نوشین کریمی علویجه

Over the past decades, emissions of pollution and environmental protection have become one of the major concerns of developing countries, because these communities need to use energy to achieve high economic growth and more energy consumption brings more environmental pollution. Investigating influencing factors on the emission of pollutants, and in particular carbon dioxide gas, can be effective in planning for the control and management of pollutants. The purpose of this study is to investigate the effect of population size, GDP, energy intensity and urbanization on carbon dioxide emissions in selected countries of the Mena region during the years 2000-2017.

Factors affecting the emission of CO2 in selected countries of the MENA region have been investigated using Panel Quantile Regression model. Important feature of this model is the estimation of independent variables in different quantiles and their effect on the dependent variable, which greatly increases the accuracy of the estimate and the result of the estimate in each quantile can be seen separately.

Research findings show that population size except for quantiles of 0.05 and 0.1 has a positive and significant effect on carbon dioxide emissions. The energy intensity and GDP at all quantiles have a positive and significant effect on CO2 emissions. The relationship between urbanization and carbon dioxide is negative at all quantiles except 0.95 and only in 0.05, 0.1, 0.7 and 0.8 quantiles is significant.

In this study, given that GDP has the greatest impact on carbon dioxide emissions, it is recommended that by upgrading production technologies, preparation renewable energy infrastructure and issuing permits to enter less polluting industries into the countries studied, create the conditions that economic growth due to the increase in GDP to be accompanied by the lowest emissions of pollutants.

Good governance is an index designed by the World Bank to classify governments in terms of their attention to people and their social and economic status. One of the most important factors in implementing good governance in many countries has been environmental decision making, in today's world, the environment is one of the most important issues facing people. Various factors affecting the environment include economic variables (industrialization, trade and technological inequality), political variables (democracy and despotism), social variables (urbanization and literacy rate) and government (size and quality of government). In this study, the effect of good governance on CO2 emissions in G8 countries is investigated.

Theoretical framework:

Governance has a broad meaning that is directly related to domains such as the economic environment or, in other words, economic security, politics, society and rights. The World Bank has introduced governance indicators to reflect the institutional quality of countries. These indicators include voice and accountability, political stability, control of corruption, regulatory burden, government effectiveness and rule of law. Various aspects of governance, both direct and indirect, affect carbon dioxide emissions.

Quantile regressions id based on a symmetric and asymmetric loss function and calculated similarly to the estimation of parameters in the Ordinary Least Squares (OLS) regression. The general definition of quantile regression is that if the linear regression model is assumed to be the followingEquation (2), the condition quantile function τ distribution of y shows to the condition of random variables x, where the following condition holds.) =To estimate the coefficients of the model, minimize the value of the absolute value of the errors is used with proper weighing: Equation (3) obtains answers by linear programming. In this study, a panel quantile regression method with fixed effects is used. Consider the following fixed-effect panel quantile regression model: Where is the conditional 100 quantile of   ,  is the fixed-effects parameters correlated with  , which exhibits the unobservable effects of each specific country and  is the slope coefficient at the 100 quantile. The unique feature of this method is that a penalty term in minimizing to address the computing problem introduces a sum of parameters; Estimates of the parameters are as follows:min(α,β) (5)In relation (5), i indicates the number of countries (N), T time period, K, the level of quantiles, x the matrix of explanatory variables and  the quantile loss function. In addition, shows the relative weight for kth quantile. In this paper, = 1/K is considered. λ is the adjustment parameter that reduces the individual effects of to zero to improve the performance of β.
 

The model presented in this study is as follows:The description of variables is as follows: The estimation results in Table (2) show that energy consumption at all quantile levels from 5% to 95% has a positive and significant effect. As shown in Figure (1), the effect of energy consumption on CO2 emissions in all countries has a constant trend. GDP has a negative effect on CO2 emissions at all quantile levels, the results of the OLS estimates also confirm the negative relationship between GDP and carbon dioxide emissions. The results of different quantile levels show a strong and positive effect on the relationship between governance and CO2 expansion.Trade openness in the quantile of 5% to 20% has a positive and significant effect on carbon dioxide emissions, but for the quantile levels above 70%, the increase in trade has a negative impact on CO2 emissions. The relationship between urbanization and carbon dioxide emissions is positive and significant at all quantile levels. The relationship between industrialization and carbon dioxide expansion is also positive and significant at all quantile levels.Chart (1)-Estimation results of panel quantile regression

Conclusions & Suggestions:

This study investigates the effect of governance on carbon dioxide emissions in the G8 countries over the period 1996 to 2016 using the panel quantile regression method. The results show that the effect of the good governance index, which shows the quality of a country's public institutions and the ability of the government to perform its duties, has a negative and significant effect on the amount of carbon dioxide emissions that represent environmental status in all quantiles. However, this effect is stronger in the lower quantiles and reduces the movement to the higher quantiles.

One of the main issues in macroeconomics is the study of the relationship between interest rates and exchange rates, the effects of these two variables have been considered by politicians and policy makers. Therefore, in this study due to the two-rate exchange rate in the Iranian economy, the two official exchange rate and the unofficial exchange rate is used. Also in this research of interest rates, one-year deposit interest rate short term and long term is five years, which will be announced by the Central Bank of the Islamic Republic of Iran. In this paper, the exchange rate during the period 1974-2014 was estimated with particle swarm optimization algorithm and genetic algorithm. And according to performance criteria, models with particle swarm optimization algorithm was selected to investigate the relationship between interest rates and exchange rates. The results show that the interest rate on short-term and long-term with official and unofficial exchange rates have indirect relationship. In fact, interest rates will increase the value of the national currency. Also in this study, the rate of money growth and gross domestic product on official and unofficial exchange rate is positive. In other words, by increasing the growth rate of money and gross domestic product, the value of the national currency decreases.