Determining Impacts on Non-Performing Loan Ratio in Romania

• Published in: Review of International Comparative Management Vol. 20; no. 2; pp. 155 - 170
• Main Authors: Ciurel, Adriana-Daniela, Stoica, Tiberiu
• Format: Journal Article
• Language: English
• Published: Bucharest EDITURA ASE 01.05.2020; ASE Publishing House; Revista de Management Comparat International
• Subjects: Banking; Credit risk; Dependent variables; Economic conditions; Economic models; Economic policy; Economic statistics; Equilibrium; Error correction & detection; Financial institutions; Financial Markets; Forecasting; GDP; Gross Domestic Product; Housing prices; Interest rates; International finance; Loans; Macroeconomics; Monetary policy; National banks; Nonperforming loans; Political economy; Studies; Unemployment; Variables; Romania; interest rate; VEC; credit risk; cointegration; nonperforming loans
• ISSN: 1582-3458; 2601-0968
• DOI: 10.24818/RMCI.2019.2.155

This paper aims to investigate some of the determinants of non-performing loans in the Romanian banking sector by means of Vector Error Correction (VEC). The increase in non-performing loans is the most relevant factor that financial institutions face in order to maintain an adequate level of solvency in the context of current economic decline. The objectives of the study presented in this document are to estimate and understand the historical relationships between various macroeconomic factors and the evolution of non-performing loans, in order to facilitate the prediction of future non-performing loans based on macroeconomic forecasts.The conclusions obtained should be taken as guidelines and be the starting point for a reflection that helps to define next steps in the methodological development of planning models as well as in other aspects detailed in the diversification sections and credit management policies. This paper presents in the first place an executive summary of the main conclusions of the study, as well as a reference to the origin of the data used and the methodology applied. In the development of the model, we use public data from the National Bank of Romania, World Bank and the National Institute.