To Örebro University

Before–after comparisons indicate that the impact of the road toll in Stockholm on traffic volumes was smaller when the system was re-opened in 2007, compared to the effect during the trial in 2006. We calibrate a modal-choice model on data for Stockholm from before and during the trial and use it to simulate the effects of some seemingly subtle changes of the design of the congestion-charge scheme. We find that the growth of the share of exempted “green” cars and the decision to make charges deductible from the income tax was about to considerably reduce the positive welfare effect of the toll at the time when the “green” car exemption was abolished.

This paper uses a static, small open economy computable General Equilibrium (CGE) model of the Swedish economy to study the impact of the consistent internalization of external effects from transport and manufacturing. We look at eight policy scenarios: first, fully implemented Social Marginal Cost Pricing (SMCP)in industry, sea and air transport, road transport,  and rail transport and then SMCP in these sectors separately or in various combinations. We evaluate the effects on, among other things, national and global emissions reductions, GDP, government budget, transport demand, and overall social welfare. The simulation results show that among the eight policy scenarios that we study, correcting prices only for rail transport generates a negative social welfare surplus, the smallest possible emissions reduction effects, and relatively low government revenue. While correcting prices only for road transport generates much larger effects across all aspects, it also increases transport demand on the already congested rail network. Combining rail and road charges generates a relatively high welfare effect, high government revenue, and high emissions reductions.

The value of transport time savings (VTTS) for freight is a critical component of cost-benefit analyses of transport projects and policies. Although there is substantial research available regarding personal travel time value, the literature about freight VTTS is sparse. There are several inherent difficulties related to freight VTTS studies, including firms’ lack of incentives to reveal information that is relevant to their competitive market power and the complexity of the nature of freight transport itself. Furthermore, previous studies of freight VTTS have tended to neglect the dependence between the choices of transport mode and shipment size.

This paper applies a simultaneous decision model for the choices of transport mode and shipment size to a dataset that is constructed by merging the Swedish Commodity Flow Survey data for 2001 with network information from the Swedish national freight transport model to study the VTTS of Swedish shippers for four groups of commodities: agricultural goods, forest goods, mining goods, and manufactured goods. The average VTTS for these four commodity groups are estimated to be 0.80, 0.41, 0.27, and 0.37 Euro per ton per hour, espectively.

In 2003, Sweden initiated a climate subsidy program known as Klimp, to encourage implementation of projects that reduce carbon emissions. A total grant of 1.8 billion SEK was approved for 912 projects, and 766 of these were implemented. The emission reduction from these projects totals 746,000 tons annually. However, it is criticized that some of the subsidized projects might have been implemented in the absence of financial support from Klimp, i.e., the projects were not additional. This concept of "additionality" brings concerns about the opportunity cost of government spending, and about what the impact of Klimp on emission reduction actually is.

This paper compares the implementation outcomes (i.e., whether a project was implemented or not) of Klimp subsidized projects with a control group of projects that were not approved for Klimp subsidies. We use an econometric model to study the treatment effect of the Klimp subsidy, and we estimate the probability that a subsidized project would be implemented with and without the Klimp subsidy. The additionality of Klimp is calculated based on estimated probabilities. The estimation results show that the additionality of Klimp is approximately 60 percent, which means that 60 percent of the Klimp-subsidized projects would not have been implemented had they not been subsidized.