Analysis of the Effects of Economic Growth and Renewable Energy Consumption on Carbon Emissions Using Multidimensional Panel Data Models

The aim of this study is to analyze the effects of economic growth and renewable energy consumption on CO2 emissions. For this purpose, an empirical study was carried out with a multidimensional panel data model including country-income level and time dimension for 176 countries using annual data for the period 1999-2020. The empirical model includes CO2 emission amount per capita as the dependent variable, and per capita income (KBG) and renewable energy consumption (YET) as the independent variables. First, in order to decide on the appropriate model, the statistical validity of each effect (country, income level and time) in the model was tested with the random effects model maximum likelihood (LR) estimation. After the LR test, fixed effects within-group transformations were applied for the appropriate model and the results obtained were compared with the LR test results. Based on the assumption that the coefficients obtained were far from each other, it was decided that the most appropriate model was the fixed effects within-group estimation results. According to the fixed effects within-group estimation results, there is a positive relationship between economic growth and CO2 emissions, and a negative relationship between renewable energy consumption and CO2 emissions. The findings show that a 1% increase in KBG increases the amount of CO2 by 0.526%, whereas a 1% increase in YET reduces the amount of CO2 emissions by 0.0313%.