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Showing 11 results for Economic Complexity
Volume 1, Issue 4 (12-2023)
Abstract
Today, carbon dioxide emission is one of the concerns of all countries in the world, so in this paper, we examine the effect of export quality, energy efficiency, and economic complexity on CO2 emissions per capita during the period of 1990 to 2014 in emerging economies. For this purpose, first, energy efficiency is calculated using mathematical programming methods (DEA). Then, the effect of export quality, energy efficiency, and economic complexity on per capita carbon dioxide emissions in the panel of emerging economies is investigated using panel quantile regression. The energy efficiency results show that the average energy efficiency of the studied countries had been increasing from 1990 to 2014. The lowest efficiency score among the studied countries is related to China. The results of quantile regression indicate that the export quality and consumption per capita of fossil fuels have a positive and significant effect on CO2 emissions per capita in all quantiles. The results also show that the coefficient increases by moving in the level of quantiles, so that, the highest effect coefficient of export quality on CO2 emission is related to the quantile 90th and about 0.874. Energy efficiency has a negative and significant effect in all quantiles except 90th, and the highest coefficient of influence (0.133) is related to quantile 10th. The increase in economic complexity increases the co2 emissions in all quantiles except 10th, and the highest coefficient (about 0.487) is related to quantile 90th.
Volume 10, Issue 3 (1-2021)
Abstract
Despite the importance of diversification and industrial development, finding a suitable way to determine homogeneity and relevance is one of the main challenges in implementing this type of strategy. For this reason, applied studies using new methods of determining homogeneity seems necessary for solving real problems in the world of policy and strategy. Therefore, the purpose of this research is to identify products that are homogenous with the current products of the country's parts and equipment manufacturing industry. The method used in this research is the economic complexity approach that identifies homogenous production opportunities with the current capabilities of the Iranian parts and equipment manufacturing industry, based on the export data of 669 commodity codes under the parts and equipment manufacturing industry between years 2002 to 2017. The findings of this study indicate the existence of 28 homogenous production opportunities with the current situation of Iran's parts and equipment manufacturing industry, which moving towards them will make the industry more diverse and complex. By producing these products, technological capabilities can be accumulated, and more export earnings can be achieved. Accordingly, the production of some types of turbines, engines, vehicle parts, tubes, machine parts and locomotives constitute a significant part of production opportunities in line with the Iranian parts and equipment manufacturing industry. Findings and methods used in this article can be used as a practical guide by industry policymakers and managers.
ّFormation and development of full-time animal husbandry in Korrivers areas during the Banesh period
Volume 12, Issue 1 (8-2020)
Abstract
Abstract:
Banesh cultural period in South of Iran is considered a vital phase in increasing socio-economic complexities in second half of fourth millennium (BC). Manufacture and specialty distribution of industrial& nutritional products, along with a change in settlement patterns and ecological strategies, demonstrate a pervasive regional evolution which establish a different system in Baneshi community of Kor River Basin. In the meantime,some archeological evidence depicts features of a specialty community in the field of manufacturing and distribution of animal products, beside agricultural and industrial communities of this Basin in a way that its existence as a modern phenomenon is affected by economical complexity in mentioned time and place period. The present paper depicts the formation and expansion of full- time pastoralism in articulation of socio-economic system of this era and represents an explanation for the evolution of productive strategies and formation of ways to exchange animal products by applying middle-range approach and historical - ethnological analogy.
Banesh cultural period in South of Iran is considered a vital phase in increasing socio-economic complexities in second half of fourth millennium (BC). Manufacture and specialty distribution of industrial& nutritional products, along with a change in settlement patterns and ecological strategies, demonstrate a pervasive regional evolution which establish a different system in Baneshi community of Kor River Basin. In the meantime,some archeological evidence depicts features of a specialty community in the field of manufacturing and distribution of animal products, beside agricultural and industrial communities of this Basin in a way that its existence as a modern phenomenon is affected by economical complexity in mentioned time and place period. The present paper depicts the formation and expansion of full- time pastoralism in articulation of socio-economic system of this era and represents an explanation for the evolution of productive strategies and formation of ways to exchange animal products by applying middle-range approach and historical - ethnological analogy.
Dr Hoda Zobeiri, Dr Mani Motameni,
Volume 20, Issue 3 (9-2020)
Volume 20, Issue 3 (9-2020)
Abstract
Economic complexity reflects the capabilities of a country and determines the level of economic growth and development. Investing in knowledge and human capital due to increasing the capabilities of economic actors is essential to achieve a complex economy. This paper examines the relationship between human capital and economic complexity in Iran during 1971-2017. Empirical analysis shows that primary school enrollment has no significant correlation to economic complexity. In addition, R&D expenditure as percentage of GDP has no significant relation to economic complexity. According to Johansen-Juselius co-integration test there is no co-integrating relationship between the variables under study. However, government expenditure on tertiary education as percentage of GDP, shown by TR, is co-integrated with economic complexity. Based on Granger causality test, there is a unidirectional causality from TR to economic complexity. Impulse response analysis indicates that economic complexity responses to TR after three years. If spending on higher education increases by 10 percent, the economic complexity index will increase by 11 percent.
Mr. Ramin Sepahvand, Dr Ali Sayehmiri, Mrs. Asma Shirkhani,
Volume 21, Issue 3 (9-2021)
Volume 21, Issue 3 (9-2021)
Abstract
In recent years, economic complexity has played an important role in explaining and revealing the latent facts of the difference in economic growth among the poor and rich countries. In this study, first the effect of economic complexity on environmental performance is investigated in 18 countries of Middle East and North Africa(MENA) using two-stage least squares regression(2SLS) method during 2002-2018. Then, the Environmental Kuznets Curve hypothesis is examined in these countries. The results show an inverse and significant relationship between economic complexity index and environmental performance index, so that by increasing one unit of economic complexity index, environmental performance index decreases by more than 7 units. In addition, the results show that there is a positive relationship between per capita income and environmental performance index, while per capita income square has an inverse relationship with environmental performance index, so Kuznets hypothesis about these countries is not confirmed. Finally, the results indicate a positive relationship between population, urbanization, corruption control, agriculture and trade with environmental performance, while industrialization and education have a negative relationship with environmental performance in the MENA countries.
Dr. Monireh Rafat, Dr. Saeedeh Ahmadi,
Volume 23, Issue 3 (8-2023)
Volume 23, Issue 3 (8-2023)
Abstract
Aims and Introduction:
An economy that is based on simple production is under threat every moment. Therefore, one of the central strategies in the realization of economic growth and development is to rely on the production and export of complex and knowledge-based products. In complex societies, people with different knowledge must be able to communicate and combine their knowledge to produce a product. Economic complexity in relation to the composition of a country's products expresses a set of abilities to combine knowledge and skills. Therefore, societies lacking this set of abilities fail to produce complex products. Accordingly, the main goal of this article is to investigate the effect of economic complexity index on Iran's GDP.
Methodology:
In this research, seasonal data over the period 1995-2019 have been used in Iran, and Bayesian vector auto-regression (BVAR) model with Minnesota prior distribution has been used to investigate the effect of economic complexity on the level of GDP. The Bayesian vector auto-regression model provides more reliable predictions on the relationship between economic complexity and the level of GDP, due to the reduction of model parameters and the consideration of prior functions.
Results and Discussion:
The results of the instantaneous reaction function of the level of gross domestic product (GDP) to the shock of the economic complexity index (ECI) show that this shock has a negative reaction on the level of GDP. Therefore, the impact of the economic complexity index shock on the level of GDP is negative in the long term. In addition, the results show that the financial freedom index (FIS) shock increases the level of GDP in the long term. The response of GDP to the shock of the Investment Freedom Index (INV) is also very weak and almost neutral during 10 periods. The reaction of the GDP level to the shock of the business freedom index (BUS) is negative. The effect of the corruption index shock (COR) on the GDP level is negative, and the reaction of the GDP level to the bank credits to the private sector (CRDT) shock indicates the negative effect of this shock on the GDP level. The reaction of the GDP level to the inflation shock (INF) is negative during the period under review. The effect of the shock of trade openness (OPN) on the level of GDP is positive and low during 10 periods. This means that the trade openness shock increases the level of GDP in the long run. In addition, the reaction of the GDP level to the domestic direct investment (FDI) shock is positive. The results of the variance analysis also show that the shock variables of the economic Freedom Index (ECON), Foreign Direct Investment (FDI) and Inflation (INF), have the greatest impact on the GDP level, respectively. The variable shock of investment freedom index (INV) also has the least effect on the dependent variable.
Conclusion:
The results show that the economic complexity index shock has a negative effect on the GDP level. According to Kremer's O-ring theory, greater complexity with increased specialized tasks and responsibilities leads to reduced production. In other words, when the production of goods is followed in a specialized manner, there is a possibility that in some stages of production, human capital and labor will not have the necessary ability to produce goods with high complexity due to lack of knowledge and skills. As a result, it causes a decrease in the production level. Therefore, the diversity of knowledge and skills in the production of products must be accompanied by the production of complex products. Iran's low rank in the economic complexity index shows the simplicity of the economy and the existence of structural weaknesses as well as vulnerability in the production and export structure. Therefore, in order to achieve economic complexity in the export portfolio and increase the level of production of products, the process of converting theoretical and scientific knowledge into complex and knowledge -based products should be followed with appropriate foundation.
Mrs. Najme Mohammadi, Dr. Bahram Sahabi, Dr. Hassan Heydari, Dr. Hossein Sadeghi,
Volume 23, Issue 4 (12-2023)
Volume 23, Issue 4 (12-2023)
Abstract
Aim and Introduction
Technology provides an opportunity for the economy to move from polluting sources to renewable sources to meet energy needs. Increasing economic complexity means more use of technology and innovation in production and may cause the expansion of effective technological products such as renewable energy. In the past few decades, the share of renewable energy has increased due to a wide range of factors, such as government regulations to promote the use of renewable energy, reduction in the cost of installing renewable energy and increasing production capacity, oil price fluctuations, and the positive effects of renewable energy in reducing emissions. Carbon and innovation processes have increased in the energy sector. Therefore, in this research, the effects of renewable energy consumption and economic complexity as well as their mutual effects on environmental pollution have been investigated using the GMM method in developing countries over the period 2000-2019.
Methodology
In dynamic models, due to the presence of a lagged dependent variable, OLS or GLS methods cannot be used to estimate the model, because the disturbance components are correlated with the lagged dependent variable, and the estimation results are biased and inconsistent as before. Therefore, to solve this problem, the GMM method proposed by Arellano and Bond (1991) is used. The GMM estimator belongs to the set of instrumental variables’ estimators. In this method, in addition to solve the problem of the correlation of the independent variable with disturbance components, the endogeneity of the variables and the heteroscedasticity of the variances are also removed. It should be noted that this method is applicable when T (number of periods) is smaller than N (number of sections).
Results
The results show that the economic complexity index has a negative and significant effect on carbon dioxide emissions in developing countries. Variables such as trade openness and energy intensity increase carbon dioxide emissions, and the Kuznets curve hypothesis is confirmed for developing countries, and economic complexity leads to an upward movement of the Kuznets curve. Renewable energy consumption has a significant effect on reducing carbon dioxide emissions, and also at higher levels of economic complexity, renewable energy consumption causes a greater reduction in carbon dioxide emissions.
Conclusion and Discussion
The need for a more accurate understanding of economic phenomena has prompted economists to review previous theories and present new theories that have a new window to economic development literature. The goal of all countries is to achieve sustainable economic growth and development. Renewable energy technologies are promising, but there is very little information about its role as a limiting factor in reducing environmental pollution, especially in developing countries. Therefore, in this research, the effects of renewable energy consumption and economic complexity as well as their mutual effects on environmental pollution have been investigated using the GMM method in developing countries over the period 2000-2019. The results show that the economic complexity index has a negative and significant effect on the emission of carbon dioxide, so it can be said that for developing countries, moving towards a more knowledge-oriented economy can improve the quality of the environment. The variables of trade openness, energy intensity significantly affect positively CO2 emissions. The EKC hypothesis was confirmed with the positive logarithm of GDP per capita and its negative square coefficient. According to the results of the study, economic complexity in countries under study leads to an upward movement of EKC, which means that as economic complexity increases in developing countries due to increased energy demand, scale effects occur and lead to higher CO2 emissions.
In this study, energy intensity has a positive effect on the increase in carbon dioxide emissions and as a result the increase in environmental pollution in developing countries.
The specific result of this article is the significant effect of renewable energy consumption on the reduction of carbon dioxide emissions in developing countries. At higher levels of economic complexity, renewable energy consumption causes a greater reduction in CO2 emissions. In terms of the role of complexity, it can be argued that in countries under consideration, the share of renewable energy should be significantly increased by using innovation processes in the energy sector. Considering the negative effects of the share of renewable energies on carbon dioxide emissions per capita, it is suggested to define new patterns of energy consumption by relying on renewable energies in development programs and using incentive tools to replace renewable energies instead of fossil fuels to reduce pollution. Developing countries should support knowledge-based industries, increase the import and production of environmentally friendly technologies, and increase the share of renewable energy in their plans to protect the environment. In addition, pricing strategies can be proposed to avoid increased fossil fuel consumption.
Technology provides an opportunity for the economy to move from polluting sources to renewable sources to meet energy needs. Increasing economic complexity means more use of technology and innovation in production and may cause the expansion of effective technological products such as renewable energy. In the past few decades, the share of renewable energy has increased due to a wide range of factors, such as government regulations to promote the use of renewable energy, reduction in the cost of installing renewable energy and increasing production capacity, oil price fluctuations, and the positive effects of renewable energy in reducing emissions. Carbon and innovation processes have increased in the energy sector. Therefore, in this research, the effects of renewable energy consumption and economic complexity as well as their mutual effects on environmental pollution have been investigated using the GMM method in developing countries over the period 2000-2019.
Methodology
In dynamic models, due to the presence of a lagged dependent variable, OLS or GLS methods cannot be used to estimate the model, because the disturbance components are correlated with the lagged dependent variable, and the estimation results are biased and inconsistent as before. Therefore, to solve this problem, the GMM method proposed by Arellano and Bond (1991) is used. The GMM estimator belongs to the set of instrumental variables’ estimators. In this method, in addition to solve the problem of the correlation of the independent variable with disturbance components, the endogeneity of the variables and the heteroscedasticity of the variances are also removed. It should be noted that this method is applicable when T (number of periods) is smaller than N (number of sections).
Results
The results show that the economic complexity index has a negative and significant effect on carbon dioxide emissions in developing countries. Variables such as trade openness and energy intensity increase carbon dioxide emissions, and the Kuznets curve hypothesis is confirmed for developing countries, and economic complexity leads to an upward movement of the Kuznets curve. Renewable energy consumption has a significant effect on reducing carbon dioxide emissions, and also at higher levels of economic complexity, renewable energy consumption causes a greater reduction in carbon dioxide emissions.
Conclusion and Discussion
The need for a more accurate understanding of economic phenomena has prompted economists to review previous theories and present new theories that have a new window to economic development literature. The goal of all countries is to achieve sustainable economic growth and development. Renewable energy technologies are promising, but there is very little information about its role as a limiting factor in reducing environmental pollution, especially in developing countries. Therefore, in this research, the effects of renewable energy consumption and economic complexity as well as their mutual effects on environmental pollution have been investigated using the GMM method in developing countries over the period 2000-2019. The results show that the economic complexity index has a negative and significant effect on the emission of carbon dioxide, so it can be said that for developing countries, moving towards a more knowledge-oriented economy can improve the quality of the environment. The variables of trade openness, energy intensity significantly affect positively CO2 emissions. The EKC hypothesis was confirmed with the positive logarithm of GDP per capita and its negative square coefficient. According to the results of the study, economic complexity in countries under study leads to an upward movement of EKC, which means that as economic complexity increases in developing countries due to increased energy demand, scale effects occur and lead to higher CO2 emissions.
In this study, energy intensity has a positive effect on the increase in carbon dioxide emissions and as a result the increase in environmental pollution in developing countries.
The specific result of this article is the significant effect of renewable energy consumption on the reduction of carbon dioxide emissions in developing countries. At higher levels of economic complexity, renewable energy consumption causes a greater reduction in CO2 emissions. In terms of the role of complexity, it can be argued that in countries under consideration, the share of renewable energy should be significantly increased by using innovation processes in the energy sector. Considering the negative effects of the share of renewable energies on carbon dioxide emissions per capita, it is suggested to define new patterns of energy consumption by relying on renewable energies in development programs and using incentive tools to replace renewable energies instead of fossil fuels to reduce pollution. Developing countries should support knowledge-based industries, increase the import and production of environmentally friendly technologies, and increase the share of renewable energy in their plans to protect the environment. In addition, pricing strategies can be proposed to avoid increased fossil fuel consumption.
Dr Bakhtiar Javaheri, Dr Saman Ghaderi, Mrs. Nikoo Ghomashi, Mr. Ramin Amani,
Volume 24, Issue 1 (3-2024)
Volume 24, Issue 1 (3-2024)
Abstract
Economic growth is one of the most common goals in both developed and developing countries. Economic growth affects various economic and social aspects, such as poverty, welfare, unemployment, and inflation. Knowing the factors influencing economic growth is critical for developing countries. Trade of goods and services affects economic growth by increasing national income. On the other hand, nowadays, the world is facing the climate change crisis and its consequences, such as floods, landslides, earthquakes, etc., which can have negative and destructive effects on economic growth. Oil exporting countries have weak export diversity due to single-product trade and are located in the hot and dry orbit of the globe due to their geographical location. The main goal of this study is to investigate the impact of economic complexity as a symbol of international trade and ecological footprint as a symbol of climate change on economic growth in OPEC from 1995 to 2020 and using the method of generalized method of moments (GMM). The results indicate a positive and very significant effect of the economic complexity index on economic growth in oil-exporting countries. On the other hand, the ecological footprint has a negative and significant impact on economic growth in OPEC.
Introduction:
Economic growth and development are main goals in developing countries, because achieving growth and development can increase living standards, increase people's well-being, reduce the level of poverty and unemployment, and consequently strengthen the foundations of governments. Knowing the factors affecting economic growth is one of the critical goals of economic policymakers (Rahimi et al., 2020). In previous studies, much research has focused on the influence of capital, labor, and productivity on economic growth. However, less attention has been paid to other factors. Today, it is clear that export diversification, which is an essential criterion of economic complexity, has a substantial effect on economic growth. On the other hand, the world today is facing climate change, which results from destructive human activities and has very adverse effects on economic growth. Therefore, the main goal of this research is to investigate the effect of economic complexity and ecological footprint on economic growth in OPEC from 1995 to 2020 using the generalized method of moments. In this research, the effect of economic complexity on economic growth in the developing countries of the OPEC organization has been investigated for the first time. On the other hand, in this innovative research, the ecological footprint variable was used to proxy climate change.
Methodology:
There are two methods for estimating model in dynamic panel data. The basic premise of GMM is called the first-order differential method. By imposing some changes to the first-order differential GMM method, the orthogonal deviation GMM method was obtained. In this research, both one- and two-step methods have been used to prevent single effects. Two tests are proposed to ensure the appropriateness of using this method for estimating the model. Initially, the Sargan test is used to demonstrate the validity of instrumental variables. The second test includes the first-order correlation test AR (1) and the second-order AR (2).
Results and Discussion:
The economic complexity index (ECI) in all three models with fixed effects, single-stage GMM, and two-stage GMM has a positive and significant effect on economic growth in OPEC. A one-unit increase in the economic complexity index increases the economic growth of OPEC by 0.028 units in the fixed effects model, 0.032 units in the single-stage GMM, and 0.154 units in the two-stage GMM. The ecological footprint (EF) index in three mentioned models has a negative and significant effect on economic growth in OPEC. A one-unit increase in the ecological footprint index causes a decrease of -0.013 units in the model with fixed effects, -0.038 units in the single-stage GMM, and -0.087 units in the two-stage GMM. The labor force (L), as the main variables of the Solo growth model, has a positive and significant effect on economic growth in OPEC in all models. A one-unit increase in the labor force index causes economic growth by 0.029, 0.028, and 0.055 in models with fixed effects, one-stage GMM, and two-stage GMM, respectively. Gross fixed capital, which is used as capital (K) in this study, has a positive and significant effect on economic growth in OPEC in all three models. A one-unit increase in capital causes an increase in the economic growth of OPEC by 0.017 units in the model with fixed effects, 0.054 units in the single-stage GMM, and 0.163 units in the two-stage GMM, respectively. Productivity of production factors (T), which is also used as technology in some research, has a positive and significant effect on economic growth in OPEC so that a one-unit increase in productivity of production factors causes an increase in economic growth by 0.009, 0.044 and 0.072 units, respectively in the model with fixed effects, single-stage GMM and two-stage GMM.
Conclusion:
The results of the present study showed that in all three fixed effects models, one-stage GMM and two-stage GMM, the economic complexity index has a positive and significant effect on economic growth in OPEC. With the increase in economic complexity, countries' knowledge, technology, and innovation in producing various goods and services will increase. As a result, exports and economic growth will be positively affected. On the other hand, the economic complexity index, in addition to creating a positive effect on quantitative indicators, has a positive effect on qualitative indicators, including the quality of human resources, innovation, savings, and increasing productivity, which can again increase economic growth. On the other hand, in all three models of fixed effects, one-stage GMM and two-stage GMM, the ecological footprint index significantly negatively affects economic growth in OPEC. An increase in the ecological footprint index means the increase in the use of all the planet's natural resources to meet a country's needs, including food, clothing, housing, etc. With the increase in the use of land resources and in the long-term time horizon, the climate change crisis can increase. With the increase in floods, global warming, landslides, and other natural disasters, economic growth will be negatively affected.
Introduction:
Economic growth and development are main goals in developing countries, because achieving growth and development can increase living standards, increase people's well-being, reduce the level of poverty and unemployment, and consequently strengthen the foundations of governments. Knowing the factors affecting economic growth is one of the critical goals of economic policymakers (Rahimi et al., 2020). In previous studies, much research has focused on the influence of capital, labor, and productivity on economic growth. However, less attention has been paid to other factors. Today, it is clear that export diversification, which is an essential criterion of economic complexity, has a substantial effect on economic growth. On the other hand, the world today is facing climate change, which results from destructive human activities and has very adverse effects on economic growth. Therefore, the main goal of this research is to investigate the effect of economic complexity and ecological footprint on economic growth in OPEC from 1995 to 2020 using the generalized method of moments. In this research, the effect of economic complexity on economic growth in the developing countries of the OPEC organization has been investigated for the first time. On the other hand, in this innovative research, the ecological footprint variable was used to proxy climate change.
Methodology:
There are two methods for estimating model in dynamic panel data. The basic premise of GMM is called the first-order differential method. By imposing some changes to the first-order differential GMM method, the orthogonal deviation GMM method was obtained. In this research, both one- and two-step methods have been used to prevent single effects. Two tests are proposed to ensure the appropriateness of using this method for estimating the model. Initially, the Sargan test is used to demonstrate the validity of instrumental variables. The second test includes the first-order correlation test AR (1) and the second-order AR (2).
Results and Discussion:
The economic complexity index (ECI) in all three models with fixed effects, single-stage GMM, and two-stage GMM has a positive and significant effect on economic growth in OPEC. A one-unit increase in the economic complexity index increases the economic growth of OPEC by 0.028 units in the fixed effects model, 0.032 units in the single-stage GMM, and 0.154 units in the two-stage GMM. The ecological footprint (EF) index in three mentioned models has a negative and significant effect on economic growth in OPEC. A one-unit increase in the ecological footprint index causes a decrease of -0.013 units in the model with fixed effects, -0.038 units in the single-stage GMM, and -0.087 units in the two-stage GMM. The labor force (L), as the main variables of the Solo growth model, has a positive and significant effect on economic growth in OPEC in all models. A one-unit increase in the labor force index causes economic growth by 0.029, 0.028, and 0.055 in models with fixed effects, one-stage GMM, and two-stage GMM, respectively. Gross fixed capital, which is used as capital (K) in this study, has a positive and significant effect on economic growth in OPEC in all three models. A one-unit increase in capital causes an increase in the economic growth of OPEC by 0.017 units in the model with fixed effects, 0.054 units in the single-stage GMM, and 0.163 units in the two-stage GMM, respectively. Productivity of production factors (T), which is also used as technology in some research, has a positive and significant effect on economic growth in OPEC so that a one-unit increase in productivity of production factors causes an increase in economic growth by 0.009, 0.044 and 0.072 units, respectively in the model with fixed effects, single-stage GMM and two-stage GMM.
Conclusion:
The results of the present study showed that in all three fixed effects models, one-stage GMM and two-stage GMM, the economic complexity index has a positive and significant effect on economic growth in OPEC. With the increase in economic complexity, countries' knowledge, technology, and innovation in producing various goods and services will increase. As a result, exports and economic growth will be positively affected. On the other hand, the economic complexity index, in addition to creating a positive effect on quantitative indicators, has a positive effect on qualitative indicators, including the quality of human resources, innovation, savings, and increasing productivity, which can again increase economic growth. On the other hand, in all three models of fixed effects, one-stage GMM and two-stage GMM, the ecological footprint index significantly negatively affects economic growth in OPEC. An increase in the ecological footprint index means the increase in the use of all the planet's natural resources to meet a country's needs, including food, clothing, housing, etc. With the increase in the use of land resources and in the long-term time horizon, the climate change crisis can increase. With the increase in floods, global warming, landslides, and other natural disasters, economic growth will be negatively affected.
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.
Mrs Najme Mohamadi, Dr Bahram Sahabi, Dr Hassan Heydari, Dr Hosin Sadeghi,
Volume 24, Issue 2 (5-2024)
Volume 24, Issue 2 (5-2024)
Abstract
Introduction
Economic complexity is an index that has been raised in the last decade and indicates the use of technology in the process of producing goods and services of a country, which leads to increased economic growth and prosperity by creating a productive structure in the composition, increased productivity and diversity of manufactured products. Economic complexity is expected to affect energy consumption because the type of products produced is an important determinant of energy consumption. If countries operate in energy-intensive industries such as metals, chemicals, and forest products, energy consumption will be high, and if they specialize in low energy and highly complex products, energy consumption in these countries will decrease. In addition, the level of technological knowledge of countries can significantly affect energy efficiency. Therefore, in this research, the effects of economic complexity and economic growth on renewable, non-renewable and total energy consumption in developing and developed countries in the period of 2000-2020 have been investigated by GMM method.
Methodology
GMM estimator is a subset of instrumental variable method estimators. In this method, in addition to solving the problem of correlation of the independent variable with disturbance components, the endogeneity of the variables and the heterogeneity of the variance of the model are also solved. It should be noted that this method is applicable when T is smaller than N (number of segments).
Results
The results of this research show that the economic complexity index affects the development of renewable energy in developing and developed countries and also causes a decrease in the use of non-renewable energy and total energy consumption in developed countries and an increase in the use of non-renewable and total energy consumption in developing countries. It is currently being developed. In this research, the opening of trade has had a positive effect on the consumption of renewable energy in both groups of countries, and in developed countries, the opening of trade has reduced the consumption of non-renewable and total energy, and in developing countries, the opposite result has been obtained. In both groups of countries, energy consumption has a positive relationship with income level. Also, the results show that if economic growth is accompanied with higher technology, it can lead to a lower increase in total energy consumption in both groups of countries.
Conclusion and Discussion
As mentioned in the introduction, economic complexity represents a complex and knowledge-based production structure of a given country that takes a long time to mature. When economic complexity increases, the use of non-renewable energy and environmental degradation increases first in a given country. However, with the increase of environmental preferences in a society, the economic actors change their energy by using non-renewable energy habits. This is completely consistent with the results of the estimation models as explained above. Based on the obtained results, it can be said that economic complexity is a policy factor for the overall transformation of renewable energy and demand for greener energy. The study recommends that complexity and structural change policies should be implemented for cleaner and greener growth and overall promotion of greener energy in developing and developed countries. Due to the movement of developing countries towards the development of technology, the need for energy will increase in the coming years. Hence, there is a need for policymakers to plan to meet energy needs. Considering the existing limitations in the use of fossil energy, which leads to complications such as environmental pollution and resource depletion, necessary investments should be made for the development of clean and renewable energy. In order to reduce energy consumption, policies that increase energy efficiency or prevent any form of waste should be formulated, especially in economic sectors. In this regard, Can and Guzgur recommend that the level of fossil energy consumption in each industry should be clearly estimated and based on that, governments should establish specific laws for each industry. Through developing policies related to trade facilitation, they should also reduce the cost of importing new technologies, or decrease the cost of discovering new technologies via financing research and development institutions. Governments should promote energy regulations to reduce fossil fuel dependence and energy intensity. Future studies could examine the impact of economic complexity on energy demand in terms of oil-importing versus oil-exporting economies. Examining the effects of economic complexity on different aspects of energy (e.g., electric and nuclear energy) can be an important research question for researchers working on energy strategy.
Economic complexity is an index that has been raised in the last decade and indicates the use of technology in the process of producing goods and services of a country, which leads to increased economic growth and prosperity by creating a productive structure in the composition, increased productivity and diversity of manufactured products. Economic complexity is expected to affect energy consumption because the type of products produced is an important determinant of energy consumption. If countries operate in energy-intensive industries such as metals, chemicals, and forest products, energy consumption will be high, and if they specialize in low energy and highly complex products, energy consumption in these countries will decrease. In addition, the level of technological knowledge of countries can significantly affect energy efficiency. Therefore, in this research, the effects of economic complexity and economic growth on renewable, non-renewable and total energy consumption in developing and developed countries in the period of 2000-2020 have been investigated by GMM method.
Methodology
GMM estimator is a subset of instrumental variable method estimators. In this method, in addition to solving the problem of correlation of the independent variable with disturbance components, the endogeneity of the variables and the heterogeneity of the variance of the model are also solved. It should be noted that this method is applicable when T is smaller than N (number of segments).
Results
The results of this research show that the economic complexity index affects the development of renewable energy in developing and developed countries and also causes a decrease in the use of non-renewable energy and total energy consumption in developed countries and an increase in the use of non-renewable and total energy consumption in developing countries. It is currently being developed. In this research, the opening of trade has had a positive effect on the consumption of renewable energy in both groups of countries, and in developed countries, the opening of trade has reduced the consumption of non-renewable and total energy, and in developing countries, the opposite result has been obtained. In both groups of countries, energy consumption has a positive relationship with income level. Also, the results show that if economic growth is accompanied with higher technology, it can lead to a lower increase in total energy consumption in both groups of countries.
Conclusion and Discussion
As mentioned in the introduction, economic complexity represents a complex and knowledge-based production structure of a given country that takes a long time to mature. When economic complexity increases, the use of non-renewable energy and environmental degradation increases first in a given country. However, with the increase of environmental preferences in a society, the economic actors change their energy by using non-renewable energy habits. This is completely consistent with the results of the estimation models as explained above. Based on the obtained results, it can be said that economic complexity is a policy factor for the overall transformation of renewable energy and demand for greener energy. The study recommends that complexity and structural change policies should be implemented for cleaner and greener growth and overall promotion of greener energy in developing and developed countries. Due to the movement of developing countries towards the development of technology, the need for energy will increase in the coming years. Hence, there is a need for policymakers to plan to meet energy needs. Considering the existing limitations in the use of fossil energy, which leads to complications such as environmental pollution and resource depletion, necessary investments should be made for the development of clean and renewable energy. In order to reduce energy consumption, policies that increase energy efficiency or prevent any form of waste should be formulated, especially in economic sectors. In this regard, Can and Guzgur recommend that the level of fossil energy consumption in each industry should be clearly estimated and based on that, governments should establish specific laws for each industry. Through developing policies related to trade facilitation, they should also reduce the cost of importing new technologies, or decrease the cost of discovering new technologies via financing research and development institutions. Governments should promote energy regulations to reduce fossil fuel dependence and energy intensity. Future studies could examine the impact of economic complexity on energy demand in terms of oil-importing versus oil-exporting economies. Examining the effects of economic complexity on different aspects of energy (e.g., electric and nuclear energy) can be an important research question for researchers working on energy strategy.
Dr Hoda Zobeiri, Mrs Maryam Ehsani,
Volume 25, Issue 1 (3-2025)
Volume 25, Issue 1 (3-2025)
Abstract
Aim and Introduction
Economic complexity means a country's ability to produce and export more diverse products with less inclusiveness. Societies with efficient institutions internalize externalities and direct investment in productive activities lead to increased economic complexity. Democracy, by ensuring a stable political environment, stable economic framework, and social efficiency, promotes the accumulation of human capital, investment, and sustainable economic growth.
One of the main contributions in this study is using multidimensional aspect of democracy (electoral democracy, liberal democracy, participatory democracy, consultative democracy, egalitarian democracy) to investigate the effect of democracy on economic complexity.
Methodology
The purpose of this study is to investigate the effect of democracy on economic complexity. The data of 109 developing and developed countries during the period of 1995-2021 and a systemic generalized moments approach (SYS-GMM) have been used. The estimation also has also been done and the results compared separately for developing and developed countries.
Research model based on studies (Njangang & Nvuh-Njoya, 2023) has been specified. In the present study, the 5 indicators of democracy by V-DEM database have been used including electoral democracy, liberal democracy, participatory democracy, consultative democracy, egalitarian democracy. This measure of democracy ranges from zero, which is poor quality to one which is considered to be the best quality democracy. Any increase from zero to one, indicates the improvement of democracy. The variables of economic growth, government size and population size were used as control variables in the model.
The two indicators of political rights and civil liberties used to check robustness. The data is extracted from the database of Freedom House and measured from 1 to 7 in which 1 indicates the highest degree of freedom and political rights and 7 indicates the lowest level. These two indicators used to show the stability of the estimated coefficients of the research model. In order to check the robustness of the estimated coefficients, the results of the SYS-GMM estimator have been compared with the results of the two-stage generalized moments (GMM) and Feasible Generalized Least Squares (FGLS) estimators.
Results and Discussion
In this research, we investigate the effect of democracy on economic complexity using the systemic generalized moments approach (SYS-GMM).
Democracy affects economic complexity through three paths of "innovation", "human capital" and "financial development"
The results of this research show the positive and significant effect of all democracy indices on economic complexity. Moreover, the positive effect of economic growth, government size and population on economic complexity is confirmed. The stability of the estimated coefficients of the model as well as the consistency of the estimation results have been checked by the SYS-GMM estimator as a sensitivity analysis. Political rights and civil right variables were used to compare the results with democracy index. The results of the SYS-GMM estimator have also been compared with the results of the two-stage Generalized Method of Moments (GMM) and Feasible Generalized Least Squares (FGLS) estimators. The stability of the estimated coefficients has been observed in all methods.
Conclusion
The purpose of this study was to investigate the impact of democracy on economic complexity during the period of 1995-2021 using the systemic generalized moments approach (SYS-GMM) for 190 countries. For this purpose, from the 5 indicators of democracy (electoral democracy, liberal democracy, participatory democracy, consultative democracy, egalitarian democracy) V-DEM database was used. The research results show the effect of democracy on economic complexity can be heterogeneous compared to the initial level of economic complexity, so that democracy is associated with greater economic complexity in countries with higher economic complexity. The positive effect of democracy on economic complexity was confirmed in all models. Based on the results of the research, the coefficient of the types of democracy in developed countries is higher than the value of this coefficient in developing countries. In addition, economic growth, government size and population had a positive effect on economic complexity. To check the robustness of the model estimation we have estimated the model again using the Generalized Method of Moments (GMM) and Feasible Generalized Least Squares (FGLS). The two variables of political rights and civil rights were used instead of democracy and estimated with the Generalized Method of Moments (GMM) for all countries, as well as developing countries and developed countries. The coefficients and results have shown the stability of the estimated coefficients in all research models
Economic complexity means a country's ability to produce and export more diverse products with less inclusiveness. Societies with efficient institutions internalize externalities and direct investment in productive activities lead to increased economic complexity. Democracy, by ensuring a stable political environment, stable economic framework, and social efficiency, promotes the accumulation of human capital, investment, and sustainable economic growth.
One of the main contributions in this study is using multidimensional aspect of democracy (electoral democracy, liberal democracy, participatory democracy, consultative democracy, egalitarian democracy) to investigate the effect of democracy on economic complexity.
Methodology
The purpose of this study is to investigate the effect of democracy on economic complexity. The data of 109 developing and developed countries during the period of 1995-2021 and a systemic generalized moments approach (SYS-GMM) have been used. The estimation also has also been done and the results compared separately for developing and developed countries.
Research model based on studies (Njangang & Nvuh-Njoya, 2023) has been specified. In the present study, the 5 indicators of democracy by V-DEM database have been used including electoral democracy, liberal democracy, participatory democracy, consultative democracy, egalitarian democracy. This measure of democracy ranges from zero, which is poor quality to one which is considered to be the best quality democracy. Any increase from zero to one, indicates the improvement of democracy. The variables of economic growth, government size and population size were used as control variables in the model.
The two indicators of political rights and civil liberties used to check robustness. The data is extracted from the database of Freedom House and measured from 1 to 7 in which 1 indicates the highest degree of freedom and political rights and 7 indicates the lowest level. These two indicators used to show the stability of the estimated coefficients of the research model. In order to check the robustness of the estimated coefficients, the results of the SYS-GMM estimator have been compared with the results of the two-stage generalized moments (GMM) and Feasible Generalized Least Squares (FGLS) estimators.
Results and Discussion
In this research, we investigate the effect of democracy on economic complexity using the systemic generalized moments approach (SYS-GMM).
Democracy affects economic complexity through three paths of "innovation", "human capital" and "financial development"
The results of this research show the positive and significant effect of all democracy indices on economic complexity. Moreover, the positive effect of economic growth, government size and population on economic complexity is confirmed. The stability of the estimated coefficients of the model as well as the consistency of the estimation results have been checked by the SYS-GMM estimator as a sensitivity analysis. Political rights and civil right variables were used to compare the results with democracy index. The results of the SYS-GMM estimator have also been compared with the results of the two-stage Generalized Method of Moments (GMM) and Feasible Generalized Least Squares (FGLS) estimators. The stability of the estimated coefficients has been observed in all methods.
Conclusion
The purpose of this study was to investigate the impact of democracy on economic complexity during the period of 1995-2021 using the systemic generalized moments approach (SYS-GMM) for 190 countries. For this purpose, from the 5 indicators of democracy (electoral democracy, liberal democracy, participatory democracy, consultative democracy, egalitarian democracy) V-DEM database was used. The research results show the effect of democracy on economic complexity can be heterogeneous compared to the initial level of economic complexity, so that democracy is associated with greater economic complexity in countries with higher economic complexity. The positive effect of democracy on economic complexity was confirmed in all models. Based on the results of the research, the coefficient of the types of democracy in developed countries is higher than the value of this coefficient in developing countries. In addition, economic growth, government size and population had a positive effect on economic complexity. To check the robustness of the model estimation we have estimated the model again using the Generalized Method of Moments (GMM) and Feasible Generalized Least Squares (FGLS). The two variables of political rights and civil rights were used instead of democracy and estimated with the Generalized Method of Moments (GMM) for all countries, as well as developing countries and developed countries. The coefficients and results have shown the stability of the estimated coefficients in all research models
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