Sources of Errors and Biases in Traffic Forecasts for Toll Road Concessions

The objective of this thesis is to study the sources of discrepancy between the actual traffic in motorways under concession schemes and the traffic forecast ex-ante. The demand forecast for a specific project is the main variable influencing its realization. From a public sector perspective, socio-economic evaluations are driven by demand forecasts, which gives the basis for choose and hierarchy public projects in order to maximise social welfare. From a private sector perspective, traffic forecasts are the base of financial evaluation and toll setting.Despite its importance and the numerous and important developments in the field, the differences of forecast and ex-post traffic are usually very high. Some recent studies show that differences as big as 20% are much more the rule than the exception.A huge amount of uncertainty is associated with the forecasting exercise. First because transport is a derived demand and depends on many exogenous variables, also uncertain; because modelling is and simplification exercise, implies many assumptions and rely on field data, many times incomplete or of low quality; moreover, modelling human (in this case users) behaviour is always a dangerous enterprise.Although these arguments could explain at least the larger part of errors associated with forecasts, one can wonder whether the agents implicated in the forecast would or could use this uncertainty strategically in their favour. In a competition for the field scheme (bids), the bidder may overestimate the demand in order to reduce the toll included in the bid. This strategic behaviour can introduce a high bias in forecasts. Also, overoptimistic (or overpessimistic) forecasters may introduce a bias in the forecast.We propose to focus in turn on the three main groups of agents involved in the demand forecast process. The forecasters, the project promoters and the users. Study all the issues related to them would be a too ambitious (or more concretely impossible) task. We then focus on some particular issues related to the modelling of the actors' behaviour in the context of the demand forecast for toll roads.Regarding the forecaster behaviour, we present the results of the first large sample survey on forecasters' perceptions and opinions about forecasting demand for transport projects, based on an on-line survey. We first describe the main characteristics of forecasters. We then describe the last forecast forecasters prepared. We turn to the models forecasters apply, the errors they declare on past forecasts and the main sources of errors according to them. We then describe the forecast environment in terms of pressure forecasters receive. These unique results provide a picture of the world of forecasters and forecasts, allowing for a better understanding of them. We turn then to the study of the optimism and overconfidence in transport forecasts. Optimism and overconfidence in general are recognized human traits. We analyze the overoptimistic bias by comparing the distribution of stated errors with actual errors found in literature; we also compare the own skilful of subjects in doing forecasts with studies showing self-evaluations of a common skill - driving. We finally propose a regression of the competence, quality and errors on the main forecasters' and projects' specific variables.Results show that the distribution of errors transport forecasters state has a smaller average magnitude and a smaller variance than those found in literature. Comparing forecasters perception of their own competence with the results found in literature about drivers skill self-evaluation, however, we could not find a significant difference, meaning that the forecasters' overconfidence is in line with what could be viewed as a normal human overconfidence level.The pressure for results forecasters receive and the strategic manipulation they affirm exist merit a special attention. They imply that while forecasters' behavioural biases may exist and should be take in account when evaluation forecasts, the project promoter may influence forecasts by pressuring the forecasters to produce results which better fit his expectancies.We then study the bidders' strategic behaviour in auctions for road concessions. We address three questions in turn. First, we investigate the overall effects of the winner's curse on bidding behaviour in such auctions. Second, we examine the effects of the winner's curse on contract auctions with differing levels of common-value components. Third, we investigate how the winner's curse affects bidding behaviour in such auctions when we account for the possibility for bidders to renegotiate. Using a unique, self-constructed, dataset of 49 worldwide road concessions, we show that the winner's curse effect is particularly strong in toll road concession contract auctions. Thus, we show that bidders bid less aggressively in toll road concession auctions when they expect more competition. We observe that this winner's curse effect is even larger for projects where the common uncertainty is greater. Moreover, we show that the winner's curse effect is weaker when the likelihood of renegotiation is higher. While the traditional implication would be that more competition is not always desirable when the winner's curse is particularly strong, we show that, in toll road concession contract auctions, more competition may be always desirable. Modelling aggregated users' behaviour, we study the long term traffic maturity. We argue that traffic maturity results from decreasing marginal utility of transport. The elasticity of individual mobility with respect to the revenue decreases after a certain level of mobility is reached. In order to find evidences of decreasing elasticity we analyse a cross-section time-series sample including 40 French motorways' sections. This analysis shows that decreasing elasticity can be observed in the long term. We then propose a decreasing function for the traffic elasticity with respect to the economic growth, which depends on the traffic level on the road. Although “unconditional” decreasing elasticities were already proposed in the literature, this is the first work, as far as we know, putting this idea in evidence and giving it a functional form. This model provides better interpretation of the coupling between traffic and economic growth, and a better long-term forecast. From the disaggregate perspective, we study the main individual modal choice variable, the value of time. The value of travel time savings is a fundamental concept in transport economics and its size strongly affects the socio-economic evaluation of transport schemes. Financial assessment of tolled roads rely upon the value of time as the main (or even the unique) willingness to pay measure. Values of time estimates, which primarily represent behavioural values, as then increasingly been used as measures of out-of-pocket money. In this setting, one of the main issues regarding the value of time is its distribution over the population. We apply the Logit, the Mixed Logit and the Bayesian Mixed Logit models to estimate the value of time in freight transport in France. Estimations with mixed logit faced many difficulties, as expected. These difficulties could be avoided using the Bayesian procedures, providing also the opportunity of properly integrating a priori beliefs. Results show that 1) using a single constant value of time, representative of an average, can lead to demand overestimation, 2) the estimated average value of time of freight transport in France is about 45 Euro, depending on the load/empty and hire/own account variables, which implies that 3) the standard value recommended in France should be reviewed upwards.