Abstract: We evaluate how anticipation and adaptation shape the aggregate and local costs of climate change. We develop a dynamic spatial model of the U.S. economy and its 3,143 counties that features costly forward-looking migration and capital investment decisions. Recent methodological advances that leverage the ‘Master Equation’ representation of the economy make the model tractable. We estimate the county-level impact of severe storms and heat waves over the 20th century on local income, population, and investment. The estimated impact of storms matches that of capital depreciation shocks in the model, while heat waves resemble combined amenity and productivity shocks. We then estimate migration and investment elasticities, as well as the structural damage functions, by matching these reduced-form results in our framework. Our findings show, first, that the impact of climate on capital depreciation magnifies the U.S. aggregate welfare costs of climate change twofold to nearly 5% in 2023 under a business-as-usual warming scenario. Second, anticipation of future climate damages amplifies climate-induced worker and investment mobility, as workers and capitalists foresee the slow build-up of climate change. Third, migration reduces substantially the spatial variance in the welfare impact of climate change. Although both anticipation and migration are important for local impacts, their effect on aggregate U.S. losses from climate change is small.
Abstract: A unilateral carbon tax trades off the distortionary costs of taxation and the future gains from slowing down global warming. Because the cost is local and immediate, whereas the benefit is global and delayed, this tradeoff tends to be unfavorable to unilateral carbon taxes. We show that this logic breaks down in a world with trade and migration where economic geography is shaped by agglomeration economies and congestion forces. Using a multisector dynamic spatial integrated assessment model (S-IAM), this paper predicts that a carbon tax introduced by the European Union (EU) and rebated locally can, if not too large, increase the size of Europe’s economy by concentrating economic activity in its high-productivity non-agricultural core and by incentivizing immigration to the EU. The resulting change in the spatial distribution of economic activity improves global efficiency and welfare. A unilateral carbon tax with local rebating introduced by the US generates similar global welfare gains. Other forms of rebating can dilute or revert this positive effect.
Abstract: We study local carbon policy to address the consequences of climate change. Standard analysis suggests that the social cost of carbon determines optimal carbon policy. We start by using the spatial integrated assessment model in Cruz and Rossi-Hansberg (2021) to measure the local social monetary cost of CO2 emissions: the Local Social Cost of Carbon (LSCC). Although the largest welfare costs from global warming are concentrated in the warmest parts of the developing world, adjusting for the local marginal utility of income implies that the LSCC peaks in warm and high-income regions like the southern parts of the U.S. and Europe, as well as Australia. We then proceed to study the effect of the actual carbon reduction pledges in the Paris Agreement and the progress they can make in implementing the expressed goal of keeping global temperature increases below 2°C. We find that although the distribution of pledges is roughly in line with the LSCC, their magnitude is largely insufficient to achieve its goals. The required carbon taxes necessary to keep temperatures below 2°C over the current century are an order of magnitude higher and involve large implicit inter-temporal transfers. Increasing the elasticity of substitution across energy sources is important to reduce the carbon taxes necessary to achieve warming goals.
Abstract: Global warming is a worldwide and protracted phenomenon with heterogeneous local economic effects. We propose a dynamic economic assessment model of the world economy with high spatial resolution to assess its consequences. Our model features several forms of adaptation to local temperature changes, including costly trade and migration, local technological innovations, and local natality rates. We quantify the model at a 1° × 1° resolution and estimate damage functions that determine the impact of temperature changes on a region’s fundamental productivity and amenities conditional on local temperatures. Welfare losses from global warming are very heterogeneous across locations, with 20% losses in parts of Africa and Latin America but also gains in some northern latitudes. Overall, spatial inequality increases. Uncertainty about average welfare effects is significant, but much smaller for relative losses across space. Migration and innovation are shown to be important adaptation mechanisms. We use the model to study the impact of carbon taxes, abatement technologies, and clean energy subsidies. Carbon taxes delay consumption of fossil fuels and help flatten the temperature curve but are much more effective when an abatement technology is forthcoming.
Abstract: This paper quantitatively assesses the world's changing economic geography and sectoral specialization due to global warming. It proposes a two-sector dynamic spatial growth model that incorporates the relation between economic activity, carbon emissions, and temperature. The model is taken to the data at the 1° by 1° resolution for the entire world. Over a 200-year horizon, rising temperatures consistent with emissions under Representative Concentration Pathway 8.5 push people and economic activity northwards to Siberia, Canada, and Scandinavia. Compared to a world without climate change, clusters of agricultural specialization shift from Central Africa, Brazil, and India's Ganges Valley, to Central Asia, parts of China and northern Canada. Equatorial latitudes that lose agriculture specialize more in non-agriculture but, due to their persistently low productivity, lose population. By the year 2200, predicted losses in real GDP and utility are 6% and 15%, respectively. Higher trade costs make adaptation through changes in sectoral specialization more costly, leading to less geographic concentration in agriculture and larger climate-induced migration.
Abstract: Sea-level rise and ensuing permanent coastal inundation will cause spatial shifts in population and economic activity over the next 200 years. Using a highly spatially disaggregated, dynamic model of the world economy that accounts for the dynamics of migration, trade, and innovation, this paper estimates the consequences of probabilistic projections of local sea-level changes under different emissions scenarios. Under an intermediate greenhouse gas concentration trajectory, permanent flooding is projected to reduce global real GDP by an average of 0.19% in present value terms, with welfare declining by 0.24% as people move to places with less attractive amenities. By the year 2200 a projected 1.46% of world population will be displaced. Losses in many coastal localities are more than an order of magnitude larger, with some low-lying urban areas particularly hard hit. When ignoring the dynamic economic adaptation of investment and migration to flooding, the loss in real GDP in 2200 increases from 0.11% to 4.5%. This shows the importance of including dynamic adaptation in future loss models.
Abstract: We propose a dynamic spatial theory to analyze the geographic impact of climate change. Agricultural and manufacturing firms locate on a hemisphere. Trade is costly, firms innovate, and technology diffuses over space. Emissions from energy used in production contribute to the atmospheric stock of carbon, which increases temperature. Warming differs across latitudes and its effect on productivity varies across sectors. We calibrate the model to analyze how climate change affects the spatial distribution of economic activity, trade, migration, growth, and welfare. We assess quantitatively the impact of migration and trade restrictions, energy taxes, and innovation subsidies.
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