Factors Effective in Farmers' Access to Agricultural Credit in Sistan Region

Transcription

1 Applied mathematics in Engineering, Management and Technology 2 (4) 2014: Factors Effective in Farmers' Access to Agricultural Credit in Sistan Region Abstract Keywords: agricultural credit, Sistan region, Logit model Fariba Miri * * MSc in Agriculture Economic and lecturer azad university of Zabol According to the significance of farmers' access to credit, in this study the factors effective in farmers' access to agricultural credit has in Sistan Region has been investigated by means of Logit model. The data and information required in this study were obtained by completing of questionnaire by farmers in this region in the crop years; to this end, by means of the random sampling method with a sample of 100 individuals, the farmers were interviewed. The results of the study showed that variables of age, the distance from the farm to the bank, number of family members, level of literacy, participation in extension classes and rate of sales are among factors that affect farmers' access to credit. Meanwhile, variables of farmer's age and distance to the bank have a negative effect and variables of family dimension, level of literacy, participation in extension classes and rate of sales have a positive effect on access to credit and are statistically significant. In the end, according to the results of the study, suggestions have been proposed. 1.Introduction In Iran, the agricultural sector has always been considered as one of the significant sectors of the country's economy in terms of production; yet the level of capital formation in this section is not considerable compared with the performance and capacities of the section and also compared with other sections; thus, the successful transition of the agricultural sector from the peasant and traditional agricultural situation into the trade and modern agriculture, specifically after implementation of land reforms in Iran and turning peasants into retail owners, reveals the need for more investment specifically investment for technological changes; but this investment requires an optimal use of the capital factor. As most technological forms require investment and smallholding farmers can't afford to provide it, therefore off-farm investment is needed so as to provide necessary facilities for technological change. This is why credit facilities of formal institutions are expected to be a proper means for the transmission process and acceleration in agricultural development, and are used as the basic factor for modernization and conformity with the new technology. Numerous factors have been stated for lowness of the production level and income of farmers in developing countries the most important of which, that has been confirmed by development policy-makers as the deterring factor in the course of accepting new technologies by smallholding farmers and transmission of traditional agriculture, is lack of capital and credit (1). Seasonality of agricultural productions has also led to the creation of a gap between agricultural payments and receipts. Farmers in developing countries also are not capable of saving money due to the low level of production and income, and this clarifies the need for using credit. Credit causes the farmer to remove his financial limitations and buy the inputs to an appropriate degree; thus, credit leads to allocative efficiency. Credit leads to purchase of technological facilities and to be precise, increases technical efficiency; credit makes it possible to better use fixed inputs such as land, family work force and economic features of the farmer, and therefore indirectly leads to an increase in production (2). in case required credit are lost or lacked, the farmer has to save part of his income after the harvest season; thus, consumption and investment decrease and the investment power of the farmer in infrastructural affairs are also reduced; therefore, short-term credit for provision of current costs, and average and long-term credit for provision of investment facilities of the agricultural infrastructure play a significant and basic part. Due to the significance of the issue, in this paper identification of factors effective in farmers' access to credit in Sistan region and personal and economic 409

2 features of the farmers have been investigated and the obstacles existing in the process of loan reception have been studied. 2.Research Background Khalid YusefKhalaf Allah (2003) in an econometric analysis, investigated the demand for loan in Sudan under Islamic laws, and by analyzing the factors effective in families' participation in rural informal markets, estimated the demand function for loan by means of type III Tobit model. His findings show that families' participation in credit markets is severely affected by economic situation and social properties such as the size of farm, training and interest rate. Petrick (2002), in his study in an econometric analysis, has investigated the effects of access to credit on the behavior of agricultural investors by means of Tobit model. The results of his study indicate that access to cheap credit (sponsored) has a determining and significant role in behavior of agricultural investors and the final effects of the credit on investment have been obtained to be smaller than one which means that credit has been partly deployed for objectives other than capital productivity; but on the whole, the results show that increase of credit leads to increase of the final effect; therefore, for growth in productivity, it is proposed that loans be given in high volumes without discrimination among small and big farmers. Rogue (2002) in studying the effects of access to credit on the behavior of investors using standard models, shows that higher access to credit not only reduces the total savings, but also reduces precautionary motive for saving, accumulation of saving for investment, family purchase or sudden consequences; also, higher access to credit leads to the transfer of people's savings from livestock and other low-yield or no-yieldactivities into high-yield savings accounts. Hussaini et al. (2008), have conducted a study with the objective of evaluating the effect of transaction costs on farmers' access to formal credit markets. The data used in this study have been collected by the two-stage random cluster sampling method among a sample of 459 villagers of the four Khorasan, Mazandaran, East Azerbaijan and Lorestan provinces in After the descriptive study of the sample, by means of the Logit econometric model the effects of factors effective in farmers' access to formal credit market, specifically the effect of transaction costs, have been estimated and investigated. The research findings showed that closeness to credit institutions, people's awareness of the bank system and credit centers and also membership in loan funds and cooperatives, as an index of the transaction costs, increase the probability of people's access to the formal credit market. The final results indicate that the transaction cost, as an important limiting factor in villagers' access to the formal credit market must be taken into consideration. Kohansal et al. (2007), according to the significance of the financial provision of farmers in Khorasan Razavi province in the production and investment process in the agricultural section and with the objective of investigating the factors effective in access to credit, conducted a survey study in 2007 on farmers in the two groups of loan borrowers and non-borrowers using the discriminant analysis model. In this study by means of interview with the farmers of the four towns of the Khorasan Razavi province, 177 questionnaires were completed. The results obtained from the estimate of the discriminant analysis showed that variables of number of loan receptions, record of using facilities and number of installments of the last received loan have the highest importance in the distinction between the two groups of loan borrowers and non-borrowers. Based on the results of the study, provision of a credit profile including a collection of data concerning the credit situation of the farmer and creation of proper incentive system for customers with no untimely repayment record was proposed in order to increase productivity and decrease poverty in agricultural section. According to, Hashemi Tabar et al. (2004) due to the capability of changing into other factors, capital has a very significant role in the production process. Also accurate deployment of capital and its combination with other inputs lead to the an increase in productivity of production factors. As the capital makes it possible to deploy adequate and proper inputs for production, necessity of capital formation and its provision can't be questioned. In the agricultural section of Sistan and Baluchestan province, due to the existence of structural constraints and shortage of facilities required by farmers, the issues related to capital and investment are of higher importance. In this study by investigating 180 farmers in Sistan and Baluchestan province, using the Tobit model the factors effective in access to agricultural credit and the role of the credit in agricultural production have been analyzed. The results indicate that factors such as cultivated area, number of family work 410

3 force, and having a saving in the bank are effective in agricultural credit and the credit has a positive role in production as well. 3.Materials and Methods This study is aimed at investigating the factors effective in farmers' access to agricultural credit in Sistan region. Different methods have been proposed in order to achieve this goal. The most common method for measuring the effect of credit is to compare farmers in a time period in the form of two groups of loan borrowers and non-borrowers. In this regard, methods which have been so far proposed are as below: 1- F-test and t-test 2-Discrimination analysis tests 3-The single equations include kinds of production and supply and profit functions The pre-supposition that exists in the aforementioned methods is that farmers in the groups of loan borrowers and non-borrowers are homogeneous and have similar features in terms of social and economic characteristics; while in practice the farmers in the group of loan borrowers may have differences with farmers in the group of non-borrowers who can use more efficient production factors even without receiving a loan (8). Therefore, as these methods can't distinguish between these features and the characteristics resulting from credit, they can't be used; also, as single equation methods only consider physical inputs, they aren't used either. In this study, the investigation of factors effective in farmers' access to credit is estimated by means of the statistical method and econometric models. The econometric model including the dependent variable of zero and one includes the three linear probability, Logit and Probit models. Therefore, it is attempted to investigate these factors and their effect using Regression models with the qualitative dependent variable (Logistic Regression). As stated by Logit and Probit econometric models are preferred to the linear probability model and are proper for estimate of such models. In this study, in order to evaluate the factors effective in the farmer's access to credit, the Logit econometric model will be used. The information and data required for this study are obtained by random sampling in The sample selection method is such that first in the Sistan and Baluchestan province, the Sistan region is selected and among thecities of this region, the two cities of Abol and Zahak have been selected. The reason for selection of these two highly populated cities is having the most farmers and also the highest number of farmers that have received loans. In the subsequent stage, a few sections of each city were randomly selected and eventually 22 villages were selected by simple random method. In the last stage, a sample of 100 farmers was selected and they were interviewed via questionnaire; among this number, 70 farmers have received credit and 30 farmers haven't received bank facilities. The total form of the Logit model is as below: Y=F(X 1,X 2,X 3,..,X n ) The variables used in this study include: (Y) (Dependent variable): it is a qualitative and discrete variable that shows the farmer's inclination toward getting a loan. The measure of (Y) is between one and zero. (X) (Independent variable): they are variables that affect the farmer's access to loan. The Regression model that is used in this study is as below: (1) y = α + βx + βx + x u 1 2 β 3 In this model, the probability of farmer k being able to attain bank credit depends on come factors. p ( ) (2) k = f z k z (3) k = α + βk + xk + uk In which p k is the probability of the farmer's attainment of credit. Z k is obtaining or not obtaining loan (access to loan=1, no access to loan=0). are the equation parameters.βand α x 1,x 2,x 3,x 4,x 5,x 6,x 7,x 8 x i = these can be the variables effective in access to loan by farmers. The variables include: X 1 : the age of farmer (year) X 2 : cultivated area 411

4 X 3 : family dimension X 4 : level of literacy X 5 : participation in extension classes X 6 :rate of sales X 7 : level of risk X 8 :distance to the bank (kilometer) Applied mathematics in Engineering, Management and Technology 2014 Diversity of cultures is one of the indexes of risk. The more the diversity of cultures is, the few the production risk, and failure in production of a product may be partly compensated successful in production of the others. Diversity of cultures has a considerable effect on capability of farmers in dealing with risky conditions such as draught, cold, price variations, etc. The risk variable X 7 = diversity of cultures X 7 = D= number of products in a crop year In the Logit model, the probability of farmers' access to loan is calculated as below: 10 1 pk = f ( zk ) = f α + Bk X K = ((4) e ZK i= 1 1+ And the probability of non-access to loan is obtained of the following relation: 1 1 (5) 1 P K = = zk xkbk 1+ e 1+ e By taking the partial derivative from the relation (5) regarding each of the explanatory variables, the final effect of that variable on the probability of the farmer's access to the credit is obtained: zk pk βie = z 2 xk ( 1+ ) (6) e k Conclusion and Discussion In order to investigate the factors effective in access to credit in Sistan region, by means of the Logit function with the dependent variable of loan reception and non0reception, the independent variables of age, level of education, participation in extension classes, cultivated area, number of family members, distance to the bank, risk and sales rate have been estimated and the results of the estimated Logit function are shown in table no.1. Table1: the estimated coefficients by Logit function variable coefficient Z-statistic Final effect C intercept X 1 Age (year) 10.0 ** X 2 Cultivated area (hectares) X 3 Family dimension (member) 62.0 ** X 4 Level of literacy 15.0 * X 5 Participation in extension classes 85.0 ** X 6 Sales rate (rial) 10.0 *** X 7 risk X 8 Distance to bank (kilometer) 64.0 ** MF R The results presented in table (5-10) indicate that the variables of age, number of family members, level of literacy, participation in extension classes, distance to the bank and sales rate have been identified as effective 412

5 factors. Also, the signs of the model variables such as age, level of literacy, participation in extension classes, sales rate, risk and distance to the bank are in accordance with theory but the variables of cultivated area and family dimension are obtained as contrary to the hypotheses since the increase in the level of cultivated area was expected to have a positive effect and the family dimension was expected to have a negative effect on the farmer's access to loan. According to the results of the table, the age coefficient sign is as expected and is statistically significant. Based on this, the relationship between the age of farmer and access to loan has been negative and when the age of the farmers increases by one year, the probability of their access to loan credit decreases. Also, according to the final effect of this variable (-0.113), it can be said that in case the age of farmers increases by one year, the probability of their access to credit decreases by 13.1%. The coefficient of the cultivated area is negative as well and it indicates that by an increase in the cultivated area the probability of the farmers' access to bank credit decreases. However, the coefficient of this variable is statistically insignificant. The variable coefficient of the family dimension is positive and statistically significant and the aforementioned variable coefficient refers to the fact that if the family dimension increases, the probability of farmers' access to loan increases as well and also according to the coefficient of the calculated final effect (0.790), it can be said that when a member increases in the family dimension, the probability of the farmers' access to credit increases by Also, variable coefficient of literacy of farmers is also positive and significant and is in line with the research hypothesis. The variable coefficient stated means that when the literacy level of farmers is higher, the probability of their access to the credit increases; in addition, according to the coefficient of the calculated final effect (0.192) it can be asserted that when the farmers are literate, the probability of their access to credit increases by 19.2%. The coefficient sign of participation in extension classes is as expected since when farmers participate more in extension classes, the probability of their access to credit increases and this coefficient is statistically significant. According to calculated final effect coefficient (0.107), it can be said that in case the participation in extension classes increases, the probability of their access to loan increases by 10.7%. Also, the coefficient sign of the sales rate is as expected since when the sales rate of farmers increases, the probability of their access to bank credit increases; additionally, this coefficient is statistically significant. According to the calculated final effect coefficient for sales rate (0.132), it can be said that when the sales rate is increased by a million rials, the probability of the farmers' access to the credit increases by 13.2%. The coefficient sign of risk is also in line with theory and is positive and indicates that when the risk level of farmers is higher in the region under study, the probability of the farmers' access to the bank credit increases. Nevertheless, this coefficient is not statistically significant. The coefficient sign of the variable of distance to the bank is also as expected and negative and is also statistically significant since when the distance from the farm to the agricultural bank is more, the level of access to credit decreases for the farmer. According to the calculated final effect coefficient for the distance to the bank (-0.819), it can be stated that when the distance to the bank is increased by one kilometer, the probability of the farmers' access to the credit decreases by 81.9%. In the estimated model, the intercept is not significant; also, the profitability of the model fit is also acceptable and equal to 85%. Conclusion and Suggestions Due to the capability of changing into other factors, capital has a very prominent role in process of agricultural productions. In agricultural section of Sistan region due to the existence of structural constraints and shortage of facilities required by farmers, the issues related to the capital and investment become more prominent. In this study by investigating 100 farmers in Sistan region by means of Logit model, the factors effective in access to agricultural credit are analyzed. The statistics and data required for this study were obtained by completion of the questionnaire by farmers of this region in the crop year The random sampling method for selection of farmers has been deployed. In this study, first by investigating the situation of credit in agricultural section, the method of its distribution in the agricultural section of Sistan region and also province and the country was examined; subsequently, using econometric models, the factors effective in access to farmers' credit in this region were studies. The results obtained from this study show that in the sample under study 66.3% of the farmers have received their required loan from formal resources and 33.7% from informal resources. Also, by investigating the results obtained from estimate of the Logit function, we realize that variables of age, distance of farm to bank, family dimension, level of literacy, participation in extension classes and sales rate are factors that affect the farmers' access to the credit. The variables of the farmer's age and distance to the bank have a negative and statistically significant relationship with access to credit such that increase in the distance of the farmer to the bank leads to an increase in side costs of loan reception such as transfer cost and also a reduction in farmer's access to the credit. The variables of family dimension, level of 413

6 literacy, participation in extension classes and sales rate are positive effects and statistically significant, such that an increase in farmers' level of literacy and awareness, increases farmers' access to credit as well. As regards the results obtained, the following suggestions can be proposed: 1- As the comparison between loan-borrowing farmers and the farmers that haven't borrowed loans shows that the latter group is mostly comprised of smallholding farmers, creation of a small credit system for payment of loan to this group of farmers is suggested. 1- According to the positive relationship between risk and loan reception, insurance development of products and establishment of income insurance are proposed. 3- According to the direct relationship between level of literacy and loan reception, expansion of formal teachings and literacy is recommended. 4- According to the effect of extension teachings and sales rate on access to loan, expansion of extension services that can lead to more production and income is suggested.. 5- According the existing problems concerning the long waiting time and high side costs of loan adoption, reduction of bureaucracy and simplification of the formalities for loan reception are recommended. 6- According to the existence of an inverse relationship between access to loan and distance to the bank and costliness of expanding the bank branches in rural regions, use of the rural cooperative branch and specifically cooperatives in villages are proposed as agricultural bank agents. The enclosed tables Table 2: comparison of the granted facilities of agricultural bank of the province and the region (a thousand rials) l share of province Share of region percentage Table 3: granted facilities of agricultural bank regarding the type of resource (billion rials) l assigned unassigned total Total

7 References Applied mathematics in Engineering, Management and Technology 2014 Table 4: granted facilities by agricultural bank, central branches ( ) (million rials) Type of payment number amount Establishing greenhouse Establishing livestock place establishment of aviculture agriculture rural housing Other projects total Hosseini, p. Khaledi, M.. (2010), "Evaluating the effect of transaction costs on farmers access to formal credit markets in Iran," Agricultural Economics and Development No Mir, J. HashemiTabar, M.. (2005), "Factors Affecting Access to agricultural credit and its role in the production: A case study of Sistan and Baluchestan." 3. Salami,.H And Tarshizi, M.. (2008), "Factors Affecting Soil Conservation Measures: A Case Study of Khorasan Razavi" 4. Ghorbani, M., et al. (2007), "Factors Affecting Farmers' Investment in soil conservation in Khorasan Razavi", Mashhad Ferdowsi University Research Initiative. 5. Koopai, M.. Bakhshi-M. (2002), "The application of discrimination analysis: A case study in Birjand city", number one, (19-11). 6. Ahmadpoor, M.. (2003), "Factors affecting demand for agricultural credit in Sistan", research project, University of Zabol. 8. Adams, D.W. and graham, D.H. (1981), "A critique of traditional agricultural credit projects and policies", journal of development economics, 8(3): Agner, D.J. Lovell, C.A.K. and Schmidt, P. (1977), "formulation and estimation of stochastic frontier production function models", journal of econometrics, 61: Amemiya, T. (1984), "Tobit models: A survey", journal of Econometrics, 24: Anderson, J. (1990), "rural credit and the mix between permanent an temporary wage labor contracts in pernambuco Brazil", American journal of agricultural Economics, 72(5): Battese, G.E. and Coelli, T.G. (1989), "Frontier production technical efficiency panel data", journal of production Analysis, 3(1): Battese, G.E. and coelli, T.G. (1993), A stochastic frontier production function in corpora ting a model for technical inefficiency effects", Working papers in Econometrics, University of New England, Amidala. 14. Belonged, M.T. and Gilbert, R.A.(1990)," The effects of federal credit programs on farm output, American journal of Agricultural Economics, 72(3):