In this paper we develop two methods for the use of mobile phone data to support the estimation of long-distance mode choice models. Both methods are based on logit formulations in which we define likelihood functions and use maximum likelihood estimation. Mobile phone data consists of information about a sequence of antennae that have detected each phone, so the mode choice is not actually observed. In the first trip-based method, the mode of each trip is inferred by a separate procedure, and the estimation process is then straightforward. However, since it is not always possible to determine the mode choice with certainty (although it is possible in the majority of cases), this method might give biased results. In our second antenna-based method we therefore base the likelihood function on the sequences of antennae that have detected the phones. The estimation aims at finding a parameter vector in the mode choice model that would explain the observed sequences best. The main challenge with the antenna-based method is the need for detailed resolution of the available data. In this paper we show the derivation of the two methods, that they coincide in case of certainty about the chosen mode and discuss the validity of assumptions and their advantages and disadvantages. Furthermore, we apply the first trip-based method to empirical data and compare the results of two different ways of implementing it.

The accuracy of a transport demand model's predictions is inherently limited by the quality of the underlying data. This issue has been highlighted by the decline in response rates for transport surveys, which have traditionally served as the primary data source for estimating transport demand models. At the same time, mobile phone network data, not requiring active participation from subjects, have become increasingly available. However, some key trip and traveller characteristics enhancing the prediction power of the estimated models are not collected in mobile phone network data. In this paper we therefore investigate what can be gained from combining mobile phone network data with travel survey data, using the strengths of each data source, to estimate long-distance mode choice models. We propose and estimate a set of mode choice demand models on joint mobile phone network data and travel survey data. We show that combining the two data sources produces more credible estimates than models estimated on each data source separately. The travel survey should preferably include the variables: travel party size, cars per household licence, licence holding, in addition to origin, destination, mode, trip purpose, age, and gender of the respondent.

It has long been well-known that economic variables such as GDP and fuel price as well as socio-demographic characteristics and spatial distribution are key factors explaining car use trends. However, due. to the recently observed plateau of total car travel in many high income countries, it has been argued that other factors, such as changes in preferences, attitudes and life-styles, have become more important drivers of car use. This paper shows that the two variables, GDP per capita and fuel price, explain most of the aggregate trends in car distances driven per adult in Sweden: as much as 80% over the years 2002 to 2012. The estimated elasticities are well in line with previous literature and can reasonably well reproduce the trend in car distances driven per adult back to 1980. We find, however, a substantial variation in elasticities between municipalities depending on public transport supply, population density, share of foreign-born inhabitants and the average income level.

This paper analyses changes in individual travel behaviour in Stockholm County over 30 years, using three large cross-sectional travel survey data sets. It shows that travel patterns have diverged over time between city, suburban and rural residents. The trends in travel behaviour that we find are consistent with changes in the labour market, ICT use, land-use and transport policy, gender equality, and population composition trends. The inner city has become increasingly attractive: the share of trips is to the inner city is increasing for all purposes, socio-economic groups, and residential locations. The reduction of car traffic in response to the introduction of the congestion charges in 2006 is more than compensated by an increase in bicycle and transit trips to the inner city. Travel times by car are increasing in the city, although the car traffic volumes have decreased. The travel behaviour gender gap has closed completely in the inner city, but not further out in the region or in the rest of the country. Understanding long term trends in travel behaviour in different population segments, and the context under which they occur, helps to understand how the conditions, opportunities and constraints for different population segments are changing, which is key for transport policy and land-use planning. Since the societal trends driving travel behaviour in Stockholm and Sweden are much the same in many cities and countries, the findings are of general relevance.

Many western countries have seen a plateau and subsequent decrease of car travel during the 21st century. What has generated particular interest and debate is the statement that the development cannot be explained by changes in traditional explanatory factors such as GDP and fuel prices. Instead, it has been argued, the observed trends are indications of substantial changes in lifestyles, preferences and attitudes to car travel; what we are experiencing is not just a temporary plateau, but a true “peak car”. However, this study shows that the traditional variables GDP and fuel price are in fact sufficient to explain the observed trends in car traffic in all the countries included in our study: the United States, France, the United Kingdom, Sweden and (to a large extent) Australia and Germany. We argue that the importance of the fuel price increases in the early 2000s has been underappreciated in the studies that shaped the later debate. Results also indicate that GDP elasticities tend to decrease with rising GDP, and that fuel price elasticities tend to increase at high price levels and during periods of rapid price increases.

We estimate the income and fuel price elasticities of private car vehicle kilometres travelled (VKT) using fixed effects on registry micro panel data covering all Swedish households from 1999 to 2018. Such registry data, covering all individuals and cars in the country, are unique to Nordic countries and are comprehensive enough to allow fine segmentation of the population by both income groups and several municipality types. To address potential endogeneity arising if employees receive a wage compensation for long commutes, we apply the temporal changes in earned income tax credits as an instrumental variable. We find lower income and price elasticities (in absolute value) in the large cities, and larger elasticities in suburbs, other cities and in rural areas. We also find that the elasticities decrease with income, excluding the lowest income quartile, having the lowest elasticities. Specifically, we show theoretically and empirically that because the income elasticity varies considerably along the income distribution, the resulting income elasticity depends heavily on how the estimator assigns weight to different income groups, unless the specification explicitly allows for variation in the impact of income on VKT. Moreover, the impact of an income increase depends on to whom the income increase accrues to. For a uniform income increase, 0.2 is the preferred income elasticity. Our preferred long-run fuel price elasticity is -0.53. The short-run elasticities are lower. These elasticities apply to the full population and not only to car owners or drivers.

It is sometimes argued that standard state-of-practice logit-based models cannot forecast the demand for substantially reduced travel times, for instance due to High Speed Rail (HSR). The present paper investigates this issue by reviewing the literature on travel time elasticities for long distance rail travel and comparing these with elasticities observed when new HSR lines have opened. This paper also validates the Swedish long distance model, Sampers, and its forecast demand for a proposed new HSR, using aggregate data revealing how the air-rail modal split varies with the difference in generalized travel time between rail and air. The Sampers long distance model is also compared to a newly developed model applying Box-Cox transformations. The paper contributes to the empirical literature on long distance travel, long distance elasticities and HSR passenger demand forecasts. Results indicate that the Sampers model is indeed able to predict the demand for HSR reasonably well. The new non-linear model has even better model fit and also slightly higher elasticities.

It is sometimes argued that standard state-of-practice logit based models cannot forecast the demand for substantially reduced travel times, for instance due to High Speed Rail (HSR). The present paper investigates this issue by reviewing travel time elasticities for long-distance rail travel in the literature and comparing these with elasticities observed when new HSR lines have opened. This paper also validates the Swedish official long-distance model and its forecasted demand for a proposed new HSR track, using aggregate data revealing how the air-rail modal split varies with the difference in generalized travel time between rail and air. The official linear-in-parameters long-distance model is also compared to a model applying Box-Cox transformations. The paper contributes to the empirical literature on long-distance travel, long-distance elasticities and HSR passenger demand forecasts. Results indicate that the Swedish state-of-practice model, and similar models, is indeed able to predict the demand for a HSR reasonably well. The non-linear model, however, has better model fit and slightly higher elasticities.

The parameters for travel time and travel cost are central in travel demand forecasting models. Since valuation of infrastructure investments requires prediction of travel demand for future evaluation years, inter-temporal variation of the travel time and travel cost parameters is a key issue in forecasting. Using two identical stated choice experiments conducted among Swedish drivers with an interval of 13 years, 1994 and 2007, this paper estimates the inter-temporal variation in travel time and cost parameters (under the assumption that the variance of the error components of the indirect utility function is equal across the two datasets). It is found that the travel time parameter has remained constant over time but that the travel cost parameter has declined in real terms. The trend decline in the cost parameter can be entirely explained by higher average income level in the 2007 sample compared to the 1994 sample. The results support the recommendation to keep the travel time parameter constant over time in forecast models, but to deflate the travel cost parameter with the forecasted income increase among travellers and the relevant income elasticity of the cost parameter. Evidence from this study further suggests that the inter-temporal and the cross-sectional income elasticities of the cost parameter are equal. The average elasticity is found to be -0.8 to -0.9 in the present sample of drivers, and the elasticity is found to increase with the real income level, both in the cross-section and over time.

The parameters for travel time and travel cost are central in travel demand forecasting models. Since valuation of infrastructure investments requires prediction of travel demand for future evaluation years, inter-temporal variation of the travel time and travel cost parameters is a key issue in forecasting. Using two identical stated choice experiments conducted among Swedish drivers with an interval of 13 years, 1994 and 2007, this paper estimates the inter-temporal variation in travel time and cost parameters. It is found that the travel time parameter has remained constant over time but that the travel cost parameter has declined in real terms. The trend decline in the cost parameter can be entirely explained by higher average income level in the 2007 sample compared to the 1994 sample. The results support the recommendation to keep the travel time parameter constant over time in forecast models but to deflate the travel cost parameter according to forecasts of income increases among travellers and the relevant income elasticity of the cost parameter. Evidence from this study further suggests that the inter-temporal and the cross-sectional income elasticity of the cost parameter are equal. The average elasticity is found to be -0.8- -0.9 in the present sample of drivers, and the elasticity is found to increases with real income level, both in the cross-section and over time.

In the current paper, a departure time choice model including travel time variability is estimated, combining stated preference and revealed preference data. We account for response scale differences between RP and SP data and, applying the mixed logit model, test for correlation of scheduling sensitivity across RP and SP choices within individuals. The analysis implies systematic differences in the RP and SP data. With support of the evaluation from the Stockholm trial, this indicates that SP is less trustworthy for trip timing analysis and forecasting, presumably because there are temporal differences in RP and SP choice situations.

This paper describes a study undertaken to estimate a departure-time and mode-choice model for Stockholm. The model is segmented according to trip purpose, and a mixed - or error component - logit model is estimated. Estimation draws on stated preference data collected from drivers travelling toward the city centre during morning peak hours. The study uncovers drivers' preferences for scheduled delay, unexpected delay, travel time and cost as well the patterns of substitution between mode and time of day alternatives. The result indicates that disutility of unexpected delay depends on the scheduled deviation from preferred arrival time. The preference for scheduled delay is roughly proportional to the time shift and varies in the population, but is much more consistent within an individual. Another finding is that constraints at the destination mainly restrict late arrival, whereas constraints at the origin mainly restrict early departure.

This study uses a stated choice experiment and drawings of four different type-environments to assess how various security-promoting factors in the built physical environment influence valuation of walking time when accessing public transport. Valuations that can be applied for evaluating policies to improve perceived security are obtained. Consistent results are achieved, indicating that the method is promising for incorporating aspects in the physical environment in the welfare analysis. The results indicate a systematic variation in value of walk time in different physical environments and it is more dependent of the physical environment for women than for men. This paper thereby contributes to the literature by showing that results by social sciences can be verified using methods and theories traditionally used in transport and welfare analysis and may therefore be incorporated in standard CBA. A contribution of this study is the insight that the perception of insecurity involved in accessing the public transport system is a welfare loss that can be quantified.

This study uses a stated choice experiment and drawings of four different type-environments to assess how various security-promoting factors in the built physical environment influence valuation of walking time when accessing public transport. Valuations that can be applied for evaluating policies to improve perceived security are obtained. Consistent results are achieved, indicating that the method is promising for incorporating aspects in the physical environment in the welfare analysis. The results indicate a systematic variation in value of walk time in different physical environments and it is more dependent of the physical environment for women than for men. This paper thereby contributes to the literature by showing that results by social sciences can be verified using methods and theories traditionally used in transport and welfare analysis and may therefore be incorporated in standard CBA. A contribution of this study is the insight that the perception of insecurity involved in accessing the public transport system is a welfare loss that can be quantified.

We analyze Internet and telephone Stated Choice (SC) survey methods in the context of the Swedish value of time study 2008. In this study, extensive piloting and follow up surveys was undertaken to assure high quality data. We use these data and data from the main survey to analyse properties of the different data collection methods. One conclusion is that Internet gives less random error in the SC data. On the other hand, the response rate drops when Internet is the only response and recruiting mode. A mixed mode survey, where Internet is the primary method but where respondents are knowingly subject to a telephone follow up survey, is found to give substantially higher Internet response rates. If the telephone follow up does not include SC questions, the value of time result will still be biased. A large part of this bias seems to be explained by socio-economic data, such as income and age, which are cheaper to collect.

We approximate the spatial and temporal distribution of the Pigouvian kilometre tax for road traffic in the most urbanized part of Sweden, with four million inhabitants and a similar "degree of urbanization" to the Netherlands and the UK, in a future scenario where most vehicles are electric. We apply the national transport model and include all links and four time-of-day periods. We find that roughly half of the vehicle kilometres travelled in Ma center dot lardalen has a marginal external cost (congestion and other external costs included) below 0.04 euro/km which is below the fuel tax in 2019). The mean marginal external cost is higher, at 0.09 euro/km. Our focus is not the exact numbers but the magnitudes and the vast variation across links in a country-like region: 90 percent of the revenue is collected on 10 percent of the road network. Hence, a nation-wide kilometre tax, implying high enforcement cost, is likely not the best option. Instead, the marginal external cost could probably be internalized fairly accurate by a congestion tax in the big cities in combination with for instance an ownership tax. We find that the Pigouvian tax would cover the public costs for our target road system. We relate our findings to the mainstem fiscal tax literature.

This paper provides two microeconomic models that derive the social cost of a low emission zone (LEZ) for light vehicles. We apply the models to a proposed LEZ for light vehicles in Stockholm, which would prohibit diesel cars of Euro 5 or lower and gasoline cars of Euro 4 or lower in the inner city (25 km2) and conduct a cost-benefit analysis of the proposed LEZ. The first model is based on how an increase in user cost impacts traffic volumes in the inner city. This rather conventional user cost calculation of drivers loss requires however some strong assumptions. The second model shows that drivers losses can be calculated based on price changes observed on the used car market. Our empirical results indicate that the welfare loss resulting from the two models are of the same magnitude. The forecast benefits of the LEZ consist primarily of air quality improvements leading to health benefits. Even if our empirical results must be interpreted with caution, it seems clear that the costs considerably outweigh the benefits in this case study.

The purpose of this paper is to explore to what extent the effects of congestion charges rely on specific features of a city and its transport system. We use Stockholm, and its current congestion charging scheme, as a case study by making various modifications in the transport system influencing the availability and attractiveness of public transport, bypasses and bottleneck capacities. We use a transport model to forecast the effects of the Stockholm charges given each transport system modification. Our main conclusion is that although the social benefit of a given charging system is considerably and non-linearly dependent on initial congestion levels, traffic effects and adaptations costs are surprisingly stable across transport system modifications. Specifically, the level of public transport provision has only small effects on baseline congestion, and therefore on the total benefit of the charges. Contrary to expectation, the charges' effect on traffic volumes remains virtually unchanged regardless of the changes in public transport supply. All results are compared to and consistent with the one-market standard model. We interpret our results with respect to common arguments against the transferability of experiences from cities having introduced congestion charges.

The purpose of this research was to explore how the values of travel time (VTT) and preferences for different modes vary within individuals compared with the variation between observed trips. With 6-week revealed preference panel data and stated preference data from a mode choice context, both collected in Switzerland, a revealed stated preference logit mode choice model was estimated. The model was applied to simulate how VTT and change in consumer surplus vary across trips within and between individuals over the 6 weeks in response to a hypothetical congestion-charging scheme. The variation in VTT arising from income differences was found to be substantially smaller than the variation in VTT between trips. Moreover, the variability in VTT averaged over all trips within each individual was considerably smaller than the variability in VTT for all observed trips. Therefore, the assumption that variation in VTT between observed trips reflects the variation in the average VTT between individuals, which is usually made in equity analyses, will over-state the between-individual variation. The results suggest that if intraindividual variation in preferences is not taken into account, the negative equity effects of congestion charges are likely to be overestimated.

We provide a synthesis of results and insights from the Swedish Value of Time study, with focus on what is relevant for transport appraisal and understanding travel behavior. We summarize recent econometric advances, and show how these enable a better understanding and identification of the value of time distribution. The influence of the sign and size of changes is estimated and discussed, including the problems of loss aversion and the value of small time savings. Further, we show how the value of time depends on trip and traveler characteristics, discuss in what dimensions the value of time should be differentiated in appraisal, and provide recommended values for use in applied transport appraisal.

We provide a synthesis of results and insights from the Swedish Value of Time study, with focus on what is relevant for transport appraisal and understanding travel behaviour. We summarize recent econometric advances, and show how these enable a better understanding and identification of the value of time distribution. The influence of the sign and size of changes is estimated and discussed, including the problems of loss aversion and the value of small time savings. Further, we show how the value of time depends on trip and traveller characteristics, discuss in what dimensions the value of time should be differentiated in appraisal, and provide recommended values for use in applied transport appraisal.

Rapporten är upplagd på följande sätt. I kapitel 2 beskrivs vad som ingår i en samhällsekonomisk kalkyl och hur den tas fram. Kapitel 3 redovisar våra slutsatser om hur samhällsekonomiska kalkyler påverkar beslut om infrastrukturinvesteringar. I kapitel 4 diskuteras vanliga invändningar mot kalkyler, till exempel att inte alla effekter finns med eller att den är att resultatet påverkas starkt av antagande om förutsättningar, till exempel framtida bränslepriser etc. Kapitel 5 diskuterar mer utförligt vad det svaga sambandet mellan samhällsekonomisk effektivitet och beslut kan bero på, vilka problem det kan leda till och vad man skulle kunna göra åt det för att få en effektivare resursanvändning i transportsektorn.

We investigate how passengers on long-distance trains value unexpected delays relative to scheduled travel time and travel cost. For scheduled services with high reliability and long headways, the value of delays is most commonly assumed to be proportional to the average delay. By exploring how the valuation of train delays depends on delay risk and delay length, using three different stated choice data sets, we find that the "average delay" approach does not hold: the disutility increases slower than linearly in the delay risk. This means that using the average delay as a performance indicator, a guide for operations planning or for investment appraisal will underestimate the value of small risks of long delays relative to large risks for short delays. It also means that estimated valuations of "average delay" will depend on the delay risk level: valuations will be higher the lower the risk levels in the study are.

We explore the issue of differentiating the valuation of travel time savings (VTTS) in transport cost-benefit analysis, summarising and discussing theories forming the basis for arguments for and against VTTS differentiation. We stress some important implications, insights and consequences of different assumptions relating to these theories, many of which we feel have been underappreciated in much of the CBA literature and practice. We derive a welfare rule including a social cost for monetary redistributions and show the implications for how the VTTS can be defined in different choice situations. Crucially, the applicable VTTS definition depends on whether travel costs (fares) are under public control and to whom benefits accrue in the long run. In some choice situations, the VTTS should be controlled for differences in income, but it is important to always take into account differences in marginal utilities of time (e.g. across travel time components, modes and trip purposes). Using Swedish data, we show that controlling the VTTS for income differences changes the VTTS only slightly; the variation in VTTS across modes, trip lengths, trip purposes apparently stems primarily from differences in marginal utilities of time rather than income.

Purpose – This chapter provides a think piece on economic evaluation and policy for cycling. Bicycle investments are often motivated by a desire to improve health, the environment and congestion conditions. However, we argue that since the bicycle is a part of the transport system, it should be evaluated as such. Focusing on implications for cycling appraisal in general, we also discuss two conflicting trends in Stockholm: a sharp decrease in cycling in the outer areas, and a sharp increase in the inner parts. Methodology – We use (i) travel survey data to analyse the potential to reduce congestion through improvements for cyclists, (ii) travel survey data from 1986 to 1987 and 2004 and bicycle counts over 25 years and (iii) a value of time survey of Stockholm cyclists including questions of exercise habits. Findings – Additional benefits in appraisal from reduced car traffic and improved health seem to be small. Given bicyclists’ high values of time and low investment costs, bicycling investments are still likely to be socially beneficial. The conflicting bicycling trends can be explained by (i) increased road congestion and improved bicycle infrastructure, (ii) increased visibility of bicyclists generating a ‘positive spiral’, (iii) increased interest in physical fitness and changes in the relative prices of cars versus central residences turn cycling into a high-status mode and (iv) in peripheral areas, increasing distances and less dense land use patterns decrease cycling levels. Practical implications – The results underscore the need for dense, mixeduse spatial planning and ‘smart’ marketing using the effects of cyclist visibility to reinforce the ‘status’ of cycling.

We estimate the value of time savings, different cycling environments and additional benefits in cost-benefit analysis of cycling investments. Cyclists' value of travel time savings turns out to be high, considerably higher than the value of time savings on alternative modes. Cyclists also value other improvements highly, such as separated bicycle lanes. As to additional benefits of cycling improvements in the form of health and reduced car traffic, our results do not support the notion that these will be a significant part in a cost-benefit analysis. Bicyclists seem to take health largely into account when making their travel choices, implying that it would be double-counting to add total health benefits to the analysis once the consumer surplus has been correctly calculated. As to reductions in car traffic, our results indicate that the cross-elasticity between car and cycle is low, and hence benefits from traffic reductions will be small. However, the valuations of improved cycling speeds and comfort are so high that it seems likely that improvements for cyclists are cost-effective compared to many other types of investments, without having to invoke second-order, indirect effects. In other words, our results suggest that bicycle should be viewed as a competitive mode of travel and not primarily as a means to achieve improved health or reduced car traffic.

We estimate the value of time savings, different cycling environments and additional benefits in cost-benefit analysis of cycling investments. Cyclists’ value of travel time savings turns out to be high, considerably higher than the value of time savings on alternative modes. Cyclists also value other improvements highly, such as separated bicycle lanes. As to additional benefits of cycling improvements in the form of health and reduced car traffic, our results do not support the notion that these will be a significant part in a cost-benefit analysis. Bicyclists seem to take health largely into account when making their travel choices, implying that it would be double-counting to add total health benefits to the analysis once the consumer surplus has been correctly calculated. As to reductions in car traffic, our results indicate that the cross-elasticity between car and cycle is low, and hence benefits from traffic reductions will be small. However, the valuations of improved cycling speeds and comfort are so high that it seems likely that improvements for cyclists are cost-effective compared to many other types of investments, without having to invoke second-order, indirect effects. In other words, our results suggest that bicycle should be viewed as a competitive mode of travel and not primarily as a means to achieve improved health or reduced car traffic.

This paper presents a study on train passengers? valuation of travel time unreliability (unexpected delays). We also discuss the theoretical underpinning and empirical performance of different ways to measure travel time unreliability, and propose a new way of presenting stated choice questions.

Investments in rail infrastructure are often motivated by the need to reduce travel time and to reduce travel time unreliability. Knowing travellers? valuation of travel time unreliability relative to in-vehicle time and travel cost is hence important for cost-benefit analysis of rail investments, and for choosing the most (socially) efficient timetable. Knowledge of travellers? valuation of delays is also crucial for the possibility of constructing useful incentive contracts between th Swedish Rail Administration and the train operators, and for operators in order to optimise their own operations.

The data source consists of two slightly different stated preference surveys conducted on long-distance trains in Sweden, covering the segments business travellers and private travellers. The first survey was conducted in April-May 2003, in which 402 respondents travelling between Stockholm and Göteborg were recruited and interviewed. 2270 travellers, recruited in different train types operating the rail stretching between Malmö and Stockholm, participated in the second study conducted in May 2006.

Both surveys, the second in particular, were preceded by careful piloting improving the respondent?s ability to interpret the risk of the presented delays. In the second study, a new variation of stated choice questions were tested, where respondents were asked for the ?most preferred improvement? relative to their current trip. Respondents were instructed to pick one out of four improvements varying between the survey questions: frequency of delay, length of delay, cost and compensation as compared to their current trip. Pairwise choices of the standard type were also included in the same survey, in order to test the relative performance of the two methods. The ?most preferred improvement? questions gave satisfying results in line with the pairwise choices. Both results from the survey and focus group studies indicate that the ?most preferred improvement? questions were easier to answer, hence improving the quaility of the results and possibly also the response rate. In particular, the method seemed to improved the respondent?s ability to interpret and value varying levels of frequency of delays, which has proven to be difficult in the pilot studies as well as in several earlier studies (see e.g. Bates et al, 2001).

The standard measure of travel time unreliability in public transit (including long-distance trains, as in this case) is the average lateness of the train. The disutility of the unreliable travel time is then assumed to be proportional to the mean of the delay (compared to the scheduled arrival time). We show, however, that this does not seem to hold; while the disutility seem to be a linear function of the length of the delay (given a certain delay risk level), the disutility depends non-linearly on the risk level. It turns out, as a first result of this study, that valuation of infrequent delays is significantly higher (per minute) than less frequent delays. We also give theoretical evidence why this should be expected (as long as there is some heterogeneity among travellers). This means that studies of the value of an ? average minute of delay? resulting from a study will depend on the risk level(s) assumed in the study, and is hence potentially misleading. We show - using these two studies and examples from the literature - that studies with high risk levels tend to get lower valuations of an ?average minute of delay?. Finally, we show that characterising travel time unreliability with the standard deviation of the travel time has much better explanatory power. This is also supported by theoretical evidence (see also Bates et al., 2001, and Fosgerau and Karlström, 2007).

Finally, the impact different kinds of compensations and information on train passenger?s valuation of unexpected delays were investigated. Preliminary results indicate that compensations and information have a significant effect on traveller?s valuation of unexpected delays, which potentially has important implications for cost-benefit analysis and incentive contracts.

Congestion charges were introduced in Stockholm in 2006, first as a trial followed by a referendum, then permanently from 2007. This paper discusses what conclusions can be drawn from the first five years of operation, until mid-2011. We show that the traffic reduction caused by the charges has increased slightly over time, once external factors are controlled for. Alternative fuel vehicles were exempt from the charges through 2008, and we show that this substantially increased the sales of such vehicles. We discuss public and political acceptability, synthesising recent research and Swedish experience. We conclude that objective and subjective effects on the traffic system, as well as general environmental and political attitudes, formed the basis of the strong public support, while institutional reforms and resolution of power issues were necessary to gain political support. Finally, we briefly discuss implications for the transport planning process in general.

The standard method of estimating the value of travel time variability for use in policy appraisal is to estimate the parameters of a reduced-form utility function, where some measure of travel time variability (such as the standard deviation) is included. A problem with this approach is that the obtained valuation will in general depend on the standardized travel time distribution, and hence cannot be transferred from one context to another. A recently suggested remedy for this problem has been to estimate a scheduling model, which in theory is transferrable, and use the implied reduced-form to derive valuations for use in appraisal. In this paper we estimate both a scheduling model and the implied reduced-form model, using stated choice data. The valuation of travel time variability implied by the scheduling model turns out to be substantially smaller than what is obtained from a reduced-form model estimated on the same sample. The results suggest that the scheduling model does not capture all of the disutility arising from travel time variability. Hence, although it can be shown that scheduling and reduced-form models are theoretically equivalent, that hypothesized equivalence is not reflected in the empirical evidence. We speculate that the derivation of reduced-form models from an underlying scheduling model omits two essential features: first, the notion of an exogenously fixed "preferred arrival time" neglects the fact that most activities can be rescheduled given full information about the travel times in advance, and second, disutility may be derived from uncertainty as such, in the form of anxiety, decisions costs or costs for having contingency plans. We also report our estimates of the valuation of travel time variability for public transit trips, for use in applied appraisal.

The standard method of estimating the value of travel time variability for use in policy appraisal is to estimate the parameters of a reduced-form utility function, where some measure of travel time variability (such as the standard deviation) is included. A problem with this approach is that the obtained valuation will in general depend on the standardized travel time distribution, and hence cannot be transferred from one context to another. A recently suggested remedy of this problem has been to estimate a scheduling model, which in theory is transferrable, and use the implied reduced-form to derive valuations for use in appraisal. In this paper we estimate both a scheduling model and the implied reduced-form model, using stated choice data. The valuation of travel time variability implied by the scheduling model turns out to be substantially smaller than what is obtained from a reduced-form model estimated on the same sample. The results suggest that the scheduling model does not capture all of the disutility arising from travel time variability. Hence, although it can be shown that scheduling and reduced-form models are “theoretically equivalent”, that hypothesized equivalence is not reflected in the empirical evidence. We speculate that the derivation of reduced-form models from an underlying scheduling model omits two essential features: first, the notion of an exogenously fixed “preferred arrival time” neglects the fact that most activities can be rescheduled given full information about the travel times in advance, and second, disutility may be derived from uncertainty as such, in the form of anxiety, decisions costs or costs for having contingency plans. We also report our estimates of the valuation of travel time variability for public transit trips, for use in applied appraisal.

Congestion charges were introduced in Stockholm in 2006, first as a trial followed by a referendum, then permanently from 2007. This paper discusses what conclusions can be drawn from the first five years of operation, until mid-2011. We show that the traffic reduction caused by the charges has increased slightly over time, once external factors are controlled for. Alternative-fuel vehicles were exempt from the charges through 2008, and we show that this substantially increased the sales of such vehicles. We discuss public and political acceptability, synthesizing recent research and Swedish experience. We conclude that objective and subjective effects on the traffic system, as well as general environmental and political attitudes, formed the basis of the strong public support, while institutional reforms and resolution of power issues were necessary to gain political support. Finally, we briefly discuss implications for the transport planning process in general.

Many cities have seen public support for congestion charges increase substantially after charges have been introduced. Several alternative explanations of this phenomenon have been suggested, but so far little evidence has been available to assess the relative importance of these explanations. We study attitudes to congestion pricing in Gothenburg before and after congestion charges were introduced in January 2013. Attitudes to the charges did indeed become more positive after the introduction, just as in previous cities. Using a two-wave postal survey, we separate contributions to the attitude change from a number of sources: benefits and costs being different than anticipated, use of hypothecated revenues, reframing processes, and changes in related attitudes such as attitudes to environment, equity, taxation and pricing measures in general. We conclude that the dominant reason for the attitude change is status quo bias, rather than any substantial changes in beliefs or related attitudes, although some of these factors also contribute. Contrary to a common belief, nothing of the attitude change is due to benefits being larger than anticipated.