We estimate the income and fuel price elasticities of household vehicle kilometres travelled (VKT) and car ownership. To model the VKT, we apply a discrete-continuous model on registrAy micro panel data, covering all Swedish households from 1999 to 2018. We model two joint choices: car ownership and VKT conditional on car ownership, where the elasticity of VKT from these two choices are obtained by using the Two-Part model. We account for unobserved household effects using a correlated random effects specification and take household adjustments into account by including lagged values of fuel prices and income. Our preferred model yields a long-run income elasticity of 0.45 for private VKT, where close to two-thirds of the effect comes from the income elasticity of car ownership. The long-run fuel price elasticity of private VKT is −1.03, with the response in VKT among car owners being larger than the response in car ownership.  

We explore cost-efficient scenarios for reaching climate targets for the transportation sectors in the EU and Sweden, covering both passenger and freight transport. Our focus is on the relative contributions to emissions reductions from electrification, biofuels and traffic reduction. Information about cost-efficient scenarios can serve as roadmaps to reach given targets. This is important not only for designing climate policies; it also has implications for traffic planning, biofuel production planning and the transformation of the vehicle manufacturing industry. Our results indicate that electrification is by far the most important factor for reaching the climate targets. With the recent EU vehicle regulations in place, it is possible to reach the climate targets at a moderate cost; with slow electrification, the long-run targets are virtually impossible to reach. Assuming that EU emission standards are binding, reaching the targets also requires considerable amounts of biofuel, especially in the short and medium term. Traffic reduction contributes only marginally to reduced emissions. Hence, other negative externalities from road traffic need to be handled by other policy measures; climate policy only makes a marginal contribution to reducing other traffic externalities.  

It has proven difficult to reduce carbon emissions from the transport sector; in fact, emissions from this sector are still increasing worldwide. Reducing emissions by reducing road transport is challenging; therefore, a transition to a vehicle fleet with low or zero emissions seems essential. Many new cars in OECD countries are sold to firms as fringe benefit cars (sometimes called company cars in the literature). The generous taxation of such cars has been shown to have negative welfare effects because it increases the consumption of cars. However, it is sometimes justified since it speeds up the transition of the car fleet to lower-emission vehicles. The purpose of this paper is to analyze how fringe benefit cars impact carbon emissions, fuel type, weight, size, engine power, and market value of new cars. We apply micro register data including all adult Swedes and their cars, spanning the years 1999 to 2020. By using a matching model that combines Exact matching and Mahalanobis distance matching, the fuel consumption of the fringe benefit car is compared to the hypothetical new private car that the employee receiving the fringe benefit would have otherwise purchased. We find that new fringe benefit cars tend to be larger, heavier, and more powerful than the hypothetical new private cars that fringe benefit car recipients would have otherwise purchased, However, we also find that new fringe benefit cars sold in 2019–2020 consumed 1.2 L less fuel per 100 km compared to hypothetical new private cars, a decrease of 20 percent. The lower fuel consumption of the fringe benefit cars in these years results from a higher share of electric vehicles among them. We also find that the likelihood of the fringe benefit car being an alternative-fuelled vehicle is 6 percentage points higher than if it was bought as a private car.

Stated choice surveys are widely used to inform policy making across a broad range of domains, including transport and environmental planning, health, and marketing. It is common practice to present respondents with multiple choice tasks in order to increase the amount of information collected. A central concern in this context is whether the same underlying preferences drive choices across all tasks, as violations of this assumption may affect the reliability of the survey. There are several reasons to expect that this may not hold: preferences may vary due to fatigue, learning effects, anchoring, or other forms of inertia. In particular, the role of the first choice task has attracted considerable attention. Some authors argue that it is the only valid task, while others view it primarily as a learning exercise. In this paper, we deliberately take no position on the validity of these competing viewpoints. Instead, we question the robustness of the commonly reported finding of stable VTT estimates across choice tasks, noting that much of the existing evidence relies on models that do not incorporate random preference heterogeneity. We therefore propose and test a range of more advanced model specifications to assess whether VTT estimates are stable across individual choice tasks and groups of tasks. Using three different datasets, we identify key modelling features that influence whether preference instability is detected. While estimates are stable for some attributes and choice tasks, they can vary by about 30% for others, and by up to 60% when using latent class models. These differences have important implications for data collection and model estimation in stated choice research, which we discuss in the concluding section. 

Reducing traffic volumes is one way to reduce carbon emissions from the transport sector. Since increasing driving costs is often met with public resistance, high hopes are often pinned on the possibility to reduce traffic volumes by non-coercive policy measures, or “carrots”. Such measures include improvements of alternative modes, strategies that affect urban forms, and “soft measures” that aim to affect behaviour by providing information or changing norms and attitudes. This paper reviews the empirical evidence regarding such measures, focusing on their potential to reduce aggregate road traffic volumes in a national perspective. While such measures can yield significant other benefits, and may also reduce traffic volumes locally, our general conclusion is that their effects on aggregate traffic volumes appear small, especially from a climate policy perspective where emissions need to be cut radically and rapidly. While they are often motivated for several other reasons, overestimating their effects on aggregate traffic volumes may cause complacency, misallocations of scarce public resources and backlashes against climate policy.  

Hur transportsystemet används beror i hög grad på de skatter och avgifter som möter användarna. Prissättningen har därför större påverkan på tillgängligheten och den samhällsekonomiska effektiviteten än exempelvis vad investeringar i ny infrastruktur har. Detta visar nationalekonomerna Maria Börjesson och Jacob Lundberg i SNS-rapporten Skatter på transporter – smartare styrning för effektivare transportsystem.

Rapporten analyserar hur skatter och avgifter i transportsektorn kan utformas för att bättre spegla de kostnader som transporter ger upphov till. Den täcker de viktigaste skatterna och avgifterna – drivmedelsskatter, fordonsskatter, trängselskatter, banavgifter, farledsavgifter, parkeringsavgifter, moms och förmånsbilsbeskattning – och sätter dem i ett bredare institutionellt och nationalekonomiskt sammanhang, med hänsyn till EU-rättsliga ramar. Rapporten presenterar 18 konkreta reformförslag som sammantaget bedöms ge ett nettotillskott till statskassan på 10–20 miljarder kronor per år.

Den bärande principen är att skatter och avgifter i första hand bör motsvara de externa kostnader som trafiken orsakar – trängsel, buller, utsläpp, olyckor och slitage – varken mer eller mindre. Analysen bygger på en genomgång av vetenskaplig litteratur samt offentlig statistik över transporter, skatteintäkter och offentliga utgifter.

This paper studies how vertical integration, subsidies, and interoperability regulation shape investment and welfare in electric vehicle (EV) public charging markets. We model the interaction between Charging Point Operators (CPOs), which invest in charging infrastructure, and Mobility Service Providers (MSPs), which sell charging services to end users. The model features indirect network externalities: denser infrastructure reduces range anxiety and increases EV adoption, while higher EV demand raises infrastructure profitability. In the benchmark laissez-faire environment, vertical integration creates a trade-off. Integrated CPOs-MSPs may foreclose rival MSPs and reduce downstream competition, but they also internalize the complementarity between infrastructure investment and EV demand, generating higher infrastructure density, EV adoption, consumer surplus, and welfare than vertical separation. This welfare ranking is established under foreclosure and is then generalized in a robustness extension with interoperability constraints. Minimum-margin rules keep the rival MSP active and soften foreclosure, while the integrated firm still retains part of its investment advantage. However, when interoperability entails compliance and coordination costs, stricter access regulation may further weaken infrastructure investment incentives. We also compare consumer subsidies and firm subsidies within the benchmark environment. Consumer subsidy dominates under vertical integration, while firm subsidy may dominate under separation only when network effects are sufficiently strong. A calibration to Italian metropolitan areas supports these mechanisms and highlights a fiscal trade-off: consumer subsidy generates larger welfare gains, whereas firm subsidy may deliver higher environmental benefits per euro spent.

Several countries have set reduction targets for the transportation sector and the EU has an emission target for the ESR sector, which includes the transport sector. Carbon emission reduction targets in the road transport sector can be achieved through a combination of reduced traffic (VKT), an increased share of biofuels, and decreased vehicle emissions per kilometer. This paper explores cost-efficient contributions from different adaptation mechanisms by determining the optimal fossil fuel tax and biofuel share needed to meet climate emission targets in the EU and Sweden. Cost-efficient scenarios, or roadmaps, are important not only for for climate policy; they have implications for traffic planning, biofuel production and the transformation of the vehicle industry. 

We first forecast the traffic increase for cars, vans, and heavy vehicles from 2020 to 2050, as well as the average emissions per VKT for the future vehicle fleet. This is based on a vintage model that accounts for how new vehicles enter the fleet and how VKT vary by vehicle age. We consider the emission requirements for new vehicles as binding in the EU, though not in individual countries. Based on the forecasted transport demand and average emissions per VKT by year, we project emission reductions for 2030 and 2050 in the baseline scenario. We then calculate the optimal combination of a carbon tax increase and biofuel share that ensures the emission targets are met and determine the traffic response. 

The EU aims to achieve climate neutrality for trucks. This paper compares the user cost of diesel trucks, battery electric trucks, and trucks that rely on overhead lines in a decision context where the developments of battery costs and overhead line investment and maintenance costs are uncertain. The user costs contain the truck capital cost and the energy costs, the possible vehicle-to-grid benefits, driver costs, and other distance costs. User costs are compared for different distance profiles and optimized battery sizes. The possible user cost developments serve as input to an analysis of investment decisions in electric motorways (e-roads). The economics of e-roads is analyzed for two representations of the EU TEN-T network. In the first analysis, average EU truck flow (veh/h) and truck trip characteristics are used. In the second representation, we consider domestic and international truck transport between two neighbouring countries with strongly diverging average traffic flows and shares of international truck trips on their TEN-T network. This allows for the analysis of the non-cooperative and cooperative solutions of the two countries. The installation of e-roads appears to be a robust investment decision for the motorways of large countries that have dense truck traffic but not for less dense countries. Cooperation between countries may increase total benefits due to economies of scale.

Achieving climate neutrality for heavy-duty trucks is, in some ways, more challenging than for cars, but it is necessary since they contribute nearly 30 percent of climate emissions from road transport. This paper compares the social costs of diesel trucks, battery-only trucks (BAT), and battery overhead line trucks (BOT), which can charge while driving via overhead lines on electric motorways (e-roads). We conduct this comparison within a decision-making context where the future developments of battery costs, as well as overhead line investment and maintenance costs, are uncertain.