It is Time to Admit the Purple Line Was a Mistake

The Path the Purple Line Will Take – Before and The View At Rock Creek Now

A.  Introduction

The proposed Purple Line, a 16-mile light-rail line passing in an arc across parts of suburban Maryland around Washington, DC, has become a fiasco.  The State of Maryland, under Republican Governor Larry Hogan, is preparing to sign a new contract with the private concessionaire that will pay that concessionaire $3.7 billion more than had been agreed to under the existing contract.  The total cost of that contract alone (there are significant other costs on top) will now be $9.3 billion (66% more than the $5.6 billion set in the earlier contract), and the opening will be delayed by at least a further 4 1/2 years (thus doubling the originally contracted construction period – now to a total of 9 years).  And the governor is doing this with no legislative approval being sought.

The Purple Line has long been controversial – due to its high cost, the disruption it is causing to a number of suburban neighborhoods, the destruction of parkland it has been routed through, and its use of scarce resources for public transit to benefit a privileged few rather than the broader community.  There are alternatives that would not only be far more cost-efficient but also less environmentally destructive.  The project illustrates well why the US has such poor public transit and poor public infrastructure more generally, as scarce resources are channeled into politically-driven white elephant projects such as this.

In response to the announcement of the terms of the revised contract with the concessionaire, I submitted to the Washington Post a short column for its “Local Opinions” section.  They have, however, declined to publish it.  This is not terribly surprising, as the Washington Post Editorial Board has long been a strong proponent of the Purple Line, with numerous editorials pushing strongly for it to go forward.  And while the Post claims that it supports an active debate on such issues, the guest opinion columns it has published, as well as letters-to-the-editor, have been very heavily weighted in number to those with a similar view as that of its Editorial Board.

I am therefore posting that column here.  It has been slightly edited to reflect developments since it was first drafted, but has been kept in style to that of an opinion column.

Opinion columns must also be short, with the Post setting a tight word limit.  That means important related issues can not be addressed due to the limited space.  But with room here, I can address several of them below.  Finally, I will discuss the calculations behind two of the statements made in the column, as a “fact check” backing up the assertions made.  These should themselves be of interest to those interested in the Purple Line project (and in public transit more broadly), as they illustrate factors that should be taken into account when assessing a project such as this.

B.  The Column Submitted to the Washington Post

This is the column submitted to the Post, with some minor changes to reflect developments since it was first drafted:

               It is Time to Admit the Purple Line was a Mistake

Governor Hogan has re-negotiated the contract with the private concessionaire that will build and operate the 16-mile long Purple Line through suburban Maryland.  The Board of Public Works has approved it, and despite an extra $3.7 billion that will be spent the Maryland legislature will have no vote.  The private concessionaire will now be paid $9.3 billion, a 66% increase over the $5.6 billion cost in the original contract.  And this is just for the contract with the concessionaire.  The total cost, including contracts with others (such as for design and engineering work) as well as direct costs at the Maryland Department of Transportation (MDOT), is likely well over $10 billion.

The amount to be paid to the concessionaire for the construction alone will rise to $3.4 billion from the earlier $2.0 billion, an increase of 70%.  And even though the construction is purportedly halfway complete (with $1.1 billion already spent), the remaining amount ($2.3 billion) is larger than the original total was supposed to be.  And the amount being paid to the private contractors for the construction will in fact be even higher, at $3.9 billion, once one includes the $219 million MDOT has paid directly to the subcontractors in the period since the primary construction contractor withdrew, and the $250 million paid to that primary contractor in settlement for the additional construction expenses it incurred.  That $3.9 billion is close to double the $2.0 billion provided for in the original contract.  In addition, the project under the new contract will require an extra 4 1/2 years (at least) before it is operational, doubling the time set in the original contract to 9 years.  Even though the project is purportedly halfway built, the remaining time required will equal the time that was supposed to have been required under the original plan for the entire project.

The critics were right.  They said it would cost more and take longer than what Maryland asserted (and with supposedly no risk to the state due to the “innovative” contract).  It also shows that it is silly to blame the opponents of the project.  The lawsuit delayed the start of construction by less than 9 months.  That cannot account for a delay of 4 1/2 years.  Furthermore, the state had the opportunity during those 9 months to better prepare the project, acquire the land required, and finalize the engineering and design work.  Construction should then have been able to proceed more smoothly.  It did not.  It also shows that Judge Leon was right when he ruled that the project had not met the legal requirements for being adequately prepared.

Even the state’s own assessment recognized that such a rail line was marginal at best at the costs originally forecast.  With the now far higher costs, no unbiased observer can deny that the project is a bad use of funds.  The only possible question is whether, with what has already been spent, the state should push on.  But so far only $1.1 billion has been spent on the construction, plus the state agreed to pay the former construction company the extra $250 million when it quit the project.  Thus close to $8 billion (plus what the state is spending outside of the contract with the concessionaire) would be saved by stopping now.

There are far better uses for those funds.  A top priority should be to support public transit in Montgomery and Prince George’s countries.  Even at the originally contracted cost for the Purple Line there would have been sufficient funds not only to double capacity on the county-run bus systems (doubling the routes or doubling the frequency on the routes or some combination), but also to end charging any fares on those buses.  Those bus systems also cover the entire counties, not simply a narrow 16-mile long corridor serving some of the richest zip codes in the nation.  In particular, better service could be provided to the southern half of Prince George’s, the location of some of the poorer communities in the DC area and where an end to bus fares would be of particular benefit.

Covid-19 has also now shown the foolishness of spending such sums on new fixed rail lines.  DC area Metro ridership is still 80% below where it was in 2019.   Rail lines are inflexible and cannot be moved, and in its contract the state will pay the concessionaire the same even if no riders show up.  Who knows what will happen to ridership in the 35 years of this contract?  In contrast, bus routes and frequency of service have the flexibility to be adjusted based on whatever develops.

It is time to cut our losses.  Acknowledge it was a mistake, don’t sign the revised contract, and use the funds saved to provide decent public transit services to all of our residents.

C.  Additional issues

a)  The Cost of Not Keeping the Original Construction Contractor

Media coverage of the proposed new contract has focussed on the overall $9.3 billion cost (understandably), as well as the cost of the construction portion alone.  The figure used for that construction cost has been $3.4 billion, a 70% increase over the originally contracted $2.0 billion cost.

But as noted in the column I drafted above, that $3.4 billion excludes what MDOT has paid directly to the subcontractors who have continued to work on the project since September 2020 (under the direct supervision of MDOT) after the original primary contractor (Fluor, a global corporation with projects on six continents) exited.  According to a report by MDOT in January 2022, $219 million was paid directly by MDOT for this work, and this will be in addition to the $3.4 billion to be paid to the concessionaire.  One should also add in the $250 million Maryland has agreed to pay the original primary contractor in the settlement for its claims that it incurred an additional $800 million in construction expenses on the project – expenses that were the fault of the state from an inadequately prepared project.  That $250 million was for construction costs incurred, and should be included as part of the overall construction costs that MDOT is paying the concessionaire.  The total to be paid for the construction (if there are no further cost increases, which based on the experience so far cannot be guaranteed) is thus in fact $3.9 billion.  This is close to double the original contracted cost of $2.0 billion.

This also raises another issue, which remarkably does not appear to have been discussed (from all that I have read).  The original contractor in 2020 had requested an additional $800 million in compensation for extra costs incurred in the project that it argued were the fault of the state.  One can debate whether this was warranted and whether it was the fault of the state or the contractor, but the amount claimed was $800 million.  Thus, had the state agreed, the total cost would then have been $2.8 billion, up from the originally contracted $2.0 billion.  The state rejected this, however, and then congratulated itself for bargaining the $800 million down to “only” $250 million.

But now we see that the overall amount to be paid the private firms building the rail line will be $3.9 billion.  Fluor was evidently right (even conservative) in its claim that building the project will cost more.  But the $3.9 billion it will now cost is $1.1 billion more than the $2.8 billion they would have paid had the state agreed to cover the $800 million (which probably could have been bargained down some as well).  This hardly looks like smart negotiating by Governor Hogan and his state officials.

Put another way, state officials refused to pay an extra $800 million for the project, insisting that that cost was too high.  They then negotiated a contract where instead of paying $800 million more they will pay $1.9 billion more – for the same work.  And then they sought praise for negotiating a new agreement where they will pay “only” an extra $1.9 billion.

Furthermore, the re-negotiated contract will not only pay $1.9 billion more for the construction, but also higher amounts for the subsequent 30 years when the concessionaire will operate and maintain the line.  Maryland had agreed to pay a total of $2.3 billion for this over the 30 years in the original 2016 contract, but in the re-negotiated contract will now pay $2.6 billion, an increase of $300 million.  Governor Hogan had earlier asserted that under its “innovative” PPP contract, the state would not have to cover any cost increases for the rail line operations over those 30 years – but now it does.  In addition, due to the now far higher construction costs and the proportionately much higher share of those costs that will be funded by borrowing (as the up-front grants to be provided will be largely the same – $1.36 billion will now be provided, vs. $1.25 billion before), the total financing costs over the life of the contract will now be $2.8 billion versus $1.3 billion before, an increase of $1.5 billion.  Thus the total contract will now cost $9.3 billion versus $5.6 billion before, an increase of $3.7 billion (which equals the $1.9 billion on construction + $0.3 billion on operations + $1.5 billion on financing).

It is difficult to see how there is any way this can be interpreted as smart negotiating.

b)  Don’t Blame the Lawsuit for the Problems

The politicians responsible for the Purple Line, starting with Governor Hogan, blame the lawsuit brought by opponents of the Purple Line for all the problems that followed.  This is simply wrong, and indeed silly.  The ruling by Judge Richard Leon delayed the start of construction by less than 9 months.  This cannot account for a delay that will now be at least 4 1/2 years (assuming no further delays).  Nor can it account for a project cost that is now $3.7 billion higher.

Judge Leon ruled in August 2016 that the State of Maryland had not fulfilled the legal conditions required for a properly prepared project.  The primary issue was whether a project such as this, with the unavoidable harm to the environment that a new rail line will have, is necessary to provide the transit services needed in the corridor.  Could there be other options that would provide the services desired with less harm to the environment?  If so, the law requires that they be considered.  The answer depends critically on the level of ridership that should be expected, and the State of Maryland argued that only a rail line would be able to handle the high ridership load they forecast.  Many of the Purple Line riders would be transferring from and to the DC Metrorail lines it would intersect, and the State of Maryland claimed that the DC Metrorail system (just Metro, for short) would see a steady rise in ridership over the years and thus serve as a primary draw for Purple Line riders.

Judge Leon observed that in fact Metro ridership had been declining in the years leading up this case (2016), and ruled that Maryland should look at this issue and determine whether, based on what was then known, a less environmentally destructive alternative to the Purple Line might in fact be possible.  If Maryland had complied with this ruling, they could have undertaken such a study and completed it within just a few months.  There would have been little surprise if such a study, under their own control, would have concluded that the Purple Line was still warranted.  The judge would have accepted this, and they could then have proceeded, with little to no delay.  Construction had only been scheduled to begin in October 2016.

Instead, the State filed numerous motions to reverse the ruling and to be allowed to proceed with no examination of their ridership assumptions.  They argued in those motions that there would be a steady rise in Metro ridership over time, and that by the year the Purple Line would open (then expected to be in 2022) Metro ridership would have been growing at a steady pace for years, which would then continue thereafter.  When Judge Leon declined to reverse his ruling, the State appealed and then won at the Appeals Court level.  The judges in the Appeals Court decided that the judicial branch should defer to the executive branch on this issue.  Construction then began in August 2017.  The Purple Line contractors said that they were delayed by 266 days ( = 8.7 months) as a result of Judge Leon’s ruling.

We now know that Judge Leon was in fact right in raising this concern with the prospects for Metro ridership.  Ridership on the system had in fact been falling for a number of years leading up to 2016, and it has continued to fall since then.  Metro ridership peaked in 2008, fell more or less steadily through 2016, and then continued to fall.  Ridership in 2016 was 14% below where it had reached in 2008 (despite the Silver Line opening with four new stations in 2015), and then was even less than 2016 levels in 2019.  And all this was pre-Covid.  Metrorail ridership then completely collapsed with the onset of Covid, with ridership in 2020 at 72% below where it was in 2019 and in 2021 at 79% below where it was in 2019.

Judge Leon was right.  Even setting aside the collapse in ridership with the onset of Covid, Metro ridership declined significantly and more or less steadily for more than a decade.  It was not safe to assume (as the state insisted in its court filings would be safe to assume) that Metro ridership would resume its pre-2008 upward climb.  And now we have seen not only the collapse in Metro ridership following from Covid, but also the near certainty that it will never fully recover due to the work-from-home arrangements that became common during the Covid crisis and are now expected to continue at some level.

In addition and importantly, while the Purple Line contractor noted that the judicial ruling delayed the start of construction by 266 days, this does not mean project completion should have been delayed by as much.  As Maryland state officials themselves noted, while the ruling meant construction could not start, the state could (and did) continue with necessary preparatory work, including final design work, acquisition of land parcels that would be needed along the right of way, and the securing of the necessary clearances and permits that are required for any construction project.  The state was responsible for each of these.  With the extra 9 months they should have been able to make good progress on each, and with this then ensure that the project could proceed smoothly and indeed at a faster pace once they began.

This turned out not to be the case.  Despite the extra 9 months to prepare, the Purple Line contractors cited each of these as major problems causing delays and higher costs.  Final designs were not ready on time or there had to be redesigns (as for a crash wall that has to be built for the portion of the Purple Line that will run parallel to CSX train tracks); state permits were delayed and/or required significant new expenditures (such as for the handling of water run-off); and the state was late in acquiring “nearly every” right of way land parcel required (there were more than 600) – and “by more than two years in some cases”.

An extra 9 months for preparation should have led to fewer such issues.  That they still were there, despite the extra 9 months, makes one wonder what the conditions would have been had they started construction 9 months earlier.  The extra time to prepare the project – where these were later revealed still to be major problems – likely saved the project money compared to what would have been the case had they started construction earlier.  It simply makes no sense now to blame that extra 9 months for the difficulties when they in fact had an extra 9 months to work on them.

c)  Diversion of MARC Revenues to Get Around Maryland’s Public Debt Limits

Under the Purple Line contract, the State of Maryland will be obliged to pay the concessionaire certain set amounts over 35 years, starting with a payment of $100 million when operations start (in a planned 4 1/2 years from now), but especially then for the following 30 years when the concessionaire will operate the line.  The state will be obliged to make those payments for those 30 years on the sole condition that the rail line is available to be operated (i.e. is in working order).  Hence those payments are called “availability payments”.  The payments will be the same regardless of ridership levels.  Indeed, they will have to be made (and in the same amount) even if no riders show up.  A major share of the availability payments will be made up of what will be required to cover the principal and interest on the loans that the concessionaire will be taking out to finance the construction of the project, with the repayment then by the state through the availability payments.  The concessionaire is in essence borrowing on behalf of the state, and the loans will then be repaid by the state via the concessionaire.

These long-term budget obligations are similar to the obligations incurred when the state borrows funds via a bond being issued.  Indeed, this can hardly be disputed for the borrowing being done by the concessionaire to finance the construction, with the state then repaying this through the availability payments.  it is also, at 35 years, a longer-term financial obligation than any bond Maryland has ever issued.  Governor Hogan will be tying the hands of future governors for a very long time, as failure to repay on the terms he negotiated would be an event of default.

Due to concerns of excessive government borrowing undermining finances, many states have set limits on the amount they can borrow.  In Maryland, the state has set two “capital debt affordability ratios”, which limit outstanding, tax-supported, state debt to less than 4% of Maryland personal income and the debt service that will be due on this debt to less than 8% of state tax and other revenues.

If the 35-year long Purple Line obligations were treated as state debt, then there could be a problem of Maryland running close to, and possibly exceeding, these debt affordability ratios.  This is discussed in further detail in an annex at the end of this blog post, with illustrative calculations.  Exceeding those limits would be a significant issue for the state, and might conceivably put it in violation of conditions written into the contracts for its outstanding state bonds.  To avoid this, or even if the Purple Line obligations would bring it closer to but not over those limits, Maryland would need to limit its public sector borrowing, postponing other projects and programs due to the limited borrowing space that the Purple Line has used up.

The issue is not new.  It already arose in the contract signed in 2016.  But it will be even more important now due to the higher cost of the concession  – $9.3 billion to be paid to the concessionaire vs. $5.6 billion before.

Lawyers can debate whether the payment obligations (or a portion of them, e.g. the portion directly tied to the debt incurred by the concessionaire on behalf of the state) should or should not be included in the state’s capital debt affordability ratios.  But to forestall such a debate, MDOT has chosen to create a special trust account from which all payments for the Purple Line would be made.  That trust would be funded by Purple Line fare revenues (whatever they are) and grant funds received for the project (primarily from federal sources).  But MDOT acknowledges that such funding would not suffice for the financial obligations being incurred for the Purple Line, at least for some time.  And if direct support to cover this was then provided from the Maryland state budget, where revenues come primarily from taxes, the Purple Line obligations would be seen as tax-supported debt and hence subject to the borrowing limits set by the capital debt affordability ratios.

So instead of openly providing funding directly from the state budget, they will channel fare revenues collected on MARC (the state-owned commuter rail system) in the amounts necessary to cover the payment obligations on the Purple Line.  But MARC does not run a surplus.  Like other commuter rail lines it runs a deficit.  Each dollar in MARC fares channeled to cover Purple Line payment obligations thus will increase that MARC deficit by a dollar.  But then, for reasons that make little sense to an economist but which a lawyer might appreciate, those higher MARC deficits can be covered by increased funding from the state budget without this impacting the state’s capital affordability limits.  The identical payments if sent directly to cover the Purple Line obligations, however, would be counted against those ratios.

But this is just a shell game.  The funding to cover the Purple Line payment obligations are ultimately coming from the state budget, and routing it via MARC transfers simply serves to allow the state to bypass the capital debt affordability limits.  It also reduces transparency on how the Purple Line costs are being covered.

Nor are the agencies that assign ratings to Maryland state bonds being fooled by this.  S&P, for example, noted specifically that it will take into account the payment obligations on the Purple Line when they compute for themselves what the capital debt affordability ratios in fact are.

d)  Role (or Lack of It) of the State Legislature

Under the new contract Governor Hogan and his administration have negotiated, a total of $9.3 billion will be paid to the concessionaire, or $3.7 billion more than the $5.6 billion that was to be paid under the original contract.  The state legislature will apparently have no say in this.  While it will bind future administrations to make specified payments over a 35 year period, with payments that must be made regardless of ridership or any factor the state has control over (the rail line needs merely to be “available”), the only recognized check on this is apparently a vote in the Board of Public Works.  But there are only three members on this Board, only two votes are required for approval, and the governor has one of those two votes.  The legislature has no role.

I find this astonishing.  The state legislature is supposed to set the budget, but no vote will be taken on whether the further $3.7 billion should be spent.  Indeed, it appears the legislature would have no role regardless of how much the current governor is binding his successors to pay (Governor Hogan will be long out of office when the payments are due), nor for how long.  Suppose it was twice as much, or ten times as much, or whatever.  And while this commitment will be for 35 years to 2056 (five years past what was in the original contract), it appears the same would apply if the revised contract were extended to 50 years, or 100 years, or whatever.  Under the current rules, it appears that the legislature has accepted that the governor can commit future administrations to pay whatever he decides and for as long as he decides, with just the approval of the Board of Public Works.

This is apparently a consequence of the state law passed in 2013 establishing the process to be followed for state projects that would be pursued via a Public-Private Partnership (PPP) approach.  The Purple Line is the first state project being pursued on the basis of that 2013 legislation, with the legislature approving also in 2013 the start of the process on the Purple Line.  This legislative approval was provided on the basis of cost estimates provided to it at the time.  MDOT then issued a Request for Qualifications in November 2013 to identify interested bidders, a Request for Proposals in July 2014, and received proposals from four bidders in November and December 2015.  Following review and final negotiations, MDOT announced the winning bidder on March 1, 2016.  Only then did they know what the cost (under that winning bid) would be, and the state legislature was given 30 days to review the draft contract (of close to 900 pages) during which time they could vote not to approve.  But no vote taken would be deemed approval.  Then, with just the approval of the Board of Public Works as well (received in early April 2016), MDOT could sign the contracts on behalf of Maryland.

However, there will be no such review by the legislature of any amendments to that contract.  Amendments apparently require nothing more than the approval of the Board of Public Works, and with that sole approval, the governor is apparently empowered to commit future administrations to pay whatever amount he deems appropriate, for as many years as he deems appropriate.  The increase in the future payment obligations in this case will be $3.7 billion, but apparently it could be any amount whatsoever, with just the approval of the Board of Public Works.

Based on this experience, one would think that the legislature would at a minimum hold public hearings to examine what went wrong with the Purple Line, and what needs to be done to ensure the legislature retains control of the state budget.  The current legislation apparently gives the governor close to a blank check (requiring only the approval of the Board of Public Works) to obligate future administrations to pay whatever amount he sees fit, for as many years as he sees fit.

Central also to any legislative review of a proposed expenditure is whether that expenditure is warranted as a good use of scarce public resources.  One can debate whether the Purple Line was warranted at the initial cost estimates.  As will be discussed below, at those initially forecast costs even the state’s own analysis indicated it was at best marginal (and inferior to alternatives).  But even if warranted at the then forecast costs, it does not mean the project makes sense at any cost.  Based on what we now know will be a far higher cost, no unbiased person can claim that the Purple Line is still (if it ever was ) a good use of public resources.

Yet remarkably, it does not appear that any assessment was done by any office in Maryland government of whether this project is justified at the now much higher costs.  The issue simply did not enter into the discussion – at least in any discussion that has been made public.  Rather, at the Board of Public Works meeting on the project, Governor Hogan praised MDOT staff for continuing to push the project forward despite the problems.  Indeed, the higher the increase in cost for the project, the more difficult it would be to proceed, and hence the more the staff should be commended (in that view) for nevertheless succeeding in pushing the project through.  This is perverse.

Legislative review is supposed to look at such issues and to set overall budget priorities.  Yet under the PPP law passed in 2013, the legislature apparently has no role to review and consider whether an amended expenditure on such a project is a good use of the budget resources available.

D.  Fact Checks

a)  The Lack of Economic Justification for the Purple Line

The column includes the statement:

Even the state’s own assessment recognized that such a rail line was marginal at best at the costs then envisaged.  With the now far higher costs, no unbiased observer can deny that the project is far from justified.

This statement is based on the results of the state’s analysis reported in the Alternatives Analysis / Draft Environmental Impact Statement, released in September 2008.  The Alternatives Analysis looked at seven options to provide improved public transit services in the Purple Line corridor – an upgrading of existing bus services (labeled TSM for Transportation System Management), three bus rapid transit options (low medium, and high), and three light rail options (low, medium, and high).  All would provide improved public transit services in the corridor.  The question is which one would be best.

The summary results from the analysis are provided in Chapter 6, and the primary measure of whether the investment would be worthwhile is the “FTA cost-effectiveness measure” – see tables 6-2 and 6-3.  The Federal Transit Administration (FTA) cost-effectiveness measure is calculated as the ratio of the extra costs of the given option (extra relative to what the costs would be under the TSM option, and with both annualized capital costs and annual operational and maintenance costs), to the extra annual hours of user benefits of that option relative to the TSM option.  That is, it is a ratio of two differences – the difference in costs (relative to TSM) as a ratio to the difference in benefits (again relative to TSM).  Thus it is a ratio of costs to benefits, and a higher number is worse.  Hours of user benefits are an estimate of the number of hours saved by riders if the given transit option is available, where they mark up those hours saved by a notional factor to account for what they say would be a more pleasant ride on a light rail line (which biases the results in favor of a rail line but, as we will see, not by enough even with this).

The FTA issues guidelines classifying projects by their cost-effectiveness ratios.  For FY2008 (the relevant year for the September 2008 Alternatives Analysis), the breakpoints for those costs were (see Table II-2 in Appendix B of the FTA’s FY2008 Annual Report on Funding Recommendations):

High (meaning best) $11.49 and under
Medium-High $11.50 – $14.99
Medium $15.00 – $22.99
Medium-Low $23.00 – $28.99
Low (meaning worst) $29.00 and over

The Alternatives Analysis estimated that the Medium Light Rail Line option would have a cost-effectiveness ratio of $22.82.  This would place it in the Medium category for the FTA cost-effectiveness measures, but just barely.  This was important, as the FTA will very rarely consider for federal grant funding a project in its Medium-Low category, and never in the Low category.

The other two light rail options examined had worse cost-effectiveness ratios ($26.51 and $23.71 for the Low and High options respectively) that would have placed them in FTA’s Medium-Low cost-effectiveness category, and thus highly unlikely to be accepted by the FTA for funding.  Not surprisingly, the Governor of Maryland (O’Malley at the time) selected the Medium Light Rail option as the state’s preferred option, as the other two light rail options would likely have been immediately rejected, while the Medium Light Rail choice would have been within the acceptable limits – although just barely so.  And while in principle they chose the Medium Light Rail option, they then added features (and costs) to it that brought it closer to what had been the High Light Rail Option, while not re-doing the cost-effectiveness analysis.

Maryland should also have considered any of the three Bus Rapid Transit options, as their cost-effectiveness measures were uniformly better than any of the light rail options (with cost-effectiveness ratios of $18.24, $14.01, and $19.34 for the Low, Medium, and High options respectively).  They were better even without the scaling-up of user benefits (by a notional factor for what was claimed would be a more pleasant ride) that biased the results in favor of the light rail options.  And most cost-effective of all would have been a simple upgrading of regular bus services, introducing express lines and other such services where there is a demand.

These were all calculated at the costs as estimated in 2008.  We now know that the costs for the light rail line option chosen will be far higher than what was estimated in 2008.  That cost then was estimated to be $1.2 billion to build the line, and an annual $25.0 million then for operations and maintenance.  Adjusting these figures for general inflation from the prices of 2007 (the prices used for these estimates) to those of December 2021 would raise them by 34%, or to $1.6 billion for the capital cost and $33.5 million for the annual operational and maintenance costs.  But under the new contract, the capital cost will be $3.9 billion, or 2.4 times higher than estimated in 2008 (in end-2021 prices).  Also, the annual operational and maintenance costs (including insurance) in the new contract will be $2.6 billion over 30 years.  This payment will be adjusted for inflation, and the $2.6 billion reflects what it would be at an assumed inflation rate of 2% a year.  One can calculate that at such a 2% inflation rate, the annual payment over the 30 years in the prices of end-2021 would be $58.0 million, or 73% higher than the $33.5 million had been forecast earlier (also at end-2021 prices).

Putting the capital cost in annualized terms in the same way as was done in the Alternatives Analysis report, and adding in the annual operational and maintenance costs, the overall costs under the new contract (with all in end-2021 prices) is 2.3 times higher than what was forecast in 2008, when the Medium Light Rail option was chosen.  To be conservative, I will round this down to just double.  To calculate what the FTA cost-effectiveness measures would have been (had the forecast costs been closer to what the new contract calls for), one also needs ridership forecasts.  While we know that those forecasts are also highly problematic (as discussed in this earlier blog post, they have mathematical impossibilities), for the purposes here I will leave them as they were forecast in the Alternatives Analysis.

Based on this, one can calculate that the FTA cost-effectiveness measure would have jumped to $50.55 had the capital and operating costs been estimated closer to what they now are under the new contract.  This would have put the Purple Line far into the Low category for cost-effectiveness (far above the $29.00 limit), and the FTA would never have approved it for funding.  And at more plausible ridership estimates, the ratio would have been higher still.

b)  For the Cost of the Purple Line, One Could Double Bus Services in Suburban Maryland, and Stop Charging Fares

Resources available for public transit are scarce, and by spending them on the Purple Line they will not be available for other transit uses.  The Purple Line will serve a relatively narrow population – those living along a 16-mile corridor passing through some of the richest zip codes in the country, providing high-end services to a relatively few riders.  The question that should have been examined (but never was) was whether the resources being spent on the Purple Line could have been used in a way that would better serve the broader community.

A specific alternative that should have been considered would have been to use the funds that are being spent on the Purple Line instead to support public transit more broadly in Montgomery and Prince George’s Counties.  What could have been done?  The alternatives can then be compared, and a determination made of which would lead to a greater benefit for the community.  Only with such a comparison can one say whether a proposed project is worthwhile.

Specifically, what could be done if such resources were used instead to support the local, county-run bus services in Montgomery and Prince George’s Counties (Ride-On and The Bus respectively)?  They already carry twice as many riders as what the Purple Line would have carried in the base period examined (according to its optimistic forecasts), had it been in operation then.  As we will see below, with the funds that the State of Maryland will make in the availability payments on the Purple Line (and net of forecast Purple Line fare revenues), one could instead end the collection of all fares on those bus systems and at the same time double the size of those systems (doubling the routes or doubling the frequency on the current routes, or, and most likely, some combination of the two).  With unchanged average bus occupancy, they could thus serve four times the number of riders that the Purple Line is forecast (optimistically, but unrealistically) to carry.

The services would also be provided to the entire counties, not just to those living along the Purple Line’s 16-mile corridor.  Especially important would be service to the southern half of Prince George’s County, where much of its poorer population lives.  The Purple Line will not be anywhere close to this.  Ending the collection of fares would also be of particular value to these riders.

For the comparison to the cost of running the county-run bus systems, I used data on their operating costs, capital costs, and fare revenues from the National Transit Database, which is managed by the Federal Transit Administration of the US Department of Transportation.  The data was downloaded on February 1, 2022.  The data is available through 2020, but I used 2019 figures so as not to be affected by the special circumstances of the Covid-19 pandemic.

The bus system costs in 2019, along with what the Purple Line costs will be, are:

(in millions of $)

County-Run Bus Systems (for 2019):
Operating costs $157.6
10-year average K costs $17.1
  Total costs $174.7
Fares collected $22.0
  Total to double capacity and no fares $196.7
Purple Line:
Annual availability payments $240.0
Less fares collected (forecast) $45.3
  Net Costs $194.7

The two bottom-line figures basically match, at around $195 million.  The net payments that will be made on the Purple Line over its 30-year life would be $194.7 million, based on the announced availability payment averaging $240.0 million per year less forecast average annual fares to be collected.  That average fare forecast is undoubtedly optimistic (as the ridership forecasts are optimistic), and is based on what was provided in 2016 when the original contract was discussed with the legislature.  I have not seen an updated forecast, but MDOT staff stated (at the Board of Public Works meeting on January 26 to discuss and vote on the new contract) that fares would not be changed from what was planned before.

The cost of doubling the size of the county-run bus systems would have been $157.6 million for the operating cost (based on the actual cost in 2019) plus $17.1 million for the capital cost (based on the 10-year annual average between 2010 and 2019, as these expenditures fluctuate a good deal year to year), or a total of $174.7 million.  It is assumed that government will continue to spend what it is spending now to support these bus systems, so the extra funding needed for doubling the systems would be those costs again (for that second half), plus what is received in fare revenues in the system now (the $22.0 million) as fares would no longer be collected.  Thus the net cost would be $196.7 million, very close to the amount that could be covered by what will be provided on a net basis to the Purple Line (and assuming, optimistically, fares averaging $45.3 million a year).

In addition to this, a total of $1.36 billion will be provided in grants to the Purple Line.  At the lower cost of the earlier, 2016, contract, a portion of those grant funds ($1.25 billion before) would have been needed to cover a share of the costs of doubling the capacity of the bus systems and ending the collection of fares.  One could in principle have invested those grant funds and at a reasonable interest rate have generated sufficient funds to close the remaining gap.  But with the now far higher costs of the renegotiated contract, there would be no need for a share of those grant funds for this, and they could instead be used to provide funding for other high-priority transit needs in the region.

E.  Conclusion

The Purple Line has long been a problematic project, and with the now far higher costs in the renegotiated contract with the concessionaire, can only be described as a fiasco.  After rejecting a demand from the contractor to pay $800 million more to complete the construction of the rail line, they will instead now pay $1.9 billion more to a total of $3.9 billion for the construction alone, or close to double the originally negotiated cost of $2.0 billion.  They will also now pay more for the subsequent operation of the line.  It is all a terribly wasteful use of the scarce funds available for public transit, and comes with great environmental harm on top.  Funds that will be spent by the state under this concession contract could have been far better used, and far more equitably used, by supporting the public transit systems that serve the entire counties.

Despite the much higher costs, there does not appear to have been any serious assessment of whether the Purple Line can be justified at these higher costs.  At least there has not been any public discussion of this.  Rather, MDOT staff appear to have been directed to do whatever it takes, and at whatever the cost it turns out to be, to push through the project.  But that is in fundamental contradiction to basic public policy.  A project might be warranted at some low cost, but that does not then mean it is still warranted if it turns out the cost will be far higher.  That needs to be examined, but there is no evidence that there was any such examination here.

We should also now recognize as obvious that forecasts of ridership on fixed rail lines are uncertain.  Ridership on the DC Metro rail lines not only fell, more or less steadily, over the decade leading up to 2019, but then collapsed in 2020 and 2021 due to the Covid crisis.  Ridership in 2021 was almost 80% below what it was in 2019.  And it is highly unlikely that Metrorail ridership will ever recover to its earlier levels, as many of the former commuters on the system will now be working from home for at least part of the workweek.

Despite this, Governor Hogan has adamantly refused to look at alternatives to building a new fixed rail line, with this to be paid for via a 35-year long concession with private investors that will tie his successors to making regular availability payments regardless of whatever ridership turns out to be, and regardless of any other developments that might lead to more urgent priorities for the state’s budget resources.  The issue is not only that the ridership forecasts on the Purple Line are highly problematic, with mathematical impossibilities and other issues.  It is also, and more importantly, that any such ridership forecasts are uncertain.  Just look at what happened with Covid.  It was totally unanticipated but led ridership to collapse almost literally overnight.  And the effects are still with us, almost two years later.

The fundamental failure is the failure to acknowledge that any such forecasts are uncertain, and highly so.  There might be future Covids, and also other future events that we have no ability to foresee or predict.  For precisely this reason, it is important to design systems that are flexible.  A rail line is not.  Once it is built (at great cost), it cannot be moved.  Bus routes, in contrast can be shifted when this might be warranted, as can the frequency of services on the routes.

None of this seems to have mattered in the decisions now being taken.  As a consequence, and despite billions of dollars being spent, we do not have the transit systems that provide the services our residents need.

 

 

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Annex:  Details on the Diversion of MARC Revenues to Get Around Maryland’s Public Debt Limits

The State of Maryland follows a policy to limit its public borrowing so that state debt does not become excessive.  Specifically, it has set two “capital debt affordability ratios”:

1) Keep the stock of tax-supported state debt below 4% of personal income in the state;

and 2)  Keep debt service on tax-supported state debt below 8% of state revenues.

I am not sure whether these are limits have been set by statute, but as policy they will in any case be reflected in the state bond ratings.  It is also possible that representations, and perhaps even covenants, have been made in the Maryland state bond contracts stating the intention of the state to keep to them.  If so, then violation of those limits could have consequences for those bonds, possibly putting the state technically in default.

The commitments Governor Hogan will be making in signing the concession contracts for the Purple Line are in essence the same as commitments made when the state issues a bond and agrees to pay amortization and interest on that bond as those payments come due.  For the Purple Line, the private concessionaire will similarly be borrowing funds, but the State of Maryland will then have the obligation under the contract to repay that borrowing through the availability payments to be paid to the concessionaire for 30 years.  In addition to repaying (with interest) the borrowings made by the concessionaire, the availability payments will also cover the operational, maintenance, and similar costs over the 30-year life of the contract during which the concessionaire will operate the line.

Under the original contract, signed in 2016, these payments were expected to average $154 million per year for 30 years.  Under the new contract, they are expected to average $240 million a year.  One can debate whether all of the availability payment (which includes payment for the operations and maintenance) or simply some share of these payments should be considered similar to debt, but the payment obligation is fundamentally the same.  Governor Hogan is committing future governors (up until 2056) to make these payments, with the sole condition that the concessionaire has ensured the rail line is available to be used (hence the label “availability payments”).  In particular, they will be obliged to make these payments regardless of what ridership turns out to be, or indeed whether any riders show up at all.  That risk is being taken on fully by the state and is not a concern of the concessionaire (who, indeed, will find things easier and hence preferable the fewer the number of riders who show up).

These availability payments have all the characteristics of a debt obligation.  But if it were treated as state debt, it would have to be included in the capital debt affordability limits, and this could affect the amount that the state could borrow for other purposes.  One can debate precisely what obligations to include and the timing of when they should be included, but purely for the sake of illustration, let’s use the 2016 contract amounts and assume that the obligation to be repaid would have had a capital value of $2.0 billion (equal to the then planned construction cost, minus grants received for it, but plus the present discounted value of non-debt operating and other costs that have been obligated).  Assume also this would have applied in 2017.  Based on figures in the November 2021 report of Maryland’s Capital Debt Affordability Committee (see Table 1 on page 26), the ratio of tax-supported state debt to Maryland personal income was 3.5% in 2017, or below the 4% limit.  However, if the full $2.0 billion from the Purple Line would have been added in 2017, following the contract signing in 2016, that ratio would have grown to 4.1%.

Similarly, the Capital Debt Affordability Committee report indicates (Table 2A on page 28) that debt service on tax-supported public debt in 2017 was 7.5% of state revenues.  If one were to add the full annual $154 million payment that would be due (under the original contract) for the Purple Line already in 2017 (too early, as it would not be due until construction is over, but this is just for illustration), the debt service ratio to state revenues would have risen from 7.5% without the Purple Line commitments to 8.2% with it – above the 8.0% limit.  Of the $154 million, about two-thirds would have been used to repay the funds borrowed to pay for the construction (plus for the equity, which was a small share of the total).  If one argued that only these payments on the debt incurred (and the similar equity cost) should be included, and not also the 30-year commitment to cover the operational and similar other costs, then the ratio would have risen to 7.98% if it applied in 2017 – basically at the 8.0% limit.

Again, these figures are simply for illustration, and the actual additions in 2017 would have been less and/or applied only in later years.  But as a rough indication, they indicate that the Purple Line debt and payments due would be materially significant and hence problematic.

it was thus important that MDOT structure these payment obligations in such a way that it could argue that they are not for “tax-supported public debt”.  This would be the case, for example, if the fare revenues from ridership on the Purple Line would suffice to cover the debt service and other payment obligations incurred.  But even MDOT had to concede the Purple Line revenues would not suffice for that in at least the early years, although it did assert (unconvincingly) that ultimately they would.

MDOT therefore established a separately managed trust for the Purple Line, which would be used to make the payments due and into which it would direct not simply Purple Line fare revenues and grants to be received for the project (primarily from federal sources), but also sufficient revenues from the MARC commuter rail line (operated by MDOT) to make the payments.  It argued also that only the debt service component of the availability payment would have to be included (about two-thirds of the total payment obligation in the 2016 contract), with the operations, maintenance, and other such costs not relevant to the capital debt affordability ratios (despite being a long-term, 30-year, commitment).  The State Treasurer, Nancy Kopp in 2016, ruled that this structure was acceptable and that Purple Line debt should thus not count against the state’s capital debt affordability limits.

But while deemed not applicable for the capital debt affordability limits, the immediate question that arises is what then happens to MARC?  Commuter rail lines in the US do not run a surplus, and require subsidies from a government budget to remain in operation.  MARC is no exception.  If a portion of MARC revenues are diverted to cover payments on Purple Line debt, then MARC’s deficit will rise by that amount and Maryland’s subsidies to MARC will have to rise by that same amount.  And those subsidies will come from state tax revenues.  Hence state tax revenues are in reality covering the Purple Line debt payments, and routing it via MARC does not change that reality.  At a minimum, transparency is being lost.

Furthermore, and as noted before, the state bond rating agencies have made it known that they are fully aware of what is going on, and will include these Purple Line obligations into their calculations.  S&P explained in May 2016 that upon the signing of the Purple Line contract, they will include the net present value of the payments to be made by the state during the construction period in their calculations of the state’s tax-supported debt ratios, and that once operations begin will include in the ratios the full availability payments net of fare revenues collected on the Purple Line only.

Maryland’s payment commitments under the revised Purple Line contract are now expected to average $240 million a year, far above the $154 million expected before.  MDOT has once again made its case with the new State Treasurer (Dereck Davis, who took office on December 17, 2021, replacing the long-time former Treasurer Kopp) that these long-term payment obligations should not count against the state’s Capital Debt Affordability Ratios.  While I have not seen a formal ruling on this from the State Treasurer’s office, presumably he agreed with the MDOT view as otherwise it would not have been presented to the Board of Public Works on January 26.

The Ridership Forecasts for the Baltimore-Washington SCMAGLEV Are Far Too High

The United States desperately needs better public transit.  While the lockdowns made necessary by the spread of the virus that causes Covid-19 led to sharp declines in transit use in 2020, with (so far) only a partial recovery, there will remain a need for transit to provide decent basic service in our metropolitan regions.  Lower-income workers are especially dependent on public transit, and many of them are, as we now see, the “essential workers” that society needs to function.  The Washington-Baltimore region is no exception.

Yet rather than focus on the basic nuts and bolts of ensuring quality services on our subways, buses, and trains, the State of Maryland is once again enamored with using the scarce resources available for public transit to build rail lines through our public parkland in order to serve a small elite.  The Purple Line light rail line was such a case.  Its dual rail lines will serve a narrow 16-mile corridor, passing through some of the richest zip codes in the nation, but destroying precious urban parkland.  As was discussed in an earlier post on this blog, with what will be spent on the Purple Line one could instead stop charging fares on the county-run bus services in the entirety of the two counties the Purple Line will pass through (Montgomery and Prince George’s), and at the same time double those bus services (i.e. double the lines, or double the service frequency, or some combination).

The administration of Governor Hogan of Maryland nonetheless pushed the Purple Line through, although construction has now been halted for close to a year due to cost overruns leading the primary construction contractor to withdraw.  Hogan’s administration is now promoting the building of a superconducting, magnetically-levitating, train (SCMAGLEV) between downtown Baltimore and downtown Washington, DC, with a stop at BWI Airport.  Over $35 million has already been spent, with a massive Draft Environmental Impact Statement (DEIS) produced.  As required by federal law, the DEIS has been made available for public comment, with comments due by May 24.

It is inevitable that such a project will lead to major, and permanent, environmental damage.  The SCMAGLEV would travel partially in tunnels underground, but also on elevated pylons parallel to the Baltimore-Washington Parkway (administered by the National Park Service).  The photos at the top of this post show what it would look like at one section of the parkway.  The question that needs to be addressed is whether any benefits will outweigh the costs (both environmental and other costs), and ridership is central to this.  If ridership is likely to be well less than that forecast, the whole case for the project collapses.  It will not cover its operating and maintenance costs, much less pay back even a portion of what will be spent to build it (up to $17 billion according to the DEIS, but likely to be far more based on experience with similar projects).  Nor would the purported economic benefits then follow.

I have copied below comments I submitted on the DEIS forecasts.  Readers may find them of interest as this project illustrates once again that despite millions of dollars being spent, the consulting firms producing such analyses can get some very basic things wrong.  The issue I focus on for the proposed SCMAGLEV is the ridership forecasts.  The SCMAGLEV project sponsors forecast that the SCMAGLEV will carry 24.9 million riders (one-way trips) in 2045.  The SCMAGLEV will require just 15 minutes to travel between downtown Baltimore and downtown Washington (with a stop at BWI), and is expected to charge a fare of $120 (roundtrip) on average and up to $160 at peak hours.  As one can already see from the fares, at best it would serve a narrow elite.

But there is already a high-speed train providing premier-level service between Baltimore and Washington – the Acela service of Amtrak.  It takes somewhat longer – 30 minutes currently – but its fare is also somewhat lower at $104 for a roundtrip, plus it operates from more convenient stations in Baltimore and Washington.  Importantly, it operates now, and we thus have a sound basis for forecasts of what its ridership might be in the future.

One can thus compare the forecast ridership on the proposed SCMAGLEV to the forecast for Acela ridership (also in the DEIS) in a scenario of no SCMAGLEV.  One would expect the forecasts to be broadly comparable.  One could allow that perhaps it might be somewhat higher on the SCMAGLEV, but probably less than twice as high and certainly less than three times as high.  But one can calculate from figures in the DEIS that the forecast SCMAGLEV ridership in 2045 would be 133 times higher than what they forecast Acela ridership would be in that year (in a scenario of no SCMAGLEV).  For those going just between downtown Baltimore and downtown Washington (i.e. excluding BWI travelers), the forecast SCMAGLEV ridership would be 154 times higher than what it would be on the comparable Acela.  This is absurd.

And it gets worse.  For reasons that are not clear, the base year figures for Acela ridership in the Baltimore-Washington market are more than eight times higher in the DEIS than figures that Amtrak itself has produced.  It is possible that the SCMAGLEV analysts included Acela riders who have boarded north of Baltimore (such as in Philadelphia or New York) and then traveled through to DC (or from DC would pass through Baltimore to ultimate destinations further north).  But such travelers should not be included, as the relevant travelers who might take the SCMAGLEV would only be those whose trips begin in either Baltimore or in Washington and end in the other metropolitan area.  The project sponsors have made no secret that they hope eventually to build a SCMAGLEV line the full distance between Washington and New York, but that would at a minimum be in the distant future.  It is not a source of riders included in their forecasts for a Baltimore to Washington SCMAGLEV.

The Amtrak forecasts of what it expects its Acela ridership would be, by market (including between Baltimore and Washington) and under various investment scenarios, come from its recent NEC FUTURE (for Northeast Corridor Future) study, for which it produced a Final Environmental Impact Statement.  Using Amtrak’s forecasts of what its Acela ridership would be in a scenario where major investments allowed the Acela to take just 20 minutes to go between Baltimore and Washington, the SCMAGLEV ridership forecasts were 727 times as high (in 2040).  That is complete nonsense.

My comment submitted on the DEIS, copied below, goes further into these results and discusses as well how the SCMAGLEV sponsors could have gotten their forecasts so absurdly wrong.  But the lesson here is that the consultants producing such forecasts are paid by project sponsors who wish to see the project built.  Thus they have little interest in even asking the question of why they have come up with an estimate that 24.9 million would take a SCMAGLEV in 2045 (requiring 15 minutes on the train itself to go between Baltimore and DC) while ridership on the Acela in that year (in a scenario where the Acela would require 5 minutes more, i.e. 20 minutes, and there is no SCMAGLEV) would be about just 34,000.

One saw similar issues with the Purple Line.  An examination of the ridership forecasts made for it found that in about half of the transit analysis zone pairs, the predicted ridership on all forms of public transit (buses, trains, and the Purple Line as well) was less than what they forecast it would be on the Purple Line only.  This is mathematically impossible.  And the fact that half were higher and half were lower suggests that the results they obtained were basically just random.  They also forecast that close to 20,000 would travel by the Purple Line into Bethesda each day but only about 10,000 would leave (which would lead to Bethesda’s population exploding, if true).  The source of this error was clear (they mixed up two formats for the trips – what is called the production/attraction format with origin/destination), but it mattered.  They concluded that the Purple Line had to be a rail line rather than a bus service in order to handle their predicted 20,000 riders each day on the segment to Bethesda.

It may not be surprising that private promoters of such projects would overlook such issues.  They may stand to gain (i.e. from the construction contracts, or from an increase in land values next to station sites), even though society as a whole loses.  Someone else (government) is paying.  But public officials in agencies such as the Maryland Department of Transportation should be looking at what is the best way to ensure quality and affordable transit services for the general public.  Problems develop once the officials see their role as promoters of some specific project.  They then seek to come up with a rationale to justify the project, and see their role as surmounting all the hurdles encountered along the way.  They are not asking whether this is the best use of scarce public resources to address our very real transit needs.

A high-speed magnetically-levitating train (with superconducting magnets, no less), may look attractive.  But officials should not assume such a shiny new toy will address our transit issues.

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May 22, 2021

Comment Submitted on the DEIS for SCMAGLEV

The Ridership Forecasts Are Far Too High

A.  Introduction

I am opposed to the construction of the proposed SCMAGLEV project between Baltimore and Washington, DC.  A key issue for any such system is whether ridership will be high enough to compensate for the environmental damage that is inevitable with such a project.  But the ridership forecasts presented in the DEIS are hugely flawed.  They are far too high and simply do not meet basic conditions of plausibility.  At more plausible ridership levels, the case for such a project collapses.  It will not cover its operating costs, much less pay back any of the investment (of up to $17 billion according to the DEIS, but based on experience likely to be far higher).  Nor will the purported positive economic benefits then follow.  But the damage to the environment will be permanent.

Specifically, there is rail service now between Baltimore and Washington, at three levels of service (the high-speed Acela service of Amtrak, the regular Amtrak Regional service, and MARC).  Ridership on the Acela service, as it is now and with what is expected with upgrades in future years, provides a benchmark that can be used.  While it could be argued that ridership on the proposed SCMAGLEV would be higher than ridership on the Acela trains, the question is how much higher.  I will discuss below in more detail the factors to take into account in making such a comparison, but briefly, the Acela service takes 30 minutes today to go between Baltimore and Washington, while the SCMAGLEV would take 15 minutes.  But given that it also takes time to get to the station and on the train, and then to the ultimate destination at the other end, the time savings would be well less than 50%.  The fare would also be higher on the SCMAGLEV (at an average, according to the DEIS, of $120 for a round-trip ticket but up to $160 at peak hours, versus an average of $104 on the Acela).  In addition, the stations the SCMAGLEV would use for travel between downtown Baltimore and downtown Washington are less conveniently located (with poorer connections to local transit) than the Acela uses.

Thus while it could be argued that the SCMAGLEV would attract more riders than the Acela, even this is not clear.  But being generous, one could allow that it might attract somewhat more riders.  The question is how many.  And this is where it becomes completely implausible.  Based on the ridership forecasts in the DEIS, for both the SCMAGLEV and for the Acela (in a scenario where the SCMAGLEV is not built), the SCMAGLEV in 2045 would carry 133 times what ridership would be on the Acela.  Excluding the BWI ridership on both, it would be 154 times higher.  There is no way to describe this other than that it is just nonsense.  And with other, likely more accurate, forecasts of what Acela ridership would be in the future (discussed below) the ratios become higher still.

Similarly, if the SCMAGLEV will be as attractive to MARC riders as the project sponsors forecast it will be, then most of those MARC riders would now be on the modestly less attractive Acela.  But they aren’t.  The Acela is 30 minutes faster than MARC (the SCMAGLEV would be 45 minutes faster), yet 28 times as many riders choose MARC over Acela between Baltimore and Washington.  I suspect the fare difference ($16 per day on MARC, vs. $104 on the Acela) plays an important role.  The model used could have been tested by calculating a forecast with their model of what Acela ridership would be under current conditions, with this then compared this to what the actual figures are.  Evidently this was not done.  Had they, their predicted Acela ridership would likely have been a high multiple of the actual and it would have been clear that their modeling framework has problems.

Why are the forecasts off by orders of magnitude?  Unfortunately, given what has been made available in the DEIS and with the accompanying papers on ridership, one cannot say for sure.  But from what has been made available, there are indications of where the modeling approach taken had issues.  I will discuss these below.

In the rest of this comment I will first discuss the use of Acela service and its ridership (both the actual now and as projected) as a basis for comparison to the ridership forecasts made for the SCMAGLEV.  They would be basically similar services, where a modest time saving on the SCMAGLEV (15 minutes now, but only 5 minutes in the future if further investments are made in the Acela service that would cut its Baltimore to DC time to just 20 minutes) is offset by a higher fare and less convenient station locations.  I will then discuss some reasons that might explain why the SCMAGLEV ridership forecasts are so hugely out-of-line with what plausible numbers might be.

B.  A Comparison of SCMAGLEV Ridership Forecasts to Those for Acela  

The DEIS provides ridership forecasts for the SCMAGLEV for both 2030 (several years after the DEIS says it would be opened, so ridership would then be stable after an initial ramping up) and for a horizon year of 2045.  I will focus here on the 2045 forecasts, and specifically on the alternative where the destination station in Baltimore is Camden Yards.  The DEIS also has forecasts for ridership in an alternative where the SCMAGLEV line would end in the less convenient Cherry Hill neighborhood of Baltimore, which is significantly further from downtown and with poorer connections to local transit options.  The Camden Yards station is more comparable to Penn Station – Baltimore, which the Acela (and Amtrak Regional trains and one of the MARC lines) use.  Penn Station – Baltimore has better local transit connections and would be more convenient for many potential riders, but this will of course depend on the particular circumstances of the rider – where he or she will be starting from and where their particular destination will be.  It will, in particular, be more convenient for riders coming from North and Northeast of Baltimore than Camden Yards would be.  And those from South and Southwest of Baltimore would be more likely to drive directly to the DC region than try to reach Camden Yards, or they would alight at BWI.

The DEIS also provides forecasts of what ridership would be on the existing train services between Baltimore and Washington:  the Acela services (operated by Amtrak), the regular Amtrak Regional trains, and the MARC commuter service operated by the State of Maryland.  Note also that the 2045 forecasts for the train services are for both a scenario where the SCMAGLEV is not built and then what they forecast the reduced ridership would be with a SCMAGLEV option.  For the purposes here, what is of interest is the scenario with no SCMAGLEV.

The SCMAGLEV would provide a premium service, requiring 15 minutes to go between downtown Baltimore and downtown Washington, DC.  Acela also provides a premium service and currently takes 30 minutes, while the regular Amtrak Regional trains take 40 to 45 minutes and MARC service takes 60 minutes.  But the fares differ substantially.  Using the DEIS figures (with all prices and fares expressed in base year 2018 dollars), the SCMAGLEV would charge an average fare of $120 for a round-trip (Baltimore-Washington), and up to $160 for a roundtrip at peak times.  The Acela also has a high fare for its also premium service, although not as high as SCMAGLEV, charging an average of $104 for a roundtrip (using the DEIS figures).  But Amtrak Regional trains charge only $34 for a similar roundtrip, and MARC only $16.

Acela service thus provides a reasonable basis for comparison to what SCMAGLEV would provide, with the great advantage that we know now what Acela ridership has actually been.  This provides a firm base for a forecast of what Acela ridership would be in a future year in a scenario where the SCMAGLEV is not built.  And while the ridership on the two would not be exactly the same, one should expect them to be in the same ballpark.

But they are far from that:

  DEIS Forecasts of SCMAGLEV vs. Acela Ridership, Annual Trips in 2045

Route

SCMAGLEV Trips

Acela Trips

Ratio

Baltimore – DC only

19,277,578

125,226

154 times as much

All, including BWI

24,938,652

187,887

133 times as much

Sources:  DEIS, Main Report Table 4.2-3; and Table D-4-48 of Appendix D.4 of the DEIS

Using estimates just from the DEIS, the project sponsor is forecasting that annual (one-way) trips on the SCMAGLEV in 2045 would be 133 times what they would be in that year on the Acela (in a scenario where the SCMAGLEV is not built).  And it would be 154 times as much for the Baltimore – Washington riders only.  This is nonsense.  One could have a reasonable debate if the SCMAGLEV figures were twice as high, and maybe even if they were three times as high.  But it is absurd that they would be 133 or 154 times as high.

And it gets worse.  The figures above are all taken from the DEIS.  But the base year Acela ridership figures in the DEIS (Appendix D.4, Table D.4-45) differ substantially from figures Amtrak itself has produced in its recent NEC FUTURE study.  This review of future investment options in Northeast Corridor (Washington to Boston) Amtrak service was concluded in July 2017.  As part of this it provided forecasts of what future Acela ridership would be under various alternatives, including one (its Alternative 3) where Acela trains would be substantially upgraded and require just 20 minutes for the trip between downtown Baltimore and downtown Washington, DC.  This would be quite similar to what SCMAGLEV service would be.

But for reasons that are not clear, the base year figures for Acela ridership between Baltimore and Washington differ substantially between what the SCMAGLEV DEIS has and what NEC FUTURE has.  The figure in the NEC FUTURE study (for a base year of 2013) puts the number of riders (one-way) between Baltimore and Washington (and not counting those who boarded north of Baltimore, at Philadelphia or New York for example, and then rode through to Washington, and similarly for those going from Washington to Baltimore) at just 17,595.  The DEIS for the SCMAGLEV put the similar Acela ridership (for a base year of 2017) at 147,831 (calculated from Table D.4-45, of Appendix D.4).  While the base years differ (2013 vs. 2017), the disparity cannot be explained by that.  It is far too large.  My guess would be that the DEIS counted all Acela travelers taking up seats between Baltimore and Washington, including those who alighted north of Baltimore (or whose destination from Washington was north of Baltimore), and not just those travelers traveling solely between Washington and Baltimore.  But the SCMAGLEV will be serving only the Baltimore-Washington market, with no interconnections with the train routes coming from north of Baltimore.

What was the source of the Acela ridership figure in the DEIS of 147,831 in 2017?  That is not clear.  Table D.4-45 of Appendix D.4 says that its source is Table 3-10 of the “SCMAGLEV Final Ridership Report”, dated November 8, 2018.  But that report, which is available along with the other DEIS reports (with a direct link at https://bwmaglev.info/index.php/component/jdownloads/?task=download.send&id=71&catid=6&m=0&Itemid=101), does not have a Table 3-10.  Significant portions of that report were redacted, but in its Table of Contents no reference is shown to a Table 3-10 (even though other redacted tables, such as Tables 5-2 and 6-3, are still referenced in the Table of Contents, but labeled as redacted).

One can only speculate on why there is no Table 3-10 in the Final Ridership Report.  Perhaps it was deleted when someone discovered that the figures reported there, which were then later used as part of the database for the ridership forecast models, were grossly out of line with the Amtrak figures.  The Amtrak figure for Acela ridership for Baltimore-Washington passengers of 17,595 (in 2013) is less than one-eighth of the figure on Acela ridership shown in the DEIS or 147,831 (in 2017).

It can be difficult for an outsider to know how many of those riding on the Acela between Washington and Baltimore are passengers going just between those two cities (as well as BWI).  Most of the passengers riding on that segment will be going on to (or coming from) cities further north.  One would need access to ticket sales data.  But it is reasonable to assume that Amtrak itself would know this, and therefore that the figures in the NEC FUTURE study would likely be accurate.  Furthermore, in the forecast horizon years, where Amtrak is trying to show what Acela (and other rail) ridership would grow to with alternative investment programs, it is reasonable to assume that Amtrak would provide relatively optimistic (i.e. higher) estimates, as higher estimates are more likely to convince Congress to provide the funding that would be required for such investments.

The Amtrak figures would in any case provide a suitable comparison to what SCMAGLEV’s future ridership might be.  The Amtrak forecasts are for 2040, so for the SCMAGLEV forecasts I interpolated to produce an estimate for 2040 assuming a constant rate of growth between the forecast SCMAGLEV ridership in 2030 and that for 2045.  Both the NEC FUTURE and SCMAGLEV figures include the stop at BWI.

    Forecasts of SCMAGLEV (DEIS) vs. Acela (NEC FUTURE) Ridership between Baltimore and Washington, Annual Trips in 2040 

Alternative

SCMAGLEV Trips

Acela Trips

Ratio

No Action

22,761,428

26,177

870 times as much

Alternative 1

22,761,428

26,779

850 times as much

Alternative 2

22,761,428

29,170

780 times as much

Alternative 3

22,761,428

31,291

727 times as much

Sources:  SCMAGLEV trips interpolated from figures on forecast ridership in 2030 and 2045 (Camden Yards) in Table 4.2-3 of DEIS.  Acela trips from NEC FUTURE Final EIS, Volume 2, Appendix B.08.

The Acela ridership figures are those estimated under various investment scenarios in the rail service in the Northeast Corridor.  NEC FUTURE examined a “No Action” scenario with just minimal investments, and then various alternative investment levels to produce increasingly capable services.  Alternative 3 (of which there were four sub-variants, but all addressing alternative investments between New York and Boston and thus not affecting directly the Washington-Baltimore route) would upgrade Acela service to the extent that it would go between Baltimore and Washington in just 20 minutes.  This would be very close to the 15 minutes for the SCMAGLEV.  Yet even with such a comparable service, the SCMAGLEV DEIS is forecasting that its service would carry 727 times as many riders as what Amtrak has forecast for its Acela service (in a scenario where there is no SCMAGLEV).  This is complete nonsense.

To be clear, I would stress again that the forecast future Acela ridership figures are a scenario under various possible investment programs by Amtrak.  The investment program in Alternative 3 would upgrade Acela service to a degree where the Baltimore – Washington trip (with a stop at BWI) would take just 20 minutes.  The NEC FUTURE study forecasts that in such a scenario the Baltimore-Washington ridership on Acela would total a bit over 31,000 trips in the year 2040.  In contrast, the DEIS for the SCMAGLEV forecasts that there would in that year be close to 23 million trips taken on the similar SCMAGLEV service, requiring 15 minutes to make such a trip.  Such a disparity makes no sense.

C.  How Could the Forecasts be so Wrong?

A well-known consulting firm, Louis Berger, prepared the ridership forecasts, and their “Final Ridership Report” dated November 8, 2018, referenced above, provides an overview on the approach they took.  Unfortunately, while I appreciate that the project sponsor provided a link to this report along with the rest of the DEIS (I had asked for this, having seen references to it in the DEIS), the report that was posted had significant sections redacted.  Due to those redactions, and possibly also limitations in what the full report itself might have included (such as summaries of the underlying data), it is impossible to say for sure why the forecasts of SCMAGLEV ridership were close to three orders of magnitude greater than what ridership has been and is expected to be on comparable Acela service.

Thus I can only speculate.  But there are several indications of what may have led the SCMAGLEV estimates to be so out of line with ridership on a service that is at least broadly comparable.  Specifically:

1)  As noted above, there were apparent problems in assembling existing data on rail ridership for the Baltimore-Washington market, in particular for the Acela.  The ridership numbers for the Acela in the DEIS were more than eight times higher in their base year (2017) than what Amtrak had in an only slightly earlier base year (2013).  The ridership numbers on Amtrak Regional trains (for Baltimore-Washington riders) were closer but still substantially different:  409,671 in Table D.4-45 of the DEIS (for 2017), vs. 172,151 in NEC FUTURE (for 2013).

Table D.4-45 states that its source for this data on rail ridership is a Table 3-10 in the Final Ridership Report of November 8, 2018.  But as noted previously, such a table is not there – it was either never there or it was redacted.  Thus it is impossible to determine why their figures differ so much from those of Amtrak.  But the differences for the Acela figures (more than a factor of eight) are huge, i.e. close to an order of magnitude by itself.  While it is impossible to say for sure, my guess (as noted above) is that the Acela ridership numbers in the DEIS included travelers whose trip began, or would end, in destinations north of Baltimore, who then traveled through Baltimore on their way to, or from, Washington, DC.  But such travelers are not part of the market the SCMAGLEV would serve.

2)  In modeling the choice those traveling between Baltimore and Washington would have between SCMAGLEV and alternatives, the analysts collapsed all the train options (Acela, Amtrak Regional, and MARC) into one.  See page 61 of the Ridership Report.  They create a weighted average for a single “train” alternative, and they note that since (in their figures) MARC ridership makes up almost 90% of the rail market, the weighted averages for travel time and the fare will be essentially that of MARC.

Thus they never looked at Acela as an alternative, with a service level not far from that of SCMAGLEV.  Nor do they even consider the question of why so many MARC riders (67.5% of MARC riders in 2045 if the Camden Yards option is chosen – see page D-56 of Appendix D-4 of the DEIS) are forecast to divert to the SCMAGLEV, but are not doing so now (nor in the future) to Acela.  According to Table D-45 of Appendix D.4 of the DEIS, in their data for their 2017 base year, there are 28 times as many MARC riders as on Acela between downtown Baltimore and downtown Washington, and 20 times as many with those going to and from the BWI stop included.  Evidently, they do not find the Acela option attractive.  Why should they then find the SCMAGLEV train attractive?

3)  The answer as to why MARC riders have not chosen to ride on the Acela almost certainly has something to do with the difference in the fares.  A round-trip on MARC costs $16 a day.  A round trip on Acela costs, according to the DEIS, an average of $104 a day.  That is not a small difference.  For someone commuting 5 days a week and 50 weeks a year (or 250 days a year), the annual cost on MARC would be $4,000 but $26,000 a year on the Acela.  And it would be an even higher $30,000 a year on the SCMAGLEV (based on an average fare of $120 for a round trip), and $40,000 a year ($160 a day) at peak hours (which would cover the times commuters would normally use).  Even for those moderately well off, $40,000 a year for commuting would be a significant expense, and not an attractive alternative to MARC with its cost of just one-tenth of this.

If such costs were properly taken into account in the forecasting model, why did it nonetheless predict that most MARC riders would switch to the SCMAGLEV?  This is not fully clear as the model details were not presented in the redacted report, but note that the modelers assigned high dollar amounts for the time value of money ($31.00 to $46.50 for commuters and other non-business travel, and $50.60 to $75.80 for business travel – see page 53 of the Ridership Report).  However, even at such high values, the numbers do not appear to be consistent.  Taking a SCMAGLEV (15 minute trip) rather than MARC (60 minutes) would save 45 minutes each way or 1 1/2 hours a day.  Only at the very high end value of time for business travelers (of $75.80 per hour, or $113.70 for 1 1/2 hours) would this value of time offset the fare difference of $104 (using the average SCMAGLEV fare of $120 minus the MARC fare of $16).  And even that would not suffice for travelers at peak hours (with its SCMAGLEV fare of $160).

But there is also a more basic problem.  It is wrong to assume that travelers on MARC treat their 60 minutes on the train as all wasted time.  They can read, do some work, check their emails, get some sleep, or plan their day.  The presumption that they would pay amounts similar to what some might on average earn in an hour based on their annual salaries is simply incorrect.  And as noted above, if it were correct, then one would see many more riders on the Acela than one does (and similarly riders on the Amtrak Regional trains, that require about 40 minutes for the Washington to Baltimore trip, with an average fare of $34 for a round trip).

There is a similar issue for those who drive.  Those who drive do not place a value on the time spent in their cars equal to what they would earn in an hourly equivalent of their regular salary.  They may well want to avoid traffic jams, which are stressful and frustrating for other reasons, but numerous studies have found that a simple value-of-time calculation based on annual salaries does not explain why so many commuters choose to drive.

4)  Data for the forecasting model also came in part from two personal surveys.  One was an in-person survey of travelers encountered on MARC, at either the MARC BWI Station or onboard Penn Line trains, or at BWI airport.  The other was an online internet survey, where they unfortunately redacted out how they chose possible respondents.

But such surveys are unreliable, with answers that depend critically on how the questions are phrased.  The Final Ridership report does not include the questionnaire itself (most such reports would), so one cannot know what bias there might have been in how the questions were worded.  As an example (and admittedly an exaggerated example, to make the point) were the MARC riders simply asked whether they would prefer a much faster, 15 minute, trip?  Or were they asked whether they would pay an extra $104 per day ($144 at peak hours) to ride a service that would save them 45 minutes each way on the train?

But even such willingness to pay questions are notoriously unreliable.  An appropriate follow-up question to a MARC rider saying they would be willing to pay up to an extra $144 a day to ride a SCMAGLEV, would be why are they evidently not now riding the Acela (at an extra $88 a day) for a ride just 15 minutes longer than what it would be on the SCMAGLEV.

One therefore has to be careful in interpreting and using the results from such a survey in forecasting how travelers would behave.  If current choices (e.g. using the MARC rather than the Acela) do not reflect the responses provided, one should be concerned.

5)  Finally, the particular mathematical form used to model the choices the future travelers would make can make a big difference to the findings.  The Final Ridership Report briefly explains (page 53) that it used a multinomial logit model as the basis for its modeling.  Logit functions assign a continuous probability (starting from 0 and rising to 100%) of some event occurring.  In this model, the event is that a traveler going from one travel zone to another will choose to travel via the SCMAGLEV, or not.  The likelihood of choosing to travel via the SCMAGLEV will be depicted as an S-shaped function, starting at zero and then smoothly rising (following the S-shape) until it reaches 100%, depending on, among other factors, what the travel time savings might be.

The results that such a model will predict will depend critically, of course, on the particular parameters chosen.  But the heavily redacted Final Ridership Report does not show what those parameters were nor how they were chosen or possibly estimated, nor even the complete set of variables used in that function.  The report says little (in what remains after the redactions) beyond that they used that functional form.

A feature of such logit models is that while the choices are discrete (one either will ride the SCMAGLEV or will not), it allows for “fuzziness” around the turning points, that recognize that between individuals, even if they confront a similar combination of variables (a combination of cost, travel time, and other measured attributes), some will simply prefer to drive while some will prefer to take the train.  That is how people are.  But then, while a higher share might prefer to take a train (or the SCMAGLEV) when travel times fall (by close to 45 minutes with the SCMAGLEV when compared to their single “train” option that is 90% MARC, and by variable amounts for those who drive depending on the travel zone pairs), how much higher that share will be will depend on the parameters they selected for their logit.

With certain parameters, the responses can be sensitive to even small reductions in travel times, and the predicted resulting shifts then large.  But are those parameters reasonable?  As noted previously, a test would have been whether the model, with the parameters chosen, would have predicted accurately the number of riders actually observed on the Acela trains in the base year.  But it does not appear such a test was done.  At least no such results were reported to test whether the model was validated or not.

Thus there are a number of possible reasons why the forecast ridership on the SCMAGLEV differs so much from what one currently observes for ridership on the Acela, and from what one might reasonably expect Acela ridership to be in the future.  It is not possible to say whether these are indeed the reasons why the SCMAGLEV forecasts are so incredibly out of line with what one observes for the Acela.  There may be, and indeed likely are, other reasons as well.  But due to issues such as those outlined here, one can understand the possible factors behind SCMAGLEV ridership forecasts that deviate so markedly from plausibility.

D.  Conclusion

The ridership forecasts for the SCMAGLEV are vastly over-estimated.  Predicted ridership on the SCMAGLEV is a minimum of two, and up to three, orders of magnitude higher than what has been observed on, and can reasonably be forecast for, the Acela.  One should not be getting predicted ridership that is more than 100 times what one observes on a comparable, existing (and thus knowable), service.

With ridership on the proposed system far less than what the project sponsors have forecast, the case for building the SCMAGLEV collapses.  Operational and maintenance costs would not be covered, much less any possibility of paying back a portion of the billions of dollars spent to build it, nor will the purported economic benefits follow.

However, the harm to the environment will have been done.  Even if the system is then shut down (due to the forecast ridership never materializing), it will not be possible to reverse much of that environmental damage.

The US very much needs to improve its public transit.  It is far too difficult, with resulting harm both to the economy and to the population, to move around in the Baltimore-Washington region.  But fixing this will require a focus on the basic nuts and bolts of operating, maintaining, and investing in the transit systems we have, including the trains and buses.  This might not look as attractive as a magnetically levitating train, but will be of benefit.  And it will be of benefit to the general public – in particular to those who rely on public transit – and not just to a narrow elite that can afford $120 fares.  Money for public transit is scarce.  It should not be wasted on shiny new toys.

The Purple Line Ridership Forecasts Are Wrong: An Example of Why We Get Our Infrastructure Wrong

Executive Summary

There are several major problems with the forecast ridership figures for the Purple Line, a proposed 16-mile light rail line that would pass in a partial arc around Washington, DC, in suburban Maryland.  The forecasts, as presented and described in the “Travel Forecasts Results Technical Report” of the Final Environmental Impact Statement for the project, are in a number of cases simply impossible.

Problems include:

a)  Forecast ridership in 2040 between many of the Transit Analysis Zone pairs along the Purple Line corridor would be higher on the Purple Line itself than it would be for total transit ridership (which includes bus, Metrorail, and commuter rail ridership, in addition to ridership on the Purple Line) between these zones.  This is impossible. Such cases are not only numerous (found in more than half of the possible cases for zones within the corridor) but often very large (12 times as high in one case).  If the forecasts for total transit ridership are correct, then correcting for this, with Purple Line ridership some reasonable share of the totals, would lead to far lower figures for Purple Line ridership.

b)  Figures on forecast hours of user benefits (primarily forecast time savings from a rail line) in a scenario where the Purple Line is built as compared to one where it is not, are often implausibly high.  In two extreme cases, the figures indicate average user benefits per trip between two specific zones, should the Purple Line be built, of 9.7 hours and 11.5 hours.  These cannot be right; one could walk faster.  But other figures on overall user benefits are also high, leading to an overall average predicted benefit of 30 minutes per trip.  Even with adjustments to the pure time savings that assign a premium to rail service, this is far too high and overestimates benefits by at least a factor of two or even three.  The user benefit figures are important for two reasons:  1) An overestimate leads to a cost-effectiveness estimate (an estimate of the cost of the project per hour of user benefits) that will be far off;  and 2) The figures used for user benefits from taking the proposed rail line enter directly into the estimation of ridership on the rail line (as part of the choice on whether to take the rail line rather than some other transit option, or to drive).  If the user benefit figures are overstated, ridership will be less.  With the user benefit figures overstated by a large margin, ridership will be far less.

c)  Figures on ridership from station to station are clearly incorrect.  They indicate, for example, that far more riders would exit at the Bethesda station (an end point on the line) each day (19,800) than would board there (10,210).  This is impossible.  More significantly, the figures indicate system capacity must be sufficient to handle 21,400 riders each day on the busiest segment (on the segment leaving Silver Spring heading towards Bethesda).  Even if the overall ridership numbers were correct, the figure for ridership on this segment is clearly too high (and it is this number which leads to the far higher number of those exiting the system in Bethesda than would enter there each day).  The figure is important as the rail line has been designed to a capacity sufficient to carry such a load.  With the true number far lower, there is even less of a case for investing in an expensive rail option.  Upgraded bus services could provide the capacity needed, and at far lower cost.

There appear to be other problems as well.  But even just these three indicate there are major issues with these forecasts.  This may also explain why a number of independent observers have noted for some time that the Purple Line ridership forecasts look implausibly high.  The figure for Purple Line ridership in 2040 of 69,300 per day is three times the average daily ridership actually observed in 2012 on 31 light rail lines built in the US over the last three decades.  It would also be 58% higher on the Purple Line than on the highest amongst those 31.  Yet the Purple Line would pass solely through suburban neighborhoods, of generally medium to low density.  Most of these other light rail lines in the US serve travel to and from downtown areas.

The causes of these errors in the ridership forecasts for the Purple Line are not always clear.  But the issues suggest at a minimum that quality checks were insufficient.  And while the Purple Line is just one example, inadequate attention to such issues might explain in part why ridership forecasts for light rail lines have often proven to be substantially wrong.

 

A.  Introduction

The Purple Line is a proposed light rail line that would be built in Suburban Maryland, stretching in a partial arc from east of Washington, DC, to north of the city.  I have written several posts previously in this blog on the proposed project (see the posts here, here, here, and here) and have been highly critical of it.  It is an extremely expensive project (the total cost to be paid to the private concessionaire to build and then operate the line for 30 years will sum to $5.6 billion, and other costs borne directly by the state and/or local counties will add at least a further $600 million to this).  And the state’s own analyses of the project found that upgraded bus services (including any one of several bus rapid transit, or BRT, options) to provide the transit services that are indeed needed in the corridor, would be both cheaper and more cost-effective.  Such alternatives would also avoid the environmental damage that is inevitable with the construction of dual rail lines along the proposed route, including the destruction of 48 acres of forest cover, the filling in of important wetland areas, and the destruction of a linear urban park that has the most visited trail in the state.

The state’s rationale for building a rail line rather than providing upgraded bus services is that ridership will be so high that at some point in the future (beyond 2040) only rail service would be able to handle the load.  But many independent analysts have long questioned those ridership forecasts.  A study from 2015 found that the forecast ridership on the Purple Line would be three times as high as the ridership actually observed in 2012 on 31 light rail lines built in the US over the last three decades.  Furthermore, the forecast Purple Line ridership would be 58% higher than ridership actually observed on the highest line among those 31.  And with the Purple Line route passing through suburban areas of generally medium to low density, in contrast to routes to and from major downtown areas for most of those 31, many have concluded the Purple Line forecasts are simply not credible.

Why did the Purple Line figures come out so high?  The most complete description provided by the State of Maryland of the ridership forecasts are provided in the chapter titled “Travel Forecasts Results Technical Report”, which is part of Volume III of the Final Environmental Impact Statement (FEIS) for the Purple Line, dated August 2013 (which I will hereafter often refer to simply as the “FEIS Travel Forecasts chapter”).  A close examination of that material indicates several clear problems with the figures.  This post will discuss three, although there might well be more.

These three are:

a)  The FEIS forecast ridership for 2040 on the Purple Line alone would be higher (in a number of cases far higher) in most of the 49 possible combinations of travel between the 7 Transit Analysis Zones (TAZs) defined along the Purple Line route, than the total number of transit riders among those zones (by bus, Metrorail, commuter rail, and the Purple Line itself).  This is impossible.

b)  Figures on user benefits per Purple Line trip (primarily the time forecast to be saved by use of a rail line) are implausibly high.  In two cases they come to 9.7 hours and 11.5 hours, respectively, per trip.  This cannot be.  One could walk faster.  But these figures for minutes of user benefits per trip were then passed through in the computations to the total forecast hours of user benefits that would accrue as a consequence of building the Purple Line, thus grossly over-estimating the benefits. Such user benefit figures would also have been used in the estimation of how many will choose to ride the Purple Line.  If these user benefit figures are overestimated (sometimes hugely overestimated), then the Purple Line ridership forecasts will be overestimated.

c)  The figure presenting rail ridership by line segment from station to station (which then was used to determine what ridership capacity would be needed to service the proposed route) shows almost twice as many riders exiting at the Bethesda station (an end of the line) as would board there each day (19,800 arriving versus 10,210 leaving each day).  While there could be some small difference (i.e. some people might take transit to work in the morning, and then get a car ride home with a colleague in the evening), it could not be so large.  The figures would imply that Bethesda would be accumulating close to 9,600 new residents each day.  The forecast ridership by line segment (which is what determines these figures) is critical as it determines what the capacity will need to be of the transit system to service such a number of riders.  With these figures over-stated, the design capacity is too high, and there is even less of a rationale for building a rail line as opposed to simply upgrading bus services in the corridor.

These three issues are clear just from an examination of the numbers presented.  But as noted, there might well be more.  We cannot say for sure what all the errors might be as the FEIS Travel Forecasts chapter does not give a complete set of the numbers and assumed relationships needed as inputs to the analysis and then resulting from it, nor more than just a cursory explanation of how the results were arrived at.  But with anomalies such as these, and with no explanations for them, one cannot treat any of the results with confidence.

And while necessarily more speculative, I will also discuss some possible reasons for why the mistakes may have been made.  This matters less than the errors themselves, but might provide a sense for why they arose.  Broadly, while the FEIS Travel Forecasts chapter (and indeed the entire FEIS report) only shows the Maryland Transit Administration (MTA) as the source for the documents, the MTA has acknowledged (and as would be the norm) that major portions of the work – in particular the ridership forecasts – were undertaken or led by hired consulting firms.  The consulting firms use standard but large models to prepare such ridership forecasts, but such models must be used carefully to ensure reliable results.  It is likely that results were generated by what might have been close to a “black box” to the user, that there were then less than sufficient quality checks to ensure the results were reasonable, and that the person assigned to write up the results (who may well have differed from the person generating the numbers) did not detect these anomalous results.

I will readily admit that this is speculation as to the possible underlying causes, and that I could be wrong on this.  But it might explain why figures were presented in the final report which were on their face impossible, with no explanation given.  In any case, what is most important is the problems themselves, regardless of the possible explanations on why they arose.

Each of the three issues will be taken up in turn.

B.  Forecast Ridership on the Purple Line Alone Would Be Higher in Many Cases than Total Transit Ridership

The first issue is that, according to the forecasts presented, there would be more riders on the Purple Line alone between many of the Transit Analysis Zones (TAZs) than the number of riders on all forms of transit.  This is impossible.

Forecast Ridership on All Transit Options in 2040:

Forecast Ridership on Purple Line Alone in 2040:

These two tables are screenshots of the upper left-hand corners of Table 16 and 22 from the FEIS Travel Forecasts chapter.  While they show the key numbers, I would recommend that the reader examine the full tables in the original FEIS Travel Forecasts chapter. Indeed, if your computer can handle it, it would be best to open the document twice in two separate browsers and then scroll down to the two tables to allow them to be compared side by side on your screen.

The tables show forecast ridership in 2040 on all forms of transit in the “Preferred Alternative” scenario where the Purple Line is built (Table 16), or for the sub-group of riders just on the Purple Line (Table 22).  And based on the total ridership figures presented at the bottoms of the full tables, the titles appear to be correct. That is, Table 16 forecasts that total transit ridership in the Washington metro region would be about 1.5 million trips per day in 2040, which is plausible (Table 13 says it was 1.1 million trips per day in 2005, which is consistent with WMATA bus and rail ridership, where WMATA accounts for 80 – 85% of total ridership in the region).  And Table 22 says the total number of trips per day on the Purple Line in 2040 would be 68,650, which is consistent (although still somewhat different from, with no explanation) with figures given elsewhere in the chapter on forecast total Purple Line trips per day in 2040 (of 69,330 in Table 24, for example, or 69,300 in Tables 25 and 26, with that small difference probably just rounding). So it does not appear that the tables were mislabeled, which was my first thought.

The full tables show the ridership between any two pairs of 22 defined Transit Analysis Zones (TAZs), in production/attraction format (which I will discuss below).  The 22 TAZs cover the entire Washington metro region, and are defined as relatively compact geographic zones along the Purple Line corridor and then progressively larger geographic areas as one goes further and further away.  They have seven TAZs defined along the Purple Line corridor itself (starting at the Bethesda zone and ending at the New Carrollton zone), but Northern Virginia has just two zones (where one, labeled “South”, also covers most of Southern Prince George’s County in Maryland).  See the map shown as Figure 4 on page 13 of the FEIS Travel Forecasts chapter for the full picture.  This aggregation to a manageable set of TAZs, with a focus on the Purple Line corridor itself, is reasonable.

The tables then show the forecast ridership between any two TAZ pairs.  For example, Table 16 says there will on average be 1,589 riders on all forms of transit each day in 2040 between Bethesda (TAZ 1, as a “producer” zone) and Silver Spring (TAZ 3, as an “attractor” zone).  But Table 22 says there will be 2,233 riders each day on average between these same two TAZs on the Purple Line alone.  This is impossible.  And there are many such impossibilities.  For the 49 possible pairs (7 x 7) for the 7 TAZs directly on the Purple Line corridor, more than half (29) have more riders on the Purple Line than on all forms of transit.  And for one pair, between Bethesda (TAZ 1) and New Carrollton (TAZ 7), the forecast is that there would be close to 12 times as many riders taking the Purple Line each day as would take all forms of public transit (which includes the Purple Line and more).

Furthermore, if one adds up all the transit ridership between these 49 possible pairs (where the totals are presented at the bottom of the tables; see the FEIS Travel Forecasts chapter), the total number of trips per day on all forms of transit sums to 29,890 among these 7 TAZs (Table 16), while the total for the Purple Line alone sums to 30,560 (Table 22).

How could such a mistake have been made?  One can only speculate, as the FEIS chapter had next to no description of the methods they followed.  One instead has to infer a good deal based on what was presented, in what sequence, and from what is commonly done in the profession to produce such forecasts.  This goes into fairly technical issues, and readers not interested in these details can skip directly to the next section below.  But it will likely be of interest at least to some, provides a short review of the modeling process commonly used to generate such ridership forecasts, and will be helpful to an understanding of the other two obvious errors in the forecasts discussed below.

To start, note that the tables say they are being presented in “production/attraction” format.  This is not the more intuitive “origin/destination” format that would have been more useful to show.  And I suspect that over 99% of readers have interpreted the figures as if they are showing travel between origin and destination pairs.  But that is not what is being shown.

The production/attraction format is an intermediate stage in the modeling process that is commonly used for such forecasts.  That modeling process is called the “four-step model”.  See this post from the Metropolitan Washington Council of Governments (MWCOG) for a non-technical short description, or this post for a more academic description.  The first step in the four-step model is to try to estimate (via a statistical regression process normally) how many trips will be “produced” in each TAZ by households and by businesses, based on their characteristics.  Trips to work, for example, will be “produced” by households at the TAZ where they live, and “attracted” by businesses at the TAZ where those businesses are located.  The number of trips so produced will be forecast based on some set of statistical regression equations (with parameters possibly taken from what might have been estimated for some other metro area, if the data does not exist here).  The number of trips per day by household will be some function of average household size in the TAZ, average household income, how many cars the households own, and other such factors.  Trips “attracted” by businesses in some TAZ will similarly be some function of how many people are employed by businesses in that TAZ, perhaps the nature of the businesses, and so on.  Businesses will also “produce” their own trips, for example for delivery of goods to other businesses, and statistical estimates will be made also for such trips.

Such estimates are unfortunately quite rough (statistical error is high), and the totals calculated for the region as a whole of the number of trips “produced” and the number of trips “attracted” will always be somewhat different, and often far different.  But by definition the totals have to be the same, as all trips involve going from somewhere to somewhere. Hence some scaling process will commonly be used to equate the totals.

This will then yield the total number of trips produced in each TAZ, and the total number attracted to each TAZ.  But this does not tell us yet the distribution of the trips.  That is, one will have the total number of trips produced in TAZ 1, say, but not how many go from TAZ 1 to TAZ 2 or to TAZ 3 or to TAZ 4, and so on.  For this, forecasters generally assume the travel patterns will fit what is called a “gravity model”, where it is assumed the trips from each TAZ will be distributed to the “attractor” TAZs in some statistical relationship which is higher depending on the “mass” (i.e. the number of jobs in some TAZ) and lower depending on the distance between them (typically measured in terms of travel times). This is also rough, and some iterative rescaling process will be needed to ensure the trips produced in each TAZ and attracted to each TAZ sum to the already determined totals for each.

This all seems crude, and it is.  Many might ask why not determine such trip distributions from a straightforward survey of households asking where they travel to.  Surveys are indeed important, and help inform what the parameters of these functions might be, but one must recognize that any practicable survey could not suffice.  The 22 TAZs defined for the Purple Line analysis were constructed (it appears; see below) from a more detailed set of TAZs defined by the Metropolitan Washington Council of Governments.  But MWCOG now identifies 3,722 separate TAZs for the Washington metro region, and travel between them would potentially involve 13.9 million possible pairs (3,722 squared)!  No survey could cover that.  Hence MWCOG had to use some form of a gravity model to allocate the trips from each zone to each zone, and that is indeed precisely what they say they did.

At this point in the process, one will have the total number of trips produced by each TAZ going to each TAZ as an attractor, which for 2040 appears as Table 8 in the FEIS chapter. This covers trips by all options, including driving.  The next step is to separate the total number of trips between those taken by car from those taken by transit, and then, at the level below, the separation of those taken by transit into each of the various transit options (e.g. Metrorail, bus, commuter rail, and the Purple Line in the scenario where it is built). This is the mode choice issue, and note that these are discrete choices where one chooses one or the other.  (A combined option such as taking a bus to a Metrorail station and then taking the train would be modeled as a separate mode choice.)  This separation into various travel modes is normally then done by what is called a nested logit (or logistic) regression model, where the choice is assumed to be a function of variables such as travel time required, out of pocket costs (such as for fares or tolls or parking), personal income, and so on.

Up to this stage, the modeling work as described above would have been carried out by MWCOG as part of its regular work program (although in the scenario of no Purple Line). Appendix A of the FEIS Travel Forecasts chapter, says specifically that the modelers producing the Purple Line ridership forecasts started from the MWCOG model results (Round 8.0 of that model for the FEIS forecasts).  By aggregating from the TAZs used by MWCOG (3,722 currently, but possibly some different number in the Round 8.0 version), to the 22 defined for the Purple Line work, the team doing the FEIS forecasts would have been able to arrive at the table showing total daily trips by all forms of transportation (including driving) between the 22 TAZs (Table 8 of the FEIS chapter), as well as the total trips by some form of transit between the 22 in the base case of no Purple Line being built (the “No Build” alternative; Table 14 of the FEIS chapter).

The next step was then to model how many total transit trips would be taken in the case where the Purple Line has been built and is operating in 2040, as well as how many of such transit trips will be taken on the Purple Line specifically.  The team producing the FEIS forecasts would likely have taken the nested logit model produced by MWCOG, and then adjusted it to incorporate the addition of the Purple Line travel option, with consequent changes in the TAZ to TAZ travel times and costs.  At the top level they then would have modeled the split in travel between by car or by any form of transit, and at the next level then modeled the split of any form of transit between the various transit options (bus, Metrorail, commuter rail, and the Purple Line itself).

This then would have led to the figures shown in Table 16 of the FEIS chapter for total transit trips each day by any transit mode (with the Purple Line built), and Table 22 for trips on the Purple Line only.  Portions of those tables are shown above.  They are still in “production/attraction” format, as noted in their headings.

While understandable as a step in the process by which such ridership forecasts are generated (as just described), trips among TAZs in production/attraction format are not terribly interesting in themselves.  They really should have gone one further step, which would have been to convert from a production/attraction format to an origin/destination format.  The fact that they did not is telling.

As discussed above, a production/attraction format will show the number of trips between each production TAZ and each attraction TAZ.  Thus a regular commute for a worker from home (production TAZ) to work (attraction TAZ) each day will appear as two trips each day between the production TAZ and the attraction TAZ.  Thus, for example, the 1,589 trips shown as total transit trips (Table 16) between TAZ 1 (Bethesda) and TAZ 3 (Silver Spring) includes not only the trips by a commuter from Bethesda to Silver Spring in the morning, but also the return trip from Silver Spring to Bethesda in the evening.  The return trip does not appear in this production/attraction format in the 4,379 trips from Silver Spring (TAZ 3) to Bethesda (TAZ 1) element of the matrix (see the portion of Table 16 shown above).  The latter is the forecast of the number of trips each day between Silver Spring as a production zone and Bethesda as an attractor.

This is easy to confuse, and I suspect that most readers seeing these tables are so confused.  What interests the reader is not this production/attraction format of the trips, which is just an intermediate stage in the modeling process, but rather the final stage showing trips from each origin TAZ to each destination TAZ.  And it only requires simple arithmetic to generate that, if one has the underlying information from the models on how many trips were produced from home to go to work or to shop or for some other purpose (where people will always then return home each day), and separately how many were produced by what they call in the profession “non-home based” activities (such as trips during the workday from business to business).

I strongly suspect that the standard software used for such models would have generated such trip distributions in origin/destination format, but they are never presented in the FEIS Travel Forecasts chapter.  Had they been, one would have seen what the forecast travel would have been between each of the TAZ pairs in each of the two possible directions. One would probably have observed an approximate (but not necessarily exact) symmetry in the matrix, as travel from one TAZ to another in one direction will mostly (but not necessarily fully) be matched by a similar flow in the reverse direction, when added up over the course of a day.  For that reason also, the row totals will match or almost match each of the column totals.  But that will not be the case in the production/attraction format.

That the person writing up the results for this FEIS chapter did not understand that an origin/destination presentation of the travel would have been of far greater interest to most readers than the production/attraction format is telling, I suspect.  They did not see the significance.  Rather, what was written up was mostly simply a restatement of some of the key numbers from the tables, with little to no attempt to explain why they were what they were.  It is perhaps then not surprising that the author did not notice the impossibility of the forecast ridership between many of the TAZ pairs being higher on the Purple Line alone (Table 22) than the total ridership on all transit options together (Table 16).

C.  User Benefits and Time Savings

The modeling exercise also produced a forecast of “user benefits” in the target year. These benefits are measured in units of time (minutes or hours) and arise primarily from the forecast savings in the time required for a trip, where estimates are made as to how much less time will be required for a trip if one has built the light rail line.  I would note that there are questions as to whether there would in fact be any time savings at all (light rail lines are slow, particularly in designs where they travel on streets with other traffic, which will be the case here for much of the proposed route), but for the moment let’s look at what the modelers evidently assumed.

“User benefits” then include a time-value equivalent of any out-of-pocket cost savings (to the extent any exists; it will be minor here for most), plus a subjective premium for what is judged to be the superior quality of a ride on a rail car rather than a regular bus. The figures in the AA/DEIS (see Table 6-2 in Chapter 6) indicate a premium of 19% was added in the case of the medium light rail alternative – the alternative that evolved into what is now the Purple Line.  The FEIS Travel Forecasts chapter does not indicate what premium they now included, but presumably it was similar.  User benefits are thus largely time savings, with some markup to reflect a subjective premium.

Forecast user benefits are important for two reasons.  One is that it is such benefits which are, to the extent they in fact exist, the primary driver of predicted ridership on the Purple Line, i.e. travelers switching to the Purple Line from other transit options (as well as from driving, although the forecast shifts out of driving were relatively small).  Second, the forecast user benefits are also important as they provide the primary metric used to estimate the benefit of building the Purple Line. Thus if the inputs used to indicate what the time savings would be by riding the Purple Line as opposed to some other option were over-estimated, one will be both over-estimating ridership on the line and over-estimating the benefits.

And it does appear that those time savings and user benefits were over-estimated.  Table 23 of the FEIS chapter presents what it labels the “Minutes of User Benefits per Project Trip”.  A screenshot of the upper left corner, focussed on the travel within the 7 TAZs through which the Purple Line would pass, is:

Note that while the author of the chapter never says what was actually done, it appears that Table 23 was calculated implicitly by dividing the figures in Table 21 of the FEIS Travel Forecasts chapter (showing calculated total hours of time savings daily for each TAZ pair) by those in Table 22 (showing the number of daily trips on the Purple Line, the same table as was discussed in the section above).  This would have been a reasonable approach, given that the time savings figures include that saved by all the forecast shifts among transit alternatives (as well as from driving) should the new rail line be built.  The Table 23 numbers thus show the overall time saved across all travel modes, per Purple Line trip.

But the figures are implausible.  Taking the most extreme cases first, the table says that there would be an average of 582 minutes of user benefits per trip for travel on the Purple line between Bethesda (TAZ 1) and Riverdale Park (TAZ 6), and 691 minutes per trip between Bethesda (TAZ 1) and New Carrollton (TAZ 7).  This works out to user benefits per trip of 9.7 hours and 11.5 hours respectively!  One could walk faster!  And this does not even take into account that travel between Bethesda and New Carrollton would be faster on Metrorail (assuming the system is still functioning in 2040).  The FEIS Travel Forecasts chapter itself, in its Table 6, shows that Metrorail between these two stations currently requires 55 minutes.  That time should remain unchanged in the future, assuming Metrorail continues to operate.  But traveling via the Purple Line would require 63 minutes (Table 11) for the same trip.  There would in fact be no time savings at all, but rather a time cost, if there were any riders between those two points.

Perhaps some of these individual cases were coding errors of some sort.  I cannot think of anything else which would have led to such results.  But even if one sets such individual cases aside, I find it impossible to understand how any of these user benefit figures could have followed from building a rail line.  They are all too large.  For example, the FEIS chapter provides in its Table 18 a detailed calculation of how much time would be saved by taking a bus (under the No Build alternative specifically) versus taking the proposed Purple Line.  Including average wait times, walking times, and transfers (when necessary), it found a savings of 11.4 minutes for a trip from Silver Spring (TAZ 3) to Bethesda (TAZ 1); 2.6 minutes for a trip from Bethesda (TAZ 1) to Glenmont (TAZ 9); and 8.0 minutes for a trip from North DC (TAZ 15) to Bethesda (TAZ 1).  Yet the minutes of user benefits per trip for these three examples from Table 23 (see the full table in the FEIS chapter) were 25 minutes, 19 minutes, and 25 minutes, respectively.  Even with a substantial premium for the rail options, I do not see how one could have arrived at such estimates.

And the figures matter.  The overall average minutes of user benefits per project trip (shown at the bottom of Table 23 in the FEIS chapter) came to 30 minutes.  If this were a more plausible average of 10 minutes, say, then with all else equal, the cost-effectiveness ratio would be three times worse.  This is not a small difference.

Importantly, the assumed figures on time savings will also matter to the estimates made of the total ridership on the Purple Line.  The forecast number of daily riders in 2040 of 68,650 (Table 22) or 69,300 (in other places in the FEIS chapter) was estimated based on inputs of travel times required by each of the various modes, and from this how much time would be saved by taking the Purple Line rather than some other option.  With implausibly large figures for travel time savings being fed in, the ridership forecasts will be too high.  If the time savings figures being fed in are far too large, the ridership forecasts will be far too high.  This is not a minor matter.

D.  Ridership by Line Segment

An important estimate is of how many riders there will be between any two station to station line segments, as that will determine what the system capacity will need to be.  Rail lines are inflexible, and completely so when, as would be the case here, the trains would be operated in full from one end of the line to the other.  The rider capacity (size) of the train cars and the spacing between each train (the headway) will then be set to accommodate what is needed to service ridership on what would be the most crowded segment.

Figure 10 of the FEIS Travel Forecasts chapter provides what would be a highly important and useful chart of ridership on each line segment, showing, it says, how many riders would (in terms of the daily average) arrive at each station, how many of those riders would get off at that station, and then how many riders would board at that station.  That would then produce the figure for how many riders will be on board traveling to the next station.  And one needs to work this out for going in each direction on the line.

Here is a portion of that figure, showing the upper left-hand corner:

Focussing on Bethesda (one end of the proposed line), the chart indicates 10,210 riders would board at Bethesda each day, while 19,800 riders would exit each day from arriving trains.  But how could that be?  While there might be a few riders who might take the Purple Line in one direction to go to work or for shopping or for whatever purpose, and then take an alternative transportation option to return home, that number is small, and would to some extent balance out by riders going in the opposite direction.  Setting this small possible number aside, the figures in the chart imply that close to twice as many riders will be exiting in Bethesda as will be entering.  They imply that Bethesda would be seeing its population grow by almost 9,600 people per day.  This is not possible.

But what happened is clear.  The tables immediately preceding this figure in the FEIS Travel Forecasts chapter (Tables 24 and 25) purport to show for each of the 21 stations on the proposed rail line, what the daily station boardings will be, with a column labeled “Total On” at each station and a column labeled “Total Off”.  Thus for Bethesda, the table indicates 10,210 riders will be getting on, while 19,800 will be getting off.  While for most of the stations, the riders getting on at that station could be taking the rail line in either direction (and those getting off could be arriving from either direction), for the two stations at the ends of the line (Bethesda, and at the other end New Carrollton) they can only go in one direction.

But as an asterisk for the “Total On” and “Total Off” column headings explicitly indicates, the figures in these two columns of Table 24 are in production/attraction format.  That is, they indicate that Bethesda will be “producing” (mostly from its households) a forecast total of 10,210 riders each day, and will be “attracting” (mostly from its businesses) 19,800 riders each day.  But as discussed above, one must not confuse the production/attraction presentation of the figures, with ridership according to origin/destination.  A household where a worker will be commuting each day to his or her office will be shown, in the production/attraction format, as two trips each day from the production TAZ going to the attraction TAZ.  They will not be shown as one trip in each direction, as they would have been had the figures been converted to an origin/destination presentation.  The person that generated the Figure 10 numbers confused this.

This was a simple and obvious error, but an important one.  Because of this mistake, the figures shown in Figure 10 for ridership between each of the station stops are completely wrong.  This is also important because ridership forecasts by line segment, such as what Figure 10 was supposed to show, are needed in order to determine system capacity.  The calculations depicted in the chart conclude that peak ridership in the line would be 21,400 each day on the segment heading west from the Woodside / 16th Street station (still part of Silver Spring) towards Lyttonsville.  Hence the train car sizes and the train frequency would need to be, according to these figures (but incorrectly), adequate to carry 21,400 riders each day. That is their forecast of ridership on the busiest segment.  The text of the chapter notes this specifically as well (see page 56).

That figure is critically important because the primary argument given by the State of Maryland for choosing a rail line rather than one of the less expensive as well as more cost-effective bus options, is that ridership will be so high at some point (not yet in 2040, but at some uncertain date not too long thereafter) that buses would be physically incapable of handling the load.  This all depends on whether the 21,400 figure for the maximum segment load in 2040 has any validity.  But it is clearly far too high; it leads to almost twice as many riders going into Bethesda as leave.  It was based on confusing ridership in a production/attraction format with ridership by origin/destination.

Correcting for this would lead to a far lower maximum load, even assuming the rest of the ridership forecasts were correct.  And at a far lower maximum load, there is even less of a case against investing in a far less expensive, as well as more cost-effective, system of upgraded bus services for the corridor.

E.  Other Issues

There are numerous other issues in the FEIS Travel Forecasts chapter which leads one to question how carefully the work was done.  One oddity, as an example and perhaps not important in itself, is that Tables 17 and 19, while titled differently, are large matrices where all the numbers contained therein are identical.  Table 17 is titled “Difference in Daily Transit Trips (2040 Preferred Alternative minus No Build Alternative) (Production/Attraction Format)”, while Table 19 is titled “New Transit Trips with the Preferred Alternative (Production/Attraction Format)”.  That the figures are all identical is not surprising – the titles suggest they should be the same.  But why show them twice?  And why, in the text discussing the tables (pp. 41-42), does the author treat them as if they were two different tables, showing different things?

But more importantly, there are a large number of inconsistencies in key figures between different parts of the chapter.  Examples include:

a)  New transit trips in 2040:  Table 17 (as well as 19) has that there would be 19,700 new transit trips daily in the Washington region in 2040, if the Purple Line is built (relative to the No Build alternative).  But on page 62, the text says the number would be 16,330 new transit trips in 2040 if it is built.  And Table B-1 on page 67 says there would be 28,626 new transit trips in 2040 (again relative to No Build).  Which is correct?  One is 75% higher than another, which is not a small difference.

b)  Total transit trips in 2040:  Table 16 says that there would be a total of 1,470,620 total transit trips in the Washington region in 2040 if the Purple Line is built, but Table B-1 on page 67 puts the figure at 1,683,700, a difference of over 213,000.

c)  Average travel time savings:  Table 23 indicates that average minutes of “user benefits” per project trip would be 30 minutes in 2040 if the Purple Line is built, but the text on page 62 says that average travel time savings would “range between 14 and 18 minutes per project trip”.  This might be explained if they assigned a 100% premium to the time savings for riding a rail line, but if so, such an assumed premium would be huge.  As noted above, the premium assigned in the AA/DEIS for the Medium Light Rail alternative (which was the alternative later chosen for the Purple Line) was just 19%.  And the 14 to 18 minutes figure for average time savings per trip itself looks too large. The simple average of the three representative examples worked out in Table 18 of the chapter was just 7.3 minutes.

d)  Total user benefit hours per day in 2040:  The text on page 62 says that the total user benefit hours per day in 2040 would sum to 17,175.  But Table B-5 says the total would come to 24,073 hours (shown as 1,444,403 minutes, and then divided by 60), while Table 21 gives a figure of 33,960 hours.  The highest figure is almost double the lowest.  Note the 33,960 hours figure is also shown in Table 20, but then shows this as 203,760 minutes (but should be 2,037,600 minutes – they multiplied by 6, not 60, for the conversion of hours to minutes).

There are other inconsistencies as well.  Perhaps some can be explained.  But they suggest that inadequate attention was paid to ensure accuracy.

F.  Conclusion

There are major problems with the forecasts of ridership on the proposed Purple Line.  The discussion above examined several of the more obvious ones.  There may well be more. Little explanation was provided in the documentation on how the forecasts were made and on the intermediate steps, so one cannot work through precisely what was done to see if all is reasonable and internally consistent.  Rather, the FEIS Travel Forecasts chapter largely presented just the final outcomes, with little description of why the numbers turned out to be what they were presented to be.

But the problems that are clear even with the limited information provided indicate that the correct Purple Line ridership forecasts would likely be well less than what their exercise produced.  Specifically:

a)  Since the Purple Line share of total transit use can never be greater than 100% (and will in general be far less), a proper division of transit ridership between the Purple Line and other transit modes will result in a figure that is well less than the 30,560 forecast for Purple Line ridership for trips wholly within the Purple Line corridor alone (shown in Table 22).  The corridor covers seven geographic zones which, as defined, stretch often from the Beltway to the DC line (or even into DC), and from Bethesda to New Carrollton.  There is a good deal of transit ridership within and between those zones, which include four Metrorail lines with a number of stations on each, plus numerous bus routes.  Based on the historical estimates for transit ridership (for 2005), the forecasts for total transit ridership in 2040 within and between those zones look reasonable.  The problem, rather, is with the specific Purple Line figures, with figures that are often higher (often far higher) than the figures for total transit use.  This is impossible.  Rather, one would expect Purple Line ridership to be some relatively small share (no more than a quarter or so, and probably well less than that) of all transit users in those zones.  Thus the Purple Line ridership forecasts, if properly done, would have been far lower than what was presented.  And while one cannot say what the precise figure would have been, it is a mathematical certainty that it cannot account for more than 100% of total transit use within and between those zones.

b)  The figures on user benefits per trip (Table 23) appear to be generally high (an overall average of 30 minutes) and sometimes ridiculously high (9.7 hours and 11.5 hours per trip in two cases).  At more plausible figures for time savings, Purple Line ridership would be far less.

c)  Even with total Purple Line ridership at the official forecast level (69,300), there will not be a concentration in ridership on the busiest segment of 21,400 (Figure 10).  The 21,400 figure was derived based on an obvious error – from a confusion in the meaning of the production/attraction format.  Furthermore, as just noted above, correcting for other obvious errors imply that total Purple Line ridership will also be far less than the 69,300 figure forecast, and hence the station to station loads will be far less.  The design capacity required to carry transit users in this corridor can therefore be far less than what these FEIS forecasts said it would need to be.  There is no need for a rail line.

These impossibilities, as well as inconsistencies in the figures cited at different points in the chapter for several of the key results, all suggest insufficient checks in the process to ensure the forecasts were, at a minimum, plausible and internally consistent.  For this, or whatever, reason, forecasts that are on their face impossible were nonetheless accepted and used to justify building an expensive rail line in this corridor.

And while the examination here has only been of the Purple Line, I suspect that such issues often arise in other such transit projects, and indeed in many proposed public infrastructure projects in the US.  When agencies responsible for assessing whether the projects are justified instead see their mission as project advocates, a hard look may not be taken at analyses whose results support going ahead.

The consequence is that a substantial share of the scarce funds available for transit and other public infrastructure projects is wasted.  Expensive new projects get funded (although only a few, as money is limited), while boring simple projects, as well as the maintenance of existing transit systems, get short-changed, and we end up with a public infrastructure that is far from what we need.