جستجوی مقالات مرتبط با کلیدواژه "پیچیدگی اقتصادی" در نشریات گروه "اقتصاد"

As economic complexity changes, rewards to different skills and knowledge levels change, thus directly affecting wage differentials. In fact, with the increase in economic complexity, the demand for knowledge and therefore the demand for skilled labor increases, which results in an increase in the wage gap between skilled and unskilled workers. On the other hand, after reaching a certain level of economic complexity, the inequality between the wages of skilled and unskilled workers decreases. The purpose of this study is to investigate the relationship between economic complexity by considering mediators such as human capital, government spending and trade openness index.

To check the integration characteristics of the studied variables, the unit root test of sharp and smooth structural breaks provided by Shahbaz, Omay and Roubaud (SOR, 2018) is used. Although there are various unit root tests to check the significance of variables, these tests provide biased experimental results due to their low explanatory power (Shehbaz et al., 2018). The uniqueness of SOR is that the nonlinear unit root test considers sharp and smooth breaks in a time series. To examine the co-accumulation relationship between variables, the bootstrap ARDL co-accumulation method of McNown et al. (2018) is used. The originality of the bootstrap ARDL approach is its ability to deal with the properties of size and weak power that exist in the conventional ARDL approach of Pesaran et al. (2001). In addition, in order to increase the power of t and F test, this approach has the ability to integrate a new cointegration test during design and add to the cointegration framework of the conventional ARDL bounds test approach. Pesaran et al. (2001) found two conditions necessary to identify clustering. First, the coefficients of the error correction term must be statistically significant. Second, the coefficients of the interrupted explanatory variables should also be statistically significant. Pesaran et al. (2001) suggest that for the second case, critical boundaries (upper and lower bounds) should be used, but for the first case, there is no test of critical boundaries or boundaries. In the first situation, when the coefficients of the error correction term are statistically significant, if all the variables of the model are accumulated from the first degree, the test can be used; Therefore, the conventional unit root test is inappropriate due to their power characteristics and low explanatory power as shown by Goh et al. (2017). This problem can be solved using the ARDL band test presented by McNown et al. (2018).

We use the (ADF) test and to check the power, we also use the Phillips-Perron (PP) test and also the Zivot-Andrews test in terms of a structural break. The results of both tests show that the variables are I(1), but in the Zivot-Andrew test, the trade openness variable is at a significant level. Also, none of the variables are accumulated with the second-order difference or I(2), so it also fulfills an important condition to perform the ARDL method. In order to check the robustness of the unit root analysis, we have also used the SOR unit root test, which includes sharp and smooth failures. The experimental results of the SOR unit root test show that the null hypothesis of the unit root is not rejected for the variables used in the study, the experimental results show that the variables include unit root processes. The ARDL bootstrap regression results show that economic complexity increases income inequality in the long term and has no effect on income inequality in the short term. This case can be because the complexity in Iran is not at a high level in general and it cannot improve the income distribution. In addition, human capital reduces income inequality in the short and long term. Therefore, improving the quality of human capital can strengthen economic structures and reduce income inequality. In the long run, per capita income reduces income inequality and the square of per capita income increases income inequality. In fact, the mode is U-shaped rather than U-shaped. This could be because economic growth in Iran is dependent on oil revenue rather than industry. Although, on a temporary basis and with an increase in oil income, it can reduce income inequality, but in the long run, considering that this income is not invested in industries with export capability and productivity is not paid much attention, it has no effect on reducing income inequality in the long term, and even the effects The negative side of unbalanced growth also increases income inequality. Government spending has no effect on income inequality in the short and long term. In fact, the government's consumption expenditure in Iran constitutes a large part of the government's expenditure and does not have much efficiency and productivity that can improve income distribution. The openness of trade in the short and long term increases income inequality, which can actually be the reason that there is very little export diversity in Iran, and therefore the openness of trade cannot have much effect on the improvement of people's conditions on a large scale.

According to the results, economic development has not been able to reduce income inequality in Iran. In fact, reducing income inequality requires a combination of several development policies. Improvements in productive capabilities that lead to higher economic complexity must be implemented along with improvements in institutions, government spending, human capital, and trade liberalization. Although human capital has reduced income inequality, it still has little effect on improving the relationship between economic complexity and income inequality. Therefore, there is a need to reform the educational system and provide appropriate training to the characteristics of Iran's labor market to facilitate the entry of people into the labor market and improve human capital and increase productivity, which can lead to the improvement of production capabilities and the improvement of production capabilities and the strengthening of economic structures. It can increase economic complexity and consequently reduce income inequality.

One of the main features and key to success of many countries in today's world is the use of knowledge in economic processes. Because knowledge is one of the most important components for determining long-term economic growth, investing in knowledge has increased the production capacity of other factors of production such as capital, natural resources and labor, and facilitates the efficient conversion of production inputs into production processes and new products. Achieving quality economic growth in the form of economic growth along with reducing income inequality is one of the most important economic issues today. Economic complexity is one of the concepts that implies the role of knowledge in production and in addition to economic growth plays an important role in changing income inequality. Accordingly, the present study uses the simultaneous equation approach to examine the relationship between income inequality and economic complexity for the period 1397-1374. The results show that increasing income inequality has increased economic complexity, but economic complexity has reduced inequality In addition, there is evidence that industrialization, human capital, and GDP lead to increased economic complexity. In addition, industrialization has reduced income inequality, and the Kuznets curve hypothesis on the relationship between GDP and income inequality has been confirmed. Increasing the quality of education, industrial development, and focusing on policies to increase GDP are among the effective policies for enjoying the benefits of economic complexity.

The main purpose of this research is to investigate the effects of compound risk shocks and its components (political, economic and financial risk) along with economic complexity on the development of Sukuk market in Iran. The data required to conduct this research is based on the variables of the proposed model related to the time period of 2010-2022 and seasonally, using the Central Asset Management Company of the Iranian Capital Market, the International Country Risk Guide Database (ICRG) and the MIT University website. has been The results of model estimation using the Wald test and Nonlinear Autoregressive Distributed Lag Model Approach (NARDL) indicate that the unexpected positive and negative shocks of the compound risk and its components have asymmetric effects on the development of the sukuk market. Among the components of composite risk, the negative shock of political risk has the most negative effect and the positive shock of financial and economic risk has the most positive effect on the development of the Iranian sukuk market in the long term. Also, the effect of economic complexity on the development of the sukuk market in the long term is positive in every equation proposed in this research

High volatilities of output and inflation in an economy have negative effects on economic growth, and also cause an uncertain economic environment. Economic complexity is one of the factors affecting changes in macroeconomic variables. By increasing economic complexity, the technological structure of production changes, and there is a movement of production resources between production activities. Therefore, this study investigates the relationship between the economic complexity index and volatility of output and inflation using the system of simultaneous equations during 1978-2019. The results of the estimation show that the increase of economic complexity would result in the decrease of output volatility by 0.121% and the decrease of inflation volatility by 0.106%. Additionally, the variables of government expenditure and trade openness, included as control variables in the equation of output volatility, have a positive effect. Moreover, the variable of exchange rate has a positive effect in the inflation volatility equation. From a policy-making perspective, based on the results of this research, it is suggested that economic complexity, through increasing products variety and promoting more specialized and knowledge-based production, can effectively contribute to economic stability and create conditions for further economic growth and development.

The main purpose of this research is to answer whether increasing economic complexity is a suitable solution to reduce dependence on natural resources in MENA countries. In this regard, using information and statistical data of 11 countries of this region from 2000 to 2022, the threshold impact of economic complexity on natural resource dependency has been investigated at the total and disaggregated levels. The results confirm the threshold impact of economic complexity on the total natural resources rent, oil rent, natural gas rent, and forest rent and its insignificant effect on mineral rent. Based on the calculated threshold level, the impact of economic complexity on the total natural resources rent and oil rent is negative, and the impact of economic complexity on natural gas rent and forest rent is inverted U-shaped and U-shaped, respectively. The average marginal impact of economic complexity on the total natural resources rent, oil rent, natural gas rent, and forest rent is estimated to be about -19.09, -17.88, -1.09, and 0.01, respectively. Based on this, it can be said that economic complexity reduces dependence on energy sources in the studied countries.

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.

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).

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.

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 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.

Improving the quality of logistics performance, which includes activities such as transportation, integration of commercial loads, domestic distribution and payment systems, enables the improvement of competitiveness in international trade. The impartiality of government policies, can affect the production and variety of export goods, investment and the granting of government aid in order to create educational infrastructure and produce knowledge, thereby contributing to economic complexity. The purpose of this article is to analyze the effects of logistics performance quality and impartiality of government policies on economic complexity and to evaluate the mediating effect of economic complexity in transferring the effects of the aforementioned indicators on economic growth in 19 selected developing countries with lower middle income in the period of 2013-2021. So, the effects of logistics performance and impartiality of government policies on economic complexity and the effect of economic complexity on economic growth were estimated by GMM method. The results showed that the logistics performance quality and impartiality of government policies had a positive effect on economic complexity and economic complexity had positive effect on economic growth. The calculation of Sobel's statistic confirms the mediating effect of economic complexity in transferring the effect of the mentioned indicators on economic growth.

The most important relative advantage of Iran has been the export of crude oil and natural gas for a long time. Considering the raw nature of these products, specialization in the production and export of these products will not have a significant impact on Iran's sustainable growth. One of the solutions is to infiltrate the downstream industries of these products, the most important of which is the development of the petrochemical industry. In this sense, since the expansion of export markets is considered as one of the important strategies in the field of marketing, the aim of this research is to identify and prioritize the export opportunities of Iran's petrochemical industry products by developing an integrated decision support model - economic complexity, in five countries that are members of the Eurasian Economic Union. It includes Belarus, Kazakhstan, Russia, Kyrgyzstan, and Armenia, and the member countries of ECOTA trade agreements include Afghanistan, Pakistan, Tajikistan, and Turkey.the current research is applied in terms of purpose, descriptive-survey in terms of data collection, and a mixed type of research. The statistical population of the research was formed by the member countries of ECO and Eurasia trade agreements during the period of 2014 to 2021. First, in order to identify the factors affecting the development of export opportunities, using a questionnaire and a fuzzy Delphi model, based on the opinions of experts working in the private sector and petrochemical companies, experts working in specialized government jobs of the Ministry of Health, and academic experts,

Economic complexity is a relatively new concept developed in recent years to assess the productive characteristics of countries. It not only explains the production structure, but also helps examine differences in income and growth across countries. In this paper, we estimate the macroeconomic impact of economic complexity on growth of a sample of N-11 countries for the period 2000-2020, using the economic complexity index developed by Hidalgo and Hausman (2009). Diagnostic tests confirmed the assumption of slope coefficient heterogeneity and cross-sectional dependence of the error term. Thus, we employ the Pesaran (2006) Common Correlated Effects Mean Group estimator (CCEMG) and the Chudik and Pesaran (2015) Common Correlated Effect Pooled Mean Group (CCEPMG) methodology. The findings suggest that economic complexity is one of the key determinants of long-term economic growth. However, its impact on economic growth is not significant in the short term, suggesting that the impact of changes in production structure on economic growth is time-sensitive. The coefficients of other control variables such as human capital, investment, institutional quality, and inflation rate were statistically significant.

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.

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).

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

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.

The impact of technological advances on energy consumption is one of the topics that has been considered by many researchers and policymakers. Numerous researchers have tried to evaluate this relationship based on various technology indicators. The index of economic complexity is one of the new indicators that has been used in recent years to measure the level of knowledge and technology in the production structure. In this paper, the index of economic complexity along with energy prices and GDP have been used as determining factors of energy consumption in Iran during the period 1976 to 2018. Quantile regression results show that the coefficients of the variables are different in the deciles. The impact of economic complexity on energy consumption in all deciles has been positive, indicating the dominance of the rebound effect on energy consumption. Price elasticity is less than one in all deciles and less in the higher consumption deciles. In contrast, the income elasticity of energy demand was higher in the upper deciles

Economic complexity is one of the criteria for measuring the knowledge-based economy of a country. Several studies have shown that improving the economic complexity index leads to sustainable economic growth and improved welfare. Therefore, policy makers tend to place the development and progress of the country in the path of knowledge-based economy and production of complex products. But the channel of influence of complexity on the economy of a country is questionable. Identifying this channel can lead to the focus of development policies. The hypothesis investigated in this research is the effectiveness of economic complexity on the field of factory activities. In the literature review, it was found that the relationship between these two variables is not predetermined. To test the hypothesis, a statistical sample including 46 countries has been selected for a period of 31 years ending in 2020. The PMG model has been used for data processing. The result of the estimation of the model shows that the increase in the added value of factory industries is one of the consequences of the improvement of economic complexity. This finding can help to set development policies.

In recent decades, economic growth along with environmental protection is important issue facing most economic societies. On the other hand, with the increase of new technologies and the trade openness, the effect of changing new and extensive structures on the environment has become very important. Therefore, the aim of this study is to evaluate the effect of economic complexity and trade openness on the ecological footprint (as an indicator of environmental degradation). For this purpose, the data of 18 developing countries in Asia during the study period from 1990 to 2017 have been used with the Panel-Quantile approach. In addition, the variables of GDP per capita, globalization and financial development were considered as control variables. The results of this study show that the increase in economic complexity in different quantiles reports different results, so that with a one percent increase in economic complexity in the 10th quantile, the ecological footprint has decreased by more than one percent, but an increase in economic complexity in the 50th quantile has caused the deterioration of the quality of the environment. The results show that the increase in trade in all quantiles has helped to improve the environment. Moreover, with increasing globalization and financial development, the ecological footprint has increased in all quantiles. In addition, the results of this study indicate that the increase in per capita income has reported different results in different quantiles.

Economic complexity indicates the amount of productive knowledge within a country and the ability to use that knowledge to produce goods with more diversity and less ubiquity, which ultimately increases national competitiveness in the global arena and accelerates the process of achieving economic growth and development. Therefore, determining the factors affecting it - especially in developing countries - is of great importance. In this regard, the present study, by approaching panel data and using the generalized moment method, has determined the interactive effect of entrepreneurship and financial development on economic complexity in two groups of developing and developed selected countries during the period 2014-2019. Estimated results showed that the dimensions of entrepreneurship, including attitudes, abilities & aspirations of entrepreneurial, as well as financial development have a positive and significant effect on economic complexity in both groups of selected countries. However, the estimated coefficient of these variables is larger for developing countries. In addition, the three dimensions of entrepreneurship and financial development have a positive and significant interactive effect on economic complexity in both groups of selected countries. Finally, the effect of the control variables of natural resource abundance and intellectual property rights on economic complexity in both groups of selected countries respectively are negative and significant and positive and significant.

Although various studies have examined the effect of economic complexity and the shadow economy on income inequality, the nonlinear effect of economic complexity and the shadow economy on income inequality, which plays an important role in reducing problems in the economic, political and social fields of countries, has been investigated to a limited extent. has taken. The main purpose of this article is to investigate the impact of economic complexity and shadow economy on income inequality in 29 member countries of the Organization for Economic Cooperation and Development (OECD) during the period of 1995-2020. For this purpose, the Gini coefficient is considered as an index of income inequality and an index of economic complexity, shadow economy, GDP per capita and trade openness. The results obtained from the self-explanatory approach with wide panel breaks (Panel ARDL) show that with the increase of the shadow economy, income inequality first has an upward trend and after a stage it starts to decrease, in other words, an inverted U-relationship. There is a form between income inequality as a dependent variable and shadow economy as an explanatory variable in the studied countries. In addition, there is a U-shaped relationship between income inequality as a dependent variable and economic complexity as an explanatory variable. As economic complexity increases, income inequality first decreases and then gradually increases. Also, empirical findings show that trade openness reduces income inequality, while economic growth increases inequality. Based on this, it is suggested that considering the complexity of these relationships, politicians and statesmen should consider the socio-economic status of these two issues (economic complexity and shadow economy) when formulating policies related to income distribution.Although various studies have examined the effect of economic complexity and the shadow economy on income inequality, the nonlinear effect of economic complexity and the shadow economy on income inequality, which plays an important role in reducing problems in the economic, political and social fields of countries, has been investigated to a limited extent. has taken. The main purpose of this article is to investigate the impact of economic complexity and shadow economy on income inequality in 29 member countries of the Organization for Economic Cooperation and Development (OECD) during the period of 1995-2020. For this purpose, the Gini coefficient is considered as an index of income inequality and an index of economic complexity, shadow economy, GDP per capita and trade openness. The results obtained from the self-explanatory approach with wide panel breaks (Panel ARDL) show that with the increase of the shadow economy, income inequality first has an upward trend and after a stage it starts to decrease, in other words, an inverted U-relationship. There is a form between income inequality as a dependent variable and shadow economy as an explanatory variable in the studied countries. In addition, there is a U-shaped relationship between income inequality as a dependent variable and economic complexity as an explanatory variable. As economic complexity increases, income inequality first decreases and then gradually increases.

The consumption of fossil fuels and its effects have caused serious challenges and concerns in the fields of energy and environment. These challenges include issues such as fuel supply security, finite energy sources, environmental pollution, and problems related to global warming. In order to solve this crisis, the use of renewable energy is proposed as an effective solution to deal with concerns related to environmental sustainability and energy security. The main purpose of this article is to investigate the effect of economic complexity on the consumption of renewable energy in Iran based on the autoregression technique with distributed lag (ARDL). For this purpose, the data of renewable energy consumption per capita, economic complexity index, foreign direct investment, gross domestic product per capita as a measure of economic growth, urbanization rate and carbon dioxide emission per capita during the period of 1368-1400 were used. has been The results of the co-accumulation test show , economic complexity leads to an increase in the consumption of renewable energy. Also, according to the results of foreign direct investment, economic growth and urbanization rate increase the consumption of renewable energy, while the per capita emission of carbon dioxide reduces the consumption of renewable energy .

Economic complexity refers to the accumulation of productive capabilities in an economy. Accelerating the accumulation of these capabilities increases the capacity to invent and absorb new technologies. Over the initial stages of economic development, most countries absorb energy-intensive technologies, which will lead to an increase in fossil energy consumption. By increasing the economic complexity of a country and the accumulation of complex capabilities, it becomes possible to absorb and invent new energy-efficient and clean technologies, which will be a factor in reducing the intensity of fossil energy consumption. In this paper, we investigate the effect of the economic complexity of Iran's provinces on the consumption of fossil energy over the period 2005-2018. For this purpose, the system GMM estimator in dynamic panel data has been applied. The results of the paper indicate that the increase in the economic complexity of the provinces is the driver of fossil energy consumption, so that the hypothesis of the "Energy-Environmental Kuznets Curve" across the provinces of the country is rejected. Accordingly, making the current production structure more complex in Iran's economy will not help to reduce fossil energy consumption. Other results show that (a) the per capita consumption of fossil energy is inelastic with respect to the relative price of fuel, and (b) the rate of urbanization is the driver of energy consumption. According to the findings of the research, it is recommended that instead of implementing pricing policies to reduce energy consumption, the government should emphasize changing the production structure by using clean technologies.

Currently, there is no proper match between Iraq's import needs and the variety of Iran's export goods to that country.According to the statistics of the International Trade Center, more than half of the country's import needs are related to mechanical and electrical machinery and transportation equipment ($16.8 billion) with a share of about 30%, and agricultural products and food industries ($11.4 billion dollar) with a share of about 20%, which Iran has allocated about 3.4% and 16.5% of the total needs of the Iraqi market in the mentioned sectors, respectively. The present article with the aim of identifying Iran's export opportunities to Iraq and prioritizing them, has used integrating a decision support model and the approaches of economic complexity and product space. A number of 627 export opportunities have been identified based on the four-digit commodity codes HS and prioritized divided into ten main commodity sections. The results show that Iran is present in half of the products in the Iraqi market with a relative advantage; So that Iran's export power to the Iraqi market (based on the revealed relative advantage) is at a higher level than the competitors of that market. Among the 590 products (according to four-digit HS) that Iran exports to the Iraqi market with a stronger advantage than other competitors, it has a comparative advantage in only 123 cases at the international level; Also, among the 351 commodity groups that have relatively high complexity, only 35 items have a comparative advantage at the international level. In addition, among Iran's export commodity groups, only 55 groups have been provided with the capabilities and capabilities needed for production in the country's economy at a level beyond 50%.

Contrary to the public perception that income inequality is due to differences in individuals' abilities and motivations, differences in economic, social, and institutional structures are also important factors in generating income inequality. The complex-structured economies and more developed institutions provide individuals with more opportunities for education and job choice and reduce income inequality. This study investigates the effect of economic complexity and institutional structure on income inequality within the Kuznets curve. The sample used in this study was 43 developing countries during the period of 2015-2002 and dynamic panel econometric method was used to analyze the data. The results indicate that good governance as a proxy for institutional quality, and economic complexity have had a significant negative impact on income inequality in developing countries. These results show that institutional and structural factors, as two other dimensions of development, have also had a significant impact on income inequality in developing countries.