JS sends an email, as he sometimes does:
The California High Speed Rail Authority (CHSRA), hired some highly qualified transportation experts to analyze their ridership and revenue projections. From what I can tell the experts determined that the original ridership and revenue model used many state of the art techniques, but did not use all the methods the reviewing experts have heard of so they need to do more projecting. In going through the projections they came up with some interesting points about bias due to using stated preference versus revealed preference and a lot of advice on how to improve the accuracy of the projections. (The Report)
Even though all of the recommendation seem reasonable in making the model more accurate, it seems to me to be much about scientism. The the model projects all modes; however, the most import for determining revenue and ridership is the High Speed Rail (HSR) component. This mode has no possibility of revealed preference data in the US much less California. So the question is for both the CHSRA modelers and model reviewers: "Where is the uncertainty?" I see a presumption that there is an answer, instead of range of possible outcomes.
Many travel models that populate the Metropolitan Planning Organizations across the US show traffic doubling from Today's levels by 2035, but from May 2001 to May 2011 the trend has only shown a 0.8% annual rate of increase. (Travel Trends Report FHWA) A rate approximately one quarter of what was projected. These car and truck models have virtually all the historical data that economtrican could want but still has huge uncertainties. In fact the auto share of the market is an integral part of the HSR model. Shouldn't the uncertainty be as or more paramount than the accuracy. With the higher uncertainty should come the naturally higher return on the $40 to $120 Billion investment. I predict little if any of the uncertainty will be addressed in the next CHSRA business plan.