Climate Change Economics

We propose a framework that, building on the pledges made by governments after the Copenhagen Accord of 2009, could be used to assign allocations of emissions of greenhouse gases (GHGs), across all countries, one budget period at a time, as envisioned at the 2011 negotiations in Durban. Under this two-part plan: (i) China, India, and other developing countries accept targets at Business as Usual (BAU) in the coming budget period, the same period in which the U.S. first agrees to cuts below BAU; and (ii) all countries are asked in the future to make further cuts in accordance with a common numerical formula that each country is likely to view as fair. We use a state of the art integrated assessment model to project economic and environmental effects of the computed emission targets.

The benefits of carbon mitigation are subject to numerous sources of uncertainty and accounting for this uncertainty in policy analysis is crucial. One often overlooked source uncertainty are the forecasts of future baseline conditions (e.g., population, economic output, emissions) from which carbon mitigation benefits are assessed. Through, in some cases highly non-linear relationships, these baseline conditions determine the forecast level and rate of climate change, exposed populations, vulnerability, and way in which inter-temporal tradeoffs are valued. We study the impact of explicitly considering this uncertainty on a widely used metric to asses the benefits of carbon dioxide mitigation, the social cost of carbon (SCC). To explore this question, a detailed integrated assessment that couples economic and climate systems to assess the damages of climate change is driven by a library of consistent probabilistic socioeconomic-emission scenarios developed using a comprehensive global computable general equilibrium (CGE) model. We find that scenario uncertainty has a significant effect on estimates of the SCC and that excluding this source of uncertainty could lead to an underestimate of the mitigation benefits. A detailed decomposition finds that this effect is driven primarily through the role that uncertainty regarding future consumption per capita growth has on the value of inter-temporal tradeoffs through the consumption discount rate.

What's the role of unilateral measures in global climate change mitigation in a post-Durban, post 2012 global policy regime? We argue that under conditions of preference heterogeneity, unilateral emissions mitigation at a subnational level may exist even when a nation is unwilling to commit to emission cuts. We establish that under certain assumptions, in a global strongly connected network of countries, learning the costs of switching to a low emissions activity can result in a universal adoption of such activities. We analyze the features of a policy proposal that could accelerate convergence to a low carbon world in the presence of global learning.

Climate in a given location influences people's housing decisions, and changes in climate may affect these decisions in ways that alter our understanding of desirable locations. This study examines the potential sensitivity of future housing prices in the United States to changes in temperature, precipitation, and humidity by developing a hedonic regression model of the relationship between climate variables and housing prices and exploring implications of different climate futures for the amenity value of climate in these prices. The model shows a significant relationship between housing prices in urban areas and certain climate variables. The study then examines the sensitivity of the amenity value of climate to future climate scenarios. Results suggest that, nationally, climate change represents a disamenity, particularly in central-to-southeastern states. However, detailed housing prices vary spatially and among scenarios. Seasonal variation in temperature, including the relative magnitudes of the change in January and July temperatures, is a key determinant of housing price change, contributing to variation across both climate scenarios and geographic location.