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Showing 3 results for Gdp Per Capita
Dr Mahnaz Rabiei,
Volume 22, Issue 1 (3-2022)
Volume 22, Issue 1 (3-2022)
Abstract
Today, information and communication technology (ICT) has affected human societies in all dimensions. Despite its significant effects on the economic, political and social development of societies, this technology also has adverse effects. Among these effects, we can mention the background of information and communication technology on social actions and conflicts. Accordingly, in this study, using Autoregressive Distributed Lag method the effect of information and communication technology and income distribution (Gini coefficient) on social unrest was investigated in Iran during the period 1984-2018. The Internal Conflict Index presented by the ICRG Political Risk Index was used as a proxy for social unrest. The results showed that information and communication technology and unfair income distribution significantly increases social unrest in Iran. As well as Inflation also significantly increases social unrest in Iran. However, GDP per capita has no significant effect on Iran's social unrest. Therefore, the policy of developing information and communication technology based on the internal Internet network, improving income distribution and curbing inflation in controlling Iran's social unrest seems necessary.
Mrs Fatemeh Arianfar, Dr Zahra (mila) Elmi,
Volume 24, Issue 2 (5-2024)
Volume 24, Issue 2 (5-2024)
Abstract
Introduction:
Economic stability via Information and Communication Technology (ICT) has sparked interesting discussions among scholars. ICT plays a crucial role in realizing sustainable development objectives. Globally, the prospective advantages of ICT are widely acknowledged. Some research has solely emphasized ICT's role in mitigating air pollution, but the ecological implications of ICT have largely been overlooked. This article is pioneering in domestic studies of ICT's influence on ecological footprint. In addition, the present research uniquely computes the ICT index through the principal component method, distinguishing it from other ICT studies conducted within Iran. In recent times, the ecological footprint has been embraced as a broader gauge for assessing environmental damage. One reason for this choice is that other environmental harm indicators, such as air and water pollution, deforestation, and others, only represent a part of the total environmental degradation. However, the ecological footprint index incorporates diverse elements like agricultural lands, pastures, fishing areas, forests, carbon footprint, and constructed lands, hence offering a more holistic measure. Concerning the topic in question, it is evident from national studies that there has been little research on identifying the factors contributing to the ecological footprint.
Methodology:
In this research, we investigate the impact of the information and communication technology (ICT) index on selected oil-exporting countries' ecological footprint from 2006 to 2020. To do this, we use the generalized moments method. We extracted the model of this research from the studies of Higon et al. (2017) and Caglar et al. (2021) for carbon dioxide emissions. The variables of our study include the ecological footprint (as the dependent variable), the information and communication technology index (an explanatory variable calculated using the principal component analysis (PCA) method), and control variables such as GDP per capita, exports of goods and services, financial development, and economic Complexity Index which is chosen on the review of other studies. The data used for this study are taken from databases such as the World Bank and the Global Resource Footprint Network and the Atlas of Economic Complexity.
Discussion and Conclusion:
Given the challenges posed by global warming to current and future generations, this study aims to explore the impact of Information and Communication Technology (ICT) on the ecological footprint in chosen oil-exporting nations. This study studied the inverse U relationship of the information and communication technology index with the emission of ecological footprints from 2006 to 2020. The ecological footprint is an index of the amount of environmental pollution and a more comprehensive index than CO2. A data description was undertaken before estimating the model. The research model, built on theoretical underpinnings and past studies, was structured, and estimated by the Generalized Moments Method.
The findings showed a non-linear connection between ICT and the ecological footprint in oil-exporting countries. ICT augments the ecological footprint per capita before a certain threshold, but it begins to diminish after that.
The positive and significant coefficient of GDP per capita indicates the increase in ecological footprint per capita for the increase of GDP per capita. This result indicates that economic activities such as industrialization and development cause the exploitation of natural resources, which causes more pollution.
Financial development has had a positive and significant effect on the ecological footprint. To prevent the destructive effect of financial development on the environment, governments in selected oil-exporting countries should develop financial markets in such a way that financial resources are available for investing in projects that help introduce clean energy technologies.
The economic complexity index has had a negative and significant effect on the per capita ecological footprint. In fact, the expansion of economic complexity in the studied countries will lead to the reduction of the ecological footprint. According to the obtained result, the economic complexity index can be considered as one of the ecological footprint control factors; Therefore, the production of more complex goods that contain higher technology can lead to a reduction in energy consumption and ecological footprint; Therefore, governments can provide tax exemptions and subsidies for those companies that use new technology and clean energy, and also support knowledge-based products.
The influence of goods and services exports on the ecological footprint has been negative and substantial. The significance of the quality and diversity of exported goods regarding environmental destruction has not yet been thoroughly considered. Therefore, the focus should be on enhancing the quality of export goods via cleaner production methods. Overall energy consumption should also be reduced in all countries, with policymakers prioritizing the use of renewable energy resources and promoting the reduction of fossil-fuel energy export products.
The influence of urban population growth on the ecological footprint has been positive and substantial. Essentially, uncontrolled population growth, especially in developing countries, creates grave issues including scarcity of food, poor air and water quality, environmental contamination, degradation of the ecological structure, waste disposal problems, and high energy usage.
Economic stability via Information and Communication Technology (ICT) has sparked interesting discussions among scholars. ICT plays a crucial role in realizing sustainable development objectives. Globally, the prospective advantages of ICT are widely acknowledged. Some research has solely emphasized ICT's role in mitigating air pollution, but the ecological implications of ICT have largely been overlooked. This article is pioneering in domestic studies of ICT's influence on ecological footprint. In addition, the present research uniquely computes the ICT index through the principal component method, distinguishing it from other ICT studies conducted within Iran. In recent times, the ecological footprint has been embraced as a broader gauge for assessing environmental damage. One reason for this choice is that other environmental harm indicators, such as air and water pollution, deforestation, and others, only represent a part of the total environmental degradation. However, the ecological footprint index incorporates diverse elements like agricultural lands, pastures, fishing areas, forests, carbon footprint, and constructed lands, hence offering a more holistic measure. Concerning the topic in question, it is evident from national studies that there has been little research on identifying the factors contributing to the ecological footprint.
Methodology:
In this research, we investigate the impact of the information and communication technology (ICT) index on selected oil-exporting countries' ecological footprint from 2006 to 2020. To do this, we use the generalized moments method. We extracted the model of this research from the studies of Higon et al. (2017) and Caglar et al. (2021) for carbon dioxide emissions. The variables of our study include the ecological footprint (as the dependent variable), the information and communication technology index (an explanatory variable calculated using the principal component analysis (PCA) method), and control variables such as GDP per capita, exports of goods and services, financial development, and economic Complexity Index which is chosen on the review of other studies. The data used for this study are taken from databases such as the World Bank and the Global Resource Footprint Network and the Atlas of Economic Complexity.
Discussion and Conclusion:
Given the challenges posed by global warming to current and future generations, this study aims to explore the impact of Information and Communication Technology (ICT) on the ecological footprint in chosen oil-exporting nations. This study studied the inverse U relationship of the information and communication technology index with the emission of ecological footprints from 2006 to 2020. The ecological footprint is an index of the amount of environmental pollution and a more comprehensive index than CO2. A data description was undertaken before estimating the model. The research model, built on theoretical underpinnings and past studies, was structured, and estimated by the Generalized Moments Method.
The findings showed a non-linear connection between ICT and the ecological footprint in oil-exporting countries. ICT augments the ecological footprint per capita before a certain threshold, but it begins to diminish after that.
The positive and significant coefficient of GDP per capita indicates the increase in ecological footprint per capita for the increase of GDP per capita. This result indicates that economic activities such as industrialization and development cause the exploitation of natural resources, which causes more pollution.
Financial development has had a positive and significant effect on the ecological footprint. To prevent the destructive effect of financial development on the environment, governments in selected oil-exporting countries should develop financial markets in such a way that financial resources are available for investing in projects that help introduce clean energy technologies.
The economic complexity index has had a negative and significant effect on the per capita ecological footprint. In fact, the expansion of economic complexity in the studied countries will lead to the reduction of the ecological footprint. According to the obtained result, the economic complexity index can be considered as one of the ecological footprint control factors; Therefore, the production of more complex goods that contain higher technology can lead to a reduction in energy consumption and ecological footprint; Therefore, governments can provide tax exemptions and subsidies for those companies that use new technology and clean energy, and also support knowledge-based products.
The influence of goods and services exports on the ecological footprint has been negative and substantial. The significance of the quality and diversity of exported goods regarding environmental destruction has not yet been thoroughly considered. Therefore, the focus should be on enhancing the quality of export goods via cleaner production methods. Overall energy consumption should also be reduced in all countries, with policymakers prioritizing the use of renewable energy resources and promoting the reduction of fossil-fuel energy export products.
The influence of urban population growth on the ecological footprint has been positive and substantial. Essentially, uncontrolled population growth, especially in developing countries, creates grave issues including scarcity of food, poor air and water quality, environmental contamination, degradation of the ecological structure, waste disposal problems, and high energy usage.
Dr Seyed Ehsan Hosseinidoust, Dr Akbar Khodabakhshi, Mrs Saeedeh Ahmadi,
Volume 24, Issue 4 (12-2024)
Volume 24, Issue 4 (12-2024)
Abstract
Aim and Introduction
Achieving a high GDP requires an answer to the question of the factors that determine GDP. Social progress is one of the important and influential factors on the GDP. The Social Development Index is a scale for measuring social well-being, which is a completely new way of looking at well-being among countries in the world without referring to GDP. On the other hand, considering the fact that economic and social indicators must be improved as preconditions for increased living standards, which would be only possible in the shadow of economic growth, assumes it as a critical component contributing into improvement of social indicators. In this study, the mutual relationship between social progress index and GDP per capita for selected member countries of the Organization of Islamic Cooperation, during the period of 2012-2021 is investigated. The countries studied in this research are: Albania, Algeria, Azerbaijan, Bahrain, Bangladesh, Benin, Cameroon, Egypt, Guinea, Indonesia, Iran, Jordan, Kazakhstan, Kyrgyzstan, Lebanon, Malaysia, Mali, Mozambique, Niger, Nigeria, Oman, Pakistan, Saudi Arabia, Senegal, Tunisia, Turkey and UAE. Since the member countries of the Organization of Islamic Cooperation are developing countries, due to problems such as lack of human skills, inefficiency in production, lack of technological development, as well as the lack of expertise needed to produce and export competitive goods, have not been able to make significant progress in economic growth and development. Therefore, it seems that in these countries, development can be realized with social progress by paying attention to the issue of education and the basic needs of human resources in order to form and develop human capital. Investing more in human power has increased the level of productivity of production factors and technological development, and in this way, it is able to provide the necessary ground for the development of international trade and to achieve higher economic growth.
Methodology
In this research, the statistics related to social progress and GDP per capita in 27 member countries of the Organization of Islamic Cooperation, which are respectively taken from the social progress index and the World Bank in the years 2012 to 2021, have been used. In order to investigate the relationship between social progress and GDP, the simultaneous equation system approach in the form of the three-stage least square method (3SLS) has been applied` using Stata software. In the application of the system of simultaneous equations, it is necessary to have two recognizability conditions, which include the degree and rank condition. For this purpose, before estimating the model, these conditions have been examined first, and then preliminary tests of the model specification, such as the cross-sectional correlation test in the disturbance component, the unit root test of the combined data, the cointegration and endogeneity test have been performed.
Findings
The results of the data estimation over the period showed that in the model of GDP, social progress index, economic freedom and government consumption expenditure have an increasing and significant effect on the GDP per capita of the studied countries. The trade openness variable also has a negative and non-significant effect on GDP per capita. In the model related to the social progress index, the global innovation index, education index and GDP per capita have a positive and significant effect on the social progress index. The urban population variable also has a negative and insignificant effect on the social progress index.
Discussion and Conclusion
The results of the model estimation show that the social progress index variable in the per capita GDP model has the greatest impact on the per capita GDP among other influencing variables. The contribution of social progress into the performance of the economy and development process can be considered through reducing inequality and poverty, increasing market efficiency, economic growth, reducing costs, increasing the efficiency of human resources and capital, creating economic institutions and organizations and improving their performance, and increasing investment and employment, as well as increasing innovation and technology. The results of the estimation of the social progress index model also show the presence of a positive and significant effect of GDP per capita on the social progress index. In other words, with the increase of GDP per capita, many basic human needs such as nutrition and health care, water, health, shelter and personal safety, which is one of the indicators of social progress, are improved. In addition, in the mentioned model, the education index among other influential variables has more weight in influencing the social progress index. In other words, manpower training improves welfare infrastructure as well as opportunities, which are two dimensions of the social progress index. Finally, according to the results obtained from both models, which confirm the existence of a positive and significant relationship between the social progress index and GDP per capita, it can be concluded that there is a complementary relationship between these two variables
Achieving a high GDP requires an answer to the question of the factors that determine GDP. Social progress is one of the important and influential factors on the GDP. The Social Development Index is a scale for measuring social well-being, which is a completely new way of looking at well-being among countries in the world without referring to GDP. On the other hand, considering the fact that economic and social indicators must be improved as preconditions for increased living standards, which would be only possible in the shadow of economic growth, assumes it as a critical component contributing into improvement of social indicators. In this study, the mutual relationship between social progress index and GDP per capita for selected member countries of the Organization of Islamic Cooperation, during the period of 2012-2021 is investigated. The countries studied in this research are: Albania, Algeria, Azerbaijan, Bahrain, Bangladesh, Benin, Cameroon, Egypt, Guinea, Indonesia, Iran, Jordan, Kazakhstan, Kyrgyzstan, Lebanon, Malaysia, Mali, Mozambique, Niger, Nigeria, Oman, Pakistan, Saudi Arabia, Senegal, Tunisia, Turkey and UAE. Since the member countries of the Organization of Islamic Cooperation are developing countries, due to problems such as lack of human skills, inefficiency in production, lack of technological development, as well as the lack of expertise needed to produce and export competitive goods, have not been able to make significant progress in economic growth and development. Therefore, it seems that in these countries, development can be realized with social progress by paying attention to the issue of education and the basic needs of human resources in order to form and develop human capital. Investing more in human power has increased the level of productivity of production factors and technological development, and in this way, it is able to provide the necessary ground for the development of international trade and to achieve higher economic growth.
Methodology
In this research, the statistics related to social progress and GDP per capita in 27 member countries of the Organization of Islamic Cooperation, which are respectively taken from the social progress index and the World Bank in the years 2012 to 2021, have been used. In order to investigate the relationship between social progress and GDP, the simultaneous equation system approach in the form of the three-stage least square method (3SLS) has been applied` using Stata software. In the application of the system of simultaneous equations, it is necessary to have two recognizability conditions, which include the degree and rank condition. For this purpose, before estimating the model, these conditions have been examined first, and then preliminary tests of the model specification, such as the cross-sectional correlation test in the disturbance component, the unit root test of the combined data, the cointegration and endogeneity test have been performed.
Findings
The results of the data estimation over the period showed that in the model of GDP, social progress index, economic freedom and government consumption expenditure have an increasing and significant effect on the GDP per capita of the studied countries. The trade openness variable also has a negative and non-significant effect on GDP per capita. In the model related to the social progress index, the global innovation index, education index and GDP per capita have a positive and significant effect on the social progress index. The urban population variable also has a negative and insignificant effect on the social progress index.
Discussion and Conclusion
The results of the model estimation show that the social progress index variable in the per capita GDP model has the greatest impact on the per capita GDP among other influencing variables. The contribution of social progress into the performance of the economy and development process can be considered through reducing inequality and poverty, increasing market efficiency, economic growth, reducing costs, increasing the efficiency of human resources and capital, creating economic institutions and organizations and improving their performance, and increasing investment and employment, as well as increasing innovation and technology. The results of the estimation of the social progress index model also show the presence of a positive and significant effect of GDP per capita on the social progress index. In other words, with the increase of GDP per capita, many basic human needs such as nutrition and health care, water, health, shelter and personal safety, which is one of the indicators of social progress, are improved. In addition, in the mentioned model, the education index among other influential variables has more weight in influencing the social progress index. In other words, manpower training improves welfare infrastructure as well as opportunities, which are two dimensions of the social progress index. Finally, according to the results obtained from both models, which confirm the existence of a positive and significant relationship between the social progress index and GDP per capita, it can be concluded that there is a complementary relationship between these two variables
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