Askill Harkjerr Halse

Public opposition remains a key barrier to the implementation of efficient environ-mental policies. We investigate what drives support for distance-based road pricing,where the per-kilometer fee varies by time and place, using a stated choice experimentwith 638 residents in the Community of Madrid, with informational treatments. First,overall support in our sample is substantial—77% of choices favour a pricing alter-native over the status quo—but depends critically on policy design: support declineswith price stringency and increases when revenues are earmarked for public transport,whileinformationaltreatmentshavelimitedeffects. Second, latentclassanalysisrevealssubstantial preference heterogeneity, with distinct groups differing in price sensitivity,revenue valuation, and demographic composition. Third, we document systematic plu-ralistic ignorance in perceived ideal car use: respondents overestimate others’ tolerancefor car-heavy behaviour, and this misperception is positively associated with policysupport in several specifications. Our results highlight the importance of policy designand heterogeneity for acceptability, and suggest that the relationship between socialnorms and environmental policy support is more nuanced than previously thought.

Travel time is less costly if it is comfortable or can be used productively. One could hence argue that the value of travel time (VTT) of car travellers in economic appraisal should be differentiated by road type, reflecting differences in road quality. We explain the theoretical foundation for such a differentiation, review the relevant literature and show the results of an empirical case study based on actual route choice of highway drivers in Norway. We find little existing literature discussing the link between road type and VTT, but closely related findings suggest that that the impact on VTT could be substantial. Our empirical case study also suggests that the VTT is lower on higher quality road types. Applying this to economic appraisal would imply higher user benefits of road projects that improve road quality.

Web-based stated preference (SP) surveys are widely used to estimate values of travel time (VTT) for cost–benefit analysis, often with internet panels as the source of recruitment. The recruitment method could potentially bias the results because (1) those who frequently participate in surveys may have a lower opportunity cost of time and (2) people who answer the survey at home or in the office may answer differently because the choice situation is less salient to them. In this paper, we investigate both mechanisms using data from a VTT choice experiment study where respondents were recruited from an internet panel, an alternative email register or on-board/on the station. Within all three groups, some complete the survey while making an actual trip. We find that respondents who were recruited from the internet panel or report being members of a panel have a significantly lower VTT, suggesting that internet panels are less representative in this respect compared to other recruitment methods. We also find that those who answer while traveling have a higher VTT, possibly because the benefits of saving travel time are more salient to them than to those who answer while not traveling.

We investigate whether geographic representation affects local voting behavior in closed-list proportional representation (PR) systems, where conventional theoretical wisdom suggests a limited role of localism in voter preferences. Using detailed data on Norwegian parliamentary candidates’ hometowns, we show that parties engage in geographic balancing when constructing candidate lists. However, because most districts contain more municipalities than seats, not all municipalities will ultimately see a local candidate elected. A regression discontinuity design applied to marginal candidates reveals that parties obtain higher within-district support in subsequent elections in incumbents’ hometowns — novel evidence of “friends-and-neighbors” voting in an otherwise party-centered environment. Exploring the mechanisms, we find that represented municipalities often continue to have locally-connected candidates in top positions, in contrast to municipalities with losing candidates, and are more frequently referenced in legislative speeches. There is no evidence that unequal representation creates inequalities in distributive policies.

Unequal descriptive representation of local subconstituencies (municipalities) within electoral districts can potentially generate differences in voting behavior and substantive policy outcomes, but causal identification of this phenomenon is a challenge due to the nonrandom nature of candidate emergence and selection within parties. We use detailed candidate-level data from Norway to investigate the effect of local representation on three outcomes—local voting behavior, central-to-local redistribution, and mentions of municipalities in legislative speeches—applying a regression discontinuity design to marginal candidates to overcome the selection bias inherent in nomination decisions. We find that parties obtain higher support in subsequent elections in the hometowns of narrowly-elected candidates, pointing to a mobilizational benefit for parties of local descriptive representation. In terms of substantive representation, we find no evidence of increased redistributive benefits for represented municipalities, but a significant increase in mentions in legislative speeches relative to unrepresented municipalities.

We study the effect of travel time reliability on passenger demand using a rich data set on period tickets and train delays over time for commuter trips in the Oslo capital region in Norway. We estimate the relationship between delays and demand using origin-destination fixed effects, which controls for any unobserved time-invariant heterogeneity across stations. The results show a negative effect of delays on demand, but smaller than the effect implied by stated preferences. As a possible explanation for this, we consider a reverse causal relationship, where high demand causes passenger crowding which again results in more delays. Splitting the sample into trips that start at crowded stations within the city-zone and trips that do not, we find evidence indicating that crowding is biasing the estimates towards zero.