رتبه‏ بندی عوامل تعیین ‏کننده ریسک اعتباری تسهیلات کشاورزی: مطالعه موردی واحدهای پرواربندی استان اردبیل

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دکتری اقتصاد کشاورزی، دانشگاه تهران، تهران، ایران

2 نویسنده مسئول و استادیار گروه اقتصاد کشاورزی، دانشگاه تهران، تهران، ایران

3 دانشجوی دکتری اقتصاد کشاورزی، دانشگاه تهران، تهران، ایران

4 دانش‏ آموخته کارشناسی ارشد علوم اقتصادی، دانشگاه شهید بهشتی، تهران، ایران

چکیده

عملکرد بانک کشاوزی در زمینه وصول مطالبات نشان­دهنده کاهش میزان بازپرداخت تسهیلات است، که ادامه آن می­ تواند یک مسئله جدی برای ادامه حیات مؤسسات مالی و اعتباری باشد. از این رو، هدف مطالعه حاضر رتبه­ بندی عوامل مؤثر بر ریسک اعتباری تسهیلات کشاورزی در واحدهای پرواربندی استان اردبیل بود. اطلاعات مورد نیاز در سال 1397 از طریق پرسشنامه و مصاحبه با کارشناسان بانکی و گیرندگان تسهیلات جمع ­آوری شد. نتایج الگوی لاجیت نشان داد که متغیرهای مشتری قبلی بانک بودن، سال­های بازپرداخت، تجربه، مبلغ تسهیلات و آورده نقدی در سطح پنج درصد و متغیرهای مساحت سالن­ها، مساحت بهاربند، تعداد اقساط، تحصیلات و مالکیت در سطح ده درصد بر بازپرداخت تسهیلات مؤثرند؛ همچنین، بر اساس تحلیل کیفی، از دیدگاه دریافت ­کنندگان تسهیلات، مهم‏ترین عوامل مؤثر بر عدم بازپرداخت عبارت‏اند از نبود نهاده غذایی به قیمت مناسب و عدم حمایت دولت، حوادث طبیعی و عدم ارزیابی طرح با قیمت روز. با توجه به عدم ارزیابی صحیح ظرفیت مالی و کشش اعتباری متقاضی و عدم ارزیابی صحیح پروژه­ ها. بنابراین، برگزاری کلاس ­ها و کارگاه­  های خبره ­پروری و آموزش کارکنان به‏ ویژه نیروهای مرتبط با اعطای تسهیلات و نظارت بر اجرای طرح­ها در راستای افزایش تخصص کارشناسان و مدیران کمیته ­های اعتباری در زمینه طرح ­های مختلف پیشنهاد می­ شود تا از این رهگذر، در اعتبارسنجی متقاضیان دریافت تسهیلات و بررسی اقتصادی و فنی طرح­ ها دقت بیشتری انجام شود.

کلیدواژه‌ها


عنوان مقاله [English]

Ranking of Factors Affecting Credit Risk of Agricultural Facilities: A Case Study of Fattening Units in Ardabil Province of Iran

نویسندگان [English]

  • M Mir 1
  • H. Rafiee 2
  • E. Ensan 3
  • R. Shakeri Bostanabad 3
  • R. Yazdanpanah 4
1 PhD Student in Agricultural Economics, University of Tehran, Tehran, Iran
2 Corresponding Author and Assistant Professor, Department of Agricultural Economics, University of Tehran, Tehran, Iran
3 PhD Student in Agricultural Economics, University of Tehran, Tehran, Iran
4 MA Graduate in Economic Sciences, Shahid Beheshti University, Tehran, Iran
چکیده [English]

The performance of Bank Keshavarzi of Iran (BKI)/ Agriculture Bank of Iran in the field of facility repayment indicates a decrease in the amount of facility repayment, which can be a serious issue for the survival of financial and credit institutions. Therefore, this study aimed at ranking the factors affecting the credit risk of agricultural facilities in fattening units in Ardabil province of Iran. The data was collected in 2019 through questionnaires and interviews with banking experts and facility recipients. The results of the logit model showed that the variables of being a previous customer of the bank, years of repayment, experience, amount of facilities and cash flow at the level of five percent and variables of hall area, farmyard and number of installments, education and ownership at level ten percent would affect the repayment of the facility; in addition, based on qualitative analysis, from the facility recipients’ viewpoints, the most important factors affecting non-repayment would include the lack of food input at a reasonable price and lack of government support, natural disasters and failure to evaluate the plan at the current price.

کلیدواژه‌ها [English]

  • Credit Risk
  • Logit Model
  • Fattening Units
  • Bank Keshavarzi of Iran (BKI)/ Agriculture Bank of Iran
  • Ardabil (Province)
  1. Ansari, v. (2002). Identifying and determining the role of factors affecting the recession of agricultural projects in Iran. Master Thesis, Faculty of Economics and Agricultural Development, University of Tehran. (Persian)
  2. Arabmazar, A. and Roueintan, P. (2006). Determinants of credit risk among bank clients: a case study of Bank Keshavarzi of Iran (BKI)/ Agricultural Bank of Iran. Journal of Iran's Economic Essays, 3(6): 46-82. (Persian)
  3. Babazadeh, T. (2013). Identifying the factors affecting the non-repayment of long-term facilities of Bank Keshavarzi of Iran (BKI)/ Agriculture Bank of Iran (Mazandaran province). MSc. Dissertation, Faculty of Economics and Agricultural Development, University of Tehran. (Persian)
  4. Bagheri, M., Najafi, B. and Moezzi, F. (2008). A study of the factors affecting agricultural credit repayment (case study: Fars province). Iranian Journal of Agriculture Science, 2-38(3): 81-90. (Persian)
  5. BKI (2017). Annual performance report of Keshavarzi Bank of Iran (2008-2017). Tehran: Bank Keshavarzi of Iran (BKI)/ Agriculture Bank of Iran, Department of Economic Studies and Planning. (Persian)
  6. CBI (2017). Performance report of Iranian banks (2008-2017). Tehran: Central Bank of Iran (CBI). (Persian)
  7. Deininger, K. and Liu, Y. (2009). Determinants of repayment performance in Indian micro-credit groups. World Bank Policy Research Working Paper Series, No. 1: WPS4885.
  8. Durguner, S., Barry, P.J. and Katchova, A.L. (2006). Credit scoring models: a comparison between crop and livestock farms.  Annual Meeting, July 23-26, 2006, Long Beach, CA 21431, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association). DOI: 10.22004/ag.econ.21431.
  9. Glantz, M. and Mun, J. (2003). Managing bank risk: an introduction to broad-base credit engineering. Academic Press.
  10. Hou, J., Skees, J.R. and Wang, W. (2005). Potential of credit scoring in microfinance institutions in US (Community Venture Corp. of Kentucky taken as case study). Annual Meeting, February 5-9, 2005, Little Rock, Arkansas35487, Southern Agricultural Economics Association. DOI: 10.22004/ag.econ.35487.
  11. Jappelli, T. (1990). Who is credit constrained in the US economy? The Quarterly Journal of Economics, 105(1): 219-234.
  12. Jouault, A. and Featherstone, A.M. (2011). Determining the probability of default of agricultural loans in a French bank. Journal of Applied Finance and Banking, 1(1): 1-30.
  13. Judge, G.G., Hill, R.C., Griffiths, W.E., Lütkepohl, H. and Lee, T.-C. (1988). Introduction to the theory and practice of econometrics. Second Edition. Wiley Series in Probability and Mathematical Studies.
  14. Limsombunchai, V., Gan, C. and Lee, M. (2005). An analysis of credit scoring for agricultural loans in Thailand. American Journal of Applied Sciences, 2(8): 1198-1205. DOI: 3844/ajassp.2005.1198.1205.
  15. Maddala, G.S. (1986). Limited-dependent and qualitative variables in econometrics. Cambridge University Press.
  16. Matin, I. (1997). Repayment performance of Grameen Bank borrowers: the “unzipped” state / La performance de remboursement des emprunteurs chez les Grameen Banks. Savings and Development, 21(4): 451-473. Available at http://www.jstor.org/stable/25830635.
  17. Mohtashami, T. (2006). Developing a credit risk forecasting model for legal applicants for facilities: a case study of Bank Keshavarzi of Iran (BKI)/ Agriculture Bank of Iran. Master Thesis. Faculty of Economics and Agricultural Development, University of Tehran. (Persian)
  18. Nawai, N. and Shariff, M.N.M. (2012). Factors affecting repayment performance in microfinance programs in Malaysia. Procedia-Social and Behavioral Sciences, 62: 806-811.
  19. Negrin, J. L. (2004). The Importance of Borrowers’ History on Credit Behavior: The Mexican Experience.  Econometric Society 2004 Latin American Meetings226, Econometric Society. Available at https://ideas.repec.org/p/ecm/latm04/226.html.
  20. Salami, H. and Ensan, E. (2018). Differentiated impact of factors affecting categories of agricultural non-performing loans. Iranian Journal of Economic Research, 23(76): 185-217. (Persian)
  21. Salami, H., Mohtashami, T. and Sadr, K. (2008). Determinants of facility risk in Islamic banking: a case study of Bank Keshavarzi of Iran (BKI)/ Agricultural Bank of Iran. Agricultural Sciences and Technology Journal, 21(2): 79-97. (Persian)
  22. Schreiner, M. (2003). Scoring: the next breakthrough in microcredit. Occasional paper, 7. Available at https://www.cgap.org/sites/default/files/CGAP-Occasional-Paper-Scoring-The-Next-Breakthrough-in-Microcredit-Jan-2003.pdf.
  23. Shaditalab, Z. (1994). Issues of agricultural credit system in Iran (non-repayment). Proceedings of the Second Symposium on Agricultural Economics in Iran, Faculty of Agriculture, Shiraz University, pp. 284-285. (Persian)
  24. Shakeri Bostanabad, R. and Salehi Komroudi, M. (2020). Factors affecting the growth of iran's agricultural sector: applying the Bayesian model averaging approach. Iranian Journal of Agricultural Economics and Development Research, 51(3): 451-467. (Persian)
  25. Tesgera, W.D. (2019). Access of credit and factors affecting loan repayment performance of smallholders in Nekemte Town East Wollega Zone of Oromia Regional State. Journal of World Economic Research, 8(2): 40-48.
  26. Turvey, C.G. and Brown, R. (1990). Credit scoring for a federal lending institution: the case of Canada's Farm Credit Corporation. Agricultural Finance Review, 50: 47-57.
  27. Youssef, S. and Rebai, A. (2007). Comparison between statistical approaches and linear programming for resolving classification problem. Paper Presented at the International Mathematical Forum,  2(61-64): 3125-3141. DOI: 12988/imf.2007.07288.
  28. Zhang, Z., Gao, G. and Shi, Y. (2014). Credit risk evaluation using multi-criteria optimization classifier with kernel, fuzzification and penalty factors. European Journal of Operational Research, 237(1): 335-348.