Variable Definitions and Measurement .1 Measures of Loan Portfolio Returns

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3. Research Methodology

3.1 Sample, Types and Sources of Data All Indonesian GBs that operated over the total 2003 to 2011 period of time were included in this research. This period encompasses the post-Asian financial crisis period from 2003 to the commencement of the global financial crisis GFC in 2007 and the post-GFC situation from 2007 onwards. This constitutes a total observation of 270 30 banks for 9 years. One large bank Bank Ekspor Indonesia that only existed for a part of the research period from August 1999 to 1 September 2009 was excluded. This research utilised secondary data from The Indonesian Central Bank Library, and the library of The Indonesian Banking Development Institute LPPI. The central bank library provides individual bank financial statements whereas LPPI provides loan interest income data. All financial data obtained from the central bank and LPPI library were based on audited financial statements provided by individual banks, therefore the data sources are highly creditable. The macroeconomic data were obtained from the Indonesian Financial Statistics accessed from Bank Indonesia website www.bi.go.id. 3.2 Variable Definitions and Measurement 3.2.1 Measures of Loan Portfolio Returns To measure the loan portfolio returns, the ratio of loan interest income to average total loans is used in this research since in the broader sense it reflects the comparative pricing applied by banks. The gross loan interest income to total loans, after loan repayment defaults, constitutes the actual achieved returns. The loan portfolio return of GBs serves as the dependent variable. 3.2.2 Measures of Bank- Specific Characteristics The independent variables representing bank-specific characteristics used in this study are: bank size, bank equity percentage, bank liquidity percentage and the loan repayment default risk. These four variables are used since they are considered as the determinants of bank performance according to literature Pasiouras and Kosmidou, 2007, Athanasoglou et al., 2008, Sufian, 2011. This research uses the natural logarithm of bank total assets as measure of size. It captures the economy of scale effect on loan portfolio returns that may result from larger loan portfolios. Bank equity percentage is measured by ratio of Total Equity to Total Assets whereas liquidity percentage is measured by the ratio of Total Loans to Total Deposits. The level of bank equity serves as indicator of the deposit safety of banks and also the ability of banks to comply with loan commitments. The liquidity ratio reflects the relative focus of banks on lending versus more liquid investments like securities. Loan portfolio repayment default risk is measured by ratio of Non-Performing Loans NPLs to Total Loans. It differs from previous research by Athanasoglou et al. 2008, Sufian 2011, and Dietrich and Wanzenried 2011 where the ratio of Loan Loss Provisions to Total Loans is used as the measure of credit risk. Loan Loss Provision 1 is subject to regulation and bank manager subjectivity. NPL gives a good proxy for the level of loan portfolio risk exposure as it serves as actual measure of the total ”non-complied” counterparty transaction value. Within this context it represents more overall comparable non-adjusted credit risk risk data that improves on the Loan Loss Provision credit risk measure used in previous studies. 95 According to Cronje 2013 loan portfolio risks are classified into two broad categories namely intrinsic- and concentration risk. Within the context of this study intrinsic risk refers to the risk inherent to each sector, and each loan type of a bank. It cannot be measured in this study since comparative risk information like loan defaults for each sector and each loan type is not available. Only loan repayment default information, provided in the form of non- performing loans for the total loan portfolio is available for individual banks and is used as proxy of overall bank loan portfolio risk. 3.2.3 Measures of Macroeconomic Variables Interest rate and Gross Domestic Product GDP growth serve as the macroeconomic variables. These macroeconomic variables represent the external environment that might affect the lending performance of banks. Appendix 3 reflects all the variables, their definitions and how they are measured. 3.3 Hypothesis It is hypothesized that bank-specific characteristics affect the loan portfolio returns as part of overall bank profit in view of the impact of bank-specific characteristics bank sizes, equity, liquidity and risk on bank profitability that various researchers have identified. 3.4 Data Analysis All research data is numerical, therefore quantitative data analysis is conducted. Firstly, descriptive statistics of the variables means and standard deviations were calculated to determine data tendency and deviations. Secondly, to determine the impact of bank-specific characteristics size, equity and liquidity and risk on portfolio returns, the following panel data regression equation is used: ……………………..3.1 = loan portfolio returns for government-owned bank i in year t = bank size for government-owned bank i in year t = bank equity ratio for government-owned bank i in year t = bank liquidity ratio for government-owned bank i in year t = loan portfolio default payment risk for bank i at year t = macroeconomic variables , = regression coefficients; and = the disturbance term. This research employs fixed effects panel data regression. The selection of the fixed effects model instead of the random effects model is based on the Hausman test. The test checks a more efficient model against a less efficient but consistent model to make sure that the more efficient model also gives consistent results. A correct robust setting has been applied in the regression.

3.5 Limitations of this Research