Assessing Productivity Impacts of Transportation Investments (2014)

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N A T I O N A L C O O P E R A T I V E H I G H W A Y R E S E A R C H P R O G R A M NCHRP REPORT 786 Assessing Productivity Impacts of Transportation Investments Glen Weisbrod and Naomi Stein Economic DEvElopmEnt REsEaRch GRoup, inc. Boston, MA Christopher Williges systEm mEtRics GRoup, inc. San Francisco, CA Peter Mackie, James Laird, and Daniel Johnson institutE foR tRanspoRt stuDiEs, univERsity of lEEDs Leeds, England David Simmonds DaviD simmonDs consultancy, ltD. Cambridge, England Elizabeth Ogard pRimE focus, llc DePere, WI David Gillen sauDER school of BusinEss, univERsity of BRitish columBia Vancouver, BC, Canada Roger Vickerman univERsity of KEnt Canterbury, England Subscriber Categories Economics • Freight Transportation • Planning and Forecasting TRANSPORTAT ION RESEARCH BOARD WASHINGTON, D.C. 2014 www.TRB.org Research sponsored by the American Association of State Highway and Transportation Officials in cooperation with the Federal Highway Administration

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C O O P E R A T I V E R E S E A R C H P R O G R A M S ACKNOWLEDGMENTS The research reported herein was performed under NCHRP Project 02-24. Economic Development Research Group, Inc. was the prime contractor for this study, supported by Systems Metrics Group, the University of Leeds, David Simmonds Consultancy, Prime Focus, and additional consultants. This report is the product of a collaborative effort of researchers including the following: •• Economic Development Research Group, Inc.—Glen Weisbrod (principal investigator) and Naomi Stein, with assistance from staff members: Chandler Duncan, Derek Cutler, and Brian Alstadt, and additional assistance from consultants Daniel Brod, John Stevens, and Michael Brown; •• System Metrics Group, Inc.—Christopher Williges; •• Institute for Transport Studies, University of Leeds (UK)—Peter Mackie, James Laird, and Daniel Johnson; •• David Simmonds Consultancy, Ltd. (UK)—David Simmonds; •• Prime Focus, LLC—Elizabeth Ogard; •• David Gillen (Sauder School of Business, University of British Columbia); •• Roger Vickerman (University of Kent). The Study team is grateful to the Wasatch Front Regional Council (the Salt Lake City area MPO) and its staff for allowing its travel demand model to be used for this project, and for supporting the project team in this effort. The study team is also grateful to Sharada Vadali of the Texas A&M Transportation Institute for suggestions and insights. Responsibility for any errors in the content of this report lies entirely with the authors. CRP STAFF FOR NCHRP REPORT 786 Christopher W. Jenks, Director, Cooperative Research Programs Christopher Hedges, Manager, National Cooperative Highway Research Program Andrew C. Lemer, Senior Program Officer Sheila Moore, Senior Program Assistant Eileen P. Delaney, Director of Publications Hilary Freer, Senior Editor NCHRP PROJECT 02-24 PANEL Field of Administration—Area of Economics Patrick E. Morin, Washington State DOT, Olympia, WA (Chair) Barry Padilla, California DOT, Sacramento, CA Alexander Heil, Port Authority of New York and New Jersey, New York, NY Joshua L. Rosenbloom, University of Kansas, Lawrence, KS Robert T. Russell, Guanajuato, Mexico Denise D. Whitney Dahlke, Oregon DOT, Salem, OR Rabinder K. Bains, FHWA Liaison

NCHRP Report 786: Assessing Productivity Impacts of Transportation Investments presents a methodology for analyzing productivity effects of transportation system improvements. The analysis is intended to inform decisionmakers—for example, regional transportation planning agencies, local-government agencies, and elected officials—making choices among alternative investments that may yield a variety of benefits. The methodology involves first screening investments to identify those for which a relatively simplified analysis may be helpful; those requiring more extensive analysis require application of advanced regional economic models. The guidance addresses data needs, availability, and sources to sup- port the analysis; agency staff capabilities; and audiences for information on productivity improvements. This report will be useful to DOT staff and others responsible for project evaluation and presentation of evaluation results to decisionmakers. State departments of transportation (DOTs) and other agencies generally must consider many more opportunities for improving their transportation systems than they have fund- ing to implement. Agency staff must evaluate the relative merits of investment options to determine which will produce the greatest benefit for taxpayers and citizens—the system’s owners. DOTs typically use various methods to make these evaluations in terms of multiple objectives such as enhanced safety, environmental protection, and cost savings. These meth- ods include multi-criteria analysis (MCA) and benefit-cost analysis (BCA). MCA involves rating and scoring proposed investments on a single or multiple scales; multiple scales may include, for example, life-cycle cost, environmental impact, and road-user safety impact. BCA relies on estimation of the economic value of an investment’s several costs and benefits accruing over the lifetime of that investment, measured in monetary terms. Under either approach, travel-time savings are typically a substantial component of ben- efit attributed to the investment. These savings are enjoyed by the transportation system’s users but have only a general relationship with the productivity of the region’s specific businesses and labor force. Productivity gains for businesses, in particular, are in principle an important consequence of transportation system improvements but critics argue that current MCA and BCA practices generally neglect the wider economic productivity gains attributable to transportation system improvements. Fast and reliable delivery of goods and services, for example, can (1) reduce the need for delivery vehicles, warehouse space, and investment in equipment and facilities; and (2) increase the rate at which workers can complete their tasks. Many economic activities simply could not continue without effective transportation facilities. The cumulative effect of multifactor productivity gains can influence the competitiveness of firms in a region and the attractiveness of the region for companies and workers considering relocation from other areas. F O R E W O R D By Andrew C. Lemer Staff Officer Transportation Research Board

The objective of NCHRP Project 02-24, “Economic Productivity and Transportation Investment Priorities,” was to develop a methodology and guide for incorporating produc- tivity gains in analysis and prioritization of transportation investments. The intent was that the methodology and guide would encourage DOTs and other agencies to apply consistent analysis methods to produce results that facilitate public decision making about transporta- tion improvement priorities within a state or other large region. The research was conducted by a team led by Economic Development Research Group, Inc., of Boston, MA. The research team conducted a critical review of literature on the links between transportation system performance and economic productivity, including theo- retical research and empirical studies and micro- as well as macro-economic perspectives. A literature review document prepared in the project’s first phase supported the team’s subsequent work to characterize the influence of transportation system performance on total factor productivity and how the influence of system improvements on productivity may be explicitly assessed. The team considered the factors driving multifactor productiv- ity improvement, the characteristics of regional economies that make them susceptible to influence by transportation improvements, and how increased productivity attributable to transportation system improvements in a region may be projected. The team then formulated a procedure for analyzing the productivity effects of trans- portation system improvements. The procedure involves screening investments to identify those for which a relatively simplified analysis may be helpful. Investments requiring more extensive analysis require application of advanced regional economic models. The research team then prepared guidance for incorporating productivity gains into analysis for priori- tizing transportation investment projects. The guidance addresses data needs, availability, and sources to support analysis and agency staff capabilities. This final report is meant to be used by DOT staff and others responsible for project evaluation and presentation of evalu- ation results to decisionmakers.

1 Summary 3 Glossary 7 Chapter 1 Introduction: Understanding Productivity 7 1.1 Motivation and Overview 9 1.2 Defining Productivity and Transportation Effects 14 1.3 Relationship to Benefit and Impact Metrics 16 1.4 Alternative Measures of Productivity 19 1.5 State of Research and Practice 21 Chapter 2 Using Productivity Information to Support Transportation Decisions 21 2.1 Defining the Elements of Productivity Impacts 22 2.2 Determining the Relevancy of Productivity Impacts 25 2.3 Incorporating Productivity Impacts into Project Evaluation 31 Chapter 3 Guidance: Steps to Assess Productivity Impacts 31 3.1 Overall Framework and Sequence of Steps 32 3.2 Step 1—Screen for Productivity Impacts 36 3.3 Step 2—Select Applicable Tools 41 3.4 Step 3—Measure STBs 46 3.5 Step 4—Calculate Wider Transportation Benefits 52 3.6 Step 5—Calculate Productivity Elements 55 3.7 Step 6—Present and Interpret Productivity Results 62 Chapter 4 Case Studies: Calculation Examples 62 4.1 Overview, Use, and Interpretation of Case Studies 63 4.2 Example A—Bypass Route to Enhance Reliability 70 4.3 Example B—Multimodal Corridor: Market Access 80 4.4 Example C—Intermodal Connectivity Enhancement 90 Chapter 5 Tools for Assessing Wider Transportation Effects 90 5.1 Use of Travel Demand Models 92 5.2 Reliability Analysis Tools 97 5.3 Accessibility Analysis Tools 101 5.4 Intermodal Connectivity Tools 103 5.5 Logistics Cost Analysis Framework 109 5.6 LUTI and Macroeconomic Impact Analysis Tools 111 References C O N T E N T S

114 Appendix A Further Refinements 121 Appendix B Calculating Agglomeration Impacts 128 Appendix C Directions for Future Research Note: Many of the photographs, figures, and tables in this report have been converted from color to grayscale for printing. The electronic version of the report (posted on the Web at www.trb.org) retains the color versions.