CALIFORNIA HIGH- SPEED PASSENGER 

RAIL

Project Estimates 

Could Be Improved to 

Better Inform Future 

Decisions

Report to Congressional Requesters

March 2013

GAO-13-304

United States Government Accountability Office

GAO
United States Government Accountability Office

Highlights of GAO-13-304, a report to 

congressional requesters 

March 2013 

CALIFORNIA HIGH-SPEED PASSENGER RAIL

Project Estimates Could Be Improved to Better 

Inform Future Decisions 

Why GAO Did This Study

The planned 520-mile California highspeed rail project, which would link 

San Francisco to Los Angeles, would

be designed to operate at speeds up to 

220 miles per hour. At an estimated 

cost of $68.4 billion (in year-ofexpenditure dollars), it is expected to 

be one of the most expensive

transportation projects undertaken in 

the United States. The Authority is

responsible for implementing the 

project and federal funding is being 

provided from the FRA’s High-Speed 

Intercity Passenger Rail program. GAO 

reviewed (1) the reliability of project 

cost estimates, (2) the reasonableness 

of revenue and passenger rail ridership 

forecasts, (3) the risks attendant with 

the project’s funding plan, and (4) the 

comprehensiveness with which the

project’s economic impacts were 

identified. 

GAO obtained documents from and 

conducted interviews with federal 

officials and officials from the Authority 

related to cost, financing, ridership and 

revenue modeling and estimation, and

business plans and analyses related to 

potential economic impacts. GAO also 

interviewed state and local officials as 

well as the project’s peer review group 

members.

What GAO Recommends

To produce reliable cost estimates, 

FRA should improve its guidance so it 

is in line with the best practices in 

GAO’s Cost Guide. The Department of 

Transportation did not agree or 

disagree with the recommendation but 

said, with further analysis, applying the 

Cost Guide would be feasible. The 

Authority said it will incorporate many 

of the report’s findings into future cost 

and ridership estimates.

What GAO Found

The California High-Speed Rail Authority (Authority) met some, but not all of the 

best practices in GAO’s Cost Estimating and Assessment Guide (Cost Guide) for 

producing cost estimates that are accurate, comprehensive, well documented,

and credible. By not following all best practices, there is increased risk of such 

things as cost overruns, missed deadlines, and unmet performance targets. The 

Authority substantially met the criteria for the accurate characteristic by, for 

example, the cost estimate’s reflecting the current scope of the project. However, 

the Authority partially met the criteria for the other three characteristics since the 

operating costs were not sufficiently detailed (comprehensive), the development 

of some cost elements were not sufficiently explained (well documented), and 

because no systematic assessment of risk was performed (credible). The 

Federal Railroad Administration (FRA) issued limited guidance for preparing cost 

estimates, and this guidance did not reflect best practices in the Cost Guide. The 

Authority plans to improve its cost estimates. 

GAO found the Authority’s ridership and revenue forecasts to be reasonable; 

however, additional updates are necessary to refine the ridership and revenue 

model for the 2014 business plan. GAO also found the travel-demand-modeling 

process used to generate these forecasts followed generally accepted traveldemand-modeling practices. For example, the Authority revised several 

assumptions, such as gasoline price forecasts, to reflect changes in current and 

anticipated future conditions. However, additional updates, such as the 

development of a new travel survey, will be necessary to further refine these 

forecasts and improve the model’s utility to make future decisions. External peer 

review groups have also recommended additional updates.

The project’s funding, which relies on both public and private sources, faces 

uncertainty, especially in a tight federal and state budget environment. Obtaining

$38.7 billion in federal funding over the construction period is one of the biggest 

challenges to completing this project. In the latter stages, the Authority will also 

rely on $13.1 billion in private-sector financing, but will require more reliable 

operating cost estimates and revenue forecasts to determine whether, or the 

extent to which, the system will be profitable. The Authority’s plan recognizes the 

uncertainty of the current funding environment and is building the project in 

phases. The Authority has also identified an alternative funding source. However,

that funding source is also uncertain.

The Authority did a comprehensive job in identifying the potential economic 

impacts of the high-speed rail project. This includes identification of user impacts, 

such as effects on travel time reliability, and non-user impacts, such as effects on 

highway congestion. However, the nature of specific economic impacts will 

depend on a number of factors, including future project decisions. GAO also

found limitations in the Authority’s benefit-cost analysis of the project that could 

limit its usefulness to decision makers. Finally, GAO found that construction of 

the high-speed rail project will not eliminate the need for additional 

improvements to meet future statewide-travel demand, but current statewidetransportation assessments and planning have given little consideration to this 

issue.

View GAO-13-304. For more information, 

contact Susan Fleming at (202) 512-2834 or 

flemings@gao.gov
Page i GAO-13-304 California High Speed Rail 

Letter 1 

Background 5

Authority Substantially or Partially Met GAO’s Best Practices for 

Producing Reliable Cost Estimates, but Can Make Improvements 13

Ridership and Revenue Forecasts Are Reasonable for Current 

Purposes, but Will Require Updates 22

The Authority’s Funding Plan Faces Uncertainty 37

The Authority Comprehensively Identified Potential Economic 

Impacts, but It Is Too Early to Determine Specific Impacts 45

Conclusion 57

Recommendation 58

Agency Comments and Our Evaluation 59

Appendix I Objectives, Scope, and Methodology 64

Appendix II GAO Analysis of California High- Speed Rail

Authority’s Cost Estimates 72

Appendix III Description of Generally Accepted Travel-DemandModeling Practices and Authority’s Methods for 

Developing Ridership and Revenue Forecasts 78

Appendix IV Comments from the California High-Speed Rail Authority 82

Appendix V GAO Contact and Staff Acknowledgment 84

Tables

Table 1: Summary of GAO’s Assessment of California High-Speed 

Rail Authority’s Cost Estimates 16

Table 2: Description of Updated California High-Speed Rail TravelDemand-Model Assumptions 33

Contents 
Page ii GAO-13-304 California High Speed Rail 

Table 3: Funding Secured for Constructing the California HighSpeed Rail Project, as of February 2013 37

Table 4: The Authority’s Funding Plan for Constructing Phase 1 of 

the California High-Speed Rail Project, as of April 2012 39

Table 5: Primary Economic Impacts Associated with High-Speed 

Rail Identified by the Authority in the April 2012 Revised 

Business Plan, BCA, or EIA 48

Table 6: Organizations and Individuals Interviewed 65

Table 7: Guidance and Reports Used to Identify Generally 

Accepted Travel-Demand-Modeling Practices 68

Figures

Figure 1: Map of Planned California High-Speed Rail System and 

Key Construction Phases, 2013 6

Figure 2: Time Line of California High-Speed Rail Project 8
Page iii GAO-13-304 California High Speed Rail 

Abbreviations

AAPOR American Association for Public Opinion Research

ASC Aviation System Consulting, LLC

BCA benefit-cost analysis 

CTC California Transportation Commission 

DOT OIG Department of Transportation Office of Inspector General 

EIA economic impact analysis 

FHWA Federal Highway Administration 

FRA Federal Railroad Administration 

FTA Federal Transit Administration 

HSIPR High Speed Intercity Passenger Rail 

ICE independent cost estimate

IOS initial operating segment 

ITS Institute of Transportation Studies

LAO Legislative Analyst’s Office

LOS level of service 

MPO Metropolitan Planning Organization

MTC Metropolitan Transportation Commission 

NEC Northeast Corridor 

NEPA National Environmental Policy Act 

NOFA Notice of Funding Availability 

O&M operations and maintenance

OMB Office of Management and Budget 

PRG peer review group 

PRIIA Passenger Rail Investment and Improvement Act of 2008 

SCC Standard Cost Categories 

TIGER Transportation Investments Generating Economic Recovery

UIC International Union of Railways

WBS work breakdown structure

YOE year of expenditure

This is a work of the U.S. government and is not subject to copyright protection in the 

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Page 1 GAO-13-304 California High Speed Rail 

United States Government Accountability Office 

Washington, DC 20548

March 28, 2013

Congressional Requesters

California’s high-speed rail project is poised to be the first rail line in the 

United States designed to operate at speeds up to 220 miles per hour.1

 At 

an estimated cost of $68.4 billion (in year-of-expenditure dollars), it is 

expected to be one of most expensive transportation projects undertaken 

in the United States.2

Over the past two decades, there has been interest in developing highspeed rail between San Francisco and Los Angeles. Rail proponents 

argue that California faces significant transportation congestion and that 

high-speed rail can help alleviate the need to expand highway and air 

infrastructure. Proponents also argue that the corridor has characteristics 

that make high-speed rail viable: it connects highly populated 

metropolitan centers along a corridor that is currently highly traveled by 

air, rail, and automobile passengers. Opponents of the project argue that 

it is too expensive, especially with tight federal and state budgets, and 

has not sufficiently demonstrated that the project will be financially viable. 

As we reported in 2009, completing a high-speed rail project requires 

significant and sustained political, public, and financial support given the 

The Federal Railroad Administration (FRA) has 

obligated nearly $3.5 billion in grants to begin construction later this year. 

To complete the project, the state of California expects to rely on 

significant public-sector funding, in addition to private funding, through the 

project’s anticipated completion date in 2028.

 

1

The National Railroad Passenger Corporation’s (Amtrak) Acela service is currently the 

fastest passenger train service in the United States—it is capable of traveling at a 

maximum of 150 miles per hour but the average speed on the Washington, D.C., to 

Boston, Massachusetts, corridor is below 80 miles per-hour.

2

Estimates of the costs and revenues associated with the high-speed rail project appear in 

this report in two different formats: year of expenditure (YOE) and inflation adjusted 

dollars. YOE means the cost is presented in nominal dollars that reflect anticipated 

inflation over the period from the base year to the year in which a specific component of 

spending would take place. These estimates are also expressed in terms of current dollars 

in the base year of 2011, reversing the inflation adjustment used to calculate YOE dollars. 

The current dollar estimate will be lower than that expressed in YOE terms. Revenue 

estimates are expressed in current dollars in a base year. See appendix 1 for a discussion 

of the choice of methods for representing the costs of a project that spends out over a 

long period. Unless otherwise noted, all costs are presented in YOE dollars. 

 
 

Page 2 GAO-13-304 California High Speed Rail 

high costs and multiple stakeholders involved.3 In recent years, legislation 

has been enacted at the state and federal level that has allowed 

California’s project to move forward by appropriating funding for highspeed rail. In 2008, California’s voters approved a $9.95-billion bond 

measure, and in 2012, the state legislature appropriated over $4 billion 

from this bond to the project and connecting transit upgrades. At the 

federal level, the Passenger Rail Investment and Improvement Act of 

2008 (PRIIA) authorized development of high-speed intercity passengerrail corridors and the American Recovery and Reinvestment Act of 2009 

(Recovery Act) appropriated $8 billion to fund development of these 

corridors and intercity passenger-rail projects.4 In June 2009, the FRA 

established the High Speed Intercity Passenger Rail (HSIPR) program 

that provides discretionary grants for high-speed or intercity passenger 

rail projects. In December 2009, the Fiscal Year 2010 Department of 

Transportation (DOT) appropriations act appropriated $2.5 billion for the 

HSIPR program ($400 million of which was later rescinded).5

The California High-Speed Rail Authority (Authority)—a state agency 

formed in 1996—has been tasked with implementing the project and has 

published four successive business plans detailing the project’s cost 

estimates, financing plan, ridership projections, and anticipated economic 

impacts. Since 2009, the scope of the project has changed along with the 

project’s estimated costs. In addition, questions have been raised about 

how the project will be funded beyond the current $11.5 billion in state 

and federal funding commitments, as well as the project’s ability to attract 

sufficient ridership and bring economic benefits to the cities and 

communities along the corridor. This report assesses: (1) the reliability of 

the Authority’s estimates of the project’s costs, (2) the reasonableness of 

the Authority’s passenger rail ridership and revenue forecasts, (3) the 

risks attendant with the Authority’s funding plan for the project, and (4) the 

comprehensiveness with which the Authority identified potential economic 

impacts of the project. As such, we are assessing the quality of the 

 

3

GAO, High-Speed Rail: Future Development Will Depend on Addressing Financial and 

Other Challenges and Establishing a Clear Federal Role, GAO-09-317, (Washington, 

D.C.: Mar. 19, 2009).

4

Pub. L. No. 110-432, div. B, 122 Stat. 4848, 4960 (Oct. 16, 2008); Pub. L. No. 111-5, 123 

Stat. 115, 208 (Feb 17, 2009).

5

Pub. L. No. 111-117, div. A, 123 Stat. 3034, 3056 (Dec. 16, 2009); Pub. L. No. 112-110, 

§ 2222 (Apr. 15, 2011). 
 

Page 3 GAO-13-304 California High Speed Rail 

available information used by policymakers. We are not evaluating the 

merits of the project itself, which should be considered in light of whether 

this project best meets the transportation needs of the estimated 51 

million Californians in 2050.

We obtained information from numerous sources to address our 

objectives, including the models underlying the various estimates and 

interviews with Authority officials and contractors that prepared them, the 

peer review group members that reviewed them, outside critics and 

supporters, high-speed rail experts and FRA officials. We based our 

analysis on estimates underlying the Authority’s April 2012 revised 

business plan.

To assess the reliability of the project’s cost estimates, we compared the 

Authority’s cost estimating approach to GAO’s best practices found in the 

2009 GAO Cost Estimating and Assessment Guide (Cost Guide).6

 

6

GAO Cost Estimating and Assessment Guide: Best Practices for Developing and 

Managing Capital Program Costs, 

We 

used the Cost Guide to conduct an in-depth evaluation of the methods 

and assumptions used by the Authority to develop cost estimates of 

Phase 1 of the project; our goal was to determine whether best practices 

were employed that would help ensure that the cost estimates are welldocumented, comprehensive, accurate, and credible. The Cost Guide 

was developed for cost estimators to assist them in preparing reliable 

estimates of capital program costs. While GAO’s Cost Guide provides 

criteria to evaluate the Authority’s methods for developing its cost 

estimates, we cannot use it to determine whether or not the Authority’s 

cost estimate is precise. Nor can we use the Cost Guide to evaluate the 

benefits of this project in comparison to other transportation 

improvements. Such an evaluation would require a cost-benefit and other 

analyses, which we did not conduct as part of this work. To assess the 

reasonableness of the ridership and revenue estimates, we analyzed the 

extent to which the Authority’s ridership model methodology adhered to 

FRA guidance and generally accepted practices and reviewed peer 

review reports assessing the model’s methodology. We also interviewed 

Authority officials, their contractor, and peer review panel members. To 

assess the Authority’s financing plan, we reviewed the plan, conducted 

interviews with Authority and other state and federal officials, and 

reviewed literature and other information on financing for high-speed rail 

GAO-09-3SP, (Washington, D.C.: March 2009).
 

Page 4 GAO-13-304 California High Speed Rail 

projects in other countries as well as large transportation projects in the 

United States. To assess the comprehensiveness with which the 

Authority identified potential economic impacts of the project, we 

compared the impacts identified in the April 2012 revised business plan 

and related economic analyses prepared by the Authority with criteria for 

such assessments contained in DOT’s program-funding notices, 

applicable legislation, and best practices found in academic literature and 

federal guidelines. For purposes of this report, potential economic 

impacts include those impacts on users of a transportation system such 

as travel time savings and those impacts to non-users of a system such 

as highway congestion or noise levels. (For more detailed information on 

our objectives, scope, and methodology, see appendix I.)

We conducted this performance audit from February 2012 to March 2013 

in accordance with generally accepted government auditing standards. 

These standards require that we plan and perform the audit to obtain 

sufficient, appropriate evidence to provide a reasonable basis for our 

findings and conclusions based on our audit objectives. We believe that 

the evidence obtained provides a reasonable basis for our findings and 

conclusions based on our audit objectives.
 

Page 5 GAO-13-304 California High Speed Rail 

In 2008, California voters approved Proposition 1A,7 which authorized 

$9.95 billion in state bond funding for construction of the California highspeed rail system and connection improvements to existing passenger 

rail systems. Proposition 1A established several requirements for this 

high-speed rail system, such as that the rail system must be capable of 

sustained operating speeds of no less than 200 miles per hour, and once 

built, must operate without a public subsidy. The planned 520-mile highspeed rail system will operate between San Francisco and Los Angeles at 

speeds up to 220 miles per hour (see fig.1). The Authority is the state 

entity charged with planning, designing, and constructing the California 

high-speed rail system. The Authority has a nine-member policy board 

appointed by the California legislature and Governor, and a staff of 

approximately 55 state employees who oversee, among other things, 

contracts for environmental review, preliminary engineering design, 

preliminary right-of-way acquisition tasks,8 contractor oversight and other 

activities.9

 

7

Proposition 1A was codified in California law. See CAL. STS. & HIGH.. Code § 2704 et seq. 

(2012).

8

This project will construct new rail right-of-way to provide service, some of which may 

require acquisition of privately owned land.

9

Program management services and ridership-and-revenue-modeling services for the 

California high-speed rail project are generally carried out by consultants under contract 

with the Authority. Parsons Brinckerhoff is the consulting firm responsible for program 

management of the California high-speed rail system. In addition, the Authority retained 

Cambridge Systematics—a transportation-consulting firm that provides ridership and 

modeling forecast services—to develop a ridership and revenue model for the project. 

Background
 

Page 6 GAO-13-304 California High Speed Rail 

Figure 1: Map of Planned California High-Speed Rail System and Key Construction 

Phases, 2013 

Construction of the California high-speed rail project is expected to occur 

in phases beginning with a 130-mile section from just north of Fresno, 

California, to just north of Bakersfield, California. Construction will begin 

in the Central Valley and proceed to other portions of the corridor as 

funding is available. The Central Valley is the furthest advanced in terms 

of design and engineering work, as well as environmental reviews. For 

example, FRA approved a preferred route alignment for the Merced to 

Fresno, California, portion of the corridor in September 2012. According 

to FRA, the federally funded portion of the project in the Central Valley 

has more complete cost estimates than subsequent segments given that 
 

Page 7 GAO-13-304 California High Speed Rail 

has more complete cost estimates than subsequent segments given that 

preliminary engineering and environmental reviews are complete or 

nearly complete. Other project segments, however, are in different stages 

of development and have different levels of information from which to 

develop cost estimates. In July 2012, the California legislature 

appropriated $4.7 billion of the $9.95 billion in state bond funds, including 

$2.6 billion for construction of the high-speed rail project and $1.1 billion 

for upgrades in the San Francisco peninsula and in the Los Angeles basin 

(commonly referred to as the “bookends”).10 The process of acquiring 

property for the right-of-way and construction has begun. Requests for 

proposals to select construction contractors and right-of-way acquisition 

were issued in March and September 2012, respectively. In addition, in 

January 2013, the Authority awarded a project and construction 

management contract for the initial phase of California’s high-speed rail 

project. According to the Authority, a design-build contract for the first 

construction (covering approximately 30 miles) is expected to be awarded 

in June 2013 with construction planned to commence in summer 2013. 

(See fig. 2).

 

10An additional $819.3 million was appropriated by the state legislature for connectivity 

projects and $252.6 million for environmental, system design, and preliminary engineering 

work. 
 

Page 8 GAO-13-304 California High Speed Rail 

Figure 2: Time Line of California High-Speed Rail Project

a

The estimated construction date refers to the date for which construction of a segment is expected to be 

completed while the expected date of operations refers to the date for which a segment is expected to 

be operational. The estimated construction dates for the IOS and Phase 1 are 2021 and 2028, 

respectively, which differs from the estimated operational dates which are 2022 and 2029, respectively.

The federal government has committed funding to the project. The FRA 

awarded the state approximately $3.3 billion in capital construction funds 

and $231 million for environmental review and preliminary engineering 

work under the HSIPR program for a total of approximately $3.5 billion.11

 

11In addition, $400 million was awarded to the Transbay Joint Powers Board for 

construction at the Transbay Transit Center in San Francisco. Pursuant to Proposition 1A, 

the Transbay Transit Center is the northern terminus of the California high-speed rail line.

The California high-speed rail project is the largest recipient of HSIPR 

funds, with about 35 percent of program funds obligated. Most of the 

HSIPR money awarded to the project was appropriated by the Recovery 

Act and, in accordance with governing grant agreements, must be 
 

Page 9 GAO-13-304 California High Speed Rail 

expended by September 30, 2017.12

Even though some funding has been committed, additional funding will be 

needed to complete the project. For example, according to the Authority’s 

finance plan, over $38 billion in federal funds and over $4 billion from 

Proposition 1A proceeds will be needed to complete Phase 1 of the 

project. In addition, the Authority is also planning to obtain another $13.1 

billion in private-sector capital to help defray the cost of construction after 

the initial operating segment is completed in 2028.

In addition, approximately $945 

million in fiscal year 2010 funding was awarded to the project by FRA and 

is to remain available until expended. While the funds remain available 

until expended under FRA’s fiscal year 2010 appropriation, the governing 

grant agreements specify the schedule for expenditure of funds.

As the federal agency responsible for awarding and overseeing grants to 

HSIPR applicants, the FRA established guidance outlining requirements 

and procedures and developed an oversight program to ensure that the 

project’s goals, objectives, performance requirements, budgets, and other 

related program criteria are being met. Thus far, FRA’s guidance to 

HSIPR grant applicants has been limited with respect to developing cost 

estimates and ridership and revenue forecasts. The Department of 

Transportation’s Office of Inspector General (DOT OIG) noted that the 

lack of clear, detailed guidance allows for analyses of widely varying 

quality, making it difficult to accurately assess whether projects will be 

viable or require substantial financial support and has recommended FRA 

improve its guidance.13

 

12The grant agreement between FRA and the Authority was amended in December 2012. 

The amendment revised the schedule of federal and state cash flows so that federal 

Recovery Act funds would be expended in advance of state funds. According to FRA, the 

amendment would ensure Recovery Act funds are expended by September 2017 and lead 

to reduced construction costs through reduced design-build contract bids. The original 

grant agreement called for a 50/50 match between federal and state funds. FRA officials 

said the grant amendment maintains this match but on a different time frame.

In addition, we have previously reported that a 

clear definition of the federal role, goals, and objectives in conjunction 

13Department of Transportation Office of Inspector General, FRA Needs to Expand Its 

Guidance on High-Speed Rail Project Viability Assessments, CR-2012-083 (Washington, 

D.C.: Mar. 28, 2012).
 

Page 10 GAO-13-304 California High Speed Rail 

with a robust grant oversight program, is critical to FRA making sound 

federal investments in high-speed rail projects.14

The Authority is required to prepare and periodically submit to the state 

legislature a business plan, which must identify, among other things, 

ridership estimates, operating and maintenance costs, and the source of 

project funding.15 The Authority’s next business plan is expected to be 

released in 2014. Several groups have been established to review and 

comment on the estimates presented in the Authority’s business plans. For 

example, an independent peer review group (PRG) was established in 

accordance with California law to evaluate the Authority’s funding plans and 

report its judgment as to the feasibility and the reasonableness of the plans, 

appropriateness of assumptions, analyses and estimates, and any 

observations or evaluations it deems necessary.16 In addition, the Authority 

convened a Ridership and Revenue Peer Review Panel (Panel) to review 

the Authority’s ridership and revenue-forecasting process and outcomes and 

conduct an in-depth review of the models used to estimate ridership and 

revenue and the forecasts derived from them. The California state auditor is 

required to periodically audit the Authority’s use of bond proceeds.17

In response to the initial high estimated cost of building the San Francisco 

to Los Angeles route—about $98 billion—and other criticisms of the 

Authority’s November 2011 draft business plan, the project underwent 

substantial revision for the April 2012 revised business plan. Most 

significantly, the Authority scaled back its plans to build dedicated highspeed rail lines over the project’s entire length. Instead, the April 2012 

revised business plan adopted a “blended” system in which high-speed rail 

service would be provided over a mix of dedicated high-speed lines and 

existing and upgraded local rail infrastructure (entirely at the bookends of 

the system on the San Francisco peninsula and in the Los Angeles basin). 

The estimated cost in the April 2012 revised business plan is $68.4 billion.

 

14GAO, High Speed Passenger Rail: Learning from Service Start-Ups, Prospects for 

Increased Industry Investment, and Federal Oversight Plans, GAO-10-625 (Washington, 

D.C.: June 17, 2010).

15CAL. PUB. UTIL. CODE § 185033(a).

16CAL. PUB. UTIL. CODE § 185035(a), (c).

17CAL. STS. & HIGH. CODE § 2704.04(e). In April 2010 and January 2012, the California 

state auditor released two reports identifying several risks with the project including 

funding uncertainties and concerns about the Authority’s level of oversight of the project. 
 

Page 11 GAO-13-304 California High Speed Rail 

The ridership and revenue forecasts in the April 2012 revised business 

plan also changed from the November 2011 plan. For example, in the 

November 2011 draft business plan, the Authority provided low and high 

estimates of ridership in 2030 of 14.4 million and 21.3 million passengers. 

In the April 2012 revised business plan, these estimates increased by 12 

and 26 percent, respectively, to 16.1 million and 26.8 million. Revenues 

similarly increased between the two plans from a low and high estimate of 

$1.05 billion and $1.56 billion in the November 2011 plan18 to $1.06 billion 

and $1.81 billion in April 2012.19 The ridership and revenue estimates 

increased because among other things, a “one-seat” service from San 

Francisco to Los Angeles would begin sooner under the blended 

approach than the original solely dedicated lines approach. However, by 

2040 ridership forecasts under the blended approach are less than the 

original full build approach. The range between the high and low 

estimates also increased between the November and April plans 

reflecting a greater degree of uncertainty in the estimates. We have 

previously reported that forecasting ridership and revenue is a complex 

and iterative process and that early stage estimates should be based on 

the best available data and what is initially known about the proposed 

project.20

Development of the high-speed rail system has been controversial with 

many strongly held beliefs among the numerous supporters and opponents 

of the project. Supporters have cited the need for high-speed rail to 

address growing congestion concerns, particularly in the metropolitan 

areas, and to address future transportation demands. Supporters have 

noted that California’s expected population growth—which is expected to 

increase from 38 million in 2012 to an estimated 51 million Californians in 

2050—and economic growth will continue to place more demands on 

California’s transportation infrastructure requiring that significant new 

capacity be added to its transportation network. Further, supporters argue 

that the cost of expanding the current network of highways and airports to 

meet current and future transportation needs is cost prohibitive and would 

be detrimental to air quality and that high-speed rail will increase economic 

As additional information becomes available, the Authority’s 

model used to produce the forecasts is intended to be updated.

 

18These revenue forecasts are in 2010 dollars. 

19These revenue forecasts are in 2011 dollars. 

20GAO, High-Speed Passenger Rail: Preliminary Assessment of California’s Cost 

Estimates and Other Challenges, GAO-13-163T (Washington, D.C.: Dec. 6, 2012). 
 

Page 12 GAO-13-304 California High Speed Rail 

development in local communities to be served by high-speed rail and 

generate new jobs. In addition, supporters also note that several critical 

airport and highway expansions are infeasible due to land constraints, 

particularly at key airports and urban segments of highways. Opponents of 

the plan have argued, among other things, that the cost of the high-speed 

rail system is too great and that future funding for the system is too 

uncertain given the current fiscal environment. Opponents have also raised 

concerns about the credibility of the ridership and revenue forecasts 

presented in the Authority’s business plans and specifically, the system’s 

ability to attract the ridership levels needed to avoid public operating 

subsidies. Local communities and property owners in California’s Central 

Valley have also raised concerns about the project and its potential impact 

to the agriculture sector in the region. As we reported in our December 

2012 testimony, the Authority will face several challenges with acquiring 

rights-of-way in a timely manner, including potential construction delays as 

well as additional project costs.21 Timely right-of-way acquisition will be 

critical since some properties are in priority construction zones. Property to 

be acquired will include homes, businesses, and farmland. Not having the 

needed right-of-way could cause delays and add to project costs. There 

are a total of approximately 1,100 parcels to be acquired for the first 

construction segment; all of which are in California’s Central Valley. 

According to Authority officials, although the Authority may face challenges 

in acquiring right-of-way, they have built contingencies for time and cost 

into their acquisition plan.

 

21GAO-13-163T. 
 

Page 13 GAO-13-304 California High Speed Rail 

The Authority estimates that Phase 1 of the high-speed rail project in 

California will cost $68.4 billion to construct and hundreds of millions of 

dollars to operate and maintain annually.22 Since the project’s financing 

plan, as articulated in the April 2012 revised business plan, will depend 

on an additional estimated nearly $38.7 billion in federal funds, it is vital 

that the Authority, FRA, and Congress be able to rely on these cost 

estimates for project planning, funding, and oversight. In addition, 

because the value of potential private investment depends on the cost of 

operating the system, it is vital that the Authority and the private sector be 

able to rely on the operating cost estimate. Given that our past work on 

high-speed rail projects around the world has shown that projects’ cost 

estimates tend to be underestimated, ensuring the reliability of the 

estimates is critical to the success of this project.23

FRA provided limited guidance to grant applicants, including the 

Authority, about preparing cost estimates. FRA grant applicants were 

required to submit detailed capital cost estimates and high-level operating

cost estimates, but FRA did not provide guidance on how applicants 

 

22The Authority developed a low cost estimate and a high cost estimate based on various 

potential routes for the train within the seven construction sections between San Francisco 

and Los Angeles. The Authority developed the low cost estimate based on a sum of the 

lowest cost route alignments in each construction section and, similarly, the high cost 

estimate reflects a sum of the highest cost route alignments in each construction section.

The Authority then adjusted the 2011 cost estimates to calculate year-of-expenditure, or 

nominal dollars, using assumptions on expected inflation rates.

23GAO-09-317. 

Authority 

Substantially or 

Partially Met GAO’s 

Best Practices for 

Producing Reliable 

Cost Estimates, but 

Can Make 

Improvements

Reliable Cost Estimates 

Are Critical to Successful 

Project Planning, Funding, 

and Oversight, but Little 

FRA Guidance Is Available
 

Page 14 GAO-13-304 California High Speed Rail 

should produce these cost estimates to help ensure reliability. Moreover, 

the limited guidance that was provided did not reflect best practices 

included in our Cost Guide. FRA officials acknowledged that they 

specified the categories and types of costs to be estimated, not how 

applicants should prepare these cost estimates. FRA officials told us that 

they did not provide prescriptive guidance to grantees in preparing cost 

estimates because of the Recovery Act requirement to begin funding 

activities quickly following the enactment of the act in February 2009. In 

addition, FRA noted that the first two rounds of the HSIPR program were 

open to a wide range of project types and the level of detail necessary for 

an individual station is different from the level of detail necessary for a 

large, long-term corridor program like California.

According to FRA officials, the Authority’s application complied with the 

HSIPR grant application requirements. FRA found the cost estimates to be 

reasonable based on their comparison of the Authority’s cost estimates (on 

a unit cost basis) to other rail projects in the United States and abroad. The 

Authority and its contractor told us that, in the absence of specific guidance 

on preparing cost estimates, they relied on their professional experience 

supplemented by available cost-estimating guidance from the Federal

Transit Administration (FTA) which they thought was the most applicable 

guidance available. For example, since FRA’s guidance did not require the 

Authority to perform an independent cost estimate (this involves a 

comparison of the Authority’s original cost estimates to those performed by 

an independent entity), the Authority turned to FTA guidance to provide 

direction on how and when to conduct an independent cost estimate.

We evaluated the Authority’s cost estimates against GAO’s Cost Guide, 

which details best practices for generating high-quality cost estimates at 

all levels of government. While not required by FRA, the best practices 

identified in our Cost Guide help estimators develop reliable cost 

estimates, which have the four following characteristics:

• An accurate cost estimate is unbiased, not overly conservative or 

overly optimistic, and based on an assessment of most likely costs.

• A credible cost estimate discusses any limitations of the analysis from 

uncertainty or biases surrounding data or assumptions.

• A comprehensive cost estimate ensures that costs are neither omitted 

nor double counted.
 

Page 15 GAO-13-304 California High Speed Rail 

• A well-documented cost estimate is thoroughly documented, including 

source data and significance, clearly detailed calculations and results, 

and explanations for choosing a particular method or reference.

Ensuring that cost estimates reflect these four characteristics helps 

minimize the risk of cost overruns, missed deadlines, and unmet 

performance targets. The Cost Guide also provides criteria for evaluating 

cost estimates to determine whether they exhibit these characteristics. 

We have previously applied the Cost Guide in reviewing several 

transportation and infrastructure projects and we applied it in our review 

of the Authority’s cost estimates.24

The Authority substantially met best practices in our Cost Guide for 

producing accurate cost estimates, but only partially met our best 

practices for producing comprehensive, well documented, and credible 

estimates. By not following all best practices, there is increased risk of 

such things as cost overruns, missed deadlines, and unmet performance 

targets.

Our assessment of the Authority’s $68.4 billion construction and operating 

cost estimates for the high-speed rail project is summarized in table 1.

Our assessment is discussed in more detail in appendix 2.

 

24Examples of where we have applied the Cost Guide can be found in the following: GAO, 

Air Traffic Control Modernization: Management Challenges Associated with Program 

Costs and Schedules Could Hinder NextGen Implementation, GAO-12-223 (Washington, 

D.C.: Feb. 16, 2012); GAO, St. Lawrence Seaway: Estimates for the Asset Renewal 

Program Will Change, and Implementing Best Practices May Improve the Estimates’ 

Reliability, GAO-10-541R (Washington, D.C.: May 13, 2010); and, GAO, VA Construction:

VA Is Working to Improve Initial Project Cost Estimates, but Should Analyze Cost and 

Schedule Risks, GAO-10-189, (Washington, D.C.: Dec. 14, 2009).

Authority Substantially or 

Partially Met Best 

Practices in our Cost 

Guide for Producing 

Reliable Cost Estimates
 

Page 16 GAO-13-304 California High Speed Rail 

Table 1: Summary of GAO’s Assessment of California High-Speed Rail Authority’s 

Cost Estimates 

Characteristics of 

a reliable cost 

estimate Description of best practices GAO assessment

Accurate  Is based on most likely costs and is 

adjusted for inflation. 

 Is based on appropriate cost estimating 

techniques and contains minimal errors. 

 Reflects the current status of the project 

and has been updated with actual costs. 

 Is based on a historical record of cost 

estimating and comparable projects. 

Substantially met 

Comprehensive  Includes all project lifecycle costs such as 

construction, operation and maintenance. 

 Reflects the technical description of the 

project and is at an appropriate level of 

detail. 

 Reflects the ground-rules and 

assumptions of the project. 

Partially met 

Well documented Is supported by documentation that shows: 

 the source data and how they were 

adjusted, 

 the calculations and estimating 

methodology, 

 a description of how the estimate was 

created, 

 consistency with the technical baseline of 

the project, 

 review and approval from management. 

Partially met 

Credible Includes:

 sensitivity analysis (assessing the impact 

of cost drivers), 

 risk and uncertainty analysis (identifying 

and quantifying risk), 

 cross-checks on major cost elements, 

 an independent cost estimate. 

Partially met 

Source: GAO. 

Note: GAO assessed the extent to which the Authority’s project cost estimates met the best practices 

derived from the Cost Guide. The individual assessments are then used to determine an overall 

assessment for each characteristic. Assessments are made on a five-point scale: Not Met, Minimally 

Met, Partially Met, Substantially Met, and Fully Met. See Appendix 1 for a description of how we 

conducted our assessment and Appendix 2 for more detail on the complete assessment. 
 

Page 17 GAO-13-304 California High Speed Rail 

We found that the Authority substantially met best practices for 

developing accurate cost estimates. Consistent with best practices, the 

estimates reflect the new “blended” system, which will rely, in part, on 

existing rail infrastructure; they contained few, if any, mathematical errors; 

and they have been adjusted for inflation. Furthermore, the Authority’s 

contractor used a construction industry database of project costs 

supplemented with actual bid-price data from other transportation 

infrastructure projects. While the Authority generally complied with best 

practices for producing accurate cost estimates, we could not determine 

whether the estimates were unbiased. This was the only best practice 

related to accuracy where the Authority fell short. To help ensure an 

unbiased estimate, the Cost Guide recommends conducting a systematic 

analysis of the potential risks to the project and their likelihood of 

occurring—called a risk and uncertainty analysis. A risk and uncertainty 

analysis is also a best practice for developing a credible cost estimate as 

discussed below.

We found that the Authority partially met best practices for producing 

comprehensive cost estimates. For example, the Authority met the best 

practice for including in the cost estimates the major components of the 

project’s construction and operating costs. The construction cost estimate 

is based on detailed construction unit costs that are, in certain cases, 

more detailed than the cost categories required by FRA in its HSIPR 

grant application. However, the operating cost estimate was not as 

detailed as its construction cost estimate, as over half of the operating 

costs are captured in a single category called Train Operations and 

Maintenance. Authority officials told us that they developed their cost 

estimates consistent with FRA’s guidance which emphasized greater 

detail on the construction cost estimate and less detail on the operating

cost estimate.25

 

25The DOT OIG has since developed best practices for developing operating cost 

estimates for high-speed rail projects and has recommended that FRA update its 

guidance to HSIPR grantees. See DOT OIG, FRA Needs to Expand its Guidance on Highspeed Rail Project Viability Assessments, CR-2012-083 (Washington, D.C.: 

Mar. 28, 2012).

FRA officials confirmed that they emphasize construction 

cost estimates because HSIPR grants are required by federal law to only 

fund the capital costs of a project, not its operating costs. However, 

sufficiently comprehensive operating cost estimates are necessary to 

determine the potential profitability of California’s project, a key 

consideration to attracting private-sector investment in the project that the 

Accurate 

Comprehensive 
 

Page 18 GAO-13-304 California High Speed Rail 

Authority is counting on to help complete construction of the project. In 

addition, the Authority did not follow the best practice that calls for clearly 

describing certain assumptions underlying the construction and operating

cost estimates. For example, Authority officials told us that the California 

project will rely on proven high-speed rail technology from systems in 

foreign countries, but it is not clear how the cost estimates were adjusted 

for applying the foreign technology in California and how these 

adjustments are reflected in the complete project cost estimates. 

California requirements on the technology may differ in terms of speed or 

safety requirements from that of other systems. Authority officials said 

that they produced a thorough description of the technical requirements 

for high-speed rail, but we were unable to see how this document was 

linked to the cost estimates, that is, a description of how these technical 

requirements will impact the project cost estimates. Without 

comprehensive cost estimates, it is not possible to independently assure 

that all cost-influencing factors and assumptions were considered.

We found that the Authority partially met best practices for producing welldocumented cost estimates. In many cases, the methodologies used to 

derive the construction cost estimate were well documented, but in other 

cases, were more limited. For example, while track infrastructure costs 

($23.6 billion in 2011 dollars) were thoroughly documented, costs for 

other elements, such as building new stations and acquiring trains ($3.2 

billion in 2011 dollars), were not supported with sufficient documentation 

to identify how these costs were developed and what costs were included 

or excluded. Authority officials told us that since station locations and train 

technology are not yet finalized, they used a higher-level cost estimate. 

Additionally, we were unable to trace the estimates back to their source 

data and recreate the estimates using the stated methodology. For

example, we were unable to identify the basis for how the operating costs 

from analogous foreign high-speed rail projects were adjusted for use in 

California. Authority officials said that the operating cost estimate was 

used at a high level to determine whether or not the California system will 

operate with an operating surplus. Authority officials plan to refine the 

operating cost estimate as the project progresses. However, without more 

detailed documentation, the Authority’s cost estimates are more difficult to 

support and it may be harder to make changes to the estimates as they 

are revised since the basis of the original estimate may not be 

documented. In addition, without more thorough documentation, FRA and 

other oversight officials cannot replicate and evaluate what the Authority 

did to prepare its estimates and potentially exposes the project to 

possible cost overruns because the basis for costs are not known. 

Well Documented
 

Page 19 GAO-13-304 California High Speed Rail 

Estimates that lack documentation are not useful for updates or 

information sharing and can hinder understanding and proper use.

We found that the Authority partially met best practices to help ensure the 

credibility of its cost estimates. Those practices include:

• testing such estimates with a sensitivity analysis, such as assessing 

the effect of changes in key cost inputs;

• obtaining an independent cost estimate conducted by an unaffiliated 

party to see how outside estimates compare to the original estimates; 

and

• conducting risk and uncertainty analysis.

In regard to the construction cost estimates, the Authority performed a 

sensitivity analysis for the approximately first 30 miles of construction and 

obtained an independent cost estimate for the first 185 miles of 

construction in the Central Valley but neither covered the entire Los

Angeles to San Francisco project. And, as noted under the accuracy 

discussion, the Authority did not conduct a risk and uncertainty analysis 

on the cost estimates for any construction segment. Authority officials told 

us that in the absence of relevant FRA guidance, they followed FTA 

guidance for these types of evaluations. They noted that FTA guidance 

recommends conducting sensitivity tests once route alignments are 

selected and that, thus far, only 30 miles of the project meet those 

criteria. Similarly, Authority officials told us that they interpreted FTA 

guidance to require an independent cost estimate for those segments that 

have passed the 15 percent design milestone, which includes the first two 

construction segments from Merced to Fresno and Fresno to Bakersfield.

Because the Authority’s cost estimates cover both construction of the full 

system—from San Francisco to Los Angeles—and include operating 

costs, sensitivity analyses and independent cost estimates are more 

beneficial when they cover the entire project to help ensure greater 

credibility. The methodology of these tests can be altered to reflect the 

level of design, so a segment that has met a certain level of design can 

still be evaluated for credibility. Finally, as noted above, the Authority did 

not perform a risk and uncertainty analysis, which would improve the 

estimates’ credibility by identifying a range of potential costs and 

indicating the degree of confidence decision-makers can place on the 

cost estimates. For example, the Authority faces the potential challenge 

of acquiring rights-of-way in a timely manner. Authority officials told us 

there about 400 parcels in the first construction package, about 100 

Credible
 

Page 20 GAO-13-304 California High Speed Rail 

parcels of which are considered to be potentially at-risk for timely delivery 

for construction. However, without a risk and uncertainty analysis it is not 

possible to determine how the cost estimates might be affected by such 

things as delays in acquiring necessary rights-of-way or having to pay 

more for property to keep the project on schedule. 

Authority officials said that they did not conduct a risk and uncertainty 

analysis yet because FRA did not require one, and the FTA guidance to 

which they turned, recommends such an analysis after a final route 

alignment is selected. In addition, Authority officials told us that they 

added contingencies to the cost estimates to account for the risk of cost 

overruns. However, according to our Cost Guide, risk and uncertainty 

analysis—as with sensitivity analysis and independent cost estimates—

should cover the entire cost estimate and can be performed at varying 

levels of detail commensurate to the level of design. And, while 

contingencies are designed to cover potential cost overruns, based on 

our review, the Authority’s contingencies, which range from 10 to 25 

percent for various cost elements, were not calculated based on the 

results of a risk and uncertainty analysis (since this was not performed) 

but rather were based on professional judgment. Without a risk and 

uncertainty analysis, we cannot be assured that the contingencies are 

accurately calculated, and more importantly, what level of confidence we 

can have in the cost estimates.

For the operating cost estimate, the Authority conducted sensitivity tests 

under various ridership scenarios as recommended by the Panel; 

however, these tests were designed to measure the ability of the initial 

operating section to cover operating costs with ticket revenues and not to 

determine the potential risk factors that may affect the operating cost 

estimate itself. The Authority also did not compare its operating cost 

estimate to an independent cost estimate or conduct a risk and 

uncertainty analysis. The Authority told us that it views the sensitivity test 

already conducted as well as a forthcoming evaluation of operating costs 

by the International Union of Railways (UIC) as sufficient to meet these 

requirements. To make its operating cost estimate more comprehensive 

and better documented, the Authority has contracted with the UIC to 

evaluate the existing methodology and data and help refine the 
 

Page 21 GAO-13-304 California High Speed Rail 

Authority’s estimates.26 While the UIC’s evaluation will likely provide an 

expert review of the Authority’s operating cost estimates, it may not 

address some of the key practices that ensure credibility. For example, 

the UIC’s evaluation is not expected to result in new, independentlyproduced cost estimates that can be compared to the Authority’s original 

estimates.

The quality of any cost estimate can be improved as more information 

becomes available. And, based in part on evaluations from the PRG, the 

Authority is taking some steps to improve the cost estimates that will be 

provided in the 2014 business plan. As noted above, the Authority has 

contracted with the UIC to evaluate and provide recommendations on the 

Authority’s operating cost estimates. While the study will provide 

additional analysis from a reputable source, it may not address all best 

practices from the Cost Guide that would help ensure that the operating

cost estimate is comprehensive, accurate and credible.

Cost estimates should also be updated with actual costs so that they are 

always relevant and current. Continual updating of a cost estimate as a 

program matures not only results in a higher-quality estimate but also 

provides an opportunity to incorporate lessons learned. While the 

Authority was not able to incorporate actual costs because construction 

had not yet begun, it will have the opportunity once contracts are awarded 

and actual costs begin to incur for the initial construction in the Central 

Valley, which is expected to begin in 2013. The bids for the first 30-mile 

construction package have been submitted to the Authority and will 

provide a check on how well the Authority has estimated the costs for this 

work, as well as provide more information on its cost estimates for other 

segments of the project.27

 

26The Authority is mandated by state law to include in its 2014 business plan the results of 

a study by the UIC, examining how the estimated operating costs compares to rail 

systems in other countries. 

27The bids for the first construction project were not yet made public at the time this report 

was prepared.

Authority Can Make 

Improvements to Its Cost 

Estimates as the Project 

Progresses
 

Page 22 GAO-13-304 California High Speed Rail 

The Authority’s ridership and revenue forecasts to date are reasonable 

and the methods used to develop them followed generally accepted 

travel-demand-modeling practices. In addition, the Authority completed 

several updates to its ridership-and-revenue forecasting model after the 

release of the April 2012 revised business plan and also completed 

several sensitivity analyses to test the reasonableness of its model. 

However, the Authority will need to complete several additional updates 

to improve its model and the resulting forecasts for the 2014 business 

plan. Authority officials stated that they have plans in place to complete 

several critical updates, including completing a new travel preference 

survey and developing a second generation travel demand model, but will 

not be able to complete these improvements in time for the 2014 

business plan.

Based on our review, we found that the Authority’s methods and model 

used to produce its ridership and revenue forecasts adhere to generally 

accepted travel-demand-modeling practices. However, the Authority will 

need to complete several updates to improve these forecasts for the 2014 

business plan. In its April 2012 revised business plan, the Authority 

forecasts between 16.1 million and 26.8 million passengers per year and 

annual revenues of $1.06 billion to $1.81 billion in 2030. These forecasts 

were derived from a statewide ridership and revenue model, developed 

under contract to the Metropolitan Transportation Commission (MTC).28

Developing travel demand and revenue forecasts is difficult in almost 

every circumstance, across every mode and for a variety of reasons. As 

we have previously reported, limited data and information, especially 

early in a project before specific service characteristics are known, make 

developing reliable ridership and revenue forecasts difficult.29

 

28The Authority was a project participant with MTC. The primary objective of this work was 

to provide information for the development of the Bay Area Regional Rail Plan, and to 

provide information to update environmental analyses to be conducted by the Authority.

To the 

extent early stage data and information are available they need to be 

updated to reflect changes in the economy, project scope, and consumer 

preferences. In addition, risks of inaccurate forecasts are a recurring 

challenge for project sponsors. Research on ridership and revenue 

forecasts for rail infrastructure projects around the world have shown that 

ridership forecasts are often overestimated. Although forecasting is 

29GAO-13-163T. 

Ridership and 

Revenue Forecasts 

Are Reasonable for 

Current Purposes, but 

Will Require Updates

Forecasts Are Reasonable 

Based on Use of Accepted 

Travel-Demand-Modeling 

Practices, but Ridership 

and Revenue Model Will 

Require Additional 

Updates
 

Page 23 GAO-13-304 California High Speed Rail 

inherently risky, reliable ridership and revenue forecasts are critical to 

accurately estimate the financial viability of a high-speed rail project and 

determine what project modifications, if any, may be needed. Such 

forecasts enable policymakers and private entities to make informed 

decisions about the proposed project and to determine the associated 

risks when making investment decisions. In addition, ridership forecasts 

are critical because they serve as the basis for revenue forecasts. If the 

California high-speed rail project is unable to generate the necessary 

ridership and revenue to cover the system’s operating costs, the project 

may not be able to operate without a subsidy—as required by Proposition 

1A. Conversely, if forecasts are overly conservative, it could lead to the 

state capturing less value from private investment than warranted. As 

such it is critical that the Authority’s process for developing these 

forecasts is reliable and provides some assurance that the resulting 

forecasts provide a reasonable estimate of future demand for the system.

Unlike our cost estimating criteria discussed earlier, there is no industry 

standard or established criteria for developing or evaluating intercity 

passenger high-speed rail ridership forecasts. FRA has not established 

guidance on acceptable approaches to the development of reliable 

ridership and revenue forecasts and has established only minimal 

requirements and guidance related to information HSIPR grant applicants 

must provide regarding forecasts. We previously reported that developing 

guidelines, methods, and analytical tools to develop credible and reliable 

ridership forecasts is necessary to ensure equitable consideration of highspeed rail as a potential option to address demands on the nation’s 

transportation system.30 We recommended that the Secretary of 

Transportation develop guidance and methods for ensuring the reliability 

of ridership and other forecasts used to determine the viability of highspeed rail projects and support the need for federal grant assistance.31

 

30

The DOT OIG has also recommended that FRA develop specific and 

detailed guidance for the preparation of HSIPR ridership and revenue 

GAO-09-317. 

31We further recommended that the methods could include such things as independent, 

third-party reviews of applicable ridership and other forecasts, identifying and 

implementing ways to structure incentives to improve the precision of ridership and cost 

estimates received from grant applications, or other methods that can ensure a high 

degree of reliability of such forecasts.
 

Page 24 GAO-13-304 California High Speed Rail 

forecasts.32 According to FRA officials, they are in the process of 

developing an oversight plan that will include criteria for evaluating 

ridership forecasts. FRA officials indicated that they intend to use the 

DOT OIG’s HSIPR Best Practices: Ridership and Revenue Forecasting 

guide as a starting point for developing this guidance.33

For the purposes of our assessment, we identified generally accepted 

travel-demand-modeling practices for high-speed rail projects from a 

variety of sources and developed criteria based on these practices to 

assess the reasonableness of the approach used to create the ridership 

and revenue models for the California high-speed rail project.34 In 

developing our criteria, we relied primarily on a 2011 report, prepared for 

the DOT OIG’s office by the firm Steer Davies Gleave, on best practices 

related to travel demand modeling.35

 

32Department of Transportation OIG, FRA Needs to Expand Its Guidance on High-Speed 

Rail Project Viability Assessments, CR-2012-083 (Washington, D.C.: Mar. 28, 2012).

In addition, we also examined other 

literature on developing rail ridership and revenue forecasts to 

supplement information in the Steer Davies Gleave report. Specifically, 

we reviewed, among other sources, our prior GAO reports, Federal 

Highway Administration (FHWA) and FRA guidance, and academic 

literature. (See app. I for a list of guidance and reports we reviewed.) 

From our review of these reports and other sources, we identified 

common approaches to developing ridership and revenue forecast 

models and elements affecting the validity of those models. We identified 

seven key steps of the ridership-and-revenue forecasting process and 

then compared the Authority’s process for completing these tasks to 

generally accepted travel-demand-modeling practices. We found that the 

33Steer Davies Gleave, Ltd., prepared for the U.S. Department of Transportation, Office of 

Inspector General, High Speed Intercity Passenger Rail Best Practices: Ridership and 

Revenue Forecasting (April 2011). 

34Developing a ridership model involves many design decisions, assumptions, and inputs 

with varying degrees of impact on the resulting forecasts. Of necessity, we did not 

evaluate every design decision, assumption, and input, so our analysis was limited to a 

high-level evaluation of the major steps taken. For the purposes of our analysis, we 

assessed “reasonableness” of the Authority’s ridership and revenue forecasts by the 

extent to which the methodology used to generate these forecasts follows generally 

accepted practices for high-speed rail ridership modeling, and as such should be expected 

to produce generally plausible and defensible model results. A reasonable assessment 

indicates a level of confidence in the methods used to generate the ridership forecast and 

the resulting forecasts for decision-making purposes. 

35Steer Davies Gleave, High Speed Intercity Passenger Rail Best Practices, April 2011. 
 

Page 25 GAO-13-304 California High Speed Rail 

Authority followed generally accepted travel-demand-modeling practices 

for each of the seven key steps: (1) developing trip tables, (2) determining 

and applying service characteristics, (3) developing mode choice models, 

(4) estimating induced travel, (5) estimating expected fare revenue, 

(6) conducting sensitivity analysis, and (7) conducting validation testing. 

(For a detailed description of generally accepted travel-demand-modeling 

practices and the Authority’s process for completing each of these steps, 

see app.III). 

The Authority’s process for developing trip tables and collecting and 

compiling data on current travel patterns followed generally accepted 

practices. A central task of the ridership forecasting process involves 

collecting and compiling data on current travel patterns along the 

proposed high-speed rail route into trip tables.36 We found that the 

Authority followed generally accepted practices for developing trip tables. 

For example, trips were distinguished by mode of travel (auto, air, rail), 

trip purpose (commute, business, recreation, and other), and trip length 

(over and under 100 miles) as is general practice. Various data sources 

were used to develop the base year trip tables, including, among other 

sources, 2000 Census Bureau data, survey data from a 2005 travel 

survey37 and a 2011 long-distance travel survey conducted by Harris 

Interactive,38 and existing regional models used by metropolitan planning 

organizations (MPOs).39

 

36Trip tables summarize data on the number of trips by mode for each city pair along the 

proposed route. 

Overall, the data sources used for developing 

the trip tables were consistent with generally accepted standards. One 

potential limitation, however, is that the 2011 survey sample was not 

selected at random from among California residents but rather was 

limited to individuals who had opted to join an online survey panel. The 

37The 2005 survey was performed under contract to and under the direction of the MTC. 

The Authority was a “project participant” with the MTC. 

38The Authority subcontracted with Harris Interactive—a market research firm—to conduct 

the May 2011 long-distance travel survey. The survey data collected were used to verify 

whether travel characteristics had changed since the earlier survey. 

39The Authority used existing data from the Metropolitan Transportation Commission and 

Southern California Association of Governments. 

Developing Trip Tables
 

Page 26 GAO-13-304 California High Speed Rail 

American Association for Public Opinion Research (AAPOR)40

The Authority’s process for determining and applying service 

characteristics followed generally accepted practices; however, as 

detailed service plans are finalized or scenarios are changed, the model 

will need to be updated to reflect revised service characteristics. 

Ridership forecasts require information on the service characteristics 

(such as travel time and fares) of competing modes of travel, such as 

automobile and air travel along the proposed route. We found that the 

Authority collected and considered relevant service characteristics and 

used appropriate data sources. These included information on service 

characteristics of the interregional transportation modes in the area 

including information on time, cost, and other service characteristics for 

each mode—auto, conventional rail, and air—based on the most currently 

available published or observed data. High-speed rail service 

characteristics were defined based on the initial service plans and fare

structure because published or observed data do not exist. Some or all of 

the high-speed rail characteristics will likely change as service plans are 

finalized and engineering decisions are made, and those changes can 

significantly affect ridership and revenue forecasts. This was illustrated in 

a 2012 sensitivity analysis completed by the Authority in which service 

characteristics for the proposed high-speed rail system were adjusted to 

reflect reduced service on the San Francisco Peninsula, which is likely 

under the current “blended” approach whereby the high-speed rail system 

has 

recommended against the use of such panels, often called “opt-in” survey 

panels, when accurate population estimates are needed, due to concerns 

about data quality and the possibility that a panel may differ from the 

intended target population in unknown ways. Data were weighted to 

adjust for differences between the survey sample and the California 

population on four characteristics—geographic location, age, wealth, and 

employment status—but, the data may still not be representative of the 

California population in other characteristics related to travel behavior. 

 

40R. Baker, et. al., Public Opinion Quarterly, Prepared for the American Association for 

Public Opinion Research, AAPOR Report on Online Panels, October 20, 2010, 74(4): 

711-781. AAPOR is an association comprised of professionals working in the survey and 

public opinion research field on various topics such as election polling, market research, 

statistics, and research methodology. AAPOR produces work focused on developing, 

among other resources, best practices in collecting, analyzing, and interpreting survey 

data.

Determining and Applying 

Service Characteristics 
 

Page 27 GAO-13-304 California High Speed Rail 

will share tracks with Caltrain.41

While the Authority mostly followed generally accepted practices as well 

as used some more advanced techniques in its mode choice model 

development, peer and academic reviewers such as the California HighSpeed Rail PRG, the Panel, and academic experts from the University of 

California Berkeley’s Institute of Transportation Studies (ITS),

This adjustment reduced high-speed rail 

ridership and revenue forecasts by 11 percent and 13 percent, 

respectively, compared with forecasts in the April 2012 revised business 

plan. Updated representations of the base and forecast year level of 

service characteristics will be important for producing realistic ridership 

forecasts in the future.

42 have 

identified limitations with the survey data used to develop the mode 

choice model. “Mode choice models”—or travel behavior models—

illustrate how different variables such as income, travel time, and travel 

costs affect travel choices, including decisions about which mode of 

transportation to use. The reliability of the mode choice model estimates 

depends heavily on the quality of data used, which in turn depends on 

methods used to collect the data.43

 

41Caltrain is a commuter rail service on the San Francisco Peninsula. According to 

Authority officials, the purpose of this sensitivity analysis was to understand the impact of 

running less frequent services in the Peninsula in order to better address the capacity 

issues on the Caltrain corridor and potentially save capital costs. Two primary changes 

were made to service characteristics in this analysis. The first was a reduction in Caltrain 

service from 12 trains per hour in the peak periods to 6 trains per hour, and only 1 train 

per hour in the off-peak period. The second change was a modification to the high-speed 

rail operating plan whereby service from San Francisco Transbay Terminal to Los Angeles 

Union Station was reduced from 4 trains per hour to 2 trains per hour in the peak and offpeak periods. Service from San Jose to Los Angeles Union Station was increased from 2 

trains per hour to 3 trains per hour in the peak period. According to Authority officials, a 

high-speed rail service frequency of 4 trains per hour in the Peninsula is the service 

alternative currently being considered by the Authority and is identified in the April 2012 

revised business plan. A 2 trains per hour alternative has not been approved. 

These models can be based on 

traveler behavior observed in actual travel situations or self reported via a 

42Academic experts from the University of California Berkeley’s ITS conducted a review of 

ridership and revenue forecast models used to develop forecasts in June 2010 and

produced a report summarizing their findings. See D. Brownstone, M. Hansen, and S. 

Madanat, Review of Bay Area/California High-Speed Rail Ridership and Revenue 

Forecasting Study, University of California Berkeley’s Institute of Transportation Studies,

UCB-ITS-RR-2010-1, June 2010. 

43Some decisions, such as parameter adjustments, are made based on professional 

judgment and experience of forecast modelers and were not evaluated as part of our 

review. 

Developing a Mode Choice 

Model
 

Page 28 GAO-13-304 California High Speed Rail 

survey (revealed preference data), or on hypothetical situations presented 

to travelers in a survey (stated preference), or both.

There are advantages and disadvantages to using revealed preference 

and stated preference data. Revealed preference data provides 

information on travelers’ actual choices made in a specific market. 

However, according to the Steer Davies Gleave report, when collected 

from travel surveys, biases may exist in the respondents’ responses due 

to a desire of respondents to justify their chosen mode. In addition, since 

true high-speed rail does not exist in the U.S., it is not possible to use 

revealed preference alone to determine how American travelers would 

actually use high-speed rail. To address this problem, stated preference 

data have been used in high-speed rail studies to asses likely traveler 

responses to a new service. According to the Steer Davies Gleave report, 

while stated preference data can provide detailed information about a 

traveler’s likely responses to different modes or services that do not 

currently exist, this type of data may also exhibit bias; specifically, survey 

respondents may respond favorably to a hypothetical new mode, when in 

reality it may be more difficult to change habitual behavior. According to 

the Steer Davies Gleave report, limitations with each of these types of 

data can be mitigated by taking various steps such as by combining both 

revealed preference and stated preference data. The primary source of 

data for the Authority’s mode choice model was a revealed preference 

and stated preference survey, of air, rail, and auto trip passengers, 

conducted at airports, rail stations, and by telephone from August to 

November 2005. However, in its July 2011 and May 2012 reports to the 

Authority, the Panel reported that the Authority’s main mode choice model 

was based solely on stated preference responses, and recommended in 

its May 2012 report that the Authority collect new survey data and use 

both revealed and stated preference data in developing a new mode 

choice model. Authority officials stated that they are currently developing 

a new revealed preference and stated preference survey, which they plan 

to begin administering in early 2013. We discuss this survey in further 

detail in the next section.

In addition, academic experts from the University of California Berkeley’s 

ITS44

 

44D. Brownstone, M. Hansen, and S. Madanat, Review of Bay Area/California High-Speed 

Rail Ridership and Revenue Forecasting Study, University of California Berkeley’s 

Institute of Transportation Studies, UCB-ITS-RR-2010-1, June 2010.

have previously reviewed the ridership and revenue model and 
 

Page 29 GAO-13-304 California High Speed Rail 

have also identified limitations in the Authority’s method of applying a 

statistical model to the survey data. These data came from a choicebased sample, meaning that survey respondents were selected for having 

already chosen a mode of transport (air, rail, or auto). The Authority used 

a conventional method of applying a statistical model to such data, but a 

newer method has been identified in a recent research paper.45

The Authority followed generally accepted practices when producing 

induced travel estimates. Induced travel refers to trips that occur as a 

result of the high-speed rail project and that might not otherwise have 

been made using existing modes. In general, these are new trips that are 

generated because a new travel mode exists. The Authority estimated 

induced travel for the California high-speed rail project to be on average 2 

percent of total high-speed rail trips. According to the Steer Davies 

Gleave report, based on its review of forecasts of proposed U.S. highspeed rail systems, an upper limit on induced travel of approximately 10 

percent of total high-speed rail trips is widely accepted for proposed U.S. 

high-speed rail systems. Steer Davies Gleave also reviewed actual 

induced travel for high-speed rail systems outside the United States and 

found that it ranged from 6 to 27 percent. The Authority forecasted 

induced travel to be on average 2 percent. This estimate appears to be

conservative and reasonable when compared to proposed U.S. highspeed rail systems and actual induced travel for high-speed rail systems 

outside the United States.

According 

to some academic experts, the use of the latest method could be an 

improvement. The Panel also reviewed this issue in its May 2012 report 

and stated that while they do not see the non-use of this new method in 

the Version 1 model as an important defect, it is worth investigating this 

issue as the Authority continues to refine the travel demand model. 

The Authority followed generally accepted practices when estimating 

expected fare revenue for the California high-speed rail project. Expected 

fare revenue is a product of forecast ridership and average fares. Highspeed rail fares are based on a boarding fare and a per mile fare for 

interregional trips. For example, travel from Los Angeles to San Francisco 

would mean an average, one-way, high-speed rail fare of $81 in 2010 

dollars or 83 percent of average 2009 airfares from Los Angeles to San 

 

45M. Bierlaire, D. Bolduc, and D. McFadden, The Estimation of Generalized Extreme 

Value Models from Choice-based Samples. Transportation Research Board (2008) 42.

Estimating Induced Travel

Estimating Expected Fare 

Revenue 
 

Page 30 GAO-13-304 California High Speed Rail 

Francisco. Forecast ridership is impacted by high-speed rail fares and 

revenue is an output of the ridership and revenue model. According to the 

Authority, the annual number of riders needed to breakeven when the 

Phase 1 blended system is opened in 2029 is 6.1 million or 23 percent of 

the high forecast. Authority officials stated that they did not produce a 

revenue optimization forecast—that is, a ridership forecast that would 

maximize revenue—to produce these high-speed-rail fare estimates and 

acknowledged that they will need to do so in the future when meeting with 

potential private high-speed rail operators, which will establish their own 

revenue-maximizing fares for the system. According to the Authority, the 

Authority will not operate the high-speed rail system and a private 

operator is expected to serve as a contract operator of the system. As 

such, the private operator will be expected to assume all revenue risks of 

the project (including setting fares). The Authority’s process for 

calculating expected fare revenue adheres to generally accepted 

practices; however, as other factors and inputs change, total expected 

fare revenue will likely also change. For example, over time, it will be 

important for the Authority to monitor changes in airfares, gasoline prices, 

and other key assumptions and incorporate these changes, as necessary, 

into future revenue forecasts.

The Authority followed generally accepted practices when conducting 

sensitivity analysis of key model assumptions for the California highspeed rail project. A sensitivity analysis is typically conducted by varying 

key model assumptions such as socioeconomic data, type of trips taken, 

gasoline and auto fleet efficiency, and airfares, or parameter values to 

determine how the model behaves in response to changes to these 

assumptions. The Authority conducted several sensitivity analyses on its 

ridership and revenue model, most in 2011. For example, the Authority 

conducted sensitivity analyses that tested key factors, such as changes in 

fuel economy, air and auto travel time, air and auto travel costs, and highspeed rail travel time assumptions. In one analysis, the Authority tested 

the overall effect of a higher auto fuel economy and found that this 

change reduced ridership and revenue forecasts by 16 and 19 percent, 

respectively, from the Phase 1 high ridership and revenue forecasts 

presented in the November 2011 draft business plan. According to the 

Panel that reviewed these analyses, the results of the various sensitivity 

analyses that the Authority has conducted show that the model is 

appropriately sensitive across the range of variables tested.

In addition, the Authority performed a sensitivity analysis of an extreme 

downside scenario to test the ridership and revenue implications of a 

series of downside events, such as increased average rail travel time 

Conducting Sensitivity Analysis
 

Page 31 GAO-13-304 California High Speed Rail 

from Merced to the San Fernando Valley (140 minutes instead of 126 

minutes), decreased train frequency (3 trains per hour instead of 4 trains 

per hour during peak times), lower auto-operating costs, and lower air 

fares (10 percent below actual 2009 average air fares). Based on this 

analysis, the Authority determined that an extreme downside scenario 

would be expected to reduce ridership and revenue forecasts by 27 

percent and 28 percent, respectively, below that shown for the low IOS 

forecasts in the April 2012 revised business plan. According to the 

Authority, they tested these events using the IOS phase because the 

financial viability will be the most fragile during the early stages of 

ridership. According to the Authority, these forecasts are still sufficient to 

cover the Authority’s estimated operating costs and not require a public 

operating subsidy. Authority officials stated that they intend to conduct 

additional sensitivity analyses going forward.

The Authority mostly followed generally accepted practices to validate the 

ridership and revenue model. Model validation generally involves verifying 

that the model reflects observed traveler behavior including total travel, 

region-to-region travel flows, and observed market shares by mode. In 

the United States, without another high-speed rail system to use for 

comparison, model validation is a difficult task. Furthermore, validating 

the proposed California project with foreign high-speed rail systems is 

difficult because some of the travel market characteristics in other 

countries with high-speed rail, such as the cost of driving, may not be 

comparable. The Authority has taken some steps to validate the model 

through tests performed using data on Amtrak’s premium Acela service in 

the Northeast Corridor (NEC) as input to the California high-speed rail 

model and compared the output with 2008 actual ridership and 2030 NEC 

forecasts.46

 

46In 2012, ridership on Amtrak’s premium Acela service was nearly 3.4 million passengers 

and total ridership on the regional NEC service (Acela and non-Acela) was more than 8.0 

million passengers. 

The results of the Authority’s comparison of the California 

high-speed rail model with NEC input to actual 2008 ridership data 

showed that ridership in the California high-speed rail model with NEClike conditions in 2008 is 79 percent of actual 2008 NEC ridership. 

Similarly, the Authority’s comparison of the California high-speed rail 

system ridership forecasts from the model run with “NEC-like” service is 

about the same as projected 2030 ridership on the Acela service. 

Authority officials told us they believe the results from these tests 

demonstrate that the ridership and revenue model is reasonably sensitive 

Conducting Validation Testing
 

Page 32 GAO-13-304 California High Speed Rail 

to speed, frequency, and fares. While the NEC corridor has some 

comparable characteristics to the proposed California high-speed rail 

corridor—such that it is capable of reaching top speeds up to 150 miles 

per hour and covers a distance of over 400 miles—the proposed 

California high-speed rail corridor and the NEC differ in important ways. 

For example, population density,47

In developing the forecasts for the April 2012 revised business plan, the 

Authority also revised several model assumptions used in the initial 

ridership and revenue forecasts presented in the November 2011 draft 

business plan. Specifically, the Authority revised model assumptions to 

reflect changes in current and anticipated future conditions for airfares 

and airline service frequencies, decreases in gasoline price forecasts, 

and anticipated declines in the growth rates for population, number of 

households, and employment. Some of the initial assumptions were 

largely based on pre-2007 data and did not reflect potential effects of the 

2007 to 2009 recession. (See table 2 for a summary of updates that have 

thus far been completed.) According to Authority officials, this was done 

to build in additional conservatism in the ridership forecasts.

congestion, and travel behavior in the 

two corridors differ, and as such, forecast comparisons should be 

interpreted with caution.

 

47For example, the populations of cities along the NEC range from 0.3 to 18.8 million while 

the populations of cities along the Los Angeles to San Francisco corridor range from 0.1 to 

12.9 million. 
 

Page 33 GAO-13-304 California High Speed Rail 

Table 2: Description of Updated California High-Speed Rail Travel-Demand-Model Assumptions 

Model input assumptions Description of revised assumptions

Airfares and airline service frequencies • Authority updated the model to reflect changes in current and anticipated future 

airfares and airline service frequencies. Initially, the model reflected 2005 average 

fares and airline service frequencies—it was updated to reflect 2009 average fares 

and airline service frequencies.

• The Authority engaged Aviation System Consulting, LLC (ASC), a California-based 

expert firm to address these issues. ASC analyzed the past decade of U.S. 

Department of Transportation data on airline service and fare levels, explained the 

economic factors affecting airline responses to changes in competition and capacity, 

and helped determine scenarios of potential airline competitive response to the 

introduction of high-speed rail service.

Conventional rail service and fare 

assumptions

• Conventional rail service and fare assumptions for 2030 were updated to reflect 2011 

current and forecasted conditions.

• Authority updated the fare assumptions for all lines to on-line published fares in 2011. 

Revised automobile operating costs 

assumptions

• Gasoline price forecasts increased: The Authority adjusted its assumptions related to 

automobile operating costs to reflect the most recent forecasts from the U.S. Energy 

Information Administration, adjusted to reflect the historical difference between 

California prices and the national average.

• Vehicle fuel economy forecasts: To align with Corporate Average Fuel Economy 

standards, forecasts were revised to show an average of 3 percent to 6 percent fuel 

economy growth.

• 2030 auto operating forecasts: The Authority estimated a range for auto operating 

costs incorporating both fuel and nonfuel components. The Authority revised 2030 

operating costs for the 2012 revised business plan. The Authority used $0.20 per 

mile in 2011 dollars for the low model scenario and $0.28 per mile for the high model 

scenario.

Socioeconomic forecast updates The 2030 population, household, and employment forecasts used for the original ridership 

and revenue model were developed in 2006-2007 from local agency socioeconomic 

projections. The Authority developed two alternate forecasts of population, households, 

and employment to account for decreased expectations regarding future socioeconomic 

growth resulting from the 2007-2009 recession:

• High forecast: To develop the 2030 forecasts, the Authority purchased forecast data 

of county-level population, households and total employment for the state, for two 

years—2008 (pre-recession data) and 2011 (post-recession data). A combination of 

these data were used to account for pre- and post-recession impacts to factor 2030 

pre-recession forecasts.

• Low forecast: 2011 county-level forecasts of population, households, and 

employment by economic sector for the state were purchased and used to develop 

2030 forecasts.

Alternative trip frequency assumptions • The Authority developed a long-distance travel survey to collect current long-distance 

travel data to help provide perspective for the 2012 revised business plan.

• The Authority contracted with Harris Interactive for the data collection, and the survey 

was fielded in May 2011.

Source: California High-Speed Rail Authority information.
 

Page 34 GAO-13-304 California High Speed Rail 

Updating model assumptions can help mitigate of the risks of 

overestimating ridership and revenue forecasts—referred to as optimism 

bias. Biased ridership forecasts are a recurring problem with rail 

infrastructure projects and we have previously reported that forecasting 

ridership and revenue is a complex and uncertain process and ridership 

forecasts of high-speed rail projects are often overestimated.48 Other 

research on ridership and revenue forecasts for rail infrastructure projects 

have confirmed that actual ridership is likely to be lower than forecasted 

unless steps are taken to incorporate more conservative assumptions into 

the model. For example, a recent study examined a sample of 62 rail 

projects and found the ridership forecasts of 53 of them were overstated; 

actual ridership was, on average, 41 percent lower than forecasted.49

Updates to model inputs, such as fuel prices and other projections, are 

important for updating ridership forecasts for any project; in this instance, 

updates to model inputs resulted in more conservative ridership forecasts.

The Authority has plans to complete future improvements to its ridership 

and revenue forecasts, including completing a new travel preference 

survey and developing a second generation travel demand model. 

However, the Authority will not be able to complete these critical 

improvements in time for the 2014 business plan. According to Authority 

officials, the 2014 plan is expected to include, among other updates, 

updated ridership and revenue forecasts. Two critical updates to the 

ridership forecasts that peer reviewers and academic experts have 

recommended are the development of a new 2013 revealed and stated 

preference travel survey and a second generation travel demand model—

which will make use of the new survey. Although the Authority has begun 

taking steps to complete both of these tasks, neither the survey nor the 

second generation model will be completed in time for the 2014 business 

plan.

The Authority began work developing a new 2013 revealed and stated 

preference survey in late 2012. According to Authority officials, a survey 

sample and survey questionnaire design was initiated in December 2012. 

 

48GAO-09-317. 

49Bent Flyvbjerg, “Quality Control and Due Diligence in Project Management: Getting 

Decisions Right by Taking the Outside View,” International Journal of Project Management 

(Nov. 2012). 

Next Business Plan Will 

Not Reflect All Planned 

Improvements to 

Ridership Forecasts
 

Page 35 GAO-13-304 California High Speed Rail 

Data collection for the 2013 revealed preference and stated preference 

survey will not begin until 2013. Full data collection, cleaning, and 

preliminary analysis of results are expected to be completed by mid-April 

2013. The new survey will include a larger sample of 4,500 respondents 

compared with the 3,172 respondents to the 2005 survey. In addition, the 

revealed preference portion of the data set will be designed and coded to 

facilitate estimation using revealed and stated preference responses 

simultaneously, which was not done in the first version of the model. 

According to the Panel, development of a new survey is critical as it will 

address several long-term issues that can only be overcome with the 

collection and analysis of new survey data.

The Authority also has plans to develop a second-generation travel 

demand model; however, the second generation model will not be 

completed in time for the 2014 business plan. According to Authority 

officials, work on the second-generation model will not begin until the 

ridership and revenue analysis for the 2014 business plan is completed. 

According to the Authority, the second generation model will use data 

from the new 2013 revealed and stated preference survey to supplement 

data from the 2005 survey. In addition, the Authority plans to replace the 

2011 Harris Interactive long-distance travel survey data with data from the 

2012 California Household Travel Survey being conducted by the 

California Department of Transportation. According to Authority officials, 

both surveys will be needed for developing its second-generation travel 

demand model. The Panel, which has released five reports assessing the 

Authority’s ridership and revenue forecasts, has reported that the 

Authority’s ridership and forecasts to date are reasonable for planning 

purposes but has also stated that additional updates and enhancements, 

particularly the development of a new model, will be critical for future 

project decision making. For example, in its most recent October 2012 

report, the Panel stated that a second-generation model will be required 

to meet the Authority’s long-term goals of completing detailed planning 

studies and make key planning and operational decisions on issues such 

as specific rail alignments, station design requirements, and pricing 

strategies.

While the Authority will not be able to complete a second-generation 

travel demand model in time for the 2014 business plan, it has begun 

work on developing an enhanced model that will be used to produce the 

ridership and revenue forecasts for the 2014 business plan. The 

enhanced model will retain the same structure of the original model, but 

some of the individual model components will be updated. For example, 

the main mode choice model will use both revealed preference and stated 
 

Page 36 GAO-13-304 California High Speed Rail 

preference results from the 2005 travel survey. According to Authority 

officials, the enhanced travel demand model will be completed by 

May 31, 2013.

Even if the Authority is not able to complete the major ridership and 

revenue forecast improvements in time for the 2014 business plan, 

ongoing disclosure of interim results from model improvements both 

before and after the business plan are published will be important to 

outside reviewers and the public. Peer reviewers and other groups that 

have examined the Authority’s ridership and revenue forecasts have 

reported the need for greater transparency in the Authority’s analyses. 

For example, in its January 2012 report, the California State Auditor 

reported that the Authority’s November 2011 draft business plan lacked 

detail in its presentation of some of the revenue forecasts. Similarly, in its 

October 2012 report, the Panel advised the Authority to provide 

summaries on the Authority’s website, describing, among other things, 

recent forecasts, key input assumptions used to develop the forecasts 

(e.g., fuel price trends, socioeconomic growth rates, and changes in 

household size and structure), and updated service characteristic 

information. According to Authority officials, documentation supporting 

analysis in its 2014 draft business plan will be available on the Authority’s 

website when the plan is made public. In addition, Authority officials 

stated that the Authority has generally posted key technical documents as 

they are made public.

The Authority also has developed a work plan for other travel demand 

model improvements. This includes, among other things, plans to 

complete additional validation testing of model results using data from the 

NEC. For the 2014 business plan, the Authority is planning to conduct 

further testing and sensitivity analysis of the ridership and revenue 

forecasts to examine the sensitivity of the forecasts to reduced 

frequencies of services; changes in alternative fare structures (for 

example, premium fares for intra-regional trips in the San Francisco Bay 

Area and Los Angeles Basin); changes to service plans (destinations and 

schedules); and other sensitivity analyses aimed at quantifying risks. In its 

October 2012 report, the Panel also recommended additional sensitivity 

analyses to be completed on the second generation travel demand 

model, including analyses examining the impact of pricing strategies on 

revenue, impact of local transit feeder systems on station choice, and 

impact of major changes in the roadway network on highway congestion 

and subsequent mode choice decisions. In addition, the Authority is 

planning to conduct Monte Carlo simulations to test numerous potential 

combinations of assumptions on the forecasts that will be part of the 2014 
 

Page 37 GAO-13-304 California High Speed Rail 

Business Plan during fiscal years 2013 through 2014, provided the 

foundational information to construct, test, and analyze the simulation and 

its results is sufficiently developed at that stage of the program. All of 

these will be important as the ridership and revenue forecasts continue to 

evolve with development of the high-speed rail project. 

The project’s funding, which relies on both public and private sources of 

financing, faces uncertainty about whether those funds can be obtained in 

a tight federal and state budget environment. The Secretary of 

Transportation and the Governor of California have committed to funding 

this project, but obtaining sustained congressional and public support for 

appropriating additional funds is one of the biggest challenges to 

completing this project. In the latter stages, the Authority will also rely on 

private-sector financing, but will require more reliable operating cost 

estimates and revenue forecasts to determine whether, and the extent to 

which, the system will be profitable, as well as the value of any private 

investment. The Authority’s financing plan recognizes the uncertainty of 

the current funding environment so the Authority is building the project in 

phases and has identified an alternative funding source that is also 

uncertain. However, delays in obtaining funds as planned will likely lead 

to project delays and higher costs for construction. A summary of funding 

already committed to date can be found in table 3. 

Table 3: Funding Secured for Constructing the California High-Speed Rail Project, 

as of February 2013 

(Dollars in billions) 

State high-speed rail bonds $8.2a

Federal HSIPR grants 3.3b

Total secured funding $11.5

Source: GAO analysis of FRA grant information and the California High-Speed Rail Authority’s April 2012 Revised Business Plan. 

a

The Authority expects approximately $8.2 billion in proceeds from the $9.95 billion authorized in 

Proposition 1A high-speed rail bonds to be available for construction of high-speed rail. The 

remainder is for connectivity projects and engineering and environmental work. 

b

Approximately $3.3 billion of $3.5 billion in obligated HSIPR grants is available for construction of 

high-speed rail project. The remainder is for engineering and environmental work. 

The Authority’s 

Funding Plan Faces 

Uncertainty 
 

Page 38 GAO-13-304 California High Speed Rail 

The Authority is relying primarily on public-sector funding to complete 

construction of Phase 1 of the project with $55 billion, or 81 percent of the 

total construction cost, expected to come from state and federal sources. 

Heavy reliance on public-sector funding is not unusual for a project of this 

size. For example, France built its high-speed train system primarily with 

public-sector funding. In the United States, federal-aid highway system 

continues to be funded by the federal government through the gas tax 

and, more recently, with transfers from the general fund.50 The Authority 

expects to obtain public sector funds over the life of the project as 

individual segments are ready for construction. This type of “phased” 

funding is typical for major transportation infrastructure projects. Table 4 

provides a summary of the Authority’s funding plan for Phase 1 the highspeed rail project.

 

50Federal funds for construction or improvement of federal-aid highways generally must 

be matched with funds from other sources. For example, unless otherwise specified in 

authorizing legislation, most projects that are part of the Interstate System have an 80 

percent federal share. 23 U.S.C. § 120(b).

Additional Public Sector 

Funding Is Needed to 

Complete the Project, but 

Securing It Will Be 

Challenging
 

Page 39 GAO-13-304 California High Speed Rail 

Table 4: The Authority’s Funding Plan for Constructing Phase 1 of the California High-Speed Rail Project, as of April 2012

(Dollars in billions)

Funding source

First

construction

Initial operating 

segment Bay-to-Basin Phase 1 blended Total

Federal $3.3 $20.3 $8.4 $10.0 $ 42.0 (61%)

State high-speed rail bond 2.7 4.4 0.0 1.1 8.2 (12)

Locally generated 0.0 0.7 1.2 3.1 5.0 (7)

Subtotal public 6.0 25.4 9.6 14.2 55.2 (81 %)

Private investment 0.0 0.0 10.1 3.0 13.1 (19)

Operating cash flow 0.0 0.0 0.2 0.0 0.2 (0)

Subtotal private investment 

and operating cash flow

0.0 0.0 10.3 3.0 13.3 (19%)

Total $6.0 $25.4 $19.9 $17.2 $68.5 (100%)

Source: GAO analysis of California High-Speed Rail Authority’s April 2012 evised business plan.

The Authority’s April 2012 revised business plan relies on approximately 

$42 billion in federal funding for the project’s construction, which includes 

the $3.3 billion that has already been obligated. The remaining $38.7 

billion in federal funds have not been identified in federal budgets or 

appropriations but would amount to an average of more than $2.5 billion 

annually over the life of the project’s construction. This exceeds the 

average annual funding made available under DOT’s New Starts transitfunding grant program since 2008 (about $1.6 billion per year). Moreover, 

it exceeds the federal government’s average annual appropriations to 

Amtrak since 2008 (about $1.5 billion per year). Largely as a result of the 

funding challenge, the Authority is taking a phased approach—planning to 

build segments as funding is available. Thus, according to the Authority’s 

2012 revised business plan, no additional funding will be needed until 

2015 when it hopes to begin construction beyond the first construction 

segment.

Based on our past work on high-speed rail, successful projects require 

significant and sustained financial commitments from the public sector 

before private investors will participate, and the Authority’s plan reflects 

this funding model.51

 

51

For example, in Japan, private investment is 

contingent on substantial government investment. Other federallyGAO-09-317. 

Federal Funding
 

Page 40 GAO-13-304 California High Speed Rail 

supported transportation programs—like those for highway and certain 

transit infrastructure—rely on a dedicated revenue source for their funding 

and allow for multi-year funding agreements for eligible projects. In 

contrast, the HSIPR program has not been funded with a dedicated 

revenue stream, but from the general fund, a process that means that the 

program has to compete for appropriations with other discretionary 

programs.52 In addition, the HSIPR program has provided one-time grants 

and, as currently structured has not awarded multi-year agreements for 

grantees. Our 2013 High-Risk Series report identified the use of general 

funds for high-speed rail projects as a challenge to project completion.53

The Authority is also relying on a total of about $8.2 billion in state highspeed rail bond proceeds (which includes the $3.7 billion that has been 

appropriated to date) and another $5 billion in locally-generated funds for 

the project’s construction.

Given that the HSIPR grant program has not received funding since 2010 

and that future funding proposals will likely be met with continued concern 

about the general level of federal spending, the largest block of expected 

funding for the California project is uncertain.

54

 

52The President’s fiscal year 2013 budget request proposed providing multi-year funding 

($47 billion over 6 years) for high-speed rail. 

The proceeds from the high-speed rail bonds 

are dedicated, in that they can only be used for this project and do not 

have to compete with other budgetary priorities. However, the remaining 

$4.5 billion will have to be appropriated to the project. The $5 billion in 

local funds—most of which are expected at the end of the project’s 

construction timeline—have not been committed by local entities yet. 

Authority officials told us that these local funds could include revenues 

derived from property development in and around high-speed rail stations 

or improved service on existing transit corridors. For example, planned 

improvements on the Caltrain corridor may result in increased ridership; if 

so, a portion of increased revenues could be earmarked for high-speed 

rail construction.

53GAO, High-Risk Series: An Update, GAO-13-283, (Washington, D.C.: February 2013)

54According to their April 2012 revised business plan, the Authority is planning on applying 

$8.2 billion of the $9.95 billion in state high-speed rail bond proceeds to project 

construction. Some $950 million of the remaining $1.75 billion will be used for 

transportation projects that will connect to high-speed rail. And, the other $800 million will 

be used for environmental, planning, and support costs.

State and Local Funding
 

Page 41 GAO-13-304 California High Speed Rail 

The Authority acknowledges the risk in relying on a significant amount of 

federal funding (and to a lesser extent, local funding) for the project. To 

help mitigate this risk, the California Department of Finance has identified 

California’s newly implemented cap-and-trade program as a potential 

source of revenue in the event other public funding is not available.55

However, there are a number of challenges with using this program as a 

potential source of revenue for the high-speed rail project. First, while the 

state of California anticipates this program to generate tens of billions of 

dollars in revenues, amounts are not certain since the auctions have only 

recently begun. The first auction of greenhouse gas emissions 

allowances was held in November 2012 and resulted in revenues at the 

low-end of the state’s initial estimates.56

 

55According to the California Air Resources Board—the state agency in charge of 

implementing the cap-and-trade program—California law requires that the volume of 

greenhouse gas emissions generated in the state be lowered to 1990 levels by 2020. To 

meet this goal, California established a limit on annual greenhouse gas emissions, or, a 

cap. The cap on pollution is divided into allowances that have to be acquired by polluting 

entities, such as coal-burning power plants. The state conducts periodic auctions to sell 

these allowances and also allows them to be traded (bought and sold) on a secondary 

market. 

The state anticipates revenue will 

increase significantly by fiscal year 2015 when more bidders are required 

to participate. Second, in order for any program revenue to benefit the 

high-speed rail project, appropriations must be enacted to provide funding 

for the project. This means that high-speed rail will have to compete with 

other state funding priorities, and the Authority cannot be assured what 

portion of cap-and-trade revenues, if any, will be dedicated for high-speed 

rail. Finally, concerns have been raised about whether revenues from the 

cap-and-trade program can be used for the high-speed rail project. An 

analysis by California’s Legislative Analyst’s Office (LAO) indicated that, 

among other things, the project might not comply with the legislative goal 

of the cap-and-trade program of reducing greenhouse gas emissions by 

2020, which raises concerns about the potential use of cap-and-trade 

revenues for the high-speed rail project. The LAO suggested that the 

California Legislature obtain legal advice to address any potential legal 

issues. However, according to the California Air Resources Board’s 2008 

plan to implement the cap-and-trade program, high-speed rail was 

56According to a report from California’s Legislative Analyst’s Office, the November 2012 

auction was expected to result in a price of $10 to $50 per credit. According to the 

California Air Resources Board, the November 2012 auction resulted in a price of about 

$10 and raised approximately $290 million in auction proceeds. 

Cap-and-Trade Funding
 

Page 42 GAO-13-304 California High Speed Rail 

identified as an eligible project to meet the state’s greenhouse gas 

reduction goals.

In addition to the challenges of obtaining public-sector funding, the 

Authority may face challenges in attracting private-sector funding if its’ 

operating cost estimate and ridership forecasts prove to be optimistic. 

The Authority expects that once the initial operating segment is 

operational in 2023, it will generate a profit that would be attractive to 

private investors. The Authority is planning to raise approximately $13.1 

billion by selling an operating concession to a private firm or consortium 

of firms.57

Our past work on high-speed rail systems has shown that private sector 

investment is easier to attract only after the public sector has made a 

substantial capital investment in the system.

The Authority plans to use the proceeds of this sale to help 

complete construction of the system. 

58

• complete construction of the IOS (this will require at least an 

additional $25 billion of investment from public sources), and

The Authority’s plan is 

consistent with this funding approach; however, to successfully attract 

private investment in this project, the Authority will have to meet two 

significant milestones:

• demonstrate that the IOS can operate at a profit.59

 

57As we reported in February 2008, an operating concession is a type of public-private 

partnership that offers rights to a private party to operate in return for a fixed-fee or 

percentage of revenues. See GAO, Highway Public-Private Partnerships: More Rigorous 

Up-front Analysis Could Better Secure Potential Benefits and Protect the Public Interest, 

GAO-08-44 (Washington, D.C.: Feb. 8, 2008). For the California high-speed rail project, 

an operating concession would be an agreement between the Authority and a private firm, 

or consortium of firms, to retain ticket revenues with the responsibility to operate and 

maintain the service, in exchange for an up-front payment to the Authority. 

58GAO-09-317. 

59The Authority is planning for approximately $38.7 billion in additional federal funds for 

completing the entire Phase 1 of the project. Of this, approximately $25 billion will be used 

to complete the Initial Operating Segment. Operating profits, which are total operating 

revenues less operating expenses, are necessary to make an operating concession viable 

without other guarantees of income to the private investor. 

Securing Private-Sector 

Investment Will Depend on 

Reliable Operating Cost 

and Ridership Forecasts
 

Page 43 GAO-13-304 California High Speed Rail 

Public-private partnerships for intercity passenger rail, such as what the 

Authority is planning for, have been proposed but not implemented in the 

United States.60 However, in other transportation sectors, public-sector 

infrastructure owners have used public-private partnerships to incorporate 

private-sector operating expertise and encourage private investment. For 

example, the state of Indiana raised $3.8 billion in 2006 by arranging a 

private operating concession for its existing Indiana Toll Road. In addition, 

according to DOT, the city of Denver, Colorado, raised nearly $100 million 

from private sources to help finance a $2 billion expansion to its transit 

and commuter rail project. While the private-sector can provide needed 

funding and management expertise to a transportation project, this 

approach is not risk-free. As we have previously reported for highway 

projects, public-private partnership can also present trade-offs, such as 

the risk that the private operator will demand more revenue from users 

(e.g., tolls) than initially expected.61

Other nations’ experiences with high-speed rail indicate that under certain 

circumstances the private sector can operate these systems and that they 

could potentially be profitable on an operating basis. For example, Japan 

sold certain high-speed rail lines to private operators and does not 

provide operating subsidies to these firms. And, in 2010, Britain sold an 

operating concession for its High-Speed 1 line to a consortium of private 

investors for approximately £2 billion (approximately $3.2 billion).62

 

60Intercity passenger rail service in the United States is provided by Amtrak mostly over 

tracks owned by private freight railroads. There have been recent proposals to use private 

operators other than Amtrak for new intercity passenger rail services, such as the Desert 

Xpress and All Aboard Florida. 

Private firms have also expressed interest in operating high-speed rail 

projects in the United States. For example, according to FRA, several 

private consortia were preparing to submit bids on a HSIPR-funded 

project between Tampa and Orlando, Florida. However, public-sector 

support was withdrawn when the governor canceled the project which 

precluded private-sector investment. And, in Texas, a privately-financed 

high-speed rail project failed when the investors encountered financial 

difficulties. Authority officials told us that they have met with a number of 

61 GAO-08-44. 

62British pounds converted to U.S. dollars based on the November 15, 2010 exchange 

rate according to historical data published by the Board of Governors of the Federal 

Reserve System.
 

Page 44 GAO-13-304 California High Speed Rail 

private firms and high-speed rail operators that have expressed interest in 

California’s project but have not entered into any agreements since the 

project has not yet been built. Attracting private investment may not only 

require up-front public investment but may also require the use of 

revenue guarantees, or public guarantees of a minimal level of income to 

the project regardless of ridership levels. Such guarantees will reduce the 

risk for private operators, and therefore their cost of raising capital, but

according to the Authority, a revenue guarantee is considered to be a 

type of operating subsidy that is barred by the legislation that authorized 

the state high-speed rail bonds (Proposition 1A bonds).

Private-sector investment in the California high-speed rail project, if any, 

will ultimately be determined by the profitability of the system—that is, the 

extent to which operating revenues exceed operating costs. The Authority 

currently estimates an operating profit in the first and all subsequent 

years of operation.63 However, this estimate is only as reliable as the 

underlying operating cost and revenue forecasts. As discussed earlier, 

the Authority’s current ridership and revenue forecasts are reasonable for 

planning purposes, however, further refinements will be required as the 

project continues to evolve. The Authority’s current operating cost 

estimates will also need to be improved in the future. Accordingly, both 

cost and ridership forecasts will change before the initial operating 

segment is completed in 2022, making the future value of potential private 

funding uncertain at this time.

 

63The Authority’s 2012 revisedbBusiness plan estimates an average of $937 million in 

annual operating profits, from 2022 through 2034. 
 

Page 45 GAO-13-304 California High Speed Rail 

The Authority comprehensively identified key economic impacts that 

could result from the high-speed rail project, including user and non-user 

impacts, as required by FRA and other federal requirements. FRA 

guidance, as contained in the program Notices of Funding Availability 

(NOFA), requires HSIPR applicants to identify the potential benefits and 

costs of proposed projects with a focus on a public return on 

investment.64 A public return on investment includes a project’s potential 

to deliver transportation, economic recovery, and other benefits. To assist 

in project evaluation, FRA encouraged HSIPR applicants to provide an 

economic analysis that quantified the monetary value of user benefits 

and, if available, public benefits.65 However, according to FRA, program 

NOFAs did not explicitly require either a formal benefit-cost analysis 

(BCA) or preparation of an economic impact analysis (EIA).66

 

6474 Fed. Reg. 29900 (June. 23, 2009). 

FRA 

officials said their review of economic impacts was based on a 

reasonableness test—that is, were economic impacts identified and were 

65User impacts (or benefits) are the impacts on passengers who actually use a 

transportation improvement. That is, travelers must use the improvement to benefit from it. 

Non-user impacts (or benefits) are those impacts on those who do not directly use an 

improvement.

66A benefit-cost analysis is designed to identify the alternative with the greatest net benefit 

by comparing the monetary value of benefits and costs of each alternative with a baseline. 

Benefit-cost analysis provides for a comparison of alternatives based on economic 

efficiency, that is, which investment or policy would provide the greatest net benefit (i.e., 

greater than costs). Economic impact analysis is a tool for assessing how the benefits and 

costs of transportation alternatives would be distributed throughout the economy and for 

identifying groups in society (for example, by region, income, or race) that are likely to 

gain from, or bear the costs of, a policy.

The Authority 

Comprehensively 

Identified Potential 

Economic Impacts, 

but It Is Too Early to 

Determine Specific 

Impacts

Potential Economic 

Impacts Were 

Comprehensively 

Identified, but Specific 

Impacts Will Depend on 

Project Decisions, 

Economic Conditions, and 

Other Factors 
 

Page 46 GAO-13-304 California High Speed Rail 

the assumptions behind the impacts reasonable. The officials said that 

FRA did not have the time or resources to conduct an in-depth analysis

and that a reasonableness test provided increased assurance as to 

potential economic impacts of project proposals. Projects awarded 

funding must also comply with the National Environmental Policy Act 

(NEPA) and its implementing regulations. NEPA requires that government 

agencies undertaking a major federal action (such as providing grant 

funding) with significant effects on the environment prepare an analysis of 

the environmental impacts of the proposed action, including a discussion 

of alternatives to the proposed action.67

To analyze the extent to which economic impacts were comprehensively 

identified by the Authority, the key components of economic impacts on 

users and non-users were identified from a variety of sources, including 

NEPA, NOFAs for the HSIPR and Transportation Investment Generating 

Economic Recovery (TIGER) programs as well as a report on best 

practices for assessments of public benefits prepared for the DOT OIG for 

the DOT OIG’s March 2012 report on FRA’s HSIPR program.

Under FRA’s guidelines for 

considering environmental impacts, among the impacts to be considered 

in a NEPA environmental assessment are such things as land use and 

potential economic effects on existing business districts and metropolitan 

areas. The program NOFAs required HSIPR applicants seeking funds to 

develop new high-speed rail corridors and intercity passenger rail 

services to complete a NEPA review and the June 2009 program NOFA 

required HSIPR applicants to present information that provided a 

business and investment justification that contained project cost and 

benefit estimates.

68

 

6742 U.S.C § 4321 et seq.

The best 

practices report identified user impacts such as travel costs and travel 

quality and non-user impacts such as highway and airway congestion and 

noise or air quality levels. Non-user impacts may also include economic 

impacts that are difficult to quantify, such as the effects improved 

68DOT OIG, FRA Needs to Expand Its Guidance on High-Speed Rail Project Viability 

Assessments, CR-2012-083 (March 28, 2012). In particular, we focused on best practices 

contained in the report HSIPR Best Practices: Public Benefits Assessment, Steer Davies 

Gleave, June 2011 that was prepared for the Office of Inspector General in conjunction 

with the March 2012 report. The Steer Davies Gleave report included a list of components 

that would be included in a public benefits assessment of high-speed rail projects. The 

components of public benefit assessments were similar to economic impacts identified 

through a review of the HSIPR NOFAs.
 

Page 47 GAO-13-304 California High Speed Rail 

transportation connectivity may have on allowing firms to access larger 

labor or product markets or increasing the labor supply because people 

can more easily access jobs. The latter are included in what is termed 

“wider economic impacts.” FRA’s requirement for a public return on 

investment from HSIPR projects included aspects of both user and nonuser impacts. The best practices report noted the importance of both 

ridership and revenue forecasts and cost estimates in determining public 

benefits. In particular, it stated that public benefits assessment depends 

heavily on ridership and revenue forecasts and the implications these 

have on project impacts on travelers and the general population.

Similarly, operating, maintenance, and capital cost estimates were also 

identified as important elements of public benefits assessments.

The Authority’s April 2012 revised business plan identified the primary 

user and non-user economic impacts of the California high-speed rail 

project (see table 5). For example, the plan identified potential user 

impacts such as travel time reliability for high-speed rail users and nonuser impacts such as the effects on highway congestion and economic 

development around stations. In addition to the business plan, the 

Authority prepared a BCA that provided a more detailed analysis of both 

user and non-user impacts included in the revised business plan. The 

Authority also prepared an EIA that focused on those other economic 

impacts of the system that do not fall into the BCA framework. According 

to the Authority, the EIA presented longer-term impacts on California’s 

economy from building the high-speed rail system.
 

Page 48 GAO-13-304 California High Speed Rail 

Table 5: Primary Economic Impacts Associated with High-Speed Rail Identified by the Authority in the April 2012 Revised

Business Plan, BCA, or EIA

Primary economic impacts associated 

with high-speed rail

Economic impacts identified by the 

Authority Where economic impact discussed

User impacts

Generalized travel costs to users. Includes 

impacts on the following:

• In-vehicle travel time

• Waiting, access, egress time

• Out-of-pocket cost

• In-vehicle travel time.

• Access and egress times.

• Vehicle operating costs (fuel and nonfuel such as operating and maintenance 

costs). 

Revised Business Plan; BCA

Travel quality. Includes crowding, comfort, 

travel time variance and reliability of service

• Comfort of high-speed rail.

• Reliability of travel times.

Revised Business Plan; BCA

Non-user impacts

Congestion. Includes reduced congestion on 

the following:

• Highway

• Air

• Rail

• Congestion impacts on highway vehicle 

miles traveled.

• Congestion impacts on aviation (flight 

and passenger delays)

• Analysis excluded potential impacts in 

urban rail corridors near Los Angeles 

and the San Francisco Bay Area.

Revised Business Plan; BCA

Environment. Includes impacts on the 

following:

• Noise

• Air quality

• Carbon emissions

• Landscape/townscape

• Automobile and truck emissions 

impacts. 

• Automobile noise pollution.

• Aviation emissions impacts.

• BCA analysis specifically excluded 

impacts on land use and land values

BCA 

Travel safety • Automobile accident cost impacts. BCA

Financial impacts, including impacts on such 

things as:

• Operator revenues

• Federal, state, and local tax revenues

• Potential impacts on state gross 

domestic product from investing in highspeed rail.

• Potential impacts on local tax revenue.

Revised Business Plan; EIA

Source: GAO analysis of Steer Davies Gleave and Authority documents.

Although the Authority comprehensively identified the primary potential 

economic impacts, it is too early to determine specific economic impacts 

since these will depend on a number of factors. These include the 

following:

• Future project decisions. The California high-speed rail project is in its 

early stages of development, and a number of project decisions have 

yet to be made, including final alignment of train routes, some station 

locations, and the type and frequency of service. Decisions such as 

these can be expected to have a bearing on potential economic 
 

Page 49 GAO-13-304 California High Speed Rail 

impacts. For example, route alignments and station locations can 

affect economic development. While acknowledging that the extent to 

which high-speed rail would change California’s economic landscape 

was not fully understood, the EIA suggested that based on studies in 

other countries, the main economic impacts from high-speed rail in 

California will likely occur in areas within 2 hours of major economic 

centers, such as the San Francisco Bay Area and Los Angeles.

However, the EIA also concluded that the greatest volume of 

redevelopment attributable to high-speed rail will likely occur in major 

metropolitan areas and that the Central Valley could see moderate 

clustering of development around stations. Although economic 

development around stations offers the potential for economic 

impacts, achieving such development may be subject to a number of 

factors, and certain impacts may not be easy to identify. In July 2012, 

we reported on the potential for economic development associated 

with bus rapid transit projects.69 We found that in the five case study 

locations we examined, although the bus rapid-transit project was 

having some positive effect on economic development, individuals 

associated with these projects were unsure about how much 

economic activity could be attributed to the presence of bus rapid 

transit compared with other factors or circumstances. In addition, the 

project sponsors and experts we spoke with told us that transitsupportive policies and development incentives can play a crucial role 

in helping to attract and spur economic development associated with 

bus rapid transit. In September 2009 we reported the characteristics 

of transit-oriented development around stations can increase nearby 

land and housing values, but we also found that determining transitoriented effects on the availability of affordable housing in these 

developments are complicated by lack of direct research and data.70

 

69GAO, Bus Rapid Transit: Projects Improve Transit Service and Can Contribute to 

Economic Development, GAO-12-811 (Washington, D.C.: July 25, 2012). Bus rapid transit 

projects vary in design but generally include service enhancements designed to attract 

riders and provide similar transit-related benefits to rail transit. For the purposes of the 

report the term economic development was used to refer to components of transit-oriented 

development, such as high-density, mixed-use developments and pedestrian-friendly 

environments and streetscapes.

70GAO, Affordable Housing in Transit-Oriented Development: Key Practices Could

Enhance Recent Collaboration Efforts between DOT-FTA and HUD, GAO-09-871 

(Washington, D.C.: Sept. 9, 2009).
 

Page 50 GAO-13-304 California High Speed Rail 

• Economic conditions over the life of the project. As we reported in 

March 2012, the closer the economy is to full employment, the smaller 

net effect a project will have on total economic activity.71 The speed 

with which the nation and California recover from the 2007 to 2009 

recession, which cannot be known in advance, will affect the net 

employment from any new infrastructure projects. If the economy 

achieves full employment, such projects would affect the composition 

of employment but not its level or rate of growth.72 The high-speed rail 

project will be constructed and operated over a period of many 

decades and likely over many economic cycles. The Authority’s April 

2012 BCA used a 67-year period (from 2013 to 2080) to estimate 

potential economic benefits and costs of the project, and, for purposes 

of analyzing potential operating and maintenance costs, the April 

2012 revised business plan assumed a 38-year operating period 

(2022 to 2060).73 Over such an extended period, economic conditions 

can be expected to change, as will potential economic impacts. The 

Authority’s April 2012 EIA recognizes that the project’s economic 

impacts will be affected by California’s economy and unemployment 

rates. According to the Authority’s EIA, as of February 2012 

California’s 10.9 percent unemployment rate was the nation’s third 

highest.74

 

71GAO, Commuter Rail: Potential Impacts and Cost Estimates for the Cancelled Hudson 

River Tunnel Project, 

It goes on to estimate that the high-speed rail project has 

the potential to create about 1 million direct and indirect job-years 

through construction of the Phase 1 blended system, based on the 

assumption that 20,000 job-years would be created for each $1 billion 

GAO-12-344 (Washington, D.C.: Mar. 9, 2012).

72According to the Bureau of Labor Statistics, a full employment economy in 2020 would 

have a 5.2 percent unemployment rate. See Bureau of Labor Statistics, Monthly Labor 

Review, January 2012.

73The BCA states that different scenarios were considered in developing the analysis 

period and, depending on the scenario, the construction period varied. The analysis period 

used was 47 years beyond project completion for the scenario with the longest 

construction period. The assumed operating period is not intended to indicate the system 

will stop operating in 2060.

74According to the EIA, the unemployment rate over the San Francisco Bay Area to Los 

Angeles corridor varied. The EIA states that through the recent recession, the San 

Francisco Bay Area unemployment rate was 1.0 to 1.5 percentage points less than the 

state as a whole. At the time of the EIA, the Central Valley unemployment rate about 4 

percent higher than the statewide average and the Southern California unemployment rate 

was within 1 percent of the statewide rate.
 

Page 51 GAO-13-304 California High Speed Rail 

in capital investment.75

• Uncertainty about some impacts. Uncertainty may particularly affect 

non-user impacts, some of which are difficult to measure or quantify.

The Authority’s April 2012 EIA discusses the potential for wider 

economic impacts from high-speed rail such as the benefits of 

bringing California’s economic activities and markets closer together 

by reducing travel times. The EIA states, by improving transportation 

connectivity and reducing congestion, the high-speed rail system 

could make California’s economy more efficient, productive, and 

competitive by such things as bringing businesses closer to labor and 

other markets and providing workers with greater access to jobs.

However, the best practices report prepared for the DOT OIG found 

that additional data on things like the relationship between economic 

density and productivity, labor supply elasticity, and price-cost 

margins were needed to assess wider economic impacts of high 

speed rail projects.

The accuracy of this estimate will depend on 

the economic conditions and unemployment rates at the time the jobs 

are created. The EIA acknowledged this uncertainty when it stated 

that multipliers used to estimate indirect and induced jobs are 

snapshots in time of an economy and represent only current or recent 

economic relationships and technologies. They do not capture 

structural changes in the economy, new technologies, or changes in 

wages that occurred since the multiplier data were produced or that 

might occur in the future.

76

 

75The Authority’s EIA states that a “job-year” refers to the idea that one person working 

one job for 20 years represents 20 job-years. It is not the number of individuals working. 

Also, the employment factor used to develop the estimate is for construction and capital 

spending and not employment that might be associated with spending for operation and 

maintenance of the high-speed rail system. 

The study went on to note that no research was 

currently available regarding wider economic impacts of U.S. highspeed rail projects since such projects do not yet exist. The 

Authority’s April 2012 EIA recognized this difficulty and states that the 

extent to which the high-speed rail project will affect the economic 

landscape of California is not well understood, though transportation 

infrastructure investments have historically created fundamental shifts 

in the spatial relationship between places. These limitations do not 

imply deficiencies in Authority or DOT performance but rather the 

inherent analytical complexities of large infrastructure investments.

76HSIPR Best Practices: Public Benefits Assessment, Steer Davies Gleave, June 2011, 

prepared for Office of Inspector General, U.S. Department of Transportation.
 

Page 52 GAO-13-304 California High Speed Rail 

• Uncertainty regarding local or regional impacts. The April 2012 EIA 

discusses the potential for economic impacts along the high-speed rail 

line, including direct and indirect employment opportunities, increased 

efficiencies and productivity from bringing labor and other markets 

closer together, and transit-oriented development around stations.

The specific impacts to regions or localities will depend on a number 

of factors, including project-related factors and factors associated with 

local policies and decisions. Among the project-related factors are 

both the rate of project spending over time as well as where project 

funds are spent. The high-speed rail project is expected to be 

constructed over a long period of time and in phases when funding 

becomes available. The rate of spending and its timing will influence 

when and to what extent regions and localities may experience 

economic impacts associated with the project. Which specific regions 

or localities may experience economic impacts will be influenced by 

such project decisions as route alignments and station locations.

Local policies and decisions will also affect regional and local 

economic impacts. Studies conducted for the Authority by the 

University of California at Berkeley suggested there are opportunities 

for economic development from the high-speed rail system in a variety 

of locations, including Fresno and Bakersfield in California’s Central 

Valley. However, the studies cautioned that the extent of economic 

development will depend on cities establishing a framework of 

planning and development policies that encourage development.

Some cities have begun taking actions to promote economic 

development related to the high-speed rail system. For example, in 

June 2012 Fresno issued a solicitation for consultants to prepare a 

master plan for its planned downtown rail station that would enable 

the city to maximize local economic benefits from the high-speed rail 

system. Other cities have not yet acted. The Authority’s April 2012 

EIA found that of the 13 potential stations on the Phase I blended 

corridor, 7 (53.8 percent) did not have station-specific development 

plans.

We also found some limitations in the specific economic analyses 

prepared by the Authority. In particular, the April 2012 BCA has 

shortcomings that could limit its usefulness to decision makers.

• Identification of negative impacts of the project and their effects on the 

BCA analysis. The BCA lacked detail regarding the handling of 

negative impacts associated with the high-speed rail project. DOT 

guidance on benefit-cost analysis suggests that negative (or adverse) 
 

Page 53 GAO-13-304 California High Speed Rail 

impacts, such as non-user (or highway) delays associated with rail 

construction, be included in BCA analyses to facilitate consistent 

project comparisons.77

Aside from roadway delays, the Authority acknowledged there were 

additional categories of economic impacts that may be negative. For 

example, the April 2012 revised business plan discusses how the 

high-speed rail system could limit access to parts of farmland in the 

Central Valley potentially reducing the output of affected farmlands.

The BCA contained little discussion of such impacts and states that

the BCA did not incorporate or monetize land use and land value 

impacts the high-speed rail project may cause (positive or negative).

The Authority said negative impacts were assumed to be part of the 

mitigation measures that would be conducted as part of the 

environmental review process and right-of-way acquisition and that 

the costs of these measures were included in the cost side of the 

benefit-cost calculation. According to the Authority, including negative 

impacts as a negative benefit would lead to double counting them as 

both a negative benefit as well as a cost in the benefit-cost 

calculation. We agree that negative impacts of the high-speed rail 

project should not be double counted, but the BCA should include 

discussion of potential negative impacts and how they are treated in 

the analysis. Such information would better inform decision makers 

about the existence of negative impacts and their potential effect on 

project benefits or costs.

The guidance recommends that negative 

impacts, such as highway delays associated with rail construction, be 

shown as a negative benefit and not included in project investment 

costs to better facilitate comparisons between projects. The April 2012 

BCA recognized that during the period of project construction there 

would be roadway delays in urban areas that would offset some travel 

time savings. However, the BCA excluded such impacts from the 

analysis since the impacts were expected to be (1) localized, (2) 

minimal since the high-speed rail project minimizes urban grade 

crossings, and (3) negligible in proportion to overall travel time 

savings once the project is complete.

• Identification of the risks and uncertainties associated with the BCA 

analysis. The BCA did not discuss the potential risks and uncertainties 

 

77U.S. Department of Transportation, Federal Highway Administration, Economic Analysis 

Primer (August 2003). 
 

Page 54 GAO-13-304 California High Speed Rail 

associated with either the benefits or costs used in the analysis.

Forecasts are inherently uncertain, including those for ridership and 

economic projections. Recognition and analysis of risks is an 

important part of project evaluation. As we reported in February 2011, 

Executive Order 12893 and Office of Management and Budget (OMB) 

Circulars Nos. A-94 and A-4 indicate that benefit and cost information 

shall be used in agency decision making and that the level of 

uncertainty in estimates of benefits and costs shall be disclosed.78

Similarly, DOT’s TIGER guidance, which the Authority used to 

prepare its BCA, requires applicants to assess the reliability of any 

forecasts used to generate benefit estimates but does not specifically 

require a discussion of risks and uncertainties in a BCA. We reported 

in February 2011 that the majority of the applications to the TIGER 

and HSIPR programs we reviewed did not provide information related 

to uncertainties in projections, data limitations, or the assumptions 

underlying their models.

In 

particular, Executive Order 12893 requires that uncertainties about 

the amount and timing of important benefits and costs associated with 

an infrastructure investment be recognized and addressed through 

appropriate quantitative and qualitative assessments.

79 Even when such information was provided, 

we found that it was not always comprehensive. We recommended 

that DOT require, among other things, grant applicants to clearly 

communicate the level of uncertainty in estimates of project benefits 

and costs. The Authority did not conduct a risk analysis beyond 

examining the potential effects of high and low cost scenarios. While 

the Authority may have used credible sources for variables in its 

analysis (e.g., fuel prices), this does not eliminate all forecasting risks, 

and those risks should be identified. In addition, as we have noted, 

decisions on route alignments and other aspects of the project have 

yet to be made; decisions that could add to project risk.

 

78GAO, Intercity Passenger and Freight Rail: Better Data and Communication of 

Uncertainties Can Help Decision Makers Understand Benefits and Trade-offs of Programs 

and Policies, GAO-11-290 (Washington, D.C.: Feb. 24, 2011); Executive Order 12893, 

Principles for Federal Infrastructure Investments(Jan. 26, 1994); OMB Circular A-94 

Revised, Guidelines and Discount Rates for Benefit-Cost Analysis of Federal Programs

(Oct. 29, 1992); and OMB Circular A-4, Regulatory Analysis (Sept. 17, 2003). 

79GAO-11-290. 
 

Page 55 GAO-13-304 California High Speed Rail 

Although the Authority comprehensively identified the project’s potential 

economic impacts, additional analysis is needed at the state level of how 

high-speed rail will affect other transportation modes and their ability to 

meet future travel demand. This includes the potential cost of additional 

improvements that may be needed or conversely planned projects that 

may not be needed. An important aspect of non-user impacts is a 

project’s potential effect on other transportation modes, including 

highways, aviation, and local transit systems. This is an important issue 

since the Authority has estimated that, as a result of population growth 

and other factors, overall interregional trips in California will increase from 

about 500 million in 2000 to about 900 million in 2030. In addition, under 

the blended approach adopted by the Authority, success of the highspeed rail system will depend in part on local transit improvements.

As part of the planning process, the Authority considered high-speed rail’s 

impact on the capacity of other transport modes. For example, in April 

2012 the Authority issued an analysis of the highway and airport 

improvements that would be needed to provide an equivalent capacity to 

the high-speed rail system envisioned in the April 2012 revised business 

plan.80 The analysis found the total cost (in 2011 dollars) of equivalent 

capacity investment in highways and airports would range between $123 

billion and $138 billion to build up to 4,600 highway lane-miles, 115 

airport gates, and 4 airport runways.81

 

80California High-Speed Rail Authority, Comparison of Providing Equivalent Capacity to 

High-Speed Rail through Other Modes (April 2012). 

However, the analysis did not 

focus on potential additional highway or other transportation 

improvements that may be required even with construction of the highspeed rail system. Rather, the analysis identified the potential highway 

and airport improvements that would be required to provide an equivalent 

capacity to that of the high-speed rail, not an assessment of additional 

improvements required to meet future intercity travel demand. Identifying 

such improvements was not the task of the Authority since its task is to 

develop a high-speed rail system. Rather, this task would fall to the state 

81The scope of the analysis was the 520-mile Phase 1 system. Comparisons between 

high-speed rail and highways and aviation were based on system capacity, or “people 

carrying” capacity, not ridership estimates. According to the analysis, system capacity was 

used, in part, to recognize that capacity provides a steady state comparison between 

transport modes since it is tied to physical infrastructure, not the number of people using 

that infrastructure. The Authority assumed 12 trains per hour would be operated in each 

direction, 1,000 seats per train, and an average load factor of 70 percent. Load factor is 

the number of average passengers on a train divided by the number of available seats.

High-Speed Rail’s Impact 

on Meeting State Travel 

Demand Has Not Been 

Fully Assessed
 

Page 56 GAO-13-304 California High Speed Rail 

as part of its overall planning responsibilities under federal transportationplanning requirements.

Constructing a high-speed rail system is not expected to meet all of 

California’s future intercity travel demand. Among other things, 

development of the phase I blended approach will affect the need for 

additional improvements to local transportation systems to support highspeed rail. For example, officials with the Orange County Transportation 

Authority told us they have bus projects and a street car project in the 

planning phases that will be linked to both local commuter rail and the 

high-speed rail system. Similarly, officials from the Southern California 

Association of Governments told us the cost of integrating high-speed rail 

with local transit was still being developed and that the cost of an initial 

list of prioritized projects to facilitate this integration exceeded $3 billion.

Of this $3 billion in projects, about $1 billion in projects were categorized 

as high priority. The officials said that although they have got agreement 

from the Authority to help fund some of the high priority projects and 

some funding is expected to come from Proposition 1A, a funding source 

for the list of potential projects had not been determined.

Even though high-speed rail is not expected to meet all of California’s 

future intercity travel demand, statewide transportation planning has not 

yet fully assessed the impact of the high-speed rail system in meeting this 

demand. In November 2011, the California Transportation Commission 

(CTC) issued a Statewide Transportation System Needs Assessment82

 

82California Transportation Commission, 2011 Statewide Transportation System Needs 

Assessment, Final Report (November 2011). 

that identified the preservation, management, and expansion projects 

required over the 2011 to 2020 period. The assessment identified a total 

cost for the projects of about $540 billion and a nearly $300 billion funding 

gap in meeting the project needs identified. According to CTC officials, 

the needs assessment included information about high-speed rail that

was readily available from Authority documents. However, high-speed rail 

was not assessed in terms of project needs, costs, or the funding gap 

because, according to CTC officials, Regional Transportation Plans that 

formed the basis of the assessment did not include high-speed rail in 

identifying project needs and costs. Similarly, California Department of 

Transportation officials told us current highway transportation planning 

has not looked at this issue, and the department’s long range 
 

Page 57 GAO-13-304 California High Speed Rail 

transportation plans have not included consideration of high-speed rail.

According to the officials, the department did not see an immediate need 

to do an assessment since the high-speed rail system is not expected to 

be operational for another 10 years or more. The officials agreed that the 

high-speed rail system will affect highways, and its impact will need to be 

considered in future transportation plans.

As currently conceived, California’s high-speed rail project is expected to 

be among the most expensive infrastructure projects that has been 

undertaken in this country. Therefore, concerns about potential cost 

escalations and optimistic ridership forecasts, as well as the potential 

burden this could place on public budgets are well placed. Cost and 

revenue estimates for large projects are, by their nature, imprecise; these 

estimates endeavor to predict many years into the future within the 

confines of what is known today. According to our past work reviewing 

high-speed rail projects in other countries, cost and ridership estimates 

tend to be overly optimistic. However, experts agree that taking steps to 

anticipate project risks and improve the credibility of such estimates will 

lower the risk of cost overruns and missed revenue forecasts. Improving 

the reliability of cost and revenue forecasts is critical to providing project 

sponsors, FRA, the Congress, and ultimately, the public with greater 

confidence that this project can be viable. This confidence is of particular 

importance as the Authority will seek significant and sustained funding 

from federal, state, and private sources.

We found that the Authority did not fully employ best practices for 

producing reliable cost estimates as expressed in GAO’s Cost Guide, 

which are recommended practices but not required. The cost estimates 

can be improved as the project progresses from design to construction, 

and ultimately, to operation. The Authority was not required to follow the 

Cost Guide; instead, it was required to follow FRA’s guidance which we 

found to be limited. That guidance identified the cost categories that 

applicants should include in its cost analyses, but did not specify how cost 

estimates should be generated. The Authority told us that it looked to 

FTA’s cost-estimating guidance to help inform the Authority’s costestimating methodology. The Authority can be commended for 

supplementing its analyses using FTA’s guidance, but this does not 

necessarily ensure a fully reliable cost estimate. Our past work, as well as 

that of the DOT OIG, has shown that FRA has yet to develop sufficient 

program guidance for project evaluation and oversight under its additional 

grant-making responsibilities under the HSIPR program. Developing 

guidance for HSIPR applicants and grantees that incorporates best 

Conclusion
 

Page 58 GAO-13-304 California High Speed Rail 

practices from the Cost Guide would allow cost estimators to improve the 

reliability of cost estimates for expensive projects like high-speed rail.

Such guidance would help ensure project costs reflect the four 

characteristics required for developing reliable cost estimates and

minimize the risk of cost overruns, missed deadlines, and unmet 

performance targets.

The Authority is in the process of updating its ridership and revenue 

model in response to recommendations provided by experts and peer 

review groups, such as the Ridership and Revenue Peer Review Panel.

We believe that these steps will have the potential to improve the 

Authority’s ridership forecasts, and we encourage continued refinement, 

as more information becomes available and continued review by peer 

review groups. Improved forecasts will be particularly important as the 

Authority seeks to secure private investment in the project. The potential 

project revenues—which are primarily dependent on ridership—will help 

determine how much the Authority may be able to obtain from private 

sources. Similar to the cost estimates, FRA has developed minimal 

guidance for applicants to develop reliable ridership and revenue 

forecasts. We, along with the DOT OIG, have previously made 

recommendations that FRA improve this guidance to ensure reliability of 

ridership and revenue forecasts that are used to determine the viability of 

high-speed rail projects. According to FRA officials, the agency is 

currently in the process of implementing these recommendations. Since 

we have already made recommendations to FRA on this issue in our prior 

work and FRA is taking actions on these recommendations, we are not at 

this time making additional recommendations related to improving FRA’s 

ridership and revenue forecasting guidance.

We recommend that the Secretary of Transportation direct the 

Administrator of FRA to improve its guidance for high-speed rail project 

sponsors to better ensure that cost estimates that are submitted by 

applicants seeking federal funding are accurate, comprehensive, welldocumented, and credible according to the best practices detailed in 

GAO’s Cost Guide. 

Recommendation
 

Page 59 GAO-13-304 California High Speed Rail 

We provided a draft of this report to DOT and the Authority for review and 

comment. DOT neither agreed nor disagreed with our recommendation. 

In an e-mailed response, DOT said it was pleased that the Authority met 

many of the criteria in the Cost Guide for producing accurate, 

comprehensive, well-documented, and credible cost estimates; that 

ridership and revenue forecasts were reasonable; and that the Authority 

did a comprehensive job in identifying potential economic impacts. 

However, DOT noted (1) that the currently funded project has sound cost 

estimates while future, currently unfunded phases will continue to be 

refined as the project progresses and data improves, (2) that FRA’s costestimating guidance was the best available at the time, and (3) that 

GAO’s Cost Guide focuses on federally managed acquisitions. DOT’s 

response noted that the project is a multi-decade effort consisting of 

many segments and phases, each in a different stage of development. 

DOT’s response also noted that the Cost Guide was issued in March 

2009, one month after passage of the Recovery Act and a few months 

before deadlines for the HSIPR guidance, and, therefore, it was not 

feasible for FRA to incorporate Cost Guide best practices into guidance. 

Finally, DOT said applying the Cost Guide principles to future FRA capital 

cost guidance, while feasible, would require analysis and adaptation to 

accommodate unique aspects of long-term grantee-managed 

transportation projects. DOT noted that the Cost Guide is focused

primarily on federally managed acquisitions and programs, not 

infrastructure projects that non-federal parties will develop and build. DOT 

also provided technical comments that we incorporated as appropriate.

We recognize DOT’ concerns; however, our charge was to assess the 

reliability of the cost estimates and not just whether they complied with 

FRA’s guidance, which we found to be less than best practices. While 

the Cost Guide was released in 2009, it is a culmination of costestimating best practices that have previously been published and have 

been available to federal agencies for many years. Therefore, these 

practices could have been considered when preparing HSIPR program

guidance. Finally, the best practices contained in the guide are applicable 

to developing cost estimates for a wide variety of programs and projects, 

whether federally managed or not. 

Agency Comments 

and Our Evaluation
 

Page 60 GAO-13-304 California High Speed Rail 

The Authority provided a letter summarizing its comments about the 

report (see app. IV). In general, the Authority believes that the report 

highlights its efforts to produce cost estimates that reflect the scope of the 

project, that methods and models used to develop ridership and revenue 

forecasts adhered to applicable best practices, and that comprehensively 

identifying potential economic impacts demonstrates a strong economic 

case for the project. However, the Authority noted that different 

components of its program (such as implementation phases and 

construction packages) are at different stages of development and that it 

would not be practicable to apply the full complement of tools in the Cost 

Guide at the program level at this time. This is because the environmental 

review is under way on a number of sections and alignments and other 

choices are still to be made. The Authority also stated it plans to improve

its cost estimates and ridership forecasts. For example, the Authority 

stated that the updated ridership model being developed for the 2014 

business plan will incorporate many of the changes we suggested and

that the Authority will improve the quantification of project risks. 

We commend the Authority for planning to improve its cost estimates and 

forecasts. Regarding not applying the Cost Guide at the program level,

we note that a program does not need to be in an advanced stage of 

planning in order to complete a sensitivity or cost risk and uncertainty 

analysis. In fact, such analyses are most valuable when performed early 

in a program’s life cycle. Single point estimates are more uncertain at the 

beginning of a program because less is known about its detailed 

requirements and the opportunity for change is greater. For example, 

undefined or unknown technical information, uncertain economic 

conditions, and political issues are often encountered during a program’s 

acquisition. For management to make good decisions, the program 

estimate must reflect the degree of uncertainty, so that a level of 

confidence can be given about the estimate. Therefore, it is important to 

conduct a risk and uncertainty analysis at all stages of a project so cost 

estimates reflect the risk and uncertainty that exist.
 

Page 61 GAO-13-304 California High Speed Rail 

As agreed with your offices, unless you publicly announce the contents of 

this report earlier, we plan no further distribution of this report until 30 

days from the report date. At that time, we will send copies of this report 

to the appropriate congressional committees, the Secretary of 

Transportation, the Administrator of FRA, and the Director of OMB. The 

report will also be available at no charge on the GAO website at 

http://www.gao.gov. 

If you or your staff have any questions about this report, please contact 

me at (202) 512-2834 or flemings@gao.gov. Contact points for our 

Offices of Congressional Relations and Public Affairs may be found on 

the last page of this report. GAO staff who made major contributions to 

this report are listed in appendix V.

Susan A. Fleming

Director

Physical Infrastructure Team
 

Page 62 GAO-13-304 California High Speed Rail 

List of Addressees

The Honorable Bill Shuster

Chairman

The Honorable Nick Rahall

Ranking Member

Committee on Transportation 

and Infrastructure

House of Representatives

The Honorable Jeff Denham

Chairman

The Honorable Corrine Brown

Ranking Member

Subcommittee on Railroads, Pipelines

and Hazardous Materials

Committee on Transportation 

and Infrastructure

House of Representatives

The Honorable Darrell Issa

Chairman

House Committee on Oversight 

and Government Reform

House of Representatives

The Honorable Karen Bass

House of Representatives

The Honorable John Campbell

House of Representatives

The Honorable Jim Costa

House of Representatives

The Honorable Mike Honda

House of Representatives

The Honorable Duncan Hunter

House of Representatives 

The Honorable Barbara Lee

House of Representatives
 

Page 63 GAO-13-304 California High Speed Rail 

The Honorable Zoe Lofgren

House of Representatives

The Honorable Kevin McCarthy

House of Representatives

The Honorable Tom McClintock

House of Representatives 

The Honorable Howard P. “Buck” McKeon

House of Representatives

The Honorable John Mica

House of Representatives

The Honorable Gary Miller

House of Representatives

The Honorable Devin Nunes

House of Representatives

The Honorable Adam Schiff

House of Representatives
Appendix I: Objectives, Scope, and 

Methodology

Page 64 GAO-13-304 California High Speed Rail 

This report assesses (1) the reliability of the California High-Speed Rail 

Authority’s (Authority) estimates of the project’s costs; (2) the 

reasonableness of the Authority’s passenger rail ridership and revenue 

forecasts; (3) the risks to the Authority’s plan to fund the project; and 

(4) the comprehensiveness with which the Authority identified potential 

economic impacts of the project. Our analysis focused on the Authority’s 

cost estimates, ridership and revenue forecasts, and economic estimates 

presented in the April 2012 revised business plan.

To address these objectives, we reviewed numerous documents, 

including Federal Railroad Administration (FRA) guidance, Department of 

Transportation Office of Inspector General (DOT OIG) reports, prior GAO 

reports, and pertinent legislation. In addition, we obtained documents 

from and conducted interviews with Authority officials to obtain 

information about the Authority’s process for developing its various cost 

estimates, ridership and revenue forecasts, and economic impact 

estimates. Specifically, we reviewed the November 2011 draft business 

plan and April 2012 revised business plans and documentation used to 

develop the analysis presented in those plans. We conducted interviews 

with the Authority’s contractors—Parsons Brinckerhoff and Cambridge 

Systematics—to obtain additional information about the Authority’s 

processes for developing these estimates and to clarify information in 

their written documentation. In addition, we also conducted interviews 

with officials from various federal and state agencies, peer review groups, 

academic experts, advocacy groups, and transit and local government 

groups to obtain information on, among other things, their role with the 

California high-speed rail project and their views on the Authority’s cost 

estimates, financing plans, ridership and revenue forecasts, and potential 

economic impacts. (See table 6 for a list of organizations and individuals 

we interviewed for this study.) 

Appendix I: Objectives, Scope, and 

Methodology 
Appendix I: Objectives, Scope, and 

Methodology

Page 65 GAO-13-304 California High Speed Rail 

Table 6: Organizations and Individuals Interviewed

Federal agencies

Department of Transportation, Federal Aviation Administration

Department of Transportation, Federal Highway Administration

Department of Transportation, Federal Railroad Administration

Department of Transportation, Federal Transit Administration 

Department of Transportation, Office of Inspector General

State agencies

California Air Resources Board

California Bureau of State Audits

California High-Speed Rail Authority

California Legislative Analyst’s Office

California State Treasurer

California Transportation Commission

Caltrans

Peer review groups

California High-Speed Rail Peer Review Group

Ridership and Revenue Peer Review Panel

Advocacy groups and experts

Californians for High-Speed Rail 

Citizens Advocating Responsible Rail Design

Samer Madanat, Mark Hansen, and David Brownstone, University of California Berkeley 

Institute of Transportation Studies

Arpad Horvath and Mikhail Chester, University of California Berkeley Civil and 

Environmental Engineering

Wendell Cox 

Julien Dehornoy 

Bent Flyvbjerg

Joseph Vranich

Transit and local government groups

Amtrak 

Bay Area Rapid Transit

Caltrain

Los Angeles County Metropolitan Transportation Authority 

Metropolitan Transportation Commission

Orange County Transportation Authority

Peninsula Corridor Joint Powers Board

San Francisco County Transportation Authority 

Southern California Association of Governments 

Southern California Regional Railroad Authority 

Transbay Transit Center Joint Powers Authority 

Source: GAO.
Appendix I: Objectives, Scope, and 

Methodology

Page 66 GAO-13-304 California High Speed Rail 

To assess the reliability of the project cost estimates, we analyzed the 

Authority’s cost estimating approach against GAO’s best practices found in 

the 2009 GAO Cost Estimating and Assessment Guide (Cost Guide).1

After a review of all source data, including but not limited to electronic 

cost models for both capital investment and operating and maintenance 

phases, all supporting documentation, personal interviews, and 

independent research, we assessed the extent to which the Authority met 

these best practices on a five-point scale:

GAO designed the Cost Guide to be used by federal agencies to assist 

them in developing reliable cost estimates and also as an evaluation tool 

for existing cost estimates. To develop the Cost Guide, GAO cost experts 

assessed measures applied by cost-estimating organizations throughout 

the federal government and industry and considered best-practices for the 

development of reliable cost-estimates. We analyzed the cost estimating 

practices used by the Authority against these best practices. For our 

reporting needs, we collapsed these best practices into four general 

categories representing practices that help ensure that a cost estimate is 

(1) accurate, (2) well documented, (3) comprehensive, and (4) credible.

• Not Met—Authority provided no evidence that satisfies any of the 

criteria. 

• Minimally Met—Authority provided evidence that satisfies a small 

portion of the criterion.

• Partially Met—Authority provided evidence that satisfies about half of 

the criterion.

• Substantially Met—Authority provided evidence that satisfies a large 

portion of the criterion.

• Fully Met—Authority provided complete evidence that satisfies the 

entire criterion.

We determined the overall assessment rating by assigning each 

individual rating a number: Not Met = 1; Minimally Met = 2; Partially 

Met = 3; Substantially Met = 4; and Fully Met = 5. For the purposes of this 

 

1

GAO, Cost Estimating and Assessment Guide: Best Practices for Developing and 

Managing Capital Program Costs, GAO-09-3SP (Washington, D.C.: March 2009).
Appendix I: Objectives, Scope, and 

Methodology

Page 67 GAO-13-304 California High Speed Rail 

assessment we have also included a Not Applicable (N/A) assessment 

category. Then, we took the average of the individual assessment ratings 

to determine the overall rating for each of the four characteristics. The 

resulting average becomes the Overall Assessment as follows: Not Met = 

0 to 1.4; Minimally Met = 1.5 to 2.4; Partially Met = 2.5 to 3.4; 

Substantially Met = 3.5 to 4.4; and Fully Met = 4.5 to 5.0.

To assess the reasonableness of the Authority’s ridership and revenue 

forecasts, we analyzed the extent to which the Authority’s methods for 

developing the ridership model and resulting ridership and revenue 

forecast adhered to federal guidance and generally accepted travel 

demand modeling practices for high-speed rail projects. Unlike with 

GAO’s cost-estimating criteria discussed earlier, there is no single 

industry standard for developing or evaluating intercity passenger highspeed rail ridership forecasts. As such, for the purposes of our 

assessment, we reviewed a variety of sources that identify generally 

accepted travel demand modeling practices and developed criteria based 

on these practices to assess the reasonableness of the approach used to 

create the ridership and revenue models for the California high-speed rail 

project.2 In developing our criteria, we relied primarily on a 2011 report 

prepared for the DOT OIG’s office by the firm Steer Davies Gleave, on 

best practices related to developing high-speed rail ridership and revenue 

forecasts.3

 

2

For the purposes of our analysis, we assessed “reasonableness” of the Authority’s 

ridership and revenue forecasts by the extent to which the methods used to generate 

these forecasts followed generally accepted practices for high-speed rail demand 

modeling, and as such should be expected to produce generally plausible and defensible 

model results. A reasonable assessment indicates a level of confidence in the methods 

used to generate the ridership forecast and the resulting forecasts for decision-making 

purposes. 

The report provides a description of current standard practices 

in high-speed rail ridership and revenue forecasting, key steps typically 

involved in completing these forecasts, and a description on the range of 

data and methods used in the forecasting process. The intent of this 

guidance is to provide information that will assist reviewers to understand 

and evaluate forecasting studies. In addition, we also examined other 

literature on developing rail ridership and revenue forecasts to 

corroborate information in the Steer Davies and Gleave report. 

Specifically, we reviewed, among other sources, forecasting guidance 

3

Steer Davies Gleave, prepared for the U.S. Department of Transportation, Office of 

Inspector General, High-Speed Intercity Passenger Rail Best Practices: Ridership and 

Revenue Forecasting (April 2011). 
Appendix I: Objectives, Scope, and 

Methodology

Page 68 GAO-13-304 California High Speed Rail 

from the FRA, Federal Highway Administration (FHWA), prior GAO 

reports and other ridership and revenue guidance in academic research. 

(See table 7 for a list of sources used to develop criteria).

Table 7: Guidance and Reports Used to Identify Generally Accepted Travel-Demand-Modeling Practices 

Source Guidance or report 

Federal agency guidance

Prepared by Steer Davies Gleave for the 

Department of Transportation, Office of Inspector 

General 

HSIPR Best Practices: Ridership and Revenue Forecasting (April 2011).

Prepared by Cambridge Systematics for the 

Federal Highway Administration

Travel Model Validation and Reasonableness Checking Manual, Second edition 

(September 2010).

Department of Transportation, Federal Railroad 

Administration

High-Speed Intercity Passenger Rail (HSIPR) Program; Notice of Funding 

Availability; issuance of interim program guidance,”74 Federal Register 119” (23 

June 2009), pp. 29900-29929.

High-Speed Intercity Passenger Rail Program, Notice of Funding Availability of 

Individual Projects (NOFA); issuance of interim program guidance, “75 Federal 

Register 126” (1 July 2010), 38365-38383.

Prior GAO reports

Intercity Passenger and Freight Rail: Better Data and Communication of 

Uncertainties Can Help Decision Makers Understand Benefits and Trade-offs of 

Programs and Policies, GAO-11-290 (Washington D.C.: Feb. 24, 2011).

High Speed Passenger Rail: Future Development Will Depend on Addressing 

Financial and Other Challenges and Establishing a Clear Federal Role, 

GAO-09-317 (Washington D.C.: Mar. 19, 2009). 

Academic Literature 

Bent Flyvbjerg, “Quality Control and Due Diligence in Project Management: 

Getting Decisions Right by Taking the Outside View,” International Journal of 

Project Management (November 2012).

Transportation Research Board, ”Metropolitan Travel Forecasting: Current 

Practice and Future Direction, Special Report 288”, (2007)

McFadden, Bolduc, Bierlaire, “The Estimation of Generalized Extreme Value 

Models from Choice-Based Samples”, School of Architecture, Civil and 

Environmental Engineering, Ecole Polytechnique Federale de Lausanne (August, 

2006)

The British Department for Transport, “Procedures for Dealing with Optimism 

Bias in Transport Planning”, (June 2004)

Flyvberg, Bruzelius, Rothengatter, “Megaprojects and Risk: An Anatomy of 

Ambition,” Cambridge University Press (2003)

Source: GAO.
Appendix I: Objectives, Scope, and 

Methodology

Page 69 GAO-13-304 California High Speed Rail 

From these sources we identified recommended practices related to 

seven key steps relating to: (1) developing trip tables, (2) determining and 

applying service characteristics, (3) developing mode choice models, 

(4) estimating induced travel, (5) estimating expected fare revenue, 

(6) conducting sensitivity analysis, and (7) conducting validation testing.

We compared generally accepted practices for each of these steps to the 

Authority’s process for developing the ridership and revenue forecast as 

outlined in the April 2012 revised business plan and in supporting 

technical documentation. We could not evaluate each of the many 

detailed design decisions, assumptions, and model inputs used by the 

Authority, but rather focused on the seven key steps and whether they 

were implemented in accordance with generally accepted practices. We 

reviewed documents from and conducted interviews with Authority 

officials and their contractor—Cambridge Systematics—to obtain 

information about the Authority’s process for developing the ridership and 

revenue forecasts. Specifically, we examined the Authority’s process for 

developing the models used to produce the various forecasts, the 

assumptions and data sources used to develop the models, the survey 

instruments used to collect data, and the Authority’s process for model 

estimation, calibration, and validation.

We focused our analysis on identifying key steps in developing ridership 

forecast models for high-speed rail projects, elements affecting validity 

and reliability of models, common limitations of models and pitfalls, and 

recommended approaches for external review. In addition, we interviewed 

organizations that had conducted reviews of the Authority’s ridership and 

revenue forecasts, such as academic experts from University of California 

Berkeley’s Institute of Transportation Studies (ITS) and members of the 

Ridership and Revenue Peer Review Panel and the California HighSpeed Rail Peer Review Group. From these interviews, we obtained 

additional information about (1) generally accepted methods used for 

project ridership and revenue for high-speed projects and elements of 

these approaches that have the greatest potential risk, (2) general 

assumptions underlying demand forecast models, elements impacting 

validity and reliability of models, and existing data limitations, and (3) the 

extent to which the Authority’s approach follows generally accepted 

practices for developing valid and reliable ridership and revenue 

estimates.

To assess the Authority’s financing plan, we reviewed the plan, 

conducted interviews with Authority officials and other state and federal 

officials, and reviewed literature and other information on financing for 
Appendix I: Objectives, Scope, and 

Methodology

Page 70 GAO-13-304 California High Speed Rail 

high-speed rail projects in other countries as well as large transportation 

projects in the United States.

To assess how well the Authority identified economic impacts associated 

with the high-speed rail project, we reviewed the April 2012 revised 

business plan as well as the April 2012 benefit-cost analysis and April 

2012 economic impact analysis. In addition, to establish criteria for the 

various components of economic impact analysis, including user and nonuser impacts, we reviewed pertinent legislation, such as the Passenger 

Rail Investment and Improvement Act of 2008 and the National 

Environmental Policy Act, and the NOFAs associated with the HSIPR and 

Transportation Investment Generating Economic Recovery (TIGER) grant 

programs. FRA officials told us the NOFA’s outlined the type of 

information HSIPR grant applicants were to provide regarding project 

benefits and costs and how this information would be reviewed by FRA in 

reviewing grant applications. We also reviewed reports from the DOT OIG 

regarding HSIPR project viability assessments. In particular, we reviewed 

the June 2011 report prepared for the DOT OIG’s office on best practices 

related to public benefit assessments of high-speed rail projects produced 

by the firm Steer Davies Gleave. The Steer Davies Gleave report 

identified important components of user and non-user impacts associated 

with public benefits assessments.

To gain a better understanding of economic impact analysis, we reviewed 

the Economic Impact Analysis Primer prepared by the FHWA’s Office of 

Asset Management. The Economic Analysis Primer identified the basic 

process of identifying and analyzing economic impacts, including benefitcost analyses. The document also identified the similarities and 

differences between benefit-cost analyses and economic impact 

analyses. We also interviewed officials from FRA, the Authority, FHWA, 

the Federal Transit Administration, DOT OIG, and Steer Davies Gleave 

about economic impact issues. To assess issues related to high-speed 

rail and future travel demand, we reviewed the Authority’s revised 

business plan and April 2012 equivalent capacity study as well as the 

November 2011 Statewide Transportation Systems Needs Assessment

prepared by the California Transportation Commission (CTC). We also 

discussed these issues with officials from CTC and the California 

Department of Transportation as well as officials with local transportation 

agencies in California about potential improvement projects they had 

planned that were associated with the high-speed rail project.
Appendix I: Objectives, Scope, and 

Methodology

Page 71 GAO-13-304 California High Speed Rail 

The proposed high-speed rail project is a very large public works project 

with costs expected to be spread over more than a decade. Depending 

on how cost figures are presented, different impressions of the magnitude 

and funding requirements of the program could be given. Whether or not 

the effects of inflation are included in the estimate is a source of 

significant differences. Year of expenditure (YOE) dollars include inflation 

in out-year costs, a convention adopted to facilitate budgeting over time 

but not necessarily a good representation of the true economic costs of 

the project. Removing the increase in cost attributable solely to inflation in 

the price level provides a better picture of burden on taxpayers and other 

funders because the tax base, including incomes, property values, and 

retail sales, would have increased with inflation as well. In the case of the 

high-speed rail project, the YOE cost total is 25 percent greater than that 

when inflation effects are removed. An estimate of the cost in present 

value terms, which accounts for inflation and the time value of money, 

would be smaller still.

We conducted this performance audit from February 2012 to March 2013 

in accordance with generally accepted government auditing standards.

These standards require that we plan and perform the audit to obtain 

sufficient, appropriate evidence to provide a reasonable basis for our 

findings and conclusions based on our audit objectives. We believe that 

the evidence obtained provides a reasonable basis for our findings and 

conclusions based on our audit objectives.
Appendix II: GAO Analysis of California HighSpeed Rail Authority’s Cost Estimates 

Page 72 GAO-13-304 California High Speed Rail 

Characteristic

Overall 

assessmenta Best practice Individual assessment

Accurate Substantially 

Met 

The cost estimate results are unbiased, 

not overly conservative or optimistic, 

and based on an assessment of most 

likely costs.

Partially Met

While the Authority has attempted to ensure accuracy 

and eliminate bias in their estimate by conducting 

sensitivity analysis, parametric checks, and the use of 

peer review, these have all been on subsets of the total 

program. No risk or sensitivity analysis has been 

developed at the program level or between the low and 

high estimates. Alternative high and low estimates do not 

create a range of estimates, but rather point estimates 

evolving around potential options. In the absence of cost 

risk and uncertainty analysis it is not possible to 

determine if the estimate is unbiased. Unless the 

estimate is based on an assessment of the most likely 

costs and reflects the degree of uncertainty given all of 

the risks considered, management will not be able to 

make informed decisions.

The estimate has been adjusted 

properly for inflation.

Substantially Met

Both capital investment and operations and maintenance 

(O&M) costs are inflated to YOE dollars using sound 

data and methodologies. Source data used for cost 

estimating are normalized to appropriate base years, 

although in some instances the normalizing processes 

were not clear.

The estimate contains few, if any, minor 

mistakes. 

Fully Met

The cost estimate is regularly updated to 

reflect significant changes in the 

program so that it is always reflecting 

current status.

Fully Met

Variances between planned and actual 

costs are documented, explained, and 

reviewed. 

Not applicable

The estimate is based on a historical 

record of cost estimating and actual 

experiences from other comparable 

programs. 

Substantially Met

The estimate relies on construction cost data from 

commercial databases heavily supplemented with local 

construction bids from analogous construction projects.

The Authority collects technical and summary-level cost 

data on existing and future high-speed trainsets, but 

there is no documentation that explains how these data 

were adjusted for use in the cost estimate. The O&M 

estimate relies on applicable historical data. However, 

the extent of applicability is unknown because 

adjustments are not thoroughly documented.

Appendix II: GAO Analysis of California HighSpeed Rail Authority’s Cost Estimates 
Appendix II: GAO Analysis of California HighSpeed Rail Authority’s Cost Estimates 

Page 73 GAO-13-304 California High Speed Rail 

Characteristic

Overall 

assessmenta

 Best practice Individual assessment

The estimating technique for each cost 

element was used appropriately.

Substantially Met

The estimating techniques are reasonable for those

Standard Cost Categories (SCC) elements discretely 

estimated, where a unit price estimating methodology 

was employed. The 2012 O&M model is a simplified 

version of the 2009 model, appropriately suited to the 

cost model’s stated purpose of establishing program 

viability. However, the simplification results in an 

unnecessary loss of fidelity in some cost elements. 

Comprehensive Partially Met The cost estimate includes all life cycle 

costs 

Substantially Met

The Authority has included all relevant costs with the 

relatively minor exclusion of disposition costs in the 

capital investment estimate.

The cost estimate completely defines 

the program, reflects the current 

schedule, and is technically reasonable

Partially Met

The technical baseline description for the capital 

investment cost estimate resides in multiple documents 

that collectively comprise the technical baseline of the 

program. However, there is no distinct technical baseline 

description for the O&M estimate. Officials stated that 

later versions of the O&M estimate will align with the 

Concept of Operations plan, which was approved in 

February 2012.

The cost estimate work breakdown 

structure (WBS) is product-oriented, 

traceable to the statement of 

work/objective, and at an appropriate 

level of detail to ensure that cost 

elements are neither omitted nor doublecounted.

Partially Met

The program utilized the FRA (SCC) and associated 

definitions for the capital investment costs. The cost 

estimate expands upon this structure to provide detailed 

identification of infrastructure work, but has reduced 

insight into common support costs. The standardized 

O&M FRA SCC elements were not used for capturing 

O&M costs because the O&M estimate was not required 

to comply with the SCC elements. While the O&M 

estimate includes common elements for administration 

and support costs, the O&M WBS is greatly simplified.

As a consequence, up to two-thirds of O&M costs are 

collected in a single cost element.
Appendix II: GAO Analysis of California HighSpeed Rail Authority’s Cost Estimates 

Page 74 GAO-13-304 California High Speed Rail 

Characteristic

Overall 

assessmenta

 Best practice Individual assessment

The estimate documents all costinfluencing ground rules and 

assumptions. 

Partially Met

Ground rules and assumptions are imbedded in much of 

the documentation for both the capital investment and 

O&M estimates as well as in the cost models, but not all 

assumptions have supporting rationale or sources. As 

the design for a specific section advances, risks are 

quantified and assigned to specific WBS elements. At 

the program level, contingency factors are used to 

capture less-defined risks. However, O&M risks are not 

specifically related to O&M WBS elements, and the 

impact of budget constraints on specific WBS elements 

has not been clearly defined. In addition, the impacts of 

technology maturity on cost are not entirely defendable.

Unless ground rules and assumptions are clearly 

documented, the cost estimate will not have a basis for 

areas of potential risk to be resolved.

Well 

documented

Partially Met The documentation should capture the 

source data used, the reliability of the 

data, and how the data were 

normalized.

Partially Met

The documentation provides some insight into the 

development of the cost estimates; however, much of 

our analysis was based on information derived from 

interviews and discussions with Authority 

representatives, not from readily available information in 

the documentation. The O&M model includes relevant 

data, but sources and variables can only be described as 

somewhat documented. For the most part, 

documentation relates how inputs are adjusted from past 

O&M models but fails to account for how earlier values 

were derived. Without sufficient background knowledge 

about the source and reliability of the data, the cost 

estimator cannot know with any confidence whether the 

data collected can be used directly or need to be 

modified. 

The documentation describes in 

sufficient detail the calculations 

performed and the estimating 

methodology used to derive each 

element’s cost.

Substantially Met

The documentation provided varying degrees of insight 

into the estimating methodology. The majority of costs—

that is, infrastructure and site work—are described at a 

detailed level by unit cost, quantities, labor rates, 

equipment, and material costs, and the like. However, 

some cost elements had little or no supporting 

documentation.
Appendix II: GAO Analysis of California HighSpeed Rail Authority’s Cost Estimates 

Page 75 GAO-13-304 California High Speed Rail 

Characteristic

Overall 

assessmenta

 Best practice Individual assessment

The documentation describes step-bystep how the estimate was developed so 

that a cost analyst unfamiliar with the 

program could understand what was 

done and replicate it.

Partially Met

Details of the estimating process and methodology were 

provided for the track structure and track and site work

elements of the capital investment model, but supporting 

data and details of how other elements are estimated 

were not available. No comprehensive document exists 

that explains the O&M model element by element.

Without good documentation, management and 

oversight will not be convinced that the estimate is 

credible. In addition, analysts unfamiliar with the program 

will not be able to replicate the estimate because they 

will not understand the logic behind it. 

The documentation discusses the 

technical baseline description and that 

the data in the baseline are consistent 

with the estimate.

Partially Met

The documentation of the capital investment cost model 

and the technical baseline are consistent with one 

another. The primary emphasis and underlying data 

sources are for the infrastructure and site work, but little 

definition or supporting data are provided for the 

remaining cost elements. In addition, the O&M cost 

estimate is not based on an approved technical baseline 

document, although officials state that later versions will 

be aligned to the Concept of Operations plan. Because 

the technical baseline is intended to serve as the basis 

for developing a cost estimate, it should be discussed in 

the cost estimate documentation. 

The documentation provides evidence 

that the cost estimate was reviewed and 

accepted by management.

Partially Met

Documents indicate that the Authority’s management 

team was engaged in reviewing the cost estimates and 

there are multiple indications that management reviewed 

pieces of the cost estimate. However, many of these 

reviews appear to be for subsets of the total program, 

either by construction package or phase, and focusing 

more on the financing rather than the detailed estimating 

methodology or underlying assumptions. While specific 

subsets of the estimate appeared to be reviewed by or 

discussed with management, we found no specific 

instance where the total program estimate, including 

supporting source data and estimating methodologies, 

was provided to senior management for review, 

discussion, and subsequent approval.

Because a cost estimate should form the basis for 

establishing the budget, it is imperative that 

management understands how the estimate was 

developed, including the risks associated with source 

data and estimating methodologies.
Appendix II: GAO Analysis of California HighSpeed Rail Authority’s Cost Estimates 

Page 76 GAO-13-304 California High Speed Rail 

Characteristic

Overall 

assessmenta

 Best practice Individual assessment

Credible Partially Met The cost estimate includes a sensitivity 

analysis that identifies a range of 

possible costs based on varying major 

assumptions, parameters, and data 

inputs.

Partially Met

A formal sensitivity analysis has been performed for 

Contract Package 1, design and construction of the first 

26-33 miles of trackway infrastructure between the 

counties of Madera and Fresno. In addition, the Authority 

conducted limited sensitivity analysis on summary-level 

variables in the O&M model. However, sensitivity 

analysis of the entire program estimate has not been 

done. The capital investment estimate includes low and 

high cost alternative alignments, and the O&M estimate 

provides three alternative scenarios driven by ridership 

options. However, without a complete sensitivity analysis 

that reveals how the cost estimate is affected by a 

change in a single assumption, the cost estimator will not 

fully understand which variable most affects the cost 

estimate.

A risk and uncertainty analysis was 

conducted that quantified the imperfectly 

understood risks and identified the 

effects of changing key cost driver 

assumptions and factors.

Partially Met

The Authority utilized FRA guidance in developing its 

estimates, guidance that does not require risk or 

uncertainty analysis at the program level this early in the 

design stage. Authority officials stated that more 

advanced engineering designs are being developed to 

support the process and that risk and uncertainty 

analysis has been undertaken on Contract Package 1.

Authority officials acknowledge the existence of risk and 

have tried to accommodate expected risk through the 

application of contingency factors. While the capital 

investment and O&M models include a contingency 

element, the factors used do not appear to be based on 

historical data or analogous sources.

Lacking risk and uncertainty analysis, management 

cannot determine a defensible level of contingency 

reserves that are necessary to cover increased costs 

resulting from unexpected design complexity, incomplete 

requirements, technology uncertainty, and other 

uncertainties. 
Appendix II: GAO Analysis of California HighSpeed Rail Authority’s Cost Estimates 

Page 77 GAO-13-304 California High Speed Rail 

Characteristic

Overall 

assessmenta

 Best practice Individual assessment

Major cost elements were crossed 

checked to see whether results were 

similar.

Partially Met

The Authority recognizes the importance of crosschecks 

and identified a series of crosschecks to verify and 

validate the results of the data. Authority officials stated 

there are several stages of crosschecks and quality 

control which are described in their cost estimating 

procedures. Yet little documentation has been provided 

that would allow us to verify that crosschecks and 

alternative methodologies have been developed. For 

example, estimators have crosschecked major cost 

factors in the O&M model with cost data from foreign 

systems, but there is no evidence that costs have been 

estimated using different methodologies.

The main purpose of cross-checking is to determine 

whether alternative methods produce similar results. If 

so, then confidence in the estimate increases, leading to 

greater credibility. The Authority has contracted with the 

International Union of Railways (UIC) for a study that 

intends to verify and validate the capital investment cost 

model. Authority officials stated that the UIC panel of 

experts will also provide a set of international cost 

comparisons for infrastructure maintenance and rolling 

stock maintenance.

An independent cost estimate was 

conducted by a group outside the 

acquiring organization to determine 

whether other estimating methods 

produce similar results.

Minimally Met

An independent cost estimate (ICE) was performed on 

the Merced-Fresno and Fresno-Bakersfield segments for 

infrastructure costs. However, while the segments cover 

35 percent of the planned system rail length, they make 

up less than 10 percent of the overall estimated program 

cost. An ICE should be performed on the entire program, 

including O&M costs. ICEs can provide decision makers 

with additional insights into a program’s potential costs 

because they frequently use different methods and are 

less burdened with organizational bias.

Source: GAO.

a

Not Met—The Authority provided no evidence that satisfies any of the criterion, Minimally Met—The 

Authority provided evidence that satisfies a small portion of the criterion, Partially Met—The Authority 

provided evidence that satisfies about half of the criterion, Substantially Met—The Authority provided 

evidence that satisfies a large portion of the criterion, and Fully Met—The Authority provided 

complete evidence that satisfies the entire criterion. 
Appendix III: Description of Generally 

Accepted Travel-Demand-Modeling Practices 

and Authority’s Methods for Developing 

Ridership and Revenue Forecasts

Page 78 GAO-13-304 California High Speed Rail 

Travel-demand-modeling 

tasks

Generally accepted travel-demand-modeling 

practices

Authority’s methods for developing ridership 

and revenue forecasts

Developing trip tables A central task of the ridership forecasting process 

involves collecting and compiling data on current 

travel patterns into trip tables. This process 

involves the following:

• Collection of trip table data: In order to 

calculate the number of trips that divert to the 

new or improved high-speed rail mode, the 

level of trip making without the new or 

improved high-speed rail mode must first be 

established. Reliable information on modal 

travel volumes is a prerequisite for valid 

ridership and revenue forecasts. The 

competing modes from which high-speed rail 

draws its share are mainly auto, rail, bus and 

air. There are various methods for collecting 

trip table data for these modes, including, 

obtaining publicly available data collected 

through travel surveys as well as from 

special-purpose surveys developed and 

undertaken for the purpose of a particular 

transportation study. Data can also be 

obtained from trip distribution models and 

ticket sales.

• Base and forecast year trip table 

development: The base and forecast year 

input trip tables are the basis for a study’s 

ridership estimates and revenue forecasts. 

Any overestimate or underestimate of the trip 

tables will translate to high or low forecasts of 

ridership. Base trip tables generally 

summarize the current total number of trips 

by mode for each city pair along the route and 

are generally prepared by using a variety of 

sources of data on actual trip making 

patterns. Growth factors—which determine 

the rate of increase over time—can then be 

applied to the base trip tables to develop 

forecast year trip tables, which contain 

estimates of future travel on various modes in 

the absence of a proposed high-speed rail 

alternative. Forecast year trip tables may also 

be prepared by estimating future-year trips 

directly.

• Trip segmentation: Trip tables are generally 

segmented by mode of travel, trip purpose, 

and other traveler characteristics. Criteria 

frequently used in defining market segments 

include trip purpose, trip length, traveler 

income, travel party size, and others.

• The Authority collected data from a variety of 

sources including, among others, 

socioeconomic data from local agencies, U.S. 

Census Bureau, and the California Department 

of Finance; travel data from various travel 

surveys; and highway, air, conventional rail, 

and urban transit network data from local 

agencies.

• The high-speed ridership and revenue model 

for inter-regional travel was developed utilizing 

surveys and other statewide travel information. 

Intra-regional travel models from Metropolitan 

Planning Organizations (MPOs) in the San 

Francisco and Los Angeles regions were 

adapted for use in the high-speed rail ridership 

and revenue model from the models maintained 

by the MPOs for those regions. A factoring 

process was used to estimate ridership in the 

San Diego region.

• Base year trip tables were developed from 

existing California regional models used by 

local authorities including the Metropolitan 

Transportation Commission (MTC) and the 

Southern California Association of 

Governments as well as interregional trip tables 

developed from travel survey data. Forecast 

year trip tables were developed by projecting 

base year forecast data to forecast year 2030, 

and then the models were run on 2030 

projections.

• Trip were segmented by long versus short trips 

(over and under 100 miles), and trip purposes 

(commute, business, recreation, other).

Appendix III: Description of Generally Accepted TravelDemand-Modeling Practices and Authority’s Methods 

for Developing Ridership and Revenue Forecasts
Appendix III: Description of Generally 

Accepted Travel-Demand-Modeling Practices 

and Authority’s Methods for Developing 

Ridership and Revenue Forecasts

Page 79 GAO-13-304 California High Speed Rail 

Travel-demand-modeling 

tasks

Generally accepted travel-demand-modeling 

practices

Authority’s methods for developing ridership 

and revenue forecasts

Determining and 

applying service 

characteristics 

Travel demand forecasts require information on 

the level of service (LOS) characteristics such as 

travel time and fares, of competing modes of 

travel, such as travel time for automobile and air 

travel, along the proposed route and of the highspeed rail alternative. LOS data are required for 

all modes in the study (i.e., air, rail, auto) and for 

base and forecast years. This information is used 

in the mode choice modeling process, whereby 

service characteristics of the various available 

modes are compared to the service characteristics 

of the proposed high-speed rail mode. This allows 

forecasters to estimate the likelihood that travelers 

will divert from their existing travel mode to highspeed rail.

Determining and applying service characteristics 

for a proposed network involves:

• Developing a network representation: 

Network representation can be detailed (i.e., 

with detailed representations of street and 

transit networks that include location, 

alignment, connections, and service 

characteristics) or can be less explicit and 

instead focus directly on zone to zone level of 

service data. A less explicit network 

representation can be used if the structure of 

the network is very simple).

• Preparing skim tables: Skim tables contain 

data on the time, cost, and other service 

characteristics of the various modes that are 

available for a trip.

Accurate and realistic representation of the base 

and forecast year LOS characteristics is of 

paramount importance for realistic high-speed 

ridership forecasting. Rail LOS information may be 

approximately derived from the service plan but 

may not represent it in complete detail. 

• The Authority developed a detailed network 

representation for the entire state to 

forecast travel between regions. Data 

were obtained from the existing statewide 

highway network and details were added 

using data from local regional models, from 

the MTC, the Southern California 

Association of Governments, the San 

Diego Association of Governments, and 

data from the Kern County region.

• LOS characteristics were defined for the 

four inter-regional travel modes: auto, 

conventional rail, high-speed rail, and air. 

LOS characteristics covered three broad 

categories: costs, times, and reliability, 

which were summarized in travel skim 

tables. Several of these characteristics 

were varied during model application to 

see how ridership and revenue would be 

impacted. Characteristics were collected 

from published or observed data from 

various sources including, the MTC and the 

Federal Aviation Administration. The highspeed rail characteristics were based on 

the initial service plan and fare structure.
Appendix III: Description of Generally 

Accepted Travel-Demand-Modeling Practices 

and Authority’s Methods for Developing 

Ridership and Revenue Forecasts 

Page 80 GAO-13-304 California High Speed Rail 

Travel-demand-modeling 

tasks

Generally accepted travel-demand-modeling 

practices

Authority’s methods for developing ridership 

and revenue forecasts

Developing a mode 

choice model

Mode choice modeling predicts the outcome of the 

decision process by which travelers choose the 

mode(s) to take from origin to destination. This 

step predicts the fraction of trips that will divert to 

the high-speed rail project from existing modes. 

Mode choice models are typically developed via a 

statistical analysis of the behavior of travelers in 

different situations. The statistical analysis may be 

based on behavior observed in actual travel 

situations (revealed preference data) or in 

hypothetical situations presented to travelers in a 

survey (stated preference data), or both.

Selection of the mode choice model structure is 

important to obtain reliable and credible ridership 

and revenue estimates. Two types of mode choice 

models are commonly used in high-speed rail 

demand forecasting:

• Choice models: These models are used to 

predict the decisions of travelers considering 

alternative transportation modes. Multinomial 

logit models and nested logit model are types 

of choice model that can be used.

• Diversion choice model: A diversion choice 

model considers only two modes–the one in 

use in the base situation and the high-speed 

rail alternative.

The Authority developed two choice models: intraregional urban model (models behavior associated 

with shorter distance and more frequent trip making) 

and an inter-regional model (models traveler 

behavior associated with longer-distance travel).

• Intra-regional (Urban) Models: For both the 

San Francisco Bay Area and the greater Los 

Angeles regions, mode choice models were 

adapted from existing models to include the 

high-speed rail mode. The updated mode 

choice models were applied using the MPO trip 

tables for each region as input. San Diego is 

the only other region that contains the 

possibility of intra-regional high-speed rail trips, 

but the estimate of these riders was very low 

relative to the other regions. Because the level 

of effort to develop, calibrate, and apply the 

regional mode choice model was very high, 

intra-regional ridership for San Diego was 

developed using a population-based estimate 

rather than a traditional mode choice model.

• Inter-regional models: The Authority 

developed four sets of models which included 

trip frequency, destination choice, primary 

mode choice, and access/egress mode choice. 

The destination choice component predicts the 

destinations of the trips generated in the trip 

frequency component based on zonal 

characteristics and travel impedances. The 

mode choice components (main mode choice, 

access mode choice and egress mode choice) 

predict the modes that the travelers would 

choose based upon the modal service levels as 

well as characteristics of the travelers and trips 

being made.

• Data were derived from, among other sources, 

the California Department of Transportation 

Statewide Model, existing regional mode choice 

models, and revealed preference and stated 

preference survey data. The economic and 

household characteristics were forecast for 

each zone in the year 2030 based on data and 

forecasts from state, regional, and local 

government agencies. The primary main mode 

choice model relied primarily on stated 

preference data. 
Appendix III: Description of Generally 

Accepted Travel-Demand-Modeling Practices 

and Authority’s Methods for Developing 

Ridership and Revenue Forecasts

Page 81 GAO-13-304 California High Speed Rail 

Travel-demand-modeling 

tasks

Generally accepted travel-demand-modeling 

practices

Authority’s methods for developing ridership 

and revenue forecasts

Estimating induced 

travel 

A high-speed rail project will improve the overall 

level of service for intercity travel within a given 

corridor. This improvement will make conditions 

more favorable for travel. Trips will therefore be 

taken on high-speed rail that might not otherwise 

have been made using any of the current modes. 

The new trips are commonly referred to as 

induced travel.

An upper limit on induced travel of approximately 

10 percent of total high-speed rail trips is widely 

accepted for proposed high-speed rail systems in 

the U.S. 

The Authority forecasted 2.05 percent induced travel 

for the blended Phase 1 low scenario. 

Estimate expected fare 

revenue 

Expected fare revenue is determined by a 

calculation using the ridership estimates 

generated by the model and the average fares. 

The total ridership for the system is generally 

calculated by adding the diverted trips calculated 

from the mode choice models and the induced 

trips to produce the total ridership for the system.

The Authority calculated fare revenue by multiplying 

the ridership estimates generated from the ridership 

model by the average high-speed rail fares 

forecasted for each region-to-region pair. 

Conduct sensitivity 

testing

All ridership and revenue forecasting studies 

should incorporate an analysis of the sensitivity of 

forecast results to key inputs and modeling 

assumptions including fare, running time, service 

frequency, station locations, and assumptions 

about socio-economic and travel growth in 

forecast years. Sensitivity analysis typically is 

conducted by varying, more or less systematically, 

selected forecasting model inputs, parameters, or 

assumptions (e.g., inflation rate or fuel cost) 

around their “standard” value, running the model, 

and examining the variation in outputs. Sensitivity 

analysis can help determine the reliability 

associated with the model output forecasts and 

can help identify the factors that have greatest 

impact on project ridership and revenue.

Several sensitivity tests were done to determine 

how the model reacted to different sets of 

assumptions such as changes to fuel costs, travel 

times, and fares. In addition, the Authority 

developed an extreme case scenario to test the 

sensitivity of the model to a series of downside 

events, such as increased average rail travel time 

from Merced to the San Fernando Valley (140 min. 

instead of 126 min), decreased train frequency (3 

trains per hour instead of 4 trains per hour during 

peak times), lower auto-operating costs and lower 

air fares (10 percent below actual 2009 average air 

fares). 

Conduct model 

validation

Model validation is a key component of ridership 

and revenue forecasting and generally consists of 

testing the validity of the model using data other 

than (and usually newer than) the data from which 

it was estimated, to assess how well the model 

predicts actual ridership.

There are two superior (but not often performed) 

ways of checking model performance: (1) the 

historical method, in which a prior-year model is 

used to forecast current travel, which is then 

compared with actual current travel; and (2) 

“backcasting,” in which a current year model is 

used to estimate travel for a prior year, which is 

then compared with actual travel in the prior year. 

Backcasting is used by 5 percent of all and 13 

percent of large MPOs. 

The Authority validated the model through tests 

performed using Amtrak’s Acela service in the 

Northeast Corridor (NEC) as input to the California 

high-speed rail model and compared the output with 

2008 actual ridership and 2030 NEC forecasts. 

Efforts to validate the model by comparing to the 

NEC appear reasonable. The NEC is not an ideal 

test for the model but it is the only one available in 

the U.S. Use of foreign systems would raise difficult 

issues of comparability.

Source: GAO, DOT OIG, FHWA, FTA, and academic studies of ridership and revenue best practices and Authority information.
Appendix IV: Comments from the California 

High-Speed Rail Authority 

Page 82 GAO-13-304 California High Speed Rail 

Appendix IV: Comments from the California 

High-Speed Rail Authority
Appendix IV: Comments from the California 

High-Speed Rail Authority 

Page 83 GAO-13-304 California High Speed Rail 
Appendix V: GAO Contact and Staff 

Acknowledgment

Page 84 GAO-13-304 California High Speed Rail 

Susan A. Fleming, (202) 512-2834 or flemings@gao.gov

In addition to the individual named above, Paul Aussendorf, Assistant 

Director; Russell Burnett; Jason Lee; Delwen Jones; Richard Jorgenson; 

James Manzo (Technomics, Inc.); Maria Mercado; Susan Offutt; Paul 

Revesz; Max Sawicky; Maria Wallace; and Crystal Wesco made key 

contributions to this report.

Appendix V: GAO Contact and Staff 

Acknowledgment 

GAO Contact

Staff 

Acknowledgments

(541090)
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