Research Article

RELATIVE PERFORMANCE OF LOAN RECOVERY IN REAL ESTATE AND NON-REAL ESTATE SECTORS IN LAGOS METROPOLIS

1 Department of Estate Management, Federal University of Technology, Akure, Nigeria
2 Department of Estate Management, Federal University of Technology, Akure, Ondo State, Nigeria
* Corresponding author: aoadewusi@futa.edu.ng
Published: Mar, 2017
Pages: 11-19
Views: 22
Downloads: 6

Abstract

Purpose: The paper investigates the recovery of loan granted for economic activities in some selected sectors of Nigerian economy. This was as a result of the growing trend of unrecovered loans with its debilitating effect on the overall economy which has become a worrisome challenge for sustainable economic development. Design/methodology/approach: The targeted population for the study comprises all commercial banks and Primary mortgage institutions in Lagos Metropolis. Fourteen (14) and forty (40) commercial banks and primary mortgage institutions respectively were randomly selected for the study. Furthermore, 3,197 loan accounts comprising of the fully recovered and partially recovered loans in different sectors of the economy were purposively accessed from the databases of the selected lending institutions between 2000 and 2015. Collected data were analysed using descriptive statistics, t-test and analysis of variance (ANOVA). Findings: The result revealed that the amount of loan recovered from various sectors of the economy is significantly different from one another. The t-test result reveals that the percentage of loan recovered from real estate sector is significantly higher in the fully recovered loan category than those in the partially recovered category, while the percentage value of loan recovered from agriculture, oil, mining, manufacturing and telecommunication sectors are significantly lower in the fully recovered loan category than in the partially recovered loan. Practical implications: The paper recommends that lending institutions should continue to make funds available and more accessible to all sectors especially real estate sector in order to boost economic activities thereby affecting the growth of the Nigeria economy. A study with larger sample that focuses on loan recovery across all lending institutions in African continent may be considered as a further study for a more adequate representation Originality/value: The research revealed that all the sectors under review achieved more than 50% loan recovery rate, however, the amount of loan recovered from the real estate sector is significantly higher than the amount of loan recovered from non-real estate sectors. 

References

  1. Ahmed, J. U. (2010). An empirical estimation of loan recovery and asset quality of commercial banks. The NEHU Journal, 8(1), 15-17.
  2. Aluko, B.T. (2000). A study of the Appropriateness of Mortgage valuation for Institutional Lending in Nigeria. An Unpublished PhD Thesis, Obafemi Awolowo University, Ile-Ife.
  3. Archer, K.J and Lemeshow, S. (2007). Goodness of Fit test for a Logistic Regression Model Using Survey Data
  4. Aremu, O.S., Suberu, O.J. and Oke, J.A. (2010). Effective credit Processing and Administration as a panacea for Non- Performing Assets in Nigerian Banking System. Journal of Economics, 1(1), 53-56.
  5. Asarnow, E. and Edwards, D. (1995). Measuring Loss on Defaulted Bank Loans. A 24-Year- Study; Journal of Commercial Lending, 77(7), 11-23.
  6. Bandyopadhyay, A. and Saha, A. (2009). Factors Deriving and Default Risk in Residential Housing Loans: Indian Evidence. National Institute of Bank Management (NIBM).
  7. Basel Committee on Banking Supervision (1999). Sound Practices for Loan Accounting and Disclosure, Bank for International Settlements, Basel.
  8. Bello, M.O. and Adewusi, A.O. (2009). A Comparative Analysis of the Performance of Real Estate and Financial Assets as Security for Mortgage Lending in Nigeria. FIG Working Week, Eilat, Isreal, 3-8 May.
  9. Caprio, G.J. and Klingebiel, D. (1999). Bank insolvency: Bad Luck, Bad Policy or Bad Banking? Annual World Bank Conference on Development Economics.
  10. Carty, L. V., and Lieberman, D. (1996). Defaulted bank loan recoveries. Moody's Investors Service, 15, 79.
  11. Caselli, S., Gatti, S., and Querci, F. (2008). The sensitivity of the loss given default rate to systematic risk: new empirical evidence on bank loans. Journal of Financial Services Research, 34(1), 1-34.
  12. CBN (2003). List of Licensed Bank in Nigeria. Annual Bulletin of the Central Bank of Nigeria
  13. Dermine, J., and De Carvalho, C. N. (2006). Bank loan losses-given-default: A case study. Journal of Banking & Finance, 30(4), 1219-1243.
  14. Fofack, H. (2005). Non- performing Loans in Sub- Saharan Africa: Causal Analysis; Implication on Macroeconomics. World Bank Policy Research Working Paper No. 3769.
  15. Grossman, R.J., Brennan, W.T. and Vento, J. (1998). Syndicated Bank Loan Recovery Study, Fitch Research, October 1997.
  16. Hoang, T.L. (2006). An Update of Non- Performing Loans Resolution and Banking Reform in Vietnam. Publication of Partner, Mekong Co. Ltd, Viet Nam.
  17. Hurt, L. and Felsovalyi, A. (1998). Measuring Loss on Latin American Defaulted Bank Loans: A 27-Year Study of 27 Countries, Citibank, July 1997.
  18. Inwon, S. (2002). Collateral in Loan Classification and Provisioning,Iinternational Monetary Fund, working Paper. WP|02|122.
  19. Khieu, H. D. and Mullineaux, D.J. (2009). The Determinants of bank loan recovery rates, College of Business, University of Southern Indiana
  20. Khieu, H.D., Mullineaux, D.J. and Yi, H. (2012). The Determinants of Bank Loan Recovery Rates. Journal of Banking and Finance, 36, 923-933
  21. Lovell, R. and French, N. (1996). Estimated Realization price what do Banks Want and what can realistically provided? Journal of property Finance, 6 (4), 7-16.
  22. Momoh, S. (2009). Stakeholders chide CBN over N200bn agric fund, Business Day, 22 April, p.49.
  23. Nargundkar, S. and Priestley, J. (2003). Model Development Techniques and Evaluation Methods for Prediction and Classification of Consumer Risk in the Credit Industry, in P. Zhang (ed), Neural Networks for Business Forecasting, IRM Press.
  24. Oloyede, S. (2004). Mortgage Financing in Nigeria: Challenges and The Search For Strategies Aimed At Achieving Global Competitiveness. Globalisation and Construction, 611.
  25. Panahian, H. (2011); Using Artificial Neural Networks for Predicting Default Risk in Banking System (A Comparative Study between Indonesian and Iranian Banking System). American Journal of Scientific Research, 30(1), 36-57. Paper, Emerging Issues Series October, 1-14.
  26. Pfister, S. and Sartori, A. (2015). A survey of banks on the prospects for real estate sector lending in Europe. Property Lending Barometer.
  27. Sanusi, L. S. (2009). Non –performing Loans in Nigerian Banks. CBN Annual Report.
  28. Somoye, R.O.C. (2008). The Performance of Commercial Banks in Post Consolidation Period in Nigeria. An Empirical Reviews. Global Academy of Business and Economic Research International
  29. Somoye, R.O.C. (2010). The Variation of Non-performing Loans on Bank Performance in Nigeria. Indian Journal of Economics and Business 9 (1), 87-99.
How to Cite

Adewusi, A. O., & Akinsanya, G. M. (2017). RELATIVE PERFORMANCE OF LOAN RECOVERY IN REAL ESTATE AND NON-REAL ESTATE SECTORS IN LAGOS METROPOLIS. Journal of Contemporary Research in the Built Environment, 1(1), 11-19. https://doi.org/10.68128/jocrebe.2017.065ayka8

A. O. Adewusi, and G. M. Akinsanya, "RELATIVE PERFORMANCE OF LOAN RECOVERY IN REAL ESTATE AND NON-REAL ESTATE SECTORS IN LAGOS METROPOLIS," Journal of Contemporary Research in the Built Environment, vol. 1, no. 1, pp. 11-19, March 2017. doi: 10.68128/jocrebe.2017.065ayka8

Share this article:
Facebook X / Twitter LinkedIn