مجله اقتصاد و توسعه کشاورزی
سال سی و پنجم شماره 1 (پیاپی 50، بهار 1400)

Water scarcity, improper management of water resources, excessive application of chemical inputs, and lack of proper cultivation patterns are present in agriculture. Lack of attention to these cases will inflict irreparable damage on the agricultural sector. Accordingly, attention to sustainable agriculture, conservation of water resources and prevention of improper use of chemical fertilizers are essential to reduce environmental pollution. In many cases, there is agreement on the river basin scale as a suitable spatial scale for analysis of water resources management. Tajan Basin with area of about 4187 km2 is one of the important parts of Caspian Sea Basin. The Current status of water resources in Tajan basin due to decrease in river runoff, has doubled the focus on the basin's water resources management.

In this study, with the help of positive mathematical planning and maximum entropy approach in GAMS, policies to reduce the use of chemical fertilizers and water in selecting the appropriate cultivation pattern for 2017 in the Tajan basin were reviewed. Within the model, the farmer maximizes the expected utility of their stochastic income, subject to resource and non-negativity constraints. To include both market and yields uncertainty, we calculated profit covariance matrices by using national averages for prices and yields for the 2018–2009 period. The resource constraints include land, water and fertilizer. Selected irrigated crops in the region include rice, wheat, rapeseed and corn. In the present study for simulating farmers' response, reduction scenarios including 5%, 10% and 15% of available water and fertilizer are considered. There are also two environmental sustainability index that are related to amount of the used fertilizer and water. The smaller the index is, the greater sustainability is provided in crop production.

Calibration of PMP pattern with maximum entropy approach showed that there is no difference between the value of target function, inputs and cultivation level in the current situation and calibration pattern. In all water reduction scenarios, the total cultivation area decreased. The results indicate that the agriculture in the basin is vulnerable due to changes in available water. The 15% decrease in water resources causes a significant decrease of 15/903% of the cultivation area. Cultivation area under fertilizer reduction scenarios has been lower in comparison with water scenarios, and so reduces the used fertilizer and increases soil conservation and water stock. In reduction scenarios of water and fertilizer, land reallocation is reduced due to less reduction in expected utility of farmers. In water scarcity conditions and lack of fertilizer, rice and wheat crops have higher economic benefits per hectare than other crops. The sustainability index for used fertilizer in all reduction scenarios of water and fertilizer is lower than the current pattern. Also the index of the used water in the PMP model is lower than the baseline in the region that decrease was 0.018%, 0.144% and 0.319% at three levels of 5%, 10% and 15%, respectively. In the scenario of 15% reduction of fertilizer, land allocation and economic benefits decreased by 13.83% and 0.034%, respectively. However used fertilizer and water index improved to 1.348% and 0.319%, respectively. Therefore, improving the water and fertilizer application index has a higher priority than reducing the expected utility in the region.

In the current cropping pattern, farmers do not pay attention to the environmental characteristics and sustainability of the region. While with the policies of reducing the quantity and price of chemical inputs and introducing different types of sustainability indicators, it is possible to develop a cultivation model. In addition to earning the necessary profit, it enables the optimal use of fertilizer and water inputs. Changing the behavior of farmers compared to the current pattern of input consumption requires strong motivation and reasons. Therefore, water quality tests and soil decomposition in the region, as well as providing appropriate formulas for optimal use of chemical fertilizers is needed. Extension services to increase people's awareness is a good solution for optimal use of inputs and increase the level of cultivation and farmers' profits.

Almost all rural communities in Iran are exclusively engaged with agriculture, therefore farming remains the largest source of income for them. Agriculture can be a major driver of growth for the Iranian economy. Therefore, increasing factor productivity in the agricultural sector is essential and by growing population rate, the need to invent more productive systems is highlighted. In this regards, smallholder agriculture, which is marked by low productivity should be transformed into agribusiness corporations which could foster the income and productivity of enterprises. Regarding the effective role of agribusiness corporations in enhancing agricultural productivity, and providing livelihoods and employment in rural communities, this study aimed at investigating the impact of location decision, social and human capital factors on the longevity of an agribusiness corporation called Khezri Agribusiness Corporation located in Khezri Township from Sothern Khorasan province. The reason for choosing Khezri Corporation as the case study was that according to surveys, this corporation has been one of the most successful agricultural associations for many years and has been able to create job opportunities to stop migration towards big cities. To the best of our knowledge, this paper is the first attempt to expendably investigate the factors affecting the continuity of an agribusiness corporation in Iran.

In order to achieve the objectives of the research, a well-structured questionnaire has been designed according to the literature review and using the opinions of university professors and experts of Khezri Agricultural Corporation. In this study, location factors, social capital and human capital are three main structures that are assessed by providing the information extracted from the questionnaire, and then, the impact of each structure on the continuity of the corporation's activity has been investigated based on indexing method. Each of the structures consists of different dimensions, and each dimension is measured by a number of items or questions using a Likert spectrum. Simple random sampling procedure was used to obtain the size of sample. At the end, the sample size was estimated at 45. Applying a systematic random sampling technique, the respondents were selected and the final questionnaire was distributed among them. At the primary analysis, 15 questionnaires were excluded from the analysis due to the large size of missing information. A total of 30 questionnaires were selected for further analysis. It is worth noting that in most cases, the questionnaires were tried to be completed in the form of interviews to increase the accuracy of the work.

Study findings suggest that location, social and human capital factors are at a high level of importance in the studied corporation. From the viewpoint of respondents, social capital had the greatest impact on the longevity of the corporation, followed by location and human capital. Furthermore, the communication dimension in social capital, the infrastructure factors in the location decision and the non-cognitive abilities in the human capital have been identified as the most influential components on the longevity of Khezri Agricultural Company's activities. Among the infrastructural factors, the criterion of "existence of basic resources" such as water wells, aqueducts, qanats, underground aquifers, etc. is the most effective criterion. According to 93.3% of respondents, this factor has a moderate to high impact on the corporation's location.

We recommend effective communication and planning in improvement of communication between organizational units and communication between managers and employees needs to be strengthened. Internalization of the organization's vision, mission, and goals, implementing a goal-based management plan, and applying the suggestion system in the organization and investing in formal and organized training are recommended as well to sustain the agribusiness corporations. It must be noted that given that the findings of this study are largely in line with the research background, its recommendations are expected to be applicable to the other agricultural business corporations in Iran. In addition, as we formerly discussed in the introduction of this paper,despite the benefits of agricultural corporations, few of these companies are currently active in the country. Therefore, analysis of factors affecting farmers’ decision to be involved in establishing agribusiness corporations should be the subject of future research.

Annually, large quantities of agricultural products are wasted and a lot of damage is done to the country's financial and food resources. The most important causes of this waste are related to the various sectors of transportation, packaging, storage, processing and distribution of agricultural products. One significant tool to increase in supply chain productivity and reduce logistics costs of the agricultural sector is to establish agricultural logistics centers. The current study seeks to identify a suitable area for the construction of an agricultural logistics center in Isfahan province. In this regard, criteria affecting the selection of locations for logistics centers (compensatory and non-compensatory) were first identified and then the process of locating was implemented in two separate phases. In the first phase, in order to identify potential site options for a logistics center within the province, geographical boundaries associated with non-compensatory criteria were excluded from the study. In the second phase, according to the mathematical model presented, the cost of establishing a logistics center was calculated in possible sites in terms of compensatory criteria and then relevant geographic data layers were developed and, at the end, all data layers were integrated.

This paper, first, studies the experimental literature in the field of successful logistics centers across the world as to identify criteria affecting the location of agricultural logistics centers in terms of non-compensatory grammatical (geological and environmental factors) and compensatory (measurable factors with quantitative values) criteria. Next, the process of locating is implemented during two stage. In the first stage, in order to identify possible sites for Logistics Park within the province, geographic data layers associated with non-compensatory criteria are gathered and the respective boundaries are excluded from the study. Note that in order to unify mapping units being studied with respect to 1: 2500000 scale map of analytical maps used, the province is divided into 4510 separate blocks of 25 Km2. For the second stage, based on the general framework of logistics activities, the spatial analysis is carried out for load flows (the production and consumption profiles) of agronomic, horticultural and livestock. According to the location theories in minimizing costs, a mathematical model is developed to compute costs of agricultural logistics center establishment per each 1440 blocks located in potential sites in terms of compensatory criteria and then under the Arc GIS software environment, all data layers related to these criteria are developed and integrated. The best option is to install a block logistics center having the minimum cost. Due to the large volume of data gathered as well as the variety of analysis and calculation units (blocks of 25 Km2), the C++ programmer is used to perform algebraic and matrix calculations. (Road and rail) distances applied in the model for different origins and destinations are calculated and extracted as the distance of the network through the Arc GIS software. Raw data of road bill of lading blocks have been obtained from the Road Maintenance and Transportation Organization of Isfahan for the period between 2013 and 2018 for the commodity groups including agronomic, horticultural and livestock

The most optimal (least expensive) area for the establishments of an agricultural logistics center is located in the west of the urban complex of Isfahan and between the counties of Tiran and Karvan, Najafabad and Lenjan. The proposed area acts as an intermediary between the production centers of agronomic, horticultural and livestock products in the west of the province and the urban complex of Isfahan as a major consumer of agronomic, horticultural and livestock products. Proximity to the west-north freeway makes it possible to send the province's surplus products to the northern and eastern provinces of the country.

Agriculture is a risky activity and a wide range of risks are affecting the income earned from agricultural products. Market risk is the main source of revenue fluctuations in agriculture in all over the world. One of the subsectors of agricultural sector is animal farming industry that its changes during recent years have greatly influenced the revenue of investors in this industry. Considering the importance of livestock subsector in the agriculture sector, identifying and estimating the risk of livestock units are important.

The first step in activity risk management is to choose a model to identify and measure the risk of that activity. Risk assessment models are selected based on different factors such as the type of projects and their risks. In this regard, a concept discussed in the field of risk assessment in agricultural units is the value at risk (VaR) criteria. Value at risk is a statistical analysis that is mainly used in determining the quantitative risk of market and measures the most expected losses under normal conditions of the market and also during a certain period of time at a specific level of confidence (Radpour & Abeduh Tabrizi, 2009). This criterion summarizes the risk of portfolio in just one number under the value at risk measure. In the present study, the profit of each calf was calculated and the risk of weekly profit of a head of calf was determined by the value at risk method using Monte Carlo simulation for two time periods of 2004 to 2018 and 2013 to 2018 by @Risk add-in. Also, a multivariate regression was estimated by @Risk to analyze the sensitivity of the expected profit for each variable in the model. Parameters that have the most impact on the profit of each head of calf are identified as the most sensitive and important inputs related to the profit variable. Finally, the value at risk of the last cattle feeding period in the confidence level of 95% using weekly VaR at a level of 95% is predicted.

In this study, after calculating the profit of each Holstein calf, a linear regression was estimated to evaluate the standard deviation of the calculated profit on the time trend. This regression coefficients indicate that the standard deviation of the profit is increasing at the rate of 1622.9 Rials/week during the studied period. In other words, the risk of fattening activity has increased over time. To assess the risk of cattle fattening industry profits, price and performance variables were considered as expected variables in calculating the risk of profit. As the concept of value at risk is tied to the probability distribution of inputs and outputs, and its calculation process is equivalent to the probability distribution estimation process in the future period and also, considering that the Monte Carlo simulation is done on the repeated unstable and random inputs prices based on their probability distribution, finding the best distribution of inputs to produce random numbers is very important. Therefore, at first, the most important inputs in calculating profit were determined and then, their probability distributions were obtained according to the defined range of distribution using @Risk add-in. Because of the continuous nature of data, the Anderson-Darling test was used for verification of the obtained distributions. After Monte Carlo simulation and production of semi-random numbers for the desired inputs, 100000 simulated profits were obtained which the corresponding percentile of 90, 95, and 99% confidence intervals of the profit distribution were extracted as a weekly value at risk of per head Holstein calf. The results of estimating profit risk by VaR criteria showed that the weekly profit value at risk during 2004 to 2018 was 302108 Rials/week which is not a small figure for each calf profit during a week and presents the high profit risk of this industry. Also, the value at risk at the last 6 years of studied period was 600000 Rials. In conclusion, the results showed that weekly profit VaR increases 65292.07 Rials in each period. According to the predictions, the VaR of next period with a confidence coefficient of 95% will be 7197729 Rials. Also, the results of sensitivity analysis revealed that the most effective inputs on weekly profits were the prices changes of the calf, maize, and alfalfa inputs. Therefore, these inputs changes can also affect the risk of profit in cattle feeding units. In conclusion, controlling the living calf market as the most important input and veal market as the product of the fattening industry and corn, alfalfa, and soy markets has the most impact on the stability of the producers' profitability and ensures the profit of each head of livestock.

In this study, VaR criterion was used to assess the profit risk of cattle feeding units in Iran. According to the results, it is suggested to introduce the VaR criterion as an applied criterion in determining the risk to producers and investors of the agricultural sector. Therefore, it is necessary to provide continuous report of the value at risk amount of the industry by relevant organizations to help the investors and producers to clarify the status of the cattle feeding industry. Also, considering the changes in market conditions during different periods, finding the most important effective inputs on profit and controlling these inputs markets in order to control the producer’s profit fluctuations should be taken into account.

Climate change and increasing global warming are intensifying droughts, changes in rainfall distribution and depletion of water resources over time. Persisting hot and dry weather has intensified the phenomenon of climate change and posed serious threats to the country's water resources, resulting in the inability to meet the needs like drinking, environmental, industrial and agricultural ones. The fifth report of the Climate Change Board also shows that the phenomenon of climate change in many parts of the world has had a negative impact on agricultural production; but the application of appropriate and timely adaptive scenarios against climate change can reduce the negative effects of this phenomenon on the agricultural crops yield. Bushehr province is mostly exposed to climate change and drought because of its geographical location. According to the National Meteorological Center, the area affected by drought in this province during the ten-year period ending in March 2019, was 83%. Up to 80% of the plains of the province have a negative groundwater level. This problem is more severe in some plains of the province, including Bushkan plain, the water level of this plain has decreased by 1.31 meters annually. This plain is considered as the agricultural hub of province and Dashtestan city. Thus the study of the effects of climate change on the hydrological and agricultural situation of the Bushkan plain and the analysis of the effectiveness of adaptive scenarios to reduce the negative effects of this phenomenon is very important.

In this study, in order to create optimistic and pessimistic scenarios of climate change, the LARS-WG microscale model was used. Then, in order to investigate the effects of climate change on the hydrological status of Bushkan plain, water needs of agricultural crops and crops yield, simulated climate change scenarios and adaptive scenarios include improve irrigation efficiency and deficit irrigation were entered into WEAP model and its agro-agricultural model, MABIA. For the purpose of investigating the adaptation of agricultural production systems to changes in available water and yield as well as to measure the effectiveness of adaptive scenarios, a positive economic planning model was used. For economic model, statistics and information related to the cultivation area, production costs, prices and yields of crops in different areas of Bushkan plain were obtained through the Jihad Agricultural Organization and also completed 100 questionnaires from farmers in the area. Random sampling method was used to calculate the sample size.

By applying two scenarios, optimistic A1B and pessimistic A2, in general, it can be concluded that the most changes in precipitation were in autumn and winter and the most temperature changes were at least in autumn and spring. Also, applying a pessimistic scenario will cause more drastic changes than an optimistic scenario. The results of MABIA model show that by applying both climatic scenarios, the average water requirement of all agricultural products increases during the simulation period compared to the base period.Increasing water demand and decreasing available water have caused water stress and as a result reduced the yield of various agricultural products in Bushkan plain. The results show that the average crop yields decreases, but the highest reduction of yield in both scenarios is related to wheat crop. The results of PMP model indicates that the application of optimistic and pessimistic scenarios will reduce the area under cultivation of this plain by 42% and 55%, respectively. On the other hand, among different crops, the area under cultivation of crops such as wheat, barley and watermelon has declined more sharply. However, the application of adaptive scenarios to improve irrigation efficiency and under-irrigation somewhat offsets the effects of climate change. In optimistic climate change, adaptive scenarios to improve irrigation efficiency and use of deficit irrigation method will improve the area under cultivation of agricultural products by 6 and 4 percent, and in pessimistic climate change by 3.8 and 2.3%.Comparison of the results of applying adaptive scenario shows that despite the less effect of deficit irrigation on improving the area under crops, the increase in profit in this scenario is more than the improvement of irrigation efficiency and the reason is the costs of improving irrigation efficiency compared to the deficit irrigation scenario.

Principles of resource management and low productivity have led to declining groundwater levels and as a result the ban on the exploitation of more groundwater in the plains of Bushehr province, including the Bushkan plain. Accordingly, in this study, the consequences of climate change on the hydrological and agricultural situation in the Bushkan plain of Bushehr province as well as the effectiveness of adaptive scenarios were investigated .Finally, based on the results of the present study, it is suggested that farmers use scenarios such as deficit irrigation methods and improve irrigation efficiency to prevent water loss and reduce the yield of these crops. However, since the results showed that using deficit irrigation method will improve agricultural profits more than improving irrigation efficiency, therefore, using deficit irrigation method has priority over improving irrigation efficiency. Also due to the low impact of climate change on water demand and canola yield, canola is suggested to local farmers as an alternative crop for wheat and barley crops.

Agriculture is one of the basic sectors of any country and is very important in creating employment and production of industrial raw materials. Although the most important role of agriculture in any country is to provide the food security. The world's population is growing, and resources are dwindling. Therefore, feeding the growing population of the world requires more agricultural production. One of the ways to increase agricultural production is to increase yield per hectare. Chemical fertilizers significantly increase production per hectare. But excessive use of chemical fertilizers can also lead to environmentally externalities such as groundwater pollution, reduced quality of agricultural products and endanger human health and the environment. Therefore, the optimal use of production inputs in the agricultural sector is essential. Unfortunately, despite the emphasis of agricultural economists on the optimal use of production inputs, this issue has been taken for granted by farmers and policymakers in the agricultural sector. The purpose of this study is to determine the optimal economic level of use of chemical fertilizers (nitrogen, phosphate and potash) in the production of irrigated wheat and barley.

In order to determine the optimal economic level of chemical fertilizer inputs (nitrogen, phosphate and potash) in the production of irrigated wheat and barley in Iran, Bayesian approach and non-normally distributed stochastic plateau function, based on the developed Von Liebig algorithm were used. The estimation of the optimal amount of input usage depends on the functional form and the distribution assumptions based on the production data. The stochastic plateau function is one of the functions has been used to determine the optimal amount of inputs (especially chemical fertilizers). The stochastic plateau function provides insight into why farmers may over-use inputs. The efficiency of the linear stochastic plateau function is better than nonlinear and polynomial functions, and it estimates a more realistic pattern of farmers' expected profits, because the function is stochastic. For simple model estimation, only the input of chemical fertilizers (nitrogen, phosphate and potash) is considered as the limiting resource. If it is assumed that the threshold point is related to the intercept, which represents the yield of crops without input consumption, the equation of the stochastic plateau function is written as the following relation: (1)   Where the yield of the crops in Iran, K is the amount of input in the crop production,  and θ are the coefficients of the yield function that must be estimated, and  is the transmitter intercept that represents all random variables. The used data in this study were collected from agricultural statistics and the production cost database of the Agriculture Ministry. The panel data were collected during 2007-2017 period.

Based on the results of the study, the average optimal consumption of nitrogen fertilizer in the production of irrigated wheat and irrigated barley in Iran was estimated 117.05 and 29.00 kg/ha, respectively, while the current average consumption of nitrogen fertilizer in the production of irrigated wheat and barley is 163.626 and 38.75 kg/ha, respectively. In other words, during the years 2007 to 2017, the amount of nitrogen fertilizer used in the production of irrigated wheat was 46.576 kg/ha (equivalent to 28.46%) and in the production of irrigated barley was 9.75 kg/ha (equivalent to 25.16%) more than the optimal level. Also, the potential yield of irrigated wheat and barley with respect to nitrogen fertilizer input was estimated 2754.5 and 2549.80 kg/ha, respectively, in the Bayesian method. The average optimal use of phosphate fertilizer in production of irrigated wheat in Iran was estimated as 97.70 kg/ha, while the current average consumption of phosphate fertilizer in production of irrigated wheat is equal to 123.06.02 kg/ha. In other words, during the years 2007 to 2017, the amount of phosphate fertilizer used in the production of irrigated wheat in Iran was 25.362 kg per hectare (equivalent to 20.609%) more than the optimal level. Also, the potential yield of irrigated wheat due to phosphate fertilizer input, about 2904.54 kg/ha has been obtained in Bayesian method. the average optimal consumption of potash fertilizer in the production of irrigated wheat and irrigated barley in Iran was estimated 39.68 and 81.81 kg/ha, respectively, while the current average consumption of potash fertilizer in the production of irrigated wheat and barley is 50.64 and 134.18 kg/ha, respectively. In other words, during the years 2007 to 2017, the amount of potash fertilizer used in the production of irrigated wheat was 10.96 kg/ha (equivalent to 21.65%) and in the production of irrigated barley was 52.37 kg/ha (equivalent to 39.02%) more than the optimal level.

According to the results of present study, farmers in the production of wheat and barley use chemical fertilizers (nitrogen, phosphate and potash) more than the optimal amount, so that the average optimal use of chemical fertilizers of nitrogen, phosphate and potash in the production of irrigated wheat, respectively 28.52, 20.59 and 78.36, and in the production of irrigated barley, the average optimal use of nitrogen and potash chemical fertilizers, respectively 74.84 and 39.03% per hectare, are less than the current amount of chemical fertilizer use in the country. According to the results of the study, in order to more efficiently use of chemical fertilizers and to reduce environmental pollution caused by their use in agricultural production, the government should reduce the direct payment of chemical fertilizer subsidies. Regarding the elimination of subsidies and pricing of chemical fertilizers (nitrogen, phosphate and potash), the importance of the type of fertilizer in crop production, input production elasticity and input demand elasticity should be considered.

One of the most important variables effective on the PPI of agricultural products is the exchange rate. With the change in the exchange rate, the relative prices of exports and imports have changed, and given that the major part of the imports in agricultural sector is the inputs required for the production of this sector, this will change the cost of agricultural products. The exchange rate directly affects the export and import of agricultural products and agricultural inputs and indirectly affects production, income, costs, profits and investment in the agricultural sector. Thus, the exchange rate affects the price index in this sector due to its effect on the supply and demand of products and inputs in the agricultural sector. Monetary policy is one of the factors that can affect the price of food and agricultural products. One of the main goals of monetary policy is to stabilize the general level of prices in the economy. In a situation where society is exposed to inflationary pressures and the CPI is rising, the application of a contractionary monetary policy can play an important role in inflation control.

In this study is used the nonlinear autoregressive distributed lags (NARDL) method for estimating of PPI agricultural products equation using Eveiws12 software. The data required for this study are related to the period 2009 (Chapter 4) to 2019 (Chapter 4), which is mainly collected from domestic library sources, including the Statistical Center of Iran, the Ministry of Agriculture-Jihad, the Central Bank of Iran and the Ministry of Economic Affairs and Finance. The data on the effective real exchange rate has been extracted from the IMF web site. Based on the theoretical foundations and fulfilled studies, the long-run relationship exists between the PPI of agricultural products and the explanatory variables such as real effective exchange rate, GDP, CPI and money supply. This equation is transformed into an unbound error correction model (UECM) using the functional form ARDL (p, q) and is estimated using the ordinary least squares (OLS) method. In this study, the Bounds test has used for investigating the existence of a long-term relationship (co-integration) between independent and dependent variables. Also the Wald test has used for investigating the symmetric or asymmetric effects of independent variables (exchange rate and money supply) on the dependent variable.

The results of the augmented Dickey-Fuller (ADF) test show that all variables are stationary in first difference. In other words, the variables are integrated from the first degree and in this research, the NARDL approach can be used. The results of Bounds test indicate that in both the linear symmetric model (ARDL) and the nonlinear asymmetric model (NARDL), the calculated F-statistic is greater than the critical values ​​of the upper bound. Thus, the long-run equilibrium relationship between the variables of both models is accepted with 99% confidence. The results of linear model (ARDL) indicate that the real effective exchange rate with a time lag, in the short term has a positive and significant effect on the PPI of agricultural products. The GDP variable only in the long run has a negative and significant effect on the PPI of agricultural products. In addition, the CPI in the short term with a time lag and in the long term has a positive and significant effect on the PPI of agricultural products. Also, in the linear model, money supply (monetary policy) has had a positive and significant effect on the PPI of agricultural products only in the long run. The results of the NARDL model show that in the short run, only the positive shock of real effective exchange rate has a positive and significant effect on the PPI of agricultural products. Accordingly, the GDP variable in the short run has a negative and significant effect on the PPI of agricultural products. In the short run, the CPI with a time lag has a positive and significant effect on the PPI of agricultural products. In addition, in the short run, the positive and negative shocks of money supply have not had a significant effect on the PPI of agricultural products. In the long run, the positive shock of real effective exchange rate has a positive and significant effect on the PPI of agricultural products. In addition, the negative shock of the real effective exchange rate in the long run has a negative and significant effect on the PPI of agricultural products. Also, positive shocks of money supply (monetary policy) in the long run have a positive and significant effect on the PPI of agricultural products. Negative shocks of money supply (monetary policy) in the long run have a positive and significant effect on the PPI of agricultural products. In the long run, GDP has had a negative and significant effect on the PPI of agricultural products.

The results indicate that the positive shock of the real effective exchange rate, both in the short run and in the long run, has a positive and significant effect on the PPI of agricultural products. Therefore, the depreciation of national currency always increases the PPI of agricultural products. Therefore, the most important step forward for the policymakers and planners to control the rising trend of prices is to prevent the depreciation of the national currency. Based on these results, positive and negative shocks of money supply (expansionary and contractionary monetary policies) have a positive and significant effect on the PPI of agricultural products only in the long run. Therefore, application of monetary policy in the agricultural sector is like a double-edged sword, and the use of these instruments by monetary authorities requires consideration of all aspects.