We focus on three environmental impacts particularly influenced by population agestructure-carbon emissions from transport and residential energy and electricity consumption-as well as aggregate carbon emissions for a panel of developed countries, and take as our starting point the STIRPAT framework. Among our contributions is to further disaggregate population into three particularly key age groups: 20-34, 35-49, and 50-64, and by doing so demonstrate that population's environmental impact differs considerably across age-groups, with the older age-groups (ones typically associated with larger households) actually exerting a negative influence. Furthermore, those age-specific population influences are different (in absolute and relative terms) for the different environmental impacts we analyze. Also, we find that urbanization, in developed countries, best measures access to a country's power grid, and thus, is positively associated with energy consumption in the residential sector. Lastly, we suggest some modelling and methodological improvements to the STIRPAT framework.

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This review summarizes the evidence from cross-country, macro-level studies on the way demographic factors and processes-specifically, population, age structure, household size, urbanization, and population density-influence carbon emissions and energy consumption. Analyses employing time-variant data have produced great variance in population elasticity estimations-sometimes significantly greater than one, sometimes significantly less than one; whereas, cross-sectional analyses typically have estimated population elasticities near one. Studies that have considered age structure typically have used standard World Bank definitions, and mostly have found those variables to be insignificant. However, when researchers have considered levels of disaggregation that approximate life-cycle behavior like family size, they have uncovered relationships that are complex and nonlinear. Average household size has a negative relationship with road energy use and aggregate carbon emissions. Urbanization appears positively associated with energy consumption and carbon emissions. Higher population density is associated with lower levels of energy consumption and emissions.

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Knowledge of the carbon emissions elasticities of income and population is important both for climate change policy/negotiations and for generating projections of carbon emissions. However, previous estimations of these elasticities using the well-known STIRPAT framework have produced such wide-ranging estimates that they add little insight. This paper presents estimates of the STIRPAT model that address that shortcoming, as well as the issues of cross-sectional dependence, heterogeneity, and the nonlinear transformation of a potentially integrated variable, i.e., income. Among the findings are that the carbon emissions elasticity of income is highly robust; and that the income elasticity for OECD countries is less than one, and likely less than the non-OECD country income elasticity, which is not significantly different from one. By contrast, the carbon emissions elasticity of population is not robust; however, that elasticity is likely not statistically significantly different from one for either OECD or non-OECD countries. Lastly, the heterogeneous estimators were exploited to reject a Carbon Kuznets Curve: while the country-specific income elasticities declined over observed average income-levels, the trend line had a slight U-shape.Keywords: Carbon Kuznets Curves; Kaya identity; population and environment; nonstationary panels; cross sectional dependence; nonlinearities in environment and development. AcknowledgementsThe Pesaran (2004)