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Showing 15 results for Oil 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.
Dr Abolghasem Golkhandan,
Volume 0, Issue 0 (12-2024)
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):
2
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
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):
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
Mohammad Hassanzadeh, Hossein Sadeghi, Ali Usefi, Bahram Sahabi, Ali Ghanbari,
Volume 12, Issue 4 (1-2013)
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.
Ali Arshadi, Habib Mossavi,
Volume 14, Issue 3 (9-2014)
Volume 14, Issue 3 (9-2014)
Abstract
Iran’s economy is vulnerable to fluctuations in oil price. This study examines the impact of oil shocks on economic growth using Vector Auto-Regressive (VAR) method. The Mork’s (2010) method was used to test hypothesis of symmetry in negative and positive shocks. The results show that, the effects of negative and positive shocks on economic growth are asymmetric. In addition, the results of variance decomposition of economic growth indicate that the effects of positives shocks in explaining economic growth fluctuations are greater than negative ones. On the other hand, the results from impulse response functions show that positive and negative shocks have positive and negative effects on economic growth, respectively; however, the size of positive shocks impact on output growth is far more than that of negative shocks in the long-run. Moreover, the estimated VAR model shows that there is a high and positive correlation between oil revenues and gross domestic product (GDP), which confirms again dependency of national economy to oil revenues.
Shadi Amiri, Masoud Homayounifar, Mostafa Karimzadeh, Mohammad Ali Falahi,
Volume 15, Issue 2 (6-2015)
Volume 15, Issue 2 (6-2015)
Abstract
This study investigates the time-varying correlations among oil and coin prices, and exchange rate in Iran. Since investment is a key factor in economic growth and development, so the necessary funds should be provided and directed towards manufacturing and industrial sectors. In addition, understanding the relationships among financial variables allows to the investor to reduce overall portfolio risk without harming to the return on investment. In this paper we use monthly data of the oil and coin prices, and exchange rate in Iran over the period 1991:3 to 2011:2 and examine time-varying correlations using Dynamic Conditional Correlation - Generalized Autoregressive Conditional Heteroskedasticity (DCC-GARCH) approach by G@RCH6 software. The analyses made in milieu of the world financial crisis (2008) show that the conditional correlations among assets are time-varying and world financial crisis causes significant changes in dynamic relationships among assets under study in Iran.
Volume 15, Issue 3 (11-2011)
Abstract
New Approaches in Forecasting Using Neuro-Fuzzy Networks (Case Study: The Crude Oil Price) Mohammad Rahim Ramezanian1, Esmael Ramezanpour2, Sayeed Hamed Pourbakhsh3 1- Assistant Professor. of Management, Guilan University, Guilan, Iran 2- Assistant Professor of Economy, Guilan University, Guilan, Iran 3- B.sc of Industrial Management, Guilan University, Guilan, Iran Received: 17 /4/2010 Accept: 18/4/2011 Our world is a rapidly changing world. So it is very important for the survival of organizations to know what lies ahead in the future, how much demand is there for their products and for what price? We cannot afford big changes unless we are able to predict the future. The application of predictability science in management has been studied in this research. With the increasing progress of science, the use of new methods and application of new intelligent technologies have also increased. In this research, new methods and algorithms such as neural networks and fuzzy logic have been explained and the application of their combination in predictability has been studied. Various methods such as Moving Average Method, Weighted Moving Average, Exponential Smoothing, Double Exponential Smoothing, Linear Trend, Combined Functional Trend, and Exponential Process were used to make predictions. The results obtained from these methods were compared with the those obtained from the neru-fuzzy networks method using 6 error measurement criteria. It was found that the neru-fuzzy networks method yielded better results, and the correspondence of data (R2 coefficient) for the Neru-fuzzy networks was about 90 percent. The data used in this research were related to the Organization of the Petroleum Exporting Countries (OPEC) for the years 1970-2000.
Volume 19, Issue 6 (11-2017)
Abstract
This study aimed to develop a multi-sector Dynamic Stochastic General Equilibrium (Large DSGE) model for Iran’s economy. In this model, economy was divided into three sectors: Agriculture, non-agriculture, and oil. Imports and exports were also included in the model. In order to adapt the model with Iran’s economic conditions, price stickiness in agriculture and non-agriculture were included. Then, the impact of rising oil prices on agricultural sector was examined. To calculate the required coefficients, 1971-2012 data was gathered and Bayesian method was used. The results showed the negative impacts of rising oil prices on agriculture as well as the negative effects of Dutch Disease.
Mrs Fateme Shamsolahrar Fard, Dr. Majid Ahmadian, Dr. Nafiseh Behradmehr, Dr. Mohsen Mehrara, Dr. Ghahraman Abdoli,
Volume 20, Issue 4 (12-2020)
Volume 20, Issue 4 (12-2020)
Abstract
This paper investigates the role of financial development factors on how to affect oil price on oil and gas rents in Iran. In order to construct a multidimensional financial development index, the principal component analysis and weighted average of nine financial development indicators are used. The oil price is derived from the estimates of spot prices. Data is collected seasonally for Iran during the period of 1970Q1-2016Q4. In order to evaluate the how to affect oil price on oil and gas rents, a simultaneous equations system, the SUR estimator, and rolling regression method are used in two stages. In the first step, the ARDL rolling method is used to estimate the effect of oil price on oil and gas rents. Then, the effect of multidimensional financial development index on the oil price is determined by simultaneous equations system of oil and gas rents. The findings indicate the positive effect of multidimensional financial development index on how to influence oil price on oil rent and gas rents. It means that increasing multidimensional financial development index strengthens the effectiveness of oil price on oil and gas rents in Iran.
Dr. Ameneh Nadalizadeh, Professor Kambiz Kiani, Dr. Shamseddin Hoseini, Dr. Kambiz Peykarjou,
Volume 21, Issue 1 (3-2021)
Volume 21, Issue 1 (3-2021)
Abstract
Oil price shocks have an undesirable effect on financial stability and banking systems, in addition to creating uncertainty and negative effects on the macroeconomic performance of oil-exporting countries. In fact, the dependency of government spending policies on oil price movements in oil exporting countries creates feedback loops between asset prices and bank credits that could lead to an increase in vulnerability of the financial sector. Therefore, considering the importance of the issue, this study aims to investigate the asymmetric effects of oil prices on non-performing loans (NPLs), as credit risk criteria, by applying data from 18 selected banks in Iran during 2006-2017. In this regard, the relationship between variables has been estimated using Panel Nonlinear Autoregressive Distributed Lag (PANEL NARDL). The predictability of symmetric and asymmetric PANEL ARDL models is assessed by applying RMSE and Campbell and Thompson (2008) tests. The results show that the asymmetric model has better performance and efficiency than the symmetric model. These asymmetric effects are significant in both short-term and long-term. Based on the results, the impact of oil price on the NPLs of some banks is positive and in the others is negative and significant.
Volume 21, Issue 3 (7-2014)
Abstract
This paper investigates the short- run and long-run effects of government size and exports on the economic growth of Iran as a developing oil export based economy for the period of 1974 - 2008 using an autoregressive distributed lags (ARDL) framework. A modified form of Feder (1982) and subsequently Ram’s (1986) model has been applied to include both government size and exports in growth equation. The findings show that in long run and short run the Armey curve (1995) is valid, indicating that both a very big size and a too small size of government are harmful for growth and government should adjust its size. The results also show that total exports, the amount of oil exports in terms of barrels and oil prices affect economic growth positively and significantly both in short-run and long-run. However, non-oil exports do not have a significant effect on growth in the long run
Volume 21, Issue 3 (7-2014)
Abstract
In general, energy prices, such as those of crude oil, are affected by deterministic events such as seasonal changes as well as non-deterministic events such as geopolitical events. It is the non-deterministic events which cause the prices to vary randomly and makes price prediction a difficult task. One could argue that these random changes act like noise which effects the deterministic variations in prices. In this paper, we employ the wavelet transform as a tool for smoothing and minimizing the noise presented in crude oil prices, and then investigate the effect of wavelet smoothing on oil price forecasting while using the GMDH neural network as the forecasting model. Furthermore, the Generalized Auto-Regressive Conditional Hetroscedasticity model is used for capturing time varying variance of crude oil price. In order to evaluate the proposed hybrid model, we employ crude oil spot price of New York and Los Angles markets. Results reveal that the prediction performance improves by more than 40% when the effect of noise is minimized and variance is captured by Auto-Regressive Conditional Hetroscedasticity model.
Volume 22, Issue 3 (12-2018)
Abstract
An examination of international political economy history shows that discovery of huge oil reservoirs has been playing an important role in defining and supporting the countries national interest. Undoubtedly, oil reserves in Iran are considered as intergenerational resources and maintaining intergenerational justice as well as enhancing national interest in the long run. These are indisputable commitments which are the main goals and missions of Iran governors. In this research, focusing on the economic aspect of the national interest and by using systems dynamic methodology, dynamics changes of Iran’s national interest are modelled considering developments in the oil industry and market. The structure of production capacity formation, amount of production and revenues of domestic and international sale of oil and oil products are investigated and modeled and variables related to economic national interest are formulated. Simulation results described in five scenarios as follows: growth in the oil market, current status, downturn in the oil market, OPEC market share target, and OPEC revenue target. According to results, increase in domestic prices of energy carriers to international prices and the increase of the budget share for investment in more value added areas in the oil industry are recommended to increase national economic benefits.
Mrs. Narges Sanjari Konarsandal, Dr Behnam Elyaspour, Dr Roohollah Babaki,
Volume 22, Issue 4 (12-2022)
Volume 22, Issue 4 (12-2022)
Abstract
Introduction:
Excessive carbon emissions and global warming caused by human activities have become serious challenges to the human society and have raised global concerns. Currently, air pollution has become so important in many big countries of the world and especially big cities of Iran. Air pollution has forced governments to adopt short-term and long-term policies and plans for solving it.
Policy uncertainty related to economic decision-making is of great importance in the global economy. Numerous researches have shown that the uncertainty of economic policies is closely related to various economic indicators. In addition to the economic effect, the uncertainty in economic policies has an environmental effect. Increasing economic policy uncertainty weakens the government's commitment to environmental governance and, as a result, affects the effectiveness of environmental policy implementation. Therefore, a reduction in economic policy uncertainty can reduce greenhouse gas emissions.
Regarding the effect of oil on the economic conditions of oil-exporting countries such as Iran, there are two points of view: in the first point of view, the positive effects of oil on improving people's quality of life are emphasized. The second point of view points to the negative effects of the development of energy resources on the environment in resource-rich countries. According to this point of view, extraction, production and consumption of oil resources causes waste of resources and destruction of the environment of the regions.
Considering that environmental pollution is one of the most challenging topics discussed in the world, the main goal of this study is to investigate the asymmetric effects of economic policy uncertainty and oil price on carbon emissions in Iran.
Methodology:
The model to investigate the asymmetric effects of economic policy uncertainty and oil price on carbon emissions is defined as follows:
where, CO2: carbon dioxide emissions, EPU: economic policy uncertainty, OP: oil price, GDP: gross domestic product and EC: energy consumption. In the process of estimating the model, the data related to economic policy uncertainty follow the study of Ashena and Shahpari (2022) from World Uncertainty Index (WUI), data on energy consumption are extracted from Ministry of Energy website and energy balance sheet, while other data are extracted from World Bank, International Monetary Fund and OPEC website during 1981-2018. In addition, the Nonlinear Autoregressive Distributed Lag (NARDL) model is used to estimate the above model.
Results and Discussion:
First, the stationarity of the variables was checked using the Phillips–Perron test. The results of the unit root test show that all the variables are I(1). In the following, the existence of long-term relationship between the variables was investigated using the Bounds test. The results indicated the existence of a long-term relationship between the variables in the model. After ensuring the validity of the model, Wald's test was used to test short-term and long-term asymmetry. The results indicated the asymmetric effect of economic policy uncertainty and the symmetric effect of oil price in the short and long term on carbon emissions. With the identification of the long-term relationship and the confirmation of asymmetry in the economic policy uncertainty variable, the study model was estimated using the NARDL model and diagnostic tests were carried out. The model estimation results showed the asymmetric effect of economic policy uncertainty on carbon emissions; So that the effect of positive changes in economic policy uncertainty variable in the short and long term on carbon emissions was positive and significant, while there was no significant relationship between the negative shock of economic policy uncertainty and carbon emissions in the short and long term. Also, the results show that the effect of oil price on carbon emissions was symmetric; So that the effect of oil price on carbon emissions in the short and long term was positive and significant. Finally, to ensure the stability of the model, CUSUM and CUSUMSQ tests were performed. The results indicated that the estimated model is stable.
Conclusion:
In Iran's economy, the government should spend the increased oil revenues resulting from the increase in oil prices to create infrastructures that will reduce air pollution, or in other words, invest the income from the increase in oil prices in technologies that they emit less carbon dioxide.
Governments in developing countries such as Iran, which are transitioning from agriculture to industry, should force industrial producers to use technologies that cause less pollution by enacting environmental laws and standards such as pollution taxes.
Iran is a rich country in renewable resources, and due to its geographical location (wind energy in the north and west of Iran, solar energy in the south of Iran), it can move towards the replacement of non-renewable resources with a systematic planning. Therefore, it is recommended to move towards the production and consumption of renewable resources, while preserving energy resources, in order to reduce the amount of carbon emissions.
Considering the positive effect of economic policy uncertainty on the emission of carbon dioxide in Iran, it is recommended to the government to give up its irregular economic policies in order to reduce the emission of pollution and to adopt its economic policies as a rule. Economic agents should act in a stable and predictable way to prevent economic policy uncertainty.
Dr. Mirhossein Mousavi, Dr. Musa Khoshkalam Khosroshahi, Mrs. Samira Torkashvand,
Volume 23, Issue 4 (12-2023)
Volume 23, Issue 4 (12-2023)
Abstract
The purpose of this study is to investigate the effect of oil price shocks on the components of the Iranian labor market and the role of government capital expenditure in this field. Labor market components include job vacancies, job finding rates, inflow rates to unemployment and unemployment rates. For this purpose, the structural vector autoregressive approach over the period 2005:2- 2019:3 has been used. The results of impulse response functions show that positive oil price shocks have significant effects on model variables. However, negative oil price shocks are not significant. The positive oil price shock increase government capital expenditure, but due to the inefficiency of government investment, job vacancies decrease and the inflow rates to unemployment increase. As a result, the unemployment rate has risen in response to positive oil price shocks. The results show the Dutch disease and the asymmetric effect of oil price shocks on the labor market.
Introduction:
In addition to creating economic problems, the problem of unemployment can be the source of behavioral disorders and political tensions and can be considered a threat to the health of a society. For this reason, analyzing the labor market and knowing the factors that lead to unemployment is one of the concerns of every economy. Oil is a source of income in exporting countries and an important production factor in importing countries. Therefore, oil price shocks are expected to have an impact on market developments in terms of income and cost effects. This study aims to answer the question of whether oil price shocks have an effect on the components of Iran's labor market. For this purpose, the effect of oil price shocks from the channel of construction expenditure on the rates of finding a job, entering unemployment, unemployment and job opportunities, which are adjustment factors and represent the components of the labor market, are investigated.
Methodology:
In this article, structural vector auto regression (SVAR) model is used to investigate the effect of oil price shock on labor market components. For this purpose, it is necessary to specify the VAR model first, and then analyze the SVAR model by applying restrictions on matrices A and B. Constraints are imposed on the relationships between the regression residuals and the disturbance terms of the structural equation system so that the structural form can be identified.
Results and Discussion:
The results related to the significance of the variables show that all the variables are at the significance level. In addition, the optimal lag for estimating the basic VAR model based on the Akaike criterion is 1. Examining the roots of the VAR equation system shows that all the roots are less than one and are inside the unit circle, so the effects of shocks disappear in the long-run and the system is stable. The findings show that one standard deviation shock to the series of positive changes in oil price causes its instant increase by 0.4 and its effect decreases in the second season and disappears from the third season onwards. Government construction expenditure has increased immediately in response to shocks (one-time lag amounts), but this increase is not lasting, and it has declined in the second season, and in the third season it disappears with a slight increase in shock effects that shows a strong dependence on oil revenues. Because the only source of construction expenditure is from oil revenues, job openings have declined due to these shocks, which last until the second season. Then it increases slightly, but less than the initial negative effect, and gradually the shock effect disappears. One standard deviation shock to the series of negative oil price changes will cause it to increase by 0.1 immediately, and its effect will disappear in the third quarter. The effect of negative oil price shocks on any of the variables is not significant. However, these shocks immediately reduce government construction spending. This again shows the dependence of construction expenditure on oil revenues because at the time of the drop in oil prices, construction expenditure is decreased and allocated to current expenditure.
Conclusion:
The aim of this study was to investigate the effect of oil price shocks on the labor market. For this purpose, the effects of positive and negative shocks of oil prices on construction expenditure, job opportunities, and unemployment rates, entering unemployment and finding jobs in a SVAR model were investigated. Positive (negative) shocks in oil prices immediately increase government construction spending. This increase (decrease) is not lasting and quickly decreases (increase) and from the third season onwards, the shock effects disappear. The positive shock of oil prices has a significant effect on four components of labor market, namely job opportunities, entering unemployment, job finding rate and unemployment rate. However, negative oil price shocks are not meaningful. Therefore, oil price shocks have asymmetric effects on the labor market. The results also confirm two problems of dependence on current expenditure and Dutch disease. Because shocks only affect the short term, while construction spending is expected to improve job opportunities in the long run.
Introduction:
In addition to creating economic problems, the problem of unemployment can be the source of behavioral disorders and political tensions and can be considered a threat to the health of a society. For this reason, analyzing the labor market and knowing the factors that lead to unemployment is one of the concerns of every economy. Oil is a source of income in exporting countries and an important production factor in importing countries. Therefore, oil price shocks are expected to have an impact on market developments in terms of income and cost effects. This study aims to answer the question of whether oil price shocks have an effect on the components of Iran's labor market. For this purpose, the effect of oil price shocks from the channel of construction expenditure on the rates of finding a job, entering unemployment, unemployment and job opportunities, which are adjustment factors and represent the components of the labor market, are investigated.
Methodology:
In this article, structural vector auto regression (SVAR) model is used to investigate the effect of oil price shock on labor market components. For this purpose, it is necessary to specify the VAR model first, and then analyze the SVAR model by applying restrictions on matrices A and B. Constraints are imposed on the relationships between the regression residuals and the disturbance terms of the structural equation system so that the structural form can be identified.
Results and Discussion:
The results related to the significance of the variables show that all the variables are at the significance level. In addition, the optimal lag for estimating the basic VAR model based on the Akaike criterion is 1. Examining the roots of the VAR equation system shows that all the roots are less than one and are inside the unit circle, so the effects of shocks disappear in the long-run and the system is stable. The findings show that one standard deviation shock to the series of positive changes in oil price causes its instant increase by 0.4 and its effect decreases in the second season and disappears from the third season onwards. Government construction expenditure has increased immediately in response to shocks (one-time lag amounts), but this increase is not lasting, and it has declined in the second season, and in the third season it disappears with a slight increase in shock effects that shows a strong dependence on oil revenues. Because the only source of construction expenditure is from oil revenues, job openings have declined due to these shocks, which last until the second season. Then it increases slightly, but less than the initial negative effect, and gradually the shock effect disappears. One standard deviation shock to the series of negative oil price changes will cause it to increase by 0.1 immediately, and its effect will disappear in the third quarter. The effect of negative oil price shocks on any of the variables is not significant. However, these shocks immediately reduce government construction spending. This again shows the dependence of construction expenditure on oil revenues because at the time of the drop in oil prices, construction expenditure is decreased and allocated to current expenditure.
Conclusion:
The aim of this study was to investigate the effect of oil price shocks on the labor market. For this purpose, the effects of positive and negative shocks of oil prices on construction expenditure, job opportunities, and unemployment rates, entering unemployment and finding jobs in a SVAR model were investigated. Positive (negative) shocks in oil prices immediately increase government construction spending. This increase (decrease) is not lasting and quickly decreases (increase) and from the third season onwards, the shock effects disappear. The positive shock of oil prices has a significant effect on four components of labor market, namely job opportunities, entering unemployment, job finding rate and unemployment rate. However, negative oil price shocks are not meaningful. Therefore, oil price shocks have asymmetric effects on the labor market. The results also confirm two problems of dependence on current expenditure and Dutch disease. Because shocks only affect the short term, while construction spending is expected to improve job opportunities in the long run.
Mr Ahmad Pourmohammadi, Dr Zohreh Tabatabaiie Nasab, Dr Yhya Abtahi, Dr Mohammad Ali Dehqantafti,
Volume 24, Issue 2 (5-2024)
Volume 24, Issue 2 (5-2024)
Abstract
Introduction
Despite the increasing debate around the role of alternative renewable sources of energy such as solar and nuclear power, oil still has a central role for a vast portion of the world’s countries. Therefore, oil price is one of the key prices in the international economy, and its effects and mechanisms on macroeconomic variables has been an important topic of economic research. In oil-exporting countries, oil price fluctuations have implications for all macroeconomic and prudential policies but due to the government ownership of natural resources, fiscal policy is especially important and can be a main mechanism for transferring these fluctuations to the economy. In this regard, this study aims to analyze the complex relationships and dynamic co-movements between international oil price movements and macroeconomic variables, emphasizing the role of fiscal policy in a time-frequency approach in the years 1978-2020. For this purpose, we implement two novel wavelet analysis techniques, namely, multiple wavelet coherence (MWC) and partial wavelet coherence (PWC), which are used to explore the real relationship between variables. The use of the wavelet tool is superior to traditional tools because it allows the analyst to determine how the series interact at different frequencies and how they evolve over time. To the best of our knowledge, the current is the first paper to implement the wavelet framework to analyze the effects of oil price dynamics on macroeconomic variables in Iran. Therefore, this study makes a modest contribution to the empirical literature by unveiling the main transmission mechanism of oil prices at different time horizons.
Methodology
The econometrics techniques that have been previously used are focused on time domain analysis. This analysis may return incomplete and ambiguous information on the relationship between economic variables. Therefore, this study is focused on time and frequency domain analysis using the wavelet transformation approach that has been left out for the relationship dynamics among these variables.
The origin of wavelets can be traced back to Fourier analysis, which is the foundation of modern time-frequency analysis. Fourier transform, examine the periodicity of phenomena by assuming that they are stationary in time. But most economic and financial time series exhibit quite complicated patterns over time. The wavelet transform approach was introduced to overcome the limitations of the Fourier transform. In fact, if the frequency components are not stationary traditional spectral tools may miss such frequency components. The wavelet analyses do not follow the initial checks to observe if the series have unit root or not. The superior feature of the wavelet analysis is related to its flexibility in monitoring several non-stationary signals.
Wavelet Analysis is a method that allows simultaneous decomposition of original time series according to both time and frequency domains. This is very important for economics and finance, as many of the variables in this field can operate and interact differently on dissimilar time scales. So, in this paper, we used two innovative wavelet approaches to study and compare the interdependence between oil prices, non-oil GDP, public expenditure, and trade balance. This approach implements the estimation of the spectral features of time series as a function of time, displaying how the various periodic components of time series vary through time. To check the relevance of the coherence of multiple independents on a dependent one, we use multiple wavelet coherence (MWC), a similar method to the multiple correlations. The partial correlation is one of the tools that can be used in a simple correlation concept. In the wavelet, the researchers can attain this using partial wavelet coherence (PWC). This approach is able to identify the partial wavelet coherence between the two-time series y and x1 after eliminating the influence of the third time series x2. Hence, we use partial wavelet coherence to identify the wavelet coherence between oil prices and government expenditure when canceling out the effect of non-oil GDP and trade balance.
Results and Discussion
The results of the wavelet analysis show that there is a strong coherence between oil prices and the macroeconomic variables at different frequencies. multiple wavelet coherence, shows a high coherency between the four variables in the short-run (1-4 years) and in the long-run horizons (8-16 years). In fact, multiple wavelet coherence between variables shows that there is always a relationship between variables over time and different scales with different coefficients.
Partial wavelet coherence between oil and non-oil GDP has been significant by removing the effects of government expenditure in the short term during the years 1988 to 1992 and also 2000 to 2012. In the scale of 6 to 8 years from 2010, the partial coherence shows an approximate value of 0.6, which is maintained at this frequency until the end of the period. This issue shows the greater correlation between oil price fluctuations and non-oil GDP by removing the effects of fiscal policy fluctuations in these years. Also, by removing the effects of the trade balance, there is a partial wavelet coherence between the pairs of oil price and non-oil GDP from 1996 to 2012 in the short-term time horizon.
The partial wavelet coherence between oil price and trade balance by removing the effect of fiscal policy and also by removing the effect of non-oil GDP indicates a limited relationship between the pair of oil price and trade balance by removing the effects of other two variables during the study period. In both cases, the relationship between the two variables is limited to the early years of the study period, and there is no independent relationship in other areas.
The results of the partial wavelet coherence between oil price and government expenditure showed that by removing the effect of non-oil GDP, the highest correlation of the variable occurred in the short-term and medium-term region. In the short-term time horizon, during the years 1979 to 1992, a strong wavelet coherence can be seen between the oil prices and government expenditure, which was repeated during the years 2010 to 2011. Also, by keeping the variable effects of the trade balance constant until the end of the 80s, there is a co-movement between oil price and government expenditure independent of the effects of the trade balance. This net correlation between the two variables well indicates the role of fiscal policy in the transmission of oil price fluctuations in multiple time scales.
Conclusion
The most important effective factor in increasing oil price fluctuations is the unforeseen and increasing risks related to oil and its related industries. Since the world has seen rapid and successive developments in recent years (including the spread of disease, war, etc.), severe fluctuations have been observed in the global oil markets during these years. Therefore, in a fluctuating environment, oil prices have forced governments and policymakers to formulate policies to deal with the uncertainty of oil prices. To implement such policies, it will be useful to examine the relationship between oil price dynamics and its transmission mechanisms in the economy. In this regard, the present article analyzes the relationship between oil price dynamics and macroeconomic variables, emphasizing the role of fiscal policy in Iran through time-frequency analysis and the new approach of multiple and partial wavelet coherence.
The results of multiple wavelet coherence show the co-movement between oil price and other variables of the model in different time scales. In such a way that this co-movement shows the greatest intensity in short and long-time horizons. Also, the partial wavelet correlation results between the variables of oil price and non-oil GDP as well as government expenditures showed that by removing the effects of other variables, the co-movement between the pair of variables can still be observed in all time horizons. While regarding the trade balance, this net relationship with oil price was not observed.
In general, based on the partial wavelet coherence results, it can be shown that fiscal policy and economic growth are the main channels of oil price fluctuations transmission in this period, which are in line with the studies of Hossein et al. (2008) and El Anshasi (2008) who showed that Fiscal policies are the main propagation mechanism that transmits the oil price shocks to the economy.
Therefore, the reduction of oil price correlation by removing the effects of fiscal policy and business cycles shows the importance of the channel of fiscal policy and GDP in the transmission of oil price fluctuations. Therefore, it is recommended that the policymakers who adjust various economic stabilization schemes for greater stability, while paying attention to the main channels of oil financial resources flowing into the economy, should consider different frequency bands as well.
Despite the increasing debate around the role of alternative renewable sources of energy such as solar and nuclear power, oil still has a central role for a vast portion of the world’s countries. Therefore, oil price is one of the key prices in the international economy, and its effects and mechanisms on macroeconomic variables has been an important topic of economic research. In oil-exporting countries, oil price fluctuations have implications for all macroeconomic and prudential policies but due to the government ownership of natural resources, fiscal policy is especially important and can be a main mechanism for transferring these fluctuations to the economy. In this regard, this study aims to analyze the complex relationships and dynamic co-movements between international oil price movements and macroeconomic variables, emphasizing the role of fiscal policy in a time-frequency approach in the years 1978-2020. For this purpose, we implement two novel wavelet analysis techniques, namely, multiple wavelet coherence (MWC) and partial wavelet coherence (PWC), which are used to explore the real relationship between variables. The use of the wavelet tool is superior to traditional tools because it allows the analyst to determine how the series interact at different frequencies and how they evolve over time. To the best of our knowledge, the current is the first paper to implement the wavelet framework to analyze the effects of oil price dynamics on macroeconomic variables in Iran. Therefore, this study makes a modest contribution to the empirical literature by unveiling the main transmission mechanism of oil prices at different time horizons.
Methodology
The econometrics techniques that have been previously used are focused on time domain analysis. This analysis may return incomplete and ambiguous information on the relationship between economic variables. Therefore, this study is focused on time and frequency domain analysis using the wavelet transformation approach that has been left out for the relationship dynamics among these variables.
The origin of wavelets can be traced back to Fourier analysis, which is the foundation of modern time-frequency analysis. Fourier transform, examine the periodicity of phenomena by assuming that they are stationary in time. But most economic and financial time series exhibit quite complicated patterns over time. The wavelet transform approach was introduced to overcome the limitations of the Fourier transform. In fact, if the frequency components are not stationary traditional spectral tools may miss such frequency components. The wavelet analyses do not follow the initial checks to observe if the series have unit root or not. The superior feature of the wavelet analysis is related to its flexibility in monitoring several non-stationary signals.
Wavelet Analysis is a method that allows simultaneous decomposition of original time series according to both time and frequency domains. This is very important for economics and finance, as many of the variables in this field can operate and interact differently on dissimilar time scales. So, in this paper, we used two innovative wavelet approaches to study and compare the interdependence between oil prices, non-oil GDP, public expenditure, and trade balance. This approach implements the estimation of the spectral features of time series as a function of time, displaying how the various periodic components of time series vary through time. To check the relevance of the coherence of multiple independents on a dependent one, we use multiple wavelet coherence (MWC), a similar method to the multiple correlations. The partial correlation is one of the tools that can be used in a simple correlation concept. In the wavelet, the researchers can attain this using partial wavelet coherence (PWC). This approach is able to identify the partial wavelet coherence between the two-time series y and x1 after eliminating the influence of the third time series x2. Hence, we use partial wavelet coherence to identify the wavelet coherence between oil prices and government expenditure when canceling out the effect of non-oil GDP and trade balance.
Results and Discussion
The results of the wavelet analysis show that there is a strong coherence between oil prices and the macroeconomic variables at different frequencies. multiple wavelet coherence, shows a high coherency between the four variables in the short-run (1-4 years) and in the long-run horizons (8-16 years). In fact, multiple wavelet coherence between variables shows that there is always a relationship between variables over time and different scales with different coefficients.
Partial wavelet coherence between oil and non-oil GDP has been significant by removing the effects of government expenditure in the short term during the years 1988 to 1992 and also 2000 to 2012. In the scale of 6 to 8 years from 2010, the partial coherence shows an approximate value of 0.6, which is maintained at this frequency until the end of the period. This issue shows the greater correlation between oil price fluctuations and non-oil GDP by removing the effects of fiscal policy fluctuations in these years. Also, by removing the effects of the trade balance, there is a partial wavelet coherence between the pairs of oil price and non-oil GDP from 1996 to 2012 in the short-term time horizon.
The partial wavelet coherence between oil price and trade balance by removing the effect of fiscal policy and also by removing the effect of non-oil GDP indicates a limited relationship between the pair of oil price and trade balance by removing the effects of other two variables during the study period. In both cases, the relationship between the two variables is limited to the early years of the study period, and there is no independent relationship in other areas.
The results of the partial wavelet coherence between oil price and government expenditure showed that by removing the effect of non-oil GDP, the highest correlation of the variable occurred in the short-term and medium-term region. In the short-term time horizon, during the years 1979 to 1992, a strong wavelet coherence can be seen between the oil prices and government expenditure, which was repeated during the years 2010 to 2011. Also, by keeping the variable effects of the trade balance constant until the end of the 80s, there is a co-movement between oil price and government expenditure independent of the effects of the trade balance. This net correlation between the two variables well indicates the role of fiscal policy in the transmission of oil price fluctuations in multiple time scales.
Conclusion
The most important effective factor in increasing oil price fluctuations is the unforeseen and increasing risks related to oil and its related industries. Since the world has seen rapid and successive developments in recent years (including the spread of disease, war, etc.), severe fluctuations have been observed in the global oil markets during these years. Therefore, in a fluctuating environment, oil prices have forced governments and policymakers to formulate policies to deal with the uncertainty of oil prices. To implement such policies, it will be useful to examine the relationship between oil price dynamics and its transmission mechanisms in the economy. In this regard, the present article analyzes the relationship between oil price dynamics and macroeconomic variables, emphasizing the role of fiscal policy in Iran through time-frequency analysis and the new approach of multiple and partial wavelet coherence.
The results of multiple wavelet coherence show the co-movement between oil price and other variables of the model in different time scales. In such a way that this co-movement shows the greatest intensity in short and long-time horizons. Also, the partial wavelet correlation results between the variables of oil price and non-oil GDP as well as government expenditures showed that by removing the effects of other variables, the co-movement between the pair of variables can still be observed in all time horizons. While regarding the trade balance, this net relationship with oil price was not observed.
In general, based on the partial wavelet coherence results, it can be shown that fiscal policy and economic growth are the main channels of oil price fluctuations transmission in this period, which are in line with the studies of Hossein et al. (2008) and El Anshasi (2008) who showed that Fiscal policies are the main propagation mechanism that transmits the oil price shocks to the economy.
Therefore, the reduction of oil price correlation by removing the effects of fiscal policy and business cycles shows the importance of the channel of fiscal policy and GDP in the transmission of oil price fluctuations. Therefore, it is recommended that the policymakers who adjust various economic stabilization schemes for greater stability, while paying attention to the main channels of oil financial resources flowing into the economy, should consider different frequency bands as well.
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