Academic papers, specifically. A few have crossed my desk that I think are worth sharing.
This paper, using a field study from King County, finds the correlation between parking use and a 100 different factors including pricing, supply, transit access and more:
The parking utilization data was correlated with the 100 factors. Independent variable relationships were assessed for their predictive powers using linear regression methods. The results showed a clearly evident and statistically relevant variation in land use to multifamily residential parking utilization. A similar relationship existed between multifamily residential parking utilization and transit access. The relationship between the price of parking and parking utilization showed utilization declining as the percentage of parking cost to rent increased. The overall findings indicate that walk and transit access to trip destinations, block size, population and job density influence parking utilization, in some cases by as much as 50 percent. Most important, the research demonstrates that higher supply of parking appears to consistently correlate with greater parking demand. By verifying intuitive perceptions with data and fact, this research provides a new tool for use in considering the proper provision of parking.
Emphasis added. As I’ve said before, simply the existence of parking is the single most important factor in determining whether people will drive or not. So newer, bigger buildings with more parking are less green that smaller, older ones with no parking.
In this paper Michael L Anderson uses econometric models and real life data to show that transit reduces congestion by a much larger amount than previous estimates have shown:
Public transit accounts for only 1% of U.S. passenger miles traveled but nevertheless attracts strong public support. Using a simple choice model, we predict that transit riders are likely to be individuals who commute along routes with the most severe roadway delays. These individuals’ choices thus have very high marginal impacts on congestion. We test this prediction with data from a sudden strike in 2003 by Los Angeles transit workers. Estimating a regression discontinuity design, we find that average highway delay increases 47% when transit service ceases. This effect is consistent with our model’s predictions and many times larger than earlier estimates, which have generally concluded that public transit provides minimal congestion relief. We find that the net benefits of transit systems appear to be much larger than previously believed.
This has always made sense to me, because transit tends to be most highly used to go to and from places that are the most congested.
More below the fold.
Last, this from Sacha Kapoor and Arvind Magesan (pdf) suggests it’s good to inform pedestrians of amount of time before a light changes from green to red, but bad to inform drivers:
Most empirical studies on the role of information in markets analyze policies that reduce asymmetries in the information that market participants possess, often suggesting that the policies improve welfare. We exploit the introduction of pedestrian countdown signals – timers that indicate when traffic lights will change – to evaluate a policy that increases the information that all market participants possess. We find that although countdown signals reduce the number of pedestrians struck by automobiles, they increase the number of collisions between automobiles. We also find that countdown signals caused more collisions overall. The findings imply welfare gains can be attained by revealing the information to pedestrians and hiding it from drivers. We conclude that policies which increase asymmetries in information can improve welfare.
It makes sense, as drivers see the seconds counting down, they speed up to try to make the light.
Let me know in the comments whether you like this post, if so, I’ll do more of these from time to time.