Iranian Agricultural Economics Society (IAES)

Document Type : Research Article

Authors

Sari Agricultural Sciences and Natural Resources University

Abstract

Introduction: Eliminating the deprivation of less developed areas has always been considered as a challenge to the realization of economic and social justice in the country that was not realized due to various reasons such as geographical isolation, imposed war and insecurities, inconsistencies and limiting factors of investment security, and credits. The budget and credit law is one of the most important strategic tools to achieve the goals of each country. Credits are the most important tools for tracking policies and priorities, programing, and modifying activities. Therefore, the proper understanding of this tool and its principled application, as well as the optimal allocation method, is very important. In general, the governments are attempting to allocate the resources optimally and reduce inequalities through optimal programing. Accreditation is regarded as a strategic tool for implementing the government's duties in the economy which can provide a competent and accountable government and promote people's participation. The previous studies indicated that traditional budget allocation patterns are not efficient and appropriate leading to inequality and widening gap between regions. Using traditional accreditation patterns led to the acceleration of inappropriate allocation of spatial areas of population, facilities, infrastructure and investment in Iran. Optimality and efficiency are considered as the most important aspects of budgeting and accreditation, which can improve the financial performance of the government, decrease inequality and increase the level of development in the regions. In this regard, the researchers always attempted to provide a scientific approach based on mathematical optimization methods for the optimal and efficient allocation of financial and credit resources.
Materials and Methods: Goal programing approach was introduced by Charnes and Cooper (7). It was one of the approaches to multi-objective decision-making problems classified as mathematical optimization approaches with multiple targets. This model presented an optimal solution for optimizing the objective function in accordance with the applied constraints based on decision-making atmosphere and developed constraints.
In this method, a certain number was determined for the goal and the related target function was categorized. Finally, the answer minimizing the total weight of each target deviation than the goal determined for the same target was searched. In order to optimize the appropriation of agricultural credits in Kerman province, a goal planning model was designed and presented for achieving the goals. In this method, for each goal, a certain number is assigned to the ideal, then the target function is formulated. Finally, a search result is obtained that the total weight of the deviation of each goal is related to the ideal determined to minimize the same goal. The most important macroeconomic, social and environmental goals including 6 indices: comparative advantage, labor productivity, water productivity, land productivity, fertilizer productivity and mechanization coefficient, respectively were considered for the model. Fuzzy AHP method was used to determine the coefficient of importance of these indices in nine northern township of this province.
Results and Discussion: The results show that to achieve the common goals of different township of the province, it is necessary to allocate more credits to all township, especially Rafsanjan, Sirjan, Shahrbabak, Bardsir and Baft. The reason for such an outcome is the existence of capacity and potential of agriculture in these township. In Kerman, considering the available capacity and potential in agriculture, it is not necessary to use more credits. Thus, allocating credits to the county of Kerman is practically equal to carrying out the project at a higher cost. Nonetheless, other township can certainly and potentially attract more funding at a lower cost. It is worthwhile to say that to achieve the overall objectives of this study, goal programing models for reallocating agricultural credits to the field has been used. In other words, due to existing and available credits, we can plan purposefully and reprogram to achieve higher levels of macro goals in agriculture in Kerman province
Conclusions: Based on the results, the credits allocated in 2014 which was made by law was not balanced. Second, considering ideals, the allocation of available credits is not optimal. Comparing the six considered ideals, all ideals, except the mechanization coefficient ideal which is higher in this situation, were lower; therefore, the present allocation of credits is not optimal. Third, the ideals could be realized if there was a convergent allocation in the agricultural credits (a convergence allocation means using more capacities and potentials in more potent Townships). In other words, the capacities and capabilities of the agricultural activities in these Townships have remained useless due to the lack of awareness and incorrect allocation of credits. Therefore, these potentials can be used with the low cost in order to reduce regional inequality, and make a convergence in the production and employment in Kerman province if a balanced budget and programs agricultural credits related can be launched.

Keywords

1- Anonymous. 2015. Agricultural Statistics. Volume I, Crop and Garden, Crop. (In Persian)
2- Ardestani M., Khaledi K., and Tousi M. 2007. Investigation of internal citrus marketing in northern Iran (case study: oranges). 6th Iranian Agricultural Economics Conference, Mashhad. (In Persian)
3- Azizi J. 2006. Economic evaluation of rice marketing strategies in guilan province. Agriculture Sciences, 4: 715- 728. (In Persian with English abstract)
4- Benedek Z., Ferto I., Barath L., and Toth J. 2014. Factors influencing the decision of small-scale farmers on marketing channel choice: a Hungarian Case Study. EAAE Congress ‘Agri-Food and Rural Innovations for Healthier Societies’. Ljubljana, Slovenia.
5- Biekzadeh P., and Chizari A.H. 2007. Study of marketing channel and effective factors on potato marketing margin. Agricultural Economics and Development, 15 (57): 81-103. (In Persian)
6- Hassanpour B. 2015. An Appropriate approach for Improving the Rice Marketing System and Reducing Its Disasters, Promotional magazine, Ministry of Agriculture Jihad, Tehran (In Persian)
7- Hausman J., and McFadden D. 1984. Specification tests for the multinomial logit model. Econometrica, 52(5):1219-1240.
8- Imran Siddique M. 2015. Factors Affecting Marketing Channel Choice Decisions in Citrus Supply Chain. PhD thesis, Massey University, New Zealand.
9- Martins F., and Carrasco P. 2004. Selection of marketing channels by intensive horticultural crop growers in Almeria. Spanish Journal of Agricultural Research, 2(1): 27-33.
10- Masuku B. M. 2013. Factors effectors he choice of marketing channel by vegetable farmers in Swaziland. Sustainable Agriculture Research, 2(1):112-123.
11- Mburu L M., Wakhungu J. W., and Gitu K. W. 2007. Determinants of smallholder dairy farmers' adoption of various milk marketing channels in Kenya highlands. Livestock Research for Rural Development. Volume 19, Article #134. Available at http://www.lrrd.org/lrrd19/9/mbur19134.htm.
12- McFadden D. 1974. Conditional Logit Analysis of Qualitative Choice Behavior. pp. 105-42 in Frontiers of Econometrics, edited by P. Zarembka. New York: Academic Press.
13- Mojaverian S.M., Rasuli, S.F. Hosseini S.A 2013. Factors affecting the selection of sales channels among Mazandaran citrus producers. Journal of Agricultural Economics and Development, 27 (2): 133-123. (In Persian with English abstract)
14- Mosanzhad M.K., and Mojaverian S.M. 1996. Citrus marketing survey in Babol. Agricultural Economics and Development, 4 (13): 101-118. (In Persian)
15- Mukiama B. K., Suphanchaimatand N., and Sriwaranun Y. 2014. Factors influencing vegetable farmer’s choice of marketing channel in Khon Kaen, Thailand. KHON KAEN AGR.J. 42 (4): 595-604
16- Mzyece A. 2010. Factors influencing cowpea producers’ choice of marketing channels in ZAMBIA, Available at: http://valuechains.k-state.edu/_Agness%20Mzyece.pdf.
17- Noori K. 2006. A Study on market distortions and its effects on rice supply, demand and import in Iran. Pajouhesh and Sazandegi (Agriculture and Horticulture), 73: 17-25. (In Persian with English abstract).
18- Nkwasibwe A. 2009. Determinants of choice of milk marketing channels by dairy farmers in Kiruhura District, Uganda. A Thesis Submitted to the directorate of research and graduate training in Partial fulfillment of the requirements for the Award of the degree of master of Agribusiness management of Makerere University.
19- Pikousova K., and Průša P. 2011. Deterministic factors for choosing of distribution model. Perner´s Contacts , 4(3): 91-97.
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