اولویت‌بندی و تخصیص بهینة اعتبارات بانک کشاورزی به تفکیک استان‌ها

نوع مقاله: مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری گروه اقتصاد کشاورزی، دانشگاه آزاد اسلامی، واحد علوم و تحقیقات تهران

2 استادیار گروه اقتصاد کشاورزی، دانشگاه آزاد اسلامی، واحد علوم و تحقیقات تهران

3 دانشایر گروه اقتصاد کشاورزی، دانشگاه آزاد اسلامی، واحد علوم و تحقیقات تهران

چکیده

بانک کشاورزی اصلی‌ترین نهاد تأمین مالی بخش کشاورزی ‌است. با توجه به محدودیت منابع بانکی، هدف این مطالعه اولویت‌بندی و تخصیص بهینة اعتبارات بانک کشاورزی در استان‌هاست. بدین منظور، ابتدا شاخص‌های مرتبط با اولویت سرمایه‌گذاری تعریف و برای دورة زمانی 90-1389 محاسبه شد[1]، سپس با استفاده از روش آنتروپی، وزن شاخص‌های مذکور برای اولویت‌بندی تعیین و روش تاپسیس برای اولویت‌بندی زیربخش‌های کشاورزی در استان‌ها به کار گرفته شد و در نهایت، از روش برنامه‌ریزی آرمانی برای تخصیص بهینة اعتبارات استفاده شد. نتایج تحقیق نشان داد که در بیشتر استان‌ها، اولویت‌های سرمایه‌گذاری به ترتیب عبارت اند از: زیربخش زراعت و باغبانی، دام و طیور،  شیلات و جنگلداری. نتایج برنامه‌ریزی آرمانی نشان داد که در حالت کلی، تخصیص اعتبارات در بانک کشاورزی بهینه نیست و در صورت تخصیص بهینه اعتبارات، حدود 9/56 درصد اعتبارت به زیربخش زراعت و باغبانی، 1/39 درصد به زیربخش دام و طیور، 7/2 درصد به زیربخش شیلات و آبزیان و 3/1 درصد به زیربخش جنگلداری اختصاص خواهد یافت.



[1]. مطالعه مذکور در سال‌های 1393-1394 انجام گرفته ولیکن با توجه به اینکه  آخرین داده‌ها مربوط به سال 1390 است، مطالعه بر مبنای آن انجام شده است.

کلیدواژه‌ها


عنوان مقاله [English]

Prioritization and Optimal Allocation of Agricultural Bank Credit in Separate Provinces of Iran

نویسندگان [English]

  • R. Mohsen Pour 1
  • A. Mohamadi-Nejad 2
  • R. Moghaddasi 3
1 PhD Student, Agricultural Economics Dep., Science and Research Branch, Islamic Azad University, Tehran, Iran
2 Assistant Professor, Agricultural Economics Dep., Science and Research Branch, Islamic Azad University, Tehran, Iran
3 Associate Professor, Agricultural Economics Dep., Science and Research Branch, Islamic Azad University, Tehran, Iran
چکیده [English]

Bank Keshavarzi (BK) is considered as the major financial entity in financing agricultural sector. Due to limitations in accessible resources, objective of this study is prioritizing and optimal allocating of agricultural credits in Iran. For this purpose, the relevant indices of investment priorities are defined and calculated. Then, by utilizing Entropy technique, the weights of mentioned indices are determined and by the use of Topsis method, the agricultural subsectors prioritized in provinces separately. Eventually, the goal programming is used for the optimum allocation of credits. The results showed that in most provinces, investment priorities are as follows, respectively: farming and horticulture, livestock and poultry, fisheries and forestry. In general, according to the goal programming results, the credit disbursement in BK is not optimal; by assuming the optimality, about 56.9 percent of such credits will be allocated to farming and horticulture, 39.1 percent for livestock and poultry, 2.7 percent and 1.3 percent for fisheries and forestry sub sectors, respectively.

کلیدواژه‌ها [English]

  • Credit
  • Prioritization
  • Optimal allocation
  • Bank Keshavarzi (BK)
  1. Abedi, Q.,  Delgushaei, B., Tabibi, S. J.  and Arianejad, M. B. GH. (2007).  The Ideal Planning Model for Resource Allocation in the Educational, Academic Department of the Ministry of Health and Medical Education. Journal of Mazandaran University of Medical Sciences, 17 (57): 87-82. (Persian)
  2. Akbari, N. and  Moradi, Z.  (2008).  Economic review and prioritizing industrial investment in kurdistan province. Journal of Humanities and Social Sciences of Economic Sciences, 8 (3): 58-33. (Persian) 
  3. Amini, A. R.  and  Haji  Mohammad, N. (2005). Estimation of the time series of capital inventory in the Iranian economy during the period 1959-2002. Plan and Budget, 90: 86-53. (Persian)
  4. Annual Report of the Agricultural Bank.  Different years. Agricultural Bank Publications. (Persian)
  5. Arab Mazar, A. and Khademian,  S. (2013). Priority of investment in Iran's Agricultural Sub-divisions. Agriculture and Development, 21 (82): 43-27. (Persian)
  6. Asgarpour, M. J. (2008).  Multiple criteria decision making.Tehran. Tehran: University Publication. (Persian) 
  7. Asghari, M.  (2011). Agricultural development priorities using Multi-criteria MCDM decision making decision: A case study agriculture division of  isfahan province.  Economic Studies of  Wisdom Path , 1 (1): 121-89. (Persian)
  8. Bakhtiari, S. and Pasban, F. (2004).  Role of  bank credits in the development of Job opportunities: A case study of Iran's Agricultural Bank. Agricultural Economics and Development, 46: 73-104. (Persian)
  9. Behkish, M. (2002). What is the economy?. Tehran: Nashr Nei Publications. (Persian)
  10. Boghizan, A. (1992).  Estimation of capital stock in major economic subdivisions (1959-1977). Master  Thesis of Economic,  Faculty of  Economics and Political Science, University of  Shahid Beheshti. (Persian)
  11.  Bulgurcu , B. (2012). Application of TOPSIS technique for financial performance evaluation of technology firms in Istanbul stock exchange market.  Social and Behavioral Sciences, 62: 1033-1040.
  12. Caplin, D. A.  and Kornbluth, J. S. H. (2004). Multi objective investment planning under uncertainty. Omega, 3(4):423-441.
  13. Colson, G. (1989). Models and methods in multiple objectives decision making. Math. Comput. Modeling, 12: 1201–11.
  14. Darvish Motawali, M. H., Darvish Motawali, M. and Esfandyar, M. (2010). Presenting an  appropriate mathematical model for resource allocation resources Case Study: Islamic Azad University of Firoozkooh Branch. Researcher, 2:95-102. (Persian)
  15. Debertin, D. ( 1997). Agricultural production economy.  Translation by Musinjad, M. GH and Najarzadeh, R. Tehran: Tarbiat Modares University Publications. (Persian)
  16.  Dong, F.,  Lu, J. and   Featherstone, A. M. (2012). Effects of credit constraints on household productivity in rural China. Agricultural Finance Review, 72 (3):402 – 415.
  17. ElSheikh, R. F.A.,  Ahmad, N., Shariff, A.R.M., Balasundram, S.K. and Yahaya, S. (2010). An agricultural investment map based on geographic information system and multi-criteria method. Journal of Applied Sciences, 10: 1596-1602.
  18. Emam Meybodi, A. (2005). Efficiency and  productivity measurement (in theory and practice). Tehran: Institute for Business Studies and Research.  (Persian)
  19. Farzin Motamed, A. (2005). Assessing the effectiveness of granting grant of agricultural bank on investing and employment in agriculture. Master  Thesis of Economic. Islamic Azad University, Science and Research Branch. (Persian)
  20. Firouzjaya,  R. (2008).  Study  the effects of agricultural bank credits on the value added of agricultural and livestock subsectors of agricultural sector. Master  Thesis of Economic. Mofid University of Qom. (Persian)
  21. Hwang, C. L. and Yoon, K. L. (1981). Multiple attribute decision making: methods and applications. Springer-Verlag, New York.
  22. Hui, Y.T., Bao, H. H. and Siou, W. (2008). Combining ANP and TOPSIS concepts for evaluation the performance of property-liability insurance companies. Science Publications. Journal of Social Sciences, 4 (1): 56-61.
  23. Jao, Y. C. (2001). Linear programming and banking in Hong Kong. Journal of Business Financial and Accounting,7(3): 49-500.
  24.  Karimi, M. S., Yusop, Z. and Hook Law, S. (2010). Location decision for foreign direct investment in ASEAN countries: a TOPSIS approach. International Research Journal of Finance and Economics, 36: 196- 207.
  25. Karimi, F. and Zahedi Keyvan, M. (2010). Optimal allocation of bank credits to applicants in different agricultural sectors by fuzzy logic. Research and Economic Policies, 18 (56): 72-53. (Persian)
  26. Khandker, Sh. R. and Faruqee, R. R. ( 2003). The impact of farm credit in Pakistan. Agricultural Economics, 28(3): 197-213.
  27. Mohaghar, M. A., Saremi, M. and  Manzari Hesar, M. (2006).  Applying the appropriate mathematical model  in order to  allocate the  provincial development credits of  the budgets' chapter   to the cities of Khorasan province. Management knowledge, 19 (72): 86-63. (Persian)
  28. Mohammadi,  M. (2009). Evaluation of the effect of  bank credits on export and production of agricultural products (1984-2006). Master  Thesis of Economic. Mofid University of Qom. (Persian)
  29. Momeni, M. (2013). New research topics in operations. Tehran:  Moallem Publishing. First edition. (Persian)
  30. Nasabian, Sh. and Nawparast, F.  (2010). Ranking of provinces for investment in agriculture in Iran. Economics Quarterly, 3(10): 128-115. (Persian)
  31. Performance Report of banking system in 2012 and previous years.  (2012). Tehran: The Central Bank of the Islamic Republic of Ira Publications. (Persian)
  32.  Pour Taheri, M.,  Sajasi Ghideari, H.  and Sadeghlu, T. (2011). Comparative evaluation of natural risk ranking methods in rural areas (case study: Zanjan province). Rural Research, 2 (3): 31-54. (Persian)
  33. Sadr, K. and Kafaee,  M.A. (2000). Measurement of  the effect of credits granted by the Agricultural Bank on the value added of the agricultural sector. Research and Development Center for Agricultural Bank. (Persian)
  34. Shahbazian, A.  (2010). Study of the effect of agricultural bank credits on the value added of agricultural sector. Master  Thesis of Economic. Islamic Azad University of Firoozkooh  Branch. (Persian)
  35. Shakeri,  A. and Mousavi, M.H. (2003). Investigating factors affecting private and public investment in agriculture. Agricultural Economics and Development, Commercial Publishing, 44-43: 115-89. (Persian)
  36. Tansel  Ic, Y. (2012). Development of a credit limit allocation model for banks using an integrated Fuzzy TOPSIS and linear programming. Expert System Application, 39: 5309-5316.
  37. Tavakoli, A. (2010). Effect of assigned and non-qualitative credit of Agricultural Bank on value added in agricultural Division (2007-2008). Master  Thesis of Economic. Islamic Azad University of Khomeini Shahr Branch. (Persian)
  38. The Yearly Statistics of the Country's Productivity from 2005 to 2012 in Different Sectors of the Economy. (2013). Tehran: The Chamber of Commerce, Industries, Mines and Agriculture of Iran  Publications. (Persian)
  39. Tun Wai, U. and Wong, Ch.h. (1982). Determination of private investment in developing countries. The Journal of  Development Studies, 19: 19-36.
  40. Wang, T. C. and Lee, H. D.   .(2009). Developing a fuzzy TOPSIS approach based on subjective weights and objective weights. Expert Systems with Applications, 36: 8980–8985.
  41. Wang, J. J., Zhang, Ch. F., Jing, Y. Y. and Zheng, G. Z. ( 2008). Using the fuzzy multi-criteria model to select the optimal cool storage system for air conditioning.  Energy and Buildings, 40:2059–2066.
  42. Zahedi Keyvan, M.  and  Khoshbakht,  M. (2009). An effective fuzzy method in assigning lending and facility to Iran export Development Bank. Tenth Conference on Intelligent and Fuzzy Systems of Iran. Yazd University. (Persian)
  43. Zamanzadeh, A. and  Shayesteh, Z. (2010). Assessing and determining the priority of allocating credits to provinces based on the capacity to attract credit. Agricultural Bank. (Persian)
  44. Zhang, H.,  Gu, Ch. L.,  Gu, L.w. and Zhang, Y. (2010). The evaluation of tourism destination competitiveness by TOPSIS & information entropy-A case in the Yangtze River Delta of China. Tourism Management, 32(2): 443-451.
  45. Zhao, X., Qingjie, Q. and Ruifeng, L. (2010). The establishment and application of fuzzy comprehensive model with weight based on entropy technology for air quality assessment.  Symposium on Security Detection and Information Processing, 7: 217–222.