The relationship between macroeconomic factors and non-performing loans of commercial bank in Malaysia/ Nur Hidayu Abdul Hakim

• 第一著者: Abdul Hakim, Nur Hidayu
• フォーマット: Student Project
• 言語: English
• 出版事項: 2018
• 主題: Macroeconomics; Bank loans. Bank credit. Commercial loans
• オンライン･アクセス: https://ir.uitm.edu.my/id/eprint/57449/1/57449.pdf; https://ir.uitm.edu.my/id/eprint/57449/

Nowadays, banking industry faced with non-performance issued due to unstable economy conditions. Economic condition associated with non-performing of commercial bank in the words. The changes of economy can influence the banking industry profitability and liquidity management. The profitability and performance of the commercial banks measure by the level of non-performing loans. The increasing of non-performing ratio shows that the bank has problems in provision of loans. This problem always occurred in banking industry when default payments happened. The ability for the bank sectors to provision the loans losses is difficult to do. This is because, the banks fund are insufficient and it difficult to meet liquidity requirement required by Bank Negara Malaysia, which is Statutory Reserved Requirement (SRR). This issue linked with the financial crisis faced by Malaysia on July 1997-1998 toward the economy and it gives wound to the country until now. This study is conduct in order to solve this problem by finding the factors that influence the level of non-performing loans in commercial banks. The sample size of this study will takes place from 2003 to 2016 taken from commercial banks in Malaysia. The study only focuses on seven commercial banks in Malaysia that listed in Bursa Malaysia. The data of this study collect using the secondary data and analysed the data using the statistical tool such as EVIEW. The non-performing loans represent as dependent variable and for the independent variables are Gross Domestic Product (GDP), interest rate on Base Lending Rate (BLR), inflation rate, unemployment rates and exchange rate. The data analyse to determine the relationship between dependent variable and independent variables. This study used the Pooled Ordinary Least Square regression models to find out the relationship between these variables.