مجله اقتصاد و توسعه کشاورزی
سال سی و یکم شماره 4 (پیاپی 37، زمستان 1396)

In recent decades too much use of production inputs to increase yield has caused a lot of environmental damages; therefore more attention has been placed to studying the sustainability and continuality of production system along with preserving the renewable natural resources. Thus, sustainable agriculture has been considered as the most effective solution for this matter by experts. This study aims to assess natural resource and agricultural sustainability in counties of East Azerbaijan Province.
In this article, agricultural and natural resource sustainability of East Azerbaijan Province counties was assessed by using composite indicators. We consider economic, social and environmental indicators as the decision-making dimensions and each of them include some sub-criteria. The indicators weight were determined by direct survey from agricultural and natural resources experts. The methodology used in this study for assessing sustainability is compromise programming that is one of the goal-programming approaches. The compromise programming is capable of handling a large amount of information. This method is a well-known MCDM approach. The basic idea in Compromise programming is the identification of an ideal solution as a point where each criterion under consideration achieves their optimum value. Since there is a trade-off among criteria, the ideal point is typically not feasible and it is used as a reference point; alternatives are ranked based on how far they are from this. The data have been collected from a variety of sources, including the Agriculture and East Azerbaijan Regional Water Authority and Statistical Yearbook of East Azerbaijan Province in 2015.
The results showed that in economic dimension, economic efficiency of irrigation, irrigated wheat yield, conservation tillage and insurance percentage indicators with coefficients of 0.188, 0.154, 0.127 and 0.122 respectively are known as the most important parameters. In social dimension literacy rate, number of agricultural expert, health indicator and agricultural employment indicator with coefficients of 0.137, 0.138, 0.120 and 0.125 respectively are known as the most important parameters. Also, in environmental dimension, the most important parameters are groundwater level, agricultural water usage indicator, water salinity, efficient irrigation systems indicator and nitrate concentration in groundwater coefficients are 0.144, 0.116, 0.093, 0.093 and 0.087, respectively. Classification results showed that in economic dimension, Ajabshir, Heris and Malekan counties are sorted as very sustainable. These counties have good condition of economic efficiency of irrigation, irrigated wheat yield and conservation tillage indicators that are the most important indicators of this dimension. In social dimension, Jolfa, Osku and Ajabshir counties are classified as very sustainable. Number of agricultural expert is the most important indicator in this dimension and Jolfa has the first place in this regard. In terms of literacy rate, the second important indicator in social dimension, all three counties are in a good shape. Osku, in terms of health and immigration indicators and Jolfa in terms of communication indicator have the first place. The low number of agricultural expert, a small number of extension activities, low per capita space and lower immigration are the characteristics of the very sustainable category which includes Malekan, Maragheh, Bostan Abad and Khoda afrin. In environmental dimension, the counties that show a good condition about groundwater level, water salinity, vegetation cover, percentage of soil organic matter and Indicator of chemical Fertilizer use, are sorted as the every sustainable category. This group includes Kaleybar, Varzeghan and Khoda Afarin counties. While less using of efficient irrigation systems, much consumption of agricultural water, higher nitrate concentrations, much use of chemical fertilizers, lack of soil organic matter, lower vegetation cover and the higher number of livestock units in per hectare ranch are common features of the very unstable category. Finally, the results of total sustainability classification show that Kaleybar, Ajabshir and Varzeghan counties are in the very sustainable category, this was far from what we expected because Kaleybar and Varzeghan counties in terms of environmental sustainability and Ajabshir County in terms of social sustainability were classified in the very sustainable category. Maragheh County in all three dimensions is the farthest from the ideal point and classified under the unstable or very unstable group and as a result, in overall, is very unstable.
In this study agricultural and natural resource sustainability of East Azerbaijan Province counties was assessed and the relative importance of the indicators was determined. The results showed that irrigation efficiency must be improved to increase the economic sustainability of agriculture and natural resources in the counties of East Azerbaijan. It is recommended to increase the distribution of improved seeds to increase crop yield. Also, results showed that due to the drought crisis in the region, water resources sustainability is the main concern of agriculture and natural resources sustainability in East Azerbaijan province. Furthermore, more equitable distribution of facilities and infrastructure such as agro-processing industries, rural schools, health centers and recreational facilities can lead to socio-economic development in disadvantaged counties of province

Today, energy supply is one of the most important issues in development process of all countries in the world. There is a close relationship between economic growth and development and energy consumption. Agriculture plays a critical role in the national economy and food production and energy has always been essential for the production of food and agricultural products. In agriculture, various fuels are used as a source of energy, including gasoline, kerosene, natural gas and electricity. Over time, the electrical equipment used in the agricultural sector has increased, and as a result, the need to use electrical energy has also increased. Electricity is one of the main inputs in the agricultural sector, so that, more than 16 percent of electricity production in Iran, allocated to this sector for more than 20 percent of the provinces in Iran, electricity power consumption in the agricultural sector is more than that of in the industrial sector. Energy intensity is one of the key terms in the literature on energy efficiency. The energy intensity of agriculture is defined as the ratio between the final energy consumption of the sector and the value added of agricultural sector. Energy efficiency refers to the activity or product that can be produced with a given amount of energy. There is a widespread assumptions in energy statistics and econometrics that energy intensity and energy efficiency are equivalent measures of energy performance of economies.
Because of the importance of efficiency in production inputs, the main objective of this study is to evaluate the efficiency of electricity consumption in the agricultural sector of Iran. For this purpose, the state of high and low efficiency of electricity consumption in the agricultural sector was detected by using Markov regime switching model during the period 1342 to 1393. The Markov switching model proposed by Hamilton (1989) is one of the most popular nonlinear time series models in the econometrics literature. A Markov switching model is constructed by combining two or more dynamic models via a Markovian switching mechanism. A Markov regime switching Model is the generalization of the simple dummy variables approach that allows regimes or states to occur several periods over time. In each period t, the state is denoted by st. There can be m possible states: st = 1,... , m. the states in this models may be recessions and expansions, high and low volatility, depressive and non-depressive or high and low efficiency states, etc. The time of transition between states and the duration in a particular state are both random and the transitions follow a Markov process. In the nonlinear models, any of the parameters (such as beta estimates, sigma, and AR components) may be different for each state. The Markov switching model and its variants discussed in the preceding sections are only suitable for stationary data. Because the order of integration of a time series is of great importance for the analysis, therefore, several statistical tests have been developed for investigating it. In this paper, we use ADF and PP unit root test for investigation of integration order of variables such as energy efficiency, growth rate of per capita GDP and consumer price index.
First, the results clearly suggested that the unit root null hypothesis for the selected variables can be rejected. The estimation of Markov regime switching model showed that the duration of low efficiency regime in the agricultural sector is more stable than the high efficiency regime. The average duration of the low efficiency regime is 2.5 months and the average duration of the high efficiency regime is 1.7months. The results also showed that the general level of prices and per capita production has negative and positive effect on the efficiency of electricity consumption in the agricultural sector, respectively.
The trend of energy consumption and efficiency of electricity in agricultural sector and at the national level shows that the average energy consumption over the past 51 years has increased and at the same time electricity efficiency (both in agricultural sector and in total economy) has declined over the long term. The trend of energy efficiency indicators shows that agricultural producers are not efficient in the process of production. According to the results of the study, systematic planning for the optimal use of inputs is suggested to improve energy efficiency in agricultural sector. In order to increase the efficiency of energy usage, especially electricity usage in the agricultural sector, following ways recommended: restructuring of the production and use of newer and more efficient technologies; financial support and providing banking facilities to optimize consumption and energy supply projects.

The first step in any planning is recognition of the actual condition and the main tool to know the present situation and move towards to the ideal conditions is the access to data and information. This study, tried to study fish consumption status and identify the factors affecting it in Sari and Mashhad Cities.
Data was collected through interviews and questionnaire and were analyzed using ordered Logit model. Often dependent variables are ordinal, but are not continuous in the sense that the metric used to code the variables is substantively meaningful. A widely used approach to estimating models of this type is an ordered response model, which almost allows employing the Logistic link function. This model is thus often referred to as the "ordered Logit" model. The central idea is that there is a latent continuous metric underlying the ordinal responses observed by the analyst. Thresholds divides the real line into a series of regions corresponding to the various ordinal categories. The latent continuous variable, y* is a linear combination of some predictors, x, plus a disturbance term that has a standard Logistic distribution. Similar to the models for binary data, we are concerned with how changes in the predictors translate into the probability of observing a particular ordinal outcome. In this model, the dependent variable is divided to different classes. Coefficients cannot be interpreted directly; so for evaluating the effect of independent variables on the dependent variable, marginal effect or marginal probability is calculated. independent variables are: Family size, Age, Price of fish, Price of meat, Price of chicken, Education, The number of people under 10 years, The number of people with specific diseases, The number of elderly, Income level, Job, Factor related to taste, Factors related to the access and ease of preparation of fish, Factors related to preparation and cook and Factors related to aquatic health.
Households, based on the frequency of buying aquatic (fish, shrimp and canned), are divided into four groups: households with no annual, monthly and weekly consumption of aquatic. So we ran order Logit model for these groups. Pseudo R2 Shows that the order Logit model has a high level of goodness of fit, and the independent variables used in the models explain 12% and 14% variations in the probability of Mashhadian and Saravian households at different levels of consumption. The value of the χ2 statistic in Wald test also indicates the significance of the whole regression. The estimated results of ordered Logit model showed that variables of the number of children under 10 years, the number of people with specific diseases, the number of elderly and income level have the positive impact on fish consumption in Sari. Variables of residential area and the number of children under 10 years have a positive impact on fish consumption in Mashhad. In other words, increasing these variables, increases the probability of fish consumption in these cities. Age has the negative impact on fish consumption in Sari. Also, factors associated with taste, factors related to lack of knowledge of preparation and cooking aquatic and factors related to the health of aquatics have a negative impact on fish consumption in Mashhad. This means that increasing these variables, puts households at lower levels of fish consumption. In such a way, the habitat of coastal towns towards non-coastal cities, reduces the probability of households to be in the low-level of aquatic consumption. This is due to the lower price of fish in coastal cities and access to fresh fish in these cities. The likelihood of Mashhadian households in the low-levels (no use) of aquatic consumption was reduced by 0.308 and increases the probability of households in annual, monthly and weekly of aquatic consumption, with increase in the residential area level by 0.091, 0.192 and 0.025 respectively. The likelihood of Sarian households in high- level of aquatic consumption (weekly and monthly) was increase by 0.120 and 0.395, with increase in the number of people with specific diseases, respectively. Increasing the income level of households also reduces the probability of Sarian households in the low-level (no use) of aquatic consumption group by about 0.0000006.
This study aimed to identify the factors affecting fish consumption in Sari and Mashhad Cities. For this purpose, data was collected through interviews and questionnaire and were analyzed using ordered Logit model. The estimated results of ordered Logit model showed that variables of the number of children under 10 years, the number of people with specific diseases, the number of elderly and income level have a positive impact on fish consumption in Sari. However, variables of residential area and the number of children under 10 years have a positive impact on fish consumption in Mashhad. In other words, increasing these variables, increases the probability of fish consumption in these cities. But factors associated with taste, factors related to lack of knowledge of preparation and cooking aquatic and factors related to the health of aquatics have the negative impact on fish consumption in Mashhad. Based on the results, holding the training classes of fish cooking for enthusiasts and creation of aquatics Markets to supply of aquatic have been proposed.

Due to dependence of households to agriculture in terms of income and consumption, study the effects of trade liberalization in this sector is necessary in developing countries. Trade liberalization policies have different results in various countries because of the factors that influence price transmission from world markets to domestic market. In other words, the extent of tariff pass-through is different in this country. Tariff pass-through determines how much tariff changes pass-through to domestic prices, therefore study the extent of tariff pass-through to prices is important. The aim of this study is determine the extent of tariff pass-through to agricultural products prices considering the heterogeneity in urban and rural area during 1384-93. For this purpose, major agricultural products in the household basket, aggregated in six groups and extent of tariff pass-through to prices of these groups, were estimated by making pseudo panel data and using Nikita (2004, 2009) tariff pass-through model. The reason to use pseudo panel data is that time series of household surveys data does not exist. Deaton (1985) states that it is possible to construct pseudo-panel data by using repeated of cross-sectional data (with individuals completely different from one to another) and obtain estimators similar to panel data. In this method, each cohort will be created using individuals who share some common characteristics. Then, observations are constructed from average of each cohort. Study the extent of tariff pass-through to agricultural prices is important because Iran has not experienced a broad liberalization and did not joined WTO; also for low income and developing countries such as Iran local markets may be exposed to high transfer costs and often poor integration into the international economy. So the regional aspects of tariff pass-through is important. The results of this study represents the ability or defect of regional markets in global prices pass-through to local prices and this will be a guidance for policymakers to reform the structure of local markets before joining WTO.
Tariff pass-through theory is based on exchange pass-through literature that examines the changes in price of imported goods due to changes in exchange rate. Tariff path-through model determines how much of observed changes in prices during the study can be directly attributed to tariff changes policy. To calculate the effect of tariff changes on prices we used Nikita (2004, 2009). He expresses that change in domestic prices of imported goods is determined by tariff change multiplied imported goods prices and adjusted by changes in exporter markup. Since the development of domestic markets is important, this model use trade costs to calculate the extent to which local markets are receptive to movements in border prices.
The results indicated an incomplete tariff pass-through for different groups of agricultural products. Tariff Change have different effects on prices of agricultural products in urban and rural areas. As in urban areas tariff pass- through to prices are in range of 0 and 17 percent and in rural areas are in range of 0 and 26 percent. This level of tariff pass-through is slightly smaller than what has been stated in the literature. For example Nikita (2009) has gained tariff pass-through to agricultural prices almost 33%. Cherkaoui et al (2011) has gained results about 13% and Marchand (2012) result show that tariff pass-through to agricultural prices are between 64 to 68 percent in urban areas and in range 33 to 49 percent in rural area. However, results of this study are not unexpected since the extend of tariff pass-through in developing countries such as Iran with limited infrastructure and incomplete markets, can be lower.
The main important result of this study is that any change in trade policy can not completely pass-through to consumers. Factors such as noncompetitive markets, defect in markets and infrastructures may keep households away from positive effects of tariff changes in urban and rural. Our results are also consistent with Marsh (18) that expresses since the self-consumption tariff path-through to prices is lower in rural areas, in some rural areas, producers and consumers may be completely separated from economy. Therefore, as can be seen in this study clearly price changes in border has not affected the local prices. It is necessary for policymakers to consider factors such as market prices transmission mechanism and infrastructure conditions in trade policies.

Poultry is now one of the largest industry in Khorasan Razavi province and chicken meat has an important role in household food needs. Developing appropriate studies that lead to strategies for handling poultry products to fulfil consumers’ demand have become quite a challenging issue especially due to crisis situation. Supply chain system in this paper means a chain of processes from the rearing farm to the final consumer of the finished product and provide useful operational analysis of system behaviors for managing supply chain under demand uncertainties and production disruptions.
In this paper, a system dynamics model is applied for studying the behavior of the chicken meat supply chain threatened by bird flu, demand fluctuation and Government (State Livestock Affairs Logistics) intervention under the Vensim environment. The model is an extended version of real-life practice which involves producers, consumers and government. A causal loop diagram used to show how interrelated variables affect one another and connect together. This important diagram can handle assumptions regarding facing various calamities and disaster which is an integral part of the poultry industry. This dynamic model development can track possible disasters in time to prepare facing them. To cover more possibility, we propose three scenarios of different levels for demand and present of loss bird. To find out the most efficient rearing rate in crisis situation, demand fluctuation and loss bird rate are considered simultaneously in scenarios. Importance of chicken meat strategic reserve for Norouz lead us to impose a constraint for government purchasing and expenditure during the last month of simulation. Operations during a 120 days are simulated and a what-if analysis performed to study the model stability under uncertainty environment.
As a starting position no bird losses rate and demand problems included and supply chain fills all of demands without purchase chicken meat from external markets. The equilibrium was reached when the available live chicken level equals to 382 (ton/day). Results showed that without changing demand levels for achieving supply chain stability, the system need to import chicken meat for entire of the crisis period and government intervenes in market to ensure remunerative prices for producers and affordable prices for consumers. In sanitary crisis situation, decreasing demand can reduce the external purchases and unexpected costs but it decreases net income of producers simultaneously. In all scenarios external purchases and unexpected government purchasing are zero when the demand decreasing level is maximum. The simulation results showed that 10 percent of domestic farms affecting by Bird flu can increase the amount of external purchases up to 40 (ton/day) and give rise to unexpected government expenditures by 3360 (million Rial). It is evident from the model that slaughtering all reared chicken (available live chickens) after exactly 42 days can give number of benefits to the industry and profit is maximize in the simulated behavior for this scenario test. Reduction of rearing time can increase the amount of available chicken meat and net income of producer by 18 percent. In contrast, an increase of 15 days in rearing time can considerably reduce net income of producer by 30 percent. This means that a reduction of rearing time (standardization of poultry size and weight) can be a solution to improve poultry industry in Khorasan Razavi province. Income of producer is sensitive to the crisis and it is reduced up to 27 percent at peak of bird loss rate. Poultry producers are suffering from economic loss due to management, bird disease and transportation stress. These factors not only affects the quantity but also decrease the quality of chicken meat. On the other hand, 5 percent decrease in slaughterhouse and transportation mortalities immediately leads to an increase in supply chain incomes and the level of chicken meat inventory. According to the result, with management of chicken transportation, slaughter and rearing time, even in the worst scenario when the loss bird rate was maximum, it is possible to fulfil demand with domestic production capacity.
The supply chain is affected by endogenous and exogenous factors such as government intervention. Therefore an establishment of an integrated system between rearing farms, transport system, slaughterhouse and government purchasing can be helpful especially in crisis period. Poultry industry can integrate complete supply chain network so decision-makers can assist calculating the economic returns and reduce the risk. Moreover, producers will be able to compete with the other provinces and global markets as well as reducing their operational costs. Future research can focus on the different variables and study poultry wastes of processing by-products on the poultry industry in Khorasan Razavi province.

The degradation and destruction of natural resources is being considered as an economic issue; because when these resources are destroyed or lost, significant values are destroyed because some of which are irreversible. The major difference between the science of economy and other subjects such as ecology on the definition of the “value” is the emphasis of economy on the preferences. Differing sensitivities are the basis for targeted communication programs and promotions. As consumer preferences and sensitivities become more diverse, it becomes less and less efficient to consider the society at the aggregate level. In this research, we will show how hierarchical Bayesian approach is ideal for these problems as it is possible to produce individual -level parameter estimates. Urmia Lake in the northwestern corner of Iran is one of the largest permanent hyper saline lakes in the world and the largest lake in the Middle East. The lake’s surface area has been estimated to be as large as 5585 km2. However, since 1995 it has declined and was estimated to be only 926 km2 in 2014 based on satellite data. Considering no significant trend in the drought pattern, Urmia Lake's observed physiographic changes may be attributable to the overuse of renewable water resources and unbalanced development of agricultural sector. Therefore this research emphasizes the active role of local communities in the conservation and revitalization of Urmia Lake and analyzes the data from the choice experiment using hierarchical Bayes.
Choice-based conjoint (discrete choice) measurement has attracted more attention over the last years. Many researchers assert that choice-based tasks are more realistic for respondents than ratings- or rankings-based conjoint questions. However, choice-based conjoint data does not contain as much information per unit of respondent effort as traditional conjoint analysis. There are different ways to analyze the choice data. Hierarchical Bayes is the newest estimation method. The mathematical specification of these model is a Bayesian hierarchical model in which, broadly speaking, a different vector of utility is defined for each respondent. The distribution of these utilities in the whole population has some specified forms, usually normal. Hierarchical Bayes allows for heterogeneity at a respondent's level by specifying different utilities for each respondent. This leads to a greater improvement in simulation techniques: simulation conducted using aggregate or clustered models often lead to the biased results. Its ability to borrow information from other respondents to stabilize part worth estimation for each individual is particularly valuable for choice data. Applying HB to choice data allow analysts largely to solve IIA problems. Four attributes consist of animal habitat, climate regulation and prevention from salt storms, aesthetic and ecotourism, and education and research were considered in this study. The required data have been collected from 13 districts located in the northwest of Iran and Exogenous stratified random sampling applied as the sampling strategy.
Estimating willingness to diagnosed climate regulation and prevention from salt storms as the most important attribute from the view of the respondents. Animal habitat, aesthetic and ecotourism, and education and research were in the next places of people’s willingness to pay priorities. Hence, from the public’s point of view, mentioned attributes in the same order, should have most importance and priority in the management scenarios. Individual-level parameters of the Bayes model showed the highest variance for the full restoration of the climate, which implies the existence of conflicting preferences in this attribute. This indicates although some variables are important, they also fluctuate in a wide range of variations and the probability of their selection is different among people. Certainly, hierarchical bayes provides information far beyond the average utility and applying this information will give experts a better understanding of the distribution of preferences. Another important subject to know is that even with four sets of choices in each questionnaire and the need for people to respond to all of them, there is still some uncertainty about the part worths of the individual level.
An important point about model estimation is the diminutive presence of individual explanatory variables. The Bayesian model is recommended to be based on just those respondents’ features that are directly related to the part worths and preferences in choosing goods. It is also recommended that, in order to attract higher rate of contributions, variables with low variation, such as reviving the current status of climate and full restoration of aesthetic and ecotourism which are generally accepted, should be used.

The existence of a variety of natural and unnatural hazards in agricultural activities have caused farmers to face uncertain and vulnerable situations. In this regard, income protection insurance is one of the new insurance policies that covers the fluctuations of yield and price, simultaneously. The main objective of this research is to design a pattern of income protection insurance for strategic agricultural crops such as rain-fed barley and compare it with yield protection crop insurance in Hamadan province, for different insurance coverage levels in order to reduce the farmer's income fluctuations. Another objective of this research is to investigate the use of the time series analysis techniques in predicting the price and yield variables of the selected crop and to determine the minimum income, in order to pay the farmers for the damages. Also, determining the best model for simulating yield and price parameters, and finally estimating the income of the rain-fed barley, under the influence of the uncertainty are other objectives of this research.
In this research, the data were analyzed in order to extract the best predictive model. A fair premium offer for agricultural products requires, a prediction of the performance of various products as well as the price fluctuations in the future. In this study, this prediction was made through predicting the price and performance time series using the ARIMA various models test. The best prediction model based on the 22-year and 32-year statistics of price and performance variables was chosen using the Akaike information criterion (AIC). Then, the expected damages, fair premium and real premium of the product of interest, were calculated once by using the yield insurance method without applying the price-performance relationship and once by using the income insurance method by applying the price-performance relationship of 2017. In order to take into account the uncertainty of the deviation parameter from the mean of the yield data, about 10,000 random samples of the deviations (the residuals of errors) were generated by the Monte Carlo algorithm substitution and accordingly, the product performance was simulated. Each of these simulations could be the actual performance of the product in the upcoming year, according to which, the expected damages and subsequently the fair and real premiums will be estimated for the following year. All of these steps were done using coding in the MATLAB software.
The results of the time series analysis indicated that the price of barley was estimated to be about 10706 Rials in the upcoming year of 1396. The rain-fed barley’s yield was also predicted to be1476 kg/ha in the same year. By simulating the farmer’s actual income using the Monte Carlo method and by considering 10,000 iterations for implementing the forecasting model. The average payable compensation payments (fair premiums) for the upcoming year, for rain-fed barley and for 50, 60, 70, and 80 percent coverage levels, were obtained equal to 42371.9, 122972.9, 288375.8, and 580106.3 Rials per hectare, respectively. Using the results of time series analysis of the price of barley product, the forecast for next year of 1396 is about 10706 Rials. The yield of barley for the next year is expected to be 1476 kg ha-1. By simulating the actual earnings of farmers in the Monte Carlo method and considering 10,000 times the repeat of the implementation of the forecast model, the average payable compensation (fair premium) in the following year for the production of barley at the surface of the coatings 50, 60, 70 and 80 percent were calculated 42371.9, 2929.92, 8837.258, and 59.50106 Rials per hectare, respectively. Accordingly, the amount of the real premium of rain-fed barley, by using the operating insurance method and without applying the price- performance relationship was obtained equal to 48503.5, 141131, 331905.4 and 668566.4 Rials per hectare for 50, 60, 70, and 80 percent coverage levels, respectively. On the other hand, the amount of rain-fed barley’s real premium was obtained 47079.9, 136636.5, 320417.6, and 644562.6 Rials per hectare, by using the income insurance method and by applying the price-performance relationship, for 50, 60, 70, and 80 percent coverage levels, respectively. By deducting 71% government subsidy from this, the amount of premium for each farmer would cost 15536.4, 45090.1, 105738.8, and 212705.6 Rials, respectively.
The results ultimately indicated that for the selected product, the amount of the computed premiums in the income protection insurance model is lower than the yield protection crop insurance. Accordingly, considering the risk of planting rain-fed products, applying the income insurance model will encourage farmers more. Also, in this model, the insurer, having understood the simultaneous effect of price and performance, will offer computing insurances with more certainty in different coverage levels. According to the results of this research, it is suggested that income insurance, taking into account the uncertainties that were caused by price prediction and product performance, should be used instead of functional insurance. This policy will make farmers more lucrative and leads to a better risk management system by insuring companies.