developing countries

 Carbon tax is one of the most important policy tools in the field of energy, which is applied to the consumption, production or distribution of fossil energy, including oil products, coal, natural gas, etc. The purpose of carbon tax is to reduce economic and environmental effects caused by pollution by including environmental costs in the price of goods and services. This policy tool can bring positive economic and environmental consequences through changes in consumer and producer behavior. The purpose of this study is to investigate the effects of carbon tax on energy-intensive and non-energy-intensive industries in different regions of the world.

Since a CGE model can describe the interactions between different factors in macroeconomic systems and examine the effects of a policy at the global level, therefore, a dynamic multi-regional CGE model has been used to better understand the policy effects.

The results show that the carbon tax in all scenarios leads to an increase in the price of goods with high energy intensity in all regions, and the price of goods with low energy intensity decreases, except in the group of developed and high-income countries. Production in the energy-intensive and non-energy-intensive sectors is facing an average decrease. Imports in the energy-intensive sector, except for the group of countries with higher-than-average income, will decrease for other groups, and in the non-energy-intensive sector as well.

To investigate the effect of carbon tax on the industries of different countries, first the countries of the world were grouped into 5 regions based on the criteria of the World Bank and then 5 policy scenarios based on the report of the International Energy Agency were implemented in each region. For modeling, a dynamic calculable general equilibrium model was used in order to achieve more accurate results, and then important industrial consequences were obtained by solving the model. From the results of this research and the studies that have been carried out so far, it can be seen that what is decisive in the consequences of the implementation of the carbon tax is the region and the country implementing the policy. Based on this, the policy makers, considering the national and regional conditions and being aware of the possible effects of the policy, can include assumptions in the design and implementation of the policy in order to achieve efficient and appropriate conditions in the implementation of the carbon tax by reducing the negative effects. Based on the results of the research, it was observed that due to the differences in the regions, the macroeconomic effects in the industry will be different for different regions of the world. Therefore, one of the important points in the effort to bring the emission of greenhouse gases to zero is to pay attention to the differences in industries in different countries and the coordinated actions of the governments with each other for technical and financial support in order to accelerate the transformation of clean energy and reach the commitment goal. Since energy consumption is mainly related to production activities, especially production from energy-intensive industries, reducing greenhouse gas emissions from industry takes more time than some economic sectors. For this purpose, governments should present regular and specific programs to attract investments in the long term so that they can guide industries in the direction of deploying the most efficient technologies. The governments that implement carbon tax policies can also use the collected tax revenues to strengthen energy innovation. Therefore, industries that use unclean energy sources as production inputs, by upgrading production technologies, in addition to reducing production costs, can specialize in producing clean products

In recent decades, bilateral and multilateral investment treaties have become key international legal tools to encourage foreign direct investment (FDI) by providing protections that attract foreign investors. Consequently, many developing countries enter into bilateral investment treaties (BITs) to boost FDI inflows. This study aims to investigate the impact of these treaties on FDI in developing countries, analyzing economic data from 21 developing nations from 2007 to 2022 through an attraction model. The findings indicate that BITs have a consistently positive and significant impact on FDI across all models, with a particularly strong effect observed among developing countries. Additional variables—including institutional quality, colonial ties, and a free trade agreement dummy variable—were added to the model. When a BIT is concluded, the host country provides foreign investors with a reliable institutional framework that may offer better investment protection than domestic institutions. In this context, BITs and domestic institutional quality appear to be substitutes, leading to an expected negative relationship. On the other hand, BITs can also serve as a signaling mechanism, indicating to foreign investors that the host country is committed to safeguarding their investments. To capture this effect, an interaction term between BITs and institutional quality was added to the model. This interaction variable is negative across most country pairs, indicating substitutability, but is positive and significant among pairs of developing countries, highlighting a unique dynamic in these contexts.

Studding the entrepreneurship literature shows that the Economic performance and the extent of entrepreneurial activities depend on the quality and different levels of institutions, and in addition, the mechanism of institutions' influence on entrepreneurial activities in developed and developing countries differs. The purpose of this research is to understand the difference in the type of influence of micro and macro institutions on entrepreneurial activities in developed and developing countries. For this purpose, while using the dynamic panel data, the good governance index and the business environment index used as macro and micro institutional factors, respectively. The results showed that the good governance significantly increase the level of entrepreneurial activities in both developing and developed countries. Contrary to expectations, micro-institutional factors do not increase the level of entrepreneurial activities in the studied developing and developed countries. The degree of economic freedom has a small effect on entrepreneurial activities in developed countries, while it strengthens entrepreneurship in developing countries. Government expenditure has a positive impact  on the level of entrepreneurial activities in developing countries, but it is ineffective in developed countries. Economic growth in both groups of countries has positive impact on the level of entrepreneurial activities. The impact of liquidity on the entrepreneurial activities of developing and developed countries is negative and positive, respectively.

Considering the vital role of money demand in monetary and economic policies and its importance in economic stability, it is necessary to know the factors affecting it. By focusing on the increasing role of new technologies and financial developments, this paper examines the effect of financial development and the expansion of information and communication technology (ICT) on the demand for money in developing countries. This study uses principal component analysis (PCA) to calculate the ICT index. The research model is estimated using annual data obtained from the World Bank and International Monetary Fund from 2002-2021 for a selected group of developing countries. The long-run relationship between the variables has been investigated in a panel-ARDL model. The research results show that ICT and financial development both have a negative and significant impact on money demand. These results point to the development of ICT infrastructure and financial resources to control money demand. In other words, increasing access to financial instruments and widespread use of ICT technologies has reduced the need to hold cash. These results indicate that structural changes in the economies of developing countries, caused by financial and technological growth, lead to changes in monetary behaviors. Therefore, policymakers should adopt strategies that can help adapt to these developments and better manage money demand

The lack of security, political dependencies, the formation, and the increase in environmental problems are the main reasons for changing the approach to energy supply from fossil fuels to renewable energies. This alteration requires financial support for the extraction of renewable energies. Foreign direct investment, investment in research and development, and financial market development are among the Financing methods that also impact the consumption of renewable energies. This study aims to assess the impact of these financing methods on the consumption of renewable energies across 26 developing countries during the period from 2008 to 2019. Findings from panel model estimations indicate that foreign direct investment and investment in research and development have a positive and significant effect on the consumption of renewable energy, while the development of financial markets does not have a significant effect on the consumption of renewable energies. Based on the results, since the defined methods of financing do not have an adverse effect on renewable energy consumption, it is recommended that the government, to guarantee the indicators of the nation's welfare, including environmental quality, put the laws covering these financing methods in the main plan and support

The insurance penetration rate is one of the most important indicators used to evaluate the insurance industry of a country. This ratio is also a measure to compare the performance of the insurance industry between developed and developing countries. The aim of this research is to compare the insurance penetration rate and the factors affecting it in high and low income countries.

The current research examines the effect of variables such as inflation rate, education, labor productivity, dependency ratio and income on the insurance penetration rate in the period 2011-2021 and using PMG and ARDL methods to derive short-term and long-term equations in 18 countries with income High and low income and the country of Iran pays.

The results obtained from the estimation of long-term PMG models in high-income countries indicate a positive effect of dependency ratio, income level and fertility level on the insurance penetration rate, as well as a negative effect of inflation rate and labor productivity on the dependent variable, also in selected countries with high income. All the variables, except for education and dependency ratio, which had a positive and significant effect on the insurance penetration rate, are statistically meaningless.   On the other hand, the findings from the estimation of the long-term ARDL model in Kesho Iran show the negative impact of the inflation rate on the insurance penetration rate and the positive impact of the education level, income level and dependency ratio on the insurance penetration rate.

The expansion of the financial sector has raised the concern of “brain drain” among industries. There are also concerns that too many financial activities may misallocate resources, both physical and human capital, from production sector to less productive ones. Financial development may make it easier for less efficient firms to stay in the market and prevent more efficient innovators from entering the market, which may harm innovation and growth. In this regard, the main purpose of this study is to investigate the role of financial development in the relationship between innovation and economic growth in developing countries.

In order to meet the research goal, a regression model is specified to describe economic growth as a function of the first-order lag of economic growth, innovation and the product of innovation and financial development. Moreover, economy openness (the ratio of exports plus imports to GDP) and the ratio of the net flow of foreign direct investment to GDP are included in the model as control variables. In this model, one of the regressors is the first-order lag of the dependent variable. The regression equation is estimated using the Generalized Method of Moment (GMM) and the data for the period of 2000-2019.In this study, the multidimensional index of financial development of the International Monetary Fund has been used as a relative ranking of countries on the depth, access, and efficiency of their financial institutions and financial markets. The Financial Institutions (FI) index is an aggregate of the Financial Institutions Depth (FID) index, which compiles the data on bank credits to the private sector in a percent of GDP, pension fund assets to GDP, mutual fund assets to GDP, and insurance premiums, life and non-life to GDP, Financial Institutions Access (FIA) index, which compiles the data on bank branches per 100,000 adults and ATMs per 1000,000 adults and Financial Institutions Efficiency (FIE) index, which compiles the data on banking sector net interest margin, lendind-deposits spread, non-interest income to total income, overhead costs to total assets, return on assets, and return on equity. Also, Financial Markets (FM) index is an aggregate of Financial Markets Depth (FMD) index, which compiles the data on stock market capitalization to Gdp, stocks traded to GDP, international debt securities of government to GDP, total debt securities of financial and nonfinancial corporations to GDP, Financial Markets Access (FMA) index, which compiles the data on a percent of market capitalization outside the top 10 largest companies, total number of issuers of debt (domestic and external, nonfinancial and financial corporations) per 100,000 adults, and Financial Markets Efficiency (FME) index, which compiles the data on stock market turnover ratio (stocks traded to capitalization). In addition, the number of the patents registered is considered as an index of innovation, and the real GDP per capita is considered as an index of economic growth.

The results of Generalized Method of Moment (GMM) show that the effect of innovation on economic growth is positive and statistically significant. Furthermore, the effect of the interaction between financial development and innovation on economic growth is negative and statistically significant, which suggests that the effect of innovation on economic growth is not independent of the level of financial development. According to the results, the threshold level of financial development is 0.76466. According to the results of descriptive statistics, the average financial development index for the selected developing countries is 0.378945, which is significantly lower than the threshold level. Therefore, if the level of financial development becomes lower than this threshold level, the higher the level of financial development, the smaller the positive effect of innovation on economic growth. In other words, when the level of financial development increases, the positive relationship between innovation and economic growth weakens.

Conclusions and policy implications:

 Based on the results, the financial development level increases the positive relationship between innovation and economic growth. Therefore, financial development weakens the positive growth effects of innovation. In other words, with a higher the level of financial development, a unit of increase in innovation leads to a smaller increase in economic growth. As empirical results indicate, trade openness and the ratio of foreign direct investment to GDP have a positive and significant effect on economic growth. It is suggested that, in parallel with the financial development, a serious solution should be provided regarding the optimal allocation of human and physical resources. The markets with low productivity should be identified, and their continuity of attendance should be prevented in order to provide the ground for the entry of new innovators and entrepreneurs. This is possible by making amendments in laws and regulations and increasing the quality of administrative systems.

In an era of economic complexity, where goods and services are produced using advanced technologies and with significant diversity, achieving economic growth without environmental pollution has become one of the primary goals for nations worldwide. This objective necessitates measures such as investment in knowledge-based production, which in turn relies heavily on investment in research and development.  The present study aimed to examine the relationship between multidimensional economic complexity and inclusive green economic growth. Given the geographic proximity of some developed and developing countries, the research employed a spatial panel econometric method using data from these nations. The results indicated a significant relationship between inclusive green growth and economic complexity in both developed and developing countries. However, this relationship is relatively weaker in developing countries.

Despite the notion that economies with abundant natural resource revenues should have a lower default risk and thus a lower share of public debt, this notion is not generally valid. Natural resources in these countries serve as a guarantee to procure more public loans and binds them in debt trap. In this regard, this article examines the short-term and long-term effects of natural resource rent on public debt in developing countries during 2000-2020. For this purpose, first, a model was designed with the presence of basic variables affecting public debt, along with the variable of share of natural resource rent from GDP, and using panel co-integration tests, the existence of a long-term equilibrium relationship between the variables of the model was confirmed. Finally, the pooled mean group (PMG) approach was used to measure long-term and short-term relationships, and the e Dumitrescu-Hurlin test was used to determine causality. The findings of this research show that the effect of the share of natural resource rent from GDP on public debt is negative (and significant) in the short term and positive (and significant) in the long term. The results of the Dumitrescu-Hurlin test also indicate the existence of a two-way causal relationship between the abundance of natural resources and public debt. Based on this, it can be said that the abundance of natural resources in developing countries leads to higher public debts in the long term, and high levels of public debts also cause rapid extraction of natural resources in these countries.

Most of developing countries face low levels of human capital. Human capital through training and improving skills and knowledge can be considered as one of the key strategies in the development of developing countries. A well-functioning financial system is necessary to reduce the risks associated with loss of income and thus strengthen human capital, increase opportunities and income distribution mechanisms, and reduce poverty. Therefore, financial inclusion plays an important role in strengthening human capital. Financial inclusion is considered as a vital factor of human development and economic growth by facilitating the access and use of financial services for all people in an economy. In addition, access to and use of financial facilities may allow individuals to deal with risk factors by investing in education and reduce the burden of financial problems, thereby having a positive impact on human capital. Considering this issue, the present study examines the effect of financial inclusion and income inequality on human capital in 52 developing countries during the period of 2005-2021 and using the generalized panel moments method. The results show that the financial inclusion index has a U-shaped non-linear effect on human capital at the significance level of ten percent. In other words, at low levels of financial inclusion, this variable cannot lead to the strengthening of human capital, but at high levels and crossing the threshold of this variable, it can lead to the strengthening of human capital. Other results show that income inequality and transfer payments have a negative and significant effect, and economic growth and consumer purchasing power have a positive and significant effect on human capital.

The present study examines the impact of shadow banking on inflation rates in four groups of selected countries (including developed countries with high levels of shadow banking, developed countries with low levels of shadow banking, developing countries with high levels of shadow banking, and developing countries with low levels of shadow banking) during the period 2002-2020. The research modeling is based on dynamic panel patterns, and the relationships between variables are estimated using the Generalized Method of Moments (GMM) technique. The results of the model estimation in two groups of countries under study, namely developed countries with high levels of shadow banking and developing countries with low levels of shadow banking, indicate that the expansion of shadow banking leads to increased inflation, with this effect being exacerbated through the production channel. Conversely, the findings suggest a negative impact of shadow banking on inflation in developed countries with low levels of shadow banking and developing countries with high levels of shadow banking. It is worth noting that the results of the model estimations show that in none of the four groups of countries examined, shadow banking has led to inflation through the money creation channel. It is worth noting that the results of the model estimations show that in none of the four groups of countries examined, shadow banking has led to inflation through the money creation channel.

Social welfare as the development of people's living standards is one of the most important socio-economic categories, which has been explained and analyzed in economic texts, and the provision of welfare of society members by different societies has been discussed among thinkers and experts for a long time. . Although welfare is a concept that is used in all social sciences, but due to the wide scope of this concept, people do not have a single understanding of it and there are confusions about what is meant by welfare. The word "social welfare" is the birth of economic and social developments and relationships of recent centuries and has become the fundamental goal of development programs in different societies until today. A goal without which development in its various dimensions (human, social, cultural, political and economic) will fail. On the other hand, according to a 10-year research conducted by the United Nations University's Global Development Economics Research Institute (unitar), most countries that have succeeded in reducing poverty and increasing access to public goods have based this progress on strong economic growth. According to Fitzpatrick, prosperity is not the goal of development, but development itself, that is, we can consider a government and a society as developed that provides the minimum or appropriate level of life from various economic, educational, health and medical dimensions for each individual and its residents. provided When developing societies cannot have a suitable level of economic growth, one of the ways out of this situation is to increase and improve the level of social welfare. Social welfare is one of the most important and attention-grabbing issues in today's world. Development and movement towards development is one of the basic issues of different societies in the world, and underdeveloped societies are trapped in the so-called vicious circle of poverty due to the lack of per capita income and countless other factors. Accordingly, one of the most important goals of economic planners is to increase social welfare in order to expand economic growth. Therefore, the present research aims to evaluate the effects of social welfare on economic growth in Iran and selected developing countries in the period of 2002-2021 using the Generalized Method of Moments. The results of the study indicate that social welfare has a very high impact on economic growth. Also, the effectiveness of the government and political stability increase economic growth.

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.

During the last two decades, with the increase in international exchange of goods and services, environmental problems, including climate change and global pollution, have increased significantly. The global effort to reduce environmental problems has put the importance of production and international trade of environmental goods on the agenda of many developed and developing countries. The environmental goods emphasized in this study include those goods that are produced or consumed by industry to reduce and manage pollution (air and water). The international effort to reduce greenhouse gas emissions has put the importance of this category of goods at the forefront of global negotiations. Considering the importance of the topic, the main goal of this study is to investigate and identify the trend of trade in environmental goods in the world and developing countries, as well as to identify its composition. The studied period includes 1996-2021. The results show that the global trade in environmental goods has increased significantly and increased nearly four times during the years 1996-2021. During this period, the position of developing countries in the export of environmental goods has increased significantly. The share of developing countries' exports from the total global export value of environmental goods increased from 7.4% in 1996 to 25.7% in 2021. In this, the participation of countries such as China, South Korea, Mexico and Singapore is very evident.

The tourism sector plays a pivotal role in national economic development because it promotes the development of related industries such as transportation. The boosting effect of tourism on economic growth is more obvious in developing countries with abundant tourism resources (Dieke, 2003). However, tourism development undergoes great dynamic changes due to complex and volatile external environments, such as global climate change and social disturbances with a high degree of uncertainty (Nguyen et al., 2020; Scott et al., 2019). thus, the tourism economy has become very fragile and has a weak ability to withstand risks from various sources (Wang et al., 2022). Therefore, this study attempts to examine the Indirect impact of tourism on economic vulnerability and other factors affecting economic vulnerability in selected developing countries over the period 1995-2021 by using a panel smooth transition regression model.

In this study, the nonlinear threshold effect of tourism on economic vulnerability in selected developing countries is examined using a PSTR model. For this purpose, following Gonzalez et al. (2005) and Colletaz & Hurlin (2006), a PSTR model with two regimes and a transition function is defined. according to the study of Colletaz & Hurlin (2006), can be chosen among the explanatory variables, the lag of the dependent variable, or any other variable outside the model that is theoretically related to the model under study and causes a nonlinear relationship.qit  represents the transition variable and, according Gonzalez et al. (2005) suggest that, in practice, considering one or two thresholds, m = 1  or m = 2 , is sufficient to account for parameter variability. For m =1 , the model implies that the two extreme regimes are associated with low and high values of transition variable with a single monotonic transition of the coefficients from β0  to β0+β1 as transition variable increases, with the change centered around location parameters. When →∞  , transition function the model becomes an indicator function Iqit>c1 , defined as IA=1  when event A occurs and 0 otherwise. In this case, the PSTR model in (1) reduces to the two-regime panel threshold model of Hansen (1999). For m = 2, the transition function has its minimum at c1+c22  and reaches 1 at both low and high values of qit . In this case, the transition function (2) becomes constant for any value of m when γ → 0 . In this case, the model collapses into a fixed effects homogeneous or linear panelregression model. Accordingly, in the PSTR model, based on the observations of the transition variable and the slope parameter, the estimated coefficients are continuous and bounded between F = 1 and F = 0.As mentioned earlier, another salient feature of the PSTR model is that it provides a parametric approach to cross-country heterogeneity and time instability of the slope coefficients, allowing the parameters to change smoothly as a function of the threshold variable yit . More precisely, the income elasticity for the i th country at time t is defined by the weighted average of the parameters β0  and β1 . It is worth noting that the estimation of the parameters of the PSTR model consists in eliminating the individual effects by removing the individual means and then applying nonlinear least squares (NLS) to the transformed model (see for details, Gonzalez et al., 2005). This method is equivalent to maximum likelihood (ML) estimation in the case of normal errors.Following Gonzalez et al. (2005), Colletaz & Hurlin (2006), and Jude (2010), the estimation steps of a PSTR model are as follows: First, the linearity test against PSTR is performed using Wald Tests (LMw ) coefficients, Fisher Tests (LMF ) coefficients and LRT Tests (LR ) coefficient statistics according to Colletaz & Hurlin (2006). Once we have rejected the linearity hypothesis, we can verify that nonlinearity no longer exists. Then it is a matter of testing whether there is a transition function or whether there are at least two transition functions.

The results show that in the first regime, trade openness has a negative effect on economic vulnerability, which has decreased and turned positive after crossing the threshold location in the second regime. Government expenditure has a positive effect on economic vulnerability, and after crossing the threshold location and entering the second regime, its effect gradually decreased and became positive. Inflation coefficients in the regime had a negative and insignificant effect on economic vulnerability, which after crossing the threshold location and entering the second regime, its effect gradually decreased and became positive, but it was significant at the 10 percent level.Also, the results show that before the threshold location and at low levels of tourism income, the logarithm of financial development has a negative and significant effect on economic vulnerability, and after the threshold location and entering the second regime, this effect is still negative and increases. The coefficients of the logarithm of total unemployment have a negative effect on economic vulnerability in the first regime and before the threshold location. By crossing the threshold location and entering the second regime, this effect decreases and becomes positive.

In this study, the threshold and Indirect effect of tourism on economic vulnerability in selected developing countries during 1995-2021 was investigated. For this purpose, the PSTR model provided and developed by Gonzalez et al. (2005) and Colletaz & Hurlin (2006) was used. The estimation results suggested a nonlinear relationship between trade openness, financial development, government spending, total unemployment, inflation and economic vulnerability. Moreover, considering a threshold with two regimes or a transition function is sufficient to investigate nonlinear behaviors. The results show that the threshold of the transition variable is equal to 3.1378 and the slope parameter is equal to 33.8978, which include only one transition function and only one threshold.Considering the positive impact of tourism on financial development and government spending, it can be said that the development of tourism income can indirectly reduce the economic vulnerability of developing countries by increasing financial development and national income and adjusting industrial structures, while this mediating effect at the level Social does not appear. Therefore, it is suggested that considering that in developing countries where the overall economic strength of a country is weak, with low economic development, the development of international tourism should be cautious. The main task should be to create infrastructure and stimulate domestic consumption. Investment should be focused on industries such as manufacturing and financial development to increase the growth of GDP and improve people's quality of life. Physical needs are the most important factor to maintain economic stability and prevent economic vulnerability. For these countries, attention should be paid to domestic tourism by strengthening the construction of tourism service facilities, adjusting the structure of the tourism industry and ensuring the sustainable development of international tourism, while accelerating the development of domestic tourism.From an institutional perspective, creating active employment policies to create preferential employment conditions for low-income people can further ensure the positive impact of low-level international tourism on economic vulnerability. Finally, regardless of the level of economic development, one should have a clear understanding of the performance of the tourism industry based on the state of the country. This is possible by correctly positioning the tourism industry and not exaggerating the role of tourism and not giving up on its development due to some negative factors. Economic vulnerability can be effectively reduced only by combining tourism with other industries and focusing on overall economic development.

During the last two decades, with the increase in international exchange of goods and services, environmental problems, including climate change and global pollution, have increased significantly. The global effort to reduce environmental problems has put the importance of production and international trade of environmental goods on the agenda of many developed and developing countries.

Institutional restrictions influence trade and export of these goods. These restrictions include environmental regulations, quality of regulations and rule of law. The aim of the present study is to investigate the effect of this category of institutional restrictions on the export of pollution management goods in developing countries in the framework of the gravity model. In this article, the environmental goods under study include those goods, which are produced or consumed by industry in order to reduce and manage air and water pollution. The econometric model is estimated by panel data for period 1996-2021 and a sample of 131 developing countries, and 196 export destinations using the fixed effects method.

The results show that the institutional limitation from the perspective of strict environmental regulations and the quality of the institutional environment of the countries of origin has an effect on the export of environmental goods that manage pollution. This result is also true from the point of view of strict environmental regulations of export destinations. Therefore, in addition to the traditional factors affecting international trade, institutional restrictions are strong drivers of the export of pollution management goods in developing countries and their export destinations.

Therefore, policies based on institutional restrictions from the perspective of strict environmental regulations in developing and destination countries help the export flow of environmental goods that manage pollution and lay the foundation for the participation of developing countries in the global and regional value chain of environmental goods.

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 effects of government size on multidimensional poverty as an important factor in the process of development and growth of countries has a decisive role, and various aspects and areas in developing countries have always been affected by this category. Accordingly, one of the most important goals of economic planners is to reduce the size of the government in order to prevent the spread of poverty, especially multidimensional poverty. Without taking into account the different dimensions of poverty, it is not possible to make an accurate analysis of poverty and its effects on societies. Therefore, the current research aims to evaluate the effects of government size on multidimensional poverty for Iran and a selection of developing countries in the period of 2012-2021 using the method of generalized moments. The results of the study indicate that the government size index has a non-linear effect on multidimensional poverty. The government size index at its low levels has left a negative impact on multidimensional poverty, but the increase in the level of the government size index and its crossing of the threshold level of 18.33 has caused the aggravation of multidimensional poverty. On the other hand, the first break of multidimensional poverty has had a positive effect and the control of corruption and public health has had a negative effect on multidimensional poverty.

Answering the fundamental question of whether technological progress can lead to unemployment has always been one of the most challenging issues in economics. In this regard, the present study investigates the effect of technology-based innovations (including process innovation and product innovation) on unemployment using panel data techniques (random effects model) and data from a sample of developing countries during the period 2008-2018. To this end, the number of patents registered is considered as an index of process innovation and the ratio of research and development (R&D) expenditure to GDP is considered as an index of product innovation. Moreover, GDP per capita, inflation and trade openness are included in the model as control variables. The results obtained from the estimation of the panel model show that both the growth of process innovation and the growth of product innovation reduce unemployment. In addition, the empirical results indicate that GDP per capita and trade openness have a negative and significant effect on unemployment, but the effect of inflation on unemployment is not statistically significant. Overall, the findings of this study have important policy implications for dealing with the problem of unemployment in developing countries through increased investment in R&D and stronger patent protection.