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Summary of "Road Traffic Demand Elasticities: A Rapid Evidence Assessment"

Core Content

This report, conducted by RAND Europe on behalf of the UK Department for Transport (DfT), presents a rapid evidence assessment (REA) of peer-reviewed papers and grey literature to evaluate the elasticity of road traffic demand with respect to key economic and demographic factors. The focus is on population growth, income growth, and fuel cost changes, though other factors may also be considered.

Main Objectives

• To understand the factors driving road transport demand, including economic and demographic variables.
• To identify available elasticity estimates for car and freight traffic.
• To assess how these elasticities may have changed over time.
• To provide a basis for forecasting and strategic planning in transport.

Key Findings

1. Fuel Price Elasticities

• The estimated fuel price elasticities for car demand range from -0.1 to -0.5.
• The range is narrower for freight demand.
• Long-run fuel price elasticities are generally lower due to the rebound effect, where improved fuel efficiency reduces the sensitivity of demand to price changes.
• Elasticities may vary by trip purpose, distance, and area type.

2. Income Elasticities

• For passenger transport, income elasticities are mostly in the range 0.5 to 1.4.
• The effect of income on car ownership is significant and indirect.
• Some studies suggest that income elasticities have decreased over time, possibly due to saturation in car ownership levels.
• GDP, household income, and expenditure are used as proxies for income, with varying impacts on elasticity.

3. Population Elasticities

• There is limited direct evidence on population elasticities.
• Some studies use demographic variables like urban density, employment, and age to infer population effects.
• These variables are often applied to future population projections rather than directly reporting elasticities.

4. Changes Over Time

• Evidence on time-related changes in elasticities is limited.
• One multi-country study suggests that fuel price elasticities were lower between 2000 and 2010 than in the previous decade.
• US studies indicate a decrease in elasticity up to 2006 followed by an increase.
• These changes may be attributed to shifts in fuel prices, real income, and fuel efficiency.

5. Transport Demand Modelling

• Elasticities are derived from different methodologies: empirical studies, literature reviews, and transport models.
• Dynamic models using time series data provide long-run elasticities.
• Some models include lagged demand effects or car ownership, while others omit these variables.
• Transport models often do not adjust for vehicle stock in elasticity calculations, but allow for changes in mode and destination choice.

6. Data Types and Methodologies

• Studies use both aggregate and disaggregate data.
• Aggregate data reflect average values across the population.
• Disaggregate data are based on individual or household-level analysis.
• Stated preference (SP) and revealed preference (RP) data are used in different studies.

7. Elasticity Estimates by Study

8. Freight Demand Elasticities

• Elasticities for freight demand with respect to economic activity are in the range 0.5 to 1.5 for an aggregate commodity sector.
• There is greater variation between sectors.
• Some studies suggest that freight demand decoupled from economic activity between 1997 and 2007.
• The relative size of commodity sectors and supply chain efficiencies are factors in elasticity variation.
• There is limited evidence on the impact of van use on freight demand.

Key Gaps in the Evidence Base

• Limited evidence on changes in elasticities over time for the UK.
• Few studies examine the impact of location (urban/rural) and demographic factors on demand.
• No direct population elasticity estimates are available.
• Limited investigation into the causes of freight demand decoupling in the 2000s.
• Many studies use outdated data, even for recent periods.

Methodology Overview

• A rapid evidence assessment was conducted to systematically review published and grey literature.
• The search was restricted to English-language studies from developed countries, with a focus on UK data.
• Only publications from 1990 onwards were included.
• The review included both passenger and freight transport studies, but excluded non-road modes.
• Studies were selected based on their relevance to the three main drivers: fuel price, income, and population.
• The final shortlist consisted of 23 studies, including 15 on passenger transport, 5 on freight, and 3 on both.

Conclusion and Recommendations

• The report highlights the need for more recent data to better understand how elasticities may have evolved.
• A reasonable range of elasticity values is recommended for use in transport models, based on existing literature.
• The findings suggest that elasticities are sensitive to country-specific factors and that transport models should account for these to improve accuracy.
• Further research is needed to explore the impact of demographic and location factors on transport demand.