Agricultural Economics
Masomeh bahadori; Bita Rahimi Badr; Alireza Nikouei; Rooya Eshraghi Samani
Abstract
Extended AbstractThe seed control and certification process is considered as a key tool to confirm the quality of the produced seeds. Considering the unique position of wheat in the agricultural and consumption system of the country, this process plays a special role in the sustainability of healthy ...
Read More
Extended AbstractThe seed control and certification process is considered as a key tool to confirm the quality of the produced seeds. Considering the unique position of wheat in the agricultural and consumption system of the country, this process plays a special role in the sustainability of healthy seed production and food security. The present study investigated factors affecting the development of the wheat seed control system and identified the most important components affecting it with the aim of designing a conceptual model.The current research used the grounded theory, and analytic network process. The results of the semi-structured interview in the qualitative stage of 20 cereal seed experts led to the identification of 47 concepts, 11 core categories and four broad categories in the form of six core classes of the paradigm model.In the following, a targeted sample was formed to perform pairwise comparisons with eight members of the academic staff specializing in seed control. The validity and reliability of the research was evaluated at the optimal level. Regarding the semantic interpretation of the conceptual model, regulatory factors and government support policies were identified as solutions with positive consequences, improving the quality of wheat seeds and the stability of the seed market.Moreover, the results showed that the quality of seed kernels and balancing the sale price of healthy seeds were more important than the costs of seed production among the components of technical and economic criteria. In addition, the ranking of seed producing units for providing incentive facilities in the top units and supporting the entry of knowledge-based companies in the supply of seed production were among the strategies developed for the development of this process.IntroductionThe seed industry is a growing industry in the world, and the role of processed seeds in increasing the production performance is undeniable. Due to the population growth, the importance of achieving food security is increasing. Healthy seed is one of the important factors in the development of agricultural production. Although agricultural production systems have increased their production, it does not seem to be enough, though. The basic problems of the seed market and insufficient supply of seeds required by farmers have made it necessary to identify samples of seed quality development. The current research was the first research at the national level dealing with the design of a conceptual model for the development of control and certification of wheat seeds using the grounded theory method and prioritization of effective factors.Materials and MethodsThis research had a fundamental-applicative goal and was applied in two stages. In the first stage, after designing the interview questions, the grounded theory was carried out in three stages of open, central, and selective coding using a systematic approach in order to design a conceptual model. After designing the paradigm model and identifying the factors affecting the development of seed control and certification, the prioritization of the components was done including technical, social, economic and structural criteria using analytic network process.Results and DiscussionAfter analyzing the interviews, 140 initial codes were identified and the initial codes were reduced to 94 and then to 47 concepts. In the following parts, 11 core categories including processed seed production standards, laws and regulations, environmental factors, regulatory factors, equipment and technology, stability in the seed market, government support policies, human factors, wheat seed quality, attitude and awareness, and economic infrastructure were identified. The results of prioritization among the four effective criteria on the development of seed certification indicated that the technical criterion was more important than the other three criteria. In terms of the prioritization of the components, the quality of the seed kernel having a weight of 0.49, the performance of the responsible expert having a weight of 0.44, the cost of producing processed seeds having a weight of 0.39 were the first priority of technical, social, and economic criteria. Applying the ranking of production units with a weight of 0.57 and making the seed market competitive with a weight of 0.26 were more important than other components of structural criteria.ConclusionAccording to the results of this study, and the first priority of the technical criterion, it is suggested to monitor the quality of seed kernels and select appropriate farm inspectors. Moreover, in order to strengthen the human resources system, it is recommended to hold continuous courses in the field of seed quality. To implement the solutions of the paradigm model, it is recommended to prevent buying and selling unhealthy seeds and balance the costs of producing and selling processed seeds.
Agricultural Economics
A. Sani Heidary; E. Safari
Abstract
IntroductionIn the continuity of human life, agriculture as a strategic activity plays a key role in providing food. In addition, the agricultural sector plays an important role in economic development, social welfare and environmental sustainability of all countries. However, this sector is facing many ...
Read More
IntroductionIn the continuity of human life, agriculture as a strategic activity plays a key role in providing food. In addition, the agricultural sector plays an important role in economic development, social welfare and environmental sustainability of all countries. However, this sector is facing many challenges in recent years. Some of its most important challenges include the increasing growth of the world's population, a 40% reduction in water and soil resources, the destruction of a quarter of agricultural land, climate change, a lack of specialized labor, poor access to financial resources, strict laws, and a decrease in the number of farmers due to a decrease in motivation. Therefore, in order to meet the growing demand for food and overcome its challenges, the agricultural sector is forced to look for new solutions such as adopting digital transformation enhanced by artificial intelligence technology. The use of artificial intelligence (AI) technology has recently become increasingly prominent in the agricultural sector. AI-based solutions assist farmers in achieving higher productivity with fewer resources, ensuring the production of high-quality and healthy products, and accelerating the marketing process. Given the significance of AI technology in enhancing the overall efficiency of the agricultural sector, this research aims to identify the key predictors that influence the behavioral intention and adoption of AI technology in agricultural companies. Materials and MethodsThe main objective of this research is to determine the key predictors of behavioral intention and behavior of using artificial intelligence technology in agricultural companies through the combination of the developed UTAUT2 model and TOE factors. The statistical population of this research is the total employees of nine cultivation and industry of Razavi Agricultural Company, which are about 465 people. Data were collected by completing multidimensional questionnaires along with semi-structured interviews from households in 2023. In total, 250 questionnaires were completed. Data of 39 respondents were excluded due to missing values. The questionnaire is designed based on the seven-point Likert scale (strongly disagree = 1, strongly agree = 7). The questionnaire used in this research includes 14 constructs in the form of 60 items. Excel 2019 software was used to analyze the raw data of the questionnaire and SmartPLS software was used to test the research hypotheses. In order to guarantee the stability of the data, a complete bootstrap method with 5000 sub-samples was performed. Results and DiscussionThe results revealed that the values of Cronbach's alpha and CR for all constructs were higher than 0.7, which shows acceptable internal consistency of the model and adequate reliability of the research constructs. AVE scores and factor loading values for all constructs are above 0.5, which indicates the correct definition of constructs and high convergence between constructs and its items. The values of rho_A as an important reliability measure for PLS-SEM for all constructs are greater than the acceptable value of 0.7. The results of the Fornell-Larcker criteria and the Heterotrait-Monotrait ratio (HTMT) indicate that the model is confirmed in terms of the constructs' discriminative validity. In addition, the research model was able to explain 89.4 and 51.7 percent of the variance of the variables of behavioral intention and the behavior of people to use artificial intelligence technology in the agricultural sector. According to the results, all research hypotheses are confirmed and the behavioral intention to adopt artificial intelligence technology is positively and significantly influenced by expected performance, social effects, hope for effort, facilitating conditions, pleasure-seeking motivation, price-value, habit, trust in technology, technological aspects, organizational aspects, and environmental aspects. However, the fear of technology variable has a negative and significant impact on people's behavioral intention. ConclusionThis study highlights the determining the role of expected performance constructs, social influences, fear of technology, and organizational and environmental aspects compared to other constructs in predicting people's behavioral intention to adopt artificial intelligence technology in the agricultural sector and provides important information for different stakeholders. According to the results, it is suggested that the government should invest in the development of the necessary infrastructure for this technology and provide a platform for its development by establishing efficient laws and paying low-interest facilities. In addition, Designers should create user-friendly tools tailored to the agricultural conditions of the country.
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. ...
Read More
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. Zolanvari Shirazy; Z. Farajzadeh
Abstract
Iran attempts to expand the non-oil exportsfor diminishing the dependency on oil export income. This research tries to examine the export and trade balance of Iran's agricultural sector. Accordingly, the gravity model was used for export, applying panel data from 1997 to 2017. Also, the trade balance ...
Read More
Iran attempts to expand the non-oil exportsfor diminishing the dependency on oil export income. This research tries to examine the export and trade balance of Iran's agricultural sector. Accordingly, the gravity model was used for export, applying panel data from 1997 to 2017. Also, the trade balance of Iran's total agricultural and the related sectors’commodities was examined. It should be noted that for the trade balance, time series data from 1978 to 2018 were used. The results of the gravity model show a negative effect for the variable of distance. The coefficients of Iran’s per capita GDP and also the GDP of trading partners are positive, as expected. It was found that a one percent increase in the per capita GDP of Iran causes a rise of 3.42 percent in the export of agricultural products; however,that of importing countries haslow statistical significance. Based on the coefficient obtained for the population, an increase in the population of the importing countries raises the demand for Iran's agricultural products.The degree of trade openness revealed a positive and significant effect on the export of agricultural products. The coefficient for the real exchange rate was found to be around 0.9 percent. It was also found that the volatility of the exchange rate is related directly to the export of agricultural products. Comprehensive sanctions have a negative and significant effect, while less restricting sanctions have an insignificant effect on the export of agricultural products. The global economic crisis has also had a dampening effect on exports. For trade balance, the results show that the value added of the agriculture has a positive effect on the trade balance of entire agriculture and sectors. The real exchange rate has a negative effect on the trade balance of agricultural commodities as a whole and livestock and agronomy sectors, confirming the J-Curve theory while it was not supported for the horticultural sector. Also, the variable of exchange rate volatility was included in the model using two measures of positive and negative series of exchange rate changes and the Autoregressive Conditional Heteroskedasticity (ARCH) effect, but their effect on the trade balance was not the same in terms of both the direction and statistical significance. The trade openness for the agricultural and horticultural sector was found with a positive coefficient, indicating that their production is based on comparative advantage. However, for the sectors of agronomy and livestock, it illustrated a negative effect. Sanctions have also harmed the trade balance.
Agricultural Economics
A. Parvar; H.R. Mirzaei Khalil Abadi; H. Mehrabi Boshrabadi; M.R. Zare Mehrjerdi
Abstract
Water is one of the main basic resources for development and is the most significant factor in Iranian agriculture production. The agricultural sector has an important role in production, employment, and gaining exchange and drastically affects other sectors of the economy. The purpose of this study ...
Read More
Water is one of the main basic resources for development and is the most significant factor in Iranian agriculture production. The agricultural sector has an important role in production, employment, and gaining exchange and drastically affects other sectors of the economy. The purpose of this study was to evaluate the effect of water resources` reduction on agricultural sub-sector and other sectors` employment. The employment data were collected from SAM, 2011 and the employment generated by the economic activities of the economic sectors and the contribution of each of these sectors to employment was examined. The service sector ranked first with 24.99% employment creation and agriculture ranked second with 19%. Construction, industry, commerce, and transportation sectors ranked third to sixth, with 82.4% of the total employed working in these six sectors. The results showed that with water resources reduction by 10, 20 and 30%, the total employment decreased to 416334, 769472 and 1044114 people, respectively. In agricultural sub-sectors, the highest decrease was in farming and horticulture subsectors with an average of 14.17%. According to the results, water saving technology was a solution to reach the major goals of agricultural development, especially for employment.
Agricultural Economics
Z. Alinezhad; S.M.B. Najafi; J. Fathollahi; N. Zali
Abstract
The pattern of knowledge-based production has recently changed economic and social relations. If one wants to use the benefits of this pattern, they have to pay serious attention to the production, distribution, and dissemination of knowledge; in this regard, Leading Knowledge (LK) plays a vital role ...
Read More
The pattern of knowledge-based production has recently changed economic and social relations. If one wants to use the benefits of this pattern, they have to pay serious attention to the production, distribution, and dissemination of knowledge; in this regard, Leading Knowledge (LK) plays a vital role in developing areas. However, since government budgets have to be spent for public, especially for science and technology which are too expensive, it is impossible to experience the simultaneous advancement in all branches of knowledge. This qualitative and descriptive analysis adopts an applied approach, and tries to identify the LK of the agricultural sector in Kermanshah province, Iran. First, the initial list of LK and Analytic Hierarchy Process (AHP) method based on key technology techniques were prepared through reviewing documents and surveys, i.e. interviews and a panel of experts. In-depth and purposeful interviews were also adopted to extract experts’ opinions. Finally, data were analyzed by a panel of experts using the Analytic Hierarchy Process in Expert Choice (EC) software. The results showed that water engineering (0.223), horticultural Science (0.196), and biotechnology (0.138) were listed in order of priority in Kermanshah province. The results can be helpful in revising the educational policies of universities and research centers at the province level, allocating limited resources to the relevant government organziations, Agriculture Jihad and related research centers, and determining the policy of science and technology park and agricultural research centers at the national level.
Agricultural Economics
F. Ghafarian; Z. Farajzadeh
Abstract
Energy products are the main sources of emissions for most of the pollutants in Iran. However, for some pollutants like Methane (CH4) and Nitrous Oxide (N2O), the production process, including the agricultural production process, plays a significant role. The aims of this study were to analysis the emissions ...
Read More
Energy products are the main sources of emissions for most of the pollutants in Iran. However, for some pollutants like Methane (CH4) and Nitrous Oxide (N2O), the production process, including the agricultural production process, plays a significant role. The aims of this study were to analysis the emissions intensity of the selected pollutants and to introduce the determinants in Iranian agricultural sector. The emission intensity in the agricultural sector was decomposed into its components using decomposition analysis. Then, the regression analysis was applied to investigate the emission intensity determinants. The selected pollutants are Carbon Dioxide (CO2), CH4, and N2O emitted from agricultural production process. The applied data cover 1973-2016. The findings showed that CH4 emission intensity has been decreasing over the study horizon by 3.9% annually. For N2O, the corresponding value was 2.6%. Based on the results, output level in agricultural sectors is an important driving factor in the emission intensity. It was found that 1% increase in livestock output level is expected to increase CH4 emission intensity by 0.9% while it will dampen the N2O emissions intensity by more than 3.3%. By contrast, the same percentage of increase in the output level of agronomy and horticultural subsector will induce an increase of 3.3% in N2O emission intensity and will reduce the CH4 emission intensity more than 0.9%. Macroeconomic variables including urbanization and trade openness failed to affect the agricultural emission intensity significantly. The emission intensity of all pollutants, measured in CO2 equivalent, has been decreasing over the study period by 3.5% annually. It was also found that, in terms of aggregated emission, output expansion in livestock and forestry sectors may induce higher emission intensity, while agronomy and horticultural output expansion can reduce the emissions intensity. Given that the output level plays a significant role in emission intensity while the macroeconomic variables have nothing to do with emission intensity, the measures taken to reduce the emission intensity in the agricultural sector should be sector-specific. Moreover, the measures should focus on each subsector individually.
Agricultural Economics
Sh. Shamsoddini; S. Ghobadi; S. Daei Karimzadeh
Abstract
Introduction: One of the most important variables effective on the PPI of agricultural products is the exchange rate. With the change in the exchange rate, the relative prices of exports and imports have changed, and given that the major part of the imports in agricultural sector is the inputs required ...
Read More
Introduction: One of the most important variables effective on the PPI of agricultural products is the exchange rate. With the change in the exchange rate, the relative prices of exports and imports have changed, and given that the major part of the imports in agricultural sector is the inputs required for the production of this sector, this will change the cost of agricultural products. The exchange rate directly affects the export and import of agricultural products and agricultural inputs and indirectly affects production, income, costs, profits and investment in the agricultural sector. Thus, the exchange rate affects the price index in this sector due to its effect on the supply and demand of products and inputs in the agricultural sector. Monetary policy is one of the factors that can affect the price of food and agricultural products. One of the main goals of monetary policy is to stabilize the general level of prices in the economy. In a situation where society is exposed to inflationary pressures and the CPI is rising, the application of a contractionary monetary policy can play an important role in inflation control. Materials and Methods: In this study is used the nonlinear autoregressive distributed lags (NARDL) method for estimating of PPI agricultural products equation using Eveiws12 software. The data required for this study are related to the period 2009 (Chapter 4) to 2019 (Chapter 4), which is mainly collected from domestic library sources, including the Statistical Center of Iran, the Ministry of Agriculture-Jihad, the Central Bank of Iran and the Ministry of Economic Affairs and Finance. The data on the effective real exchange rate has been extracted from the IMF web site. Based on the theoretical foundations and fulfilled studies, the long-run relationship exists between the PPI of agricultural products and the explanatory variables such as real effective exchange rate, GDP, CPI and money supply. This equation is transformed into an unbound error correction model (UECM) using the functional form ARDL (p, q) and is estimated using the ordinary least squares (OLS) method. In this study, the Bounds test has used for investigating the existence of a long-term relationship (co-integration) between independent and dependent variables. Also the Wald test has used for investigating the symmetric or asymmetric effects of independent variables (exchange rate and money supply) on the dependent variable. Results and Discussion: The results of the augmented Dickey-Fuller (ADF) test show that all variables are stationary in first difference. In other words, the variables are integrated from the first degree and in this research, the NARDL approach can be used. The results of Bounds test indicate that in both the linear symmetric model (ARDL) and the nonlinear asymmetric model (NARDL), the calculated F-statistic is greater than the critical values of the upper bound. Thus, the long-run equilibrium relationship between the variables of both models is accepted with 99% confidence. The results of linear model (ARDL) indicate that the real effective exchange rate with a time lag, in the short term has a positive and significant effect on the PPI of agricultural products. The GDP variable only in the long run has a negative and significant effect on the PPI of agricultural products. In addition, the CPI in the short term with a time lag and in the long term has a positive and significant effect on the PPI of agricultural products. Also, in the linear model, money supply (monetary policy) has had a positive and significant effect on the PPI of agricultural products only in the long run. The results of the NARDL model show that in the short run, only the positive shock of real effective exchange rate has a positive and significant effect on the PPI of agricultural products. Accordingly, the GDP variable in the short run has a negative and significant effect on the PPI of agricultural products. In the short run, the CPI with a time lag has a positive and significant effect on the PPI of agricultural products. In addition, in the short run, the positive and negative shocks of money supply have not had a significant effect on the PPI of agricultural products. In the long run, the positive shock of real effective exchange rate has a positive and significant effect on the PPI of agricultural products. In addition, the negative shock of the real effective exchange rate in the long run has a negative and significant effect on the PPI of agricultural products. Also, positive shocks of money supply (monetary policy) in the long run have a positive and significant effect on the PPI of agricultural products. Negative shocks of money supply (monetary policy) in the long run have a positive and significant effect on the PPI of agricultural products. In the long run, GDP has had a negative and significant effect on the PPI of agricultural products. Conclusion: The results indicate that the positive shock of the real effective exchange rate, both in the short run and in the long run, has a positive and significant effect on the PPI of agricultural products. Therefore, the depreciation of national currency always increases the PPI of agricultural products. Therefore, the most important step forward for the policymakers and planners to control the rising trend of prices is to prevent the depreciation of the national currency. Based on these results, positive and negative shocks of money supply (expansionary and contractionary monetary policies) have a positive and significant effect on the PPI of agricultural products only in the long run. Therefore, application of monetary policy in the agricultural sector is like a double-edged sword, and the use of these instruments by monetary authorities requires consideration of all aspects.
N. Barani; A. Karami
Abstract
Introduction: Due to fossil fuels overuse, land use change, global population growth and the development of industrial activity to meet the welfare and demands of the global community, global climate has undergone gradual, but drastic, changes in the post-industrial revolution era mainly manifested in ...
Read More
Introduction: Due to fossil fuels overuse, land use change, global population growth and the development of industrial activity to meet the welfare and demands of the global community, global climate has undergone gradual, but drastic, changes in the post-industrial revolution era mainly manifested in the rise of mean temperature, more frequent extreme climatic events like floods, hails, tropical storms, heat and cold waves, rising sea level, polar ice melting, droughts and etc. Climate change is a mix of dominant and lasting atmospheric characteristics of a geographic area over time and is often based on such variables as temperature, precipitation, humidity, wind, solar radiation, and number of sunny days, sea level temperature, and the thickness of ice layers at sea. Climate of a region is dedictated by a set of these factors in the long run, as well as other local characteristics such as the length of growing season and the intensity of floods whose change influences how people live and harm different sectors including agriculture and environment. Present study aimed to explore the impact of climate change on total agronomical production in 10 agro-ecological zones of Iran.Materials and Methods: Present study employed panel data econometrics to explore the impact of climate change (mean precipitation, temperature, evapotranspiration rate, relative humidity, wind speed) on total agronomical production over the 1985-2015 periods. The panel data set included the observations related to multiple sectors and have been collected at different times. Panel data has been used when it is impossible to use just time series data or cross-sectional data. They contain more information in addition they are more diverse and have less multicollinearity between variables, so they are more efficient. In analysis of the combined data firstly should consider a certain section (e.g. country, region or province) and then focus on the attributes of the variables related to all N sections over a certain period, T. The number of data is not required to be equal over the sections (unbalanced panel model) and it is also possible to have variables that are constant in a certain section over the studied time period. In a panel data model, the variables are measured sequentially both among the sections of the statistical population and over time. In panel data, before proceeding to model estimation, we should firstly recognize whether panel or pool model is appropriate for the estimation and statistical inference. To do this, we first integrate whole data as pool to estimate the model and calculate the sum of residual squares. Then, the model is estimated as a panel model with different y-intercepts for a certain section and the residual squares are again summed. Finally, F-statistic is applied as the following equation to test the constructed model. The data were collected from Iran Meteorological Organization and Ministry of Jihad-e Agriculture. After checking the stationarity of the data, panel model with random effects has been estimated.Results and Discussion: The results showed that total agronomical production has been influenced by temperature, evapotranspiration, and wind speed at 0.05 level and precipitation at 0.10 level. The impacts of global warming can be currently observed across the world. Agricultural sector is especially vulnerable to climate change so the rise in average seasonal temperature would shorten the growth period of most crops, causing the loss of their yields. Climate changes, such as the change in temperature, precipitation, pest and disease outbreaks adversely influence food production systems, decrease harvest and jeopardize food security. As predicted for Iran, it is expected that occurrence of climate change – which is characterized by rainfall decline, rise in temperature, and increase in the occurrence of extreme weather conditions – have harmful consequences for the agronomical production.Conclusion: Climate change imposes remarkable economic costs on agronomical producers. The producers may have to either stop growing these crops or adapt to climate change as far as possible. In most cases, it is not economically feasible for producers to apply adaptive methods and the majority of their life aspects are potentially influenced. According to the results, it is recommended to use water pricing policies in agricultural sector that motivate farmers to use modern irrigation technologies and low irrigation-resistant cultivars, alter planting pattern towards crops with higher water use efficiency, therefore plan for and grant financial facilities, such as crop insurance, in order to prepare agronomical farmers for climate change.
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 ...
Read More
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.
F. Alijani; M. Salarpour; M. Sabouhi
Abstract
Considering the importance of the impact of subsidy reform on the agricultural sector, the study aimed at understanding consequences of changes in the rates of production subsidy using General equilibrium model based on input-output table in the year 2001.The study conducted based on three scenarios ...
Read More
Considering the importance of the impact of subsidy reform on the agricultural sector, the study aimed at understanding consequences of changes in the rates of production subsidy using General equilibrium model based on input-output table in the year 2001.The study conducted based on three scenarios containing step, down and finally removed rates of production subsidy. The effects on production, value added, employment, export and import activities in the agricultural sector were analyzed. Results showed that production, value added and export of cultivation, livestock and poultry activities have been reduced more than other activities in the field. Results also showed that employment in sub-sections of the agricultural sector and paltry activities have been reduced. Furthermore, elimination of production subsidies had a negative impact on the fish imports, while the impact was positive for imports of other products. Therefore, since the policy had negative impact on the agricultural products, supporting agricultural sector along with reduction in the government’s expenditures is recommended.
H. Mehrabi Boshrabadi; E. Javdan
Abstract
AbstractResearch and Development (R&D) spending plays a major role in innovation, raising productivity and increasing economic growth. The purpose of this paper is to investigate the impact of R&D spending on growth and total factor productivity (TFP) in Iran's agricultural sector. We estimate ...
Read More
AbstractResearch and Development (R&D) spending plays a major role in innovation, raising productivity and increasing economic growth. The purpose of this paper is to investigate the impact of R&D spending on growth and total factor productivity (TFP) in Iran's agricultural sector. We estimate growth and productivity models using Auto-Regressive Distributed Lag (ARDL) approach and data over 1974 to 2007. Our results indicate that research and development spending has positive and significant effects on growth and total factor productivity in Iran's agricultural sector in short and long term. Therefore research and development can be used a main source of further growth of agricultural sector.JEL Classification: O4, D24, Q16
S. Naghavi; H.R. Mirzaei Khalil Abadi; S.A. Jalaee Esfandabadi; H. Mehrabi Boshrabadi
Abstract
AbstractIn present paper has tried to examine and investigate quality of effectiveness of monetary Shocks on the growth of agricultural Sector by using Time series dataes of Iran Economy during 1960-2006 , filter Hodric-Prescott method and liner Regressive models. The resultes Show that qualily of effectiveness ...
Read More
AbstractIn present paper has tried to examine and investigate quality of effectiveness of monetary Shocks on the growth of agricultural Sector by using Time series dataes of Iran Economy during 1960-2006 , filter Hodric-Prescott method and liner Regressive models. The resultes Show that qualily of effectiveness monetary shocks on growth of Agricultural Sector is Asymmetric and length of effectiveness Monetary Shocks is symmetric . in other words negetive monetary shocks affect growth of agricultural Sector more than positive monetary shocks on the and reflection of value added of agricultural to positive monetary shocks is small than negetive monetary shochs.however, monetary policies aren,t suitable for influence on production of agricultural sector. However, it is Necessery policemakes use suitable policies for influence production of sector agricultural.
M. Zarif; M. Salarpour; A. Karbasi
Abstract
AbstractThis study uses gravity model to examine the most important determinants of was agricultural trade. To This aim, import and export statistics of Iran agricultural products for the period 1380 to 1387 was provided from Iran customs organization and other information was obtained from different ...
Read More
AbstractThis study uses gravity model to examine the most important determinants of was agricultural trade. To This aim, import and export statistics of Iran agricultural products for the period 1380 to 1387 was provided from Iran customs organization and other information was obtained from different internet bases. Random effects estimating and Hausman test ratio result in fixed effects model, which determined the effects of dependent variables over independent ones. First, the effect of independent variables such as GDP, per capita income, Linder effect, geographic distance, exchange rates, exchange rate uncertainty and dummy variable of border was determined on each import and export of agricultural sector. Then dummy variables related to the regional integrations of Organization of Islamic Conference and the ECO were also applied in model. The results showed that the GDP of commercial Partner has positive effect on export and import of agricultural trade but it is smaller for OIC members. Linder effect, geographical distance and exchange rate uncertainty have negative effects on both export and import of Iran agricultural products. Per capita income had a negative effect on export, while it had a huge positive effect on import. real exchange rate had positive but very small effect on import and negative effect on export of Iran agricultural sector. The results showed that cooperating with the OIC members lead to an increase in import and export of Iran agricultural products and it would reduce negative effects of exchange rate uncertainty. Because of the opposite relation between geographical distance and export or import is suggested reinforcement of international transporting infrastructures. In addition Islamic countries Which have shorter geographical distance from Iran have high commercial potential and the necessity for concluding local contracts with them is clearly understood.
M.R. Pakravan; H. Mehrabi Boshrabadi; O. Gilanpour
Abstract
AbstractExport of nonoil goods in economic activities is so important and its effect on economic and comparative growth is undeniable. So, Emphasize on agricultural sector and development of export in this sector prepares good conditions, for Iran, to be present at international markets relying its advantages. ...
Read More
AbstractExport of nonoil goods in economic activities is so important and its effect on economic and comparative growth is undeniable. So, Emphasize on agricultural sector and development of export in this sector prepares good conditions, for Iran, to be present at international markets relying its advantages. The study tries to recognize necessary policies to enhance agricultural export potentialities. To this end, this study investigates determinants of supply and demand of Iran’s agricultural products export from 1965 to 2007 by using Tree-stage least square. The result indicates that shadow exchange rate, relative prices, product quantity, domestic price and dummy variable related to war, are effective variables on demand and supply of exports. Also, price elasticity in long run and short run for export demand are estimated to be -1.83 and -2.12, respectively. And Price elasticity of export supply in short run is 2.17.JEL Classification: F10, F11, Q11 ،Q17, Q19
H. Khaksar Astane; A. Karbasi
Abstract
AbstractAgricultural research and promotion are factors of the same system that activity in different organizations framework and have common marginal goal. Therefore, The Joining between research and promotion is important. Both activities are very important, therefore the investment in one part should ...
Read More
AbstractAgricultural research and promotion are factors of the same system that activity in different organizations framework and have common marginal goal. Therefore, The Joining between research and promotion is important. Both activities are very important, therefore the investment in one part should not have had effect in other part. Therefore, total Goal of this study, is consideration of Substitution or supplementary relation between investment in agricultural research and promotion. Therefore, The Productivity model was used; also, Total Factor Productivity was calculated with Tornquist – Theil indicator. Data was collective from different sources, during 1979-2004. The Results was shown one percent increasing in agricultural research investment, increases total factor productivity 0.080974 percent. Also 1 percent increase in promotion investment; increases total factor productivity 0.038398 percent. The variable of interaction between research and promotion has had significant with negative mark. To become negative this variable shows the both of these variable effect with total factor productivity and these are substitution, the reason is lack of research and promotion budgets in agricultural section.
A. Karbasi; H. Asnashari; .A Aghel
Abstract
AbstractAgricultural sector is the most important sectors in the country which has a large share in total employment. The increasing supply of labor because population growth and low capacity of production cause the country with high rate of unemployment. Therefore, stand with this crisis is one of the ...
Read More
AbstractAgricultural sector is the most important sectors in the country which has a large share in total employment. The increasing supply of labor because population growth and low capacity of production cause the country with high rate of unemployment. Therefore, stand with this crisis is one of the most important works of government. In this study using Artificial Neural Network, the employment is forecasted by 1958-2004 data for 14 years later and results show that the trend of employment in agricultural sector in later years first is diminished and then increased.