Search published articles
Dr Zana Mozaffari, Dr Saeed Khani, Dr. Bakhtiar Javaheri,
Volume 23, Issue 3 (8-2023)
Volume 23, Issue 3 (8-2023)
Abstract
Introduction
Nowadays, environmental problems, especially air pollution, are one of the major issues in the world's metropolises with increasing its dimensions and side effects. Humans are one of the main sources of air pollution. The age structure of the population is an important indicator in the progress of societies. It can be said that one of the effective factors in economic growth and long-term socio-economic development plans is the age structure of the population (youth or aging population). In working-age (provided that the labor market has the capacity to absorb more workforce in activities), increasing labor supply leads to economic growth.
In general, the age structure of population is important because economic activities and energy consumption vary by age or stage of life. On the other hand, the age of household head is related to household size (people over 65 usually have smaller households than middle-aged people). Studies conducted in Iran have mostly focused on examining Kuznets' environmental hypothesis, the impact of income and population changes on carbon dioxide emissions, and so far have not examined the effect of aging on carbon dioxide emissions. Therefore, this article examines the effect of aging on air pollution in Iran. This article uses the GMM to investigate the dynamic effect of population aging on air pollution during 1981-2020.
Methodology
To collect information for this study, a documentary method was used. The research was conducted based on annual data from 1982 to 2020 in Iran's economy. EViews software was used to estimate the model. It should be noted that data related to research variables were extracted from various sources such as the Central Bank of Iran Statistical Center of Iran, and Energy Balance Sheets.
To estimate the model, a time series econometric method called GMM was used because the model used in this study is dynamic and satisfies generalized moment conditions. In fact, GMM is used for time series models that are linear and also provide generalized moment conditions and instrumental variable properties. This method have many advantages.
Results and Discussion
In this study, the impact of population aging on air pollution was investigated using the GMM in Iran during the period of 1981-2020. The estimation of the model indicates that increasing the age of the population and the transition of the age structure of the population to the aging stage has a negative effect on air pollution. As it is predicted, Iran will face the problem of population aging in the next few years. According to the results, with increasing population, it can be expected that air pollution and environmental degradation will decrease. Due to the negative coefficient of the per capita income squared, the Kuznets environmental hypothesis is confirmed by considering the age structure of the population. In addition, urbanization, industrialization, trade openness, pollution of the previous period have positive and significant effects on air pollution.
The results indicate an inverted U-shaped EKC pattern between environmental degradation (pollution emissions) and per capita income (economic growth); therefore, it can be concluded that environmental degradation initially increases with increasing per capita income in a country, but after reaching a certain level of economic growth, environmental degradation stops and then decreases. Therefore, the results confirm the Kuznets environmental hypothesis for Iran. Based on this, it is recommended that the government design its plans with environmental considerations, especially air pollution. The results indicate that population aging has a significant negative effect on air pollution emissions. Population aging is detrimental to a country's economy and although it is inevitable for any country, policies to increase the number of elderly people in the population mix cannot be formulated and implemented even though it reduces air pollution levels. However, the harm caused by population aging outweighs this benefit. Of course, recently topics such as "active aging" have been raised to deal with population aging logically and should be on policymakers' agenda given the transition of age structure and movement towards aging in future years.
Conclusion
Based on the evidence of Iran's population age distribution during the period under study, it can be said that in future decades, older individuals will make up a higher percentage of the total population. This will lead to a reduction in carbon dioxide pollution automatically without government intervention or any other actions. The results of this study also show that urbanization and industrialization have positive impacts on air pollution. This result indicates that with the increase in the number of industrial enterprises and the trend towards urbanization in Iran, air pollution has increased. The reason for this is that most industries in Iran are energy-intensive and use fossil fuels. Another reason is the outdated technology with low efficiency in production. Other research findings show that pollution from previous periods and trade liberalization have positive effects on air pollution. The policy of economic liberalization by creating division of labor and using advantages, increasing capacity utilization in industries, increasing capital formation rates, changing technology, and creating competition in international markets lead to higher productivity levels for all production factors at a higher level.
Nowadays, environmental problems, especially air pollution, are one of the major issues in the world's metropolises with increasing its dimensions and side effects. Humans are one of the main sources of air pollution. The age structure of the population is an important indicator in the progress of societies. It can be said that one of the effective factors in economic growth and long-term socio-economic development plans is the age structure of the population (youth or aging population). In working-age (provided that the labor market has the capacity to absorb more workforce in activities), increasing labor supply leads to economic growth.
In general, the age structure of population is important because economic activities and energy consumption vary by age or stage of life. On the other hand, the age of household head is related to household size (people over 65 usually have smaller households than middle-aged people). Studies conducted in Iran have mostly focused on examining Kuznets' environmental hypothesis, the impact of income and population changes on carbon dioxide emissions, and so far have not examined the effect of aging on carbon dioxide emissions. Therefore, this article examines the effect of aging on air pollution in Iran. This article uses the GMM to investigate the dynamic effect of population aging on air pollution during 1981-2020.
Methodology
To collect information for this study, a documentary method was used. The research was conducted based on annual data from 1982 to 2020 in Iran's economy. EViews software was used to estimate the model. It should be noted that data related to research variables were extracted from various sources such as the Central Bank of Iran Statistical Center of Iran, and Energy Balance Sheets.
To estimate the model, a time series econometric method called GMM was used because the model used in this study is dynamic and satisfies generalized moment conditions. In fact, GMM is used for time series models that are linear and also provide generalized moment conditions and instrumental variable properties. This method have many advantages.
Results and Discussion
In this study, the impact of population aging on air pollution was investigated using the GMM in Iran during the period of 1981-2020. The estimation of the model indicates that increasing the age of the population and the transition of the age structure of the population to the aging stage has a negative effect on air pollution. As it is predicted, Iran will face the problem of population aging in the next few years. According to the results, with increasing population, it can be expected that air pollution and environmental degradation will decrease. Due to the negative coefficient of the per capita income squared, the Kuznets environmental hypothesis is confirmed by considering the age structure of the population. In addition, urbanization, industrialization, trade openness, pollution of the previous period have positive and significant effects on air pollution.
The results indicate an inverted U-shaped EKC pattern between environmental degradation (pollution emissions) and per capita income (economic growth); therefore, it can be concluded that environmental degradation initially increases with increasing per capita income in a country, but after reaching a certain level of economic growth, environmental degradation stops and then decreases. Therefore, the results confirm the Kuznets environmental hypothesis for Iran. Based on this, it is recommended that the government design its plans with environmental considerations, especially air pollution. The results indicate that population aging has a significant negative effect on air pollution emissions. Population aging is detrimental to a country's economy and although it is inevitable for any country, policies to increase the number of elderly people in the population mix cannot be formulated and implemented even though it reduces air pollution levels. However, the harm caused by population aging outweighs this benefit. Of course, recently topics such as "active aging" have been raised to deal with population aging logically and should be on policymakers' agenda given the transition of age structure and movement towards aging in future years.
Conclusion
Based on the evidence of Iran's population age distribution during the period under study, it can be said that in future decades, older individuals will make up a higher percentage of the total population. This will lead to a reduction in carbon dioxide pollution automatically without government intervention or any other actions. The results of this study also show that urbanization and industrialization have positive impacts on air pollution. This result indicates that with the increase in the number of industrial enterprises and the trend towards urbanization in Iran, air pollution has increased. The reason for this is that most industries in Iran are energy-intensive and use fossil fuels. Another reason is the outdated technology with low efficiency in production. Other research findings show that pollution from previous periods and trade liberalization have positive effects on air pollution. The policy of economic liberalization by creating division of labor and using advantages, increasing capacity utilization in industries, increasing capital formation rates, changing technology, and creating competition in international markets lead to higher productivity levels for all production factors at a higher level.
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.
Dr. Amir Hallaji, Dr Saleh Ghavidel, Dr Masoud Soufi Majidpour, Dr Ali Abbas Heydari,
Volume 24, Issue 1 (3-2024)
Volume 24, Issue 1 (3-2024)
Abstract
Introduction:
Iran's economy will become bigger in the coming years and the GDP will increase every year. Therefore, the economy will need more labor force, which is provided through population growth. Now this question is raised, will population growth be enough for Iran's future economic growth?
During the last 50 years, the situation of Iran's labor market has been such that the supply has increased over the demand, so unemployment has been one of the chronic problems of Iran. For example, the active population in 2021 was about 25.8 million people, of which 2.3 million were unemployed and 23.5 million were employed, that is, the unemployment rate was 9.2% (Statistical Center of Iran, Results of the 2021 Labor Force Survey Plan), but the population outlook in Iran shows major changes in the coming years. This research shows that in the future, the labor market of Iran will not experience unemployment, rather the possibility of labor force shortage will not be surprising. In this article, the supply of and demand for labor in Iran are estimated until 2050, then the gap between the two is predicted.
Methodology:
To predict the labor supply, first, the population by age has been estimated using the cohort method until 2050. Then we consider two scenarios for the labor force participation rate. First, it is assumed that the labor force participation rate will be constant until the year 2050. Second, it is assumed that the participation rate will increase along the trend of "average years of education of women". With the availability of the participation rate and the working age population (15-64), the active population has been estimated until 2050.
The demand for labor is estimated according to the production elasticity of employment. With the assumption of this elasticity and the assumption of economic growth at least level for Iran's economy, labor demand is predicted. The average production elasticity of employment in Iran is about 0.7, which means that with economic growth of 1%, the demand for labor increases by 0.7%. Assuming that this elasticity is constant until 2050 and considering the scenario for economic growth (minimum economic growth), the labor demand is estimated for the next 30 years.
Findings:
A realistic scenario that predicts the labor force participation rate in line with the trend of "average years of education for women", the active population is predicted to be 30.35 million in 2050. On the other hand, by using the output elasticity of employment and two scenarios for Iran's economic growth, the demand for the labor force has been predicted until 2050. Assuming an average economic growth, 2.6% per year and an output elasticity, 0.7, the demand for labor in 2050 is predicted to be around 40.26 million people. With a realistic scenario, the results show that there is unemployment in Iran until 2030, although the trend is decreasing. In 2030, unemployment will reach zero, which means labor supply and demand will be equal. From 2030 onwards, the excess demand for the labor force begins with an increasing trend, so that in 2050 the excess demand for the labor force reaches about 10 million people.
Discussion and Conclusion:
In this research, labor supply and demand have been predicted using very conservative and reasonable assumptions. The results show that with a minimum economic growth rate (1% per year) and the maximum increase in the labor force participation rate up to 50% in 2050, there will still be a lack of labor demand. There are three ways to reduce excess demand. The first is to increase productivity. Through improving technology and human capital through education, health, skills, etc., labor productivity can be increased. With the improvement of technology and the use of advanced machines, the use of robots, the mechanization of various economic sectors, and the use of artificial intelligence (IA), the majority of excess demand can be provided. The second is to use of foreign labor. Many countries use the supply excess of foreign labor from countries that face supply excess to offset their excess demand. The third way is to increase the labor force participation rate of women in Iran.
It should be noted that the assumption of other conditions is always met in any forecasting. Among these conditions are sanctions, oil exports, technology, environmental changes, and so forth. For example, if the sanctions are lifted, Iran's economic growth can up to 7 percent annually. Higher economic growth leads to higher demand for labor, and excess demand occurs sooner. Therefore, changing any of the unexpected factors in the future can increase or decrease the forecast of supply and demand.
Iran's economy will become bigger in the coming years and the GDP will increase every year. Therefore, the economy will need more labor force, which is provided through population growth. Now this question is raised, will population growth be enough for Iran's future economic growth?
During the last 50 years, the situation of Iran's labor market has been such that the supply has increased over the demand, so unemployment has been one of the chronic problems of Iran. For example, the active population in 2021 was about 25.8 million people, of which 2.3 million were unemployed and 23.5 million were employed, that is, the unemployment rate was 9.2% (Statistical Center of Iran, Results of the 2021 Labor Force Survey Plan), but the population outlook in Iran shows major changes in the coming years. This research shows that in the future, the labor market of Iran will not experience unemployment, rather the possibility of labor force shortage will not be surprising. In this article, the supply of and demand for labor in Iran are estimated until 2050, then the gap between the two is predicted.
Methodology:
To predict the labor supply, first, the population by age has been estimated using the cohort method until 2050. Then we consider two scenarios for the labor force participation rate. First, it is assumed that the labor force participation rate will be constant until the year 2050. Second, it is assumed that the participation rate will increase along the trend of "average years of education of women". With the availability of the participation rate and the working age population (15-64), the active population has been estimated until 2050.
The demand for labor is estimated according to the production elasticity of employment. With the assumption of this elasticity and the assumption of economic growth at least level for Iran's economy, labor demand is predicted. The average production elasticity of employment in Iran is about 0.7, which means that with economic growth of 1%, the demand for labor increases by 0.7%. Assuming that this elasticity is constant until 2050 and considering the scenario for economic growth (minimum economic growth), the labor demand is estimated for the next 30 years.
Findings:
A realistic scenario that predicts the labor force participation rate in line with the trend of "average years of education for women", the active population is predicted to be 30.35 million in 2050. On the other hand, by using the output elasticity of employment and two scenarios for Iran's economic growth, the demand for the labor force has been predicted until 2050. Assuming an average economic growth, 2.6% per year and an output elasticity, 0.7, the demand for labor in 2050 is predicted to be around 40.26 million people. With a realistic scenario, the results show that there is unemployment in Iran until 2030, although the trend is decreasing. In 2030, unemployment will reach zero, which means labor supply and demand will be equal. From 2030 onwards, the excess demand for the labor force begins with an increasing trend, so that in 2050 the excess demand for the labor force reaches about 10 million people.
Discussion and Conclusion:
In this research, labor supply and demand have been predicted using very conservative and reasonable assumptions. The results show that with a minimum economic growth rate (1% per year) and the maximum increase in the labor force participation rate up to 50% in 2050, there will still be a lack of labor demand. There are three ways to reduce excess demand. The first is to increase productivity. Through improving technology and human capital through education, health, skills, etc., labor productivity can be increased. With the improvement of technology and the use of advanced machines, the use of robots, the mechanization of various economic sectors, and the use of artificial intelligence (IA), the majority of excess demand can be provided. The second is to use of foreign labor. Many countries use the supply excess of foreign labor from countries that face supply excess to offset their excess demand. The third way is to increase the labor force participation rate of women in Iran.
It should be noted that the assumption of other conditions is always met in any forecasting. Among these conditions are sanctions, oil exports, technology, environmental changes, and so forth. For example, if the sanctions are lifted, Iran's economic growth can up to 7 percent annually. Higher economic growth leads to higher demand for labor, and excess demand occurs sooner. Therefore, changing any of the unexpected factors in the future can increase or decrease the forecast of supply and demand.
| Page 1 from 1 |