An Econometric Analysis Regarding the Path of Non Performing Loans-A Panel Data Analysis from Mauritian Banks and Implications for the Banking Industry

Abstract

The present study pertains to unravelling the internal (bank specific) and external (macroeconomic) determinants of nonperforming loans in Mauritius using annual report data from a panel of 10 existing banks and macroeconomic data for the period 2000 to 2012. The model used in the present instance comprises of a vector of bank specific and macro economic variables which include the inflation rate, lending interest rates, growth of the construction sector and tourism sector as well as global variables such as the Euro zone’s GDP growth. The model is tested both in a static and dynamic framework. Four estimation techniques are considered, viz Fixed Effects, differenced GMM, System GMM and Random coefficient estimation. The results indicate that, notwithstanding there are many significant factors influencing NPL, the most critical elements nevertheless remain declines in the construction sector and the rise in cross border loans. Interestingly, the study provides important policy insights which centres on the improvement of credit concentration guidelines as well as the modification of the MCIB reporting.

Nexus between financial innovations, remittances and credit performance: Evidence from augmented ARDL and nonlinear ARDL

“…In addition, macroeconomic and bank-specific variables affect non-performing loans (Anjom & Karim, 2016;Md Qamruzzaman et al, 2020). As external economic factors are uncontrollable and affect the overall performance of financial institutions, compared to the bank-specific factors, NPLs react most by the macroeconomic factors (Kjosevski & Petkovski, 2017;Klein, 2013; D. P. Louzis, et al, 2012;Polodoo et al, 2015), while opposite conclusions were made by Amuakwa-Mensah and Boakye-Adjei (2015), Dimitrios et al (2016), Haniifah (2015), and Rifat (2016).…”

Strategi Pengelolaan Non Performing Loan (Npl) Bank Umum Yang Go Public

“…Semakin besar kredit yang disalurkan maka dapat berdampak pada meningkatnya kredit bermasalah (Jayanti & Haryanto, 2013). Besarnya aktiva atau asset yang dimiliki suatu bank menunjukan volume kredit yang dapat disalurkan oleh bank tersebut, ukuran bank yang diproksikan total aset berpengaruh negatif terhadap NPL (Diyanti & Widyarti, 2012;Abedalfattah & Faris, 2013;Polodoo et al, 2015). Berdasarkan uraian diatas maka dapat disusun hipotesis berikut: H 2 : Total aset berpengaruh signifikan terhadap non performing loan…”

Determinants of Credit Infections: Evidence from Banking Sector in an Emerging Economy

“…This is because of the prevalent uncertainty in the economic and political environment, which could adversely affect performance of businesses and force them to default on their obligations. This view is supported by Polodoo et al (2015) who find this to be a significant variable in explaining the occurrence of NPLs. This study expects a positive relationship between the NPLs and lagged total loans.…”

“…However, other studies find a positive association between bank size and NPLs. Polodoo et al (2015) and Rajan and Dhal (2003) suggest an increase in bad loans as the size of the bank increases due to complexity and the volume of their advances. This hypothesis suggests that large banks tend to be more lenient in extending credit and taking on more risk in their portfolio.…”

“…The determinants of NPLs have been explored quite extensively for banking systems around the world. Polodoo et al (2015) conducted a study on the ten banks in Mauritius from 2000-2012 to determine the main factors impacting NPLs. They used both bank-specific and macroeconomic determinants for analysis.…”