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This paper presents a framework to include feedbacks from climate impacts on the economy in integrated assessment models. The proposed framework uses a production function approach, which links climate impacts to key variables and parameters used in the specification of economic activity. The key endpoints within climate impact categories are linked to the relevant connections for a range of sectors in the economy. The paper pays particular attention to the challenges of distinguishing between damages and the costs of adapting to climate change. The paper also reviews existing studies and available data that can be used to establish linkages between climate impacts and key variables within economic models. There is considerable heterogeneity across the timing and geographic distribution of changes in climatic variables, the consequent changes in key physical and biogeochemical “endpoints” that might occur over time and space, and the magnitude of the resulting damages that these effects are likely to impose on the range of sectors in the economy. The review underlines the uncertainty involved in each of these dimensions and the research needs for the future.

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This paper presents a framework to include feedbacks from climate impacts on the economy in integrated assessment models. The proposed framework uses a production function approach, which links climate impacts to key variables and parameters used in the specification of economic activity. The key endpoints within climate impact categories are linked to the relevant connections for a range of sectors in the economy. The paper pays particular attention to the challenges of distinguishing between damages and the costs of adapting to climate change. The paper also reviews existing studies and available data that can be used to establish linkages between climate impacts and key variables within economic models. There is considerable heterogeneity across the timing and geographic distribution of changes in climatic variables, the consequent changes in key physical and biogeochemical “endpoints” that might occur over time and space, and the magnitude of the resulting damages that these effects are likely to impose on the range of sectors in the economy. The review underlines the uncertainty involved in each of these dimensions and the research needs for the future.

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Assessments of the economic benefits of transportation infrastructure investments are critical to good policy decisions. At present, most such assessments are based of two types of studies: micro-scale studies in the form of cost-benefit analysis (CBA) and macro-scale studies in the form of national or regional econometric analysis. While the former type takes a partial equilibrium perspective and may therefore miss broader economic benefits, the latter type is too widely focused to provide much guidance concerning specific infrastructure projects or programs. Intermediate (meso-scale) analytical frameworks, which are both specific with respect to the infrastructure improvement in question and comprehensive in terms of the range of economic impacts they represent, are needed. This paper contributes to the development of meso-scale analysis via the specification of a computable general equilibrium (CGE) model that can assess the broad economic impact of improvements in transportation infrastructure networks. The model builds on recent CGE formulations that seek to capture the productivity penalty on firms and the utility penalty on households imposed by congestion (Meyers and Proost, 1997; Conrad, 1997) and others that model congestion via the device of explicit household time budgets (Parry and Bento, 2001, 2002). The centerpiece of our approach is a representation of the process through which markets for non-transport commodities and labor create derived demands for freight, shopping and commuting trips. Congestion, which arises due to a mismatch between the derived demand for trips and infrastructure capacity, is modeled as increased travel time along individual network links. Increased travel time impinges on the time budgets of households and reduces the ability of transportation service firms to provide trips using given levels of inputs. These effects translate into changes in productivity, labor supply, prices and income. A complete algebraic specification of the model is provided, along with details of implementation and a discussion of data resources needed for model calibration and application in policy analysis.

Transport