I’m interested in forecasting in the same way I am interested in divination. If planning is really about trying to create future imaginaries and understanding futures, forecasting is its quantitive arm. Today’s entry in the stuff I’ve enjoyed reading this year is about how experts who work with forecasts understand them. Transit New Start project forecasts have improved over time—which makes sense. The more people do, the better we get at it; the more projects we start, the more data on passenger behavior we get.
(People used to get mad at me because I was appalled at the CA HSR cost projections and not the ridership projections, but I stand my ground on that. HSR in CA would be an entirely new service. But we should know full damn well how much it costs to pour concrete in California. Passenger forecasts are extremely hard in my mind, for a lot of reasons that not the fault of either the analysts or the project promoters. That said, the incentive to diddle them is real and there’s a reason for the upward bias.)
This is a neat paper because she’s able to interview at least one person associated with all of the 82 New Start Projects that have been funded. It’s nice to see them all examined in retrospect. I look forward to seeing more of Voulgaris’ ideas here. One thing I’ve really wished for is that planners are not the only people who introduce new services, and I wonder sometimes if the world of market research and social marketing would yield some interesting insights on the field of passenger forecasts in transit and in influencing people to try transit.
Here is the citation and the link. It’s behind a paywall, but if you ask me or the author, I suspect we can find you a copy of it between the two of us.
The forecasts transit agencies submit in support of applications for federal New Starts funding have historically overestimated ridership, as have ridership forecasts for rail projects in several countries and contexts. Forecast accuracy for New Starts projects has improved over time. Understanding the motivations of forecasters to produce accurate or biased forecasts can help forecast users determine whether to trust new forecasts. For this study I interviewed 13 transit professionals who have helped prepare or evaluate applications for federal New Starts funds. This sample includes interviewees who have had varying levels of involvement in all 82 New Starts projects that opened between 1976 and 2016. I recruited interviewees through a snowball sampling method; my interviews focus on the interviewees’ perspectives on how New Starts project evaluation and ridership forecasting has changed over time. Interview results suggest that ridership forecasters’ motivations to produce accurate forecasts may have increased with increased transparency, increased influence on local decision making, and decreased influence on external (federal) funding.
Takeaway for practice: Planners can evaluate the likely trustworthiness of forecasts based on transparency, internal influence, and external influence. If forecast users cannot easily determine a forecast’s key inputs and assumptions, if the forecaster has been tasked with producing a forecast to justify a predetermined action, and if an unfavorable forecast would circumvent decisions by the forecaster’s immediate client, forecasts should viewed with skepticism. Planners should seek to alter conditions that may create these conflicts of interest. Forecasters seem to be willing and able to improve forecast accuracy when the demand for accurate forecasts increases.