Cost-Benefit Analysis of Transit Projects: Current Practice and Methodological Advances

Transcription

1 Cost-Benefit Analysis of Transit Projects: Current Practice and Methodological Advances Elena Safirova Presented at New York University October 26, 2011

2 Outline What is Cost-Benefit Analysis? Benefits of Transit Transit Infrastructure CBA: State of Practice Transit Benefits: Potential Drawbacks FTA LUSTRE Project Project Goals LUSTRE Framework Work Description Concluding Remarks

3 What is CBA? A cost-benefit analysis is a systematic evaluation of the economic advantages (benefits) and disadvantages (costs) of a set of investment alternatives A sum of discounted benefits is compared to a stream of discounted costs. Benefit/cost ratio should be greater than 1 to justify the investment

4 Benefits of Transit (1) Benefits to System s Users Travel time reduction Travel cost reduction Non-user Benefits Congestion reduction Social Benefits Related to overall VMT reduction Environmental Benefits Accident Reductions

5 Benefits of Transit (2) Benefits to vulnerable populations Significant reductions in costs to individuals Reduction in agency costs (e.g. paratransit) Benefits of Transit-Oriented Development (TOD) Changes in travel patterns Changes in lifestyle (e.g. health benefits) Increase in land values

6 Costs of Transit Projects Not significantly different from other infrastructure projects Cost escalation due to project delay and initial cost underestimation Solution: cost management in a riskanalytic framework

7 Transit CBA in Practice: Menu of Programs FTA: New Starts DOT: TIGER I TIGER II TIGER III State and MPO-level programs

8 Transit CBA: Methodology Usually: a collection of disjoint categories of benefits Inclusion of a particular benefit is largely data-driven Due to the fragmentary approach, positive changes in benefits may be included while negative are omitted

9 Common Drawbacks of Practical Approach High probability of double-counting E.g. travel-related benefits an TOD-related benefits High probability of omitting large categories of benefits Fragmentary nature of accounting Inconsistencies between benefit categories

10 Benefits of Travel and TOD TOD and travel are interconnected TOD affects the demand for travel TOD changes spatial distribution of economic activity in the entire region, and, as a result, changes the demand for travel However, travel-related benefits are projected using regional travel demand model, and TOD benefits are estimated separately using different methods

11 FTA LUSTRE Project Objectives Develop proof of a concept framework that demonstrates a relationship between transportation and environment benefits of transit projects Investigate the ratio of transportation and environment benefits Advance evaluation methodology of transit projects

12 Land Use, Strategic Transport, Regional Economy (LUSTRE) Literature Review Spatially Distributed Households Spatially Disaggregated Transportation Industry Modeling General Equilibrium Effects LUSTRE Overview LUSTRE=START+RELU Data and Calibration November 11

13 Washington-START Model Transportation simulation model Developed by RFF researchers using START modeling suite Designed for quick policy analysis Evaluation of policies using a consistent economic framework Not politically constrained Calibrated for Washington, DC metro area November 11

14 RELU Model Features Spatially disaggregated general equilibrium model of economic activity without predetermined location of residents and firms Some extras 4 income classes Employed and unemployed Explicit modeling of housing Developers and landlords decisions Income and property taxes November 11

15 LUSTRE Model Overview LUSTRE GCT START Supply-Side Module Route Network Rail Systems Bus System Parking Facilities Demand-Side Module Logit Tree: Purpose/Origin (given) Trip Generation Destination Mode Time Route Trips Generalized Costs of Travel Wages & Trips Real Estate Labor Supply/ Wage Developers RELU Individuals Discrete Choices: Choice of Work Status Choice of Work Location Choice of Residence Continuous Choices: Housing Consumption Retail Goods & Services Producers Retail Agriculture Manufacturing Business Services Constr/Demo Labor Capital Stock Rent I/O* Space Price Rent Rent I/O Freight Landlords Generalized Costs of Travel *Intermediate demand for finished goods and services, also referred as Input/Output (I/O) tables.

16 LUSTRE features Consistent spatial disaggregation Non-monocentricity Agent heterogeneity Unemployment Frictions Income and real estate taxes Congestible alternative modes November 11

17 2000 Census SF1A & SF3A CTPP Data Sources BEA production data Consumer Expenditure Survey MWCOG transportation data Land use data November 11

18 Wage and Income Information for LUSTRE Baseline Average Net Income* (2000$/year) Average Gross Wages Rates (2000$/hour) Income Tax Rates.. Quartile % Quartile % Quartile % Quartile % *Net of taxes and commuting costs November 11

19 Population Distribution Over the Region Quartile 1 (relative to active population) Quartile 2 (relative to active population) Quartile 3 (relative to active population) Quartile 4 (relative to active population) Total (relative to active population) All Study Area Active Population Employed (56.1%) (78.5%) (92.0%) (97.5%) (76.7%) Population Distribution for the Downtown Core Quartile 1 (relative to active population) Quartile 2 (relative to active population) Quartile 3 (relative to active population) Quartile 4 (relative to active population) Total (relative to active population) Downtown Core Residents Workers from All Zones Active Population Employed Total per year (53.0%) (74.8%) (88.7%) (96.8%) (72.2%) November 11

20 Trips Distribution for LUSTRE Baseline Distribution over Time Periods All Study Area Ending at Downtown Core Commuting Shopping All Trips Commuting Shopping All Trips Trips Trips Trips Trips (Thousands (Thousands (Thousands (Thousands (Thousands (Thousands /Day) /Day) /Day) /Day) /Day) /Day) AM Peak PMPeak Off Peak Total AM Peak : From 6:30 am to 9:30 am PM Peak : From 3:30 pm to 6:30 pm Distribution over Mode of Transportation Bus Rail SOV HOV Walking / Biking All Study Area Commuting Shopping All Trips Trips Trips (Thousands (Thousands (Thousands /Day) /Day) /Day) SOV : Single Occupancy Vehicle HOV : High Occupancy Vehicle Ending at Downtown Core Commuting Shopping All Trips Trips Trips (Thousands (Thousands (Thousands /Day) /Day) /Day) November 11

21 Modeling area November 11

22 Dulles Rail Project 23-mile extension of the existing Metrorail system Will connect Downtown Washington DC with Dulles International Airport and surrounding area The project will include 11 new stations

23

24

25 Zoom-in Tool Zoom-in Land Use Module Zoom-in Transportation Module Approaches: Little LUSTRE Little RELU + Simplified transportation module (STM) Simplified RELU + Little START Simplified RELU + Simplified transportation module (STM)

26 Simplified Transportation Module 3 suggested versions Start Lite Simple mode choice model Likely a Logit based mode choice, with a very simple route structure. (No parking search, etc) Econometric model We can calibrate this model by using START model runs

27 Simplified RELU Several features could be suppressed/simplified: Shopping modeling Features of Closed Economy Modified developers module Goal: to retain consistency in welfare measurement while capturing key land use metrics

28 Integration between Big LUSTRE and zoom-in tool Complete Integration (iteration until convergence on several aggregate parameters, e.g. residents, jobs, etc., trip times) Partial integration Focusing on population movements and transportation cost equivalency Post-processing (loose connection)

29 Assumed Unchanged Big LUSTRE Calibration Area Population Initial Building Stocks Transportation Infrastructure Except for the Dulles rail project Initial Income Levels Big LUSTRE Structure Long-term equilibrium framework

30 Resulting framework capabilities Consistent (or largely consistent) welfare measurement Account of population and job movement Changes in travel patterns in response to infrastructure improvement/construction Changes in wages, rents, incomes, etc.

31 Mini-RELU Design Focus on developers decisions New development Redevelopment Focus on relocation of residents and businesses within the localized area Don t explicitly model variation in prices and wages in the zoom-in area

32 Mini-LUSTRE Data Work Define zone structure Consistent with project goals Consistent with data availability Obtain Data RELU data (population, housing, land use, economic fundamentals) Transportation data Calibrate the model

33

34

35 Zone # Description County Tracts 1 Tysons Fairfax , , , Tysons East Fairfax , Reston North Fairfax , , , , 4821, , , , Reston South Fairfax , , , , , Herndon North Fairfax , , , , , Herndon South Fairfax , , , , Sterling/Dulles Town Center Loudoun , , , , 6113, 6114, Ashburn Loudoun , , , , , , , , , Cascades Belmont/Landsdowne 11 Leesburg Loudoun Loudoun Loudoun 6111, , , Dulles Airport Fairfax, Loudoun 9802, Great Falls Fairfax 4801, Northeast Fairfax Fairfax 4803, Dunn Loring Fairfax , Vienna North Fairfax 4608, Vienna South Fairfax , , South of 66 Fairfax , , 4617, Woodburn Fairfax 4401, , City of Fairfax Fairfax C of F North of Oakton Fairfax 4611, 4615, , 4618, Wolf Trap Fairfax 4602, 4603, Fairfax Northwest Fairfax , , East of Franklin Farm Fairfax 4815, 4816, , Fair Oaks/Fair Lakes Fairfax , , , , , , , Loudon/Prince William Fairfax 4910, , , , , , , Chantilly Fairfax , , , , Arcola/Stone Ridge Loudoun , , , , ,

36

37 Table 2a: Average Weighted Travel Time Difference (Build - Baseline): Peak Walk to Transit PKWKWTD DC Core DC Other VA Core VA Arlington Orange Line VA ARL Columbia Pike Alexandria/Springfield Vienna Corr Tysons Dulles Corr Ashburn/Sterling Rest of Loudoun PW County MTG County PG County Outer VA Outer MD

38 Table 2b: Average Weighted Travel Time Difference (Build - Baseline): Peak Drive to Transit PKDRWTD DC Core DC Other VA Core VA Arlington Orange Line VA ARL Columbia Pike Alexandria/Springfield Vienna Corr Tysons Dulles Corr Ashburn/Sterling Rest of Loudoun PW County MTG County PG County Outer VA Outer MD

39 Zone # Description County Tracts 1 Tysons Fairfax , , , Tysons East Fairfax , Reston North Fairfax , , , , 4821, , , , Reston South Fairfax , , , , , Herndon North Fairfax , , , , , Herndon South Fairfax , , , , Sterling/Dulles Town Center Loudoun , , , , 6113, 6114, Ashburn Loudoun , , , , , , , , , Cascades Belmont/Landsdowne 11 Leesburg Loudoun Loudoun Loudoun 6111, , , Dulles Airport Fairfax, Loudoun 9802, Great Falls Fairfax 4801, Northeast Fairfax Fairfax 4803, Dunn Loring Fairfax , Vienna North Fairfax 4608, Vienna South Fairfax , , South of 66 Fairfax , , 4617, Woodburn Fairfax 4401, , City of Fairfax Fairfax C of F North of Oakton Fairfax 4611, 4615, , 4618, Wolf Trap Fairfax 4602, 4603, Fairfax Northwest Fairfax , , East of Franklin Farm Fairfax 4815, 4816, , Fair Oaks/Fair Lakes Fairfax , , , , , , , Loudon/Prince William Fairfax 4910, , , , , , , Chantilly Fairfax , , , , Arcola/Stone Ridge Loudoun , , , , ,

40 Long-Term Growth in Residents Zone # Change in number of Residents

41 Long-term Change in Single Family Housing Zone # Floor Space

42 Long-term Change in Multi Family Housing Zone # Floor Space

43 Long-Term Change in Commercial Building Space Zone # Floor Space

44 Mini-LUSTRE Summary Residential Growth: 10,791 (3.1%) Single Family Housing Growth: 8,300,000 sq. ft. (2.35%) Multi-Family Housing Growth: 876,000 sq. ft. (2.31%) Commercial Building Floor Space Growth: 10,355,000 sq.ft. (1.73%)

45 Residential Movement in "Big" LUSTRE Change Zone #

46 Caveats Model is calibrated on 2000 data 2000 Census No new infrastructure included (e.g. ICC) No natural population growth, economic growth, technological progress, etc. The outcome is static long-term equilibrium Only marginal effects are displayed; policy interactions are ignored

47 Concluding Remarks There is a wide gap between theory and practice of evaluating benefits of transit investments Various categories of benefits are interconnected and should not be estimated separately from disconnected sources Improvements in accuracy of demand estimates is likely to lead to more accurate CBAs in general