The impact of macroeconomic and bank-specific factors toward non-performing loan: evidence from Indonesian public banks
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DOIhttp://dx.doi.org/10.21511/bbs.12(1).2017.08
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Article InfoVolume 12 2017, Issue #1, pp. 67-74
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The present study focuses on the need for banking sector to be more reactive when facing globalization that could bring impact on banking industries complexity. Based on empirical studies, there is a need to analyze non performing loan determinants comprehensively using macroeconomic and bank-specific factors to make a good condition on bank, because combining macroeconomic and bank-specific variable as NPL determinants has made a big improvement to analyze NPL. The object of present study is 20 Banks listed in Indonesia Stock Exchange (IDX) between q12005-q42014. Using dynamic panel data GMM-system method shows that the previous period of NPL (non performing loan), change of PDB (Gross Domestic Product) and inflation rate have a significantly negative impact on NPL. However, BOPO (Operations Expenses to Operations Income) and ROE (Return on Equity) has a significantly positve relationship to NPL. On the other hand, this research does not find any significance on BI rate (interest rate), solvency ratio, and size to NPL. From the result, it can be concluded that combining macroeconomic and bank-specific variable could be an alternative method to analyze NPL determinants on bank.
Keywords: nonperforming loans, banks, credit risk, globalization, dynamic panel data, banking industries.
JEL Classification: G21, E44, E51, E5, F60
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References24
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Tables3
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Figures0
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- Table 1. Descriptive statistic
- Table 2. Sample of Bank
- Table 3. Result discussion
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- Abid, Lobna, Med, Nejib Ouertani and Zouari-Ghorbel, Sonia. (2014). Macroeconomic and Bank-Spesific Determinants of Household’s Non-Performing Loans in Tunisia; a Dynamic Panel Data, Procedia Economics and Finance, 13, pp. 58-68.
- Arellano, Manuel and Bond, Stephen. (1991). Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations, Review of Economic Studies, 58, pp. 277-297.
- Arellano, Manuel and Bover, Olympia. (1995). Another look at the instrumental variable estimation of error-component models, Journal of Econometrics, 68, pp. 29-51.
- Berge, Tor Oddvar and Boye, Katrine Godding. (2007). An Analysis of Bank’s Problem Loans, Norges Bank Economic Bulletin, 78, pp. 65-76.
- Berger, Allen and DeYoung, Robert. (1997). Problem loans and cost efficiency in commercial banks, Journal of Banking and Finance, 21, pp. 849-870.
- Blundell, Richard and Bond, Stephen. (1998). Initial conditions and moment conditions in dynamic panel data models, Journal of Econometrics, 87, pp. 115-143.
- Bobba, Matteo and Coviello, Decio. (2007). Weak instruments and weak identification, inestimating the impacts of education, on democracy, Economics Letters, 96, pp. 301-306.
- Endut, Roziela, Nurul, Syuhada, Fathiah, Ismail, and Mahmood, Wan Mansor W. (2013). Macroeconomic Implications on Non-Performing Loans in Asian Pacific Region, World Applied Sciences Journal 23 Enhancing Emerging Market Competitiveness in the Global Economy, pp. 57-60.
- Febrianti, dan Khusnul Ashar, Silvia Eka. (2015). Analisis Pengaruh Pertumbuhan PDB, Inflasi, BI Rate, dan Nilai Tukar Terhadap Kredit Bermasalah pada Bank Konvensional dan Bank Syariah, Jurnal Ilmilah Mahasiswa Fakultas Ekonomi Bisnis Universitas Brawijaya, Vol. 3, No. 2
- Judson, Ruth A. and Owen, Ann L. (1999). Estimating dynamic panel data models: a guide for macroeconomists, Economics Letters, 65, pp. 9-15.
- Khemraj, Tarron and Sukrishnalall Pasha. (2009). The determinants of non-performing loans: An econometric case study of Guyana, Paper Presented at The Caribbean Centre for Banking and Finance Bi-annual Conference on Banking and Finance, St. Augustine, Trinidad and Tobago, May 27 to 29.
- Klein, Nir. (2013). Non-Performing Loans in CESEE: Determinants and Impact on Macroeconomic Performance, IMF Working Paper European Department. No. 13/72.
- Koch, Timothy W. and MacDonald, S. Scot. (2015). Bank Management (8th ed.), Boston: Cengage Learning Press.
- Louzis, Dimitrios, Aggelos T. Vouldis, and Metaxas, Vasilios L. (2012). Macroeconomic and Bank-Specific Determinants of Non-Performing Loans in Greece: A Comparative Study of Mortgage, business, and consumer loan portofolios, Journal of Banking & Finance, 36, pp. 1012-1027.
- Macit, Fatih. (2012). Bank Specific and Macroeconomic Determinants of Profitability: Evidence From Participation Banks in Turkey, AccessEcon Economics Bulletin, 32, pp. 586-595.
- Nkusu, Mwanza. (2011). Nonperforming Loans and Macrofinancial Vulnerabilities in Advanced Economies, IMF Working Paper No 11/161.
- Podpiera, Jiri and Weill, Laurent. (2008). Bad Luck or Bad Management? Emerging Banking Market Experience, Journal of Financial Stability, 4, pp. 135-148.
- Rajan, Raghuram G. (1994). Why Bank Credit Policies Fluctuate: A Theory And Some Evidence, Oxford Journals: Quarterly Journal of Economics, 109, pp. 399-441.
- Rinaldi, Laura and Sanchis-Arellano, Alicia. (2006). Household Debt Sustainability: What Explains Household Non-performing Loans? An Empirical Analysis, ECB Working Paper.
- Salas, Vicente and Jesus Saurina. (2002). Credit risk in two institutional regimes: Spanish commercial and savings banks, Journal of Financial Services Research, 22, pp. 203-224.
- Saunders, Anthony and Cornett, Marcia Millon. (2012). Financial Markets and Institutions (5th ed), New York: Mc Graw-Hill International Edition.
- Saunders, Anthony and Garnett, Marcia Millon. (2008). Financial Institutions Management : A Risk Management Approach (6th ed.), New York: Mc Graw-Hill International Edition.
- Shu, Chang. (2002). The impact of macroeconomic environment on the asset quality of Hong Kong’s Banking Sector, Hongkong’s Monetary Authority Research Memorandum.
- Skarica, Bruna. (2014). Determinants of non-performing loans in Central and Eastern European countries, Financial Theory and Practice, 2014, vol. 38, issue 1, pp. 37-59.