Agricultural Economics
H. Amirnejad; S.A. Hosseini-Yekani; S.M. Mojaverian; F. Kashiri Kolaei; M. Taslimi
Abstract
Introduction: The resistive economy, in the sense of managing the current situation in the country, minimizes the risks. In other words, establishment of the necessary institution in Iranian economy by using a set of policies, laws, and executive measures in such a way to minimize its risk against harmful ...
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Introduction: The resistive economy, in the sense of managing the current situation in the country, minimizes the risks. In other words, establishment of the necessary institution in Iranian economy by using a set of policies, laws, and executive measures in such a way to minimize its risk against harmful shocks and disturbances, especially foreign and international ones, would provide the ground for the country to achieve sustainable economic progress. One of the most important methods in this regard, in creating the infrastructure of a resistive economy, is development of the agricultural sector. In fact, due to the distinctive features of the agricultural sector, this sector can be considered as the driving force of the economy within the framework of the resistive economy. To achieve such an economy, the challenges and potentials facing this sector must be identified while determining optimal investment for the basic sectors. Due to the capabilities of agricultural production in Mazandaran province, in this study, for identifying the problems and opportunities in the subsectors of agriculture and horticulture, a type of SWOT analysis was used in which relative weights are calculated through a linear mathematical programming model. Finally, by using the QSPM approach, prioritization strategies were developed for each subsector.
Material and Methods: In the SWOT analysis, the AHP approach was used to extract the pairwise comparisons of internal and external factors from the opinions of the interviewed experts in the subsectors of agriculture and horticulture. SWOT analysis has been used to determine strengths, weaknesses, opportunities, threats, and the combination of linear programming. Therefore, AHP approach is used to calculate the weight for criteria and alternatives at each level. In this research, a two-step linear programming method has been used to calculate the priority vector. In the first step, according to the pairwise comparison matrix, a formulation that provides a consistency limit is used. In the second step, according to the compatibility limits obtained in the previous step, for calculating marginal weights of the criteria, another linear programming model is used. After calculating the relative weights of each of the components of strengths, weaknesses, opportunities and threats, as well as determining some strategies, using expert opinions, the QSPM approach has been used to prioritize strategies. For this purpose, the attractiveness coefficients of each strategy were extracted according to the Swot components and by multiplying the attractiveness coefficients by the relative weights, the total score for each Swot component was calculated for each strategy and finally with the total score of the Swot components, a total score for each strategy was calculated. Finally, Excel and GAMS software were used to estimate the results.
Results and Discussion: According to the results of SWOT analysis in the agriculture and horticulture sector, among the important strengths in Mazandaran province, this subsector can be ranked first in the production of various products, variety of climatic conditions and suitable water resources, the existence of fertile and suitable lands and variety of products. In contrast to the above strengths, weaknesses such as traditional and small units of exploitation, lack of guaranteed purchase and non-payment of debts on time by the government and cooperatives, low irrigation efficiency and low productivity of inputs (land, labor, etc.), lack of proper marketing system and the weak role of the government are some of important challenges in the subsectors of agriculture and horticulture in Mazandaran province. The opportunities facing the subsectors of agriculture and horticulture include the existence of ports and export terminals, existence of suitable fields for the construction of processing industries, improvement and establishment of fruit and vegetable terminals, and the existence of agricultural sub-graduates. The most important factors that threaten the activity of subsectors of agriculture and horticulture are related to the problems of financing and bank interest rates, land-use change and land trade, excessive import of agricultural and horticultural products, and small number of related processing industries. The results of prioritizing strategies through the QSPM approach also showed that according to aggressive strategies, in the subsectors of agriculture and horticulture, strategies like "Increased aggressive racial reform research ", "Establishment of fruit and vegetable export terminals" and "Development of processing industries", in the subsector of livestock strategies like "Export development and entry into global markets", "Product and market development", "Establishment of facilities for export to the Caspian littoral states" and "Improvement of livestock breeds to increase production" , and in the subsector of fisheries "Aquaculture Development", "Development of Fisheries Industry", "Private and public sector support and investment" and "Establishment of facilities for export to international markets" are among strategies for strengthening the economy of the province and the country that can be considered.
Conclusion: According to the results of this study, it is suggested that more attention in terms of capital support, and regional policies should be given to the subsectors of agriculture and horticulture in this situation. Also, appropriate measures should be taken to increase the productivity of the agricultural sector in line with the resistance economy. It is also suggested that solutions such as guaranteed purchase, providing facilities for small and job-creating projects, use of agricultural researchers and graduates for improving and implementing of racial reform research, support and development of processing industry of agricultural products, market development and increasing exports of agricultural products, should be used.
F. Mojtahedi; S.M. Mojaverian; S.A. Hosseini Yekani
Abstract
Introduction: stock market may play a significant role in financing food industries. Nowadays, people select an optimized portfolio with several shares instead of choosing only one in order to cope with the investment risk. For this, the systematic risk could be very important as the market is so fluctuating, ...
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Introduction: stock market may play a significant role in financing food industries. Nowadays, people select an optimized portfolio with several shares instead of choosing only one in order to cope with the investment risk. For this, the systematic risk could be very important as the market is so fluctuating, especially in Iran. So in this paper, we enter a constraint for systematic risk that helps investors in making decision.
Materials and Methods: As we said, we want to enter systematic risk in the portfolio selection model. We use Extreme Downside Hedge (hereafter EDH) as the measure for the systematic risk of each company in the food industry. This measure relies on the argument that investors are able to hedge against extreme downside risk. The EDH can be estimated by regressing stock returns on a measure of market tail risk. We use Expected Tail Loss (ETL) to measure market tail risk. ETL is defined as the expected value of the loss given that the loss exceeds VaR. Then, the factor models are introduced to capture the systematic risk. In order to actively allocate the systematic risk, we use the definition of the marginal systematic risk introduced by Li et al (2018) to measure the systematic risk contribution of a risk contributor. First, we choose some variables as factors that affect the return of each company. After that, we calculate the covariance between factors and then make an equation that shows the systematic risk for each company. We apply our methodology to the return time series of 11 companies and the index for the food industry, all listed on the Tehran Stock Exchange (TSE). The data covers the period from 2015 to 2019. Other variables include oil prices, gold prices and exchange rates extracted from the Economic and Financial Databank of Iran.
Results and Discussion: The results show the Behshahr Ind, Glucosan, Kalber, Margarin, Pars Mino, Pegah Fars and Salemin have positive EDH. This means for these companies the stock returns are affected by volatility of the market, in other words as the volatility increases, the stock returns decrease. It should be noted that the higher the EDH is, the greater the impact is. Also, Gorji Biscuit, Mahram Mfg, Minoo Co and Azar Pegah have negative EDH, indicating the reverse impactability of these companies' returns from market volatility. The higher the EDH, the lower the companies' volatility, also the higher the negative EDH, the higher the market volatility. After calculating the factor model and entering it in the portfolio model, we obtained the optimized result. According to the results, Azar Pegah and Pars Mino, with 86% and 12% have the highest percentage of the optimal portfolio, while Kalber, Pegah Fars and Salemin altogether have 2% of the portfolio, respectively. As the results show, the largest share belongs to the Azar Pegah Company, which is also according to the EDH of the company, in fact, the results show the company whose shares have the highest negative impact from the market has entered to the model. The presence of four other companies in the portfolio given the positive EDH is due to their high average return rather than other companies, since we consider the return as a constraint in the model because of its importance in decision making. It is also worth noting that, the two companies, kalber and behshahr Ind, with the highest positive EDH are not in the optimal portfolio. In order to investigate the effect of systematic risk the model was estimated without considering this constraint. The results show, without systematic risk constraint the optimal portfolio has shifted to companies with higher return and lower risk. Thus, the results of this study indicate that with systematic risk, based on expectations, portfolios will shift to companies with lower impactability from market volatility on the one hand and higher returns on the other.
Conclusion: Finally, the results of the study show, the systematic risk in the model shift the portfolio towards the stocks of companies that are less affected by market conditions. Therefore, given today's fluctuating conditions, it may be useful to apply a model that considers this part of the risk.
S.S. Ahmadzadeh; H. Amirnejad; S.A. Hosseini Yekani
Abstract
Introduction: The overuse of fertilizers in recent years has led to the production of harmful agricultural products and environmental pollution. Studying the environmental efficiency of agricultural activities and transferring the results of these studies to farmers and making practical use of them is ...
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Introduction: The overuse of fertilizers in recent years has led to the production of harmful agricultural products and environmental pollution. Studying the environmental efficiency of agricultural activities and transferring the results of these studies to farmers and making practical use of them is one of the important strategies that can have a significant impact on the production of healthy products with less negative impacts on the environment. The main objective of this research is to measure the technical and environmental efficiency of rice farms in Guilan province. Previous studies in agriculture sector considered pesticides and fertilizers as undesirable inputs in the environmental model but considering undesirable outputs as inputs leads to an unbounded PPS, which is not rational from an economic perspective. So in this study, the nutrient surplus (nitrogen and phosphorus surplus) from rice fields, caused by overuse of chemical fertilizer, was considered as an undesirable product in the environmental model.
Materials and Methods: The presence of outliers in the dataset may bias efficiency estimates: this could make the results meaningless and misleading. The data cloud method is useful in identifying and removing outliers in the data, thus leading to more accurate efficiency estimates. Therefore, at first, farms that were identified as outliers were deleted from the sample. Then the nitrogen and phosphorus surplus were calculated by material balance condition and farms with negative or zero NS and PS were removed from sample, then the remaining farms were used to estimate the technical and environmental efficiency. To determine efficiency, the directional output distance function method was used. In this method, it is assumed that undesirable output is produced along with the desirable output and that means maximizing optimum output while reducing undesired output. The required data were collected by questionnaires from 427 Rice farmers.
Results and Discussion: The results indicated that the amount of nitrogen and phosphorus surplus in rice farms of Guilan province were 44.63 and 14.31 kg/ha, respectively. Therefore, if rice farmers continue to use current levels of nitrogen and phosphorus fertilizers, environmental problems caused by NS and PS would increase.
The average technical efficiency of farmers in constant and variable returns to scale is 59 and 69 percent, respectively. So, it is possible to improve the efficiency of rice farms. In other words, the technical efficiency of farms under assumption of CRS and VRS can be improved 41% and 31%, respectively, through increasing output. The average environmental efficiency was 52%, it indicates that environmental efficiency is low. So according to the directional nutrients efficiency measure, rice farmers can increase their rice production and reduce environmental pollution simultaneously.
Based on the results, environmental efficiency of farmers is lower than technical efficiency and there is a significant difference between the average efficiency with regard to nutrient surplus and without it, so if the nutrient is not considered in the model the efficiency score is estimated more than the actual value by 17%. The results also showed that almost 82% of these rice farmers are technically inefficient and 85% are environmentally inefficient. Spearman correlation coefficient between technical and environmental efficiency was 0.772. This indicated there is a positive relationship between these two kinds of efficiency and units with high technical efficiency also have high environmental efficiency.
Conclusion: One of the reasons for over usage of fertilizers and neglecting chemical fertilizer damages by farmers is that most farmers cultivate rice based on past experiences and they are more concerned with the economic aspect of production and not considering the external effects of increasing production methods. Lack of facilities and appropriate market for introducing and supplying healthy crops and the absence of appropriate agricultural policies are major obstacles to producing healthy crops that leads to continued usage of conventional production methods and the inadequate consumption of pesticides and fertilizers. So controlling fertilizer usage in farms, encouraging the consumption of healthy products, establishing training classes for farmers and raising their awareness about dangers of overuse of chemical fertilizers are essential for improving the environmental efficiency of Rice farmers in Guilan province.
F. Kashiri Kolaei; S.A. Hosseini Yekani; S.M. Mojaverian
Abstract
Introduction: Selecting suitable crops for cultivation in a non-certain environment is considered as an important management topic in the agricultural sector. Despite the multiple application of probability theory in quantifying uncertainty in the form of risk programming, validity of this theory depends ...
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Introduction: Selecting suitable crops for cultivation in a non-certain environment is considered as an important management topic in the agricultural sector. Despite the multiple application of probability theory in quantifying uncertainty in the form of risk programming, validity of this theory depends on the existence of frequency for uncertain variable. For events that cannot be measured by frequency, the only solution is to use subjective judgment of persons in the domain field rather than historical data. Some experts have mistakenly considered subjective judgmentl as a subjective probability and thus used the probability theory to quantify subjective judgmental. But based on existing evidence, the quantification of subjective judgment should be carried out in another theory called the uncertainty theory. In uncertainty theory, in addition to using the belief degree rather than frequency for calculating mathematical moments, the expected value of multiplicative variables will be different with their corresponding relations in the probability theory. Considering these conditions and having in mind that the agricultural sector is always faced with uncertain variables such as price of crops and weather conditions like rainfall, in this study the revenue uncertainty measures of major crops in the Goharbaran region of Sari have been calculated and compared. There are different measures for uncertainty, which in the present study variance and Tail Value at Risk (TVaR) have been used.
Materials and Methods: The first step in the application of the uncertainty theory is the elicitation of the belief degree or subjective judgments of the farmers about the crop's price and rainfall during the crop season. To elicit the uncertainty distribution of these variables based on the subjective judgments of farmers, 120 farmers were randomly selected in 2018. After eliciting the farmers' beliefs about uncertain rainfall and prices in the cdf method, it was necessary to select the number of belief degree which current practice was based on previous studies in this field. After calculating the above subjective judgments, while assuming linear, zigzag, normal and normal forms for uncertainty distribution, the parameters of each function were calculated using the least squares method. Among the forms of uncertainty distribution functions, the best form of the uncertainty distribution for each crop's price and rainfall was selected by comparing the RMSE indexes. Subsequently, by calculating a causal relationship between rainfall and crop yield, inverse uncertainty distribution of yield was also extracted. Given the inverse uncertainty distribution functions of crop price and yield, required parameters such as expected revenue, variance and TVaR of revenue at 95% confidence were calculated based on operational laws of uncertainty theory and probability theory. Eviews and Matlab software were used to estimate the yield response function and the uncertainty distribution functions, respectively.
Results and Discussion: In this study, after collecting the belief degree of farmers in the studied area about different levels of price and rainfall, three groups of comprehensive beliefs about prices and rainfall were determined by goodness of fit test. Then, according to the relationship between crop yield and rainfall, the inverse function uncertainty distribution is also calculated. With the uncertainty distribution function of crops price and yield, the expected revenue, variance (standard deviation) and TVaR measure for revenue per hectare of crops were calculated and compared with the uncertainty theory as well as probability theory. Based on the results of this study, the amount of the above measures varied in different belief degree groups, which is due to differences in the uncertainty distribution parameters. Also, based on the results of this study in all groups of beliefs for all crops, the probability theory compared to the uncertainty theory has estimated the variance approximately more than 30% less, which is a significant result. In other words, applying probability theory to belief modeling will lead to erroneous and misleading results. In the case of the TVaR measure in binary multiplicative variable conditions, the use of probability theory and uncertainty theory in calculating TVaR does not yield conflicting results.
Conclusion: The purpose of this study was to compare the results of applying probability theory for modeling belief degree rather than uncertainty theory in order to illustrate the necessity of using uncertainty theory in belief degree modeling. Studying the effect of probability theory in modeling the belief degree also suggests that the application of probability theory in the presence of two uncertain variables has no significant effect on expected values and TVaR but has a significant effect on variance size. Based on the results of the present study, assuming the binary multiplicative variable, in calculating higher mathematical moments such as variance, the results of probability theory and uncertainty theory make a considerable difference. This demonstrates the need to promote the uncertainty theory in belief degree modeling. In other words, basic training in the belief degree modeling method should be considered.
R. Zahedian Tejeneki; S.M. Mojaverian; S..A. Hosseini-Yekani
Abstract
Introduction: The creation of agricultural processing and complementary industries is one of the ways to reduce poverty and unemployment in rural areas. Therefore, in order to encourage economic agents to create such industries, it is necessary to identify the affective factors on their decision. Information ...
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Introduction: The creation of agricultural processing and complementary industries is one of the ways to reduce poverty and unemployment in rural areas. Therefore, in order to encourage economic agents to create such industries, it is necessary to identify the affective factors on their decision. Information of the Agricultural Jihad Organization of Mazandaran province shows that the concentration of these industries in cities of Amol, Babol and Sari is more than other cities. In addition, the distribution rate of exploited processing industries is different from year to year. By considering the different rate of exploitation in years and locations, this question arises: Does location and time have any effect on exploitation of the agricultural processing and complementary industries in Mazandaran province? What is the contribution of these factors to the exploitation of processing industries?
Methods: To answer research questions, the data of 2572 exploited and unexploited units are collected from the Agricultural Jihad Organization of Mazandaran province. The status of exploitation of processing industries is a qualitative variable with two values of zero and one. To determine the effect time in exploitation, the data are divided according to the Location and the commencing time of unit construction. The two-level Logit model is used for estimating model. In the estimated multilevel model, only intercept component is considered as a random component. Also, in this study, the Variance Partition Coefficient (Vpc) and the Likelihood ratio test is used to evaluate the multilevel model
Results: The value of the likelihood ratio statistic in commencing time of construction model is 330/72 that it indicates that two-level logit model is more suitable than the logit model for estimating data. The Variance Partition Coefficient shows that classifying processing and complementary industries based on the time of construction in Mazandaran province, can explain 28.37 percent of the observed deviation on average, which is not explained by independent variables in the model. While 1.2% of the observed deviation is explained by classifying the industries of Mazandaran province according to construction site. Also the share of location in the exploitation of the processing industries in Mazandaran province varies from 0.2 to 4.6%. In other words, the share of worst and the best location in terms of spatial characteristics are 0.2 and 4.6%, respectively. While the impact of the commencing time of construction in the exploitation of the processing industries of Mazandaran province varies from 19% to 40%. The results of the estimation model show that variables of cooperative ownership, planned capacity, unit area, establishment in the industrial parks, the amount of capital and type of activity effect on creation and exploitation the agricultural processing and complementary industries. Marginal effect of Horticultural activity variables, establishment in industrial parks and livestock activity, are more than other variables.
Conclusion: The results show unlike the high emphasis on location factor in locational studies, the share of this factor in construction and exploitation of the processing and complementary industries varies from 0.2 to 2.4 percent. One of the most important reasons for low share of the location factor can be attributed to the right choice of place for construction by entrepreneurs. The results of the two-level logit model indicate that the start time of construction unit explains 28.37 percent of the variation in the exploitation of the agricultural processing in the Mazandaran province. The best and worst time to start construction is 42% and 19% respectively in the exploitation of the processing industries. The high share of start time shows that if an economic agent starts a single unit at different times, the chance of exploiting from the unit varies in different times. The variability of the conditions creates a concept that is called time rendering, in which the success of the construction of processing industries is a function of the conditions of the start date and not the characteristics of applicants for these designs. Therefore, it is recommended to condition creation of new units and exploiting from existing half-unit (including inflation rates, exchange rates, facility rates, facility quantity and rules) to be equal over time. Which this goal would be achieved by adopting to policies and doing activities that are matched with time, trustees and authorities of country.
K. Sam Daliri; S.A. Hosseini-Yekani; S.M. Mojaverian
Abstract
Introduction: Agricultural products market in Iran is facing structural problems with non-competitive and inefficient conditions for trade of agricultural products, which leads to high price fluctuations for these products. Future markets as one of the risk sharing strategies would shift price risk to ...
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Introduction: Agricultural products market in Iran is facing structural problems with non-competitive and inefficient conditions for trade of agricultural products, which leads to high price fluctuations for these products. Future markets as one of the risk sharing strategies would shift price risk to brokers and intermediaries. So, future markets are considered as one of the best tools for reducing agricultural risk. Designing and implementing future contracts is time-consuming and costly. Therefore, in order to succeed in setting up such contracts, it is essential to pay attention to several main issues consisting selecting the correct commodity for exchange, determining the optimal specification of the future contracts of agricultural products, and the way of decision making and preferences of market participants.
Materials and Methods: Despite the precise design of future contracts, future markets may fail after commencing due to lack of access for farmers, to use these tools. The purpose of this study is to predict future market acceptance by rice farmers in Sari.
To achieve this goal, the positive Mathematical Programming Model (PMP) is used in the simulation of the traditional and future market within the framework of the GAMS software. All required data were derived from statistics provided by the Ministry of Agriculture and Statistical Center of Iran during 2000 to 2015. The objective function of the model was a calibrated objective function which maximizes the actual quantities of farmers' production. But it should be noted that in solving this model, it was assumed that when the future market is launched the decision of the producers regarding the amount of production is not affected and only a part of their product will be offered in the future market, rather than in the traditional market, with the aim of reducing the price risk. Since this assumption does not validate in the actual operating conditions and it is expected that the producers' decision-making process would also be affected after entering the futures market and trading in this market.
Results and Discussion: The results of simulation of the traditional market showed that the real average of the production, consumption, and net exports respectively were about 1.1663*10+5, 24074.390 and 1.4071*10+5 tone and the total profit of the producers of these products was about 3.7928*10+8 million Rials..
Based on the results of simulation of future market, the real average of the production, Consumption and Net exports equals about 1.4349*10+5, 26199.05 and 1.1729*10+5 tone respectively and the total profit of the producers of these products is about 3.7958*10+8 million Rials. Thus it is expected that after commencing future market for agricultural products, 44% of all rice farmers would sell their product using future contracts.
Therefore producers' decisions are not affected by the level of production and only a part of their product would be offered in the future market instead of the traditional market with the aim of reducing the price risk. In addition to comparing this market to the traditional market, the launch of the future market will increase the production, consumption and net exports about 1.9, 8.8 and 5.6 percent respectively.
Conclusion: Due to the strategic condition of the rice product and the suitability of this product to enter the future market, it should be noted that in the process of optimal design of future contracts, without paying attention to all dimensions for launching the upcoming market, this market will not be successful. Therefore, in this study determination of the amount of participation by rice farmers before launching a successful future market for rice crops has been considered. The first stage were simulating conditions before the launch of the future market, named traditional market conditions of rice, and the average real values of production, consumption, net exports and total profit of the producers of this product were estimated in Sari city. Subsequently, with the goal of reducing the price risk, the conditions after launch of the future market were simulated that represent about half of rice producers will be participanting in the upcoming market. Base on the results of this study, it is suggested that the launch of futures markets and transfering process to the Agricultural Commodity Exchange would need cultural and extension courses to understand the benefits of entering this market.
Z. Nematollahi; S.A. Hosseini-Yekani; H. Amirnejad
Abstract
Introduction: Weather factors such as temperature has an enormous influence on agriculture. Therefore, efficient weather risk management has become an urgent requirement for this sector. In recent years, a new instrument named weather derivatives has been introduced to cope with production risk. So, ...
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Introduction: Weather factors such as temperature has an enormous influence on agriculture. Therefore, efficient weather risk management has become an urgent requirement for this sector. In recent years, a new instrument named weather derivatives has been introduced to cope with production risk. So, this paper aims at designing and pricing the temperature-based weather derivatives (WD) in order to reduce risk exposure for Iranian agriculture industry. For this purpose, a put option with cumulated growing degree days (GDD) as its underlying index has been selected
Materials and Methods: We first examine the relationship behavior of temperature and yield for wheat and Rice in Shiraz. Then, for designing and pricing WD in agriculture, GDD index has been selected as one of the most widely used temperature indicators in agricultural sector. We design this contract for each stage of wheat and rice life cycles instead of designing one contract for crop’s growing seasons. So, the life cycles of two crops (Wheat and Rice) divided into 7 stages titled: Emergence, Tillering, and stem elongation, Gravidity, Flowering, Milky ripe and Maturity. Since contract design happens during these stages, we have 6 contracts for each product. Each contract starts with the beginning of one stage and continues until the other stagestarts.
The GDD index is calculated based on the temperature data and the life cycles of the wheat and rice in Shiraz. So, the long-term mean of GDD is calculated as the Strike level of put option contract. The simulation method based on daily temperature data is used for pricing the contracts. Finally, the expected payoff and the price of the options are determined using the Monte Carlo simulation method.
Results and Discussion: The results revealed a significantly positive relationship between wheat yield and GDD as well as a positive impact of GDD on Rice yield. This implies that increasing growing degree days would increase wheat and rice yield. The R2 coefficient also indicates that 76 percent of the variations in yield of wheat and rice are explained by the growing degree day's index. Therefore, the design of temperature based weather derivatives contracts will have high efficiency in order to cover the risk of farmers.
As expected, rice has a relatively higher strike price than wheat as rice-groups accumulate GDD in warm seasons. We assume that the annual risk-free interest rate r is 15 percent and the expected payoff also the price of the contract put option is calculated based on 10000 Monte Carlo simulations. Based on the results, the most wheat payoff in Shiraz was related to the second contract (from the November 21st to the March 6st). Therefore, the use of the temperature option in this period will compensate farmers for their loss. In terms of rice, the most payoffs in Shiraz have occurred in the twelfth contract (Aug 19st to Oct 17st).
Conclusion: Financial weather derivatives (WD) are designed to serve as hedging instruments against weather risk and to balance the income of producers such as farmers. WD was first traded in 1997 and since then their popularity has increased. However, weather derivatives as well as designing and pricing of contracts based on weather has not been introduced in Iran. Therefore, in present research, while introducing the mechanism of the weather derivatives and options based on weather indicators the designing and pricing of put option contracts based on temperature have been discussed in Shiraz. For this purpose, GDD index has been selected as one of the most widely used temperature indicators in agricultural sector. The GDD index is calculated based on the temperature data and the life cycles of the wheat and rice in Shiraz. So, the long-term mean of GDD is calculated as the Strike level of put option contract. The simulation method based on daily temperature data is used for pricing the contracts. Finally, the expected payoff and the price of the options are determined using the Monte Carlo simulation method. As discussed before, the temperature options for each city and product are designed based on the different stages of life cycles of the crops so we plan and set the price of put options for six different time periods. Based on the results, the most wheat payoff in Shiraz was related to the second contract during the November 21st to the March 6st. Therefore, the utilization of the temperature option in this period will compensate farmers for their loss. In the case of rice, the most payoffs in Shiraz have occurred in the twelfth contract (Aug 19st to Oct 17st). Therefore, it is recommended to use the results of the present study to launch a weather derivative’s market. In addition, it is vital to change and revise these contracts by conducting various studies about the effects of changing contracts specifications on farmers and other Contributors in the market.
S. A. Hosseini Yekani; Z. Nematollahi; M. Hosseinzadeh
Abstract
Introduction: Measuring changes in economic welfare have been known as one of the practical economic issues. So that, this study aimed to calculate the welfare changes resulting from the change in the price of rice in Mazandaran province and is the first study that done using the food groups’ details ...
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Introduction: Measuring changes in economic welfare have been known as one of the practical economic issues. So that, this study aimed to calculate the welfare changes resulting from the change in the price of rice in Mazandaran province and is the first study that done using the food groups’ details and household’s data for estimates demand functionin the country. For this purpose, welfare microeconomic theory and compensating variation (CV) criteria and household income and expenditure data of Mazandaran province in 2014 wereused.
Materials and Methods: Compensating variation represents the net income that the household must be given to restore themto the utility level they were at before the price change. It is negative after a price increasebecause it is expressed as a central authority expenditure to restore the household to thepre-price change utility level. Estimation of compensating variation needtheestimation of households demand system. In this paper, the parameters of the demand system are estimated by applying nonlinear regression to the system of eight share equations. Parameter estimates provided a clearer understanding of household food consumption behavior in 2014, summarized through income and price elasticity. Parameterestimates provide a theoretically consistent model of household food demand that can be usedto evaluate the welfare implications of food price increases.
Results and Discussion: Estimates of income elasticity of demand for urban and rural households are presented in Table 4. The income elasticity revealsthat none of the goods are inferior, while the rice and meat are a luxury for urban households. Other groups such as cereals, dairy, oils and fats, fruits and vegetables, other foods and beverages are also essential commodities for urban households. Rice, meat and fruit and vegetable are the luxury goods for rural households, too. The income elasticity of fruits and vegetables, and other foods are close toone for urban households, demonstrating that welfare analysis of price changes need to account for shifts in demandcaused by the income effect of the changes. The elasticityindicate that the income effectcould be large for these commodity groups. Further evidence about these effects will be provided by the compensatedprice elasticity.Compensated own price elasticity, which measure pure substitution effects, are reportedinTable 5 for urban households and Table 6 for rural households. The elasticity of demand for a beverage is large for all householdsand the elasticity of demand forrice is small for all households. These results indicate that households reduce beverage consumption significantly more than rice consumption in response to price increases. Next, consider a 25, 50 and 198 percent increase in the rice price. This price change causes an increase in household expenditure for both urban and rural households by compensating variation. Increasing in households expenditure for rural households has been greater than urban households. According to the results, urban households have seen 0.38 percent increase in their expenditure by 25 percent increase in rice price. 50 and 198 percent Rice price increasing, increase 1.13 and 19.98 percent of urban expenditure accordingly. Rural expenditure increased 1.31, 3.63 and 52.57 percent by increasing 25, 50 and 198 percent in rice price accordingly. Moreover, the comparison between reductions in household welfare in different income groups has shown that household welfare has declined less when levels of income increased.
Conclusion: This study aimed to calculate the welfare changes resulting from the change in the price of rice in Mazandaran province. For this purpose, welfare microeconomic theory and compensating variation (CV) criteria and household income and expenditure data of Mazandaran province in 2014 wereused. Based on the results, with rising rice prices, household welfare of Mazandaran province has fallen. The welfare of rural households has fallen more than the welfare of urban households. The comparison between reductions in household welfare in different income groups has shown that household welfare has declined less when levels of income increased. Therefore, it is necessary to maintain the household welfare of provinces when the rice price rises and support policies must be adopted.
R. Heydari Kamalabadi; S.A. Hosseini yekani; M. Mojaverian; A.R. Nikooie
Abstract
Introduction: Uncertainty existence in farmers crop production pulsed on important and necessity of science of risk management in the agricultural sector. The new risk management selects the best tools and techniques to minimize risks and consequences of decisions. Furthermore, determining the nature ...
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Introduction: Uncertainty existence in farmers crop production pulsed on important and necessity of science of risk management in the agricultural sector. The new risk management selects the best tools and techniques to minimize risks and consequences of decisions. Furthermore, determining the nature of the risk of crops yield can provide useful information about how to manage the risk of the agricultural sector. One of the effects of climate change is caused damage in the agricultural sector. Dependence of crops to climate change is caused that climate factors have a determinative role in the occurrence of crops damaged. Performed studies on the economic effects of climate change have shown that climate change has a significant impact on agricultural yield and its production risk. Moreover, climate change influences crop yield and the risk of crop yield. Although several studies have been carried out about the impact of climate change on crops yield in Iran, the effect of climate change on crops yield risk is infrequently considered. Therefore, this article tries to offer a new way for calculating the risk of crops yield using of CVaR in the period 2017-2047 in the zayanderud agricultural system. The innovation of this study can be stated as follows:1) This study used of Value at Risk index, as one of the most important indicators of risk measuring, to measure the risk of crops yield, 2) For calculating of Value at Risk index, different studies are used from a famous probability distribution such as normal distribution, historical data or Monte-Carlo simulation, while in this study tried to calculate VaR index based on the forecasted scenarios of crops yield, and 3) In this study, in order to produce future scenarios of crops yield is used from ANN-PSO combined method for forecasting crops yield.
Materials and Methods: The method of this study includes the following steps:
1) The production of possible scenarios of temperature and precipitation using of AOGCM models: Today, one of the best tools for the production of climate scenarios is Atmosphere-Ocean General Circulation Models (AOGCM).But the main problem in the use of the output of the AOGCM models is the large spatial scale of their computational cells toward the area under study. LARS-WG model is also one of the most famous models to small scale for outputs of AOGCM models. In this study uncertainty related to AOGCM models, is used of for scenarios of all AOGCM models(including A1B, B1 and A2).
2)The production of scenarios of selected crop yield and available water in the period 2017-2047: The production of scenarios of selected crops yield and available water is performed using of combinedmethod of ANN-PSO.To combine neural network with particles warm optimization algorithm, from particles warm optimization algorithm is instead of training the neural network using gradient-based algorithms.
3) Measuring risk of crops yield using of VaR and CVaR indexes: VaR index is one of the most important criteria to measure downside risk that it determines the maximum amount of expected losses of a variable for a certain time period and specific confidence level. In this study (according to the non-normal distribution of crops yield scenarios) is used on the historical simulation approach.
Results and Discussion: In the first phase of research methodology, for producing of climate scenarios from daily available stats related to weather stations of Isfahan, Kabuotarabad, Kuohrang, and Daranwere used. Validation results of LARS-WG model showed that this model is well able to simulate changes of climate parameters. Eventually, 44 scenarios of the maximum temperature, minimum temperature and rainfall wereproduced in each studied stations and for each year. The results of the network design using trial and error methods revealed the best forecast combination model obtained with 3 and6 neurons in the input layer and hidden layer of neural network and assuming the initial population of 200, in PSO algorithm. Results of this step showed that ANN-PSO model is well able to forecast crops yield (wheat, barley, maize and alfalfa) and available water. Furthermore, calculating VaR and CvaR criterain confidence level %95 and for future period of 2017-2047, showed that the values of these two criterions for wheat, barley, maize and alfalfa were equal to (4240, 4205), (4062, 4057), (49061,48480) and (10875,10743) kg/ha. The comparison of the values of these two criterions with the values of last period also showed that for all selected crops, VaR and CvaR criterions is bigger in future period toward last period.
Conclusions: The new offered method can calculate the risk of crops yield due to climate change. The more accurate measuring of risk using of new methods such as CVaR can be suitable guidance for policy man to better management of production risk of crops.
S. Ahangari; S.M. Mojaverian; S.A. Hosseini Yekani
Abstract
Introduction: The market of agricultural products has always faced with a lot of limits and structural problems in Iran. The most part of these problems are related to non development of agricultural economy of our country and also traditional and inefficient structure of the market of agricultural products. ...
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Introduction: The market of agricultural products has always faced with a lot of limits and structural problems in Iran. The most part of these problems are related to non development of agricultural economy of our country and also traditional and inefficient structure of the market of agricultural products. According to non-transparency of market information, its traditional structure, as well as the risk of agricultural activity, it was expected that agricultural ring of Iran Mercantile Exchange (IME) is effective in order to prevent the above mentioned obstacles; however from 2007 up to now, less than 1 percent of agricultural products arrived to this market and IME couldn’t have a leading role in the market of agricultural products. Although previous studies have examined some of the obstacles of IME development, but few researches have investigated choose of suitable products for trading across this market. In this study, it is tried to study the performance of agriculture ring of IME with focus on commodity selection criteria of such markets.
Materials and methods: In this study, two approaches of conventional taxonomy and weighted taxonomy are used in order to achieving the goals. In conventional taxonomy, component coefficients are constant and equal to one. But at the same weight taxonomy approach, data were weighted by Shannon entropy method. The required data of this study have been gathered from official websites of Statistical Center of Iran, Iranian National Standards Organization, Ministry of agriculture Jihad and Iran Mercantile Exchange. It is worth noting because of lack of access to updated data; the data of 2013 was used in this research.
Results and Discussion: Because of lack of data, 10 out of the 19 accepted commodities of IME were analyzed. The most obvious difference between the two methods of conventional and weighted taxonomy in this study is removal of pistachios in the conventional taxonomy. After obtaining the distance matrix, it was observed that pistachios have passed upper bounds and therefore, this product has been removed for the rest of the calculations. In the weighted taxonomy through Shannon entropy, none of the goods is removed. Finally, rice and maize identified as two top products on the list of most suitable commodities for trading at IME. Wheat and tea are also got the ranks of third and fourth respectively in conventional and weighted taxonomy approaches. According to the Iranian people's taste, good choice of rice as the first rank in this study was not surprising and is in line with reality. This product has an important role in satisfying the protein and calories of the world people. So, the more rice trades at IME, the more agricultural ring is successful. Corn, wheat and tea have also comparative importance across the studied agricultural commodities and expanding their trades at IME would have a major contribution in the success of agricultural ring.
Conclusions: As mentioned, rice has upper priority across the other studied commodities for trading at IME. After rice, corn, wheat and tea ranked second, third and fourth more suitable commodities. According to the results of this study, it is suggested that, factors such as the coefficient of importance and continuity in supply should consider as importance factors of commodity selection. According to the ranks of selected commodities, direct support of government could have an important role in the success of commodity in trading at IME. In order to successful entrance of agricultural commodities to IME, further support from the government is required. It is also proposed that free regional public educations are planned for small and large farmers to understand the agricultural ring of IME and its common standards and trading strategies. A package of incentive policies such as purchase guarantees in the absence of successful trading at IME and partial waivers on transporting costs to the warehouses is also proposed. Next to the contrary, it is also required to have some punishment policies so that in the absence of trading at IME for some farmers, financial supports such as loans or guaranteed purchase of those farmers would be far out of reach. Also decreasing the distance between IME and farmers through expanding the number of accepted warehouses in production areas by IME could ease the entrance of farmers to this market.
T. Ranjbar Malekshah; S. A. Hosseini-Yekani; S. M. Mojaverian
Abstract
Introduction: Farming has a significant role in the economy of developing countries. The farming activities face with various dangerous, non-certainties and lots of problems due to natural disasters, price fluctuations in market place and social and behavioral conditions of farmers. Farmers encounter ...
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Introduction: Farming has a significant role in the economy of developing countries. The farming activities face with various dangerous, non-certainties and lots of problems due to natural disasters, price fluctuations in market place and social and behavioral conditions of farmers. Farmers encounter lots of risks in their farming decisions. Generally, there are three kinds of farmers including 1) risk-averse 2) risk-neutral and 3) risk-taker. The majority of previous studies have shown that the most of farmers are risk-averse, but with different rates of risk aversion.
Materials and Methods: Estimating the utility function is one way to quantify the risk. But while there is no certainty and decision making condition is risky, concept of “expected utility” will be considered instead of general concept of utility. In the present study, Direct Elicitation Utility Function (DEU) is used in order to calculating the degree of absolute risk aversion of farmers. In this approach, it is assumed that individual farmers are concerned about the variability of return of production decisions.
The utility function will be shown with U(Y) in which Y is the monetary gross margin of a farmer in specific period of time. The expected utility of the farmer is . The expected monetary margin will be defined with and certainty equivalent (CE) is the monetary margin that comes from the relation of . In DEU method, several mathematical forms of utility functions can be considered as the utility function of producers. Since in the form of negative exponential utility function, the absolute risk aversion coefficient is constant, in this study, the utility function of producers is , where shows the degree of absolute risk aversion. After calculation of farmers’ absolute risk aversion coefficients, the relationship between calculated coefficients and socio-economic characteristics of farmers (such as their age, farm size, family size, education and agricultural experience) were analyzed.
Results and Discussion: In compliance with relation and considering the negative exponential utility function, can be proved:
Where to are four probable levels of farmers’ gross revenues and to are the probabilities of these revenues. Utilizing DEU method, the rates of absolute risk aversion of farmers (high risk aversion, weak risk aversion and medium risk aversion) were calculated for 169 farmers in Sari-Goharbaran. According to the results, 41 farmers (24.2 percent) were weak risk averse, 81 farmers (47.9 percent) were medium risk averse and 47 farmers (27.8 percent) were high risk averse. Findings of the study showed that most of the farmers are medium risk averse. The second part of the findings showed that there is a significant relationship between farmers’ age, farm size, family size and farming experience and the rate of absolute risk aversion. As it was shown in the table 3, the age of farmers has positive relation with the degree of absolute risk aversion of farmers and the family size, farming experiences as well as farm size have negative relation with that degree. Also, according to the t-statistic, estimated coefficients were statistically meaningful at 95% and 99% which means if the farmer’s age increases by one year, then the degree of risk aversion of farmers rises by 95% confidence level, ceteris paribus. In addition, it can be stated that if the farming experiences increase by one year, the absolute risk aversion coefficient declined by 0.34 unit, by 99% certainty. Similarly, by increasing the number of family members and size of farms by one unit, the degree of risk aversion of farmers reduced to 0.37 and 0.98 unit respectively as well.
Conclusion: As the results advocate, the majority of farmers are in the class of average risk averse. Therefore, some measures should be taken to decrease the degree of risk aversion of farmers. This can carried out by the farmers as well as the agricultural sector policy makers. Utilizing the risk reduction techniques, such as crop diversification, insurance, establishing commodity derivatives and futures markets, farmers can reduce their risks. According to one of the results of this study, stating that whenever the farm sizes have risen, the degree of risk aversion has dropped, it is suggested that policy makers try to integrate lands in the agricultural sector. Also, as it is revealed that, by enhancing the experience of the farmers, their degree of risk aversion declines, so, through the educational and prompter classes, the farmers experience can be enhanced, despite the fact that education directly has no significant effect on the degree of risk aversion.
Z. Nematollahi; S.A. Hosseini-yekani; M. Hosseinzadeh
Abstract
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 ...
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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.
S.J. Mohammadi; S.A. Hosseini Yekani; H. Ghaderzadeh
Abstract
Introduction: In the developed world, particularly in developing countries, livestock is the most important agricultural sub-sector.Livestock of primary and secondary industries has an especial place in the national economybecause of their greatvalue of products, creating job opportunities, providing ...
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Introduction: In the developed world, particularly in developing countries, livestock is the most important agricultural sub-sector.Livestock of primary and secondary industries has an especial place in the national economybecause of their greatvalue of products, creating job opportunities, providing health products for consumers, increasing export income of the economy throughaccessing global markets of livestock products and finally their undeniable role in acquiring food security.The demand for milk in Iran increased due to an increase in population and the amount of milk production was also increased. The great share of increased produced milk goes to the industrial dairy farms. One of the major methods to increase the amount of milk production continually is to make its production efficient and improve economic conditions. The current study attempts to determine the efficiency and ranking of industrial dairy farms in Saqqez and Divandarreh cities using super-efficiency model.
Materials and Methods: The statistical populations of the study are all active industrial dairy farms of Saqqez and Divandarreh cities which are about 19 farms. The required data for calculating the efficiency were gathered by surveying and completing questionnaires for the year 2013. In this study first, for each farm Data Envelopment Analysis (DEA) method and GAMS software package were used to estimate super efficiency. Super efficiency is a form of modified DEA model in which each farm can get an efficiency greater than one. Then in order to make sure about being unbiased the obtained super-efficiency scores, the modified model of Banker and Gifford, was re-estimated and the conventional efficiency scores of farms were compared by normalizing and removing some of the scores of outlier farm based on pre-selected screens. The model has suggested conditions for which some of the estimates for dairy farms might have been contaminated with error.As a t result, it has been ranked as an efficient farm.
Results and Discussion: The statistical description of the farms studied showed that, the highest and lowest amount of produced milk from one dairy were in the range of 845 and 250 kg per month. The super efficiency estimation showed that the mean of farms'super efficiency based on the assumption of variable return to scale for input-oriented is 1.01. About 58 per cent of the studied dairy cattle farms were inefficient and the Super-efficiency of about 42 per cent of total farms got scores under the average. The amount of λ_k^* for all farms except for farms 3 and 5 has become 0. Furthermore, these two farms in primitive super efficiency model have become infeasible. Therefore, they have been considered as reference farms. The results of super-efficiency method and efficiency conventional DEA method were compared together and inefficient farms got the similar efficiency and super-efficiency scores, and efficient farms whose super-efficiency score had been equaled or more than 1, stand over frontier production function in the conventional model. To determine the sensitivity of results to removing the outliers, three different levels (1
F. Kashiri Kolaei; S. A. Hosseini Yekani; S. M. Mojaverian
Abstract
Introduction: Market power is an important factor affecting welfare. Existence of market power on the purchase side reduces supplier welfare. However, existence of market power on the sales side reduces supplier welfare. Some believe that the agricultural market structure is a monopoly. In fact, most ...
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Introduction: Market power is an important factor affecting welfare. Existence of market power on the purchase side reduces supplier welfare. However, existence of market power on the sales side reduces supplier welfare. Some believe that the agricultural market structure is a monopoly. In fact, most of the agricultural products can be purchased by small firms and then delivered to consumers because they are perishable and need certain storage conditions. Thus, a monopoly condition is created in the market. In Iran, pistachios are amongst the agricultural products that can be important for investigating the market structure and for its effects on social welfare. This is due to the fact that the price of pistachios has fluctuated sharply because of many reasons such as the existence of major buyers such as the Rafsanjan Pistachios Producers Cooperative. Monopolistic firms determine the price that causes problems such as losing trade, creating extra profits for the seller and reducing consumer surplus. However, effective implementation of policies requires identification of market structure. In this context, in the present study for investigating the effects of Iran pistachios market structure on social welfare, the spatial equilibrium model was used which is based on maximizing net social payoff (NSP) and is able to consider the variety of market powers in suppliers and consumers.
Materials and Methods: One of the noteworthy features of the spatial equilibrium model is that it is able to examine the price equilibrium in each of the market power degrees. In this study, the conjectural variations parameter was used to consider the market power in the model. This index represents the reaction of firms to change the behavior of a particular firm. The final equations of Iran pistachios spatial equilibrium model can be seen in the following equations:
Max NSP = -
s.t - +
+
j
, , xfj,k, ti,j ≥0
Where NSP is the net social payoff, i and j respectively represent the pistachios supplier and consumer provinces and f represents the method of export of pistachios including by road, sea, air or railway. Vfjk is the yield per Kg of pistachios exports in different ways from the j-th province to the k-th country, Sfj is the pistachios exports capacity of the various ways from the j-th province, Xfjk represents the pistachios exports from the j-th province using the f-th way to the k-th country and mk is the imported pistachios of each country from Iran. Moreover, rij represents conjectural variation, and respectively represent pistachios supply and demand in the provinces j and i, and represent the total shipped pistachios from the i-th province to the j-th province and shipped pistachios for domestic consumption of j-th province, respectively. and respectively represent the demand and supply curve equations according to and . It should be noted that in the perfect competition market rij is equal to -1 while in a monopoly market it is equal to 0. In this study, the 2010 data were used for the calculation of the parameters. Also, for welfare investigating, the surplus of consumers and suppliers were calculated by the following equations:
Consumer surplus : CSj=
Producer surplus: PSi=
Results and Discussion: According to the results of this study, pistachios market structure is far from perfect competition in Iran and creating the perfect competition conditions leads to nearly a double increase in consumers’ welfare and a reduction in the suppliers’ welfare about 0.13%. In general, switching the Iran pistachios market structure has significant effects on domestic consumers but pistachios suppliers are less affected because they export more pistachios to foreign countries. Most of the changes in consumers’ welfare are made in the provinces that are mostly consumers of pistachios and have low or no pistachios production (such as Golestan, Hamedan, Ardebil, Chaharmahal and Bakhtiari, Kordestan and Markazi). In contrast, the lowest welfare changes are associated with the major pistachios supplier (such as Kerman, Yazd, Hormozgan and Sistan and Baluchestan).
Conclusion: Since pistachios are mainly exported and in fact the price of pistachios in the domestic market is higher than the price of Iranian pistachios in foreign markets, a significant increase in the price of pistachios has negative effects on domestic sales and consumers welfare. Since one of the main reasons for the high price of pistachios in Iran is related to market power and the existing monopoly, it is essential to establish certain policies to combat this monopoly. Pistachios exchange can be noted among the policies that are effective in changing the market structure. Also, creating conditions for the entry of new firms into the pistachios market is effective in reducing monopoly in it.
Keywords: Market Structure, Welfare, Spatial Equilibrium Model, Pistachios
S.M. Mojaverian; F. Rasouli; S.A. Hosseini-Yekani
Abstract
One of the farmers' marketing decisions is how to sell their products to the market. They sell their products in different ways, for example pre-sell, local dealers and wholesalers,. This paper aims at investigating citrus distribution channels and evaluation of factors affecting the choice of each ...
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One of the farmers' marketing decisions is how to sell their products to the market. They sell their products in different ways, for example pre-sell, local dealers and wholesalers,. This paper aims at investigating citrus distribution channels and evaluation of factors affecting the choice of each channels by Mazandaran ‘s producers. The data was collected by simple random sampling method. 252 farmers from 15 cities were interviewed in 2011. In order to conduct the study, the Method of three-layer Nested Logit model was used. The estimated results showed that the variables of the garden distance from nearest town, gardener experience, selling time, marketing costs, product type and dominant style of selling in the region are crucial factors in selecting the distribution channel. Each of these variables had different effect on selecting in each selling channels, Nevertheless, the variables of selling time and product type were of a greater importance.
S..A. Hosseini-Yekani; M. Zibaei
Abstract
Abstract
In this paper an attempt is made to determine the most suitable agricultural commodities to be adopted for establishing a futures market in Iran. Two different approaches are adopted: the first involves identifying factors that contribute significantly to the success or failure of existing ...
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Abstract
In this paper an attempt is made to determine the most suitable agricultural commodities to be adopted for establishing a futures market in Iran. Two different approaches are adopted: the first involves identifying factors that contribute significantly to the success or failure of existing agricultural commodities futures contracts in established futures markets. The second involves simulating the hedging performance of potential commodities to determine the optimum contract choice. According the results of this study, commercialization rates, cash market size and spot price fluctuations of commodities have the greatest effects in the success of their futures trading. Also, although some of commodities have acceptable levels of the necessary conditions for entering them into futures market, they don’t have enough attraction for their use as futures contracts in terms of producers' hedging effectiveness. The results suggest that saffron, pistachios and rice are the three most feasible commodities to be adopted in order to establish commodity futures trading in Iran.
Keywords: Futures Contracts, Commodity Specifications, Hedging Performance, Agricultural Commodity Exchange, Iran