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Using panel data from 21 Organization for Economic Cooperation and Development (OECD) countries collected between 2000 and 2016, this study analyzes the effect of age structure on greenhouse gas (GHG) emissions from road transportation. Previous studies have failed to reflect the driver&rsquo, s behavior patterns, especially by age group. We apply the Fully-Modified Ordinary Least Squares (FMOLS) method, including the age structure effect by reorganizing 17 age groups into a polynomial structure. The age structure exhibits an asymmetric inverted U-shaped effect on GHG emissions. Initially, people emit more GHGs as they age, and reach peak emissions in their late 20s, after which emissions fall until around the age of 70, when GHG emissions remain constant because of minimum mobility demand. Factors, such as higher income, increased vehicle ownership, and raised transport volumes increase emission rates. On the other hand, fuel transition and increased fuel price, population density, urbanization rate, and fuel economy reduce GHG emissions. Furthermore, we perform a projection of GHG emissions until 2050, and conclude that the effect of age structure is limited because of the minimum mobility demand of the elderly. We conclude that various policy measures, such as increased fuel economy and urbanization, must be considered in order to achieve sustainable transport

The purpose of this article is to empirically find the Environmental Kuznets Curve (EKC) relationship between income and carbon dioxide (CO2) emissions and to analyze the influence of population aging on such emissions. We utilize Korean regional panel data of 16 provinces during the period from 1998 to 2016. To account for the nonstationary time series in the panel, we employ a fully modified ordinary least squares (FMOLS) and estimate long-run elasticity. From the empirical results, we can find the nonlinear relationship between income and CO2 emissions. Additionally, we verify the fact that population aging reduces CO2 emissions. A 1% increase in the proportion of the elderly results in a 0.4% decrease in CO2 emissions. On the other hand, the younger population increases CO2 emissions. These results were in line with those of additional analysis on residential and transportation CO2 emissions, for the robustness check.

Mounting evidence shows that economic and climate variables such as income, energy price, and temperature impact energy demand. We examined another variable, population age distribution, which has rarely been considered, that could affect energy demand. We employ population polynomials to account for the impact of population age distribution on residential electricity consumption in Korea. Using panel data from 1990 to 2016, we verify that populations aged 20~44, and those over 60, raise residential electricity consumption. We additionally evaluate the impact of population age distribution in forecasting future electricity consumption and conclude that age distribution effects dominate total population growth effects.