MSME lending and bank efficiency: Evidence from Indonesia
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Author(s)Irfan Adhityo DinutistomoLink to ORCID Index: https://orcid.org/0000-0002-7383-6779
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Arief Wibisono LubisLink to ORCID Index: https://orcid.org/0000-0002-0689-2092
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DOIhttp://dx.doi.org/10.21511/bbs.16(3).2021.09
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Article InfoVolume 16 2021 , Issue #3, pp. 93-103
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Banks prefer to lend to bigger clients for a variety of reasons, including transaction costs and risk considerations. Due to this phenomenon, the Central Bank of Indonesia issued a regulation that requires banks to channel a minimum proportion of their credit portfolio to micro, small, and medium enterprises (MSMEs). Nevertheless, the impact of channeling funds to MSMEs remains a subject of controversy, in part depending on the dimensions and metrics used. This study examines how MSME lending affects the efficiency of banks in Indonesia, a country where MSMEs constitute more than 99% of business entities. Using a total of 175 panel data observations of banks in Indonesia from 2014–2018, banks’ cost efficiency is first estimated using a stochastic frontier approach (SFA). Panel data regression is used to examine the impact of MSME lending on efficiency. The result of this study shows a significant and positive impact of the proportion of MSME lending on bank efficiency, which indicates that requiring banks to channel funds to MSMEs does not only potentially support economic development, but also is beneficial from the business perspective in the Indonesian context.
Acknowledgment
The research was also made possible with the support of PUTI Grant by Universitas Indonesia No. NKB-2036/UN2.RST/HKP.05.00/2020.
- Keywords
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JEL Classification (Paper profile tab)G21, G28
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References46
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Tables7
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Figures0
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- Table 1. Summary of hypothesis and testing type
- Table 2. Variable definitions of cost function
- Table 3. Variable definitions and descriptions in the efficiency model
- Table 4. Results of the stochastic cost frontier model
- Table 5. Descriptive statistics of the efficiency model
- Table 6. Pairwise correlation of EFF and CIR
- Table 7. Efficiency model result
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- Ang, J. S. (1991). Small business uniqueness and the theory of financial management. Journal of Small Business Finance, 1(1), 1-13.
- Asmare, E., & Begashaw, A. (2018). Review on parametric and nonparametric methods of efficiency analysis. Biostatistics and Bioinformatics, 2(2), 1-7.
- Banna, H., Ahmad, R., & Koh, E. H. Y. (2017). Determinants of commercial banks’ efficiency in Bangladesh: Does crisis matter? The Journal of Asian Finance, Economics and Business, 4(3), 19-26.
- Battese, G. E., & Coelli, T. J. (1995). A model for technical inefficiency effects in a stochastic frontier production function for panel data. Empirical Economics, 20, 325-332.
- Beck, T., & Demirgüç-Kunt, A. (2004). SMEs, growth, and poverty. Do pro-SME policies work? (Note No. 264). Washington: World Bank.
- Beck, T., & Demirgüç-Kunt, A. (2006). Small and medium-size enterprises: Access to finance as a growth constraint. Journal of Banking and Finance, 30(11), 2931-2943.
- Berger, A. N., & Mester, L. J. (1997). Inside the black box: What explains differences in the efficiencies of financial institutions? Journal of Banking and Finance, 21(7), 895-947.
- Berger, A. N., & Udell, G. F. (1995). Relationship lending and lines of credit in small firm finance. The Journal of Business, 68(3), 351-381.
- Berger, A. N., Klapper, L. F., & Udell, G. F. (2001). The ability of banks to lend to informationally opaque small businesses. Journal of Banking and Finance, 25(12), 2127-2167.
- Bernauer, T., & Koubi, V. (2002). Regulating bank capital: Does market discipline facilitate or replace capital adequacy rules? (Working Paper). Zurich: Center for International Studies, ETH Zurich.
- Boadi, E.K., Li, Y., & Lartey, V.C. (2016). Role of bank specific, macroeconomic and risk determinants of banks profitability: Empirical evidence from Ghana’s rural banking industry. International Journal of Economics and Financial, 6(2), 813-823.
- Boushnak, E., Rageb, M. A., Ragab, A. A., & Sakr, A. M. (2018). Factors influencing credit decision for lending SMEs: A case study on National Bank of Egypt. Open Access Library Journal, 5, e4996.
- Brooks, C. (2014). Introductory Econometrics for Finance (3rd ed.). Cambridge: Cambridge University Press.
- Burger, A., & Moormann, J. (2008). Productivity in banks: Myths & truths of the cost income ratio. Banks and Bank Systems, 3(4), 85-94.
- Central Bank of Indonesia and LPPI. (2015). Profil Bisnis Usaha Mikro, Kecil, dan Menengah. Bank Indonesia, Jakarta. (In Indonesian).
- Central Bank of Indonesia. (2012). Commercial Banks Lending or Financing for Micro, Small and Medium Enterprises Development (Regulation No. 14/22/PBI/2012). (In Indonesian).
- Central Bank of Indonesia. (2015). Revision of Commercial Banks Lending or Financing for Micro, Small and Medium Enterprises Development (Regulation No. 17/12/PBI/2015). (In Indonesian).
- Chih, S. H., Liang, L, & Huang, B. (2018). The study on the relationship between bank M&A, SME lending, credit guarantee, and bank efficiency. Romanian Journal of Economic Forecasting, 21(2), 95-117.
- Christensen, L. R., Jorgenson, D. W., & Lau, L. J. (1973). Transcendental logarithmic production frontiers. The Review of Economics and Statistics, 55(1), 28-45.
- Das, A., & Ghosh, S. (2006). Financial deregulation and efficiency: An empirical analysis of Indian banks during the post reform period. Review of Financial Economics, 15(3), 193-221.
- Duarte, F. D., Ana, P. M. G., & Jose, P. E. (2016). Collateral-based in SME lending: The role of business collateral and personal collateral in less-developed countries. Research in International Business and Finance, 39(A), 406-422.
- Gordo, G. M. (2013). Estimating Philippine bank efficiencies using frontier analysis. Philippine Management Review, 20, 17-36.
- Government of Republic of Indonesia. (2008). Micro, Small, and Medium Enterprises. Law of The Republic of Indonesia No. 20 of 2008.
- Gujarati, D. N., & Porter, D. C. (2009). Basic Econometric (5th ed.). New York: McGraw-Hill.
- Huang, T. H., & Wang, M. H. (2002). Comparison of economic efficiency estimation methods: Parametric and non-parametric techniques. Manchester School, 70(5), 682-709.
- Indonesia Ministry of Cooperatives and SMEs. (2018). Laporan Perkembangan Data Usaha Mikro, Kecil, Menengah (UMKM) dan Usaha Besar (UB) Tahun 2016–2017. (In Indonesian).
- International Finance Corporation (IFC). (2019). Banking on SMEs: Trends and Challenges.
- Liang, L. W., Huang, B. Y., Liao, C. F., & Gao, Y. T. (2017). The impact of SMEs’ lending and credit guarantee on bank efficiency in South Korea. Review of Development Finance, 7(2), 134-141.
- Niţoi, M., & Spulbar, C. (2015). An examination of banks’ cost efficiency in Central and Eastern Europe, Procedia Economics and Finance, 22, 544-551.
- OECD. (2005). OECD SME and Entrepreneurship Outlook 2005. Paris: OECD Publishing.
- OECD. (2006). The SME financing gap: theory and evidence. Financial Market Trends, 2, 89-97.
- Oral, M., & Yolalan, R. (1990). An empirical study on measuring operating efficiency and profitability of bank branches. European Journal of Operational Research, 46(3), 282-29.
- Pasiouras, F., & Kosmidou, K. (2007). Factors influencing the profitability of domestic and foreign commercial banks in the European Union. Research in International Business and Finance, 21(2), 222-237.
- Pasiouras, F., Liadaki, A., & Zopounidis, C. (2008). Bank efficiency and share performance: Evidence from Greece. Applied Financial Economics, 18(14), 1121-1130.
- Rajan, R. G., & Petersen, M. A. (1994). The benefits of lending relationships: Evidence from small business data. The Journal of Finance, 49(1), 3-37.
- Ramcharran, H. (2017). Financing small and medium-sized enterprises in Thailand: The importance of bank loans and financing diversification. The Journal of Entrepreneurial Finance, 19(2).
- Řepková, I. (2015). Banking efficiency determinants in the Czech banking sector. Procedia Economics and Finance, 23, 191-196.
- Sari, P. Z., & Saraswati, E. (2017). The determinant of banking efficiency in Indonesia: DEA approach. Journal of Accounting and Business Education, 1(2), 208-229.
- Schlüter, T., Busch, R., Hartmann-Wendels, T., & Sievers, S. (2012). Determinants of the interest rate pass-through of banks: Evidence from German loan products (Discussion Papers No. 26/2012). Deutsche Bundesbank.
- Shihadeh, F. H., Gamage, S. K. N., & Hannoon, A. (2019). The causal relationship between SME sustainability and banks’ risk. Economic Research-Ekonomska Istraživanja, 32(1), 2743-2760.
- Siudek, T. (2008). Theoretical foundations of banks efficiency and empirical evidence from Poland. Socialiniai Tyrimai, 13(3), 150-158.
- Stiglitz, J., & Weiss, A. (1981). Credit rationing in markets with imperfect information. American Economic Review, 71(3), 393-410.
- Tambunan, T. (2017). The performance of Indonesia’s public credit guarantee scheme for MSMEs: A regional comparative perspective. Journal of Southeast Asian Economics, 35(2), 319-32.
- Wardhono, A., Modjo, M. I., & Utami, E. W. (2019). Role of credit guarantee for financing MSMEs: Evidence from rural and urban areas in Indonesia (ADBI Working Paper Series No. 967). Asian Development Bank Institute.
- World Bank. (2008). Finance for all? Policies and Pitfalls in Expanding Access. World Bank Policy Research Report.
- Zouhaier, H. (2015). Financial efficiency, competitiveness and profitability of Islamic banks. Journal of Applied Economic Sciences, 10(4), 593-606.
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Perceived health risk, online retail ethics, and consumer behavior within online shopping during the COVID-19 pandemic
Yuniarti Fihartini ,
Arief Helmi ,
Meydia Hassan ,
Yevis Marty Oesman
doi: http://dx.doi.org/10.21511/im.17(3).2021.02
Innovative Marketing Volume 17, 2021 Issue #3 pp. 17-29 Views: 3937 Downloads: 1523 TO CITE АНОТАЦІЯThe risk of virus contracting during the COVID-19 pandemic has changed consumer preference for online shopping to meet their daily needs than shopping in brick-and-mortar stores. Online shopping presents a different environment, atmosphere, and experience. The possibility of ethical violations is higher during online than face-to-face transactions. Therefore, this study was conducted to investigate the influence of perceived health risk and customer perception of online retail ethics on consumer online shopping behavior during the COVID-19 pandemic, involving seven variables, namely perceived health risk, security, privacy, non-deception, reliability fulfillment, service recovery, and online shopping behavior. The data were collected through an online survey by employing the purposive sampling technique to a consumer who has shopped online during the COVID-19 pandemic in Indonesia. 315 valid responses were obtained and analyzed through quantitative method using SEM-Amos. The results showed that perceived health risk and four variables of online retail ethics including security, privacy, reliability fulfillment, and service recovery affected online shopping behavior. Meanwhile, non-deception was found to have an insignificant effect. The coefficient value proved perceived health risk to be more dominant in influencing online shopping behavior than the variables of online retail ethics. Thus, consumers pay more concern for their health during online shopping. However, positive consumer perceptions of the behavior of online retail websites in providing services also can encourage consumers to shop online during this pandemic.
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Positive contribution of the good corporate governance rating to stability and performance: evidence from Indonesia
RR. Iramani , Muazaroh Muazaroh , Abdul Mongid
doi: http://dx.doi.org/10.21511/ppm.16(2).2018.01
Problems and Perspectives in Management Volume 16, 2018 Issue #2 pp. 1-11 Views: 2981 Downloads: 251 TO CITE АНОТАЦІЯThis paper aims to examine the impact of Good Corporate Governance (GCG) practice on bank stability and performance. Governance is measured using the GCG rating that covers eleven aspects. The authors apply instrumental regression to link governance to performance and stability. The study covers a sample of 150 banks. The result shows that bank stability can mediate bank governance and bank performance. On the determinant of bank performance, it can be concluded that the GCG rating is positive and directly influences bank performance. Bank stability is also positive for bank performance indicating the indirect contribution of the GCG rating to bank performance. NPL, LDR, CAR and bank’s size (LASSET) are all negative and significant. The aim of this paper is to provide strong empirical evidence on the importance of governance and stability for performance. The limitations of this paper are the size of the sample and that it only covers public banks which are theoretically required to apply better governance in all aspects of their business by the Capital Market Authority.
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Human resource management in promoting innovation and organizational performance
I Gede Riana ,
Gede Suparna ,
I Gusti Made Suwandana ,
Sebastian Kot 
,
Ismi Rajiani
doi: http://dx.doi.org/10.21511/ppm.18(1).2020.10
Problems and Perspectives in Management Volume 18, 2020 Issue #1 pp. 107-118 Views: 2960 Downloads: 667 TO CITE АНОТАЦІЯHuman resource management (HRM) is one of the elements enabling an organization to remain competitive in turbulence conditions. The effective practice of HRM makes competent and innovative employees contributing to the achievement of organizational objectives. This study aims to analyze HRM practices in creating innovation and organizational performance. The questionnaire was used to measure the respondents’ perceptions of variables used by a Likert scale. A survey of 126 manager samples and middle managers at export-oriented short and medium enterprises (SMEs) in Bali, Indonesia, was conducted to test the model. The analysis has shown that the proposed model was proven to be compliant with the research hypotheses. HRM significantly affects organizational performance and innovation, and it was found out that innovation can improve organizational performance. However, in the process of simultaneous testing, it was found out that innovation cannot improve organizational performance. The lack of attention to investments in human resources became one of the barriers to SMEs in creating innovation.
