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An Almost Ideal Demand System Model of Household Vehicle Fuel Expenditure Allocation in the United States

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  • Gbadebo Oladosu

Abstract

In this study I model vehicle-fuel expenditure allocation in multi-vehicle households based on the Almost Ideal Demand System (AIDS). Using data from surveys conducted by the Energy Information Administration in 1988, 1991 and 1994, I estimate the AIDS model, augmented with a comprehensive set of household and vehicle characteristics for households owning 1 to 4 vehicles ordered by vehicle age. Results show that vehicle characteristics are the most significant factors in the expenditure allocation process. Mean and standard deviation of price, expenditure and Allen substitution elasticities are calculated across households. Own-price elasticities for all vehicles are close to 1. Allen substitution elasticities indicate that all vehicle pairs are substitutes, and only vehicle 1 is found to be expenditure inelastic. The approach taken in this study enables a disentangling of vehicle allocation/substitution effects from aggregate household vehicle use behavior. This will be useful in the analysis of efficiency and distributional effects of policies affecting household transportation.

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  • Gbadebo Oladosu, 2003. "An Almost Ideal Demand System Model of Household Vehicle Fuel Expenditure Allocation in the United States," The Energy Journal, , vol. 24(1), pages 1-21, January.
    • Handle: RePEc:sae:enejou:v:24:y:2003:i:1:p:1-21
    DOI: 10.5547/ISSN0195-6574-EJ-Vol24-No1-1
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    1. Pinelopi Koujianou Goldbe, 1996. "The Effects of the Corporate Average Fuel Efficiency Standards," NBER Working Papers 5673, National Bureau of Economic Research, Inc.
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    3. Golob, Thomas F. & Kim, Seyoung & Ren, Weiping, 1996. "How Households Use Different Types of Vehicles: A Structural Driver Allocation and Usage Model," University of California Transportation Center, Working Papers qt6xx6j51x, University of California Transportation Center.
    4. Kayser, Hilke A., 2000. "Gasoline demand and car choice: estimating gasoline demand using household information," Energy Economics, Elsevier, vol. 22(3), pages 331-348, June.
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