Revisions to the Wharton EFA Automobile Demand Model : The Wharton EFA Motor Vehicle Demand Model (Mark I)

Loxley, Colin J.; Luce, Priscilla; Osiecki, Tim; Rodenrys, Kate; Thanawala, S. · 1980 · ROSA P / United States. Department of Transportation. National Highway Traffic Safety Administration

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Summary

This report documents the development of the Wharton EFA Motor Vehicle Demand Model (Mark I), a revision of the Wharton EFA Automobile Demand Model prepared for the U.S. Department of Transportation’s National Highway Traffic Safety Administration. The primary motivation was to provide technical support for Automobile Fuel Economy Regulation rule-making. A significant structural change involved excluding passenger vans from automobile data, reclassifying them as personal-use light-duty trucks to better align with regulatory policy analysis. The study aimed to enhance the model by adding behavioral equations for imported vehicle shares, re-estimating desired stock equations using alternative demographic scalars, and developing consistent procedures for estimating fuel consumption and vehicle miles traveled. The methodology involved re-estimating cross-section and time-series equations using 1972 state data and historical time-series data. The researchers tested alternative formulations for the desired auto stock equation, replacing the previous "family units" variable with licensed drivers and population aged 16 and over. They found that family units, licensed drivers, and the population aged 16–64 produced statistically robust and behaviorally similar results. The model also introduced new share equations for foreign and domestic vehicles by size class (subcompact, compact, mid-size, full-size, luxury), utilizing relative cost terms based on neighboring classes rather than the entire fleet to reduce volatility. Additionally, the study re-estimated equations for new registrations, scrappage, on-road and EPA miles per gallon (MPG), and vehicle miles traveled. Due to data limitations, a behavioral analysis of scrappage by size class was deemed infeasible; instead, scrappage by class was driven by identities with provisions for exogenous adjustment. Key findings indicate that the revised desired stock equations are robust across different demographic denominators, with income and cost per mile remaining significant determinants. The new share equations for foreign and domestic vehicles provided more stable simulations than previous versions, though luxury foreign shares exhibited high cost elasticities. The exclusion of passenger vans reduced total automobile stock estimates and the full-size share. The study also established consistent algorithms for aggregating vehicle miles and MPG to calculate average fuel economy and gasoline consumption. Finally, the report presents a baseline forecast through 1987, detailing projections for new car sales, imports, prices, scrappage, and fuel consumption based on economic, energy, demographic, and vehicle design assumptions. The significance of this work lies in its provision of a refined, operational forecasting tool for long-run automobile demand and fuel efficiency analysis. By integrating passenger vans into a separate light-duty truck category and improving the behavioral modeling of import shares and fuel economy, the Mark I model offers more accurate inputs for regulatory impact assessments. The robustness of the desired stock equations across different demographic measures enhances the model's reliability for policy simulation. The report serves as a critical resource for understanding the long-run determinants of U.S. automobile demand, particularly in the context of fuel economy regulations and market shifts toward imported and smaller vehicles.

Key finding

The revised model successfully integrates foreign and domestic share equations with refined cost comparisons and excludes passenger vans to provide a consistent framework for forecasting vehicle demand, fuel economy, and gasoline consumption.

Methodology

modeling

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Information type

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• Theoretical Contribution: computational model