برآورد ضريب ريسك‌گريزي كشاورزان شهرستان اسفراين و عوامل مؤثر بر آن (رويكرد ناپارامتريك)

Estimation of Esfarayen Farmers Risk Aversion Coefficient and Its Influencing Factors (Nonparametric Approach)

با توجه به ماهیت توأم با ریسك و عدم قطعیت بخش كشاورزی، مطالعه حاضر به منظور بررسی ضریب ریسك‌گریزی كشاورزان شهرستان اسفراین انجام شده است. در این راستا از جدیدترین روش ناپارامتریك محاسبه ضریب ریسك‌گریزی و با بهره‌گیری از مدل برنامه‌ریزی درجه دو (QP) استفاده شده است. بدین منظور داده‌های پانلی 100 كشاورز، طی 4 سال (1388- 1391) و برای 14 محصول جمع‌آوری شده است. نتایج مطالعه نشان داد اكثر كشاورزان منطقه مورد مطالعه دارای درجه ریسك‌گریزی بسیار زیاد و شدیداً ریسك گریز می‌باشند. حق بیمه اجتناب از ریسك كشاورزان نمونه مورد بررسی 303113 ریال به دست آمده است. همچنین متغیر سن تأثیر مثبت و سطح ثروت و تنوع كشت تأثیر منفی بر ضریب ریسك‌گریزی كشاورزان داشته است. با توجه به نتایج به دست آمده توسعه بیمه و سرمایه‌گذاری در زمینه بورس كالاهای كشاورزی به منظور كاهش ضریب ریسك‌گریزی پیشنهاد می‌شود.

Introduction: Due to existence of the risk and uncertainty in agriculture, risk management is crucial for management in agriculture. Therefore the present study was designed to determine the risk aversion coefficient for Esfarayens farmers. Materials and Methods: The following approaches have been utilized to assess risk attitudes: (1) direct elicitation of utility functions, (2) experimental procedures in which individuals are presented with hypothetical questionnaires regarding risky alternatives with or without real payments and (3): Inference from observation of economic behavior. In this paper, we focused on approach (3): inference from observation of economic behavior, based on this assumption of existence of the relationship between the actual behavior of a decision maker and the behavior predicted from empirically specified models. A new non-parametric method and the QP method were used to calculate the coefficient of risk aversion. We maximized the decision maker expected utility with the E-V formulation (Freund, 1956). Ideally, in constructing a QP model, the variance-covariance matrix should be formed for each individual farmer. For this purpose, a sample of 100 farmers was selected using random sampling and their data about 14 products of years 2008- 2012 were assembled. The lowlands of Esfarayen were used since within this area, production possibilities are rather homogeneous. Results and Discussion: The results of this study showed that there was low correlation between some of the activities, which implies opportunities for income stabilization through diversification. With respect to transitory income, Ra, vary from 0.000006 to 0.000361 and the absolute coefficient of risk aversion in our sample were 0.00005. The estimated Ra values vary considerably from farm to farm. The results showed that the estimated Ra for the subsample existing of 'non-wealthy ' farmers was 0.00010. The subsample with farmers in the 'wealthy ' group had an absolute risk aversion of 0.00003, which is lower than for the subsample existing of farmers in the 'non-wealthy ' group. This assumption that the absolute risk aversion is a decreasing function of wealth is in accordance with Arrow (1970) expectation. The method used was to calculate the proportional risk premium (PRP) representing the proportion of the expected payoff of a risky prospect that the farmers would be willing to pay to trade away all the risk for a certain thing, proposed by Hardaker (2000). Our finding showed that the higher risk averse the farmer was, the higher will the PRP would be. Farmers risk premium was 303113 IRR. It should be mentioned that the 'non-wealthy ' group had a larger PRP than the 'wealthy ' group. Following Freund (1956), if the net revenue for each activity is normally distributed and assuming a negative exponential utility function, we can utilize the absolute risk aversion coefficient to obtain relative risk aversion coefficient (Rr). Based on this study, Rr vary from 0.31 to 8.49 and the relative coefficient of risk aversion in our sample was 4.79. Our results showed that the majority of farmers in the study area are highly risk averse (Anderson and Dillon, 1992). The relationships between the relative risk aversion coefficients of farmers and their socio-economic characteristics were also evaluated in this study. Results showed that the age had a positive impact, level of wealth and diversity had negative impacts on farmers ' risk aversion coefficient. Conclusion: Due to existence of the risk and uncertainty in agriculture, the present study was designed to determine the risk aversion coefficient for Esfarayen farmers. A new non-parametric method and the QP method were used to calculate the coefficient of risk aversion. The model used in this analysis found the optimal farm plan given a planning horizon of 1 year. Thus, the historical mean GM vector and variance-covariance matrix were assumed to represent farmers beliefs. Our results showed that the majority of farmers in the study area are highly risk averse. In addition the more risk averse the farmer was, the higher will the PRP would be. Farmers risk premium was 303113 IRR. Our finding showed that the age had a positive impact, level of wealth and diversity had negative impacts on farmers risk aversion coefficient. According to the results, insurance development and investment in agricultural commodities exchange was suggested to reduce the coefficient of risk aversion.