Rebound Effects

Implications for Transport Planning


TDM Encyclopedia

Victoria Transport Policy Institute


Updated 31 August 2014

This chapter discusses “Rebound Effects” and their implications for transportation planning. Rebound effects refer to increased consumption that often occurs when efficiency improvements reduce user costs. Transportation rebound effects include generated traffic that results from urban roadway capacity expansion, induced vehicle mileage that results from increased fuel efficiency, and increased risk taking that occurs when drivers feel safer. These rebound effects often change the nature of benefits from congestion reduction, fuel efficiency, and traffic safety programs. It is important to consider these impacts in transportation project evaluation.



What is a Rebound Effect?

A Rebound Effect (also called a Takeback Effect or Offsetting Behavior) refers to increased consumption that results from actions that increase efficiency and reduce consumer costs (Herring 1998; Gorham 2009; UKERC 2007). For example, a home insulation program that reduces heat losses by 50% does not usually result in a full 50% reduction in energy consumption, because residents of insulated homes find that they can afford to keep their homes warmer. As a result, they reinvest a portion of potential energy savings on comfort. The difference between the 50% potential energy savings and the actual savings is the Rebound Effect.


The Rebound Effect is an extension of the “Law of Demand”, a basic principle of economics, which states that if prices (costs perceived by consumers) decline, consumption usually increases. A program or technology that reduces consumers’ costs tends to increase consumption. These effects are not limited to financial costs, they may involve reductions in time costs, risk or discomfort. For example, strategies that increase fuel efficiency or reduce traffic congestion, and therefore reduce the per-mile cost of driving, tend to increase total vehicle mileage. Similarly, strategies that make driving seem safer tend to encourage somewhat more “intensive” driving (i.e., faster, closer spacing between vehicles, more distractions) than what would occur if vehicle use appears riskier to drivers.


This is not to suggest that Rebound Effects eliminates the benefits of efficiency gains. There is usually a net congestion reductions or energy savings after the Rebound Effect occurs. In addition, consumers benefit directly from increased vehicle travel or higher vehicle speeds. However, the Rebound Effect can significantly change the nature of the benefits that result from a particular policy or project. It is important to account for rebound effects to accurately Evaluate a policy or project.



Transportation Rebound Effects

This section describes three Rebound Effects related to transportation.


Generated Traffic

Generated Traffic is the additional vehicle travel that occurs when a roadway improvement increases traffic speeds or reduces vehicle operating costs (SACTRA 1994; Litman 2001; FHWA 2000). Increasing urban roadway capacity tends to generate additional peak-period trips that would otherwise not occur. This consists of a combination of diverted vehicle trips (trips shifted in time, route and destination), and induced vehicle travel (shifts from other modes, longer trips and new vehicle trips). Over the long run, Generated Traffic often fills a significant portion (50-90%) of added urban roadway capacity (Hansen and Huang 1997; Noland 2001).


Table 1          Portion of New Capacity Absorbed by Induced Traffic



Long-term (3+ years)



50 - 100%




Johnson and Ceerla


60 - 90%

Hansen and Huang



Fulton, et al.

10 - 40%

50 - 80%



76 - 85%


20 - 50%

70 - 100%

This table summarizes the results of various studies that measure the amount of added urban roadway capacity that is filled with induced travel.



In other words, urban traffic congestion tends to maintain a self-limiting equilibrium: vehicle traffic volumes increase to fill available capacity until congestion limits further growth. Travel that would not occur if roads are congested, but will occur if roads become less congested, is called latent travel demand. Increasing road capacity, or reducing vehicle use by a small group, creates additional road space that is filled with latent demand. Any time a consumer makes a travel decision based on congestion (“Should I run that errand now? No, I’ll wait until later when traffic will be lighter”) they contribute to this self-limiting equilibrium.




Generated Traffic: Additional vehicle trips on a particular roadway or area that occur when roadway capacity is increased, or travel conditions are improved in other ways. This may consist of shifts in travel time, route, mode, destination and frequency).


Induced travel: An increase in total vehicle mileage due to increased motor vehicle trip frequency, longer trip distances or shifts from other modes, but excludes travel shifted from other times and routes.


Latent demand: Additional trips that would be made if travel conditions improved (less congested, higher design speeds, lower vehicle costs or tolls).



Generated traffic can be considered from two perspectives. Project planners are primarily concerned with the traffic generated on a road segment that is expanded, since this affects the project’s Congestion Reduction benefits. Others may be concerned with changes in total vehicle travel (induced travel), which affects overall benefits and costs. Induced travel tends to directly benefit consumers, by increasing their mobility, but it also tends to increase total crash risk, pollution emissions and urban sprawl. In many situations, adding capacity on a particular road will generate additional traffic that increases downstream traffic congestion, road and parking costs.


Some TDM strategies can also have Rebound Effects. On congested urban roadways, Flextime or Telework programs by themselves may do little to reduce long-term congestion, because each space created by an avoided peak-period vehicle trip is filled with latent demand (potential vehicle trips that are constrained by congestion).


In a case study of a proposed roadway expansion project in Copenhagen, Denmark, Næss, Nicolaisen and Strand (2012) found that ignoring a portion of induced traffic effects significantly affected cost-benefit results: results show lower travel time savings, more adverse environmental impacts and a considerably lower benefit-cost ratio when induced traffic is partly accounted for than when it is ignored. They conclude that, “By exaggerating the economic benefits of road capacity increase and underestimating its  negative effects, omission of induced traffic can result in overallocation of public money on road construction and correspondingly less focus on other ways of dealing with congestion and environmental problems in urban areas.”


This is not to suggest that increasing road capacity provides no benefits, but Generated Traffic affects the nature of these benefits. It changes congestion reduction benefits into mobility benefits, offset by any increase in external costs associated with the induced traffic (Ramsey 2005). Accurate transport project evaluation must consider four specific effects:


Generated traffic tends to reduce the predicted congestion reduction benefits of increased road capacity.



Ignoring Generated Traffic effects tends to overstate the benefits of roadway capacity expansion, and undervalues alternative modes and Transportation Demand Management alternatives. Models that fail to consider generated traffic can overvalue roadway capacity expansion benefits by 50% or more (Williams and Yamashita 1992). The FHWA “Spreadsheet Model for Induced Travel Estimation” (SMITE) is specifically developed to predict the amount of vehicle traffic induced by a highway improvement, and its effects on consumer welfare and vehicle emissions (FHWA 1999). It is a relatively easy way to incorporate generated traffic impacts into highway project assessments.


In order to truly reduce urban traffic congestion it is necessary to reduce the point of congestion equilibrium. Some types of TDM strategies do this (Congestion Reduction Strategies).


·         Pricing strategies with higher charges for driving under urban-peak conditions, such as Congestion Pricing and variable Parking Pricing.


·         Strategies that increase the price of driving, such as Parking Pricing and Distance-Based Charges.


·         Strategies that make alternative modes more competitive, such as HOV Priority, Transit Improvements and Commuter Financial Incentives.


·         Strategies that improve land use Accessibility, such as Location Efficient Development and Smart Growth.



The quality of travel alternatives has a significant effect on the point of congestion equilibrium. If travel alternatives are inferior, a relatively high time or financial price is needed to induce travelers to change mode. If alternatives are attractive, travelers will be more inclined to use them, resulting in lower congestion equilibrium and a smaller Road Price needed to reduce congestion. For example, grade separated transit and other HOV Priority strategies can reduce congestion on parallel highways (Social Benefits of Public Transit). When congestion makes driving slower than transit, a portion of travelers shift mode until the highway reaches a new equilibrium (that it, until transit is no longer faster than driving). The faster, cheaper and more comfortable the transit service, the faster the traffic speeds on parallel highways. Improvements to alternative modes can therefore benefit all travelers on a corridor, both those who shift modes and those who continue to drive.


A single TDM strategy is unlikely to have a major effect on overall regional traffic congestion, but a comprehensive TDM program that includes a combination of disincentives to peak-period driving and improvements to alternative modes may reduce the point of congestion equilibrium. A TDM program that is implemented instead of a road capacity expansion project will avoid generating traffic, since congestion levels stay the same.


Table 1          Generated Traffic Impacts

Strategies Likely to Generate Traffic
Strategies Unlikely To Generate Traffic




Fuel Efficiency Standards and Feebates

Some Energy Conservation and Emission Reduction strategies cause motorists to purchase more fuel efficient vehicles than they would otherwise. Fuel Efficiency Standards (such as Corporate Average Fuel Efficiency or CAFE standards) require vehicle manufactures to produce and sell vehicles that meet certain minimum fuel efficiency. Feebates are surcharges on the purchase of fuel inefficient vehicles with revenue used to provide rebates on the purchase of fuel-efficient vehicles. These strategies are intended to encourage energy conservation and reduce Climate Change Emissions (Jansen and Denis 1999; Greene, et al. 1999; Small and Van Dender 2005; UKERC 2007).


However, these efficiency gains reduce per-mile vehicle operating costs, which encourages increased per-vehicle annual mileage, resulting in a takeback effect. For example, if these incentives causes motorists to choose vehicles that are 10% more fuel efficient, this does not usually result in a full 10% fuel savings (Greene, Kahn and Gibson, 1999). Because a more fuel-efficient vehicle costs less per mile to drive, there is a Rebound Effect, which is typically 10-30% over the long run (UKERC 2007). This reflects the elasticity of vehicle travel with respect to fuel price (Transportation Elasticities). As a result, a 10% increase in fuel efficiency actually provides a 7-8% net reduction in fuel consumption and a 1-3% increase in vehicle mileage. For example, a program that increases average fuel efficiency by 10% might reduce the average cost of driving from 10¢ to 9¢ per mile, causing motorists to increase their annual mileage from 12,000 to 12,300.


Research by Enerdata (2009) indicates that each 1% reduction in global oil demand reduces oil prices by 1.6 to 1.8% over a 10 year timeframe, and by 1.2 to 1.3% over a 20-year timeframe. As a result, some of the projected energy savings that result from technical strategies that increase vehicle fuel efficiency (such as fuel efficiency standards) will be offset by increased fuel consumption due to reduced energy prices, a Rebound Effect that does not result if Fuel Taxes increase fuel efficiency.


Although there is still a net reduction in fuel consumption, the increased vehicle mileage tends to exacerbate other transportation problems, including traffic congestion, road and parking facility costs, crashes, pollution and urban sprawl. Ignoring these Rebound Effects tends to overstate the benefits of fuel efficiency standards, and undervalues TDM as an emission reduction strategy (Litman 2002).



Traffic Safety Programs

Road design and vehicle safety features which make drivers feel more secure (wider lanes, larger vehicles, seat belts, air bags, etc.) tend to encourage more “intensive” driving that offsets a portion of the motorists own safety gains and increases risk to other road users, called offsetting behavior or risk compensation (Chirinko and Harper, 1993; Wilde, 1994; Heino, 1996; Noland, 2001). Most research suggests that approximately one-third of potential safety increases are offset by increased driving intensity. For example, if air bags would prevent 3,000 vehicle occupant deaths per year if there were no change in driver behavior, only 2,000 lives would actually be saved, due to this Rebound Effect.


This helps explain why motor vehicle crash rates have not declined as much as would be expected considering the large improvements that have occurred over the last half-century in motorist protection, reduced drunk driving, and emergency medical treatment (TDM Safety Impacts). It also explains why traffic densities have increased significantly over the last decades, with vehicles following closer behind each other on congested roads. This increased feeling of safety may also contribute to overall increases in vehicle mileage. This is not to suggest that improved motorist protection provides no benefits. There is usually a 2/3 net reduction in traffic casualties, and motorists benefit from increased traffic speeds and mobility. However, the safety benefits are not as large as would be predicted if Rebound Effects are ignored, and there are increased risks to other road users.


Although many TDM strategies improve Road Safety, they do this by changing the amount and type of mobility that occurs, rather than reducing risk per vehicle-mile. Failing to consider this Rebound Effect tends to overstate the benefits of conventional safety strategies, such as vehicle occupant protection, and understates the value of TDM as a traffic safety strategy.


HOW WE DRIVE; Roads Are Safer; Cars Are Safer. Drivers? Forget It.

By John M. Broder


Dr. Evans, who is the president of the International Traffic Medicine Association, contends that so-called safety devices in cars, particularly air bags, have had an insidious and deadly effect on driver behavior.


He said that as recently as the late 1970s the United States had the safest highways, using the measure of traffic deaths per 100,000 registered vehicles. Today, he said, the United States is in 12th place and sinking.


“If the United States had simply matched Canada’s performance over that period,” Dr. Evans said, “annual U.S. fatalities this year would be 28,000, rather than more than 41,000.”


He said that since the mid-60’s, American have spent billions of dollar seeking the perfect technological fix to prevent fatalities. Their solutions, the air bag and other “passive” devices, have only compounded the problem. Other industrial nations, Dr. Evans said, have pursued a more balance approach -- better and early driver education, stricter enforcement of traffic and seat-belt laws, use of cameras to detect speeding and red-light running and campaigns against aggressive driving.


“We have just receive the wonderful good news that the air bag is killing fewer people than it used to,” he said. “When was that an advertisement for a safety device, that it’s killing fewer people than it used to?”


Dr. Evans said that the air bag and other safety devices had the same effect collectively as advances in cardiac medicine. Angioplasty and bypass surgery have not decreased the rate of death from heat disease, he said and might have convinced people that there is a technological “cure” for the unhealthy behaviors that lead to heart attacks.


“We see American collectively driving a couple of miles an hour faster because of a false sense of security,” he said. “And that collective increase in speed more than washes away the alleged benefit of air bags.”




Rebound Effects occur when a program or technology reduces perceived consumer costs, thereby encouraging increased consumption. Congestion reduction, fuel efficiency and road safety programs all tend to have significant Rebound Effects. Rebound Effects do not eliminate all benefits, but they can significantly affect the nature of benefits and so should be considered in program evaluation. The magnitude of the Rebound Effect varies depending on many factors, but it often reduces a policy or program’s effectiveness at achieving its primary goal by 10-50%. This is particularly important to consider if it leads to increased vehicle mileage or more intensive driving that increases external costs. These additional external costs should be considered in policy and program evaluation.


Conventional transportation planning practices often ignore Rebound Effects. For example, conventional traffic modeling does not incorporate all types of generated traffic. Similarly, analyses of energy conservation and road safety programs often ignore Rebound Effects.


Failing to consider Rebound Effects tends to overstate the benefits of technical solutions that address a single problem (such as roadway capacity expansion, fuel efficiency standards, or injury risk to vehicle occupants), and understate the relative benefits of TDM alternatives that reduce total vehicle travel and encourage more efficient use of transportation resources.


Wit and Humor

David received a parrot for his birthday. The parrot was fully grown with a bad attitude and worse vocabulary. Every other word as an expletive. Those that weren’t expletives, were to say the least, rude.


David tried hard to change the bird’s attitude and was constantly saying polite words, playing soft music, anything he could think of to try and set a good example. Nothing worked. He yelled at the bird and the bird yelled back. He shook the bird and the bird just got more angry and more rude. Finally, in a moment of desperation, David grabbed the parrot and threw it in the freezer.


For a few moments he heard the bird squawk and kick and scream - then suddenly, there was quiet. Not a sound for half a minute. David was frightened that he might have hurt the bird and quickly opened the freezer door. The parrot calmly stepped out onto David’s extended arm and said, “I believe I may have offended you with my rude language and actions. I will immediately correct my behavior. I really am truly sorry and beg your forgiveness.”


David was astonished at the bird’s change in attitude and was about to ask what had made such a dramatic change when the parrot continued, “by the way... May I ask what the chicken did?”



References And Resources For More Information


Robert Chirinko and Edward Harper, Jr. (1993), “Buckle Up or Slow Down? New Estimates of Offsetting Behavior and their Implications for Automobile Safety Regulation,” Journal of Policy Analysis and Management, Vol. 12, No. 2, pp. 270-296; at


Enerdata (2009), The Impact Of Lower Oil Consumption In Europe On World Oil Prices, European Federation for Transportation and Environment (; at


FHWA (1999), Spreadsheet Model for Induced Travel Estimation (SMITE), Federal Highway Administration, (


FHWA (2000), Highway Economic Requirements System: Technical Report, Federal Highway Administration, U.S. Department of Transportation (


Roger Gorham (2009), Demystifying Induced Travel Demand, Sustainable Transportation Technical Document, Sustainable Urban Transportation Project (; at


David L. Greene, James Kahn and Robert Gibson (1999), “Fuel Economy Rebound Effect for U.S. Household Vehicles,” Energy Journal, Volume 20, Issue 3 (, July 1999, pp. 1-31.


Mark Hansen and Yuanlin Huang (1997), “Road Supply and Traffic in California Urban Areas,” Transportation Research A, Vol. 31, No. 3, pp. 205-218.


Adriaan Heino (1996), Risk Taking In Car Driving; Perceptions, Individual Differences and Effects of Safety Incentives, Rijksuniversiteit Groningen (University of Groningen, Netherlands).


Horace Herring (1998), Does Energy Efficiency Save Energy: The Implications of Accepting the Khazzoom-Brookes Postulate, EERU, the Open University (


Kent M. Hymel, Kenneth A. Small and Kurt Van Dender (2010), “Induced Demand And Rebound Effects In Road Transport,” Transportation Research B (


Annika K. Jägerbrand, et al. (2014), Rebound Effects Of Energy Efficiency Measures In The Transport Sector In Sweden, The Swedish Energy Agency (; at


Heinz Jansen and Cecile Denis (1999),A Welfare Cost Assessment of Various Policy Measures to Reduce Pollutant Emissions from Passenger Road Transport,” Transportation Research D, Vol. 4, No. 6, November, pp. 379-396.


Joshua Linn (2013), The Rebound Effect for Passenger Vehicles, Discussion Paper 13-19, Resources for the Future (; at


David Lewis and Fred Laurence Williams (1999), Policy and Planning as Public Choice: Mass Transit in the United States, Ashgate (


Todd Litman (2001), “Generated Traffic; Implications for Transport Planning,” ITE Journal, Vol. 71, No. 4, Institute of Transportation Engineers (, April, pp. 38-47; at


Todd Litman (2005), “Efficient Vehicles Versus Efficient Transportation: Comparing Transportation Energy Conservation Strategies,” Transport Policy, Volume 12, Issue 2, March 2005, Pages 121-129; at


Todd Litman (2008), Transportation Elasticities: How Prices and Other Factors Affect Travel Behavior, Victoria Transport Policy Institute (; at


Todd Litman (2011), Smart Congestion Relief: Comprehensive Analysis Of Traffic Congestion Costs and Congestion Reduction Benefits, Victoria Transport Policy Institute (; at


Todd Litman (2012), “Changing North American Vehicle-Travel Price Sensitivities: Implications For Transport and Energy PolicyTransport Policy (; full report at


Martin Mogridge (1990), Travel in Towns: Jam Yesterday, Jam today, and Jam Tomorrow?, Macmillan.


Petter Næss, Morten Skou Nicolaisen and Arvid Strand (2012), “Traffic Forecasts Ignoring Induced Demand: a Shaky Fundament for Cost-Benefit Analyses,” European Journal of Transport and Infrastructure Research, Vol. 12 (3), pp. 291-301; at


Robert Noland (2001), “Relationships Between Highway Capacity and Induced Vehicle Travel,” Transportation Research, A, Vol. 35, No. 1, January 2001, pp. 47-72.


Robert Noland (2001), Traffic Fatalities And Injuries: Are Reductions The Result Of ‘Improvements’ In Highway Design Standards?, Imperial College, London (, presented at the Transportation Research Board Annual Meeting.


Robert B. Noland and Lewison L. Lem (2002), “A Review of the Evidence for Induced Travel and Changes in Transportation and Environmental Policy in the US and the UK,” Transportation Research D, Vol. 7, No. 1 (, January, pp. 1-26.


Risk Compensation ( Wikipedia.


Stuart Ramsey (2005), “Of Mice and Elephants,” ITE Journal, Vol. 75, No. 9 (, Sept., pp. 38-41.


SACTRA (Standing Advisory Committee on Trunk Road Assessment) (1994), Trunk Roads and the Generation of Traffic, UKDoT, HMSO (London).


Kenneth Small and Kurt Van Dender (2005), The Effect of Improved Fuel Economy on Vehicle Miles Traveled: Estimating the Rebound Effect Using U.S. State Data, 1966-2001, University of California Energy Institute's (UCEI) Energy Policy and Economics Working Paper Series (


Kenneth A. Small and Kurt Van Dender (2007), “Fuel Efficiency and Motor Vehicle Travel: The Declining Rebound Effect,” Energy Journal, Vol. 28, No. 1, pp. 25-51; at Also see “If Cars Were More Efficient, Would We Use Less Fuel?,” Access, Number 31, University of California Transportation Center (, Fall 2007, pp. 8-13.


UKERC (2007), The Rebound Effect: An Assessment Of The Evidence For Economy-Wide Energy Savings From Improved Energy Efficiency, The Technology And Policy Assessment Function Of The UK Energy Research Centre (; at


Gerald Wilde (1994), Target Risk, PDE Publications (


Huw C. W. L. Williams and Yaeko Yamashita (1992), “Travel Demand Forecasts and the Evaluation of Highway Schemes Under Congested Conditions,” Journal of Transport Economics and Policy, Vol. 26, No. 3, September 1992, pp. 261-282; at

This Encyclopedia is produced by the Victoria Transport Policy Institute to help improve understanding of Transportation Demand Management. It is an ongoing project. Please send us your comments and suggestions for improvement.




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