A simple calculation suggests that an individual would have to earn at least $363,000 a year for him or her to find the maglev ticket price worth the modest reduction in door-to-door travel time

A cartoon depicting area residents reacting to the ticket price for the proposed Baltimore Washington maglev.

Common sense tells us that few people would be willing to pay 40 to 80 dollars to save just 8 to 27 minutes. If common sense is right, then the advertised utility of a 17-billion-dollar project would evaporate. The project in question is the proposed Baltimore-Washington magnetic-levitation rail line known as “the maglev.” ^[1]

Here are the facts. In January 2021, the Federal Railroad Administration published the draft environmental impact statement for the proposed maglev. In this document, the agency stated that maglev customers would save on average 8 to 27 minutes of travel time, door to door. The agency also considered various options for the maglev’s ticket price but settled on $40 to $80 in the computer simulation that was used to forecast how many trips would be made on the maglev.[2]

Common sense suggests that only a small proportion of the population is wealthy enough to be willing to pay this much money to save so little time. US Census data and the calculation described in the present article suggest that no more than 4% of workers in the Baltimore-Washington region earn this much. Two percent is the most likely figure.

Background

The companies that want to build a maglev between Baltimore and Washington are trying to persuade elected officials and the public that the proposed maglev is for everyone, not just the rich. These companies are Baltimore Washington Rapid Rail (BWRR) and its parent company, The Northeast Maglev. On its website, BWRR states that the maglev would be “highly valued across all travel purposes and income segments.” The Northeast Maglev’s website states that the company is “looking in to innovative ways to make the train accessible to all.” ^[3]

The question of whether only the wealthy would ride the maglev is ignored in the Executive Summary of the draft environmental impact statement published by the Federal Railroad Administration. Buried in an appendix is a limp sentence on this subject: “higher income workers would be the most likely to use SCMAGLEV for commuting” (Appendix D4, pg. D-81). Then again, the draft impact statement also contains a sentence that implies that a majority of the region’s residents would find the maglev a good deal:

The ridership report assumes that about 70.0 percent of business travelers in the defined catchment area and 67.0 percent of non-business travelers, which includes those making personal trips as well as commuters, between Baltimore and Washington, D.C. would choose the SCMAGLEV service if it were available. (Chapter 4.6, pg. 4.6-3)

The anticipated SCMAGLEV services are estimated to reduce travel times by 8 to 27 minutes of travel time savings depending on the trip purpose and length under each of the Build Alternatives. (Appendix D4, pg. C-6)

Putting these two quotes together, the draft impact statement seems to imply that, among the people whose trip origin and destination are close enough to a maglev station that the maglev would save them 8 to 27 minutes, 67% of these people would earn enough money that they would be happy to buy a maglev ticket. If this is the correct interpretation of these two quotes, then the 67% figure seems too high given that a maglev ticket would cost $40 to $80 one way.

Complicating matters, it is unclear exactly what the 67% refers to because its description in the draft impact statement is so brief. The draft impact statement obtained the 67% figure from a ridership report written by the Louis Berger consulting company, but the public is not allowed to read that report. Many of the documents that underlie the draft impact statement are hidden from public view. For all we know, even the Louis Berger report does not adequately explain the meaning and derivation of the 67%.

With the air of a farce, the Federal Railroad Administration released a heavily redacted copy of the Louis Berger ridership report toward the end of the public-comment period on the draft impact statement. The redacted copy is a mere shell, completely hiding the numerical data and the text that would assist in interpreting the 67% figure and other aspects of the maglev’s ridership forecast.[4]

To generate a precise forecast of the fraction of the population that would make use of a proposed transportation facility, complicated analysis of carefully constructed surveys is required. It may involve mode-choice analysis of stated-preference surveys, to repeat the jargon used in the maglev’s draft environmental impact statement.[5]

But the calculation is much simpler if the goal is just an upper and lower bound on the fraction of the population that would find the travel cost and time-savings attractive. This calculation is simple enough to be performed on a hand-held calculator instead of requiring simulation software designed by a team of experts.[6]

The calculation described in the present article is this sort of reality check. Mathematical details and supporting data are provided in the appendix of the present article, which can be found in this PDF file.

Serving the 2%

Before estimating who would ride the maglev, one needs to take care of two preliminaries. First, one chooses an estimate for how much a traveler would be willing to pay to save time. A plausible approximation is that an individual is willing to pay for travel-time savings at a rate similar to the rate at which he or she earns money at his or her job. One variation or other of this idea is encountered in various transportation-modeling studies.

Second, one needs an estimate for the averages of two quantities. These quantities are the price difference and the door-to-door travel-time difference between riding the maglev and driving directly to the destination. The maglev would be more expensive than driving and in some cases faster depending on the location of the trip origin and destination. A range for the travel-time difference is stated in the draft impact statement: 8 to 27 minutes. Determining the price difference requires a little math.[7]

The price difference would be $33 to $73 for an individual traveling alone, with a family traveling together considered later. This estimate for an individual traveling alone comes from taking the $40-to-$80 per-person one-way maglev ticket price that is stated in the draft impact statement and subtracting the cost of driving. The per-vehicle cost of driving a car between Baltimore and Washington is about $7, and this estimate may be calculated from two numbers. Start with the draft impact statement where it states that typical car trips between the two cities are 39.6-miles long. Multiple that distance by AAA’s estimate of a typical car’s per-mile cost for gas and maintenance. One could use a somewhat different value than $7 for the cost of driving and the results would be essentially unchanged, as discussed in the appendix of the present paper.[8]

The middle of the above-mentioned range for the extra cost to ride the maglev is $53, and the middle of the time-savings range is 17.5 minutes.

Someone who finds it a fair deal to pay about $53 to save about 17.5 minutes would be demonstrating a willingness to pay $181.71 per hour. Such a person would most likely earn at least $181.71 per hour, which would mean an annual income of about $363,000. Annual income is about 2,000 times greater than hourly income.[9]

The Census Bureau reports that only about 2% of workers in the Baltimore-Washington region earn at least $363,000 a year. We can draw the conclusion that, for this reason, only about 2% of workers would choose to ride the maglev. As discussed in the appendix of the present article, only 2 to 3 percent of worker earn $363,000 a year in the Washington area and only 1 to 2 percent in the Baltimore area do so. Only 1% of US workers earn this much, which reduces the chance that the average visitor would find the maglev to be a prudent way to travel between Baltimore and Washington.

The just-described calculation for an individual traveler is shown schematically in the image below.

A schematic diagram of the calculation that shows only the wealthiest 2% of the population is likely to find the maglev ticket price worth the travel-time savings.

For a family traveling together, the picture is even less rosy than for an individual traveling alone. With more than one wage earner in many families, household income is often greater than individual income, but a family of four would need four maglev tickets. Few families would think that it was a good deal to save a few minute on a trip between Baltimore and Washington by paying $160–$320 for 4 maglev tickets instead of driving and paying about $7 for gas and car maintenance. As shown in the appendix of the present article, annual household income would have to be above $1.6 million for a family of four to consider the maglev reasonably priced under these conditions. Fewer than 1% of households earn this much in the Baltimore-Washington region.

The calculations in the present article have so far assumed that people are willing to pay for travel-time savings at a rate of 100% of their hourly income. The next section varies this assumed value of willingness to pay.

Willingness to Pay

By analyzing many surveys and traffic studies, transportation modelers have found that people are typically willing to pay no more than about 50% to 150% of their hourly income in order to save an hour of travel time.[10]

If one varies the traveler’s willingness to pay from 50% to 150%, then one arrives at a range of incomes at which the individual would see the maglev ticket price as worth the travel-time saved. The lower someone’s willingness to pay, the higher their income would need to be before the maglev would seem attractive to them. The range of incomes is $242,000 and $727,000, as worked out in the appendix of the present article.

If most Baltimore-Washington residents had a low willingness to pay for travel-time savings, it would result in under 1% of individual workers finding the maglev attractive in the Baltimore-Washington region. If most of the region’s residents had a high willingness to pay for travel-time-savings then approximately 4% of them would find the maglev an attractive option. Under no combination of assumptions would anywhere near a majority of the region’s residents earn enough that the maglev’s travel-time savings would, in their eyes, justify the maglev ticket price.

Serving the 2%, Kind of

In a sense, the 2% figure calculated in the present article overstates the market share of the proposed Baltimore-Washington maglev. The unmentioned issue is that the maglev would serve only a small portion of the region. In an article titled “The maglev would serve a small geographic area,” Kelley (2021) showed that the maglev’s three stations could save people travel time only on the small fraction of possible trips that happen to start and end fairly close to a maglev station.

Another approach to estimating the maglev’s maximum-possible market share is to look at commuter data from the US Census. The Census Bureau has determined that under 1% of the region’s workers commute between Baltimore and Washington to reach their job. This means that, even if the maglev could somehow capture all of these commuters, it would still be serving only 1% of the workforce.

The maglev would arbitrarily and disproportionally benefit the small fraction of the region’s wealthy who happen to make frequent trips between downtown Baltimore and Washington and whose trips just happen to start and end near maglev stations. The rest of the wealthy would be poorly served by the maglev.

To put this information together, one might say that the maglev serves 1% of the 2%. That is to say, the people who would use the maglev both would be rich (2% of the population) and would also be geographically lucky, i.e., part of the 1% or so of the region’s population who frequently travels between the two cities. ^[11]

Conclusion

The people who would ride the proposed Baltimore-Washington maglev would be drawn from the richest 2% of the region’s population. The calculation that supports this prediction has two steps. In the first step, the concept of “willingness to pay” is used to estimate the income that an individual would need before the maglev would seem like a good deal to them, given the maglev’s ticket price and travel-time savings. In the second step, the income distribution reported in the US Census is used to determine what percent of the region’s population earns this much.

Someone would have to earn at least $363,000 a year before the maglev’s travel-time savings would seem worth its ticket price. Only 2% of workers earn this much in the Baltimore-Washington region.

Varying a person’s willingness to pay for travel-time savings would result in a range for the minimum income needed for the maglev be an attractive option: an annual income of $242,000 to $727,000. Approximately 4% of workers in the Baltimore-Washington region reach the bottom of this income range and under 1% reach the top.

Broadly speaking, the people who would choose to ride the maglev would be more than mere millionaires. They would be earning another million dollars every few years.

While small, the 2% figure just described overstates the maglev’s market share in one sense. The 2% figure was calculated from the set of travelers contemplating a certain kind of trip. Specifically, a trip in which the maglev would save them time, door to door, compared to other travel options like driving directly to their destination. But few trips start and end close enough to a maglev station to fit in this category, as discussed in the article “The maglev would serve a small geographic area” (Kelley 2021). The maglev does not always save you time especially if you have to drive out of your way to reach the maglev station, wait for the train, and then find a ride from the final maglev station to your actual destination.

The Federal Railroad Administration has mostly avoided the question of what portion of the region’s population would make use of the maglev. One would hope, however, that elected officials would want to know if the proposed maglev would serve the region as a whole or if it would only serve a small number of wealthy people lucky enough to be living or working near one of the three maglev stations.

By remaining largely silent on this question, the Federal Railroad Administration has made it easier for maglev proponents to broadcast their message. Both before and after the draft impact statement was published, the website of Baltimore Washington Rapid Rail, the company that wants to build the maglev, has claimed that the maglev would be “highly valued” by “all income segments.”

References

AAA, 2020 Dec. 14: Your Driving Cost: 2020. 8 pp., https://newsroom.aaa.com/wp-content/uploads/2020/12/2020-Your-Driving-Costs-Brochure-Interactive-FINAL-12-9-20.pdf.

Boardman A. E, D. H. Greenberg, A. R. Vining, and D. L. Weimer, 2018: Cost-Benefit Analysis: Concepts and Practice. 5th ed., Cambridge Univ. Press, 594 pp.

EPA, 2019: The 2019 EPA Automotive Trends Report. 211 pp., https://nepis.epa.gov/Exe/ZyPDF.cgi?Dockey=P100YVFS.pdf. Page 5 states the average fuel economy of 25.1 miles per gallon for new cars.

Federal Railroad Administration, 2021 Jan.: Baltimore-Washington Superconducting MAGLEV Project Draft Environmental Impact Statement and Draft Section 4(f) Evaluation. 654 pages of text plus 3,053 pages of appendices, https://bwmaglev.info/index.php/project-documents/deis. Use the MacOS terminal command “mdls -n kMDItemNumberOfPages *.pdf” to count pages.

Gas Buddy, 2021: 120 month average retail price chart. web page, https://www.gasbuddy.com/charts. States the average price per gallon of gas in the US, Washington area, and Baltimore area.

Kelley, O. A., 2021 May 2: Maglev riders would come from the wealthiest 2% of the Baltimore-Washington population. blog post, Greenbelt Online blog, https://www.greenbeltonline.org/maglev-wealth/.

Kelley, O. A., 2021 March 25: The maglev would serve a small geographic area. blog post, Greenbelt Online blog, https://www.greenbeltonline.org/operating-the-maglev-would-increase-greenhouse-gas-emissions-federal-railroad-administration-finds/.

Khattak, A., A. Kanafani, and E. Le Colletter, 1994: Stated and reported route diversion behavior: Implications on the benefits of ATIS. research report, Institute of Transportation Studies, Univ. California, Berkeley, ISSN 1055-1425, 36pp., https://escholarship.org/uc/item/4fz4h20k.

Louis Berger, 2018 Nov. 08: Baltimore-Washington SCMAGLEV Project Final Ridership Report. As of April 2021, this document is unavailable to the public. Page 48 of this document states the 67% figure discussed in the present article according to the DEIS, Chapter 4.6, page 4.6-3, footnote 9.

Meyer, J. R., W. B. Tye, C. Winton, and J. A. Gomez-Ibanez, 1999: Essays in Transportation Economics and Policy: A handbook in honor of John R. Meyer. Brookings Institute Press, https://play.google.com/books/reader?id=MFhkehz-Ky0C&hl=en&pg=GBS.PA42. Page 42 cites McFadden, Travitie, and associates (1966, pg. 116).

Ortuzar, J., and L. G., Willumsen, 2011: Modeling Transportation. 4th ed., Wiley, 586 pp.

US Census Bureau, 2014: American Community Survey: Design and Methodology. 222 pp., https://www2.census.gov/programs-surveys/acs/methodology/design_and_methodology/acs_design_methodology_report_2014.pdf.

US Census Bureau, 2015: Table 4, Residence MCD/County to Workplace MCD/County Commuting Flows for the United States and Puerto Rico Sorted by Workplace Geography: 5-Year ACS, 2011-2015. An Excel spreadsheet for the entire country with over 594,000 rows. On the web page titled “2011–2015 5-year ACS commuting flows,” https://www.census.gov/data/tables/2015/demo/metro-micro/commuting-flows-2015.html.

US Dept. of Transportation, 2016: The Value of Travel Time Savings: Departmental Guidance for Conducting Economic Evaluations Revision 2 (2016 Update). 26 pp., https://www.transportation.gov/office-policy/transportation-policy/revised-departmental-guidance-valuation-travel-time-economic.

Whittington, D., and J. Cook, 2019: Valuing Changes in Time Use in Low- and Middle-Income Countries. J. Benefit-Cost Analysis, 10, 51–72, doi:10.1017/bca.2018.21. Earlier draft: Guidelines for Benefit-Cost Analysis, Working Paper #1, Benefit‐Cost Analysis Reference Case Guidance Project.

Willumsen, L., 2014: Better Traffic and Revenue Forecasting. Maida Vale Press, 258 pp.

Notes

[1] $15–17 billion construction cost: DEIS, Appendix D4, Table D4-8, pg. D-21; 8–27 minutes saved travel time: Appendix D4, pg. C-6; $40–$80 ticket price: Appendix D2, pg. D-107, D-108.

[2] The DEIS considered a maglev ticket price as low as $27 but determined the official ridership forecast based on a $40–$80 ticket price: Appendix D2, pg. D-107, D-108, “Final SCMAGLEV Fare Assumptions” section.

[3] BWRR: https://bwrapidrail.com; TNEM: northeastmaglev.com/.

[4] Page 48 of Louis Berger (2018 Nov 08) states the 67% figure, according to the DEIS, Chapter 4.6, page 4.6-3, footnote 9. The FRA released a heavily redacted copy of the Louis Berger report at bwmaglev.info/index.php/project-documents/deis, on 23 April 2021. The DEIS comment period runs January through May 24, 2021.

[5] Appendix D2, pg. C-105.

[6] This topic is discussed in Chapter 12 of Ortuzar and Willumsen (2011).

[7] 8–27 minutes saved travel time: Appendix D4, pg. C-6.

[8] 7.08 = 39.6 · 0.1787; 39.6 mile trip length: Appendix D4, Table D4-59, pg. E-82; $0.1787/mile for medium sedan: AAA 2020.

[9] $182 h^-1 = $53 · 60 min. h^-1 ÷ 17.5 min.

[10] The appendix of the present article discusses the use of this rule of thumb in the transportation-modeling field. The appendix can be found in this PDF file.

[11] The 2015 American Commuter Survey (ACS) of the US Census Bureau reported 1.829 million employed people in the following five jurisdictions: District of Columbia, Alexandria, Arlington County, City of Baltimore, and Baltimore County. The ACS also reported that 13,087 of these employed people either worked in Baltimore and lived in Washington or vise versa. See US Census Bureau 2014, 2015. These 5 jurisdictions are, to a first approximation, the geographic extent of the maglev ridership area as analyzed by Kelley (2021).

About the Author: Owen Kelley has a science background and in his free time, he enjoys exploring and writing about the forests around Greenbelt. In recent years, he has written several articles about the proposed Baltimore Washington maglev.

Disclaimer: Kelley is writing in his capacity as a individual citizen examining a non-partisan issue of interest to the public. If errors are suspected, please contact him at okelley@gmu.edu.