E-bikes are a viable alternative to cars in urban areas, but their effectiveness in reducing carbon emissions is unclear. This column reveals that a 2018 Swedish e-bike subsidy program succeeded in persuading people to buy an e-bike, and that there was considerable substitution of cycling for driving. However, for the program to be cost-effective, the social cost of carbon is well above the frequently discussed $50-$100 estimates. Other social benefits, such as boosting adoption, promoting health, or reducing congestion, are needed to motivate these interventions.
Emissions from transportation account for approximately 29% of total US greenhouse gas (GHG) emissions, making it the single largest contributor by sector to global warming.
In the transportation sector, cars alone are responsible for 58% of all transportation emissions, according to the US Environmental Protection Agency. Along with electric cars, e-bikes or VAE (electric bicycles) are a potentially important tool in the fight against global warming (Holland et al. 2015). With rechargeable batteries that make them capable of traveling long distances, they can replace car trips to work in dense and growing urban areas around the world.
Since e-bikes are relatively expensive, policymakers have introduced subsidies to boost and accelerate adoption. However, analyzing the welfare of these e-bike subsidy programs is difficult for several reasons:
- Impact: A welfare analysis requires measures of how the subsidy is distributed between consumers and producers. If supply is relatively inelastic, producers compensate each other for higher quantities demanded.
- Additionality: Beyond sharing the surplus, policy makers fear that the programs will attract additional users and not only benefit those who would have converted even in the absence of any subsidy (Joskow and Marron 1992, Boomhower and Davis 2014) .
- Substitution driving: The second point also raises the question of whether a family buying an electric bike will necessarily reduce their driving or whether the bike will replace other means of transport.
Swedish subsidy for e-bikes
To address these issues, in Anderson and Hong (2022), we combine administrative, insurance, and survey data from a large-scale Swedish subsidy program for e-bikes from 2018. The program, which offered a 25% discount on the purchase price, is similar in structure to programs run and offered in other countries. It was very popular. The billion kroner ($115 million) program was supposed to run for three years, but exceeded its annual spending limit in its first year, with nearly 100,000 e-bikes sold. The subsidy amounted to 25% of the retail price, with a limit of 10,000 crowns (approximately $1,100).
In order to assess the effect of the subsidy on prices, we merge subsidy data with sales data from a major bicycle insurance provider in Sweden, obtaining sales data both during and outside of the grant period.
Figure 1 plots the prices and volumes of the 38 top-selling e-bike models throughout the period across the country’s 49 largest retailers, obtained by matching the two data sets. The bold line shows the average price, which barely changed before and after the introduction of the subsidy. The average price is determined by currency depreciation (and a host of other fixed effects that we consider). We find that the entire rebate provided to consumers through the subsidy has landed in the hands of consumers.
Figure 1 Average price and quantities of the best-selling electric bicycle models around the 2018 subsidy
The gray bars in Figure 1 show the effect on quantities, where the darker shades indicate the subsidy period. Consistent with the overall volume increase reported, we see approximately 70% more e-bikes sold during the subsidy. We also use the SEPA survey, which asked people to rate the size of the subsidy, and find that around two-thirds of consumers would not have purchased the e-bike without the subsidy.
For the final analysis, we need data on driving behavior before and after the purchase of the e-bike. Data on commuting is available in the SEPA survey. We are seeing significant changes in driving behavior. Nearly two-thirds of our sample say they use a car to some extent for getting around before purchasing an e-bike, and more than half use it daily. After buying the electric bike, only 4% continue to use the car every day and 54% use it less frequently (of this last group, 23% have completely stopped using the car to get to work). The change in travel behavior by car is more pronounced than by other means of transport, such as the ordinary bicycle or public transport. Interestingly, we find that the recovery of subsidies was relatively greater in less populated regions and not in large cities.
For the last part of the analysis, we collate our results. The average unit cost of the subsidy is around $500, but since it is also paid to non-additional users, it is $766 per additional unit sold. The driving behavior change data allows us to extract the average reduction in car use for the additional users. By multiplying the average lifespan of an e-bike and also taking into account the carbon footprint of the e-bike itself, we find that the average total net carbon reduction is 1.3 tonnes per additional e-bike. To break even at $766, the social cost of carbon must be on the order of $600 per ton, which is far from the $50 to $100 estimates frequently discussed by economists (Nordhaus 2017). The main conclusion is that the subsidy for e-bikes cannot be justified on the basis of the social cost of carbon alone.
Our estimates do not include potential side effects attributed to reduced traffic congestion, road safety, improved health or peer effects and increased adoption rates. A disproportionate increase in subsidies in large cities goes against the fact that the subsidy is an effective tool to reduce congestion. Driving safety and health is not only difficult to measure, but can go both ways. Motorists constitute 42% of our sample of additional users. For them, driving safety may be reduced, although their general state of health is positive. There are signs of increasing adoption rates. Although Figure 1 shows a slowdown in purchases immediately after the subsidy, sales quickly picked up in the following period. The counterfactual is difficult to estimate, but an increase in the conversion rate resulting from the subsidy could be an important motivation for the subsidy that did not enter into our calculations.
We document a relatively large gap between costs and benefits based on carbon savings emissions and leave it to future research to incorporate these other social benefits into the analysis.
Anderson, A and H Hong (2022), ‘Welfare implications of e-bike subsidies: evidence from Sweden’, NBER Working Paper w29913.
Boomhower, J and LW Davis (2014), “A Credible Approach to Measuring Inframarginal Participation in the Energy Efficiency Agenda”, Journal of Public Economics 113: 67–79.
Holland, S, E Mansur, N Muller and A Yates (2015), “Analysis of the environmental benefits of driving electric vehicles”, VoxEU.org, 9 August.
Joskow, PL and DB Marron (1992), “What Does a Negawatt Really Cost? Evidence of utility conservation program,” The Energy Diary 13(4).
Nordhaus, WD (2017), “Revisiting the social cost of carbon”, Proceedings of the National Academy of Sciences 114(7): 1518-1523.