THE INFLUENCE OF BANK SPECIFIC VARIABLES AND MACROECONOMIC FACTORS ON CAPITAL ADEQUACY RATIO (CAR) IN 19 COMMERCIAL BANKS IN INDONESIA (CASE STUDY: PERIOD 2008-2014)

• Main Author: Nugroho Addo Wibowo, Hubertus
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/72353
• Institution: Institut Teknologi Bandung

To create a healthy banking system, and also to have the ability to compete globally, banks are required to prepare a certain amount of capital, measured by Capital Adequacy Ratio (CAR), to ensure that banks can handle risk exposures. The regulation regarding minimum capital requirement is designed to ensure that banks maintain sufficient capital for the risks they have. By doing this, the government has lower the risk of a bank going default, thus creating more stable economy and building trust over banking industry in individuals and business entities. The significance of capital adequacy on banking industry calls for more in-depth research about the factors that determines CAR. This research aims to explain the significances and relationships of several bank specific variables: Bank’s Size (LNSIZE), Less Risky Liquid Assets to Total Assets (LRLA), Risky Liquid Assets to Total Assets (RLATA), External Funding Ratio (EFR), Non-Performing Loan Ratio (NPLR), Operating Expenses to Operating Income (OEOI), Return on Assets (ROA), and Return on Equity (ROE), and two macroeconomic factors: Rupiah Exchange Rate (EXCR) and BI Rate (BIRATE), towards the dependent variable, Capital Adequacy Ratio (CAR) in 19 commercial banks (BUKU III and BUKU IV) in Indonesia, in the period of 2008 to 2014. This research uses Generalized Least Square (random effect) method to produce the regression estimation output. Classical Linear Regression Assumption test is also done prior to the regression analysis. The result of this research shows that LRLA, RLATA, and ROA have significant positive effect toward CAR. LNSIZE, OEOI, ROE, and BIRATE in the other hand, have significant negative effect toward CAR. The other variables: EFR, NPLR, and EXCR have insignificant effect toward CAR. ROA is the independent variable that has largest positive coefficient in this regression model (3.786602), while ROE has the largest negative coefficient in this regression model (-0.508370). The regression model proposed in this research explains 48.7% of CAR (Rsquared = 0.486953).