Congestion, risk aversion and the value of information

Information about traffic conditions is conveyed to drivers by radio and variable message signs, and more recently available via the Internet and Advanced Traveler Information Systems (ATIS). This has spurred research on how travelers respond to information, how much they are likely to benefit from it and how much they are willing to pay for it. We analyze the decisions of drivers whether to acquire information and which route to take on a simple congested road network. Four information regimes are considered: No information, Free information which is publicly available at no cost, Costly information which is publicly available for a fee, and Private information which is available free to a single individual. We find that Private information is individually more valuable than either Free or Costly information, while the benefits from Free and Costly information cannot be ranked in general. We also find that Free or Costly information can decrease the expected utility of drivers who are sufficiently risk-averse.

Risk aversion, the value of information and traffic equilibrium

Information about traffic conditions has traditionally been conveyed to drivers by radio and variable message signs, and more recently via the Internet and Advanced Traveler Information Systems. This has spurred research on how travelers respond to information, how much they are willing to pay for it and how much they are likely to benefit from it collectively. In this paper we analyze the decisions of drivers whether to acquire information and which route to take on a simple congested road network. Drivers vary in their degree of risk aversion with respect to travel time. Four information regimes are considered: No information, Free information which is publicly available at no cost, Costly information which is publicly available for a fee, and Private information which is available free to a single individual. Private information is shown to be individually more valuable than either Free or Costly information, while the benefits from Free and Costly information cannot be ranked in general. Free or Costly information can decrease the expected utility of drivers who are very risk-averse, and with sufficient risk aversion in the population the aggregate compensating variation for information can be negative.Transportation, route choice, information provision, expected utility, congestion

Risk aversion, the value of information and traffic equilibrium

Information about traffic conditions has traditionally been conveyed to drivers by radio and variable message signs, and more recently via the Internet and Advanced Traveler Information Systems. This has spurred research on how travelers respond to information, how much they are willing to pay for it and how much they are likely to benefit from it collectively. In this paper we analyze the decisions of drivers whether to acquire information and which route to take on a simple congested road network. Drivers vary in their degree of risk aversion with respect to travel time. Four information regimes are considered: No information, Free information which is publicly available at no cost, Costly information which is publicly available for a fee, and Private information which is available free to a single individual. Private information is shown to be individually more valuable than either Free or Costly information, while the benefits from Free and Costly information cannot be ranked in general. Free or Costly information can decrease the expected utility of drivers who are very risk-averse, and with sufficient risk aversion in the population the aggregate compensating variation for information can be negative

Network Data

Many economic activities are embedded in networks: sets of agents and the (often) rivalrous relationships connecting them to one another. Input sourcing by firms, interbank lending, scientific research, and job search are four examples, among many, of networked economic activities. Motivated by the premise that networks' structures are consequential, this chapter describes econometric methods for analyzing them. I emphasize (i) dyadic regression analysis incorporating unobserved agent-specific heterogeneity and supporting causal inference, (ii) techniques for estimating, and conducting inference on, summary network parameters (e.g., the degree distribution or transitivity index); and (iii) empirical models of strategic network formation admitting interdependencies in preferences. Current research challenges and open questions are also discussed

Trip-timing decisions and congestion with household scheduling preferences

Most traffic congestion models assume that agents make trip-timing decisions independently and receive payoffs at the origin and destination that do not depend on whether other agents are present. We depart from this paradigm by considering a variant of Vickrey's bottleneck model of the morning commute in which individuals live as couples and value time at home more when together than when alone. We show that the costs of congestion can be higher than for a comparable population of individuals living alone. The costs can be even higher if spouses collaborate with each other when choosing their departure times. To calibrate the model we estimate trip-timing preferences for married and unmarried men and women in the Greater Paris region. Jel Classifications: D11, D70, R41