سامان قادری

Climate change has become one of the major global challenges due to its widespread impacts on human ecosystems and the environment. In this context, good governance, through appropriate management and strong measures against climate change, plays a crucial role in preserving natural resources and mitigating its negative effects. The aim of this study is to examine the impact of good governance on climate change performance in selected countries over the period from 2017 to 2020. In this regard, the study employs a panel threshold regression approach and bootstrap simulation method to approximate the limiting distribution of the test statistic. The findings from the non-threshold model estimation indicate that good governance has a significant and positive impact on climate change performance. On the other hand, the estimation of the threshold random-effects model suggests the existence of a threshold value of 60.345% for the good governance index. Taking the threshold effect into account, the results show that both before and after the threshold, good governance has a positive and significant impact, reducing climate change. In other words, it has a positive and significant effect in both regimes. Therefore, good governance has an impact on climate change performance and can act as a mitigating factor for climate change in both developing and developed countries to control the increasing trends of climate change. Furthermore, according to the results of this study, the economic growth variable has a positive effect, while industrialization and research and development expenditure have a negative and significant effect on climate change.

Economic freedom plays a crucial role in assessing a nation's economic development. It grants individuals or communities the ability to make decisions according to their own desires or intentions. Economic literature from the 1990s onwards has primarily focused on the quality of institutions and economic freedom for the development of countries' economies. Consequently, empirical studies have placed greater emphasis on this subject. The aim of this paper is to examine the effects of value-added in agriculture, industry, services, and foreign direct investment on the economic freedom index from 1990 to 2021 using a Quantile Regression approach. The results of this study indicate that the value-added in agriculture, services, and industry has a positive and significant effect on the economic freedom index. Furthermore, the study suggests that while foreign direct investment has a positive impact, it is relatively weak on the economic freedom index.

In recent years, the COVID-19 pandemic has imposed considerable harm on economies globally. This situation has prompted researchers to thoroughly examine the issue from different perspectives and view bolstering the resilience of countries as the most effective strategy to address the vulnerabilities. Such efforts can mitigate the harmful effects and negative outcomes of the disease. The susceptibility of economic systems to the shock of the COVID-19 pandemic varies, with some being significantly more vulnerable to its effects. In this context, the greater a country's ability to mobilize its resources against such risks, the more resilient it becomes. Hence, economic resilience is regarded as a comprehensive approach to enhancing the existing capacities and reducing economic vulnerability in the face of various crises and environmental threats. Moreover, economic resilience is shaped by the implementation of economic policies and has an accumulative nature. Individuals and different schools of thought have focused on the concept of resilience within the economic realm, structuring their studies accordingly. Economic resilience emerges as a pervasive criterion in the literature on economic stabilization.In the economic discourse, particular emphasis is placed on assessing the composite index of economic resilience against external shocks, aiming to quantify this notion. This study sets out to investigate how the COVID-19 pandemic has impacted the economic resilience of countries across high, medium and low levels of income. Addressing 150 nations, this research employs the PSTR model over the timeframe spanning 2020 to 2021. The Economic Resilience Index is computed utilizing the Bruegel method for this inquiry. 

The PSTAR (Panel Smooth Transition Autoregressive) model is a powerful tool utilized to analyze nonlinearities and regime shifts in panel data. It extends traditional autoregressive models by allowing for smooth transitions between different states or regimes, thereby capturing complex dynamics in economic time series data.The PSTAR model assumes that the relationship between variables evolves smoothly over time and across different regimes. It is particularly useful in capturing threshold effects, where the impacts of one or more variables on the dependent variable change abruptly beyond a certain threshold level. This is achieved through the specification of transition functions, which determine how the model transitions occur between different regimes based on the values of certain threshold variables. The PSTAR model estimation involves several steps, including the specification of transition functions, estimation of model parameters using maximum likelihood or other suitable methods, and diagnostic checks to assess the model's goodness-of-fit and validity of assumptions. Additionally, we conduct robustness checks and sensitivity analyses to ensure the reliability of our findings.

This study reveals a significant negative impact of the COVID-19 pandemic on the economic resilience of countries across different income levels. Employing a two-regime model, the analysis demonstrates a nonlinear correlation among the variables, suggesting varied adjustment speeds among economic regimes. Specifically, countries with high incomes experience a moderate pace of adjustment, those with moderate incomes adjust slowly, and low-income countries adjust rapidly. This suggests that economic changes in response to the pandemic occur at different speeds across income groups.The COVID-19 pandemic has induced structural and performance alterations in economies worldwide, including increased unemployment, reduced growth, and shifts in consumption and investment patterns. These changes, coupled with challenges such as quarantine restrictions and decreased incomes, have led to considerable adjustments in economic dynamics, varying in speed from one state to another.Overall, economic changes during the pandemic are of significant diversity across countries, affecting consumption and production behaviors, policy frameworks, and international relations. Threshold values, representing critical points of pandemic severity, determine whether economic variables behave linearly or nonlinearly. When the pandemic's impact surpasses these thresholds, economic variables begin shifting to nonlinear regimes.Estimations from the smooth panel regression approach indicate a notable negative effect of the pandemic on economic vulnerability, affecting countries with high, medium, and low incomes alike. Per capita GDP, remittances, and foreign direct investment emerge as key influencers of economic resilience. While per capita GDP decreases during the pandemic for high and medium-income countries, it increases in the second threshold regime and boosts economic resilience. Remittances positively impact economic resilience in high-income countries but negatively affect medium and low-income ones initially, transitioning to positive effects after crossing the threshold. Foreign direct investment initially reduces economic resilience across all income levels but becomes positive and significant in high-income countries after crossing the threshold.In summary, the study underscores the complex interplay between the COVID-19 pandemic and economic resilience, emphasizing the need for tailored policy responses to mitigate its adverse effects across different income groups.Conclusions and Policy Implications: Although the public health system is evolving, the world remains susceptible to shocks caused by contagious diseases that present fundamental challenges to economies. The vulnerability resulting from the COVID-19 pandemic has spurred countries to allocate more funds to ensure economic security and global health. Nations across the globe are working to reduce the economic impact of the COVID-19 crisis through well-balanced policies, seeking to mitigate risks to the society as much as possible. To tackle the COVID-19 crisis, extensive actions are being taken, including sharing knowledge and experiences regarding strategies, policies and improvement plans, examining common responses, and coordinating actions to enhance resilience and effective recovery preparedness. Strengthening communication among policymakers, development planners, and relevant stakeholders, establishing strong multilateral institutions with political support for global health shock coordination, creating fast financial procurement mechanisms for essential goods, increasing investment in disease surveillance at global and regional levels, developing regional production capacities for vaccines, tests and medicines, sharing medical technology and knowledge, and transferring medical technologies are the measures being taken. Additionally, strategic approaches to national improvement, including economic and financial measures, effective financial procurement design, and financial resource mobilization efforts to mitigate the effects of COVID-19, are being pursued. These measures aim to enhance the resilience and sustainability of public health systems and foster systematic research and development for the preparation of effective and safe vaccines against any virus. Therefore, based on the findings of this research and similar studies, policymakers need to focus on strengthening the economic resilience of countries, in addition to implementing other policies aimed at reducing the spread of and preventing the COVID-19 disease. These actions may include policies to strengthen healthcare infrastructure, develop economic and social crisis response plans, and encourage the development of human resources needed to combat the disease and its economic impacts.

Examining the state of countries' welfare requires indicators that adequately show the well-being of people's lives. One of the indicators that can affect this issue is the economic welfare index provided by the Sustainable Society Foundation. In this research, the impact of economic globalization on the economic well-being of developed and developing countries from 2000 to 2020 was investigated using the panel smooth transition regression (PSTR) method. The results show the existence of a non-linear relationship between the research variables. Also, for developed and developing countries, two transfer functions and two thresholds representing a three-regime model were chosen as the optimal model. For developed countries, the speed of adjustment, i.e., the transition from the linear regime to the intermediate regime, is carried out much faster than the transition from the intermediate regime to the third limit regime. Also, for developing countries, the regime transition is done at a moderate speed in all three regimes, but the transition from the first regime to the middle regime is faster than the transition from the middle regime to the third regime. Economic globalization in developed countries has a negative effect on economic well-being in the first limit regime and a positive effect in the second and third limit regimes. While in developing countries, economic globalization has a positive effect on economic well-being in all three regimes. Considering the different effects of economic globalization on the welfare of countries, economic policies should be designed to take advantage of the positive opportunities of globalization in developed and developing countries and accelerate the transition to more favorable regimes. Especially in developing countries, strengthening infrastructure and upgrading economic capacities can help to benefit more from the benefits of globalization.

One of the most important challenges of societies in the last few decades is the destructive and repeated human activities to destroy the environment. The ecological footprint is the latest index measuring the extent of individuals’ influence and engagement in addressing the issue of climate change as well as their negative impact on the environment. The economic policies adopted by societies have a significant effect on the process of ecological footprint. Monetary and Fiscal Policies are among the most important policies that, in addition to affecting the productive and economic activities of society, also affect the environment. Therefore, the main purpose of this study is to investigate the effect of monetary and Fiscal policies on the ecological footprint in Iran during the period from 1980 to 2021 and using the structural vector autoregression method. “Liquidity and the government’s final consumption expenditures have been employed as monetary and fiscal policy tools, while economic growth, urbanization, and foreign direct investment have been utilized as control variables.” The results of this research show that foreign direct investment and urbanization have a negative and significant impact on the ecological footprint. Also, economic growth, monetary policy, Fiscal policy and the dependent variable itself have a positive and significant effect on the ecological footprint and lead to an increase in the ecological footprint during the mentioned time period. On the other hand, fiscal policy impulses in the long term have resulted in a rise in environmental degradation in Iran. The results of variance analysis in the 10th period show that monetary policy explains 6.70% and Fiscal policy 24.06% of changes in the dependent variable.

The current research provides new evidence regarding the impact of innovation and creative industries on the process of economic wellbeing. In this context, a smooth transition panel regression approach has been utilized for the period from 2013 to 2020. The optimal model for developed countries was estimated with two threshold levels and two transition functions, while for developing countries, it was estimated with two threshold levels and one transition function. In developed countries, the speed of transition from the first limit regime to the second limit regime was equal to 14.0361 and the speed of transfer from the second limit regime to the third regime was equal to 28.2824, which shows that the transition from the first regime to second regime smoother than the transition from the second to the third regime. In developing countries, the speed of transition from the first regime to the second is equal to 25.6488, which indicates a smooth transition from the first regime to the second regime. The results indicate that innovation in developed countries has a significant negative impact on economic welfare in the first regime, but this impact turns positive and significant in the second and third regimes. In developing countries, innovation does not significantly affect economic wellbeing in the first regime, but it has a positive and significant effect in the second regime.

Improving the level of social welfare is one of the main aims of countries. Various factors can affect social welfare the privatization is one of these factors. this study has investigated the effect of privatization on social welfare in Iran based on Amartya Sen social welfare index during the period 1991 to 2022 Using the smooth transition regression approach. The control variables of the research include trade openness, industrialization, energy consumption and carbon dioxide emissions. Based on the findings of the research, the optimal model is non-linear with 2 regimes and the transition from regime 1 to regime 2 has happened very gently. The results indicate that privatization before the threshold value of 2476.16 during 1991 before 2003 has a positive and significant effect on the social welfare index and after passing the threshold value during 2003 to 2022, the positive effect has decreased and gradually changed to a negative effect. Trade openness has no significant effect on social welfare in the first regime and has a negative and significant effect in the second regime. Industrialization and energy consumption variables had a negative and significant effect in the first regime and a positive and significant effect in the second regime.

Nowadays, good governance is recognized as a fundamental concept that holds significant importance at every level of organizations and societies. This type of governance, which focuses on transparency, justice, participation, and efficiency, profoundly impacts performance and development. Through transparent and accountable processes, good governance strengthens public trust and contributes to sustainable development. On the other hand, unemployment, as an economic and social phenomenon, is of notable importance. Therefore, the primary aim of this research is to examine the impact of good governance on the unemployment rate in Iran during the period from 1990 to 2021 using the quantile regression method. To achieve the research objective, variables such as foreign direct investment, per capita GDP, the real effective exchange rate, and the inflation rate have been used as control variables. The results of this study indicate that the good governance index has a negative and significant effect on the unemployment rate across all unemployment rate deciles. Per capita GDP and foreign direct investment also have a negative and significant impact on the unemployment rate across all deciles. Meanwhile, the inflation rate and the real effective exchange rate have a negative and significant effect on the unemployment rate from the first to the fifth decile, and a positive and significant effect from the sixth to the ninth decile.

The Covid-19 pandemic, as one of the recent world crises, has brought costs to the economies, which has drawn the attention of researchers and politicians to the concept of economic vulnerability in the form of a warning index to evaluate this external shock. The main aim of this study is to investigate the impact of the COVID-19 pandemic on economic vulnerability in high, medium, and low-income levels countries. This study was conducted for 150 countries using the Panel Smooth Transition Regression (PSTR) approach over 2020-2021. In this regard, the Briguglio method was used to calculate the Economic Vulnerability Index. The results of this research indicate that the COVID-19 pandemic has had a positive and significant effect on the economic vulnerability of countries. The linear test results confirm the non-linear relationship between the variables. Moreover, by considering a transfer function with a threshold parameter (the level of COVID-19 morbidity and mortality), a two-regime model is presented to specify the non-linear relationship between the pattern variables for three groups of high, medium, and low-income countries. The slope parameter (transfer rate) for these three groups of countries is 5.9876, 6.1569, and 3.9987, respectively. The model estimation results show that in both linear and non-linear regimes, COVID-19 has a positive impact on the economic vulnerability of countries with high, medium, and low incomes, meaning that an increase in the COVID-19 pandemic has led to a decrease in the economic vulnerability of these groups of countries.

Through extensive research and data collection, a sample of 150 countries for the period 2020-2021 has been selected. The primary criterion for selecting countries and the period is the availability of data. The research database includes sources such as the World Bank, the International Monetary Fund, and the United Nations Development Organization. The dependent variables in this study are the Vulnerability Index. The Vulnerability Index is constructed based on the Briguglio method using four components: 1) Trade openness 2) Export concentration 3) Dependency on strategic imports, and 4) Exposure to natural disasters. Other variables included in the model are the number of COVID-19 deaths, per capita gross domestic product (GDP), foreign direct investment, and remittances as a percentage of GDP, which have been collected from the World Bank and other reliable sources. This study used Panel Smooth Transition Regression (PSTR) approach. PSTR is a statistical model that is commonly used to analyze the non-linear relationships between economic variables. This model is particularly useful for investigating the behavior of variables that exhibit non-linear patterns or changes in their behavior over time. PSTR is a flexible model that can be used to capture the complex relationships between different variables, making it a popular choice in various fields, such as economics, finance, and social sciences. The PSTR model is an extension of the Smooth Transition Regression (STR) model, which is a non-linear regression model that allows for the specification of the transition function between two different regimes. In the PSTR model, the transition function is extended to include panel data, which allows for the analysis of the non-linear relationships between variables across multiple units, such as countries or firms, over time. PSTR is a powerful tool for analyzing the impact of various economic factors on different regions or countries. For example, it can be used to investigate whether the impact of a particular economic policy or event is uniform across different countries or regions, or whether it varies depending on the level of economic development or other relevant factors. Additionally, PSTR can be applied to different types of data, including cross-sectional, time series, and panel data, making it a versatile tool for analyzing a wide range of economic phenomena.

the vulnerability model indicates that the slope parameter, which represents the speed of transition from one regime to another, is equal to 1191.414, and the regime change location is 435.6, with the logarithm of its anti-value being 2213094. Therefore, as long as the COVID-19 pandemic (mortality) value is less than the anti-logarithm values, the variables will behave according to the first regime. If the value of the COVID-19 pandemic exceeds the anti-logarithm values, the variables will follow the second regime. Based on the results of the two regimes, it is evident that the COVID-19 pandemic variable has had a positive and significant impact, both linear and nonlinear on countries. This means that the increase in the COVID-19 pandemic has led to an increase in the economic vulnerability of countries. In other studies, such as Brzyska & Szamrej (2021), Marti (2021), and Puertas, it has been demonstrated that the COVID-19 pandemic has had a positive and significant effect on the vulnerability of countries in the European Union, which mostly includes high-income countries.

This paper examines the impact of the COVID-19 pandemic on economic vulnerability in 150 countries during 2020-2021. The results obtained from the Panel Smooth Transition Regression (PSTR) model confirm a nonlinear relationship between the variables and the presence of two threshold regimes with a threshold for economic vulnerability and model. It also indicates that the COVID-19 pandemic has a positive effect on vulnerability. This means that an increase in the COVID-19 pandemic has led to an increase in vulnerability and a decrease in economic resilience in these countries.

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.

Energy security is one of human society's most important topics, affecting many tensions and relations between different countries. Considering the breadth of the concept of energy security and its mutual effects in the economic, political, social and environmental fields, it has become an essential concern of governments and thinkers. The energy security risk index examines a country’s level of security risk e factors affecting energy security in geopolitical, economic, political and environmental fields by measuring 29 determining components. The main goal of the current research is to investigate the impact of renewable and non-renewable energy consumption on the energy security risk in Iran from 1980 to 2020 using the structural vector autoregression (SVAR) method. The obtained results show that the consumption of renewable energy has a negative and decreasing effect, and the consumption of non-renewable energy has a positive and increasing impact on Iran’s energy security risk. Also, the added value variables of the industry sector and government size have a positive and increasing effect on the energy security risk in Iran. On the other hand, the results of this research show that one of the reasons for the increasing trend of the energy risk index for Iran is the rising consumption of non-renewable energies. Following that, the amount of environmental pollution has also been increasing; Therefore, to prevent this, policies should be implemented to reduce the consumption of this type of energy and to replace it with other energy, including renewable energy.

One of the most important factors influencing the exchange rate volatility is currency substitution due to the dollarization of the economy. Currency substitution is a common phenomenon in developing countries. The purpose of this study is to investigate the asymmetric effect of currency substitution on exchange rate volatility in Iran. In this study, the quarterly data of Iran's economy during the period 1990-2021has been used by applying the Bound test method and autoregressive with distributive Lag and Markov switching methods. Based on the results, Model MSIH(2)-AR(2) was chosen as the optimal model. In addition, in measuring the amount of money, due to the important role of defining the amount of money from monetary aggregates, simple sum and Divisia are used. The results show that the Divisia monetary aggregate is more appropriate than the simple sum in the expression of asymmetries. Currency substitution in the low-volatility regime had a negative effect on exchange rate volatility, but in the high-volatility regime, the effect of currency substitution was significantly positive. It illustrates the asymmetry effect of currency substitution on exchange rate volatility in various exchange rate regimes and confirms the asymmetric effect of currency substitution on exchange rate volatility.

Aim and Introduction :

Nowadays, the environmental impacts of human activities are considered one of the limitations of economic growth. Developing countries are facing the problem of environmental degradation, which hinders economic growth and development. On the other hand, the process of economic development of countries has become one of the environmental challenges and one of the most critical concerns of policymakers over the years. Due to the significant role of the government in the economy of the countries, government economic enterprises are also sources of pollution along with the private sector. The main reason is the unprecedented concentration of greenhouse gases, which leads to the intense and continuous production of carbon dioxide gas. In addition to being a dangerous factor for human health, air pollution also has an economic burden on societies, which causes a decrease in the quality of life and the welfare of society. Thus, developing countries, including Iran, are facing the problem of environmental degradation. Privatization can be a helpful policy and a government tool to influence economic productivity and social welfare through ecological pollution control. Most domestic research on privatisation's impact on environmental pollution has been interview-based and qualitative. For this reason, this research aims to investigate the impact of privatization on carbon dioxide emissions in Iran using the time-varying parameter vector autoregression (TVP – VAR) model. The model is considered dynamic due to the time factor, and the impact of privatization on environmental pollution in Iran can be accurately observed in different years.

The present study investigates the impact of privatization on environmental pollution in Iran during 1991-2020 using the data of the Privatization Organization, the Central Bank of Iran, the World Bank, the Globalization Index website, and the energy balance sheet of the Ministry of Energy. Furthermore, the time-varying parameter vector autoregression (TVP – VAR) model has been used to study the relationship between variables. In this method, the optimal interval length of the model was determined first. Then, the data durability was checked through the unit root test of Zivot and Andrews (1992), considering the structural break. The next step examined cointegration tests, serial correlation, variance heteroscedasticity, and polynomial inverse root circle tests. In the end, the results of the impulse response function of the TVP – VAR model were presented. For this purpose, the emission rate of carbon dioxide has been used as an index of pollution, and the value of the transfer of shares and assets from the public sector to the private sector has been considered an index of privatization. The TVP – VAR method, unlike the vector autoregression model, allows the calculation of variable coefficients over time. Due to changing conditions, structural break and cyclical changes were observed in time series in macroeconomics. As a result, the TVP – VAR model enabled us to accurately obtain the nature of the economic structure’s temporal changes.

In this research, the mechanisms of the impact of privatization on environmental pollution have been analyzed, and the time series data of 1991-2020 and the TVP-VAR model have been used as experimental work. The present research findings show that despite the incomplete, unscientific, and politicized implementation of privatization in Iran, privatization has reduced the emission of carbon dioxide gas in Iran.

Based on the results, the relationship between the privatization index and environmental pollution is confirmed. It indicates that privatization has a negative and significant effect on the emission of carbon dioxide in Iran. With the increase of privatization, pollution is decreased because when privatization increases, the productivity of labor and capital and the access to new technology for reducing pollutants is also increased. In developing countries like Iran, economic issues are prioritized over environmental considerations, leading to policymaking without considering environmental costs. In contrast, by including environmental calculations in the studies related to economic policies, it is possible to view the environmental damage caused. Based on the results, it is concluded that the economic globalization index, investment, gross domestic product without oil, and human development index have significant and positive effects on production and carbon dioxide emissions. When the size of the government increases, efficiency and productivity decrease. In Iran, one solution can be importing environment-friendly technologies and more investment in this area. According to the results, it can be seen that the increase in privatization can reduce greenhouse gases, and this is due to the rise in the efficiency of private companies in the exploitation and optimal use of natural resources. Thus, policymakers can consider privatization as a part of the solution to fight environmental pollution.3

The current research's main aim is to investigate globalization's impact on industrialization in Iran from 1979 to 2020 using vector autoregression model with time-varying parameters (TVP-VAR). The industrialization and economic globalization indexes have been used to achieve the research purpose. On the other hand, foreign direct investment, government size, and gross domestic product per capita have been used as control variables. This research illustrates that economic globalization has a very positive effect on industrialization in Iran. As a result, it is suggested to the policymakers to reduce international tensions between Iran and other countries to augment globalization, increase the import of new technologies and amplify industrialization. On the other hand, foreign direct investment has a very positive effect on industrialization in Iran. Moreover, GDP per capita has a positive but less intense effect on the industrialization index. Finally, the size of the government has a very negative impact on industrialization in Iran. As a result, policymakers are suggested to consider globalization as a critical and vital factor in increasing industrialization in Iran.

The amount of innovation has a fundamental and tremendous impact on the economic growth and development of a country, which has caused most researchers and policymakers to pay attention to creativity and innovation as a new solution for development. For this reason, several studies have been conducted in relation to the factors affecting innovation at the micro level (companies and enterprises) and at the macro level (at the level of different countries and regions). Therefore, the purpose of this study is to investigate the effects of human capital and social capital on innovation in selected members of OPEC countries, including Iran, Saudi Arabia, Kuwait, Qatar, and the United Arab Emirates during 2012-2021 using the Panel ARDL approach. The results of the model have shown that in the short term, among the variables, only two variables, human capital (HC) and Research and Development (R&D), have a positive and significant effect on the global innovation index in the short term, and other variables in the short term have not a significant effect on the innovation index of countries. Also, the examination of the long-term coefficients of the variables shows that human capital, social capital, gross domestic product and research and development expenditure have a significant and positive effect on the global innovation index in countries. Therefore, it is suggested that increasing human capital and research and development expenses should be prioritized in short-term planning for the innovation index in society. Also, government spending should be increased in sectors that have high innovation potential and capacity in those sectors.

Industrialization is the engine of economic growth on the one hand, and on the other hand, it has the greatest effect on the emission of carbon dioxide. According to the economic literature, one of the most important factors in the emission of air pollutants is industrialization and the production structure in the industrial sector. Based on this, the aim of this research is to investigate the effect of industrial concentration on carbon dioxide emissions. This research was conducted using the panel data econometric model for 30 provinces during the period of 2010-2017. Investigating the industrial concentration index shows that the highest value is related to Bushehr province with 0.66 and the lowest value is related to Qazvin province with 0.018. In addition, at the country level, this index has increased from 0.110 in 2010 to 0.114 in 2017. The results of the model estimation show that industrial concentration, energy intensity, population and GDP have a positive and significant effect on carbon dioxide emissions. According to the research results, diversification of industrial activities in Iran's provinces is recommended based on regional advantage and the use of new production technologies to reduce energy intensity and thus reduce the emission of pollutants.

One of the factors affecting the industrialization of the economy is human capital. In many previous studies, education has been used as a traditional index of human capital, but in addition to education, human capital is also affected by other aspects such as skills and health. Given that industrialization is a dynamic process, the present study has investigated the effect of human capital on industrialization in Iran during 1981-2019 by using the Generalized Moment Method in the context of time series and also applying traditional and comprehensive indicators of human capital. In this regard, using fuzzy logic, the comprehensive index of human capital has been estimated by considering three aspects of education, skills and health. The results show the significant growth of human capital during the study period. The results of estimating the model using the traditional index of average years of education showed the insignificant and inconsistency of coefficients and the estimation results using the comprehensive index of human capital showed that the promotion of human capital level leads to increasing value added of industry as a percentage of GDP. Also, the effect of the first lag of industrialization, labor force participation, capital stock and technical progress has been evaluated positively and significantly.

Given the importance of income inequality, which is one of the major problems of macroeconomics, especially in developing countries, and considering the direct impact of remittances on the income of recipient households, the purpose of this study is to investigate the effect of remittances on income inequality. In this regard, the panel threshold regression approach for selected developing countries in the period 2018-2000 using the bootstrap simulation method has been used to approximate the asymptotic distribution of test statistics in Stata software. Findings from estimating the non-threshold linear model showed that the relationship between remittances and income inequality is negative and statistically significant, so that increasing the amount of remittances reduces the income inequality by 0.12 units. On the other hand, estimating the threshold fixed effects model indicates the existence of a threshold of 8.43% for the inflation rate and different effects of remittances on income inequality in two different inflation regimes. Considering the threshold effect, in order to investigate the effects of remittances on income inequality, the results show that remittances before the inflation threshold (low inflation regime), remittances reduce income inequality, but after the threshold (High inflation regime) remittances had a negative effect on income inequality but were not statistically significant. Therefore, the existence of high inflation can neutralize the effect of remittances on income inequality in countries with inflation above the threshold. Also, according to the results of the present study, the economic growth variable has reduced income inequality, but the variables of government size, trade openness, population growth rate and unemployment rate have increased income inequality.

Horizontal and Vertical Intra-industry trade (HIIT and VIIT) determine the real competitive and relative advantages of countries considering the method and technology of production. In the course of development and expansion of its commercial relations, Iran requires a suitable pattern to identify and strengthen the competitive and relative advantages in efficiency sectors, as well. One of these sectors is the industry sector that development and growth of which need technological development. This, in turn, the development of technology affected from investment in domestic research and development (R&D) and purchase of foreign technology (capital and intermediate commodities).  Accordingly, in this research, the spillover effects of R&D on horizontal and vertical intra-industry trade in Iran’s manufacturing industries have been investigated. To this end, based on the latest available data of Iran’s manufacturing industries at the 4-digit aggregation level of ISIC classification during 2004- 2016, panel data estimation method has been used. The results of fixed effects estimation show that the accumulation of domestic and foreign R&D don’t have a positive effect on HIIT and VIIT. Also, results indicate that the spillover of accumulation of foreign R&D by import have a negative and significant effect on HIIT and VIIT but, the spillover of accumulation of foreign R&D by human capital has a positive and significant effect on HIIT and VIIT. Thus, it’s proposed to invest in human capital and R&D, in order to facilitate the absorption and dissemination of hidden imported technology in the intermediary and capital commodities of business partners, that this produce the qualifier commodities and help for increasing the intra-industry trade share in international level.

The commodities especially oil, wheat and iron have key role in economy because of they are the main components of many common goods in human lives. An increases or a decrease in the commodity prices affects the economies all over the world. Despite the importance of commodity prices, only few studies have emphasized their impact on stock prices. This study contributes to the empirical literature about the relationships between stock and commodity markets. Given that the Tehran Stock Exchange is a commodity-based market, the purpose of this study is to investigate the effect of world commodity price on Tehran stock returns.

In this study, the monthly data of stock market during the period of 2009–2019 were used by applying Markov switching model with time-varying transition probabilities (MS-TVTP).

Based on the results, model MSIH (2)-AR (1) has been chosen as the optimal model. In the estimated model, the first regime determines the lower stock return and the second regime determines the higher stock return, and transmission probabilities in two models represent the persistence of first regime in the stockmarket of Iran. In addition, results show that one percent increase in commodity price will lead to 0.343 percent increase in stock return, but in the higher Stock return regime, lead to a 1.133 percent increase in stock returns. In this regard, the inequality of the two coefficients in the two regimes has confirmed by the Wald test. Also, expected duration in lower stock return regime is about 12 months and in higherstock regime is about 6 months.

This study illustrates the asymmetric effect of commodity priceon stockreturn in various regimes in Iran. It indicates that lower stock return regime is more stationary. Therefore, this study proposes to use the commodity price index as a warning indicator of a change in the stock return regime for investors.

The purpose of this study is to compare the impact of Global Metals Price Index on the stock returns of Base Metals group and Extraction of Metal Minerals group in the Tehran Stock Exchange. In this respect, the monthly data of stock market during the period of 2009M01–2019M05 has been used by applying Markov switching model with Fixed Transition Probabilities (MS-FTP). Based on Akaike information criterion, MSIAH (2)-AR (1) and MSIH (2)-AR (1) were proposed as optimal models in metal and Extraction of Metal Minerals groups, respectively. In estimated models, the first and second regimes determine the high and low stock return. In addition, results show that in the high and low stock return regime of metal group, one percent increase in global metals price will lead to 0.477 and 0.365 percent increase in stock return, respectively. Also, results in Extraction of Metal Minerals group indicates that in the high stock return regime, one percent increase in global metals price lead to 0.535 percent increase in stock returns but is not effective in low stock return. Therefore, the change of global metals price could be having the important role in signaling of changing stock returns especially in high stock return regime.

The aim of this study is to investigate the role of total factor productivity (TFP) in adjustment costs of labor in the Kurdistan province’s manufacturing  industries.  For this purpose, TFP is measured and analysed using Divisia index in the province’s industry in 4-digit ISIC codes. Different indicators are used for calculating the adjustment cost. In this study, for estimating adjustment costs, two indicators including the effect of total reallocation and the absolute of employment changes have been used. The results of model estimation by using  pooled data method over the period 2004-2013, show that the Divisia index of TFP reduced the adjustment costs in  manufacturing  industries. Also, the results show that the  human capital has a negative and significant impact on the adjustment costs. Therefore, it is recommended that in using the production increasing policies, in order to prevent of the unintended adjustment costs,  TFP promotion is emphasized.

This study examines the hysteresis effect of currency substitution in Iran using a model of money-in-the-utility function with two currencies (home and foreign). In this respect, Divisia monetary aggregates has been used for calculating the dollars in circulating. The bounds testing approach to the analysis of level relationship proposed by Pesaran et al. (2001) and Autoregressive Distributed Lag (ARDL) model have been used for Iranian quarterly data during 1990- 2014. The results indicate that there is evidence supporting the existence of the hysteresis effect of currency substitution in Iran. In other words, currency substitution process is irreversible. Therefore, it is suggested that the central bank consider the effect of the hysteresis of dollarization phenomenon on monetary policy and the purpose of controlling inflation and reducing exchange rate volatility as the main reasons of currency substitution, continues to be a priority for economic policy.