Research Article
A.A. Baghestany
Abstract
Introduction: Developing economies suffer from high degree of macroeconomic uncertainty. Growth, inflation, real exchange rates and other key macroeconomic variables are much more volatile, and the consequences of this excess volatility for aggregate performance in several dimensions like growth, investment ...
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Introduction: Developing economies suffer from high degree of macroeconomic uncertainty. Growth, inflation, real exchange rates and other key macroeconomic variables are much more volatile, and the consequences of this excess volatility for aggregate performance in several dimensions like growth, investment and trade, have attracted some attention in recent empirical literature. In the case of investment, this concern has been renewed by recent theoretical work identifying several channels through which uncertainty can impact investment, under various assumptions about risk aversion, adjustment costs to investment and other factors. Iran, has a high degree of uncertainty in the macroeconomic variables. One of the major challenges related to the management of the foreign exchange market in Iran comes back to agricultural investment. Among different investments in economic sectors, investment in agricultural sector possesses a special prominence and position since investment in agricultural sector not only induce the growth of production and employment in this very sector, but also encourages production and employment growth in other economic sectors. Therefore, identifying effective factors on investment in agricultural sector and adopting suitable policies for increasing investment, possesses a supreme prominence. In Iran, the notions of finance and investment have always been facing several difficulties due to deep independence to oil revenues and instability of its price as well as high risk it involves; and for this reason, investing in different sectors, including agriculture, has always experienced severe fluctuations.
Materials and Methods: Data on agricultural investment in Iran were provided by annual statistics from 1978-2016. All of the following data were gathered from the statistical office of the Central Bank of Iran including Investment in agricultural sector in Rials using a constant price of 2011 = 100, Annual real GDP using a constant price of 2011 = 100, Short run interest rate on bank facilities and loan, and loans given to agricultural sector by banks.
NARDL Method When the order of integration is not the same for all variables then we use the lagged variables as proposed by Pesaran et al. (2001). Imagine two variables and their relation as follow:
To check the asymmetries, we have to make a separate series for appreciation and depreciation as proposed by Bahmani-Oskooee and Soharabian (1992). A series of exchange rate will be divided in its positive movements or appreciation, as indicated by, and negative movements or depreciation, as indicated by, and is given as follows:
To check the impact of positive and negative movements of one variable on the other variable, Equation above will be transformed as:
The non-linear ARDL model can be described as follows
Results and Discussion: In order to study the nonlinear effect of exchange rate and its shock on investment in agricultural sector, a NARDL model has been used. The results of Ramsey Reset Test show that the model is well-specified. LM test has been applied to investigate auto correlation. The results of LM test also reveal that the zero hypothesis is not rejected, and the final model does not have the problem of consistent correlation. The Breusch-Pagan-Godfrey Test (BPG) has been employed to investigate the phenomenon of heteroskedasticity. The results of this test also indicate that for the final model, the zero hypothesis is not rejected, and therefore the pattern do not have the problem of Heteroskedasticity. Positive shocks of exchange rate have shown a negative impact on agricultural investment in the current and previous two periods. While negative shocks of exchange rate have had a positive effect on current investment. NARDL pattern is a method which considers the short-run dynamics among the variables and estimates the long-run relationships as well. In this pattern first the dynamic model, then the long-run relation and error correcting pattern are fitted. The results of the Wald test show that the hypothesis of symmetry between positive and negative shocks is rejected and hence the effect of currency shocks is asymmetric. In the long run, changes in positive currency shocks have had a negative effect on investment. Results of F test also approve the long run relation. H0 is rejected and the presence of long-run relation is confirmed. The presence of co-integration among a set of economic variables provides a statistical base for using the error correction pattern. In the short term, current currency shocks and the previous two period currency shocks have had a negative and significant impact on agricultural investment. In Short term, changes in negative shock had no effect on investment. Also, after 1.5 periods, the short-term imbalances are adjusted in the long run.
Conclusion: This study used a non-linear autoregressive distributed lag (NARDL) model to check an asymmetrical relationship between Exchange volatilities and agricultural Investment. In current study, the Hodrick Prescott filter has been used to derive exchange rate volatilities. Results have shown that: 1) there is a negative and significant relationship between exchange rate shocks and investment in the agricultural sector in the short and long term. 2) With respect to negative impact of exchange rate on investing in agricultural sector, if this exchange rate increases remain stable, investment in the agricultural sector would decline very severe. Given the direct and historical impact of investing in the current period, investment will also be a problem for future years. Since given loan have had a positive impact on the investment, it is suggested that government increases these loans and facilities. The purpose of this policy is to prevent current investments decreases. 3) With respect to negative reaction of investment to US-Dollar-denominated shocks, the decline in US-Dollar dependency and the use of other high-yielding currencies such as the EURO currencies are appropriate. There are asymmetrical linkages between these two variables therefore negative exchange rate volatilities have positive effect and positive exchange rate volatilities have negative and significant effect on agricultural investment. The effect of negative shocks was less than the positive ones.
Research Article
H. Ailbakhshi; A. Dourandish; M. Sabouhi
Abstract
Introduction: Understanding the temporal and spatial fluctuations of climatic parameters (such as temperature, precipitation, relative humidity, etc.) and its impact on agricultural sector is essential for managing agricultural resources and adopting appropriate strategies. Precipitation directly ...
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Introduction: Understanding the temporal and spatial fluctuations of climatic parameters (such as temperature, precipitation, relative humidity, etc.) and its impact on agricultural sector is essential for managing agricultural resources and adopting appropriate strategies. Precipitation directly affects the production of dry crops by supplying the required moisture for the plant, and indirectly affects the production of aquatic crops through supplying surface and underground water resources. Climate change has an effect on temperature and precipitation distribution and consequently affects the plants water requirement and agricultural water consumption. Overall, climate change is influenced by both temperature and precipitation. Due to the changing rainfall pattern and average temperature of the atmosphere, this phenomenon can damage the production of agricultural products that maintain the major food sources of the country. Given the important role of agriculture in the country's economy and the existence of the ongoing water crisis and drought in the country, climate change can have major impacts on their aggravation. The purpose of the present study is to investigate the effects of climate change and water scarcity on agricultural production, price and income in Iran.
Materials and Methods: The multi-market model, sometimes referred to as the "finite general equilibrium" or "multi-market partial equilibrium model", has reduced the complexities of computable general equilibrium (CGE) models. The AMM template was used for this purpose. To simulate the effects of climate change, crop yields were calculated using yield response coefficients. Then, the demand function of different products was calculated using estimated elasticities and finally climate change has been simulated for 2025.
Results and Discussion: The results showed that climate change would increase, yield of rainfed wheat, blue barley, dry barley and maize grain in semi-arid climate and subtropical climate, in addition dry barley and barley products in warm semi-arid climate and subtropical climate, and finally rainfed barley and corn products Grain in temperate semi-arid climates and subtropicals climate by 2025 relative to current levels. Climate change also would decrease yields of dry wheat and barley in temperate semi-arid climates and subtropicals, and also wheat in warm and semi-arid climates and subtropicals for 2025 compared to the present value. The results also showed that climate change would expand the water available for the blue wheat crop in the semi-arid climate and sub-climates, besides the blue barley crop in the semi-arid, semi-arid, and temperate semi-arid climates for 2025 compared to the present value. Climate change also might reduce the amount of water available for the blue wheat crop in the climate and sub-arid and semi-arid sub-climates, therefor the corn yield in the cold and semi-arid sub-climates and sub-climates for 2025 compared to the present value. The results also revealed that climate change would diminish cultivation of maize crop in semi-arid climate and temperate climates in addition irrigated and rainfed wheat crop in warm and semi-arid sub-climate and also rainfed wheat crop in semi-arid climate by 2025 relative to the present situation. Also the area under cultivation of blue barley and dry barley crops in warm and semi-arid climates, cold and semi-arid climates, and blue wheat crop in semi-arid climates and rainfed wheat crop in temperate and semi-arid climates would decrease by 2025.
Conclusion: The results also demonstrated that with the climate change, the amount of maize crop production in cold and semi-arid climates and sub-climates, and the production of blue and dry wheat crops in warm and semi-arid climates, cold semi-arid, temperate and dry semi-arid climates for 20 years would decrease relative to current value. Also, the production of irrigated and rainfed barley in warm and semi-arid climates, sub-climates and temperate semi-arid climates for 2025 would increase compared to the present situation. Thus the first hypothesis of the study: "Climate change and water scarcity reduces agricultural production" is not approved in Iran. The results also explained that with the climate change the prices of wheat, barley and maize crops in the semi-arid and temperate climates for the year 2025 would also rise, so the second hypothesis of the study "Climate change and scarcity of water resources will increase the prices of agricultural products in Iran” is confirmed. The results also show that with climate change, farmers 'incomes in cold and semi-arid climates, temperate and warm semi-arid climates would increase by 2025 relative to their present value, so the third research hypothesis that "climate change and water scarcity reduces farmers' income" In Iran, " is not confirmed. The results also indicated that wheat, barley and maize exports remained negative by the creation of net climate change for 2025 and that the country's climate change created an importer of these products.
Research Article
F. Mojtahedi; S.M. Mojaverian; S.A. Hosseini-Yekani
Abstract
Introduction: stock market may play a significant role in financing food industries. Nowadays, people select an optimized portfolio with several shares instead of choosing only one in order to cope with the investment risk. For this, the systematic risk could be very important as the market is so fluctuating, ...
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Introduction: stock market may play a significant role in financing food industries. Nowadays, people select an optimized portfolio with several shares instead of choosing only one in order to cope with the investment risk. For this, the systematic risk could be very important as the market is so fluctuating, especially in Iran. So in this paper, we enter a constraint for systematic risk that helps investors in making decision.
Materials and Methods: As we said, we want to enter systematic risk in the portfolio selection model. We use Extreme Downside Hedge (hereafter EDH) as the measure for the systematic risk of each company in the food industry. This measure relies on the argument that investors are able to hedge against extreme downside risk. The EDH can be estimated by regressing stock returns on a measure of market tail risk. We use Expected Tail Loss (ETL) to measure market tail risk. ETL is defined as the expected value of the loss given that the loss exceeds VaR. Then, the factor models are introduced to capture the systematic risk. In order to actively allocate the systematic risk, we use the definition of the marginal systematic risk introduced by Li et al (2018) to measure the systematic risk contribution of a risk contributor. First, we choose some variables as factors that affect the return of each company. After that, we calculate the covariance between factors and then make an equation that shows the systematic risk for each company. We apply our methodology to the return time series of 11 companies and the index for the food industry, all listed on the Tehran Stock Exchange (TSE). The data covers the period from 2015 to 2019. Other variables include oil prices, gold prices and exchange rates extracted from the Economic and Financial Databank of Iran.
Results and Discussion: The results show the Behshahr Ind, Glucosan, Kalber, Margarin, Pars Mino, Pegah Fars and Salemin have positive EDH. This means for these companies the stock returns are affected by volatility of the market, in other words as the volatility increases, the stock returns decrease. It should be noted that the higher the EDH is, the greater the impact is. Also, Gorji Biscuit, Mahram Mfg, Minoo Co and Azar Pegah have negative EDH, indicating the reverse impactability of these companies' returns from market volatility. The higher the EDH, the lower the companies' volatility, also the higher the negative EDH, the higher the market volatility. After calculating the factor model and entering it in the portfolio model, we obtained the optimized result. According to the results, Azar Pegah and Pars Mino, with 86% and 12% have the highest percentage of the optimal portfolio, while Kalber, Pegah Fars and Salemin altogether have 2% of the portfolio, respectively. As the results show, the largest share belongs to the Azar Pegah Company, which is also according to the EDH of the company, in fact, the results show the company whose shares have the highest negative impact from the market has entered to the model. The presence of four other companies in the portfolio given the positive EDH is due to their high average return rather than other companies, since we consider the return as a constraint in the model because of its importance in decision making. It is also worth noting that, the two companies, kalber and behshahr Ind, with the highest positive EDH are not in the optimal portfolio. In order to investigate the effect of systematic risk the model was estimated without considering this constraint. The results show, without systematic risk constraint the optimal portfolio has shifted to companies with higher return and lower risk. Thus, the results of this study indicate that with systematic risk, based on expectations, portfolios will shift to companies with lower impactability from market volatility on the one hand and higher returns on the other.
Conclusion: Finally, the results of the study show, the systematic risk in the model shift the portfolio towards the stocks of companies that are less affected by market conditions. Therefore, given today's fluctuating conditions, it may be useful to apply a model that considers this part of the risk.
Research Article
S. Naghavi; A. Mirzaei
Abstract
Introduction: Food security is one of the main goals of economic growth and development of each country. , in this study, Due to the importance of agricultural sector in food security, the effect of agricultural productivity and Business environment on food production index in Iran was investigated using ...
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Introduction: Food security is one of the main goals of economic growth and development of each country. , in this study, Due to the importance of agricultural sector in food security, the effect of agricultural productivity and Business environment on food production index in Iran was investigated using Bayesian network during 2001-2016. One of the indicators of food security that is based on micro data is the food production index. The food production index includes food products that are considered edible and contain nutrients. But coffee and tea are an exception, because although they are edible, they have no nutritional value. This index is calculated as the ratio of food production value to the value of basic food production. Also, the health and food security of a country is directly dependent on agricultural production. One of the important indicators in the field of improving domestic production and subsequent food security is improving business environment, which its role in increasing production, especially in the agricultural sector, has been ignored. Improving the business environment is a key step in developing private sector investment, product and employment in the country. Although many studies have attempted to investigate effective factors on food security, but impact of the agricultural productivity index and business environment has not been considered. The institutional environment in which all economic businesses are formed, or have gone bankrupt and exit is called the business environment of economic activities. Improving the business environment by increasing entrepreneurship, increasing investment, reducing the informal sector, reducing production costs and prices of domestic goods, strengthening property rights, reducing corruption and reducing smuggling will increase economic growth. In this study, the effect of two factors of agricultural sector productivity and business environment on food security as factors affecting domestic production has been investigated. Various studies have proven the establishment of food security through supportive policies in the agricultural sector and increasing production in this sector. None of the studies, in particular, examined the effect of agricultural productivity on food security.
Materials and Method: In this study, the effect of agricultural productivity and Business environment on food production index in Iran is investigated using Bayesian network during 2001-2016. The Bayesian network is a probabilistic graph pattern that shows a set of variables and probabilities associated with each. This network is a straightforward, cyclical graph in which nodes are problem variables. The structure of a Bayesian network is, in fact, a graph of the interaction of the variables to be modeled. In addition to showing the quality of the relationship between the problem variables, it also shows the quantity of the relationship between these variables. Each network consists of three components: 1) nodes 2) the relationship between nodes and 3) the conditional probability table of nodes. The variables in the graph and the links show the relationships between the variables. The conditional probability table is also used to define the conditional probability of causal relationships.
Results and Discussion: The results showed that the increase in the real exchange rate, agricultural productivity, water productivity in the agricultural sector, and the improvement of the business environment have led to an increase in the food production index in Iran. The business environment is very important in the prosperity of production because an unfavorable business environment would increase production costs and reduce the competitiveness of goods in the international arena. Inadequate business environment has a significant impact on reducing economic growth and, consequently, the growth of the agricultural sector. Agriculture is considered as an area or platform for business. Therefore the development of agricultural businesses is also a manifestation of entrepreneurial behavior in this sector. Improving the business environment is a key step in the development of private sector investment, production and employment in the country. By providing the right conditions for competitiveness and effective entry of the private sector, a decisive role in it plays the economic growth and development of the country. Therefore, simplifying the licensing process; Reducing administrative procedures and time to enforce customs tariffs and simplifying rules and regulations are effective in improving the business environment.
The health and food security of a country is directly dependent on the production of the agricultural sector. The results showed that the share of value added of the agricultural sector in GDP and grain production, as indicators of agricultural productivity, has a positive effect on food security. The agricultural sector has an important role to play in achieving a prosperous production and food security. Therefore, the need to pay attention to the agricultural sector and appropriate support for this sector is felt. Increasing the level of productivity can improve economic growth, optimal use of resources, cost reduction, profitability and production capacity. For this purpose, it is necessary to review the necessary parameters in the design of irrigation systems and to develop design instructions according to the crisis water and soil conditions of the country.
Research Article
S. Esmaili; M. Ghahremanzadeh; A. Mahmodi; M. Mehrara; Gh. 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 ...
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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.
Research Article
Z. Sarabi; V. Ansari; H. Salami; S.S. Hosseini
Abstract
Introduction: The exchange rate in Iran has experienced considerable increase with some fluctuations over last two decades. This has resulted in an increased cost of food production in Iran. Since, further increase in exchange rate is expected in the future, it is important to determine which groups ...
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Introduction: The exchange rate in Iran has experienced considerable increase with some fluctuations over last two decades. This has resulted in an increased cost of food production in Iran. Since, further increase in exchange rate is expected in the future, it is important to determine which groups of agricultural products, produced in different agricultural sub-sectors, are more sensitive to these changes and also to specify the major paths through which exchange rate increase is transmitted to different agricultural products. The main objective of this study is to provide explanations for these questions.
Materials and Methods: To achieve the objectives of the study, a social accounting matrix (SAM) has been constructed based on the latest Iranian Input-Output Table released in 2011 by the Statistical Center of Iran. This SAM is a 110× 110 matrix and consists of different accounts. Three accounts for factors of production (labor, land and capital), 6 household accounts (rural and urban households divided into three groups of low, middle and high income), one government account, one capital account, one account for rest of the world, and finally, one account for commodities which includes 49 domestic commodities and 49 imported commodities. To trace the effects of changes in exchange rate on prices of different products, the matrix of SAM is transformed to a SAM-based price analytical model. Then, the structural path decomposition approach is used to specify the major paths through which the effects of increase in exchange rate are transferred to major agricultural products in different sub-sectors.
Results and Discussion: Results of this study revealed that livestock and poultry products are the most responsive products to a shock on the exchange rate. Thus, the effect of the shock on the prices of these products is significant. Forestry and agricultural services are in the second place from this point of view. Crop farming products, fish and other fisheries products, and horticultural products are ranked on the next place. Since producing livestock and poultry products extensively depend on the imported feed materials, the production cost and consequently, the prices of the first group of products experience the highest increase. Subsidizing feed materials, following an exchange rate shock, or direct payment to the low income households’ group might be a way to mitigate the negative effects of the exchange rate shock on food security in Iran. The results of structural path analysis indicate that the effects of increase in exchange rate on the prices of agricultural products are mostly transmitted through increasing import prices in six main economic sectors namely; “materials and chemical products”, “crop farming products”, “food products” “textiles, leather and their products”, “the machinery and equipment” and “hotel and restaurant services”. However, impacts of the above sectors on prices are not the same in all agricultural subsectors. Price of “crop farming products” is mostly affected by prices of imported “crop farming products” as well as “materials and chemical products”. Prices of “horticultural products” and “forestry and agricultural services” are mainly affected by increasing prices of imported “materials and chemical products”. On the other hand, price of “livestock and poultry products” changes considerably with increase in import prices of “crop farming products (raw materials)” and “food products”. Finally, price of “fish and other fishing products” is mostly affected by price of imported “food products”.
Based on the results of structural path analysis, the paths through which exchange rate shock are transferred to the cost of production and consequently prices of agricultural products are two separate channels. Increase in import prices of “materials and chemical products”, “crop farming products” and “food products” is transmitted to the prices of agricultural products as these products are utilized as inputs in production process of agricultural products directly or indirectly. On the other hand, an increase in import prices of “textiles, leather and their products” and “the machinery and equipment” indirectly affects production cost of agricultural products by first stimulating an increase in prices of primary factors, following increased cost of living for owners of these inputs.
Conclusion: To decrease the negative impact of exchange shock on prices of food products, different policies can be adopted, depending on the sectors playing the main role in increasing the cost of production and the path through which the shock is transmitted. Generally, subsidizing feed materials, following an exchange rate shock, through allocation of preferred exchange rate or supplying these materials with a subsidized price is recommended for the products such as poultry products in which most of the feeding materials are imported. On the other hand, direct payment to the low income households’ group might be a way to mitigate the negative effects of the exchange rate shock on food security in cases that most of the increased cost of production comes from increase in the cost of primary inputs.
Research Article
Z. Malakoutikhah; Z. Farajzadeh
Abstract
Introduction: The increase in greenhouse gases has affected global weather, resulting in changes in climate zones. Climate change is mostly characterized by changes in temperature. There is strong evidence showing that climate change will adversely affect the world especially developing countries in ...
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Introduction: The increase in greenhouse gases has affected global weather, resulting in changes in climate zones. Climate change is mostly characterized by changes in temperature. There is strong evidence showing that climate change will adversely affect the world especially developing countries in the following decades. Agricultural activities are more vulnerable to climate change as they are more dependent on water resources and temperature. Moreover, damages to agricultural activities may contract output in other sectors as well. Given the importance of the issue, Iran is a prominent example since it is located in an arid and semi-arid region, and its average annual precipitation is less than one-third of the global precipitation. In addition, there is a large body of literature indicating an increase in average temperature of Iran over the last decades. Therefore, this study aims to investigate the effect of climate change on the economic growth in Iran.
Materials and Methods: The Solow-Swan growth model was applied to investigate economic growth under climate changing environment. The growth models were estimated using time series data of 1350-1395 (1971-2016). In the growth model, a damage function, change in which damage is a function of temperature, was applied to examine the effect of climate changes. The growth model determinants are physical as well as other types of capital including human, social and environmental capitals. Internet access and phone access were used as proxies for social capital. Also, literacy rate, primary school enrolment rate, and university students were applied as proxies for human capital. Agriculture, mining, and oil and gas production were considered as proxies for natural and environmental resources. Another proxy for environmental capital was the value of natural resources marginal product. This variable is defined as the ratio of CO2 damages to GDP. Trade impact on economic growth was also investigated through using Foreign Direct Investment (FDI) and trade openness variables. Also, to examine the trend of temperature, an ARMA model was used. GDP is technically considered as an endogenous variable so Generalized Method of Moments (GMM) method is applied.
Results and Discussion: The specification of ARMA model revealed two significant moving average trends including five-year and nine-year. These trends indicate an increasing average for temperature, leaving less doubt about the phenomenon of climate change. Our results showed that the increase in temperature will negatively affect economic growth. It was also found that one-degree increase in average temperature is expected to reduce Iranian GDP by 5-6.6 percent. Physical capital showed the highest contribution to Iranian GDP. Its contribution to the economic growth, in terms of elasticity, was found to be 0.08-0.16. The corresponding values for human and social capital were 0.02-0.06 and 0.03-0.08, respectively. However, environmental capital failed to affect the economic growth significantly. Among the variables applied for human capital, university students were found to play a more significant role. The insignificant effect of environmental capital on economic growth may be attributed to its nature that is used as a public good, resulting in intensive as well as irrational use. Among the variables applied for environmental capital, the value of natural resources marginal product showed a slightly strong effect, needing to be considered as a proxy for environmental capital. Also, FDI showed an insignificant effect; however, trade openness was found to affect economic growth positively.
Conclusion: The general trend of the economic growth in Iran is far from what is expected. In addition, this trend is threatening by, among the others, climate change which is characterized by increasing average temperature as well as decreasing precipitation. Also, as far as the capital is considered, economic growth in Iran is highly dependent on physical capital while the contribution of other types of capital including human, social and environmental capital is not significant. However, it is worth noting that environmental capital seems to be used intensively while for human capital reasons like inappropriateness of labor quality and education system is more acceptable. Even for physical capital, higher contribution is expected since the Iranian economy enjoys lower capital accumulation. It was also found that removing trade barriers and being more connected with the global economy may provide more opportunities to enjoy higher growth.