Agricultural Economics
behnaz nazerani; javad hosseinzad; Muhammad Ghahremanzadeh
Abstract
1. Introduction
The agricultural sector in developing countries, including Iran, has not been able to benefit from its presence in the stock market due to the lack of supporting infrastructure, active capital supply companies, weakness in financial literacy, inadequate technical knowledge, and lack of ...
Read More
1. Introduction
The agricultural sector in developing countries, including Iran, has not been able to benefit from its presence in the stock market due to the lack of supporting infrastructure, active capital supply companies, weakness in financial literacy, inadequate technical knowledge, and lack of proper understanding of environmental conditions. Also, over the past ten years, agricultural sector firms have recorded the lowest sales among listed companies. Severe price fluctuations, lack of transparency and information flow in local agricultural product markets, and the widespread presence of brokers and intermediaries in various sectors of distribution and sales of these products are among the problems that have severely weakened the position of agricultural sector firms in the stock market. So, over the past ten years, agricultural sector firms have recorded the lowest sales among listed companies.These problems have mainly affected the agricultural sector of Iran in the absence of a coherent, organized and competitive market. The stock market, by using trading tools and methods, can significantly solve these problems by creating a competitive, transparent and efficient market and provide a very strong potential for agricultural enterprises to enter the stock market in Iran. Entering the stock market and offering shares of agricultural enterprises, in addition to providing capital, will lead to the discovery of the real price of shares and greater prosperity and profitability, and ultimately increasing the financial performance of these enterprises. There is. In order to better understand and further investigate this issue, the present study attempts to study the exact relationship between financial performance and stock price.
2. Materials and Methods
In the present study, the simultaneous equations method has been used to examine the relationship between stock prices and financial efficiency of agricultural firms and companies. In the present study, four financial ratios such as return on assets ratio, total asset turnover ratio, debt-to-capital ratio and Tobin's Q ratio have been used to measure financial efficiency. Also, in the system, a set of control variables that affect the stock prices of companies were considered, such as liquidity, financial leverage, company size and history, sales growth, company cash flow, and profit performance or efficiency. Statistics and information related to performing calculations and estimating models have been collected from various relevant sources and organizations such as Tehran Stock Exchange, Central Bank and Ministry of Agricultural Jihad.
3. Results and Discussion
The results of the system estimation using simultaneous equations have shown that there is a positive and significant relationship between return on assets, asset turnover ratio, debt-to-equity ratio, and Tobin's Q with stock price. While the relationship between debt-to-equity ratio and stock price has been negative and significant. This indicates the importance of paying attention to financial efficiency in determining the value of companies' stocks. In fact, improving financial efficiency makes the company's stocks more valuable to customers. That is, the better the company's financial performance or efficiency, the more investors who are interested and need to buy shares in the company, which also leads to an increase in stock price. An increase in stock price also leads to an improvement in financial ratios, which also requires an increase in financial performance. This shows the importance of considering financial efficiency in determining the value of company shares. In fact, improving financial efficiency makes the shares of companies and firms more valuable to customers. That is, the better the company's financial performance or efficiency, the more investors who are interested and have a demand to buy shares in the company, which also leads to an increase in the stock price. Changes in stock prices affect financial ratios, and these ratios can be used in the evaluation and analysis of companies and investments.
4. Conclusion
Stock price and financial efficiency are interrelated. In other words, stock price de-graphication increases financial efficiency by improving financial ratios. Improving financial ratios and increasing financial efficiency also increase shareholders' expectations for profit and capital increase if the company's financial ratios improve. This also increases the demand for shares and ultimately increases the value and price of shares. By examining the factors affecting financial efficiency and stock price and their relationship in agricultural enterprises, it is possible to identify and eliminate the causes of the decline in the acceptance of agricultural enterprises by the stock market and to encourage and facilitate the presence of these enterprises in the stock market by removing obstacles.
Agricultural Economics
Jabraeil Vahedi; Mohammad Ghahremanzadeh; Ghader Dashti; Parisa Pakrooh
Abstract
Introduction
Optimizing agricultural resources is crucial to meeting the food demands of a growing population. This involves increasing cultivated land or maximizing production efficiency, especially in the face of challenges like climate change and water scarcity. Evaluating the efficiency of agricultural ...
Read More
Introduction
Optimizing agricultural resources is crucial to meeting the food demands of a growing population. This involves increasing cultivated land or maximizing production efficiency, especially in the face of challenges like climate change and water scarcity. Evaluating the efficiency of agricultural producers helps identify gaps between top performers and others, which can inform policies aimed at enhancing productivity. Ahar County is a key wheat production area, contributing about 10% of East Azerbaijan Province's wheat cultivation, with 28,000 out of 52,000 hectares dedicated to this crop. While this indicates the county's significance, the varying yields necessitate further investigation into technical efficiency (TE).
Conducting economic research on wheat production in Ahar could positively impact regional yield. This study aims to provide a framework for analyzing factors affecting efficiency, aiding farmers in making informed resource management decisions. Furthermore, data mining techniques can analyze economic, social, and environmental data to uncover complex relationships influencing efficiency, thereby enhancing production optimization and guiding policymakers in improving agricultural productivity.
Material and methods
In this study, data mining techniques are employed to classify farmers based on TE and to analyze the factors influencing it. First, TE is calculated using wheat output (kg) and inputs such as cultivated area (hectares), seeds (kg), labor (person-days), and tractor usage (hours) through Data Envelopment Analysis (DEA).
Farmers are classified into two groups: High-efficiency farmers (above regional average efficiency) and low-efficiency farmers (below average efficiency). Next, the most suitable machine learning algorithm is identified to predict farmers' TE and categorize them accordingly. The aim is to find an algorithm that closely predicts the actual classifications based on efficiency calculations. Higher algorithm accuracy improves the reliability of the analyses. Machine learning, particularly supervised learning algorithms, is used for this analysis. Classification algorithms aim to create a model for predicting outcomes by sorting database records into predefined categories based on specific criteria. Common tools include logistic regression, support vector machines, k-nearest neighbors, and random forests.
After estimating machine learning models, it is essential to evaluate their performance using various metrics to ensure the models function correctly. Key metrics include the confusion matrix, recall, accuracy, precision, F1 score, Cohen’s kappa statistic, and the Receiver Operating Characteristic (ROC) curve, each highlighting different aspects of model performance. Utilizing these metrics allows for a more detailed analysis of predictive results. The data used in this study were collected through simple random sampling via in-person interviews and questionnaires from 223 wheat producers in Ahar County.
Results and discussion
The average TE was calculated to be 0.59. Farmers with an efficiency below this value were categorized into group zero, while those with an efficiency above this value were placed in group one. The results of the statistical tests indicated that continuous variables such as nitrogen fertilizer, land rental value, age, and experience; countable variables like the number of plots and household members with university education; dummy variables including residence, seed sourcing, land ownership, harvesting method, off-farm income, animal manure, herbicide, and pesticide; and weed control, as the only ordinal variable, significantly affect technical efficiency and should be included in the machine learning model.
The study utilized several algorithms, including logistic regression, support vector machine, K-nearest neighbors, and random forest. Logistic regression achieved the highest average accuracy of 88.7% with five-fold cross-validation and outperformed the others, showing an AUC of 0.98 on ROC curves and strong performance in the confusion matrix. The results of the logistic regression indicate that variables such as herbicide use, weed control, animal manure, land rental value for wheat farms, nitrogen fertilizer, number of farm plots, pesticide use, age, combined harvesting methods, experience, household members with university education, seed supply from the Agricultural Jihad Organization, and living in rural areas positively affect TE. Conversely, land ownership (personal-rented), sourcing seeds from personal resources, and having off-farm income negatively impact efficiency.
Optimal herbicide application can reduce competition with wheat, enhance crop quality, and improve nutrient and rainfall absorption, thereby increasing TE. Using animal manure improves soil quality, aiding wheat's nutritional needs. High land rental values may indicate suitable soil quality and production potential, facilitating modern management practices that positively influence efficiency. Nitrogen fertilizer can enhance plant growth and yield by increasing soil nitrogen levels. Farmers with multiple plots can mitigate risks from weather or pests and employ better planting and harvesting strategies. Additionally, pesticides help prevent damage from pests, increasing overall production. Age often reflects a farmer's experience in farming, with older farmers typically having more expertise in effective agricultural practices, which can improve TE. Experienced farmers tend to adopt better strategies to address agricultural challenges. Using combined harvesting methods can optimize the harvesting process, allowing better use of time and resources and resulting in higher yields. The presence of educated members within farming households can enhance agricultural management knowledge and skills. Sourcing seeds from reputable institutions like the Agricultural Jihad Organization, which provides quality and pest-resistant seeds, can effectively enhance crop yield. Living in rural areas is a crucial factor for timely agricultural operations.
On the negative side, land ownership (personal-rented) can reduce farmers' incentives to invest in land improvement and resource optimization, ultimately impacting their TE. Sourcing seeds from local personal resources can lead to lower quality and pest-sensitive seeds, resulting in reduced productivity. Additionally, off-farm income may divert farmers' focus from agricultural activities, diminishing attention and investment in farming practices, which can lead to decreased TE.
Conclusion
The study suggests that training programs and sourcing seeds from reliable suppliers, like the Agricultural Jihad Organization, can enhance farmers' yields and crop quality. However, land ownership (personal- rented) and sourcing seeds from personal resources may reduce efficiency. Policymakers should motivate farmers on rented land with financial incentives and improve access to quality seeds through distribution centers in rural areas. Collaborations with seed-producing companies can ensure a steady supply of high-quality seeds, further boosting yields.
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 ...
Read More
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
F. Tagavi; B. Hayati; M. Ghahremanzadeh
Abstract
IntroductionBread holds a crucial position in Iranian cuisine and encompasses various types such as Barbari, Lavash, and Sangak. However, these bread varieties are often made from refined flours, lacking the nutritional benefits of whole grains. Reports from the Statistical Center of Iran indicate that ...
Read More
IntroductionBread holds a crucial position in Iranian cuisine and encompasses various types such as Barbari, Lavash, and Sangak. However, these bread varieties are often made from refined flours, lacking the nutritional benefits of whole grains. Reports from the Statistical Center of Iran indicate that bread purchases constitute a significant portion of household expenses. Recent studies have raised concerns about the adverse health effects associated with excessive consumption of refined bread, potatoes, and rice, including diabetes, indigestion, obesity, cardiovascular issues, and digestive system disorders. These concerns highlight the limitations of whole grain food consumption, such as whole wheat-grain bread. To address these health concerns, it becomes necessary to provide stronger incentives or encourage individuals to incorporate more whole grain products into their diets. Thus, the present study aims to analyze the factors influencing households' willingness to pay extra for whole wheat-grain bread, specifically Lavash and Sangak, in the city of Tabriz over a specified time period. By examining these factors, valuable insights can be gained to promote the consumption of healthier bread options and enhance public health outcomes.Materials and MethodsTo achieve the research objective, a questionnaire was developed, and data was collected through a random sampling method from households residing in the ten provinces of Tabriz city. Face-to-face interviews were conducted with 302 households during the summer of 2020. The data obtained from the questionnaire was analyzed using statistical and empirical techniques, specifically the Contingent Valuation Method (CVM), Sequential Logit (LS) model, and Generalized Sequential Logit (GSL) model. To ensure the validity of the models used, the Brant test of parallel regression was applied. This test evaluated whether there was proportionality in the odds model for ordinal logistic regression. It examined whether the observed deviations from our ordinal logistic regression model were significantly larger than what could be expected due to chance alone. This assessment helped ensure the reliability and accuracy of the statistical analysis conducted in the study.Results and DiscussionThe results of the study indicate that a high percentage of households in Tabriz city, specifically 90.73% for Lavash bread and 93.38% for Sangak bread, were willing to pay extra for whole wheat-grain options. Among the households, 40.4% expressed their willingness to pay less than 20% extra for the bread, while 26.82% were willing to pay more than 50% extra. Several factors were found to influence households' willingness to pay for whole wheat-grain bread. Positive effects were observed for the health index, knowledge of the benefits of whole wheat bread, education level, family income, presence of elderly individuals in the family, and frequent consumption of whole wheat Lavash bread. However, gender had a negative effect on households' willingness to pay for whole wheat-grain Lavash bread. Similarly, for whole wheat-grain Sangak bread, the health index, knowledge of the benefits of whole wheat bread, family income, and the presence of a patient individual in the family had positive effects, while gender had a negative effect. As the null hypothesis of the parallel regression test was rejected, the Generalized Sequential Logit model was applied to analyze the effects of various factors on households' willingness to pay at different levels (0%, less than 20%, 21-30%, 31-40%, 41-50%, and more than 50%) for different types of whole wheat-grain bread. The results of the model yielded different outcomes. Increases in the health index, awareness of whole wheat bread, family income, education level, presence of a patient individual in the family, and frequent consumption of whole wheat bread positively influenced households' willingness to pay more for both Lavash and Sangak bread. Education level and the presence of a patient individual in the family acted as incentives for whole wheat-grain Lavash bread, while gender and the number of household members deterred households from paying more. The general index of bread purchase was the only factor influencing households' willingness to pay more for whole wheat-grain Sangak bread. Education level, knowledge of the benefits of whole wheat bread, gender, and the number of household members had a negative impact on households' willingness to pay for Sangak bread. Moreover, the marginal effects of the coefficients were estimated at different levels, indicating how changes in the independent variables (such as health index, general index of bread purchase, awareness of whole wheat bread, family income, education level, knowledge of the benefits of whole wheat bread, frequent consumption of whole wheat bread, number of household members, presence of elderly individuals in the family, and presence of a patient individual in the family) affected households' willingness to pay for whole wheat-grain bread.Conclusion According to the results, limitation in producing, supplying, and distributing the whole wheat-grain breads across the city, lack of easy access to whole wheat-grain stores, high prices, remote locations for purchases, and family awareness were the main and significant factors of using whole wheat-grain Lavash and Sangak breads among the Tabriz households. In this regard, the following policies were recommended: 1) Increasing the number of whole wheat-grain breads baking units and purchasing stores, 2) Group media can help to the acculturation and adaptation to the consumption of the whole grain bread, 3) Increasing awareness of whole wheat-grain bread benefits on health could be effective steps on the consumption of whole wheat-grain breads in Tabriz city.
Agricultural Economics
M. Ghahremanzadeh; M. Samadpour; J. Hosseinzad
Abstract
Trade liberalization of agricultural products and its effect on food prices, because of the importance of food in the household consumption basket, is one of the most important goals of governments for public access to health and food security. The present study investigated the effect of trade liberalization ...
Read More
Trade liberalization of agricultural products and its effect on food prices, because of the importance of food in the household consumption basket, is one of the most important goals of governments for public access to health and food security. The present study investigated the effect of trade liberalization on domestic food prices in Iran. In this context, the single-equation error correction model (SEECM) was applied using the required time series data during 1989-2019. The results show that in the short-term, only increases in global food prices, liquidity, and exchange rates significantly affect domestic food prices. However, domestic food prices show more reaction to exchange rate fluctuations than to world prices. The estimated long-run equilibrium relationship demonstrated that world food prices have a positive and trade liberalization has a negative effect on domestic food prices. In addition, in the long run, the effect of liquidity on the domestic food price of food is more than other factors. The estimated error-correction term indicates that in the long run, if a shock occurs to the domestic food price, the domestic market can adjust it by only 35% annually. Considering the fluctuations of global prices and exchange rates, and their impacts on domestic prices, it is necessary to pay attention to these fluctuations in revising trade policies.
Agricultural Economics
M. Ghahremanzadeh; F. Jafarzadeh; R. Fathi
Abstract
IntroductionFood security and food security are considered important development goals in all countries, so that reducing food insecurity is seen as an important political goal for all people. Accessing this goal can be achieved by increasing food supply, improving access to food, and increasing people's ...
Read More
IntroductionFood security and food security are considered important development goals in all countries, so that reducing food insecurity is seen as an important political goal for all people. Accessing this goal can be achieved by increasing food supply, improving access to food, and increasing people's purchasing power. But evaluating these programs is challenging. In this regard, the purpose of this study is to investigate food insecurity and determine the economic value of food in the country. For this purpose, the analysis of welfare economics proposed by Chavez (2017) has been used. Materials and MethodsThe data and information required in this study include household consumption expenditure for six major food groups: 1- bread and cereals, 2- meats, 3- dairy products, 4- fresh fruits, 5- oils and fats, and 6- fresh vegetables that have been used from the statistics of the raw income-household data questionnaire for 2018. In this study, household demand was estimated using the near-ideal Quadratic Almost Ideal Demand System (QUAIDS) and then the income, compensatory price (Hicks), and non-compensatory elasticities (Marshall) were calculated. Finally, the economic value of food (food benefit) was calculated for the six groups of food under three scenarios: 1- High food insecurity, 2- Moderate food insecurity, and 3- Food security. Results and DiscussionThe results of income elasticity calculations showed that the group of bread and cereals, dairy products, oils and fats, and vegetables are among the essential goods and the meat of luxury goods and fruits have the same elasticity According to the results of compensatory price elasticity (Hicks), all negative own-price elasticities are consistent with economic theory and show a negative relationship between the price of each commodity and the demand for that commodity. In all studied groups, own-elasticity is less than one price and therefore they are less elastic concerning their price. A comparison of the own-price elasticity of demand for the studied goods showed that the absolute value of own-price elasticity is higher for dairy products than other goods and less for meat than other goods. In other words, for a one percent increase in the price of dairy products, the demand for it decreases more than other goods. The amount of cross-price elasticity for all food groups in terms of absolute value is less than one. In other words, in most cases, consumers change the demand of another group less by changing the price of one group. After calculating price and cross-price elasticities, the economic value of food (food benefit) of each urban household was calculated in three scenarios: 1- high food insecurity, 2- moderate food insecurity, and 3- food security. The food benefit of each household in the high food insecurity scenario for the group, bread and cereals are 2903.7 (1000Rials), meat 5947.3 (1000Rials), dairy 5601.4 (1000Rials), fruit 5486.1 (1000Rials), oils and fats 1859.2 (1000Rials) and vegetables 2394.3 (1000Rials). In total, the economic value of food for an urban household with a high level of food insecurity is equal to 24192.0 (1000Rials). While for the food security scenario equal to 77046.8 (1000Rials) has been obtained. Conclusion A comparison of the economic value of the food groups studied in the moderate food insecurity scenario compared to the high food insecurity scenario indicates that the value of food under the second scenario is at least 1.6 times higher than the first scenario and the economic value of meat in the moderate food insecurity scenario has increased more than other food items and the economic value of oils and fats has increased less than other food items. Also, the economic value of selected food groups in the food security scenario compared to the high food insecurity scenario, indicates that bread and cereals are 3.18 times, meat 3.29 times, dairy products 3.22 times, fruit 3.16 times, Oils and fats are 2.94 times and vegetables are 3.11 times. In this case, the economic value of meat has increased more than other foods and the economic value of oils and fats has increased less than other foods. According to the results of food insecurity scenarios, it was observed that household income is the main factor in household food security and food benefit and has the greatest impact on it. Therefore, it is suggested that the goals of policies in the field of supporting low-income groups are to pave the way for increasing the income of this group.
S. Esmaili; M. Ghahremanzadeh; A. Mahmoudi; M. Mehrara; Gh.R. Yavari
Abstract
Introduction: Exchange rate and oil prices are the important factors for foreign trade in any country and even fluctuation in these variables will affect the economic and trade growth. The purpose of this study is to investigate the effect of exchange rate and oil price fluctuations on trade balance ...
Read More
Introduction: Exchange rate and oil prices are the important factors for foreign trade in any country and even fluctuation in these variables will affect the economic and trade growth. The purpose of this study is to investigate the effect of exchange rate and oil price fluctuations on trade balance of Iran's agriculture sector with its 8 major trading partner over the period 1998 to 2017 and examine also the existence of the J Curve in these countries. To this end, linear and nonlinear ARDL models were utilized based on literature and tried to determine lung-run and short run effect of underling variables. Then, the results of linear and non-linear ARDL models were compared.Materials and Methods Methodology: Since eight countries, including the United Arab Emirates (UAE), Iraq, Afghanistan, Turkey, Korea, India, Germany and China are Iran's largest trading partners during 1998-2017, we focused on these countries. In this context, the model proposed by Oskoee et al. (2011) has been used to evaluate the impact of exchange rate and oil price fluctuations on agriculture trade balance. To capture the exchange rate and oil price fluctuations, the GARCH family models were applied (including EGARCHT, GARCH, SAGARCH, and NGARCH). Time series of exchange rate and oil price fluctuations which are extracted from GARCH models, are expected to be stationary. So, according to the empirical studies, the ARDL model is an appropriate model. However, both linear and nonlinear ARDL models were estimated. To specify trade balance equation, variables including Iran's GDP, GDP of eight trading partner countries, exchange rate, Oil prices fluctuations, exchange rate fluctuations and economic sanctions have been used. We used the ADF unit root test to check stationary of the variables.Results and Discussion: The estimated results of the GARCH family models show that the sum of the coefficients of α+β for Turkey, Iraq, India, China, Afghanistan, Germany, and Korea are 0.88, 0.94, 1, 0.92, and 0.82, respectively. As the sum of the coefficients must be between 0 and 1, the predicted fluctuations series of exchange rate are stationary and also the predicted fluctuations series is as well. After obtaining fluctuations series of exchange rate and oil price, the number of optimal lags should be determined in ARDL model. According to the FPE criterion, the optimal lag is two and according to the AIC and SBC the optimal one is three. Since the number of observations is low, the optimal lag number was selected two and the Linear and non-linear ARDL model was estimated. The results revealed that if Iran's GDP increased by 1%, the trade balance between Iran and Turkey would improve by 18.20% and this value for Iraq, Afghanistan, UAE, China, Germany, Korea would be 59.07, 8.40, 26.28, 91.17, 16.32, 0.16, 22.02 respectively. In the long run, if Turkey's GDP rises 1%, the trade balance between Iran and Turkey will improve 14.34%. Moreover, if GDP in Iraq, Afghanistan, UAE, Chinese, German, Korean climb by 1%, the trade balance reaches 38.31, 7.003, 10.41, 17.99, 0.39 24.6 respectively. If the exchange rate rises 1% in Iraq and Germany, the trade balance will improve roughly 26.9, 69.4 respectively. Escalating National currency in Turkey and India has reverse effects on the trade balance. In fact, as the exchange rate rises, imports from Turkey and India increased and this contradiction may be due to sanctions and economic conditions. In China and India, positive and negative fluctuation has positive and negative effects on the trade balance. Indeed, by increasing the positive exchange rate fluctuations, the trade balance would improve and with the negative exchange rate fluctuations (the exchange rate decline) the trade balance might worsen. In the nonlinear ARDL method, exchange rate fluctuations in India and China are positive and have significant effect, and it shows that there is a j-curve between Iran and these countries. Also separating exchange rate fluctuations in positive and negative groups can prove the existence of the j Curve.Conclusion: According to the results, the highest value of agricultural exports is related to Iraq and the least is to Korea. The UAE has the highest imports from Iran and Iraq has the lowest one. The co-integration test reveals that the underlining variables follow and influence each other in the long run. Based on previous studies and predicted signs for coefficients of the variables in the models, the non-linear ARDL model provides better results. The finding showed that GDP of 8 countries were positive and had significant effects and Iran's GDP was negative and significant in these eight countries. In the long run, an oil price fluctuation in Turkey, Afghanistan, Germany and India has positive and significant impact. In fact, as oil prices increase, the agricultural trade balance improves. In the short run, as oil prices rise, the agricultural trade balance would decline in countries such as Turkey, Germany and India and increase in Iraq and China. By dividing the exchange rate fluctuations into positive and negative parts, we conclude that positive exchange rate fluctuations in China and India have a positive effect on the trade balance and negative fluctuations have a negative effect on the trade Balance. The current study confirmed the existence of the J curve in India and China.
E. Pishbahar; F. Sani; M. Ghahremanzadeh
Abstract
Introduction: Global warming is an important issue for all people in the world. Once greenhouse gases (GHGs) are generated, they accumulate in the atmosphere for a very long period. For this reason, the scope of their impact is not only limited to the present generation, but also will continue ...
Read More
Introduction: Global warming is an important issue for all people in the world. Once greenhouse gases (GHGs) are generated, they accumulate in the atmosphere for a very long period. For this reason, the scope of their impact is not only limited to the present generation, but also will continue to affect coming generations. Due to these long lasting effects, global warming must be dealt with seriously in order to achieve environmental and economic sustainability. Among the six dominant greenhouse gases (GHGs) mentioned by the UNFCCC, carbon dioxide emissions (CO2) are the main contributor to the bulk of accumulated GHG emissions and showing the highest growth rates over time. These national climate action plans, communicated by 189 participating countries to date, will not be sufficient to meet the level required to stay well below 2°C. In order to achieve the long term goals contained in the Agreement, governments will regularly set or update their emissions reductions targets. Hence, the international community has taken some measures to solve this problem it includes the Kyoto Protocol and the Paris Agreement.Materials and Methods: In this paper, we empirically investigate the impact of the Kyoto Protocol and Paris Agreement on CO2 emissions using a sample of 139 countries.To analyze the effect of the Kyoto Protocol on the emission of CO2, the period 2005-2012 are considered and in Paris agreement the years of 2014-2017 are included. We propose the use of a difference-in-difference (DiD) regression and a propensity score matching (PSM) methods to address the endogeneity of the policy variable, namely Kyoto and Paris commitments. Countries are matched according to observable characteristics to create a suitable counterfactual. We correspondingly estimated a panel data model for the whole sample and the matched sample and compared the results to those obtained using a Covariates variable. The model proposed to estimate the effects of the Kyoto Protocol on CO2 emissions includes GDP, Foreign direct investment (FDI), The proportion of urban population to total (UP), The share of value added in industry (AVI) as main drivers of emissions. A differences-in-difference estimator has been proposed, in which rather than evaluating the effect on the outcome variable, evaluating the effect on the change in the outcome variable before and after the intervention is done. Our inference in difference in difference method is based on the differences between committed and non-committed countries over two time periods: a pre-treatment period of 2014-2015 and a post-treatment year of 2016-2017.Results and Discussion: As the coefficient for facing future commitments from Kyoto protocol and Paris Agreement is statistically significant, we conclude that the Kyoto protocol and Paris agreement effect are due to pre-ratification differences in emissions. In Kyoto protocol the results of the difference in difference method indicate that countries that face emission commitments emit on average 1.89 percent less CO2 compared to the control group of countries, which face similar conditions in terms of GDP, FDI, and AVI and UP, but do not have to cut emissions. In propensity score matching result illustrate CO2 emissions has reduced by 1.76 percent. Similar to other studies estimating the Kyoto effect, we also obtain that ratifying Kyoto has a negative and significant effect on emissions. In particular, our results show that a country with emission commitments emits on average 1.8 percent less CO2 than a country without reduction commitments. The results of the difference in difference method indicate that countries with emission commitments from the Paris agreement has reduced on average about 1.21 percent less CO2 than similar countries that did not ratify the agreement and according to the PSM method, in the commitment countries in Paris agreement, it has dropped by 1.45 percent.Conclusion: According to the result, the impact of the Kyoto Protocol and the Paris Agreement based on two approaches are different, but it is obviously clear that these international agreements have been successful in reducing CO2 emissions. Yet, in order to stabilize global warming at 2 degrees Celsius, much more serious measures would have to be taken. Although emissions from the developed countries with reduction commitments have declined and some countries achieved their targets, the decline in emissions is unlikely to be enough to stabilize levels of GHGs in the atmosphere. The main policy recommendation derived from this study is that policy makers should actively work towards finding a way of extending the international agreement to a wider range of countries, including the so-called new industrialized nations, which indeed should be renamed ‘already’ industrialized countries.
E. Pishbahar; Sh. Bagherpour; M. Ghahremanzadeh
Abstract
Introduction: Poverty is prevalent in majority of the world's nations. If a country is not on the path of eliminating or reducing poverty, it will not be on the path of growth and development. Undoubtedly, the first step in planning of anti-poverty and reducing inequality for development of society is ...
Read More
Introduction: Poverty is prevalent in majority of the world's nations. If a country is not on the path of eliminating or reducing poverty, it will not be on the path of growth and development. Undoubtedly, the first step in planning of anti-poverty and reducing inequality for development of society is a good recognizing of poor people and poverty situations. To do so, it is necessary to define and use poverty indicators for measuring poverty, which can reveal the different aspects of poverty. Indeed, more precisely identifying the number and grade of households below the poverty line in different locations can help policymakers toward better planning. According to the statistics provided by the Statistical Centre of Iran, in recent years, due to the low level of income of villagers, it has been emphasized more on poverty issue in the rural sector than the urban sector, and the size and severity of poverty in rural areas have been more tangible. Income inequalities (using the Gini coefficient) have always been higher in rural areas than in urban areas. So in this regard, the main purpose of this study is to "survey the rural poverty indices and its affecting factors in rural areas of Iran".Materials and Methods: One of the most important concerns of governments is awareness of poverty and inequality in society to take action to improve the status of poverty and distribution of income. In this regard, it is important to determine the poverty line and poverty measurement indicators. In this study, poverty indicators were categorized into two categories of "Classical indicators", including "Head Quant Ratio", "Poverty Gap index", "Income Gap Ratio", "Kakwani Index", "Kakwani - Sen index", "Sen Index" and "Modern indicators", including "Gini coefficient index", "Atkinson index", "Araar Index", "DER Index", "Foster - Wolfon index", and "Steban Grading Ray Index". It should be noted that the classification of indices is done to simplify the subject, although the basis of this classification is the observance of the two "monotonicity axiom" and "transfer axiom" by the indexes, that is, the use or absence of polarization in the distribution of income (and inequality). The polarization distribution of a variable is the degree of distribution be distributed around a polar group. Many papers and studies have examined the difference between indices of inequality and polarized indicators and concluded that, in general, phenomena such as "middle class disappeared" or "boundary grouping" cannot be estimated by indices of inequality such as "Gini coefficient index". These topics require more robust and complete indicators that can also analyze the polarity of the data.Results and Discussion: the aim of this research is examining the situation of poverty and distribution of income “inequality”. Indicators of poverty measurement include modern and classical indicators then the impact of some macroeconomics variables on poverty has been investigated using data of income plan for households in rural areas in years 1987-2016, with Stata software and DASP package calculating classical indicators which includes: "Head Quant Ratio", "Poverty Gap", "Income Gap Ratio", "Kakwan index", "Severity Poverty of Sen", "Sen Poverty index" and modern indicators which includes: "Gini index", "Atkinson index", "Arrar index", "DER index", "Foster - Wolfson index, "Steban Gradin Ray index. In order to investigate the factors affecting poverty, firstly, between two linear and logarithmic functional forms, logarithmic forms are used as the appropriate form for running regression. In addition, White's powerful variance has been used to solve the heterogeneity variance problem. The results of regression estimation for factors affecting poverty indicators show that economic growth, fertility rate, unemployment, household size, time trend, rural population, agricultural producer price index, net capital agriculture and agricultural value added affect all six modern indicators of poverty.Conclusion: The result of indicators using income plan data for households in rural areas for years 1987-2016, with Stata 14.0 software and DASP 3.0 package shows that poverty increased in years 1987-1992 and 2012-2016 but decreased in 1993 till 2011. Reducing unemployment, controlling inflation and controlling the growth rate of rural populations are important factors affecting poverty. Increasing agricultural producers' prices will improve rural incomes and improve poverty, as well as increase in agricultural investment and increase in agricultural value added, which can have a major impact on rural welfare and poverty. It is also recommended that supportive policies based on spatial and regional differences should be developed and applied based on the difference in income deciles.
F. Vajdi Hokmabad; M. Ghahremanzadeh; J. Hosseinzad
Abstract
Introduction: over the previous years, with development and expansion of broiler breeding units and its increasing production, chicken meat has become an essential commodity in the household food basket and has been attributed as one of the most important sources of protein supply for households. Recently, ...
Read More
Introduction: over the previous years, with development and expansion of broiler breeding units and its increasing production, chicken meat has become an essential commodity in the household food basket and has been attributed as one of the most important sources of protein supply for households. Recently, the chicken market pricing as well as exchange rate volatility has become one of the issues in that industry. One of the main sources of this risk in the chicken market is the exchange rate volatility, which affects the imported inputs markets.
Materials and Methods: The current analysis is based on 21 years of monthly data on exchange rate, chicken price, corn price, soybean meal price and fish powder price over the period 1995-2016 obtained from the Central Bank of the Islamic Republic of IRAN and Livestock Support Company of Iran. In present study, the risk of overflow between the exchange market and the chicken market and its major import inflows are examined. Estimation has been carried out using GARCH-type models, based on the multi variation GARCH (MV-GARCH), for both the extreme downside and upside Value-at-Risks (VaR) of exchange rate volatility risk and chicken market and its major inputs markets. It depicts market risk by means of the probability distribution of a random variable and evaluates the risk with a single real number. While the VaR method is used to measure extreme market risk, as the risk interaction and spillover effect among different markets is apparent. Furthermore, according to a new concept of Granger causality in risk, a kernel-based test is proposed to detect extreme risk spillover effect between two mentioned markets. The methodology used is Granger causality in risk provided by Hong (2001) and Hong et al. (2003). It requires that the time-varying VaR to be evaluated for each return, and then it should be determined if the historical information about risk in one market increases one's ability to forecast its occurrence in another market in terms of Granger causality concept.
Results and Discussion: According to the results of the Dickey-Fuller unit root test, all variables are stationary at first difference, and based on the results of the seasonal unit root test, seasonal behavior pattern in variables has been found. Then volatility clustering was confirmed by testing heterogeneity of conditional variance. Since the results showed cluster fluctuations in the variables, we evaluated the MGARCH and TGARCH models and then we used VaR to estimate the value series at risk for all variables. The result of VaR section showed that the upside risk of chicken and Fish powder is the highest, and soybean meal and exchange rate having the least risk. In the downside risk chicken and fish powder were known as the most risky markets, corn and exchange rate as least risky. But it is fascinating about the exchange rate that it has a higher upside risk than the downside risk. In other words, there is a greater risk for an increase in the exchange rate market. Finally, the relationship between risks of markets was investigated using risk granger causation. The results indicated that there are over and over additional risks for traders in all of these markets and there is a significant risk spillover between the exchange market and the chicken market and its major inputs markets, the severity of upside spillover is higher than the falling price of the exchange rate. There is a significant risk spillover between the chicken market and its major inputs market at the 95% and 99% confidence levels and in all interruptions, there is a spillover of upside and downside risk.
Conclusions: The exchange rate as a key variable, influences many of the government's policies and economic decisions. Any volatility in the exchange rate will have an adverse impact on both micro and macro levels. Given its impact on the imported input market, it is recommended that a coherent program of foreign exchange market management and stabilization to be developed by the central bank and the government. taking into account the high impression of the input market from volatility and exchange rate risk, it is suggested that, as far as the principle of comparative advantage allows, more strategic inputs such as corn and soybeans to be produced. Considering impressionability of Chicken markets from its inputs market in order to provide consumer welfare and prevent the imposition of additional costs, it is recommended a duplicate effort to be made to implement the policies of market regulation of inputs and reduce volatility in these markets.
M. Jafari Sani; B. Hayati; J. Nematian; M. Ghahremanzadeh
Abstract
Introduction: Qaleh Chay dam basin is one of the largest irrigation regions for food production in Ajabshir and household livelihood mostly depends on agriculture but the occurrence of drought periods and extraction of underground water has led to a reduction in surface water and underground aquifers. ...
Read More
Introduction: Qaleh Chay dam basin is one of the largest irrigation regions for food production in Ajabshir and household livelihood mostly depends on agriculture but the occurrence of drought periods and extraction of underground water has led to a reduction in surface water and underground aquifers. Continuing this process will reduce the agricultural production and consequently the region will encounter economic crisis. On the other hand, the uncertainties of various factors such as rainfall and temperature, which are not easily quantified, would affect agricultural resource system. in current study in order to response to mentioned crisis and uncertainties, interval two-stage stochastic programming (ITSP) has been proposed for water allocation of Ajbashir Qaleh chay dam among agricultural products and the results have been compared with extended ITSP.
Materials and Methods: Interval two-stage stochastic programming (ITSP) is an effective alternative to deal with uncertainties and it can be formulated as follows:
Subject to:
(water availability constraint)
(water allocation goal constraint)
(non- negativity and technical constraint)
where = system benefit; = net benefit to crop per m3 of water allocated; = promised target of water allocation quantity for crop ; = deficit to crop per m3 of water not delivered; = water deficit to crop when the flow is ; = the total amount of flow that take values with probabilities ; = water loss rate in transport process; = the maximum allowable allocation for crop ; = the total amount of crops; = type of crop. Extended ITSP is an effective alternative to cope with water scarcity. The model can be formulated as follows:
Subject to:
Where = cost of increasing 1 m3 water for crop while using alternative ; = total number of alternatives; = available amount of water for crop while using alternative ; is a binary decision variable that takes 1 if crop when using alternative and the seasonal flow is .
Results and Discussion: The data for the selected products (wheat, barley, potato, onion, grape, walnut, almond and apple) were collected from Regional Water Authority and Agriculture Jihad Organization of East Azarbaijan in 2015-16, and in some cases, completed by a questionnaire. The model was written in the GAMS package. Results of ITSP showed that under the low flow level, the total amount of water allocated to all crops would be zero with the exception of almonds where the final allocation of water for it would be [3.64, 20.61]. therefor,Under the medium flow level, the allocation of water for potato, onions, walnuts, almonds and apples would be[0, 5.49], [0, 28.57], [1.30, 35.71], 31.43 and 20 ×1000 m3 respectively and it would be zero for others. Finally under high flow level there would be no water shortage for all products. Water shortages may occur when the seasonal water flows do not be adequate for the promised water allocation for each crop. In such cases users will have to utilize supplementary resources. The results of extended ITSP showed that for wheat, barley, onion, grape and almond the third alternative under low level and the first one under medium flow level can be used. For potato and apple under low level the first alternative and under medium flow level the third one can be applied. Both the first and the third alternative could be utilized for walnut if the flow level was low. Finally, comparing the value of the objective function of ITSP and extended ITSP showed that with the utilization of supplementary resources for satisfying the water needs, the net profit of the system decreases slightly.
Conclusion: In this paper, ITSP method was used to allocate water to agriculture products. The results showed that there was water scarcity for products on drought and normal years. Users can utilize supplementary resources to cope with water scarcity. An extended ITSP method is based on retrieving water shortage and its results revealed that the system net benefit decreases as supplementary water reservoirs were used for water shortages. Based on the results obtained, highlighting the irrigation efficiency is recommended.
M. Ghahremanzadeh; S. Khalili Malakshah; E. Pishbahar
Abstract
Introduction: Due to dependence of households to agriculture in terms of income and consumption, study the effects of trade liberalization in this sector is necessary in developing countries. Trade liberalization policies have different results in various countries because of the factors that influence ...
Read More
Introduction: Due to dependence of households to agriculture in terms of income and consumption, study the effects of trade liberalization in this sector is necessary in developing countries. Trade liberalization policies have different results in various countries because of the factors that influence price transmission from world markets to domestic market. In other words, the extent of tariff pass-through is different in this country. Tariff pass-through determines how much tariff changes pass-through to domestic prices, therefore study the extent of tariff pass-through to prices is important. The aim of this study is determine the extent of tariff pass-through to agricultural products prices considering the heterogeneity in urban and rural area during 1384-93. For this purpose, major agricultural products in the household basket, aggregated in six groups and extent of tariff pass-through to prices of these groups, were estimated by making pseudo panel data and using Nikita (2004, 2009) tariff pass-through model. The reason to use pseudo panel data is that time series of household surveys data does not exist. Deaton (1985) states that it is possible to construct pseudo-panel data by using repeated of cross-sectional data (with individuals completely different from one to another) and obtain estimators similar to panel data. In this method, each cohort will be created using individuals who share some common characteristics. Then, observations are constructed from average of each cohort. Study the extent of tariff pass-through to agricultural prices is important because Iran has not experienced a broad liberalization and did not joined WTO; also for low income and developing countries such as Iran local markets may be exposed to high transfer costs and often poor integration into the international economy. So the regional aspects of tariff pass-through is important. The results of this study represents the ability or defect of regional markets in global prices pass-through to local prices and this will be a guidance for policymakers to reform the structure of local markets before joining WTO.
Materials and Methods: Tariff pass-through theory is based on exchange pass-through literature that examines the changes in price of imported goods due to changes in exchange rate. Tariff path-through model determines how much of observed changes in prices during the study can be directly attributed to tariff changes policy. To calculate the effect of tariff changes on prices we used Nikita (2004, 2009). He expresses that change in domestic prices of imported goods is determined by tariff change multiplied imported goods prices and adjusted by changes in exporter markup. Since the development of domestic markets is important, this model use trade costs to calculate the extent to which local markets are receptive to movements in border prices.
Results and Discussion: The results indicated an incomplete tariff pass-through for different groups of agricultural products. Tariff Change have different effects on prices of agricultural products in urban and rural areas. As in urban areas tariff pass- through to prices are in range of 0 and 17 percent and in rural areas are in range of 0 and 26 percent. This level of tariff pass-through is slightly smaller than what has been stated in the literature. For example Nikita (2009) has gained tariff pass-through to agricultural prices almost 33%. Cherkaoui et al (2011) has gained results about 13% and Marchand (2012) result show that tariff pass-through to agricultural prices are between 64 to 68 percent in urban areas and in range 33 to 49 percent in rural area. However, results of this study are not unexpected since the extend of tariff pass-through in developing countries such as Iran with limited infrastructure and incomplete markets, can be lower.
Conclusions: The main important result of this study is that any change in trade policy can not completely pass-through to consumers. Factors such as noncompetitive markets, defect in markets and infrastructures may keep households away from positive effects of tariff changes in urban and rural. Our results are also consistent with Marsh (18) that expresses since the self-consumption tariff path-through to prices is lower in rural areas, in some rural areas, producers and consumers may be completely separated from economy. Therefore, as can be seen in this study clearly price changes in border has not affected the local prices. It is necessary for policymakers to consider factors such as market prices transmission mechanism and infrastructure conditions in trade policies.
E. Pishbahar; P. Pakrooh; M. Ghahremanzadeh
Abstract
Introduction: Thepoultry industry, as sub-sectors of the agricultural sector,isone of the economic activities as considered risky and play a significant role in the public life of our community. The poultry industryin Iran has a bilateral relationship with global markets because on the one hand is exporters ...
Read More
Introduction: Thepoultry industry, as sub-sectors of the agricultural sector,isone of the economic activities as considered risky and play a significant role in the public life of our community. The poultry industryin Iran has a bilateral relationship with global markets because on the one hand is exporters of agriculture production and on the other hand is a major importer of inputs such a cornandsoybean. So in terms of high transactions volume, poultry industriesare influenced by international prices and volatilities. Crude oil is one of the most important commodities in the global economyand in Iran has a comparative advantage that is seen as a strategic resource. A significant portion of Iran's revenue is from oil exports account and crude oil price. Therefore, oil prices in the world is an important factor that affecting the ability of our import volume. Recent observations show that the volatility and uncertainty in oil prices are transmitted through exchange rate (USD America) to real economic markets, other markets, the exchanges and the domestic agricultural and food products markets. This articleseems clearly impressive after Iraq-USA war in 2002 and the Global Financial Crisis in 2005. So in this paper, we try to analysis correlation between oil prices, exchange rates and the price of poultry inputs for the two periods, before the Global Financial Crisis and Iraq-USA war (1995-2004) and after that (2005-2014).
Material and Method: Theperiods ofstudy are pre and after the Iraq-USA war and the Global Financial Crisis. Our monthly data collected from the Central Bank of Iran, Animal Support Company since 1995 to 2014. For the purpose of this paper, we used Vine Copula-MGARCH approaches. Before everything at first, we controlled the stationary and seasonal unitroots behavior in data with ADF,KPSS and HEGY stationary and seasonal tests.After that for analysis the correlation of prices, we used MGARCH models for modeling volatilities and collecting the residual of equations. Because of the limitation in linear correlation coefficients and the advantages of copulas for modeling and analysis correlation, we used copula approaches for this sector. At first, we modeledvolatilities with kind of MGARCH models such as CCC and DCC GARCHes and after that for collection pure residuals we must eliminate the past effect of each variable or in other means we can tell, using ARMA with MGARCHmodel can give us residuals that have not any effect of past behaviors in variables.
Results and Discussion: The results of the ADF unit-root test has indicatedthat all variables are not stationary and accumulated from the first stages. Similarly, the KPSS unit root test has shownsuch as ADF test results. Based on these tests our variables are not stationary and in two periods of study and the first stage of a difference,they are accumulated. Seasonal unit root test or "HEGY test" results also showed there arenot seasonal behaviors in two periods of variables. After these tests for modeling volatilities at first, we needed to detect ARCH behaviors in variables. Because of that, we controlled ARCH effect behaviors in variables and for this aim, we use an ARCH-LM test. Detecting ARCH behaviors help us to use the kind of MGARCH models for modeling volatilities. Our results indicate that CCC and DCC models with ARMA model have flexibility for modeling. So after that examination, we have collected the residuals of equations and collected the residuals of each equationin ARIMA-CCC-MGARCH model. We calculated the correlation of oil price, exchange rate and input prices with kind of Vine-Copulas. Results of R-Vine, C-Vine and D-Vine models indicated that the correlation between oil price and exchange rate are different in two periods, as the positive correlation of oil and exchange rate, in the first period, change to a negative correlation in the second periods. Correlation of oil price and input pricesin second time are more than beforethe crisis. Clarke and Voung tests for choosing Vine models indicate that R-Vine models for after and before period are the best.
Conclusions: Based on R-Vine models our results indicated that correlation between oil price and input prices are more than before the crisis and this is not a suitable situation for Iran's industries. At last, we offer that, using oil incomes forincreased infrastructures of input productions it may be better than importing inputs.
T. Aref Eshghi; M. Ghahremanzadeh; H. Raheli; Gh. Dashti
Abstract
Introduction risk is as an uncertainty that has effects on individual’s welfare, which is often related to the adversities and loss and is defined as the probability of adversity or loss too. Activity in the agriculture sector is different from the other sectors because the producers' incomes are affected ...
Read More
Introduction risk is as an uncertainty that has effects on individual’s welfare, which is often related to the adversities and loss and is defined as the probability of adversity or loss too. Activity in the agriculture sector is different from the other sectors because the producers' incomes are affected by a lot of risks. Agricultural insurance is mentioned always as a good strategy for the risk management of the agricultural sector. In designing and rating a crop insurance contract, the modeling of yield risk is fully analogous to modeling the probability of distribution for the crop yield and significantly depends on the distribution function, thus in appropriate designing of agricultural insurance contracts, the accurate modeling of the crop yield distribution is vital.
Materials and Methods There are three approaches for modeling yield distributions, parametric, non-parametric and semi-parametric methods which parametric and nonparametric approaches are more conventional. In many cases, crop yields show increasing trends over time because of technological change which deviation from this pattern (the error term) is often causes variance heterogeneity and reject the assumption that the yields are independently distributed. Thus A common approach to yield risk modeling is detrending the data and using detrended series for modeling yield risk. This approach is often called a two-step approach. The candidate parameterizations includes beta as the parametric and kernel as the nonparametric distribution. The area under the density to the left of the guaranteed yield presents the probability of loss thus the integral of the curve between zero and the insurer yield guaranteed should be calculated as the probability of loss. The Integral under the kernel density to present the probabilities of loss was numerically estimated using a trapezoid rule. Now the yield insurance is running traditionally by the Agricultural Insurance Fund and is faced with problems of mismatch in received insurance premiums and payment indemnities. Therefore, consideration to diversification of insurance products and using the accurate and conventional methods to calculate the probability of losses and premiums in order to improve the current situation is very important. This study attempts to calculate the probability of loss using the parametric and nonparametric approaches for the area yield crop insurance contract and employs historical county-level yield data for irrigated and dry wheat and barley during the years of 1975 to 2013 for Ahar and Hashtrood counties in East Azarbaijan province published by Agriculture-Jihad Organization.
Results and Discussion The descriptive statistics for the detrended yields for all counties and crops indicates that the yields exhibit negative skewness in more than 63 percent of the cases. Negative skewness suggests fatter right-hand-side tails with yields close to the maximum yield observed more frequently than very low yields. We calculate the probability of loss in different coverage levels (65%, 70%, 75%, 80%, 85% and 90%) and the results indicate that the ranges of their variations are different. The results show that the values of probability of loss in parametric approach (beta distribution) are higher than nonparametric approach (kernel distribution). To compare the parametric and nonparametric distributions, the CDF plots of the kernel, beta and empirical distribution are evaluated and the results showed that the kernel distribution fit the sample data very well and fits the data better than beta CDF. Moreover the results show that except for some coverage levels of dry wheat, in all the cases, the values of probability of loss are higher in rain fed crops than irrigated crops. The results also show that the probability of loss in Hashtrood County is more than Ahar County, indicating that the crop yield risk in Hashtrood County is more than Ahar County, thus the probability of indemnity payments will increase and the higher premiums will be needed for this county.
Conclusions In general, the results indicate that the values of the probability of loss obtained from two approaches are significantly different from each other and the nonparametric approach results are more accurate. Therefore, it is recommended that in estimating the premium rates and yield risk calculation, the characteristics of distribution functions to be considered and the appropriate approach to be selected. Due to the results that show the probability of loss in Hashtrood County is more than Ahar County, it is recommended that in determining the premiums, the smaller divisions than province to be considered to organize the homogeneous risk groups. Moreover since the availability of different coverage levels provide better choice power for producer to manage their farm risks, it is recommended that the premium rates which due to the different probability of loss in different coverage levels are different, present in the variable coverage levels to the insurers.
Gh. Dashti; Kh. Alefi; M. Ghahremanzadeh
Abstract
Introduction: The increasing global consensus built on empirical evidence, expresses that the world, is facing a threat from climate change. As a result, this can affect the agricultural sector through its productivity changes and so influence food security in the world. This can be more intuitive for ...
Read More
Introduction: The increasing global consensus built on empirical evidence, expresses that the world, is facing a threat from climate change. As a result, this can affect the agricultural sector through its productivity changes and so influence food security in the world. This can be more intuitive for countries that are dependent on agriculture. Agriculture is an important sector in Iran that provides 12 percent of gross domestic production (GDP) and 21.2 percent of employment. In this country, annual crops as an important agricultural production have 12.2 million hectare cultivation areas. They are grouped into vegetables, cereals, beans, industrials crops, forage crops and cucurbits. The shares of planted aria for these groups vary in different country's regions due to cultivation conditions differences including climatic variables. This indicates the importance of studying the climatic variable effects on these shares. Therefore, this study is aimed to assess the effect of climatic variables such as temperature, participation, humidity and wind speed on land allocation between annual crop groups in Iran's counties. This can provide useful information about the effects of climatic variable on crop shares. To achieve the purpose, using statistical methods and specifically the fractional multinomial logit model is considered. This study is benefited from advantages such as using of fractional multinomial logit model, comprehensiveness and choosing the whole country as a case study and the specific crops grouping way that distinguishes it's from the other related studies in the country.
Materials and Methods: Because the shares (fractions) of annual crop cultivation area for each county(observation) are limited values that vary between 0 and 1 and the sum of them is one, using of fractional models, is considered. In these models the dependant variables vary between 0 and 1, and each observation has several fractions that their summation is one. Papke and Wooldridge (1996) introduced the fractional logit and probit models that have a tow fraction for each observation. After them, Sivakumar & Bhat (2002) introduced the multinomial fractional logit model that can include more than two fractions for each observation. These models use quasi-likelihood methods for estimation of parameters and their standard errors. For estimation of the fractional multinomial logit model, this study uses Iran's 336 counties agricultural and weather information. Annual agricultural crops information is taken from the agricultural ministry and weather information is taken from the national meteorology organization. In this regard, the crops planted area shares and weather information in 1391 are used to explain the shares of annual crops planted area shares in 1392.
Results and Discussion: Since the weather information was on monthly scale, estimation of different models with annual crop shares variables and annualy and seasonally, Weather variables (their average, standard errors and coefficient of variation) was considered for choosing the best model based on Akaike information criterion and Bayesian information criterion. Comparing the models showed that the model with annual weather variables averages is the best. So in the next step, using the model, the marginal effects were estimated. According to the result, increasing temperature has created concerns in all fields, including the agricultural sector, affects cereals and beans productions as two important sources of food in the world. It increases the planted area share of cereals and decreases the cultivation area share of beans. The participation affects all groups' cultivation area shares except cucurbits. That is the effect of cereals planted area and its share is stronger, one centigrade degree increasing of temperature increase the share of cereals cultivation area 0.02 percent. Humidity percent influences vegetables and industrial crops planted area shares and increase them. Wind speed respectively decreases and increases industrial crops and cereals cultivation area shares. According to the results also, conventional farming patterns and other agricultural system’s rules such as crop rotation in each area has important effects on the farmers' decisions on land allocations.
Conclusion: Based on the above results we can conclude that along with the climate changing, the annuals crops cultivation area shares and thus the amount of their production will be affected in the future. This shows the importance of using accurate methods to predict the possible values of climate variables in country's regions under different scenarios for next years. Because in this way, we can predict potential changes in the future annual crops productions and compare potential production and population food needs. This can determine the gaps between potential production and potential consumption in the future. In this regard, decreasing of agricultural sector problems in the face of climate change in the next decades would be possible by providing appropriate policies and procedures. One appropriate procedure is producing of resistant varieties of climate change results such as rising temperatures. This can define as one of the objectives of agricultural research centers. Considering that this research has studied the land allocation between annual crops, it is suggested to researchers that consider studying of other agriculture's sectors productions such as livestock and Fruit in the next research.
M. Ghahremanzadeh; Gh. Dashti; Z. Rasouli Birami
Abstract
Introduction: The relationship between different market levels is an essential issue in economy. Understanding of linkages between different market levels will help to assess the potential impact of agricultural policies. Given the importance of the vertical market relationship, the present study examines ...
Read More
Introduction: The relationship between different market levels is an essential issue in economy. Understanding of linkages between different market levels will help to assess the potential impact of agricultural policies. Given the importance of the vertical market relationship, the present study examines price volatility spillover in vertical market levels of Iranian livestock and poultry market prices. For this, we use monthly returns series of broiler feed, chicken, broiler (as substitutes for broiler vertical market levels), hay, sheep, mutton (as substitutes for mutton vertical market levels), hay, calf and beef (as substitutes for beef vertical market levels) during the period of April 1997 to March 2014. Another important aspect that is considered in this study is the volatility regime switching. Many variables undergo events that seem their time series’ behavior has changed quite dramatically. Such structural breaks are mainly observed in the economic and financial time series data. The regime switching must not be totally considered as a predictable and deterministic event. As if the process has changed in the past, it could obviously change in the future too. Therefore, it should be considered as a random variable and hence a full-time series model will include probabilistic inference about switching from one regime to another regime. Hence, by doing a present study, we will be able to answer the questions such as: whether a significant regime change happened in livestock and poultry vertical market levels? Is there any significant volatility spillover in vertical market levels? Is there any difference between the volatility spillovers in high and low volatility regimes? To what extent the price volatility spills over the vertical markets?
Materials and Methods: A multivariate Markov switching model, that is best for our study aims, has been introduced by Haas and Mittnik (2008) to the volatility spillover literature which is a generalization of Haas et al. (2004) univariate model. In fact, it is a multi-regime version of Bollerslev et al. (1988) VECH model. Regime depended on variance matrices are defined by equation below:
Aij, i = 0, …, q, and Bij, i = 1, …, p, are parameter matrices. Index j is determining the volatility regime. This model does not directly estimable and to ensure positive definite covariance matrices some limitation should be imposed. For this purpose, Haas and Mittnik (2008) used Engle and Kroner (1995) proposed approach as:
Where are lower triangular matrices and Aij* and Bij* are M M parameter matrices that must be estimated (Hess and Mittnik, 2008). The Aij* elements are the coefficients that explain the effect of volatility shocks or news and the Bij* elements are the coefficients that explain the effect of past volatilities on the current volatility of prices.
Results and Discussion: The results indicate the existence of two volatility regimes in vertical market levels of all three studied markets and also successive switches of volatility regimes, especially for meat (mutton and beef) market. According to evidence obtained in this study, although the durability of low volatility regime is lower than the high volatility regime in all cases and unconditional probability of staying in the high volatility regime is lower, but still the number of months and the length of periods in the high volatility regime are not in acceptable ranges. Based on the results, different shock and volatility spillovers between the different levels of the three markets have been occurring in both regimes; although the spillovers in high volatility regimes were more severe.
Conclusion: Price spikes like those we have witnessed for Iranian poultry and livestock products in recent years are not just part of a trend of higher prices. They are also part of a different phenomenon, price volatility, as its presence can be proved from our findings of broiler feed, chicken, broiler, hay, calf, sheep, beef and mutton – a combination of the abnormal unpredictability of prices and of unusually large variations, particularly upward. Although our findings differ in the magnitude of price volatility in each studied market, we agree that livestock market is more volatile than the poultry market and that volatility will persist in the coming years as past. While higher food prices can be an opportunity for farmers, price volatility hurts both consumers and producers. This extreme range of price volatilities hurts net food consumers and makes their welfare to change time to time. Moreover, the unpredictability of prices inhibits planning, makes investment risky and discourages farmers from producing more for the market. This represents a lost opportunity for farmers to raise their incomes, and for the country to develop the potential of programs to contribute to food security.
Z. Rasouli Birami; M. Ghahremanzadeh; Gh. Dashti; R. Mohammad Rezaie
Abstract
Introduction: Over the past few years, the price volatility of agricultural products and food markets has attracted attention of many researchers and policy makers. This growing attention was started from the food price crisis in 2007 and 2008 when major agricultural products faced accelerated price ...
Read More
Introduction: Over the past few years, the price volatility of agricultural products and food markets has attracted attention of many researchers and policy makers. This growing attention was started from the food price crisis in 2007 and 2008 when major agricultural products faced accelerated price increases and then rapidly decreased. This paper focused on the price volatility of major commodities related to three market levels of Iran’s meat market, including hay (the input level), calf and sheep (the wholesale level) and beef and mutton (the retail level). In particular, efforts will made to find more appropriate models for explaining the behavior of volatility of the return series and to identify which return series are more volatile. The effects of good and bad news on the volatility of prices in each return series will also be studied.
Materials and Methods: Different GARCH type models have been considered the best for modeling volatility of return series. Nonlinear GARCH models were introduced to capture the effect of good and bad news separately. The paper uses some GARCH type models including GARCH, Exponential GARCH (EGARCH), GJR-GARCH, Threshold GARCH (TGARCH), Simple Asymmetric GARCH (SAGARCH), Power GARCH (PGARCH), Non-linear GARCH (NGARCH), Asymmetric Power GARCH (APGARCH) and Non-linear Power GARCH (NPGARCH) to model the volatility of hay, calf, sheep, beef and mutton return series. The data on hay, calf, sheep, and beef and mutton monthly prices are published by Iran’s livestock support firm. The paper uses monthly data over the sample period of the May 1992 to the March 2014.
Results and Discussion: Descriptive statistics of the studied return series show evidence of skewness and kurtosis. The results here show that all the series has fat tails. The significant p-values for the Ljung-Box Q-statistics mean that the auto-correlation exists in the squared residuals. The presence of unit roots in the return series is confirmed by the results of the ADF and PP unit root tests. Different GARCH type models mentioned in materials and method were fitted to the return series and then have been compared based on 7 loss functions MSE_2, MSE_1, PSE, QLIKE, R2LOG, MAD_2, MAD_1, two information criteria AIC and BIC and log likelihood. The selected models for modeling the behavior of volatility in the hay, calf, sheep, beef and mutton return series are SAGARCH (1,1) with a t distribution, NGARCH (1,1), TGARCH (1,1), SAGARCH (1,1) and EGARCH (1,1) all with Gaussian distribution. The coefficient of asymmetry (γ) in all models shows signs of asymmetric behavior in volatilities so that for all of the return series except hay returns positive shocks have more effect on volatility relative than negative shocks of the same size. This evidence is vice versa for the hay return, in which negative shocks have more effect on volatility. The (α + β) in all models are greater than 0.7 which means the high persistence of shocks to volatilities. In other words, shocks might die out very gradually. This feature is more pronounced in the case of beef and calf return series with α + β greater than 0.9. Sensitivity of the current volatility to the new shock or news, α, in calf (0.76) and beef (0.71) returns are greater than that of others. The low sensitivity to the news is related to the sheep returns (0.16). The effect of current conditional variance for the next month conditional variance, β, in sheep (0.55) and mutton (0.42) returns are relatively high. Minimal β (0.14) is related to the calf returns.
Conclusion: The paper attempts to study persist shocks to volatility as well as how positive (good) or negative (bad) shocks (news) may have an asymmetric effect on the volatility of a return series of hay, calf, sheep, beef and mutton prices in Iran. The findings show signs of asymmetry and persistence in volatilities. The sensitivities of price were also, volatility to the news in the calf and beef markets is greater than other return series. By the way, the effect of current conditional variance of the next month conditional variance in sheep and mutton returns is greater than others. This finding indicates that when new shocks occurs in the meat market calf and beef returns are more influenced by them and sheep and mutton returns highly transmit the current volatility in the future. This suggests less political tensions in the country as much as possible to calm the economic and political space.
M. Ghahremanzadeh; F. Faryadi Shahgoli; Gh. Dashti
Abstract
Introduction: Regarding to the ever-increasing consumption of egg and consequently enhancement of its production during recent years, consideration to this output's market integration has special importance. Considering the fact that information on market integration may provide specific evidence as ...
Read More
Introduction: Regarding to the ever-increasing consumption of egg and consequently enhancement of its production during recent years, consideration to this output's market integration has special importance. Considering the fact that information on market integration may provide specific evidence as to the competitiveness of market, the effectiveness of arbitrage and the efficiency of pricing could be, likewise, useful to guide subsequent interventions aimed at improving the performance of market. In this context, in present study, validity of Law of One Price (LOP) will be tested in the egg market and among selected provinces.
Materials and Methods: Nonlinearity naturally extracted from local market due to existence of transportation and other transaction costs, so common cointegration test results are not suitable for market integration. In this study, at first, for being sure that series follow nonlinear behavior, Luukkonen et al. (1988) and BDS nonlinearity tests were used. Then for testing Law of One price in the egg market, nonlinear unit root test proposed by Emmanouilides and Fousekis (2012), which is an auxiliary regression for ESTAR model, was used. The data are daily retail prices of egg with the sample period ranging from April 2006 to march 2014 for north-west provinces of Iran including West Azerbaijan, East Azerbaijan, Ardebil, Tehran and Zanjan, which were obtained from State Live Stock Affairs Logistics Incorporated Company.
Results and Discussion: Based on the DF-GLS unit root test, the null hypothesis of unit root for egg price differentials was rejected. So, all series of price differentials are stationary. In the next step nonlinearity of price differentials of egg between two provinces was examined. In BDS test, at the beginning, an ARMA model was estimated then the test was carried out to the residual of estimated model with embedding dimension (m) 2-8 and the dimensional distance (ε) chosen equals to 0.5 and 2 times of standard deviation of the data. Based on the results from this test and Luukkonen et al. (1988) test, null of linearity was rejected and existent of nonlinear relation between series was confirmed. Then, existence of a unit root in price differential series was carried out by nonlinear method. The results showed that mentioned markets are well integrated and LOP holds in all market pairs in a way that strong version of LOP holds for all market pairs except Tehran-Ardebil that weak version LOP holds for them.
Conclusion: Results of this study showed that there is full transmission of shocks among selected provinces and implies that the markets considered are well integrated. It means that arbitrage activities profitably use existent opportunities and enhance economic efficiency. Moreover, the egg markets in selected provinces are taken into account as a unit market so if the government performs any kind of policy in one of these provinces (in the context of considered market), the effects of that policy will be transferred to other provinces and the welfare of consumers and producers in these provinces will be affected. Therefore, it is recommended to policy makers to regard this fact while they are choosing any new policy and to be aware of adopting the policies regionally.
M. Ghahremanzadeh; Kh. Alefi
Abstract
Agriculture as one of the major economic sectors of Iran, has an important role in Gross Domestic Production by providing about 14% of GDP. This study attempts to forecast the value of the agriculture GDP using Periodic Autoregressive model (PAR), as the new seasonal time series techniques. To address ...
Read More
Agriculture as one of the major economic sectors of Iran, has an important role in Gross Domestic Production by providing about 14% of GDP. This study attempts to forecast the value of the agriculture GDP using Periodic Autoregressive model (PAR), as the new seasonal time series techniques. To address this aim, the quarterly data were collected from March 1988 to July 1989. The collected data was firstly analyzed using periodic unit root test Franses & Paap (2004). The analysis found non-periodic unit root in the seasonal data. Second, periodic seasonal behavior (Boswijk & Franses, 1996) was examined. The results showed that periodic autoregressive model fits agriculture GDP well. This makes an accurate forecast of agriculture GDP possible. Using the estimated model, the future value of quarter agricultural GDP from March 2011 to July 2012was forecasted. With consideration to the fair fit of this model with agricultural GDP, It is recommended to use periodic autoregressive model for the future studies.
M. Salehnia; B. Hayati; M. Ghahremanzadeh; M. Molaei
Abstract
The lake Urmia and satellite wetlands was selected as a demonstration site for the UNDP/GEF/DOE conservation of Iranian Wetlands Project. This project aims to demonstrate reduction of the major threats of this wetland protected area coordinated through an integrated management plan. We developed a choice ...
Read More
The lake Urmia and satellite wetlands was selected as a demonstration site for the UNDP/GEF/DOE conservation of Iranian Wetlands Project. This project aims to demonstrate reduction of the major threats of this wetland protected area coordinated through an integrated management plan. We developed a choice experiment to examine public preferences and elicit their willingness to pay on improvements in lake’s indicators toward good environmental status. A pilot choice experiment study was administered in Urmia municipality and the data were analyzed using mixed logit model. The results revealed that residents of this municipality may strongly prefer improvement in water quantity and are willing to pay significant amounts (26000 RLs per household per year) to promote current water level to the high level. Furthermore, water quality, numbers of flamingos and Artemia stock (23000, 14670 and 11330 RLs per household per year respectively) were identified as next important issues that warrant additional management attention.
E. Pishbahar; M. Ghahremanzadeh; M. Jafari Sani
Abstract
Achieving an acceptable level of price growth is one of the main objectives of economic policies. With consideration to the importance of food, information on food price response to monetary policies is important. To achieve the object, scholars recently emphasize the use of models in which a wide range ...
Read More
Achieving an acceptable level of price growth is one of the main objectives of economic policies. With consideration to the importance of food, information on food price response to monetary policies is important. To achieve the object, scholars recently emphasize the use of models in which a wide range of economic data are included. These models are created by inclusion of one or more factors within the traditional VAR models. In this study, we tried to evaluate the effect of monetary policy on food price by using small scale of FAVAR model. For the purpose, 31 macroeconomic variables in periods 1367:1 to 1387:4 were included. The results showed that the liquidity shock has not influenced food price index for approximately ten next seasons. After this period, the liquidity shock makes increasing fluctuations on food price in such a way that the equilibrium has not been reachable. Therefore, a monetary shock will lead to instability fluctuations in the food price index for the long run. The fluctuations are cyclic and will increase over time in the way that they present reductions and increases around an equilibrium point.
E. Shabani; Gh. Dashti; M. Ghahremanzadeh; B. Haiati; J. Hosseinzad
Abstract
The object of this study was to investigate growth sources of agronomic products in Iran. To achive our object, we used Fan's Frontier Production Function approach, which includes input changes, technical changes and institutional changes. The study conducted for the period between 1977 and 2011 years. ...
Read More
The object of this study was to investigate growth sources of agronomic products in Iran. To achive our object, we used Fan's Frontier Production Function approach, which includes input changes, technical changes and institutional changes. The study conducted for the period between 1977 and 2011 years. Results of ADF test showed that all variables were integrated of order one. In addition, Johansen’s cointegration test indicated that there are at least two cointegration vectors between these variables. Furthermore, outcomes of analysing growth sources of agronomic products indicated that annual growth of agronomic products has been 3.41% , of which 85.9% has been due to increasing the physical inputs including machinery, labor, land and chemical fertilizer with the shares of 39.58%, 26.97%, 11.14% and 0.17%, respectively. Moreover, the shares of the technical changes and the institutional changes in the annual growth of agronomic products were about 8% and 6%, respectively. Considering the highest share of physical inputs in the growth of agronomic products, policies and strategies for increasing the productivity of inputs are recommended.
M. Ghahremanzadeh; T. Aref Eshghi
Abstract
The price fluctuations of chicken and its production inputs are one of the main challenges in broiler industry which affects the producer and consumer‘s welfare. This study investigates the price fluctuations of broiler and the price fluctuations of the two important inputs of broiler production -e.g. ...
Read More
The price fluctuations of chicken and its production inputs are one of the main challenges in broiler industry which affects the producer and consumer‘s welfare. This study investigates the price fluctuations of broiler and the price fluctuations of the two important inputs of broiler production -e.g. one day-old chick and soybean meal- in Tehran province. To achieve the purpose, the non-linear GARCH model (EGARCH، TGARCH، GJRGARCH، NGARCH) were estimated, using weekly data during the years 2006-2011. Analyzing non-linear GARCH models, the results presented that the TGARCH, EGARCH and GJRGARCH are the best models for broiler price, one day-old chick and soybean meal, respectively. Analyzing different forms of non-linear GARCH models revealed that the TGARCH, EGARCH and GJRGARCH are the best ones for broiler price, one day-old chick and soybean meal, , respectively. The results show that there is leverage effect for all three sets of prices. This indicates that the negative shocks and positive shocks have different effects on the price fluctuations. The bad news has greater impacts on the price fluctuations than the good news.
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 ...
Read More
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.
M. Ghahremanzadeh; A. Falsafian
Abstract
The price volatility spillover effect indicates that price volatility in different markets can be mutually affected. The objective of the study is to analyze volatility price spillover effects on the vertical levels including input, wholesale and retail sale levels in the Tehran beef supply chain. The ...
Read More
The price volatility spillover effect indicates that price volatility in different markets can be mutually affected. The objective of the study is to analyze volatility price spillover effects on the vertical levels including input, wholesale and retail sale levels in the Tehran beef supply chain. The multivariate generalized autoregressive conditional heteroskedastic (MVGARCH) model was used by monthly price series over the period between the first month 1376 and the first month 1378. The results show that there are strong volatility spillover effects from both the feed inputs and the beef retail markets on the wholesale live cattle (producer) market. The estimated magnitude of the volatility spillover coefficients indicate that the volatility of live cattle prices is more sensitive to volatility changes in the beef retail prices than to volatility changes in the input prices.
