Day: 2015-02-17

Rising gas prices might make us safer

| David Levinson

Tim Harlow at the Star Tribune Drive column reports on our research. Rising gas prices might make us safer

Death, prices correlated

Researcher Guangqing Chi of the Department of Sociology and Rural Studies at South Dakota State University looked at the correlation between gas prices and traffic safety. In a study examining crash data in Minnesota from 1998 to 2007, Chi found that a 20-cent drop in gas prices resulted in 15 more fatalities a year. Conversely, he found that a 20-cent increase would bring a decrease of 15 deaths annually.

The study also found that as gas prices rise, the crash rate per million miles traveled dropped in urban and rural areas. It found higher gasoline prices also have significant effects in reducing property damage and injury crashes.

In another study using data from Alabama and Mississippi, Chi found higher gas prices had the biggest effect on teens. With their lower incomes, teens are discouraged from driving by high gas prices and that reduces their crash rate. That makes the roads safer for other drivers, he said.

When fuel prices skyrocketed to more than $4 a gallon in 2008, many drivers drove less frequently and perhaps less aggressively, which reduced their chances of having a crash, the study said.

The bottom line is that when gas prices go up, “we suspect that people drive more carefully,” Chi said.

Read the paper here: Chi, Guangchi, Mohammed Quddus, Arthur Huang and David Levinson (2013) Gasoline Price Effects on Traffic Safety in Urban and Rural Areas: Evidence from Minnesota, 1998–2007. Safety Science 59: pp. 154-162

Stochastic Congestion and Pricing Model with Endogenous Departure Time Selection and Heterogeneous Travelers

| David Levinson

Recently published:

  • Xin, Wuping and David Levinson (2015) Stochastic Congestion and Pricing Model with Endogenous Departure Time Selection and Heterogeneous Travelers. Mathematical Population Studies. Volume 22, Issue 1, 2015, pages 37- 52
    Published online: 11 Feb 2015 [doi] [Paywall, but free copy here] [This is part of a special issue on Risk and Uncertainty in Urban and Transport Economics]

    Abstract: In a stochastic roadway congestion and pricing model, one scheme (omniscient pricing) relies on the full knowledge of each individual journey cost and of early and late penalties of the traveler. A second scheme (observable pricing) is based on observed queuing delays only. Travelers are characterized by late-acceptance levels. The effects of various late-acceptance levels on congestion patterns with and without pricing are compared through simulations. The omniscient pricing scheme is most effective in suppressing the congestion at peak hours and in distributing travel demands over a longer time horizon. Heterogeneity of travelers reduces congestion when pricing is imposed, and congestion pricing becomes more effective when cost structures are diversified rather than identical. Omniscient pricing better reduces the expected total social cost; however, more travelers improve welfare individually with observable pricing. The benefits of a pricing scheme depend on travelers’ cost structures and on the proportion of late-tolerant, late-averse, and late-neutral travelers in the population.

    Keywords: commute, congestion pricing, omniscient and observable pricing schemes, road pricing, second-best pricing, social cost and individual welfare, stochastic network equilibrium, traveler departure patterns

(Personal note. This paper was first submitted in 2005. Revised and accepted in 2007, and published in 2015. Sadly this tops my previous record for the longest a paper has taken, which had gone to Ramp Metering and Freeway Bottleneck Capacity at 7 years.  My thanks to my co-author for his infinite patience. However, this is theory, rather than empirical, and so we have not been trumped by other research.)