1. Freight Transportation System Performance and the Economy Identifying Economic Benefits Resulting from Freight Infrastructure Improvements FHWA Talking Freight Seminar Series Rob Mulholland ICF International December 12, 2007 for

2. 1 Today’s Presentation ■ Background/Introduction  Transportation Planning and Project Evaluation  Infrastructure and Economic Activity  Study Introduction ■ Freight BCA Project Update  Project Scope  Theoretical Framework  Benefits Estimation  Regional Planning Tool Development Photos from FHWA website

3. 2 Background –Transportation Planning and Project Evaluation ■ Given: Transportation planners should seek to maximize the return on infrastructure investments  BCA is a critical tool in the investment decision process ■ BCA models currently in use are proven and reliable but have some limitations  Benefits arising from transportation infrastructure improvements accrue over time  Short-run benefits are captured using existing tools but long- run benefits are not

4. 3 Background –Infrastructure and Economic Activity ■ Transportation infrastructure investment decisions affect system performance  Efficiency (velocity, cost, reliability)  Productivity (output per unit of input) ■ When productivity improves, economic expansion is possible  Over time, businesses change their operations in response to changes in production costs (including transportation)  Output (volume) increases

5. 4 Study Introduction ■ A new methodology is needed to capture these long- run benefits  Develop a BCA framework that recognizes gains from productivity enhancing logistics changes in response to transportation infrastructure improvements  Identifying tangible economic benefits associated with improved freight flow will facilitate the incorporation of freight considerations into the planning process

6. 5 Freight BCA Project Scope ■ Phase I  Established Theory  Developed Conceptual Framework ■ Phase II  Developed National BCA Model  Empirical Testing and Preliminary Benefits Estimation ■ Phase III  Developed Regional BCA Model  Developed Planning Tool ■ Phase IV  Outreach and Education

7. 6 Theoretical Framework Development ■ Transportation infrastructure improvements enhance freight movement and produce economic benefits  Increased velocity and reliability (reduced transportation costs)  Increased productivity (more and longer trips using same resources)  Increased supply-chain efficiency (improved reliability and reduced costs allow market expansion and change transportation and inventory balance -- overall production costs decrease)  Increased volume (reduced production costs lead to 1) supply chain evolution, and 2) reduced costs for finished products or improved products -- demand and output increase)

8. 7 Theoretical Framework Development ■ Short-run  Shipper behavior doesn’t change, but shipper receives benefit in the form of reduced costs ■ Medium-run  Shipper behavior changes, shipper buys more transportation but doesn’t make wholesale changes to logistics network — Shipper may source materials from different suppliers or begin to replace inventory with transportation — Shippers are still hedging bets ■ Long-run  Shipper behavior changes, supply-chain is permanently altered — Inventory models, routing, facility locations change, new supply-chain partnerships emerge — Markets expand, the freight transportation demand curve shifts

9. 8 Shipper Response to Transportation Cost Reductions C0C0 C1C1 a b c Q2Q2 Q1Q1 Q0Q0 Benefits Categories a = Short-run benefits (cost reduction) b = Medium-run benefits (buy more transport) c = Long-run benefits (supply-chain evolution) Transportation Units Transportation Cost per Unit D1D1 D0D0

10. 9 Categories of Benefits Measurable with Current Models Not Measured Short-run * Transit time reductions * Operating cost reductions * Reduced crashes * Reduced emissions Long-run * Supply-chain evolution * Suppliers, routes, facilities, partners * New demand curve Medium-run * Buy more transportation * Minor (preliminary) logistics changes a c b

11. 10 Phase II - Estimating Demand Elasticity ■ Demand elasticity can be measured as a function of transport cost and reliability, where:  Transport cost equals the monetary costs (or rates) of shipping goods — In a free market, changes in shipper rates reflect changes in carrier operating costs  Reliability equals the level of highway performance for a given segment of infrastructure — All other things being equal, as the volume-to-capacity ratio (V/C) decreases, velocity increases and delay is reduced

12. 11 Phase II - Preliminary Demand Elasticity Estimate ■ Regression analysis using data for 30 highway corridors over 8 years (1993-2000) showed the following correlations:  There is a positive relationship between freight rates and highway performance measures — Increased highway congestion leads to increased shipping rates over a specific corridor (holding other variables constant)  There is a negative relationship between demand for freight transportation and freight rates — Increased shipping rates lead to reduced truck traffic over a specific corridor (holding other variables constant)  There is a negative relationship between demand for freight transportation and highway performance measures — Increased highway congestion leads to reduced truck traffic over a specific corridor (holding other variables constant)

13. 12 Phase II - Preliminary Demand Elasticity Estimate ■ A quantifiable relationship between transportation infrastructure improvements and long-run shipper behavior exists  Based on national data, a 10% decrease in measured congestion (V/C ratio) along a corridor would increase freight demand (truck volumes) by up to 1% — This is a measure of the shift in the demand curve  This led to a finding that traditional BCA models may underestimate long-run benefits by as much as 15% — This is a measure of benefit “c” as a percentage of benefits “a” + “b” — [ c / ( a + b ) ]

14. 13 Phase II - Limitations to Preliminary Demand Elasticity Estimate ■ A tool is only as reliable as the supporting data  The thirty (30) corridors included in the study were selected because they had significant freight volumes during the study period — The corridors were located across the Nation — The corridors varied greatly in length (ranging from 105 miles for Harrisburg-Philadelphia to 734 miles for Salt Lake City-San Francisco), structure, total traffic volume, and congestion level  V/C and delay data from HPMS  Demand (truck volume) data from HPMS and FAF

15. 14 Phase II – Other Key Findings ■ The elasticity is smaller when generalized cost is relatively low and higher when generalized cost is relatively high, implying that demand is more sensitive to changes in highway conditions when congestion is high than when congestion is low ■ For years, freight moved relatively efficiently through the modal transportation networks as capacity was sufficient ■ The modal networks are increasingly congested, and growth in intermodal freight has led to bottlenecks at modal interchanges ■ Freight and passenger VMT have and will continue to increase at a much faster rate than capacity expansion ■ Future transportation system improvements can have a significant economic impact

16. 15 Applicability of Phase II Findings ■ Though the national model produced defensible results, there was a real question left to be answered  To whom do the benefits accrue? ■ Much freight moves over long distances  Freight is footloose (routes and volumes continually changing in response to market forces)  Freight tends to follow the path of least resistance

17. 16 Applicability of Phase II Findings ■ Much of the freight transportation network is publicly owned and maintained  In general, road transportation infrastructure planning occurs at the local level — Historically, the primary focus has been on improving local passenger travel — Recently, transportation planners are becoming more interested in freight movement issues and are looking for ways to better incorporate freight considerations in the planning process  Transportation infrastructure funding requires a long-term public commitment  The transportation planning process is deliberate

18. 17 Applicability of Phase II Findings ■ Philanthropy is a noble pursuit, but local planners rightly are concerned first with the well-being of their own region  Without a model that can measure economic benefits on a regional scale, the theoretical framework is of little practical use  The next problem would be to distill the key elements from the national model and apply them on the regional level

19. 18 Phase III Regional Model ■ HDR developed a tool that estimates freight demand elasticity (and long-run economic benefits resulting from freight volume increases) with respect to highway performance for three regions (East, Central, West)  The tool is based on analysis of 59 corridors over 12 years (1992-2003) ■ The tool is distributable and user accessible  Microsoft Excel-based  508 Compliant ■ The tool is supplemented by a complete user guide

20. 19 Regional Model Welcome Screen

21. 20 Regional Model Process ■ Planners provide project-specific inputs  Segment information  Value of time  Vehicle operating costs  Changes in travel time, operating costs and reliability ■ Default values can be used if particular inputs are unavailable.

22. 21 Regional Model Input Screens

23. 22 Regional Model Benefits Estimation ■ Outputs from an existing BCA model are used to determine:  Baseline Demand and Performance  Expected Improvement  Measured Freight-specific Benefits (“a”) + (“b”) ■ Regionally elasticities are used to estimate long-run demand shift ■ Ratio of long-run benefit (“c”) to cost savings (“a”) + consumer surplus (“b”) is calculated ■ Reorganization benefit is added to traditional benefit

24. 23 Regional Model Long-Run Demand Shift

25. 24 Regional Model Additive Benefits

26. 25 For Further Information ■ Presentation  Rob Mulholland  RMulholland@icfi.com ■ Regional BCA Tool  Ed Strocko  Ed.Strocko@dot.gov  http://ops.fhwa.dot.gov/freight/freight_analysis/econ_methods.htm