Browsing by Author "Prest, BC"
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Item Open Access A discounting rule for the social cost of carbon(Journal of the Association of Environmental and Resource Economists, 2022-09-01) Newell, RG; Pizer, WA; Prest, BCWe develop a discounting rule for estimating the social cost of carbon (SCC) given uncertain economic growth. Diminishing marginal utility of income implies a relationship between the discount rate term structure and economic growth uncertainty. In the classic Ramsey framework, this relationship is governed by parameters reflecting pure time preference and the elasticity of the marginal utility of consumption, yet disagreement remains about the values of these parameters. We calibrate these parameters to match empirical evidence on both the future interest rate term structure and economic growth uncertainty, while also maintaining consistency with discount rates used for shorter-term benefit-cost analysis. Such an integrated approach is crucial amid growth uncertainty, where growth is also a key determinant of climate damages. This results in an empirically driven, stochastic discounting rule to be used in estimating the SCC that also accounts for the correlation between climate damage estimates and discount rates.Item Open Access Prices Versus Quantities with Policy Updating(2016-06) Pizer, WA; Prest, BCItem Open Access The GDP-Temperature relationship: Implications for climate change damages(Journal of Environmental Economics and Management, 2021-07-01) Newell, RG; Prest, BC; Sexton, SEEconometric models of temperature impacts on GDP are increasingly used to inform global warming damage assessments. But theory does not prescribe estimable forms of this relationship. By estimating 800 plausible specifications of the temperature-GDP relationship, we demonstrate that a wide variety of models are statistically indistinguishable in their out-of-sample performance, including models that exclude any temperature effect. This full set of models, however, implies a wide range of climate change impacts by 2100, yielding considerable model uncertainty. The uncertainty is greatest for models that specify effects of temperature on GDP growth that accumulate over time; the 95% confidence interval that accounts for both sampling and model uncertainty across the best-performing models ranges from 84% GDP losses to 359% gains. Models of GDP levels effects yield a much narrower distribution of GDP impacts centered around 1–3% losses, consistent with damage functions of major integrated assessment models. Further, models that incorporate lagged temperature effects are indicative of impacts on GDP levels rather than GDP growth. We identify statistically significant marginal effects of temperature on poor country GDP and agricultural production, but not rich country GDP, non-agricultural production, or GDP growth.Item Open Access The Social Cost of Carbon: Advances in Long-Term Probabilistic Projections of Population, GDP, Emissions, and Discount Rates(Brookings Papers on Economic Activity, 2021-09-01) Rennert, K; Prest, BC; Pizer, WA; Newell, RG; Anthoff, D; Kingdon, C; Rennels, L; Cooke, R; Raftery, AE; Ševčíková, H; Errickson, FThe social cost of carbon (SCC) is a crucial metric for inform-ing climate policy, most notably for guiding climate regulations issued by the US government. Characterization of uncertainty and transparency of assump-tions are critical for supporting such an influential metric. Challenges inherent to SCC estimation push the boundaries of typical analytical techniques and require augmented approaches to assess uncertainty, raising important considerations for discounting. This paper addresses the challenges of projecting very long-term economic growth, population, and greenhouse gas emissions, as well as cali-bration of discounting parameters for consistency with those projections. Our work improves on alternative approaches, such as nonprobabilistic scenarios and constant discounting, that have been used by the government but do not fully characterize the uncertainty distribution of fully probabilistic model input data or corresponding SCC estimate outputs. Incorporating the full range of economic uncertainty in the social cost of carbon underscores the importance of adopting a stochastic discounting approach to account for uncertainty in an integrated manner.