Disaggregating Household Transport in the MIT-EPPA Model

An explicit representation of the household transportation is important for the quantitative analysis of energy and environmental policy. Household transportation is among the more rapidly growing energy uses, transportation fuels are often taxed at much higher rates, policies directed toward energy use and environmental control generally treat the transportation and automobile energy efficiency differently than other uses, and substitution toward or away from automobile use in response to price and policy changes at the first level is likely to be toward purchased transportation. Aggregation of automobile fuel use with other fuels makes it impossible to study these factors explicitly. The GTAP version 5 dataset has three transportation sectors. However, household transportation expenditures related to private automobiles are not represented explicitly in the data. We augment the existing GTAP data to separately disaggregate household transportation and explore the implications of this in the MIT Emissions Predictions and Policy Analysis (EPPA) model. In order to model the household transportation sector, we derive a household expenditure share of own-supplied transport and a refined oil expenditure share for transport of the total household expenditure on refined oil in different regions. For this work we use OECD, Eurostat, UN, IEA, and USDOE data. Based on the resulting data, we modify the household transportation sector in the EPPA model, which consists of purchased and own-supplied transport. The corresponding adjustments to the household demand structure are also made. By introducing this change and specifying elasticities of substitution for energy and between own- and purchased transportation that are representative of evidence in the literature we expect that differences, if they occur from the model without transport disaggregated, will show up in policy cases that increase fuel prices. Climate policy designed to limit carbon emissions effects the fuel cost. Thus, we calculate a change in welfare for a carbon policy scenario with and without household transportation sector. The disaggregation allows us to make better use of the extensive work in the transportation sector to understand substitution possibilities.

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