Iranian Agricultural Economics Society (IAES)

Document Type : Research Article

Authors

Ferdowsi University of Mashhad

Abstract

Introduction: The role of credits in agricultural development is very important, especially after implementing land reform and converting subjects to a large class of small owners, the demand has been intensified. Seasonality of agricultural productions usually creates temporary vacuum among farmers payments and receipts, thus farmers need to save their previous incomes or seek financial help out of the sector in order to pay current expenses and investments in agriculture sector. Due to farmers low income, the saving possibility is low and therefore farmers are not in a situation that they can invest in agriculture sector from their savings or to purchase required inputs
Materials and Methods: The aim of this study was to prioritize the factors affecting the delay and lack in repaying loans, therefore at first it should identify the payment factors. This means that one should find what factors are affecting the lack or delay in repayment of loans granted to farmers. So the factors affecting the delay or failure to repay the loans were identified by using the Delphi method and then prioritizing the factors will be discussed with regard to experts perspectives by using the analytical network process model.
Analytical network process (ANP) is one of the most efficient techniques for decision making with multiple criteria that it was proposed by Thomas Almaty for the first time in 1982 and as the developed form of AHP method. In cases where lower levels affect the upper levels or elements in a same level are not independent of each other, AHP method cannot be used. ANP technique is a more general form of AHP, but it does not require the hierarchical structure and therefore it show more complex relationships between different levels of decision in network form and it considers the interactions and feedbacks between criteria and alternatives. In fact the main objective of this process is to determine the overall impact of all factors in the face together.
Results and discussion: In the study, factors affecting repayment were divided into the five categories, including farmers, the rules of bank loan payment, banking laws, the government and Jihad agricultural organization . In farmers sector, the farmers primary earned cash had weight of 0.3 out of 1 among five variables. The second stage is the farmers experience which has allocated the weight of 0.23 percent itself. Project failure is located in the third rank. The duration of project restoration and farmers activity volume has less weight than other variables. The results in section of rules of bank loan payment showed that lobbying in bank is in the first place with weight of 0.28. Insurance Fund was also one of the factors that its lack causes lack of immediate repayment of the loans. About bank laws, deep court sentences also were among the factors that its lacking may lead to delay or failure to repay loans. This variable with the weight of 0.2 is among variables affecting on the loan repayment. Long process of enforcements is a factor that in bank experts perspective, it has weight of 0.19 percent compared to other variables. Experts specialties has little weight compared to the other variables. Agriculture-related factors suggested that the accuracy and frequency of visits from project are the most important variables among agents. Preventing the failure of the project is among the factors that had allocated the weight of25% to it. The focus of special funds is among factors that have allocated the weight of 20% to itself that it be considered as an important factor. Jihad agricultural experts specialty and lobbying are the factors that are not of high importance and they are in grades 4 and 5. Agents related to government that effect the loan repayment according to the results also indicated that attention to relations in the macro-level and lobbying have high impacts on non-repayment of the granted facilities. In Agricultural Bank experts views, the repayment extending policy is among the factors that cause to non-repayment of the granted facilities. This variable has the weight of 25 percent among the other variables. Interest and inflation rates are the factors that have common weight in non-repayment of the granted facilities.
Conclusions: The results showed that in bank experts views, banking laws are the most important criterion that affects the absence or delay in repayment of installments. Experts believe that if the banking system strongly enters into financial markets, it will contribute to the development of national economy. Accordingly, it was determined that lobbying in bank is the most important variable of banking laws subset, and it is the most effective factor on the lack and delay in repayment of loans. It means that if the banking legislations is performed correctly and enforced, then the payment of loans is timely and will ease the problems of lack of timely payment. On the other hand, according to bank experts, including measures that affects the delay and lack in timely payment. If the farmers have proper cash and sufficient experience in their own field, they can be successful in the timely payment.

Keywords

1- Adams D.W., and Graham D.H. 1981. A critique of traditional agricultural credit projects and Policies. Journal of development Economics, 8(3): 347-366.
2- Ahmadi N. 2010. Review Delphi. Journal of Social Sciences, No 22: 100-108, (in Persian)
3- Al-Sharafat A., Qtaishat, T., And Majdalawi, M. 2013. Loan repayment performance of public agricultural credit agencies: Evidence from Jordan. Journal of Agricultural Science; Vol. 5, No. 6: 221-229.
4- AsliSh. 2012. Look at the pattern of payment with credit risk management in other countries. Research and Risk Control Department, Bank Sepah (in Persian with English abstract).
5- Azar V., and Rajabzade, A. 2003. Practical decision. NegaheDanesh Publication, Tehran, (in Persian).
6- Bagheri M., Najafi, B. and Moazezi, F. 2006. Factors affecting agriculture credit defaults: A case study in Fars province. Iranian Journal of Agricultural Sciences, No38: 81-90 (in Persian with English abstract)
7- Child M.N. 2008. The effect of a depressed economy on agricultural sector. Journal of African Studies, Vol 3, No. 2: 152-167.
8- Dagdeviren M., and Yuksel, I. 2008. A fuzzy analytic network process model to identify behavior risk (FBR) in Work System. Safety science, 46: 771-783.
9- Godsipour H. 2007. Issues in multi criteria decision making (analytical hierarchy process). Amirkabir University, Tehran (in Persian).
10- Helmer O., and Rescher, N. 1959. On the epistemology of the inexact science. Management Science, 6, 25-53.
11- IrannejadZh. 1997. Of credit and investment in agriculture. Planning and Agricultural Economics Research Institute, Tehran (in Persian).
12- Khavari M. 2012. Depending on the analysis of monetary policy and banking policy and regulatory year 2012. Proceedings of the Twenty- Second Conference on Islamic Banking. Institute of Banking Publications, pages 3 to 19 (in Persian).
13- Kurttila M., Pesonen, M., Kangas, J. and Kajanis, M. 2000. Utilizing the analytic hierarchy process in SWOT analysis: A hybrid model and its application to a forest certification case. Forest Policy and Economics, 1: 41-52.
14- Mahmoudi N. and Sharifi, H. 2014. Investigate the causes and factors contributing to the lack of quick repayment facilities at the National Bank of. First National Conference on Economic Outlook's email, with the support of the national approach (In Persian).
15- Meade L.M. and Sarkis, J. 1999. Analyzing organizational project alternative for quickmanufacturing processes: An Analytic Network approach. International Journal of Production Research, 37(2): 241-261.
16- Mehmood Y., Ahmad M. and Anjam M.B. 2012. Factors Affecting Delay in Repayments of Agricultural Credit; a case study of district Kasur of Punjab province. World Applied Sciences Journal 17 (4): 447-451.
17- Ostadi H., and Alizade A. 2010. Explore ways to support the formation and development of cooperatives through bank lending, case study Kohkiloye and Boyer-Ahmad province. Journal of Cooperatives, No 206:58-47 (in Persian)
18- Powell C. 2003. The Dephlie Technique: myths and realities. Journal of Advanced Nursing, 41(4), 376-382
19- Ronaghi H., 1997. Remedy the shortcomings of the agricultural sector. Monthly political - economic data, year 10, No. 5 (in Persian).
20- Saaty T.L., 1980. The Analytic Hierarchy Process. McGraw-Hill, New York.
21- Saaty T.L., 1996. Decision making with dependence and feedback: The analytic network process. RWS Publications, Pittsburg.
22- Saaty T.L., 2004. Fundamentals of the ANP: Dependence and feedback in decision making with the single networks.Journal of System Science and System Engineering, 13 (2): 1-35.
23- Saaty T.L., and Eczeel, B. 1986. Axiomatic foundation of the analytic hierarchy process. Manage Sci. 32(7): 16-32.
24- Varmarzyari H., Kalantari, Kh. and Shabanalifami, H. 2014. Analysis of factors affecting the use of bank loans (about: city of Khoy). Journal of Rural Studies, Issue 4: 83-109 (in Persian with English abstract).
25- Wongnaa C.A., and Awunyo-Vitor, D. 2013. Factors affecting loan repayment performance among yam farmers in the Sene District: Ghana. Agris on-line papers in economics and informatics, 5(2): 111-122.
26- Yasori M., 2008. Introduction to the rural economy, with emphasis on the agricultural sector. Mashhad: Behnashr (In Persian).
27- Yazdanbakhsh S., and Shahnoushi, N. 2012. Factors affecting the production of food and beverage Khorasan. Master's thesis, Agricultural Economics, University of Mashhad (in Persian with English abstract).
28- Yazdani S., 2004. Review on performance, features and agricultural credit policy in Iran and other developing countries. Proceedings of the Second Symposium of Agricultural Economics, College of Agriculture, Shiraz University, 243-231 (In Persian).
29- Zeller M., 1994. Determinant of credit rationing: A study of informal lenders and formal credit groups in Madagascar, World Development, 22(12): 1895-1907.
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