ANALYZING NON-PERFORMING ASSETS IN EDUCATIONAL LOANS: A CASE STUDY OF INDIA
Keywords:
Educational Loans; Non-Performing Assets; Multi Stage Disproportionate Sampling method;Economic Growth; technological developmentAbstract
The primary objective of this research study is to investigate non-performing assets in Indian educational loans. Education is a critical foundation of the Indian economy. It represents the primary source of livelihood for the development and the development of an economy. Educational loans are very important in order to achieve technological development and, implicitly, to reduce costs and use sustainable strategies. The data sample was collected from 80 lenders (bank managers) and 80 borrowers of education loans from Pudukkottai district, Tamilnadu state in India. The Multi Stage Disproportionate Sampling method has been applied for the purpose of collecting information from both the borrowers and the lenders. The analysis results refute the hypothesis, as there is no substantial variation in how various types of banks manage non- performing assets in educational credit, since the bulk of NPA instances in educational credit are the consequence of borrowers' intentional default. The majority of defaults were caused by political leaders' announcements of debt forgiveness. The empirical results are relevant and contribute to a better understanding of the impact of non-performing assets in educational loans on sustainable economic growth in India.
References
Abu Bakar, E., Masud, J. &Jusoh M.Z. (2006), ‘Knowledge, attitude and perceptions of university students towards educational loans in Malaysia’, Journal of family economics issue, Vol. 27, pp. 692–701.
Bakar, E. A., Masud, J., &Jusoh, Z. M. (2006). Knowledge, attitude and perceptions of university students towards educational loans in Malaysia. Journal of family and economic issues, 27(4), 692-701.
Baradi, N. K., &Malla, V. D. K. Educational Loans from Scheduled Commercial Banks: A CriticalAssessment.
Baum, S. & O’Malley, M. (2003), College on credit: how borrowers perceive their education debt: results of the 2002 National Loan Survey (Final Report), Braintree, MA: Nellie Mae.
Baum, S. & Saunders, D. (1998), Life after debt: results of the national student loan Survey (Final Report), Braintree, MA: Nellie Mae.
Behrens, R. H. (1992). Commercial Loan Officer’s Handbook. Japan: Bankers Publishing Company, Toppan Company, Limited.
BrownBridge, M. (1998), “Financial distress in local banks in Kenya, Uganda and Zambia: causes and implications for regulatory policy”, Development Policy Review Journal, 16 (2), 173 – 89
Christman, D.E. (2000), Multiple realities: characteristics of loan defaulters at a two-year public institution, Community college review, Vol. 27 (4), pp. 16–32.
Churaman, C.V. (1992), Financing of college education by single-parent and two-parent families, Family and economics issues, Vol. 13 (1), pp. 96–113.
Clarke, P. S. and Johnston, D. H. (1995). The Problem Loan-Problem Solver-Step-by-Step Strategies for Resolving Bankruptcy, Lender Liability and Other Problem Loan Situations. United States of America: A BankLine Publication, Probus Publishing.
Das, S (2010) Management of NonPerforming Assets In Indian Public Sector Banks With Special Reference To Jharkhand. Retrievied from http://www.igidr.ac.in/newspdf/money/mfc
_10/Santanu%20Das_submission_45.pdf
Davies, E. & Lea, S.E.G. (1995), ‘Student attitudes to student debt’, Journal of economic psychology, (16), pp. 663–679. Dynan, K. E. (2009). Changing household financial opportunities and economic security. Journal of Economic
Perspectives, 23(4), 49-68
Dynarski, M. (1994), Who defaults on student loans? Findings from the National Postsecondary Student Aid study, Economics of education review, Vol. 13 (1), pp. 55–68.
Fossey, R. & Bateman, M. (1998), Condemning students to debt: college loans and public policy, Teacher College Press. Fox, M. (1992), Student debt and enrolment in graduate and professional school, applied economics, Vol. 24, pp. 669–
Gjonca, E. & Calderwood, L. (2004), Socio-demographic characteristics, Institute for Fiscal Studies, National Centre for Social Research, University College London.
Goyal, K. (2010). Empirical study of non-performing assets management of Indian public sector banks. Asia Pacific Journal of Research in Business Management, 1(1), 114-131.
Harrast, S.A. (2004), ‘Undergraduate borrowing: a study of debtor students and their ability to retire undergraduate loans’, NASFAA journal of student financial aid, Vol. 34 (1).
Harrast, S.A. (2004), ‘Undergraduate borrowing: a study of debtor students and their ability to retire undergraduate loans’, NASFAA journal of student financial aid, Vol. 34 (1).
Herr, E. & Burt, L. (2005), ‘Predicting student loan default for the University of Texas at Austin’, NASFAA journal of student financial aid, Vol. 35 (2).
Hira, T.K., Anderson, M.M. & Petersen, K. (2000), ‘Students’ perceptions of their education debt and its impact on life after graduation’, Journal of student financial aid, Vol. 30, pp.7–19
Ismail, S. and Serguieva, A., (2009) Investigating the effect of socio-demographics on students’ attitude towards student loan repayment in Malaysia, The European Conference for Academic Disciplines, November 09-13, Gottenheim, Germany (ISSN 1943-6114)
Ismail, S., Serguieva, A. & Karem, W., (2009) Student Loan Repayment in Malaysia: A study of borrowers’ attitude and perceptions, Research Poster Conference 2009, May 06-07, 2009, Brunel University, United Kingdom.
Jain, A., Jain, V., & Jain, S. (2012). Non performing assets in India. Indian Journal of Accounting, 42(2), 11-18.
Jayadev, M., Shah, N., &Vadlamani, R. (2019). Predicting Educational Loan Defaults: Application of Artificial Intelligence Models. IIM Bangalore Research Paper, (601).
Joseph, A. L., & Prakash, M. (2014). A study on analyzing the trend of NPA level in private sector banks and public sector banks. International Journal of Scientific and Research Publications, 4(7), 1-9.
Knapp, L.G. &Seaks, T.G. (1992), An analysis of the probability of default on federally guaranteed student loans, The review of economics and statistics, Vol. 74 (3), pp. 404–411.
Knapp, L.G. &Seaks, T.G. (1992), An analysis of the probability of default on federally guaranteed student loans, The review of economics and statistics, Vol. 74 (3), pp. 404–411.
Kochhar, R., Fry, R., & Taylor, P. (2011). Twenty-to-one: Wealth gaps rise to recordhighs between Whites, Blacks, Hispanics (Social & Demographic Trends report). Retrieved from http://www.pewsocialtrends.org/files/2011/07/SDT-WealthReport_7-26-11_FINAL.pdf
Kumar, M., & Singh, G. (2012). Mounting NPAs in Indian commercial banks. International Journal of Transformations in Business Management, 1(6), 1-6.
Lamkin, M.D. (2004), To achieve the dream, first look at the facts. Change, Vol. 36 (6), pp. 12–15. Lavanya, R., & Ramachandran, S. A Study of Repayment of Education Loan in Tamil Nadu.
Livingstone, S.M. & Lunt, P.K. (1992), ‘Predicting personal debt and debt repayment: psychological, social and economic antecedents’, Journal of economic psychology, Vol. 13(1), pp. 111–134.
Manoj, P. K., & Varghese, K. X. (2013). Educational loans and the higher education sector in India.
Marzan, N. (2014). Loan processing, credit appraisal, follow–up & recovery procedure of IFIC Bank Limited. Monks, J. (2001). Loan burdens and educational outcomes. Economics of Education Review, 20, 545-550.
Moran, M. (1987), Student financial aid and women: equity dilemma? ERIC Digest, pp. 1– 4.
Mot, H. O., Masinde, J. S., Mugenda, N. G., &Sindani, M. N. (2012). Effectiveness of Credit Management Systemon Loan Performance: Empirical Evidence from Micro Finance Sector in Kenya.
Myers, G. &Siera, S. (1980), ‘Development and validation of discriminant analysis models for student loan defaulters’, Journal of student financial aid, Vol. 10 (1), pp. 9–17.
Narula, S., & Singla, M. (2014). Empirical study on non-performing assets of bank. International Journal of advance Research in Computer science and management studies, 2(1).
Panjali, N., &Kasilingam, R. (2014). A Study on the Sources for Creating Awareness of Education Loan. Sumedha Journal of Management, 3(4), 53.
Patnaik, B. C. M., Satpathy, I., Litt, D., & Mohapatra, A. K. (2011). Demystifying npas on education loan: A survey (with special reference to selected urban, rural areas and bank officials of Odisha). Journal of Banking Financial Services and Insurance Research, 1(4), 16-31.
Podgursky, M. (2002), ‘Student loan defaults and enrolment persistence’, Journal of tudent financial aid, Vol. 32 (3), pp.
–42.
Schwartz, S. & Finnie, R. (2002), Student loans in Canada: an analysis of borrowing and repayment, Economics of education review, Vol. 21 (5), pp. 497–512.
Seaward, H.G.W. & Kemp, S. (2000), ‘Optimism bias and student debt’, New Zealand journal of psychology, Vol. 29(1), pp. 17–19.
Steiner, M. &Teszler, N. (2003), The characteristics associated with student loan default at Texas A&M University, Produced by Texas guaranteed in association with Texas A&M University.
Tilak, J. B. G. (1992). Students Loans in Financing Higher Education in India. Journal of Higher Education. 23: 389-404. Varghese, K. X., & Manoj, P. K. A REVIEW OF EDUCATIONAL LOANS DISBURSED DURING FY: 2005-2011.
Visaria, S. (2009). Legal Reform and Loan Repayment: The Microeconomic Impact of Debt Recovery Tribunals in India.
American Economic Journal: Applied Economics, 1(3), 59–81. doi:10.1257/app.1.3.59
Volkwein, J.F. &Szelest, B.P. (1995), Individual and campus characteristics associated with student loan default, Research in Higher Education, Vol. 36 (1), pp 41-72.
Volkwein, J.F., Szelest, B.P., Cabrera, A.F. &Napierski-Prancl, M.R. (1998), ‘Factors associated with student loan default among different racial and ethnic groups’, Journal of higher education, Vol. 69(2), pp. 206–237.
Wilms, W.W., Moore, R.W. & Bolus, R.E. (1987), Whose fault is default? A study of the impact of student characteristics and institutional practices on guaranteed student loan default rates in California, Educational evaluation and policy analysis, Vol. 9(1), pp. 41–54.
Woo, J.H. (2002), ‘Factors affecting the probability of default: student loans in California’, Journal of student financial aid, Vol. 32 (2), pp. 5–25.
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
You are free to:
- Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
- The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
- Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Notices:
You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation .
No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.
