Demographics and carbon emissions: implications for macroeconomic policy

What are the causal effects of demographic change on carbon emissions? How should climate policy be adjusted in response to shifts in the age structure of the population? The world population is aging, and global carbon emissions are increasing. But not all the demographic transitions are alike. There is significant heterogeneity across countries and over time, and we aim to exploit such a temporal and geographic variation in demographics to estimate causal effects. Why is this important? It is crucial because demography and its macroeconomic impacts have mostly been neglected in the economics of climate change. This project investigates the implications of demographics and carbon emissions for macroeconomic policy. We establish empirically that (i) population aging -measured by the share of old people in total population- has a negative impact on carbon dioxide emissions both at the country and US state level over the period 1960-2018, and that (ii) the carbon content of household consumption over the life cycle is “hump-shaped”, peaking in middle age and then declining thereafter. These new facts suggest that demographics matter for climate policy and that population policies should be a crucial part of the approach to mitigate the adverse effects of global warming. We develop a large-scale overlapping generations model, moving away from the infinitely lived representative agent paradigm, and quantify the aggregate consequences of aging for carbon emissions and the social costs of carbon, i.e., the net present value of future damages from emitting one additional unit of carbon into the atmosphere today, bearing in mind general equilibrium effects and household heterogeneity. The project makes two contributions relative to the literature: (i) by quantifying the effects of population aging on carbon emissions using two different datasets, that is, a large and unbalanced yearly panel of cross-country data and a balanced yearly panel of US state-level data from 1960-2018, and (ii) by examining which channels can explain the negative and statistically significant effect on carbon emissions coming from demographic change. To do so, we document new cross-sectional patterns in consumption expenditures by considering the carbon content of the goods and services they consume using household-level microdata from the U.S. Consumer Expenditure Survey over the period 1998-2014, and information about emissions intensity at the sectoral level. We then develop a quantitative macro-climate model that accounts for these empirical facts. Our research relates to different strands of literature. Firstly, there are a bunch of empirical studies that examine the relationship between economic growth, population dynamics, and carbon emissions using cross-country data see Liddle (2014), for an extensive literature review. We add to this literature by using a larger country data set, regional variation within the U.S, and by describing a potential transmission channel by means of household-level expenditure information. Secondly, demographic change has been connected to various macro-economic variables, for example, higher aggregate household saving rates and lower capital returns (Bloom et al., 2007; Eggertsson et al., 2019; Curtis et al., 2015; Carvalho et al., 2016; Imrohoroglu and Zhao, 2017), international trade and capital flows (Krueger and Ludwig, 2007; Backus et al., 2014), fiscal multipliers (Basso and Rachedi, 2021), robots, and automation (Basso and Jimeno, 2021), and carbon prices (Gerlagh et al., 2017). We link empirically and theoretically demographics and carbon emissions, contributing to the literature that uses integrated assessment models with overlapping generations too, in the spirit of Kotlikoff et al., (2021). table.MsoNormalTable {mso-style-name:"Tabla normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin-top:0cm; mso-para-margin-right:0cm; mso-para-margin-bottom:8.0pt; mso-para-margin-left:0cm; line-height:107%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri",sans-serif; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi; mso-fareast-language:EN-US;}