from banks listed on the Tehran Stock Exchange over the period 2013–2023. An innovation emergence index was constructed using four indicators: number of bank accounts per capita, number of ATMs per capita, value of internet banking transactions, and value of mobile banking transactions. Principal Component Analysis was applied for dimensionality reduction, followed by estimation of nonlinear relationships using the Panel Smooth Transition Regression model. Stationarity and long-run relationships among variables were evaluated using standard econometric tests.
Findings: The findings indicate a statistically significant nonlinear relationship between banking innovation and monetary policy effectiveness. In the nonlinear regime, higher levels of banking innovation substantially strengthen the effectiveness of monetary policy. Diagnostic tests confirm model robustness, validity, and compliance with classical assumptions, as well as stability of parameters across regimes.
Conclusion: The results demonstrate that technological development in the banking sector is a key driver of monetary policy effectiveness and should be prioritized by monetary authorities as a complementary policy instrument.
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