forecasting transportation revenue sources: survey...
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NCHRP Project 20-05 ● Synthesis Topic 45-07
Forecasting Transportation Revenue Sources: Survey of State Practices
Martin Wachs Department of Urban Planning, UCLA
Benton Heimsath
HR&A Advisors, Inc.
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Revenue Forecasting • Financial forecasts provide baseline information needed
for transportation planning and system management.
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Purpose of the Synthesis • To help practitioners improve methods of forecasting and
to assist DOTs as they explore ways to enhance future revenue, including the development of new methods of revenue generation
• Questions:
• How do states forecast transportation revenues? • Which states have the most sophisticated forecasting tools? Is that
sophistication helpful or important? • What are states doing to account for “innovative” (non-traditional)
transportation revenue sources?
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Transportation Funding Context • State transportation revenues are stagnant and declining. • Raising motor fuel tax is politically challenging. • The federal gasoline tax is unchanged since 1993. • Gasoline consumption has declined each year since 2008.
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Vehicle Miles Traveled
Gas Consumption withIncreased Efficiency
Revenue Loss
VMT Growth
Background • Fuel shocks in 1970s led to an interest in accurate
forecasting of future revenues. • Main variable examined was demand for gasoline (VMT,
fleet fuel efficiency) • Regression models using socioeconomic factors such as
income, employment, population.
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Surface Transportation Funding
21%
43%
36%
By Revenue Source
FederalStateLocal
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(Source: AASHTO Center for Excellence in Project Finance)
Elements of the Synthesis • Information on current standard methods and new
developments in revenue forecasting by state DOTs • How states project revenue from both traditional and new
and non-traditional sources • What issues they have faced implementing new revenue
generating mechanisms and approaches, and how those issues were addressed
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Research Methods Used • Review of the literature
• recent academic research reports, articles in professional journals, agency newsletters
• National survey of state DOTs • 47 of 52 DOTs responded (87% response rate)
• Telephone interviews of state officials • Reviews of documents describing state practices.
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Example Survey Questions “Does your agency produce long-term revenue forecasts, or are they produced by another entity?” “Which revenues are typically projected?” “Has your agency changed its methods recently?” “What are the major challenges your agency faces?”
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Responses: 44 states and DC • 87% response rate • Respondents were economists, planners, financial
analysts, transportation commissioners, etc.
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Yes 13 No 31 Unsure 1
Types of Revenues Forecast Revenue Type # of States % State gasoline per gallon taxes 43 96% State diesel fuel per gallon taxes 42 93% State vehicle registration and/or license fees 39 87% Federal funds allocated to the state 39 87% State sales taxes designated for transportation 23 51% Allocations of state general revenues 15 33% Other 14 31% Tolls 9 20% Local (county or regional) sales and property taxes 6 13%
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Consensus of Experts
Simple Extrapolation
Econometric Regression
Approaches to Conducting Forecasts
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Interesting Observations Not Anticipated • State DOTs reported that they see themselves as
“operating agencies,” which refrain from making forecasts for the purpose of influencing policies or suggesting new options to legislators or governors…. • “If the state wants to evaluate the consequences of a new revenue
source, they should not ask us, but rather should rely on legislative staff, governor’s staff, or consultants”
• DOT revenue forecasts of revenue are more associated with revenue management and operational planning than with strategic innovation
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Other Agencies Involved CO: General Assembly Legislative Council Staff and Office of State Planning and Budgeting CA: Department of Finance DC: Office of Tax and Revenue + Bureau of Transportation Statistics to estimate fuel efficiency FL: Twice-yearly Revenue Estimating Conference for 10 yr forecast, members include Legislature, Dept of Revenue, Dept of Highway Safety, DMV GA: Cambridge Systematics does long term forecast that is used in the development of Statewide Transportation Plan LA: Revenue Estimating Conference for short-term, simplified growth assumptions for long-term forecast
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Econometric Regression • Majority of state respondents used some form of
econometric analysis.
• Simple linear regression vs. time series analysis
• Often used to estimate quantities, such as gallons of gasoline consumed, which are then multiplied by taxes/fees to determine revenue forecasts.
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Washington • The Washington gasoline forecast is derived from a regression model
that estimates per capita gasoline consumption using 10 independent variables.
• Quarterly Model Equation –The equation for gasoline consumption in Washington is defined as
ln (Gas) = α + φln(WA_Emp) + φ(WA_GasP*Eff) + δ(Dummy) + ε Where 1. Gas= Quarterly gross gas consumption from Treasurer Reports (log), 2. WA_Emp= Quarterly Washington non-farm employment(log), 3. WA_GasP*Eff = Quarterly Washington gas prices* US average fuel efficiency(log)lagged
2 quarters, 4. Dummy = Quarterly dummy variable for periods of severe oil shortages. 5. ε = Stochastic disturbance on gasoline consumption. • Independent variables are able to explain most of the variations in
gasoline consumption.
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Sources of Data for Washington DOT’s Econometric Models
Variables Sources WA personal income Based on the Washington Economic and Revenue
Forecast Council in short-term (through 2017) based on forecasts from Blue Chip average US GDP growth rates
and NYMEX fuel prices; and long-term Global Insight forecast
Population Preliminary Office of Financial Management population projections
Inflation (2 measures: CPI and IPDC)
Washington Economic and Revenue Forecast Council for short-term and Global Insight forecast for long-term
Employment WA non-ag. employment; WA TTU, WA retail trade and national unemployment rates
Oil price index 2014 Global Insight forecast Fuel efficiency 2014 short and long-term Global Insight forecast
U.S. sales of light vehicles 2014 Global Insight forecast and November 2013 long-term Global Insight forecast3
U.S. fuel prices (retail gas and diesel and index of petroleum
products)
EIA for short-term and Global Insight for long-term
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Washington - Motor Vehicle Fuel Consumption Forecast, June 2013
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Source: Transportation Revenue Forecast Council June 2013 Transportation Economic and Revenue Forecasts
Washington - Motor Vehicle Fuel Tax Revenue Forecast, June 2013
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Source: Transportation Revenue Forecast Council June 2013 Transportation Economic and Revenue Forecasts
Missouri • In 2006, MODOT commissioned a private consulting firm
to address decreasing accuracy in revenue forecasts.
• New proposed model used six independent variables (up from four), a more sophisticated risk analysis process and time-series regression models.
• The framework is no longer used by MODOT staff. • Takeaway: More complexity does not necessarily result in
more useful or accurate models.
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Source: Revised 2014–2016 Revenue Outlook (dollars in millions)
Staff Recommended Consensus Forecast Update— Difference from July 2013 Forecast
2014 2015 2016 Dollars Percent Dollars Percent Dollars Percent
General Fund $8.4 0.6% -$0.4 0.0% -$13.8 -1.0%
Transportation Fund $4.2 1.7% $1.1 0.4% -$0.6 -0.2%
Education Fund $1.1 0.6% -$0.1 -0.1% -$0.5 -0.3%
Total $13.7 0.8% $0.5 0.0% -$15.0 -0.8%
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Accuracy Measurement • Several states reported that they commonly performed
retrospective analysis to determine forecasting accuracy.
Vermont Emergency Board Consensus Update to Fund Forecasts
Interesting Excerpts from Responses AK: “All our forecasting techniques are based on assumptions.” CT: “Purposely very conservative.” DE: “Forecasts have been very accurate, except in recessionary periods.” IN: “5 year forecast each year within 98% match.” LA: “The economists that provide forecasts are more interested in the state general fund forecast and sometimes do not fully analyze the factors affecting the forecast of gasoline tax.”
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Many States Use “Takedowns” from Federal Agency Forecasts • Federal Revenue Forecasting Model (FRFM) maintained
by FHWA - a fairly simple multiple spreadsheet models manually updated using some data series which may be out of date. Twenty classes of vehicles, 36 weight groups many revenue types; limited public documentation available
• National Energy Modeling System (NEMS) by Energy
Information Agency (EIA) of the Department of Energy (DOE). More complex and better documented; includes a specific “transportation module.”
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Minnesota: A Blended Approach
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Minnesota’s DOT’s Fuel Consumption Inputs, 2013–2017
Source: Minnesota’s DOT 2014 Transportation Funds Forecast (2014).
Conclusions • There is little evidence of attempts to forecast innovative,
“non-traditional” revenue sources
• More research is needed to share knowledge and develop state-of-the-art forecasting econometric tools for state DOT needs
• State forecasting needs vary widely in terms of sophistication and breadth
• States should proactively develop forecasts to inform policymakers about the revenue implications of new revenue sources
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Potential Initiatives • DOT staff responsible for revenue forecasting in some
states regularly consult with those having similar responsibilities in other states, but many other state forecasters do not.
• There is insufficient knowledge to lead us to suggest that states adopt standard methods.
• Information sharing among the states could be improved.
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Potential Initiatives • A regularly updated website on transportation revenue
forecasting, perhaps maintained by AASHTO’s Center of Excellence in Project Finance
• A blog to facilitate exchanges between relevant staff and different state agencies
• Regular sessions on transportation revenue forecasting at AASHTO and TRB Annual Meetings
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For More Details Please See Our Report • NCHRP Synthesis Report 479 –
Forecasting Transportation Revenue Sources: survey of State Practices Thanks for your attention – It’s time for Questions, Comments, and ….
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