Purpose: This paper explores the most important determinants of friction in the Tunisian credit market. The previous literature argued that friction is largely explained by the increase in Non-Performing Loans Nkusu, 2011; Abadi et al. 2014; Rulyasri et al.2017, Roland et all, 2013. Research methodology: We constructed a multivariate Vector Error Correction Model, with five macroeconomic variables (industrial production index, the money supply, money market interest rate) to examine the impact of Non-Performing Loans increase in amplifying the Tunisian credit frictions. Results: The Vector Error Correction Model (VECM) regression results show a negative and important relationship between economic growth and Non-Performing Loans (NPL) ratio, which is very robust during the political crisis of 2011. The money market interest rate and the money supply are positively related to the Non-Performing loan ratio. Limitation: This study was only focused on Tunisian banking sector as one of the pillars of the Tunisian economy. Contributions: This highlights that the nature of the monetary policy adopted by the monetary authority of Tunisia plays a significant role in the fluctuation of the Non-Performing Loans ratio. Bank capitalization is positively and statistically significant with Non-Performing Loan ratio, implying that banks with a low level of capital are more likely to have a riskier credit portfolio that causes the increase of Non-Performing Loans in their balance sheet.
Since the last financial crisis, the financial system has taken and continues to be on guard against these unexpected shocks. In this direction, this article focused with these decision-makers as well as his researchers on a more advanced macroeconomic modeling, based on the integration of different hazards (economic, social, cultural, environmental…), the concept of micro-foundations, of the different types of imperfect competition accompanied by some price rigidities. We are proposing a new Dynamic Stochastic General Equilibrium (DSGE) model tailored to the banking sector in Tunisia. Our model captures the role played by prudential regulations in correcting fluctuations in the business cycle and restoring macroeconomic and financial stability.
This survey presented the various ways that are utilized in the literature to include financial market frictions in dynamic stochastic general equilibrium (DSGE) models. It focuses on the fundamental issue: to what extent the Taylor rules are optimal when the central bank introduces the goal of financial stability. Indeed, the latest financial crisis shows that the vulnerability of the credit cycle is considered the main source for the amplification of a small transitory shock. This conclusion changed the instrument that drives the transmission of monetary policy through the economy and pushed the policymakers to include financial stability as a second objective of the central bank.
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