Showing 84 results for Price
Volume 0, Issue 0 (1-2024)
Abstract
Oil is one of the significant factors in promoting economic activities. Oil provides a considerable part of the government's revenue sources. The price of oil has always been fluctuating over the years for various reasons including political, social, and economic developments in countries. Since the price of oil affects different sectors of economy including the agricultural sector through the government budget and the revenue sources of the government, this study investigated the effect of positive and negative fluctuations in OPEC oil prices on the value added of the agricultural sector during 1990-2019. The new GAS method was used for estimating the OPEC oil price fluctuations and the NARDL method was used for estimating the long-term relationships between positive and negative OPEC oil price fluctuations on the value added of the agricultural sector. In addition to OPEC oil price fluctuations, other independent variables such as the consumer price index, employment in the agricultural sector, and the degree of trade openness were examined in the model. Based on the obtained results, the positive and negative fluctuations of OPEC oil prices in the long term had a negative effect on the value added of the agricultural sector. Furthermore, the degree of trade openness had a positive effect on the value added of the agricultural sector in a long term. results indicate that oil income is one of the most important issues that decline value added of agriculture sector and government should control this negative relation to develop agriculture as a vital sector of economic.
Volume 0, Issue 0 (1-2024)
Abstract
This study investigates the factors affecting coffee exports in Cameroon. For this purpose, we employed the gravity model. Considering the sample characteristics, the model is estimated with the Poisson pseudo-maximum likelihood (PPML) method. The main material of the study is a panel data set covering the years 2001-2021 for ten countries, Cameroon’s main coffee export partners. The findings show that the GDP of importing countries, coffee export prices, and bilateral investment treaties (BITs) positively influence exports, whereas distance, exchange rates, and Cameroon’s GDP have negative impacts. The results highlight Cameroon’s logistics infrastructure deficiencies and the significance of stable, high-quality production. The Cameroonian government should implement policies to improve production quality and efficiency by expanding agricultural extension services and offering farmers input and investment incentives to address these challenges. Additionally, improving port efficiency will necessitate the digitalization of operations, implementation of data-driven planning, and strategic infrastructure investments.
Mrs Saeideh Shahabi Rabori, Dr Sadegh Khalilian, Dr Seyed Habibollah Mosavi, Dr Hamed Najafi Alamdarlo,
Volume 0, Issue 0 (12-2024)
Abstract
Aim and Introduction
Today, the environment is considered as one of the most important pillars of sustainable development, and the development of other economic and social sectors depends on its sustainability and proper functioning. Environmental pollution has become one of the main challenges of countries. Environmental health is currently one of the most critical concerns of people and officials round the world. Almost all managers and decision makers believe that this national wealth should be protected not only for the current generation but also for future generations, since the pollutants caused by industries are highly costly and detrimental to health.
Active industries are one of the main sources of environmental pollution. One of the necessary conditions for economic progress and the introduction of extensive structural changes in economic and technological fields is industrialization and industrial development. In the production process, using production inputs whose main source is the environment, in addition to desirable outputs such as consumer goods, undesirable outputs such as environmental pollutants are also produced. If the number of outputs is not controlled and disproportionate, the losses from undesirable outputs will be greater than the benefits of desirable products in such a way that damages to the environment would be irreparable and sustainable development less likely to be achieved.
One of the most important concerns related to industrialization is the effects and environmental consequences of industrial activities. Therefore, achieving the necessary solutions to control such consequences is vitally important. Minerals are essential for human survival, but their extraction and processing are not environmentally friendly practices which contribute to problems such as soil erosion, air and water pollution. On the other hand, mineral sector is one of the largest energy consumers which has active contribution to air pollution and global warming. The main purpose of this study is to investigate the economic effects of Gol Gohar mine in Sirjan. For this purpose, it is intended to determine the type and amount of pollutants released from this complex, and also to determine the amount of the green tax of the complex as a solution to reduce pollution and examine the social welfare resulting from reducing pollution.
Methodology
In this study, the economic effects of environmental pollutants of Gol Gohar Iron Mine in Sirjan (Southeastern Iran), is investigated using the input distance function model from 2001 to 2022. Through calculating the shadow price of pollutants, a criterion for determining the green tax is determined, and then the amount of social cost resulting from the emission of pollutants is calculated.
The shadow price of the undesirable output is the cost that the producer must bear if they plan to reduce the production of the undesirable output. In fact, it can be interpreted as the marginal cost of reducing pollution for each producer. Therefore, the shadow price of the desirable output is considered positive and equal to the market price of that output, but the shadow price of the undesirable output must be estimated to be less than zero.
Findings
The products of Gol Gohar Iron Ore Complex in Sirjan, include granulated iron ore, iron ore concentrate and pelletized in the production process. The most greenhouse gases and air pollutants are related to carbon dioxide (CO2), sulfur oxides (Sox), nitrogen oxides (Nox) and particulate matter (SPM). According to the obtained results, the average shadow price for air pollutants in Gol Gohar complex for CO2, Sox Nox, and SPM was calculated as 11.15, 3,074.5, 5,529.62, and 1,875.62 rials per kilogram respectively. Moreover, the average total social costs resulting from the production of Gol Gohar Sirjan Complex was calculated as 92,710 billion Rials according to the amount of pollution produced over the period.
Discussion and Conclusion
The estimation of environmental costs is actually an introduction to providing solutions for internalizing and reducing environmental costs, using the input distance function model and the shadow price of environmental pollutants in the industrial and mineral complex of Gol Gohar, Sirjan. The title of the largest producer of iron ore in the country was calculated, and the social cost resulting from the emission of pollutants was also evaluated. Finally, in this study, solutions and mechanisms for reducing environmental costs have been proposed.
Considering that the ability to absorb pollutants by the environment is limited, the shadow price of pollutants, which represents their real social cost, should be taken into consideration. The damages should also be determined based on the shadow price of the pollutants. In other words, the amounts of pollutant emission should be calculated and while taking into account the allowed limit of pollutant emission and shadow prices, based on a legal plan, the environmental costs should be reimbursed. Taking such measures would surely require more studies and capable executive management system
Dr Abolghasem Golkhandan,
Volume 0, Issue 0 (12-2024)
Abstract
Aim and Introduction
Ecological footprint accounting is composed of two metrics, the “demand-side” (ecological footprint) and the “supply-side” (biocapacity). While the ecological footprint calculates the demand for natural assets in global hectares, biocapacity symbolizes the supply capacity of nature to meet this demand with the same unit of measurement. Ecological deficit also shows the difference between ecological footprint and biological capacity. Globally, the degree of ecological deficits continued to expand over the last decade due to the increase in EF and reduction in biocapacity, which is caused by the following: increasing consumption of fossil fuel energy, overexploitation of natural resources, unsustainable production methods, and economic activities.
Iran is one of the countries that has a weak environmental performance. According to the Global Footprint Network, Iran's ecological footprint exceeded 333% of its biological capacity in 2022. Iran's ecological deficit, which was - 0.55 global per capita hectares in 1961, has increased by 554% to 2.50 global per capita hectares in 2022, and the destruction and pollution of the environment in Iran have reached unsustainable levels. Therefore, the analysis of the determinants of environmental quality can provide insights into the design of appropriate environmental policies in Iran.
In this regard, the environmental effects of dependence on crude oil have attracted considerable attention. Crude oil is an important and largest source of energy, especially for developing countries such as Iran. It is a fossil-based fuel and a major source of carbon emissions in the world. Hence, many studies have linked oil price shocks to environment quality. In contrast to oil-importing economies, where oil price increases encourage a shift to cheaper and cleaner alternative energy sources, the environmental policy issue in oil-exporting countries is entirely different. Indeed, a fall in oil prices may be associated with a decreased investment in environmentally friendly energy sources. By comparison, an increase in oil prices revealed a reluctance to diversify the economy away from its reliance on non-eco-friendly fossil fuel energy.
Based on the explanations above, the main purpose of this article is to investigate the asymmetric impact of scaled oil price impulses on the environmental Load Capacity Factor (LCF) in Iran using the Non-linear Autoregressive Distributed Lag (MATNARDL) approach. The paper intends to make the following contributions to the literature. Firstly, this article is the first to look into the effect of oil prices on the LCF in Iran by applying asymmetric methodologies. Secondly, it is the first study with a reverse load capacity factor as an environmental sustainability indicator. Thirdly, this paper applied the advanced and newly developed MATNARDL for asymmetric and nonlinear analysis to provide a more robust result that exhibits relevant policy implications. Finally, this innovative study investigated the effects of oil prices on the LCF in Iran between 1961 and 2022 in the framework of the LCC hypothesis.
Methodology
The study compiles annual data for the period 1961-2022 for Iran from three different sources. According to Statista, OP represents average annual OPEC crude oil price (in US dollars per barrel). The data are obtained from the World Bank, GDP per capita, (constant 2015 dollars), Energy Consumption (EC) as kg of oil equivalent per capita, Ecological Footprint (per capita, gha) and LCF (the load capacity factor) are obtained from Global Footprint Network. Because the LCF includes biocapacity in the numerator and EF in the denominator, it allows for simultaneous environmental assessment on the supply and demand sides. A higher LCF indicates a better environment. The current paper's economic functions are illustrated in Equations (1):
LnLCFt=fLnOPt, LnGDPt,LnGDPt2,LnECt,εt (1)
The main objective of this study is to examine the major, medium and minimal scales of positive and negative changes in oil price on the environmental quality index in Iran. For this purpose, the MATNARDL is used as an estimator to examine the effect of minor to major adverse shocks and minor to major positive surprises in the explanatory variable on the explained variable.
Findings
The bounds cointegration test results confirm a long-term relationship in the asymmetric model. The estimation of the model has been performed by categorizing the positive and negative impulses of the oil price in three small (quantiles less than the τ30 threshold), medium (quantiles between the τ30 and τ70 thresholds), and large (quantiles greater than the τ70 threshold) scales in the form of MATNARDL approach. The results indicate that in the long term, small scale of positive (negative) oil price impulses had a positive (negative) and significant effect on the load capacity factor; while these impulses have a negative effect on the load capacity factor in the long term in both medium and large scales. Based on other results, energy consumption has a negative and significant effect on the load capacity coefficient, and the environmental hypothesis of the load capacity curve (LLC) in Iran is confirmed.
Discussion and Conclusion
Based on the obtained results, it can be said that the effect of oil price on the load capacity factor in Iran is asymmetric. Among positive impulses, only with increase in small scale of oil price, we can see an increase in load capacity factor and environmental sustainability in the country. Moreover, the positive impulses of the oil price on both medium and large scales lead to the increase of environmental instability by prioritizing economic achievements and activities over environmental issues
Volume 5, Issue 2 (8-2015)
Abstract
Lack of a structured anticipation about different aspects of high usage product of the national petrochemical company, has forced this company to buy published anticipated prices from foreign countries. Prevent the outflow of foreign exchange and tolerance of political factors, such as sanctions in this field, require a prediction of prices in Iran. Due to chain-like nature of petrochemical products and the absence of precise knowledge of effects of many factors on price, researchers are forced to solve problems with high complexity and high grade of equations. Selecting number and type of input variables of neural network has a significant impact on the performance of a system. Therefore fundamental analysis relying on theory of supply / demand and macroeconomic perspective alongside of Delphi statistical method were used to select the most influential factor. This factor is the price of petroleum products. At First, the overall topology of the neural network is designed using controlled variables, then, considering the independent variables, the optimal network has selected. After creating the user interface, communication of system with optimal neural network was established. To evaluate the actual price of considered product in reference year, it compared with the prices predicted by the proposed system and purchased prices predicted from CMAI; acquired results proved acceptable effectiveness of the proposed system with less than 3% error in predicting of considered chain. Using this system can result in petrochemical companies’ independency from buying forecasted prices from foreign companies and prevent exiting currency from country.
Volume 7, Issue 3 (7-2019)
Abstract
Aims: The present study has used results of the application of Revised Universal Soil Loss Equation (RUSLE) in integrated with the economic cost of soil loss to prioritize sub-watersheds of Selj-Anbar Watershed in Mazandaran Province, northern of Iran.
Materials and Methods: Overlay of five input layers of RUSLE model, viz., rainfall erosivity (R), soil erodibility (K), slope length and steepness (LS), cover and management (C) and support and conservations practices (P) factors has been done in Geographical Information system (GIS) platform for the study watershed. Then, the soil loss and sedimentation cost have assessed using soil nutrient depletion analysis. In this method, monetary value to the depleted nutrients based on the cost of purchasing an equivalent amount of used chemical fertilizer in the watershed was assigned.
Findings: The average soil loss and sediment rates of 4.92 and 1.98 t ha-1, respectively was obtained for the study watershed. In addition, the direct and indirect costs caused by soil loss during the five-year period in the Selj-Anbar Watershed were obtained 4.32×105 and 6.40×105 US$ which was totally equal to 10.98×105 US$. The highest (5.59×104 US$) and lowest (1.16×104 US$) annual cost of soil loss was estimated in the sub-watersheds S1-1-1 and S1-1-2, respectively.
Conclusion: Spatial distribution of soil loss and erosion cost could provide a basis for comprehensive and sustainable watershed management. The sub-watersheds with high soil erosion and cost rates deserve superior priority for implementation of conservation activities.
, Majid Aghaei, Mohammad Rezaeepour,
Volume 9, Issue 1 (4-2009)
Abstract
Exchange rate and inflation rate consistently affect stock price and the return on stocks. Since such effects could impact income distribution, it is important to study such issue carefully. In this paper an attempt is made to study the impact of exchange rate and inflation rate on the real returns as well as the stock price index in Tehran stock market.
In this paper, we use a vector autoregreesion (VAR) model as well a vector error correction model (VECM) to examine the relationship among variables. This study uses monthly data from 1983M4 through 2007M3. The results indicate that there exists a stable long–run relationship among the variables included in the model. Exchange rate and inflation rate positively affect the real rate of stock return. However, the impact of inflation rate is stronger than the impact of the exchange rate.
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Volume 9, Issue 1 (4-2009)
Abstract
The purpose of this paper is to investigate the effect of increasing electricity price on compensated variation (CV) and deadweight loss (DWL) of different income groups in Iran over the 1967-2004 period. An autoregressive distributed lag (ARDL) model is employed and five electricity demand functions are estimated for different income groups and based the estimates, CV and DWL are calculated. The effects of electricity price increase on CV and DWL are examined and the following results are obtained:
• Comparing CV in different income groups shows that CV increases from the poor to the rich.
• Comparing DWL in different income groups shows that DWL increases from the poor to the rich.
• By increasing electricity price and using direct subsidy, the welfare of low and middle income groups increase while the welfare of high income groups decrease.
Hossein Sadeghi, Touhid Ferouzan Sarnaghi,
Volume 10, Issue 1 (5-2010)
Abstract
According to the neoclassical approach, input prices as a measure of resources scarcity induce firms to cost-minimizing and efficient allocation of recourses. But when the prices are distorted, the effective competitive inputs are used inefficiently and have resulted in under- or over-utilization of production factors relative to their endowments or allocative inefficiency.
In this paper, the shadow cost approach and system of equations are used to estimate allocative inefficiency using the Iran's manufacturing data over the period 1976-2006. The results show that there is strong allocative inefficiency and increasing cost of production of firms in Iran's Manufacturing Sector.
Abdoulkarim Esmaeili, Robab Mohsenpour,
Volume 10, Issue 4 (1-2011)
Abstract
Regarding environmental importance and the lack of analytical methods for environmental policies, in this paper, shadow price for NOx and SOx emissions has been estimated for the Iranian electric industry. Input distance function is used for estimating shadow prices. The estimated shadow prices have revealed that the cost of Iranian electric industry for reducing one KG of NOx and Sox is 14991 and 17687 Rials, respectively. Estimated shadow prices in this study are greater than the amount offered by EPO (Environment Protection Organization) and World Bank. So it is recommended that any fine should be taken according to the emission shadow price.
Bahram Sahabi, Hussein Sadeqi, Ali Akbar Shurehkandi,
Volume 11, Issue 1 (5-2011)
Abstract
This paper investigates the impact of exchange rate on non-oil export covering the period from 1978 to 2006. The method used in this study is Panel data, and these countries are selected as the hosts: Turkey, The United Arab Emirates, Saudi Arabia, Kuwait and Pakistan. In this research, Gross Domestic Product of the host country, Bilateral Exchange Rate, Price Raito and Dummy Variable are used as regressor for non-oil exports. The result of this study shows that, gross domestic product and exchange rate have positive effect, but price ratio and dummy variable have negative effect on non-oil exports of Iran to these countries. Also Cross Section Specific coefficient shows that exchange rate has positive effect on export to Turkey, The UAE and Pakistan, while negative effect on other countries.
Volume 11, Issue 1 (1-2009)
Abstract
This study investigated the factors influencing the decision to plant almonds in the Saman region of Chaharmahal-Bakhtiari Province in central Iran through conducting an economic survey in 2005. Using portfolio investment theory and econometric model esti-mation (Shively, 1998), this paper identifies the most important factors influencing the in-dividual farmer’s decision concerning the number of almond trees planted during 1995-2004. Results of this study show that farm size, permission for water use, a one-year fore-cast of almond price changes, and the upcoming year’s expected change in the guaranteed price of wheat as a competitor crop in the use of land and water had a significant impact on the number of trees planted. This study indicates that policymakers should take notice of the adverse impact of the increasing wheat price trends on tree planting and indirectly promote more research on the environmental impact of almond plantations, particularly as it relates to soil erosion and environmental issues.
Mirfieyz Falah Shams, Mahmood Mohammadi,
Volume 11, Issue 2 (8-2011)
Abstract
Price manipulation in the Tehran Stock Exchange has been one of the most widely discussed issues among academic and professional practitioners in recent years. In this article, we first calculated the abnormal Returns- significance difference between actual and risk-based adjusted expected returns- by using an autoregressive test, for all 130 accepted firms in the Tehran stock market during 2002-2006, which seemed to be manipulated, since they had experienced great fluctuations in their stock prices. For any firm, if changes in share prices are not at random and/or its stock prices are autocorrelated with the past ones, it can be concluded that the firm is under a price manipulation. In the next stage, we have developed a binary logit regression model for predicting the firms' price manipulation based on four factors i.e. the information transparency, the liquidity of the shares, the size (capital) of the firm and the P/E ratio. Finally, the model efficiency for predicting price manipulation in the Tehran Stock Exchange is validated by using appropriate statistical tests such as, The Wald, Likelihoods Function, and the Wilk's Lambda tests. The results showed that the model is efficient and robust for predicting the price manipulation (P<0.05, Wilk's Lambda=0.205; Cox & Snell R2=0.792 ,0.799; -2Log likelihood= 27.49).
Shahriar Nessabian, Saleh Ghavidel, Mehdi Fathabadi,
Volume 11, Issue 3 (10-2011)
Abstract
Using Haskel theory, in this paper the main factors of change in wage ratios of agricultural and non-agricultural labor force are explored. Theoretically, the wage gap between these two sectors is explained by the gap between price and the one between TFP of these two sectors. In recent years, the wage gap between the two sectors has been decreasing in Iran. The international trade model (Haskel model) has been used in this paper and the results reveal that the major factor contributing to wage gap is the price one. The TFP is considered insignificant for wage gap. Mainly, the reason for increasing agricultural product index price, compared to that of non-agricultural index price has been government protection of agricultural products during these years.
Hossein Asgharpour, Sakineh Sojoodi, Nasim Mahin Aslani Nia,
Volume 11, Issue 3 (10-2011)
Abstract
According to exchange rate pass-through models, exchange rate has a great impact on the competitiveness of exports and determining the effects of exchange rate on export prices can be useful in planning for export promotion. For this purpose, in this paper it has been attempted in the theoretical framework of exchange rate pass- through models and applying ARDL approach the effects of exchange rate on non- oil exports price of Iran during 1971 to 2007 has been tested empirically. The findings show that there is a significant positive relationship between exchange rate and export price index so that by increasing exchange rate (devaluation of national currency) export price index increases significantly. Exchange rate pass- through to export prices is complete and to import prices in terms of destination currency is zero. In other words, the empirical results of this study indicate that in the Iranian economy, exporters are faced with devaluation of national currency (increase in exchange rate), which increases export prices in terms of domestic currency. Thus, the exchange rate changes have not significant effects on export prices in terms of destination currency and just affect the profits of exporters.
Amir Reza Soori, Hassan Heydari, Hossien Afzali,
Volume 12, Issue 1 (5-2012)
Abstract
The purpose of this paper is to examine the relationship between bank loan rate and housing prices in Iran. For this purpose, some VAR models have been applied, using the following variables: real loan rate, money supply (including the high powered money and the liquidity), GDP, housing services index, and the number of licenses for new houses. The results show that a reduction in the loan interest rate will increase the demand for housing sector because of reduction in cost of borrowing from banking system in order to invest in this sector. In other word, the research findings have implied a negative relationship between bank loan interest rates and housing prices. The results have also revealed that financial repression in the form of bank loan rates control policy induces more investment in housing sector and results into resource depletion of banking system.
Seyed Fakhredin Fakhrehosseini, Asghar Shahmoradi, Mohammad Ali Ehsani,
Volume 12, Issue 1 (5-2012)
Abstract
Fluctuations in fiscal policy affect monetary policy and the central bank, because the government’s general budget is highly dependent on oil prices and its fluctuations. Therefore, this paper designs a New Keynesian model for Iran with nominal rigidities (prices and wages) and analyzes the impact of technology, oil price, government spending and money supply shocks on macroeconomic variables (inflation, output) in economy of Iran. The data in this article are related to the fixed prices in the year 2004 and run annually from 1966 to 2008 on a per capita basis. Having logarithms taken, the variables are de-traded through Hodrick - Prescott filter. The final model equations are linearized around the steady state and using Uhlig (1999) approach, accidental equations are also linearized and are specified as space state pattern in Matlab software. Finally, the calibration of parameters are assessed, variables are simulated and compared with real data. The results show that the recommended model can simulate the impact of shocks on macroeconomic variables. It also shows that inflation rises in response to all shocks except that of technology. As the figures show, it is also revealed that non-oil output increases in response to technology, oil price, government spending and money supply.
Volume 12, Issue 2 (9-2022)
Abstract
The probability of stock prices crash has great importance in portfolio analysis and pricing of capital assets. Therefore, one of the major issues that investors face in the capital markets is predicting the fall of stocks. Given this necessity, the purpose of this study is to provide an approach to estimate the risk of stock price crashes. Recently, methods called "artificial neural networks" have been used to predict monetary and financial variables in parallel with structural models and time series. These models, which are actually derived from the brain learning process, use computer computational speed to learn complex relationships between variables and use them to predict the future. Using the data of 20 companies listed in the Tehran Stock Exchange, the present study presents models to estimate the probability of stock prices crash in the Iranian stock market using artificial neural networks. The results indicate that artificial neural networks have good performance in estimating the probability of stock prices crash in the Iranian stock market.
Maryam Moghimi Feyzabadi, Naser Shahnoushi,
Volume 12, Issue 3 (9-2012)
Abstract
One of the main inputs in manufacturing sector of Iran is fossil fuels with prices much lower than prices elsewhere in the world which are offered to producers and consumers. This accounts for a large share of subsidy payments allocated to different sectors of economy. The effect of subsidies on energy costs and prices of goods and services incur complex changes on the economy through allocation of resources. In this paper, using the computational general equilibrium model, effects of removal of fuel subsidies on production changes, cost and price in the Khorasan Razavi province has been studied. The results show that the elimination of subsidy on fossil fuels increased production, cost and price Indices. The highest growth rate of production and cost indices is in the gas sector and the highest growth rate of price index is in the oil sector.
Mohammad Hassanzadeh, Hossein Sadeghi, Ali Usefi, Bahram Sahabi, Ali Ghanbari,
Volume 12, Issue 4 (1-2013)
Abstract
In this paper the impacts of oil price fluctuations on the household welfare for different income groups have been studied using computational general equilibrium model. Equivalent Variation (EV) criterion is also used to evaluate changes in household welfare. The results show that oil price fluctuation has a greater impact on income, expenditure and welfare of urban households compared with the rural ones. In other words, dependence of urban household income on oil price is stronger in comparison to the rural ones. It has also been revealed that an oil price increase is more effective than the price reduction on household welfare, income and expenditure. Ratio of EV to total expenditure is almost the same for the poor and rich households, implying that both of them suffer a percentage of welfare loss in the same way.
