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Based on the literature on pollution tax on capital and labor, we have analyzed the impact of an optimal fiscal policy (tax) on the Iran economy based on the Ramsey solution. To achieve this, we created a dynamic economic-climatic model for the Iranian economy by adding externalities to a simple general equilibrium model without a foreign sector. Thus first we developed a dynamic model in two cases with and without side effects. Findings indicate that in the conditions of no pollution of the production sector, the model reaches equilibrium with zero capital tax. When we take into account the pollution in the model, in order to have a unique optimal point and keep the economy on the saddle path and it converged towards an optimal point, so capital-based pollution tax became essential. In our model, endogenous labor plays an important role as it indicates an increase in household environmental awareness, the supply of working hours, consumption, production, and environmental quality. In the models with exogenous labor, low household awareness of environmental quality leads to more severe degradation of environmental quality. According to our results considering the Ramsey solution on the economy, in a situation where: labor is endogenous, capital-based pollution tax is implemented, with a dynamic general economic-climatic equilibrium model, two environmental parameters are vital to be taken care of, “the weight of environmental quality” and “the polluting technology”. In an environment where we use increasingly polluting technology, in the absence of an increasing pollution tax regime, the quality of the environment and society’s welfare will diminish subsequently [ABSTRACT FROM AUTHOR]

Most scholars support the increase in carbon dioxide (CO2) emissions as one of the major causes of the increase in global climate change. Therefore, reducing CO2 emissions from the main emitter countries, including Iran as the sixth emitter, is important to deal with the harmful effects of global climate change. Accordingly, the main aim of this paper was to analyze the social, economic, and technical factors affecting CO2 emissions in Iran. Previous studies on diverse variables affecting emissions are not very accurate and reliable as they do not consider indirect effects. This study applied a structural equation model (SEM) to estimate the direct and indirect impacts of factors on the emissions by panel data for 28 provinces of Iran from 2003 to 2019. According to geographical location, three distinct regions, the north, center, and south of Iran were considered. The findings suggest that a 1% increase in social factor directly increased CO2 emissions by 2.23% (in the north) and 1.58% (in the center), but indirectly reduced emissions by 0.41% (in the north) and 0.92% (in the center). Hence, the total effects of the social factor on CO2 emissions were estimated at 1.82%, and 0.66% in the northern, and central regions, respectively. In addition, the total effects of the economic factor on CO2 emissions were estimated at 1.52%, and 0.73% in those regions. The results of this study showed that the direct effects of a technical factor on CO2 emissions were negative in the north and center. However, they were positive in the south of Iran. Based on the empirical results of this study, three policy implications are discussed in order to control CO2 emissions in regional distinctions of Iran as follows: First, policymakers should pay attention to the social factor, i.e., the growth of human capital in the southern region with the aim of increasing sustainable development. Second, Iranian policymakers must prevent unilaterally increasing gross domestic product (GDP) and financial development in the north and center. Third, policymakers should pay attention to the technical factor, i.e., improving energy efficiency, as well as upgrading information and communications technology (ICT) in the northern and central regions, and limiting the technical factor in the southern region. [ABSTRACT FROM AUTHOR]

It is essential to study CO2 emissions intensity as the most critical factor affecting temperature increase and climate change in a country like Iran, which ranked seven regarding CO2 emissions intensity. Investigating the convergence of CO2 emissions intensity is essential in recognizing its dynamics in identifying the effectiveness of government environmental policies. In this paper, using the Markov chain and spatial Markov chain methods, the convergence of CO2 emissions intensity from fossil-fuel consumption has been investigated in 28 provinces of Iran from 2002 to 2016. The empirical results showed that convergence clubs and neighbors significantly influenced the transition probability of regions to clubs with high and low CO2 emissions. Therefore, if a province had a neighbor with low (high) CO2 emissions intensity, the transition probability of this province to the club with low (high) CO2 intensity increased. Therefore, in provinces that have neighbors with low (high) CO2 emissions intensity, the transition probability to the club with low (high) CO2 intensity increases. [ABSTRACT FROM AUTHOR]

However, urbanization can have positive effects on the labor force and economic growth in urban areas the unplanned and rapid pace of urbanization process can ultimately lead to unpleasant consequences including marginalization, unemployment, poverty, the emergence of slums and shanty towns and the prevalence of crime in urban areas. Therefore, the objective of this study was to investigate the spatial spillover effects of urbanization on crime in 30 Iranian provinces during the period from 2006 to 2015 using dynamic spatial panel data models. The results of the study revealed that urbanization had a positive and statistically significant impacts on crime per capita in Iranian provinces indicating an increase in urbanization enhances the crime level. In addition, unemployment rate, and human capital had significant and negative effects on crime in Iranian provinces, respectively. Finally, the crime per capita in a previous period exerted a significant positive effect on the current crime which stablished the dynamic nature of this phenomenon. Moreover, the results of the study demonstrated that increasing crime per capita in neighboring provinces could elevate the crime in a given province. [ABSTRACT FROM AUTHOR]

The three basic concepts which are fundamental to the framework of this study are the 3Ds -Density, Distance and Division. These Variables was introduced by World Development Report 2009.Population Density refers to the Population mass per unit of land area, or the geographic compactness of population. Distance refers to the ease or difficulty for goods, services, labor, capital, information, and ideas to traverse space. Distance, in this sense, is an economic concept, not just a physical one. Division is the most important dimension internationally. Religion, ethnicity, and language are among the main attributes that lead to divisions between places. Thus, the main aim of this paper is analysis of the effect of population density, economic distance and division on regional economic growth. For this aim, this study was proposed a simple theoretical framework to study the impact of population density, economic distance and division on regional economic growth. The framework has presented in a unified way the main insights of NEG models with endogenous growth and free capital mobility. [ABSTRACT FROM AUTHOR]