Driving towards the low-emission society

The project aims to provide accurate and reliable knowledge on the effects of existing and potential future policies to support the transition to zero and low-emission automobiles in Norway. The project has studied how different policies affect how many cars households own, by type of car (electric vs. petrol or diesel driven), and how far households drive them. In addition, the project discusses environmental consequences, such as global and local emissions, energy demand, and distributional effects across households and individuals. The analyses in the project use a novel database assembled from administrative registers encompassing the entire Norwegian population, combining disaggregate information on passenger cars and owner characteristics. "Who goes electric? The anatomy of electric car ownership" describes Norwegian BEV owners using administrative register data containing the entire population of private car owners in Norway. The results show that owning a BEV is positively associated with income, wealth, and education. Over time, the typical owner of a BEV has become more similar to other car owners. The results also show a lower probability that buyers of electric cars sell the car they owned from before than buyers of other cars. However, this difference also has become less over time. "Congestion Pricing, Air Pollution, and Individual-level Behavioral Responses" studies the effects of a congestion charge implemented in Bergen in 2016. The congestion charge gave higher tolls during rush hours for conventional cars while electric cars were exempted from all road tolls. This article shows that higher tariffs reduced traffic during rush hour as well as local air pollution. While the effect of increased rush hour rate on total car ownership was close to zero, demand for electric cars increased. About 1/3 of the increase in electric car ownership between 2014 and 2017 among affected households can be attributed to the increased rush hour rate. The effect is greatest for the rich and highly educated, households with children, long distances to work, and poor access to public transport. The article shows that the congestion charge is an effective way to reduce emissions and promote green technology, but the distributional effects can be undesirable. "Local Incentives and Electric Vehicle Adoption" examines the effects of road tolls and bus lanes on the commute to work on car ownership and driving and how different types of households are affected differently. Exposure to local BEV privileges in road toll exemptions and bus lanes raises demand for electric cars. However, they also affect ownership in general as well as the driving distance of conventional cars. Calculations based on the results show how these local measures reduce CO2 emissions from the car fleet. "Substitution Patterns and Demand for Battery Electric Vehicles" focuses on new car sales in Norway from 2010-2016. The estimated demand model shows great variation in the population when it comes to preferences for electric cars. On average, those who buy an electric car have a higher income and thus are less price-sensitive than the general population. The model is used to simulate the effects of policies. In 2016, the VAT exemption for electric cars led to an increase in electric car sales by 23 percent. One-third of these new electric cars were in addition to other car sales, while two-thirds displaced sales of new traditional cars. "Portfolio Complementarities and Electric Vehicle Adoption" focuses on the role of electric cars in household decisions about driving and car ownership. The article develops and estimates a model for households' choice between owning 0, 1, or 2 cars, what kind of cars, and how far the households drive the cars. The model shows that households benefit more from an electric car if they also own a conventional car. One consequence of this is that electric car incentives will increase the number of two-car households. Unless considering this complementarity, the efficiency of electric car incentives as an environmental tool will be overestimated. It will miss that two-car households drive more than single-car households, and electric cars also contribute to local negative externalities such as queues, road wear, and airborne dust. In three articles published in 2021, TØI researchers study car taxes in Norway and their impact on market development and greenhouse gas emissions. First, they study the direct and cross-price elasticities for electric, hybrid, petrol, and diesel cars. Second, they estimate the implicit carbon price built into taxes for passenger cars to NOK 13,000 per ton of CO2. A third article compares the car tax systems in Denmark, Norway, and Sweden. The Norwegian system has the largest effect on new passenger cars' average CO2 emissions but generates less public revenue than in Denmark. Swedish car taxes provide small revenues to the state and are inefficient as a climate measure.

Prosjektet har: -ført til publiserte artikler i anerkjente tidsskrift, og flere er underveis. -gitt nyttige erfaringer fra bruk av sammenkoblete registerdata innenfor transportfeltet for prosjektmedlemmer, forskersamfunnet og offentlig forvaltning. -samfinansiert en doktorgrad om elbiler med en empirisk tilnærming og bruk av registerdata. -styrket samarbeid mellom forskningsmiljøer i Norge med komplementær kompetanse: Transportøkonomisk Institutt og Frischsenteret, og gitt grobunn for videre samarbeid. -styrket internasjonalt forskningssamarbeid med Universitet i København, det eneste fagmiljøet som før dette prosjektet hadde erfaring med denne typen registerdata innenfor transportforskningen. -gitt innsikt om hvem som eier elbil og effekter av politiske virkemidler for etterspørsel og bruk av elbiler samt følger for utslipp fra transportsektoren, og fordelingshensyn. -gitt nyttig kunnskap for nasjonale og lokale myndigheter i samordning av transportpolitikk og miljøambisjoner.

The project will assemble a novel database encompassing the entire Norwegian population, combining detailed individual information about their cars and household characteristics from administrative registers. The data covers income, wealth, tax and employment registers, motor vehicle and driver's license registries, the odometer readings at periodic vehicle inspections, as well as miscellaneous geographic information including public transport supply and travel distances. Based on the rapid uptake of zero emission vehicles in Norway, the project will provide solid evidence and understanding of how policy can help transform the passenger transport sector from relying primarily on vehicles with combustion engines, mainly running on fossil fuels, to using electric vehicles. The project will examine and quantify how households choose between different vehicle makes and models, and also, given that the household owns one or more cars, how much each car is used. The analyses will take explicit account of, and provide insight into, the interdependence between car ownership and use. The estimated choice models will be used to simulate effects of a rich set of alternative policies promoting the use of low-carbon cars. Each counterfactual study will predict outcomes at the disaggregate household level. This will provide an excellent basis for evaluating both effectiveness and distributional effects, across, say income groups and geographical areas.