Economic complexity means a country's ability to produce and export more diverse products with less inclusiveness. Societies with efficient institutions internalize externalities and direct investment in productive activities lead to increased economic complexity. Democracy, by ensuring a stable political environment, stable economic framework, and social efficiency, promotes the accumulation of human capital, investment, and sustainable economic growth. One of the main contributions in this study is using multidimensional aspect of democracy (electoral democracy, liberal democracy, participatory democracy, consultative democracy, egalitarian democracy) to investigate the effect of democracy on economic complexity.

The purpose of this study is to investigate the effect of democracy on economic complexity. The data of 109 developing and developed countries during the period of 1995-2021 and a systemic generalized moments approach (SYS-GMM) have been used. The estimation also has also been done and the results compared separately for developing and developed countries.Research model based on studies (Njangang & Nvuh-Njoya, 2023) has been specified. In the present study, the 5 indicators of democracy by V-DEM database have been used including electoral democracy, liberal democracy, participatory democracy, consultative democracy, egalitarian democracy. This measure of democracy ranges from zero, which is poor quality to one which is considered to be the best quality democracy. Any increase from zero to one, indicates the improvement of democracy. The variables of economic growth, government size and population size were used as control variables in the model.  The two indicators of political rights and civil liberties used to check robustness. The data is extracted from the database of Freedom House and measured from 1 to 7 in which 1 indicates the highest degree of freedom and political rights and 7 indicates the lowest level. These two indicators used to show the stability of the estimated coefficients of the research model.  In order to check the robustness of the estimated coefficients, the results of the SYS-GMM estimator have been compared with the results of the two-stage generalized moments (GMM) and Feasible Generalized Least Squares (FGLS) estimators.

In this research, we investigate the effect of democracy on economic complexity using the systemic generalized moments approach (SYS-GMM). Democracy affects economic complexity through three paths of "innovation", "human capital" and "financial development" The results of this research show the positive and significant effect of all democracy indices on economic complexity. Moreover, the positive effect of economic growth, government size and population on economic complexity is confirmed. The stability of the estimated coefficients of the model as well as the consistency of the estimation results have been checked by the SYS-GMM estimator as a sensitivity analysis. Political rights and civil right variables were used to compare the results with democracy index. The results of the SYS-GMM estimator have also been compared with the results of the two-stage Generalized Method of Moments (GMM) and Feasible Generalized Least Squares (FGLS) estimators. The stability of the estimated coefficients has been observed in all methods.

The purpose of this study was to investigate the impact of democracy on economic complexity during the period of 1995-2021 using the systemic generalized moments approach (SYS-GMM) for 190 countries. For this purpose, from the 5 indicators of democracy (electoral democracy, liberal democracy, participatory democracy, consultative democracy, egalitarian democracy) V-DEM database was used. The research results show the effect of democracy on economic complexity can be heterogeneous compared to the initial level of economic complexity, so that democracy is associated with greater economic complexity in countries with higher economic complexity. The positive effect of democracy on economic complexity was confirmed in all models. Based on the results of the research, the coefficient of the types of democracy in developed countries is higher than the value of this coefficient in developing countries. In addition, economic growth, government size and population had a positive effect on economic complexity. To check the robustness of the model estimation we have estimated the model again using the Generalized Method of Moments (GMM) and Feasible Generalized Least Squares (FGLS). The two variables of political rights and civil rights were used instead of democracy and estimated with the Generalized Method of Moments (GMM) for all countries, as well as developing countries and developed countries. The coefficients and results have shown the stability of the estimated coefficients in all research models

The main goal of this study is to investigate the effects of political risks, uncertainty, and economic complexity on the ecological footprint in a selection of developing countries. We estimate our model using the Systemic Generalized Moments method (SYS-GMM) for a panel of 22 oil-exporting developing countries. The method allows us to resolve the possible endogeneity problem. Other control variables include economic growth, human capital, and trade openness. The estimation results show that reducing political risks increases the quality of the environment. Moreover, an increase in the world uncertainty index improves the quality of the environment because it reduces investment and output growth in oil-exporting developing countries and, hence, decreases the use of natural resources. In addition, we also find that economic complexity increases the ecological footprint. In other words, higher complexity might result in lower environmental quality in oil-exporting economies. Furthermore, higher per capita GDP growth rate, human capital, and trade openness increase the ecological footprint. It means these variables are likely to increase environmental degradation in oil-exporting countries. Our results might have important policy implications for policymakers. Our research emphasizes the significance of mitigating political risks to enhance environmental quality.

This study investigates the effect of weighting predictors on the performance of habitat suitability index (HSI) models using arithmetic mean (AMM) and geometric mean (GMM) methods. The case study focused on the catch data of Caspian Kutum (Rutilus frisii), with habitat parameters including day-time sea surface temperature, near-surface chlorophyll-a concentration, particulate organic carbon concentration, distance from fishing points to the river mouth, and bottom slope. Relative weights of environmental variables and suitability index (SI) fitting were determined using the support vector machine (SVM) technique. Sea surface temperature and particulate organic carbon concentration were identified as the most influential variables, with weights of 0.315 and 0.231, respectively, in explaining fish catch variance. Model performance evaluation revealed that the HSIWGMM model outperformed others, showing the lowest RMSE (training: 0.1818, testing: 0.2540) and the highest correlation coefficient (training: 0.4693, testing: 0.1953). In contrast, the HSIWAMM model showed the weakest performance (training: RMSE = 0.4023, r = 0.3843; testing: RMSE = 0.3858, r = 0.1360).

Block trading is used by investors in the capital market because it provides company-specific information, which is a tool for optimal stock pricing. Additionally, the media can bring the interests of managers and shareholders closer together by publishing company-specific news, thereby reducing information asymmetry, increasing stock price awareness, and decreasing stock price coincidence. Therefore, the purpose of this study is to investigate the moderating role of media coverage in the effect of block trading on stock price synchronicity. The statistical population of this research consists of companies listed on the Tehran Stock Exchange from 1393 to 1401, which were selected through systematic deletion of data from 100 companies, including 11,237 block transactions for review, experience, and analysis. The results of the Multivariate regression model based on composite data showed that the number and block trading ratio have a positive effect on stock price synchrony. Moreover, media coverage as a moderator variable in the effect of block trading ratio has a negative effect on stock price synchrony. These findings emphasize the inefficiency and lack of transparency of information in the Iranian stock market, which prevents the timely incorporation of company-specific information into stock prices.

With the increasing emphasis on the welfare and supportive responsibilities of governments for low-income groups, the role of government social expenditures in achieving macroeconomic and developmental goals has gained significance. This study examines the impact of government social expenditures in education and healthcare on poverty, per capita income, and income inequality. To this end, a system of simultaneous equations is estimated using data from 1357 to 1399 and the Generalized Method of Moments (GMM). The results of the growth-poverty-inequality triangle estimates indicate that economic growth in Iran, given the level of income inequality, has been poverty-inducing. Additionally, expenditures on education have led to poverty reduction, whereas insufficient healthcare expenditures have not had the same effect. Therefore, the proper allocation of government expenditures can adjust the relationships within this triangle toward pro-poor growth and poverty eradication.

Nowadays, knowledge trade can increase the productivity of production factors and facilitate the advancement of technical knowledge and reduce the consumption of natural resources and environmental pollution and stimulate green and sustainable development. Therefore, the current research was considered with the aim of investigating the effect of knowledge trade and environment-biased technical progress on sustainable (green) development. In order to investigate the effect of knowledge trade caused by direct technology imports, foreign direct investment technology spillovers and reverse engineering of imported products and environment-biased technical progress on sustainable development, the GMM estimator has been used in the time period of 2012- 2022 and 15 industries. The results showed: Import trade is a method of absorbing technical spillovers. Domestic companies can acquire general or partial knowledge by importing advanced products. However, the ability to learn advanced knowledge from advanced products is limited by human capital. The higher and more efficient human capital is, the easier it is to take advantage of the knowledge spillover. Environmental knowledge can only be improved through the direct import of knowledge. Neither foreign direct investment nor imports can improve the level of environmental knowledge. Technical spillover and reverse engineering require efficient and knowledgeable human capital. At a certain level of environmental technology, knowledge trade, regardless of its form, has a positive effect on sustainable and green development. Therefore, although the effects of knowledge trade on green development may be limited, if a country improves its independent innovation ability, technology absorption capacity, technical level and managerial experience, the country's economy can grow stably and sustainably in the long term.

The Human Development Index (HDI), as a measure of the level of economic and social development, has an impact on the level of environmental degradation and pressure. So far, few researchers have focused on the relationship between human development and environmental quality through the lens of the traditional Environmental Kuznets Curve. In this context, the aim of this research is to assess the impact of the Human Development Index, together with other explanatory variables such as trade, energy consumption and urbanisation, on the Ecological Footprint Index in oil and non-oil countries in the Middle East. This study uses the combined data available in the databases of the World Bank, the United Nations Development Programme, and Global Footprint Network for 8 oil countries (Bahrain, Iran, Iraq, Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates) and 5 non-oil countries (Egypt, Jordan, Lebanon, Malta, Morocco, and the United Arab Emirates) in the Middle East region for the period 2000 to 2019. The two-stage difference GMM estimation method was also used to estimate the regression. In this method, after specifying the initial model, it is differentiated from the regression to remove the effects of cross from the model. Then, in the second step, the remaining residuals from the first step are used to balance the variance-covariance matrix.The results showed that there is an inverted U-shaped relationship between human development and ecological footprint for non-oil countries. Thus, improving the human development index in the early stages of development by increasing the ecological footprint index damages the environment of non-oil countries. In spite of that with the improvement of the development level of the countries, this trend is reversed. However, a further increase in human development leads to continuous improvement of environmental quality in oil countries. Moreover, the results showed that the positive effect of energy consumption on the ecological footprint index is numerically more significant in oil countries than in non-oil countries. This is despite the fact that the effect coefficient of the trade volume variable on the ecological footprint index for oil and non-oil countries has been met, respectively, negatively and positively. The effect of the urbanization variable on the ecological footprint index for both groups of oil and non-oil countries is as expected and positive. Therefore, policymakers should be aware of the existing causality between human development and the ecological footprint index and focus on accelerating human development to reverse the current process of environmental degradation.

Foreign Direct Investment (FDI) is a key factor in accelerating the growth and development of the digital economy across various countries. By facilitating technology transfer, improving digital infrastructure, and enhancing local workforce skills, FDI contributes to the formation of advanced digital ecosystems. In today’s competitive environment, where countries are striving to attract FDI, they are implementing policies and incentives to draw foreign investors into critical sectors of the digital economy, such as information and communication technology. This study aims to evaluate the spatial impact of FDI, financial deepening, trade openness, government size, and economic growth on digital economy development in MENA countries from 2000 to 2023. To conduct statistical tests, we employ the dynamic spatial panel model using the Generalized Method of Moments (GMM) with the two-step Arellano-Bover/Blundell-Bond estimator. The results indicate that the first lag of the dependent variable has a positive effect (0.83) on digital economy development, meaning that the digital economy’s growth in the current period is dependent on its development in the previous year. The first spatial lag is also positive and significant (0.005), demonstrating a positive spatial dependence among MENA countries. This suggests that an increase in digital economy development in one country positively affects neighboring countries, leading to spillover effects. Furthermore, according to technology transfer theory, FDI can introduce advanced technologies to the host country, which contributes to digital economy development in the region with a coefficient of 0.07. Additionally, financial deepening, economic growth, government size, and trade openness all have a positive and direct impact on digital economy development, with economic growth having the smallest estimated coefficient and trade openness having the largest.