Working papers in Transport Economics,
CTS - Centre for Transport Studies Stockholm (KTH and VTI)

Abstract: Dedicated to show climate leadership, Sweden has committed to cut 70% of greenhouse gas emissions in the domestic transport sector by 2030 as compared to levels in 2010 (except flights). The aim of this study was to quantify car type choice among private buyers and individuals with cars provided as a fringe benefit, and to investigate the impacts of retrospective policy scenarios using Sweden as a case study. Models were developed using revealed preferences data relating to car attributes and buyer socioeconomics. The company car type choice model reflected both company policy restrictions and employee preferences. The results indicated that range and safety were crucial factors for the widespread introduction of electric cars and plug-in hybrids. Company car owners were more inclined to choose cars with climate friendly fuels than private buyers. Average CO2 emissions per car were however similar in the two groups, which might relate to a stronger preference for heavier and larger cars among company car holders, in combination with the weights-based ‘Clean car’ definition in Sweden. A ‘Clean car’ restriction was company policy for 7.5% of employees, among whom the share of diesel cars was 88%. Policy scenario modeling results further indicated that the impact of recent climate and transport policies has been small: the most notable effect was a policy of reduced fringe benefits taxation on alternative fuels, worth up to €1,100 annually, which resulted in 0.7 % lower average CO2/km per car. For private buyers, a ‘Super Clean Car’ premium, worth ca € 2,000 – € 4,000, had a 0.4 % effect on the average emissions per car, according to models. This effect was twice as high as that for a five year tax-exemption for ‘Clean cars’, worth ca €200 annually for private buyers. Apparently, in order to substantially change the fleet of new cars in Sweden there is a need for tougher transport policies related to climate change mitigation.

Keywords: Public transport; bus; demand model; fares; frequencies; supply; optimization; urban; welfare

JEL-codes: R41; R42; R48

19 pages, May 22, 2018

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