Journalpublished

Elasticities of Road Traffic and Fuel Consumption with Respect to Price and Income

Phil Goodwin (University College London), Joyce Dargay (ESRC Transport Studies Unit), Mark Hanly (ESRC Transport Studies Unit)
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Curated by Ted Lango
Published May 9, 2026Updated May 10, 2026
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Abstract

This paper draws on over 50 years of empirical research to estimate elasticities of road traffic levels and fuel consumption with respect to fuel price and income. Long-run elasticities are found to be approximately 2-3 times the short-run values, with significant implications for transport policy and demand forecasting.

Curator Summary

Goodwin, Dargay & Hanly's finding that long-run elasticities are 2-3x short-run is the mathematical foundation for the Savings Time Decay model in the FOW-Value framework. It explains why Year 1 savings look promising but erode by Year 3: customer behavior takes time to fully adjust to lower-effort channels. Short-run elasticity captures immediate behavioral response; long-run captures habit formation, word-of-mouth, and structural adaptation.

Why It Matters

This directly affects multi-year workforce planning and business case construction. Year 1 realizes 50-70% of projected savings (short-run elasticity). By Year 3, only 25-45% remains as long-run behavioral adjustment completes. If your business case projects linear or improving savings over 3 years, this research says you're wrong — model the decay curve or your CFO will be asking uncomfortable questions.

Caveats

Transportation demand elasticities may not map 1:1 to service demand elasticities. The meta-analysis covers a wide time period with varying methodologies. The 2-3x multiplier is an average — specific contexts may see higher or lower ratios. The research predates the AI/digital transformation era.

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