Agricultural Economics
A. Karbasi; S. Jalalian
Abstract
AbstractThe COVID-19 pandemic presented major global challenges, including a decline in per capita income growth across all income groups in 2020. The protein sector, particularly Animal-Source Foods (ASF) faced increased pressure on both supply and demand, resulting in price volatility. This study examines ...
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AbstractThe COVID-19 pandemic presented major global challenges, including a decline in per capita income growth across all income groups in 2020. The protein sector, particularly Animal-Source Foods (ASF) faced increased pressure on both supply and demand, resulting in price volatility. This study examines how income shocks affected food expenditure patterns and consumption behavior, with a focus on protein-rich ASF. Utilizing the QUAIDS model, budget data from Iranian households in rural and urban areas were analyzed for 2019 (pre-pandemic) and 2020 (during pandemic). The findings yield three key insights: (1) The average food expenditure share rose from 37% to 42%, with a sharper increase in rural areas; (2) Positive expenditure elasticities were observed across the six ASF groups including livestock meat, poultry, aquatic animal products, dairy, eggs, and fats, while own-price elasticities were relatively smaller; and (3) Welfare losses across ASF groups ranged from 2% to 24.2%, driven by policy imbalances, supply chain disruptions, and unequal utility distribution. Rural households experienced greater welfare losses in all ASF categories except fats. The study recommends targeted interventions: price-based support for urban areas and expanded social services for rural regions. To strengthen policy responses and enhance long-term food security, future research should assess the potential for substituting plant-based proteins as sustainable and cost-effective alternatives. These findings offer valuable guidance for policymakers aiming to improve nutritional resilience and economic stability in the post-pandemic era.
Agricultural Economics
R. Heydari; E. Javdan; M. Shabanzadeh Khoshrody
Abstract
IntroductionFood prices are an important indicator of societal well-being, and food inflation can deepen poverty in developing economies. Severe food price fluctuations not only affect food security in developing countries, but also affect economic growth and social stability. Any increase in food prices ...
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IntroductionFood prices are an important indicator of societal well-being, and food inflation can deepen poverty in developing economies. Severe food price fluctuations not only affect food security in developing countries, but also affect economic growth and social stability. Any increase in food prices can push many people back below the poverty line. Rising food prices hit low-income households hard, as the household food basket accounts for nearly half of household living expenses. Therefore, food price stability is of particular importance to policymakers trying to lift households above the poverty line. Food prices in Iran have always been on the rise, and even in recent years, the rate of food price growth has accelerated. Today, inflation, especially food inflation, remains a major problem in Iran, and policymakers are always trying to reduce food inflation. In this regard, and with the aim of controlling food prices, different policies have been implemented in Iran, and the effectiveness of these policies has been discussed. Therefore, understanding the behavior of food prices in response to macroeconomic factors is essential for policymakers to implement appropriate policies at the right time and place to keep domestic prices stable. In this regard, in the present study, the asymmetric effect of macroeconomic variables (money supply, GDP per capita, exchange rate, and trade openness) affecting food inflation in Iran is examined using the nonlinear ARDL approach. Materials and MethodsThe main objective of this study is to examine the asymmetric effect of domestic macroeconomic factors on food prices in Iran using a Non-linear Autoregressive Distributed Lag (NARDL) model. According to the theoretical literature, in this study, it is assumed that food prices are a function of macroeconomic variables, including money supply (MS), GDP per capita (GDPER), exchange rate (RATE), trade openness (OPEN), and global economic policy uncertainty index (EPU). Therefore, in accordance with Shin et al. (2014), the NARDL model used in this study is developed to examine the asymmetric effect of domestic macroeconomic factors (for example, money supply) as follows: In the above relationship, each of the macroeconomic factors (including the money supply, GDP per capita, exchange rate, and trade openness) is separated into the sum of positive and negative components. In fact, two additional variables are created in each equation, one indicating an increase in the variable of interest with a positive sign and the other indicating a decrease with a negative sign. The variable of global economic policy uncertainty index also plays the role of a control variable. Due to the availability of data, the time period in this study is 1991 to 2022. Results and DiscussionThe results of the linear and nonlinear bounds test in the ARDL model showed that there is a long-term relationship between macroeconomic variables including money supply, GDP per capita, exchange rate, trade openness, global economic policy uncertainty and food prices in Iran. In addition, the results of short-term and long-term symmetry tests using the Wald test showed that the effect of the exchange rate variable on food inflation in Iran is asymmetric in the long and short run, while the effect of the money supply and GDP per capita variables is asymmetric only in the long run; the effect of the trade openness variable is also symmetric in the short and long run and has a linear behavior. The results of the ARDL linear model estimation showed that in the short and long run, the effect of the growth of the variables of money supply, GDP per capita, exchange rate and global economic policy uncertainty on food inflation in Iran is positive and significant, while the effect of trade openness is negative and significant. The results of the NARDL model estimation also showed that the response of food inflation to increases and decreases in money supply and GDP growth is positive and significant, and their increase on food inflation is greater than the effect of their decrease. The response of food inflation in the long and short term to increases in the exchange rate is positive and significant, while the effect of decreasing the exchange rate in the long and short term is negative, but not statistically significant, and the effect of increasing the exchange rate on food inflation in the long term is greater than its effect in the short term. The effect of trade openness on food inflation is symmetric, with an increase in trade openness leading to a reduction in food inflation in both the short and long term. ConclusionLinking the prices of agricultural products to market conditions and liberalizing the market for these products is an appropriate method for coordinating the effects of macro policies and specific agricultural policies that should be considered by policymakers. Given the importance of the agricultural sector, the government's economic policies in relation to food prices will be of high importance and sensitivity. Considering the results of implementing contractionary monetary policies in coordination with other Central Bank policies, increasing investment and efforts to increase productivity in the agricultural sector, appropriate foreign exchange policies are recommended to prevent unreasonable increases in the exchange rate, and reducing tariffs and trade restrictions to increase trade openness.
Agricultural Economics
W. Qelich
Abstract
IntroductionGlobal environmental changes have become a significant challenge for humanity, highlighting the need for robust support for environmental projects across all dimensions, including financial and economic. Integrating ethics and human and social values with environmental concerns in economic ...
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IntroductionGlobal environmental changes have become a significant challenge for humanity, highlighting the need for robust support for environmental projects across all dimensions, including financial and economic. Integrating ethics and human and social values with environmental concerns in economic activities creates a new approach for sectors such as banking, manufacturing, industry, and insurance, reshaping their operations in response to these challenges. It is necessary to put aside the purely market-oriented approaches focused on the rapid development of financial markets at any cost, so that other policies with greater health can replace them. Meanwhile, the concept called "green banking" is one of the most important examples of this support. This kind of banking, as an important part of ethical banking, plays a special role in protecting the environment. With a comprehensive explanation of green banking and by using theoretical studies and international experiences and obtaining opinions from relevant experts and experts, this research identified the factors affecting the trend of the country's banking network towards green banking by using the Delphi method, questionnaire analysis and Friedman's test. Materials and MethodsThe current research is completely practical in terms of its purpose and qualitative and descriptive-analytical in terms of implementation method. First, by using the Delphi method, the factors affecting the tendency of the banking to implement green banking are identified, and then the relevant data is collected using a questionnaire. In the following, the known factors are ranked and prioritized with Friedman's test. The statistical population of this research was all managers and banking experts in Tehran. In the Delphi method, a standard statistical sample typically ranges from 10 to 30 questionnaires, with 28 initially considered for this research. After follow-up, 23 questionnaires were completed and included in the analysis. Additionally, 142 questionnaires were prepared and collected for Friedman's test implementation. At this stage, a Likert scale was used for the research questions, scored by managers, branch heads, and banking experts. A combined method has been used in the collection of research statistical data. At first, the concepts of green banking and ethical banking have been explained by using the library method and conducting free theoretical and field studies. In the following, with the Delphi technique and obtaining the opinions of relevant experts and experts, the most important factors affecting the tendency of the banking network to implement green banking have been calculated. In the following, the remaining important factors have been added to the set of factors with the method of intellectual generation. Results and DiscussionBased on the results of the research, four main economic, structural, managerial and social criteria were identified in order to influence this tendency. In the sub-criteria section, the high inflation rate, the relative cheapness of energy prices and the presence of profitable parallel markets along with green deposits are mentioned as the most important reasons for the low tendency towards green banking. Also, the laws and regulations and the legal system, the recruitment system, the promotion and encouragement of bank managers and employees, the central bank's supervisory system, the senior managers' attitudes towards environmental issues, corporate governance, the bank's internal supervision, the attention to green banking in the selection and decision Customers, society's attitude towards environmental issues and the culture of demand among the most important sub-criteria affecting the trend of the Iranian banking towards green banking have been evaluated and introduced. ConclusionThis research tried to identify and analyze the factors affecting the tendency of Iranian banking network towards green banking with a more comprehensive explanation of green banking and by using theoretical studies and international experiences and obtaining opinions from relevant experts and experts. Based on the research results, four main structural, economic, managerial and social factors influencing this trend were identified. Surveys showed that in the first place, economic factors were more effective than other factors in the trend of the banking towards green banking. Among the study factors categories, structural, managerial and social factors have the most influence on the trend of the country's banking network towards green banking. It is suggested that for the greater desire and tendency of the banking to implement and realize green banking, it is necessary to improve the economic components with the aim of more stabilization, inflation control, strengthening of supervisory dimensions and balance sheet reform of the banking network. Also, reforming the legal system in the supervision and support of green bankers, reforming the incentive and recruitment system, strengthening the attitude of senior bank managers and the general public to the necessity of protecting the environment, as well as reviewing the frameworks and processes of corporate governance in banks with a green perspective to encourage Iranian banking, is necessary towards green banking. In the meantime, undoubtedly the role of the central bank as the supervisory body and upstream regulatory body in reforming the general structures of the banking system and improving the management situation of the public sector of the banking network can be useful and effective in increasing the tendency of banks to establish green banking and comply with its criteria.
Agricultural Economics
S. Nikan; Gh. Dashti; J. Hosseinzad; M. Ghahremanzadeh
Abstract
Rice is a crucial agricultural product, and enhancing its productivity is essential for increasing production. This study aims to analyze the total factor productivity growth of rice production in Iran from 2000 to 2020. Using parametric (stochastic frontier analysis) approaches, the research evaluated ...
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Rice is a crucial agricultural product, and enhancing its productivity is essential for increasing production. This study aims to analyze the total factor productivity growth of rice production in Iran from 2000 to 2020. Using parametric (stochastic frontier analysis) approaches, the research evaluated the rice productivity growth and its components, including scale and technological changes. Based on the estimated Translog Cost Function, the annual total factor productivity growth was 2.1%, with positive technological change as the primary driver of these improvements. To further enhance productivity, the study recommends utilizing improved seeds, modern machinery, fertilizers, and nutritional solutions during rice cultivation. Additionally, the research suggests the application of parametric approaches in future studies to assess the impact of technological changes on crop yields.
Agricultural Economics
M. Majidian; A. Dourandish
Abstract
Exporting agricultural products is considered as one of the strategies for developing non-oil exports and achieving sustainable economic growth in developing countries. Saffron, as an export commodity, holds particular significance in Iran's non-oil exports. Given Iran's position among the top four saffron-exporting ...
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Exporting agricultural products is considered as one of the strategies for developing non-oil exports and achieving sustainable economic growth in developing countries. Saffron, as an export commodity, holds particular significance in Iran's non-oil exports. Given Iran's position among the top four saffron-exporting countries globally, this study aims to prioritize Iran's saffron target markets based on market competition indices and calculate its relative advantage and export stability index in the world market and Iran's export target countries. Comparison of the global market structure of the product during 2003 to 2022 revealed that despite the significant shares of Iran, Spain, England, and Nigeria in most years, the market structure has been characterized by a multi-sided monopoly, open and closed, and in some years dominated by oligopoly, indicating an increase in the number of competitors and the competitiveness of the export market for this product. Iran, with an average share of 13.6% in the saffron export market and producing over 80% of saffron, does not have a direct share in global exports, and most of Iran's saffron is exported to countries such as the UAE, Spain, China, and Oman, and then re-exported to other countries, for which strategies such as market expansion and branding need to be prioritized. The results showed that in 2022, four countries, Nigeria, Sri Lanka, Iran, and Spain, accounted for 93% of the total world exports, and Iran ranked second in terms of export volume in the saffron export market during the study period. Also, Iran had an export stability index of less than one (0.96) but the trend of this index indicates a decrease in Iran's stability. The results showed that the majority of Iran's saffron exports are concentrated in only four countries, with the composition of these countries varying over time. To enhance market stability and growth, it is crucial to expand the target export markets. Prioritization should be given to China, UAE, Spain, India, USA, Germany, France, Italy, Sweden, and Kuwait, with average priority ranks of 4.15, 6.85, 7.7, 7.95, 8.9, 12.3, 14.35, 15.25, 15.5, and 16.45 respectively. Furthermore, the results indicated that the export market for saffron is oligopolistic. Therefore, it is essential for all exporting countries to collaborate in determining the price and market share for each country. This collaborative approach can help in stabilizing the market, ensuring fair pricing, and promoting sustainable growth in the saffron industry.
Agricultural Economics
K. Khaledi
Abstract
IntroductionTheoretically in relation to economic growth and methods of calculating value added, the four factors of labor, capital, labor productivity, and capital productivity are considered, and the amount of value added will be the final product of the state and direct performance of these four factors. ...
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IntroductionTheoretically in relation to economic growth and methods of calculating value added, the four factors of labor, capital, labor productivity, and capital productivity are considered, and the amount of value added will be the final product of the state and direct performance of these four factors. Since investment is an available option and has faster execution capability than the change in the quality of agricultural labor and the driver of changes in the productivity of other production factors, it is inevitable to focus on it by statesmen and macro and sector planners to realize the target economic growth in the agricultural sector. With this description, the macroeconomic planners of the agricultural sector have not determined the required amounts of investment, labor and productivity of labor and capital in the agricultural sector to realize the economic growth target in the 7th development plan. The role of investment as the driver of this (realization of the economic growth goal of the 7th development plan years) is not hidden from anyone, and determining the amount of investment required in this process will be very important for the policymaker. The main question of this study is, what is the amount of annual investment needed to realize the economic growth of Iran's agricultural goal in the 7th development plan? For this reason, the present study aims to estimate the amount of investment needed to realize the economic growth of the country's agricultural target (assumed) in the seventh development plan (2024-2028). Materials and MethodsThe current research is analytical-descriptive and with a computational approach, it deals with the estimation of the investment needed to realize the economic growth of the agricultural sector of Iran in the 7th Development Plan (2024-28). The time period considered in this study is 2011-2028. The estimation of the required investment of the agricultural sector in order to realize the economic growth of this sector in the 7th development plan has been done parametrically (algebraically) and by using the capital elasticity in the studies, the increasing ratio of capital to production (ICOR) and the average productivity of the net capital balance. Considering that the target economic growth for economic sectors including the agricultural sector in the 7th Development Plan has not been specified, therefore, in the form of different scenarios, three different economic growths (3.5 percent, 5.5 percent, and 8 percent) as The target (assumed) economic growth for the agricultural sector is considered in the years of the 7th development plan. Results and DiscussionClimate changes and destruction of basic production resources are the most important challenges facing Iran's agriculture. In the 7th Development plan bill, economic growth of 8% is defined for the entire country's economy. In order to avoid over-reliance on basic resources in the agricultural production process and increase its resilience, a sustainable leap in targeted agricultural investment will be the most important choice of the government in the mid-term (7th development plan) and long-term. The aim of this study is to estimate the annual investment required in the agricultural sector in the 7th development plan, and in this regard, three approaches have been used to estimate the amount of annual investment required in the agricultural sector of Iran to achieve the target (assumed) economic growth. Examining the average of different approaches to estimate the annual investment for the target (assumed) value added growth of agriculture showed that according to the assumptions of the study and based on the prices of the base year 2016 (2016=100) to realize the growth of the value added of 3.5% necessary with a growth rate of 4.5%, an average of 183 thousand billion rials will be invested in Iran's agricultural sector annually. These figures will be 6.1% and about 234 thousand billion rials respectively to achieve 5.5% value added growth and 8.2% respectively and about 304 thousand billion rials to achieve 8% value added growth. There is no doubt that in addition to making the necessary investment, the realization of each of the target (assumed) growth of value added in the agricultural sector in the years of the 7th plan, on the one hand, depends on the existence of suitable and stable climatic conditions (as the main prerequisite for the production of agricultural products) and on the other hand, it is not imposing new shocks or crises on the agricultural economy of our country. ConclusionThe destruction of basic resources and climate changes in Iran's agricultural field are taking place in such a way that it has made it difficult to produce agricultural products in a large area of Iran in the field (the need to develop greenhouse crops) and on the other hand, the development of capital in the process of agricultural production (as a supplement or substitute for other production inputs) in order to increase productivity and preserve the limited and deteriorating production resources has made agriculture more necessary than in the past. Past experiences show that changing the financing approach for investing in Iran's agricultural sector is inevitable. Therefore, it is necessary that in the seventh development plan while separating investment facilities and agricultural working capital facilities during the 7th development plan, improving the environment for agricultural investment and the mechanism for transferring savings to this sector, optimal allocating domestic financial resources (National Development Fund, banking system, support fund for The development of investment, micro-agricultural funds, etc.) and foreign financial resources (foreign direct investment) should be planned in such a way that the investment made in the agricultural sector is coordinated and proportionate with the economic growth of the program.
Agricultural Economics
S.M. Mojaverian; F. Eshghi; S. Ahangari
Abstract
In addition to imposing a negative impact on public health, Covid-19 has made the world face a huge financial-economic crisis. The worldwide spread of the coronavirus has also affected the volume of transactions and the value of stocks. Since the food market is more affected under crisis conditions, ...
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In addition to imposing a negative impact on public health, Covid-19 has made the world face a huge financial-economic crisis. The worldwide spread of the coronavirus has also affected the volume of transactions and the value of stocks. Since the food market is more affected under crisis conditions, this relationship has been investigated in the stock exchange in the present study. In order to investigate the effect of Covid-19 patients on the stock index value of food industry companies as well as the relationship between risk and stock index value, the official daily data of the Ministry of Health and Medical Education and the Financial Information Processing Center of Iran were collected from March 3, 2021 when the first report was announced, to June 2, 2021. Mean Conditional heteroscedasticityvariance regression models were used in the current study. The statistical model specification tests showed that, first, the assumption of heteroscedasticitywas rejected and the needto useheteroscedasticitymodels was proved. Secondly, the asymmetry assumption was accepted. Model estimation results showed a relationship between the numbers of Covid-19 patients with the stock value of the food industry that was an increase in the number of infected people causes a decrease in the stock value of the food industry. Therefore, like other economic sectors, the capital market was affected by the Covid-19 crisis, and increasing exchange rate as a competing market had a negative effect on the stock price index. Also, considering the relationship between risk and stock value of food industries, as expected, there was an inverse and significant relationship between risk and stock value of food industry companies. In other words, an increase in risk leads to a decrease in the stock price of food industries.
Agricultural Economics
A. Kazem Pour; H. Rafiee; H. Noroozi; S.A. Zarer; L. Yousefzadeh; M. Kaboudtabar
Abstract
Introduction In the modern world, there is interdependence between the economies of different countries and it is difficult to find a country that has a closed economy. In other words, all the economies of the world are interconnected, but the degree of openness of the economy varies from country ...
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Introduction In the modern world, there is interdependence between the economies of different countries and it is difficult to find a country that has a closed economy. In other words, all the economies of the world are interconnected, but the degree of openness of the economy varies from country to country. One of the ways to reach global markets in transition countries is to develop the export of non-oil products, especially agricultural products, which cannot be achieved without considering the market structure of exportable commodities. Due to the high share of the country in the production of this product versus its small share in the export of this product and on the other hand the lack of comprehensive research on determining appropriate target markets and active presence in it, the present study seeks to examine the comparative advantage , The structure of the export market and finally the prioritization of the target countries of Iranian tomato export using numerical taxonomy (by prioritizing the target countries of Iran based on a set of indicators) to provide scientific solutions to producers of this product to identify and select the appropriate target market.Materials and Methods Considering the high potential of the country in the field of tomato production and export, the present study was conducted with the aim of examining the comparative advantage, determining the structure of the export market and prioritizing the export target markets of this product in Iran. The study period of this research is 2001-2018. For this purpose, the present study has examined the business model and structure of the export market of tomatoes in Iran and the world using the revealed comparative advantage, symmetric revealed comparative advantage, concentration ratios and Herfindahl-Hirschman index. After introducing the indicators of comparative advantage, the market structure index will be examined. Market structure reflects the organizational characteristics of the market, including the concentration of sellers, buyers' concentration, entry conditions and the degree of homogeneity of goods, which can be identified by identifying the nature of pricing, market competition and market type between competition and complete monopoly. Then, in order to prioritize the target markets of Iranian tomatoes, the method of numerical taxonomy analysis was used, which can be used to rank the regions in terms of comparative advantages and potentials and capacities. In this method, first each set is transformed into a homogeneous set based on the desired indicators and then prioritization will be done based on the expressed indicators.Results and Discussion The study of tomato export trends in recent years shows that there is a growth in the export value of this product, but in contrast to the export advantage of Iranian tomatoes during the period under review has been accompanied by many fluctuations and this indicates a competitive risk for tomato exporters in the country. Therefore, adopting policies for permanent monitoring and policy-making to improve the level of competitiveness of Iranian exporters, such as raising the quality of packaging, advertising to introduce the product in new and developed markets, as well as setting preferential tariffs with other countries seems necessary. The study of the structure of the Iranian tomato market showed that during the period under review, the structure of the Iranian tomato export market was not diverse and focused on a few specific countries, which caused instability and a decrease in foreign currency income from tomato exports. The bargaining power of Iran in the world market of this product has decreased, which has ultimately been to the detriment of Iran and the benefit of importing countries. Therefore, it is recommended in the field of trade of this product by identifying new and emerging export target markets and shipping commodities to these countries, as well as increasing the number of export target markets and bringing Iran's export market closer to a competitive state, to prevent Iran's tomato exports to concentrate on a few limited and traditional markets (dominant firm).Conclusion In this study, using the method of numerical taxonomy analysis as an efficient method, we tried to identify Iran's export target markets during the period 2001-2009. Finally, according to the ten indicators of market attractiveness, potential target markets for future exports of Iranian tomatoes were selected. The results of prioritizing the target markets of Iranian tomatoes showed that out of 25 countries importing Iranian tomatoes, 23 countries were among the target markets for exporting Iranian tomatoes. Among the major actual markets of Iranian tomatoes, which account for the largest imports of this product from Iran, only 4 countries, Azerbaijan, Afghanistan, UAE and Armenia are among the 10 countries with high priority, and the rest of the importers of tomatoes from Iran is considered as a target market with low priority. Therefore, in the export of tomatoes, a policy should be adopted that shifts the main focus to high-priority countries to penetrate them with full awareness of all the conditions of the target markets, especially the tastes of customers.
Agricultural Economics
N. Mohammadrezazade Bazaz; M. Ghorbani; A. Dourandish
Abstract
Due to the importantance of sugar in daily consumption of Iranian households, governments annually store sugar as a strategic reserve. Therefore, managing and timing adjustment for the inventory of this product is essential in its ability to compete in markets, modifying the temporal and spatial distribution ...
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Due to the importantance of sugar in daily consumption of Iranian households, governments annually store sugar as a strategic reserve. Therefore, managing and timing adjustment for the inventory of this product is essential in its ability to compete in markets, modifying the temporal and spatial distribution of products and inputs in economic subdivisions. In recent years, at national scale there was extra sugar in warehouses and a few cases of shortages in stock were exception. Higher sugar production along with lower sale, will increase the costs, so the aim of this study was to investigate the factors affecting sugar surplus and its export in Iran data time searies 1991-2017. In this study our results showed that sugar beet and sugar price as product price did not play a decisive role in stock surplus. Therefore, the stock surplus can neither be the result of price policies nor it be resolved through price policies. It seems that the government should adopt other policies, such as adjusting the timing of import decisions, resolving conflicts between government objectives, and providing strategic reserves from domestic products and gradual elimination of imports, support factories for improving and upgrading equipment, and help sugar beet producers to achieve cheaper product rather than using price policies related to sugar and sugar beet prices.
S. Moradi; O. Javanbakht; H. Khalilvandi Behroozyar
Abstract
Introduction: 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 ...
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Introduction: 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. Materials and Methods: 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. Results and Discussion: 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. Conclusion: 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.
H. Salami; A. Salim
Abstract
Introduction: Risk is considered as a negative factor in producing agricultural products. Yet, the presence of risk is not restraining producers from production as long as the generated revenue is proportional to the perceived risk and thereby, the cost of the risk is compensated. The purpose of this ...
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Introduction: Risk is considered as a negative factor in producing agricultural products. Yet, the presence of risk is not restraining producers from production as long as the generated revenue is proportional to the perceived risk and thereby, the cost of the risk is compensated. The purpose of this study is to measure systematic risk of wheat production in Iran's provinces, and evaluate how the risk is offset in these regions.Materials and Methods: According to Markowitz, there is a tradeoff between risk and returns in considering alternative investment by rational investors. That is, investors expect higher returns for accepting higher risk in considering any investment. Capital Asset Pricing Model (CAPM) is an equilibrium model based on this theory which measures systematic risk of an investment (activity) and shows how an asset is priced according to its perceived risk. Thus, this model can be used to examine the systematic risk of producing wheat in different regions and the relationship between the risk of producing this crop and the expected price to generate appropriate returns to compensate the undertaken risk by producers. According to Sharp, by regressing the returns of an investment on the returns of market portfolio, the systematic risk factor for such investment is obtained. The risk factor which takes different values from zero to greater than one is a measure of systematic risk of an activity relative to the risk of overall portfolio. This risk factor is used to compute the returns required to compensate the risk associated to the activity.Results and Discussion: Results reveal that Yazd province with 0.45 beta coefficient is the least risky province and Mazandaran province with 1.26 beta coefficient is the riskiest province for wheat production in Iran. In fact, based on the results, 20 percent of the wheat producing provinces are classified as high risk in production of this crop. Ardebil, Zanjan and Alborz provinces with systematic risk coefficient of 0.96, West Azerbaijan and Isfahan with systematic risk coefficient of 0.90 are grouped as risky ones. Gilan, Semnan and Hormozgan with systematic risk factor of 0.73 and Bushehr and North Khorasan provinces with systematic risk factor of 0.72 that have similar risk factor are classified as other risky zones. As the results indicate, with 15 percent risk-free rate on investment in the country, wheat producers expect a minimum return of 18 percent in producing wheat in Iran. On the other hand, if the risk-free rate of return on investment rises to 20 percent, wheat producers expect a minimal rate of 19.5 percent. Based on these calculations, prices of this product, and consequently the generated revenues, are in such a way that the returns offset the risk of wheat production in 14 provinces. From this point of view, wheat production in Kurdistan province has the best condition while the production of wheat in the southern province of Kerman shows the worst situation. In addition, results revealed that uncompensated risk in most of the provinces is the result of low yield per hectare and consequently, high average cost in these regions. Thus, focusing on improving productivity is suggested for the specified provinces.Conclusion: According to the results, uncompensated risk in most of the provinces is the result of low level of yield per hectare and consequently, high level of average cost in these regions. Therefore, it is expected that in the long run, crops with higher yield will be replaced for the wheat and this crop will gradually be removed from the cultivation plan in such provinces. Since wheat is a strategic crop in Iran and to guarantee its production, improving productivity of this product is recommended for the specified provinces.
H. Ailbakhshi; A. Dourandish; M. Sabouhi
Abstract
Introduction: Understanding the temporal and spatial fluctuations of climatic parameters (such as temperature, precipitation, relative humidity, etc.) and its impact on agricultural sector is essential for managing agricultural resources and adopting appropriate strategies. Precipitation directly affects ...
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Introduction: Understanding the temporal and spatial fluctuations of climatic parameters (such as temperature, precipitation, relative humidity, etc.) and its impact on agricultural sector is essential for managing agricultural resources and adopting appropriate strategies. Precipitation directly affects the production of dry crops by supplying the required moisture for the plant, and indirectly affects the production of aquatic crops through supplying surface and underground water resources. Climate change has an effect on temperature and precipitation distribution and consequently affects the plants water requirement and agricultural water consumption. Overall, climate change is influenced by both temperature and precipitation. Due to the changing rainfall pattern and average temperature of the atmosphere, this phenomenon can damage the production of agricultural products that maintain the major food sources of the country. Given the important role of agriculture in the country's economy and the existence of the ongoing water crisis and drought in the country, climate change can have major impacts on their aggravation. The purpose of the present study is to investigate the effects of climate change and water scarcity on agricultural production, price and income in Iran.Materials and Methods: The multi-market model, sometimes referred to as the "finite general equilibrium" or "multi-market partial equilibrium model", has reduced the complexities of computable general equilibrium (CGE) models. The AMM template was used for this purpose. To simulate the effects of climate change, crop yields were calculated using yield response coefficients. Then, the demand function of different products was calculated using estimated elasticities and finally climate change has been simulated for 2025.Results and Discussion: The results showed that climate change would increase, yield of rainfed wheat, blue barley, dry barley and maize grain in semi-arid climate and subtropical climate, in addition dry barley and barley products in warm semi-arid climate and subtropical climate, and finally rainfed barley and corn products Grain in temperate semi-arid climates and subtropicals climate by 2025 relative to current levels. Climate change also would decrease yields of dry wheat and barley in temperate semi-arid climates and subtropicals, and also wheat in warm and semi-arid climates and subtropicals for 2025 compared to the present value. The results also showed that climate change would expand the water available for the blue wheat crop in the semi-arid climate and sub-climates, besides the blue barley crop in the semi-arid, semi-arid, and temperate semi-arid climates for 2025 compared to the present value. Climate change also might reduce the amount of water available for the blue wheat crop in the climate and sub-arid and semi-arid sub-climates, therefor the corn yield in the cold and semi-arid sub-climates and sub-climates for 2025 compared to the present value. The results also revealed that climate change would diminish cultivation of maize crop in semi-arid climate and temperate climates in addition irrigated and rainfed wheat crop in warm and semi-arid sub-climate and also rainfed wheat crop in semi-arid climate by 2025 relative to the present situation. Also the area under cultivation of blue barley and dry barley crops in warm and semi-arid climates, cold and semi-arid climates, and blue wheat crop in semi-arid climates and rainfed wheat crop in temperate and semi-arid climates would decrease by 2025.Conclusion: The results also demonstrated that with the climate change, the amount of maize crop production in cold and semi-arid climates and sub-climates, and the production of blue and dry wheat crops in warm and semi-arid climates, cold semi-arid, temperate and dry semi-arid climates for 20 years would decrease relative to current value. Also, the production of irrigated and rainfed barley in warm and semi-arid climates, sub-climates and temperate semi-arid climates for 2025 would increase compared to the present situation. Thus the first hypothesis of the study: "Climate change and water scarcity reduces agricultural production" is not approved in Iran. The results also explained that with the climate change the prices of wheat, barley and maize crops in the semi-arid and temperate climates for the year 2025 would also rise, so the second hypothesis of the study "Climate change and scarcity of water resources will increase the prices of agricultural products in Iran” is confirmed. The results also show that with climate change, farmers 'incomes in cold and semi-arid climates, temperate and warm semi-arid climates would increase by 2025 relative to their present value, so the third research hypothesis that "climate change and water scarcity reduces farmers' income" In Iran, " is not confirmed. The results also indicated that wheat, barley and maize exports remained negative by the creation of net climate change for 2025 and that the country's climate change created an importer of these products.
H. Mohammadi; M. Aminizadeh; H. Aghasafari
Abstract
Introduction: International trade leads to financial and economic development by improving domestic productivity. Given the importance of trade, various trade topics such as intra-industry trade, trade survival, trade balance and trade liberalization have been examined in the research literature. One ...
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Introduction: International trade leads to financial and economic development by improving domestic productivity. Given the importance of trade, various trade topics such as intra-industry trade, trade survival, trade balance and trade liberalization have been examined in the research literature. One of the most important trade concepts received less attention is export efficiency. The export efficiency is defined as the ratio of actual exports to the maximum export potential in the destination markets. Pistachio is one of the important products in Iran’s agricultural exports. The share of Iran’s pistachio exports has dramatically decreased from 58 percent in 2000 to 24 percent in 2016. Despite the importance of investigating the exports efficiency in planning and policymaking, there is no empirical study about the measuring pistachio exports efficiency. So, this paper aims to assess the main determinants of pistachio exports of Iran and evaluate the export efficiency in the main destination countriesMethodology and Data: In this study, the stochastic frontier gravity model is employed for investigating the Iran’s pistachio export efficiency in its importing countries. The gravity model is a well-known tool by international trade economists which explains trade flows between two trading countries based on economic size and geographical distance. The analysis is based on panel data covering 42 trading countries during 2001-2016. The selected countries are Australia, Bahrain, Belgium, Bulgaria, Canada, China, Cyprus, Czech Republic, Egypt, France, Germany, Greece, Hong Kong, Hungary, India, Iraq, Italy, Japan, Jordan, Kazakhstan, Kuwait, Lebanon, Luxembourg, Malaysia, Mexico, Netherlands, Pakistan, Poland, Qatar, Romania, Russia, Saudi Arabia, Slovakia, Spain, Sweden, Switzerland, Syria, Tunisia, Turkey, Turkmenistan, United Arab Emirates and United Kingdom.Results: The results of Fisher and IPS (Im, Pesaran and Shin) panel unit root tests clearly show that all the variables are stationary. The results of Chaw and Hausman tests indicated that fixed effect model is the best model. The coefficient of Iran’s GDP carries a positive sign on its coefficient and is consistent to expectations. The coefficient of importers’ GDP carries the expected positive sign on its coefficient and is highly statistically significant at 1 percent level, indicating that higher GDP has translated into higher demand and so higher imports. The coefficient of the variable geographical distance is as expected negative and statistically significant at 10 percent level. This means that distance play an impeding role in pistachio exports from Iran to its importers. The coefficient of the variable per capita GDP difference as a proxy of economic difference is positive and significantly statistically at 10 percent level. This shows that pistachio export from Iran to its importing countries with different economic structure is higher compared to importing countries with similar economic structure.According to the results, the coefficient of the dummy variable for regional trade agreement is positive and statistically significant at 5 percent level. This indicates that membership of Iran and its partner in same agreements has significantly affected Iran’s pistachio exports to its importing countries. The coefficient of the dummy variable for common border is positive and highly statistically significant at 1 percent level indicating that common border between Iran and its partner led to same food-style and lower transaction cost which have increasing effect on Iran’s pistachio exports. The coefficient of dummy variable for high income is positive and significant at 10 percent level, suggesting that Iran’s pistachio exports to high income countries is higher compared to other countries. The coefficient of dummy variable for global economic crisis is negative and highly statistically significant at 1 percent level. This means that economic crisis led to decrease demand for unnecessary food. The coefficient of dummy variable for economic sanctions is negative and highly statistically significant at 1 percent level, showing that economic sanction led to decreasing supply from Iran to its importing countries particularly EU countries.Based on the efficiency results, none of the country showed100% technical efficiency. Also, the average of Iran’s export efficiency has decreased in all destination markets over the period 2001-2016. In the panels of Asia and Europe as important destination regions, Iran’s export efficiency has increased and decreased respectively.Discussion: According to the empirical findings, there is a lot of potential in order to increase Iranian pistachio exports to destination countries. Therefore, due to the positive and significant effect of common border, it is suggested that trading countries with same border (land or sea border) should be a top priority for pistachio exports. Also, based on the positive effect of regional trade agreement, it is recommended that exporters be granted through access to larger and safer destination markets by joining larger trade agreements.
A. Nikoukar; I. Tajnia
Abstract
Introduction: The concept of low-carbon economy postulates the consumption of less natural resources and causing less environmental pollution, while gaining more economic efficiency. According to the concept of low-carbon economy, low carbon agriculture is a specific model of agricultural production ...
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Introduction: The concept of low-carbon economy postulates the consumption of less natural resources and causing less environmental pollution, while gaining more economic efficiency. According to the concept of low-carbon economy, low carbon agriculture is a specific model of agricultural production operations with both the lowest greenhouse gas emissions and maximum economic benefits having which has three characteristics including lower energy consumption, lower greenhouse gas emissions and lower pollution. Therefore, this research studies the approaches to low-carbon agriculture in IranMaterials and Methods: In this research, energy consumption and consequently economic growth, which is expected to play a role in carbon emissions, other macroeconomic variables such as trade openness and financial development have been used. The estimated model of the research is linear-logarithmic based on Shahzad et al (2017). For this purpose, the ARDL and ECM patterns and the time series data of 1989-2014 have been used in current study. The data related to carbon dioxide emissions and energy consumption have been collected from the energy balance sheet of the Ministry of Energy, The data related to financial development have been collected from World Bank, Value Added of agriculture section Growth Ratio and Trade Openness data have been gathered from Central Bank of the Islamic Republic of Iran. Eviews9 software has been used to analyze the results.Results and Discussion: Statistically significant impact of energy consumption logarithm and energy consumption logarithm square on carbon dioxide emissions at the level of 1% in the long run has been revealed by the results. The positive amount of energy consumption and negative amount of the square of energy consumption indicates a U-shaped inverted relationship between energy consumption and carbon dioxide emissions. The energy consumption threshold in the agricultural sector is 46.98 million barrels of crude oil, while the actual maximum energy consumption is 50.26 million barrels of crude oil. So the agricultural sector's performance is now above the mentioned level, then it is expected to reduce carbon emissions by technological improvements while increasing energy consumption. The coefficient of financial development variable in the long run is -0.014169. The financial development efficiency index is considered as national development variable which means each one percent of increase in bank credits allocated to the private sector will reduce about 1.02 ton of carbon dioxide. The coefficient of trade openness variable is 0.010443 in long run. Whereas the trade openness index is considered as the ratio of the total value of exports and imports to gross domestic product, so every one percent increase in the volume of exchanges to gross domestic product leads to a 1.01 ton increase in carbon dioxide and pollution which confirms the hypothesis. The growth rate of value added of agriculture section in the long run does not have any effect on carbon dioxide emissions. In the short run, the coefficient of trade openness is 0.00581. In other words, one percent increase in the ratio of international trade to GDP will increase about one ton of carbon dioxide emissions. The growth rate of value added of agriculture section, financial development, and the first lag of financial development in short run have no effect on carbon dioxide emissions.Conclusion: The results indicated a long-term U-shaped inverted relationship between carbon emissions and energy consumption in this sector. The maximum energy consumption threshold was also equivalent to 46.98 billion barrels of crude oil. At present, performance of the sector is on downward, and carbon emissions are expected to gradually decrease by the technological improvement as energy consumption increases. Higher level of the energy consumption than the threshold level indicates that technology effect dominates the scale and composition effects. The results shows that the growth rate of value added of agriculture section in long and short run did not affect carbon emissions. Moreover, in the long run, financial development has negative effect on carbon emissions while in the short run financial development has no effect on carbon emissions. But the effect of trade openness index on carbon emissions in the long and short run is positive. According to the results of the study, increasing the volume of credits to the private sector will help reduce carbon emissions. It is also proposed to change the pattern of trade considering the environmental advantages and the use of green energy programs to reduce carbon emissions.
H. Salami; E. Taheri
Abstract
Introduction: Rapid growth in the world population would substantially exacerbate pressure on all resources particularly water resources and consequently would cause difficulties in global food security. In addition, degradation of water resources is one of the greatest environmental challenges facing ...
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Introduction: Rapid growth in the world population would substantially exacerbate pressure on all resources particularly water resources and consequently would cause difficulties in global food security. In addition, degradation of water resources is one of the greatest environmental challenges facing almost all countries around the world including Iran. In Iran, the situation is even worse as it is located in a dried and low precipitation region. Thus, before Iran reaches at an irrevocable point, it needs to revisit its development policies. In fact, what is considered as a strategic principle in the path of sustainable development is the balance between the development policies and the state of the existing country's natural resources base, specially the water resources. Thus, in order to manage optimal usage of water resources and to coordinate farm land utilization policies and water resource availability in different provinces, information on water security situation in terms of physical, social and economic factors are necessary. The present study seeks to specify the status of water security in provinces of Iran using water poverty index.Materials and Methods: Given that water security is a multidimensional concept and it is not possible to use one variable to represent its different dimensions, the indicator method is typically used to evaluate this concept. In the present study, the Poverty Index is utilized to measure water security in different provinces of Iran. This index consists of five main water related components including: Resources Accessibility, Capacity, Consumption, and Environment. These components in turns are determined by various variables such as the volume of groundwater resources and annual surface water per person, the variation of rainfall in a 10-year period, number of household having access to public water pipeline, percentage of population having access to urban wastewater collection and disposal services, percentage of population covered by the social security services, literacy rates in the population over the age of 6, rate of participation, GDP at constant prices, employment rate in non-agricultural activities, annual water usages, percentage of irrigated land, amount of fertilizer and pesticides distributed annually, and percentage of protected areas under the management of the Environmental Protection Agency. These variables are first standardized using minimum-maximum method Then, an index for each of the five components are computed. Next, an index of water poverty is calculated for each province by aggregating all five components. At the end, based on the index of water poverty all provinces are classified into Water Unsafe, Lower safe, Moderate safe, Upper safe, and Full Safe provinces.Results and Discussion: Results revealed that, five provinces, including Sistan va Baluchestan, Qom, Kerman, Hormozgan and Golestan were the most insecure provinces based on the calculated water poverty index. These regions are facing a severe water crisis. Two provinces, including Tehran and Gilan, had lower safe water security. Also, five provinces, consisting of East Azerbaijan, Zanjan, Semnan, Kermanshah and Lorestan faced upper safe situation, while five provinces, including Bushehr, Chahar Mahaal va Bakhtiari, Kohgiluyeh va Boyer-Ahmad, Kurdistan and Markazi had full Safe of water security. Other provinces were ranked in moderate safe status in Iran. The correlation between Water Poverty Index (WPI) and its components indicates that all components are positively and significantly correlated with the Water Poverty Index, except for the capacity item. The magnitudes of the calculated correlation coefficients in this study were 0.459, 0.628, 0.776 and 0.518, respectively for resources accessibility, capacity, consumption, and environment components. The consumption item has the strongest relationship with the Water Poverty Index. Consequently, in order to improve water security, it is recommended that policy makers give priority to this item. Suggestion: Given that the roots of existing water poverty in different provinces were not the same, it is suggested that water policy makers and planners take into consideration the province-specific factors for setting up the planes aiming to prevent more water insecurity in Iran. From this point of view, the WPI results can be used to prioritize the provinces and understand the roots of water insecurity in each of the provinces. Providing water security or water poverty map for Iran is essential for having a clear understanding of water security situation in different regions in Iran and is recommended. Finally, information provided by WPI can be used in efficient management of water resources in different provinces and at national level.
Y. Rostami; S.S. Hosseini; R. Moghaddasi
Abstract
Introduction: In recent years, price transmission analysis either spatially or vertically among separated markets has increasingly been drawn by methods that account not only for common non-stationary but also, for nonlinear dynamics in co-integration relationship of price series. If the price transmission ...
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Introduction: In recent years, price transmission analysis either spatially or vertically among separated markets has increasingly been drawn by methods that account not only for common non-stationary but also, for nonlinear dynamics in co-integration relationship of price series. If the price transmission is asymmetric among the specific stages of the supply chain, the price changes will not be affected quickly at the production level through the processing and/or retail level. A positive (negative) price asymmetry occurs, when a decrease (increase) is not immediately transmitted in prices at the farm level; whereas, an increase (decrease) would influence final consumer rapidly. Asymmetric price transmission is crucial because it influences welfare negatively. Prices allow producers and consumers to decide synchronously and also, leave the doors open for scarce resources to be allocated influentially. The transition from a planned economy to a market one mostly causes price liberalization come into play. However, price liberalization not only improves resource allocation but also, brings about higher price instability in comparison with an administrative system with fixed prices.
Materials and Methods: Many popular modeling techniques used to analyze vertical price transmission were initially investigated by using variations of a model which was first developed by Wolffram (1971) and later modified by Houck (1977), that known as a traditional approach in price transmission studies. The response of the retail price (RP) to a shock in the farm price (FP) was calculated by estimating the following equation:
Where:
and lnPr is the log of retail price , lnPf is the log of farm price, are the increases and decreases of the price at the farm respectively. M1 and M2 are legs duration and is coefficient of increase or decrease on retail price.
Markov-switching vector error correction model:
The Markov-switching vector error correction model (MSVECM) is a special case of the general Markov-switching vector autoregressive model which was initially proposed by Hamilton (1989) for analyzing the U.S. business cycle. The applicability of this model is, however, not restricted to this specific research question. Consequently, it can be viewed as a general framework for analyzing time series with different regimes whenever the corresponding state variable is not observed. According to the state of the system, MSVECM with shifts in some of the parameters can be expected to be more appropriate in this setting:
here, pt = (pft ,pmt)’ is the vector of market prices for farm (superscript f) and retail (superscript r), respectively, denotes the vector of intercept terms, α is the vector of adjustment coefficients, β is the co-integrating (long-run equilibrium) vector, ∆ indicates first differences, and D1, D2, … , Dk are matrices of short-run coefficients. The vector contains the residual errors of the farm and the retail equations.
Results and Discussion:-Houck`s model: The estimated parameters of the final Houck`s model are presented in Table 2
Table 2-Houck model results (dependent variable: retail price)
Price
transmission
Test
result
Valed
test
long run coefficient
Price change
Dec. Inc.
Short run coefficient
Price change
Dec. Inc.
Variable
Asymmetry
H0 riject
14.24
0.89 0.99
0.61 0.73
producer price
Source: Research findings
Markov-switching vector error correction model:
The number of regimes and lags were determined according Akaike information criterion. Therefore, a model with two regimes with three lags has finally been chosen and estimated. Adjustment pace, residual standard errors and the resulting margin in the long-run relation (which may be calculated from the estimated coefficient for the regime-specific constant and the corresponding adjustment rate coefficient estimation) allowed a more detailed interpretation of the single regimes to be put. Two regime equations are as follows:
Regime 1 Regime 2
LRMPt = -0.46 + 1.08LPMPt (4) LRMPt = -0.05 + 1.09LPMPt (5)
stdv (0.12) (0.01) stdv (0.04) (0.004)
Here regime 2, points to data that relates to 2003 until the end of 2006 and also, 2013 to 2015; whereas regime 1 refers to the first of 2007 till end of 2012. Thus the type of relationship between two series depends on policy actions that government adopts during the period. In other words, one should consider different relations prevailing in different periods and this is the novelty of current study in comparison with previous researches.
Conclusion: This paper analyzed vertical market integration for Iranian fluid milk market over the years 2003-2015. We exploit Houck and MSVECM models in order to analyze market integration deploying 153 monthly observations from March 2003 to December 2015. The results of this paper corroborate a view, claiming retailers can exercise significant market power, as used to be evidenced by asymmetric price responses in Iranian fluid milk market. Due to the existence of positive price asymmetry in farm-retail price transmission, the retail prices would be inclining more quickly to increases in farm price than to decreases implying serious welfare losses to the consumers. This result is also consistent with the empirical evidence of a significant market power in the milk market.
S.M. Ghaffari Esmaeili; A. Akbari; F. Kashiri Kolaei
Abstract
Introduction: Climate change is one of the most important issues that affect different sectors of the economy. Climate change affects precipitation and temperature and by disrupting optimal growth conditions will reduce crop yields and thus exert influence on food security and the spread of poverty in ...
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Introduction: Climate change is one of the most important issues that affect different sectors of the economy. Climate change affects precipitation and temperature and by disrupting optimal growth conditions will reduce crop yields and thus exert influence on food security and the spread of poverty in agricultural societies as a consequence. Production sectors, labor income and institutional income are affected by changing climate, and sectors that are more interactive with the agricultural. Specific features of the agricultural sector such as the dependence on climate variables have made this sector the focal point of climate change. Based on this, the present study examines the effect of climate change on economic growth of agriculture in Iran in the form of a dynamic computable general equilibrium model (DCGE).
Materials and Methods: In this research, DCGE has been used to investigate the effects of climate change (e.g. reduction of rainfall) on macroeconomic variables in Iran's agricultural sector. In order to implement the DCGE model, the social accounting matrix of 2011 has been used. The social accounting matrix represents the circular flow of funds between sectors, factors and institutions in a market economy. The social accounting matrix, which is a square matrix, is set up to equal the sum of rows and columns. The columns represent the receipts (revenue) and the rows represent the payments. Therefore, according to this definition, the total revenue of all accounts must be equal to the total expenditures of all accounts. In other words, the income of each economy is equal to the total cost of that economy. Since the social accounting matrix is a descriptive tool for illustrating the details of the structure of a country's economy, it will also be considered as a tool for general equilibrium analysis as it provides information on the relationship between production sectors and the external world as well as the relationship between income and consumption.
It should be noted that in the current study, the model was solved in the form of GAMS software. In order to estimate the results, it is necessary to go through two steps. At first, the model parameters are estimated to the value of the model decision variables then the solution would be equal to real values which are called calibration. Subsequently, by changing the variables related to climate change the model decision changes over the years are examined. In other words, by using the DCGE model, we studied the effects of climate change on important variables in the agricultural sector.
Results and Discussion: The results of this study about the effect of precipitation on the productivity of the agricultural sector indicate that one percent change in rainfall will reduce the productivity of agriculture by 0.79 percent. Based on the results of previous studies, by 2030 rainfall in Iran will be reduced by 9%, which means rainfall will decrease by an average of 0.3% per year. Thus, the productivity of agricultural sector will decreases by an average of 0.237% per year. Accordingly, the effect of changes in agricultural productivity (technological coefficient of Cobb-Douglas function), as a result of climate change, was measured on the macroeconomic variables of the agricultural sector including production, consumption, investment, exports and import. Results show that climate change decreases the production, consumption, investment and exports, and increases the imports by 2030.
Conclusion: The results of this study indicate that considering the amount of rainfall reduction in the 20-year horizon by 2030, the amount of production, consumption, investment and export of agricultural sector will decrease by 4.469, 5.025, 4.462 and 13.770 percent respectively, but imports in this sector will increase by 5.504 percent. Given the impacts of climate change on the macroeconomic variables in the agricultural sector, it is imperative that the government take appropriate measures to support this sector while confronting unfavorable climate. Considering role of capital in agriculture, results of this study indicate that due to the consequences of climate change in the assumed period the investment process of agricultural sector has a smaller share than other sectors. Therefore, in these circumstances, policies such as fixing the price of agricultural commodities, increasing the granting of loans by banks and other policies should be undertaken to encourage the private sector to invest in this sector.
Kh. Jahangiri; H. Heidari; S.A. Hoseini Ebrahimabad
Abstract
Introduction: Today, energy supply is one of the most important issues in development process of all countries in the world. There is a close relationship between economic growth and development and energy consumption. Agriculture plays a critical role in the national economy and food production and ...
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Introduction: Today, energy supply is one of the most important issues in development process of all countries in the world. There is a close relationship between economic growth and development and energy consumption. Agriculture plays a critical role in the national economy and food production and energy has always been essential for the production of food and agricultural products. In agriculture, various fuels are used as a source of energy, including gasoline, kerosene, natural gas and electricity. Over time, the electrical equipment used in the agricultural sector has increased, and as a result, the need to use electrical energy has also increased. Electricity is one of the main inputs in the agricultural sector, so that, more than 16 percent of electricity production in Iran, allocated to this sector for more than 20 percent of the provinces in Iran, electricity power consumption in the agricultural sector is more than that of in the industrial sector. Energy intensity is one of the key terms in the literature on energy efficiency. The energy intensity of agriculture is defined as the ratio between the final energy consumption of the sector and the value added of agricultural sector. Energy efficiency refers to the activity or product that can be produced with a given amount of energy. There is a widespread assumptions in energy statistics and econometrics that energy intensity and energy efficiency are equivalent measures of energy performance of economies.
Materials and Methods: Because of the importance of efficiency in production inputs, the main objective of this study is to evaluate the efficiency of electricity consumption in the agricultural sector of Iran. For this purpose, the state of high and low efficiency of electricity consumption in the agricultural sector was detected by using Markov regime switching model during the period 1342 to 1393. The Markov switching model proposed by Hamilton (1989) is one of the most popular nonlinear time series models in the econometrics literature. A Markov switching model is constructed by combining two or more dynamic models via a Markovian switching mechanism. A Markov regime switching Model is the generalization of the simple dummy variables approach that allows regimes or states to occur several periods over time. In each period t, the state is denoted by st. There can be m possible states: st = 1,... , m. the states in this models may be recessions and expansions, high and low volatility, depressive and non-depressive or high and low efficiency states, etc. The time of transition between states and the duration in a particular state are both random and the transitions follow a Markov process. In the nonlinear models, any of the parameters (such as beta estimates, sigma, and AR components) may be different for each state. The Markov switching model and its variants discussed in the preceding sections are only suitable for stationary data. Because the order of integration of a time series is of great importance for the analysis, therefore, several statistical tests have been developed for investigating it. In this paper, we use ADF and PP unit root test for investigation of integration order of variables such as energy efficiency, growth rate of per capita GDP and consumer price index.
Results and Discussion: First, the results clearly suggested that the unit root null hypothesis for the selected variables can be rejected. The estimation of Markov regime switching model showed that the duration of low efficiency regime in the agricultural sector is more stable than the high efficiency regime. The average duration of the low efficiency regime is 2.5 months and the average duration of the high efficiency regime is 1.7months. The results also showed that the general level of prices and per capita production has negative and positive effect on the efficiency of electricity consumption in the agricultural sector, respectively.
Conclusions: The trend of energy consumption and efficiency of electricity in agricultural sector and at the national level shows that the average energy consumption over the past 51 years has increased and at the same time electricity efficiency (both in agricultural sector and in total economy) has declined over the long term. The trend of energy efficiency indicators shows that agricultural producers are not efficient in the process of production. According to the results of the study, systematic planning for the optimal use of inputs is suggested to improve energy efficiency in agricultural sector. In order to increase the efficiency of energy usage, especially electricity usage in the agricultural sector, following ways recommended: restructuring of the production and use of newer and more efficient technologies; financial support and providing banking facilities to optimize consumption and energy supply projects.
E. Moradi; M. Afsharmanesh
Abstract
Introduction
One of the characteristics of agricultural products in Iran is continuous price fluctuations. There are many factors that can lead to fluctuations in prices in the agricultural sector. The important of these factors are the seasonal and cyclical changes in supply, the shift from global ...
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Introduction
One of the characteristics of agricultural products in Iran is continuous price fluctuations. There are many factors that can lead to fluctuations in prices in the agricultural sector. The important of these factors are the seasonal and cyclical changes in supply, the shift from global prices to the domestic market of agricultural products, the shifting of the volatility of inputs into products and the fluctuations caused by the general trend of prices The aim of this study is to evaluate the impact of price shock inputs that are used in the production of corn, on the price of the corn crop. Studies in Iran are further on the transfer of the farm to the retail price and the transmission of price shocks from the inputs market to product market has not been established. To examine this matter, VAR model with panel data was used.
Materials and Methods
For this purpose, we used data on the prices of inputs used in corn production, including land, fertilizer, labor, seed, and pesticides, as well as the price of corn since 1999 to 2012 year, for 16 provinces in Iran. That these provinces produce 93.5 percent of total corn Produced in the country. In order to analyze the data model is specified in the form of PVAR (Vector Auto Regression with Panel Data). Time-series vector auto regression (VAR) models originated in the macro econometric literature as an alternative to multivariate simultaneous equation models. All variables in a VAR system are typically treated as endogenous, although identifying restrictions based on theoretical models or on statistical procedures may be imposed to disentangle the impact of exogenous shocks on the system. To specify the model input price shock impacts the price of corn. The model introduced by Kilian was used as the basis model. According to the study, the effect of input price shocks on the price of corn models was modified.
Results and Discussion
If the shock rise in the price of pesticide, fertilizer, and land to occur each of these shocks separately will increase the price of corn, the effect of these shocks has been moved to later periods. Fertilizers price shocks are long-term and neutralization of this process is very slow. However the impact of price shocks of agricultural pesticides and the land quickly neutralized and this index converges whit corn price. Shock rise in corn prices over a period, Makes the corn prices generally decline in the next period and increase the area under cultivation in the following year, with increasing the area under cultivation may take advantage of economies of scale provided and on the other hand, there is the possibility of commuting buying with more inputs. The effect of all impulses can be said after ten periods, will be neutralized. Only shock that after ten periods are not neutral and it is still its effects visible as the shock of the price of fertilizer. The results showed that the corn price volatility is partly influenced by the price of production inputs.63% of the corn price growth changes related to changing values of its past, 8/4% due to changes in land rental growth, 24% of the change in the growth of the price of fertilizer; 1.5% growth related to changes in the price of seed growth (according to the results of the effect is reversed), and 4.1% related to changes in the growth of prices of agricultural pesticides.
Conclusions
Time of purchase of chemical fertilizers is during planting (phosphate fertilizers) and retention period product (Nitrogen fertilizers).In this sense, it seems that the price of fertilizer and how to increase or decrease is one of the important variables and decision-making (after the price trend of maize) in the formation of corn prices on the market. The ownership structure of the agricultural sector is in such a way that most farmers have their land ownership. The cost of renting land is in the form of implicit costs and not obvious and its role in decision-making between variables is low. The cost of agricultural pesticides in the entire cost of production is not significant and the results show that its role in the formation of corn price changes is small. Organization of market demand and supply and timely distribution of inputs for control market price fluctuations and shocks on inputs market can be effective in stabilizing the price of corn.
M.R. Pakravan; O. Gilanpour; Sh. Zarif
Abstract
liberalization of energy price increases costs of agricultural inputs and costs of agricultural production. All these changes may affect the overall competitiveness of domestic products with similar foreign products. As a result of that, total cost of agricultural products are increased and profitability ...
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liberalization of energy price increases costs of agricultural inputs and costs of agricultural production. All these changes may affect the overall competitiveness of domestic products with similar foreign products. As a result of that, total cost of agricultural products are increased and profitability are decreased. In this paper, energy consumption for producing Corn were calculated using cost- production database from Jahad-Keshavarzi for the years 2001-2010. Then, the cost function, production function and demand function for this crop were estimated in the form of panel data structure. Furthermore, the import function of corn and the associated elasticity were calculated using time series data for the years 1981-2000. The results show that, for the corn production, the elasticity of energy input and price elasticity of energy demand are 2.47 and -0.005, respectively. Considering to the fact that the production elasticity in the import function is -0/83, every one percent increase in the price of fuel due to the energy price liberalization policy increases the import of corn by 0/01 percent. Accordingly, increasing energy price has a negative effect on the food self-sufficiency that is one of the main objectives of the fifth national development plan. Ultimately, it is proposed that policy makers provide corn producers with more supports in order to reduce the negative effect of energy price liberalization on the national corn products.
H. Salami; M. Nemati
Abstract
The presence of yield systematic risk in agricultural sector is one of the main reasons for facing this sector with huge damages and is one of the restricting factors in developing agricultural insurance in Iran. This study explores the presence of systematic yield risk and the extent and severity of ...
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The presence of yield systematic risk in agricultural sector is one of the main reasons for facing this sector with huge damages and is one of the restricting factors in developing agricultural insurance in Iran. This study explores the presence of systematic yield risk and the extent and severity of yield spatial dependence for apple production in Iran. To this end, the apple production regions were grouped into two climatic regions based on their thermal regimes. In the second step, systematic yield risk was explored using the first order spatial autoregressive (FAR) model in each of the two climatic regions.Finally, the effects of climatic variables on the yield of apple have been estimated using more general spatial autoregressive models. Results indicate that apple production regions can be classified into two mountainous and plain regions. Apple yields are correlated across space in each of the two regions. Frost in the first region and drought in the second region is accounted for the presence of systematic yield risk in apple production in Iran. Results from more general models revealed that one year lag of drought, the occurrence of frost in March, average of temperature in June and July, total annual precipitation, and variation of precipitation are important climate variables that affect apple yield in Iran.
Z. Rasooli; M. Ghahremanzadeh
Abstract
In this paper, nonlinear adjustments and price transmission mechanism between the two levels of wholesale and retail for the egg market has been examined under the threshold vector error correction model (TVECM) framework using Hansen and Seo (2002)’s two-regimes). The unit root test showed that both ...
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In this paper, nonlinear adjustments and price transmission mechanism between the two levels of wholesale and retail for the egg market has been examined under the threshold vector error correction model (TVECM) framework using Hansen and Seo (2002)’s two-regimes). The unit root test showed that both wholesale and retail egg price series were integrated of order one . The Johansen co-integration test indicated that in the long term, the prices at both ends of marketing chain were quite integrated, i.e. any change in the price of one level is fully transmitted to the other level. In the next step, the SupLM test confirmed threshold adjustment between wholesale and retail series towards the long-run equilibrium. The estimated TVECM (2) showed that the error correction coefficients of retail price equation were significant in both regimes and its value in the first regime was larger than the second regime, while they were insignificant for the wholesale price equation. This indicates that when deviations in the long-run equilibrium occur, wholesalers are reluctant to react, but retailers react to both positive and negative shocks. The findings revealed that the reaction rate is much higher for the positive shocks then the negative ones. The short-run dynamics are almost the same in both regimes; however the speed of adjustment in the second regime is higher than the first regime.
S.S. Hosseini; H. Shahbazi
Abstract
Estimation of agricultural sector demand and supply and identification of its determinants could lead to more efficient policies and planning of this section. In this study, aggregate demand and supply of agriculture sector for years of 1959-2007 by using of nonlinear restricted ARMAX model are estimated. ...
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Estimation of agricultural sector demand and supply and identification of its determinants could lead to more efficient policies and planning of this section. In this study, aggregate demand and supply of agriculture sector for years of 1959-2007 by using of nonlinear restricted ARMAX model are estimated. Result indicates that aggregate agriculture demand is inelastic in short and long run. Those elasticities are -0.118 and -0.162, respectively. Demand own price adjustment coefficient is about 0.273. Also, supply short and long run own price elasticities are 0.129 and 0.166, respectively. Its adjustment coefficient is 0.225. These results accentuate to Agricultural Product necessity nature.
M.R. Pakravan; O. Gilanpour
Abstract
Present study, compares Iran's agricultural products competitiveness power with MENA's countries during 1995-2011. For accomplishing mentioned goal, first, agricultural commodities export and import indices calculated for each one of twenty countries of mentioned region and then revealed comparative ...
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Present study, compares Iran's agricultural products competitiveness power with MENA's countries during 1995-2011. For accomplishing mentioned goal, first, agricultural commodities export and import indices calculated for each one of twenty countries of mentioned region and then revealed comparative advantages index of agricultural commodities trade calculated. Results showed that Iran had comparative advantages in agricultural commodities export only in 1998. Investigating correlation among MENA's countries revealed that Iran had positive relationship with Libya, Lebanon, Saudi Arabia, Oman and Syria. So, it is concluded that Iran's agricultural products export comparative advantages correlated with mentioned countries and for developing agricultural products export we should consider mentioned countries policies in a way that new export goal markets and trade benefits increase have been accomplished. In order to investigate Iran's position in exporting agricultural commodity, Iran's export comparative advantages forecasted till 2017 via ARIMA. Results revealed that mentioned index had declining trend in forecasted period which raised the need of applying serious policies for controlling negative consequences and also, performing the program of nonpetroleum commodities trade expansion document and reducing the petroleum income dependency. Evaluating Iran's trade plan showed that Iran was the loser in market during 2007 till 2009 in agricultural commodities export and loses trade goal markets or could not acquire new share in markets proportionate with global import growth.
O. Javanbakht; H. Salami
Abstract
This study investigates the effects of two policies of reducing profit rate and increasing supply of credits on the growth of production in the economic sectors in Iran. To achieve the goal, the ORANI-G computable general equilibrium model was modified tothe present situation of Iranian economy. The ...
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This study investigates the effects of two policies of reducing profit rate and increasing supply of credits on the growth of production in the economic sectors in Iran. To achieve the goal, the ORANI-G computable general equilibrium model was modified tothe present situation of Iranian economy. The model was also extended to accommodate the financial sector of the economy. To use the CGE model, a financial social accounting matrix based on the latest input-output table published by Statistical Center of Iran in the year 2001 was developed. Using the developed model, two scenarios were simulated. Simulation results of reducing interest rate of credits supplied to the sectors showed that the effects of this scenario on expansion of economic sectors is higher than the impact of the second scenario in the form of increasing supply of credits. This increased the real GDP growth rateby almost twice (1.2% versus 0.6%) of that in the second scenario. furthermore, the total exports experienced positive growth in the first scenario while it faced the negative growth in the second one. Additionally, a reduction in the profit rate of credits reduced prices of commodities and services, which in turns increased the inflation rate by 0.53 percent. However, increase in supply of credits led to an increase in the prices of commodities and services . This caused a rise in inflation rate by 0.04 percent. Increase in supply of credits, however, caused an increase in fixed capital formation in the economy by 1.6 times comparing to the profit rates reduction scenario. These results revealed that there is a compromise between these two policies with respect to their effects on the economy. Based on the goals and priorities of policymakers, one of the policies might be preferred to the other one.