REGIONAL ECONOMIC IMPACT OF ACE RAIL SYSTEM EXPANSION INTO THE SAN JOAQUIN VALLEY Presented by: The Great Valley Center 1120 13th Street, Suite C. Modesto, CA 95354 (209)522-5103 www.greatvalley.org October 2014 An Economic Impact Study of the SJRRC’s Potential Extension of the ACE Train into the San Joaquin Valley Prepared for the Great Valley Center by: David Gallo, Ph.D., Chief Economist and Primary Investigator Gus Koehler, Ph.D., VP of Research www.timestructures.com [email protected] Funded by: San Joaquin Regional Rail Commission C O N T E N T S list of tables ................................................................................................................................................. 3 Executive Summary ..................................................................................................................................... 5 Introduction ............................................................................................................................................. 5 Estimated Economic Value and Impacts .................................................................................................. 5 Potential Impacts not Quantified ............................................................................................................ 6 Introduction ................................................................................................................................................. 8 The ACE Commuter Rail System .............................................................................................................. 8 Proposed Upgrades and Expansion ......................................................................................................... 8 Purpose of the Study ............................................................................................................................... 8 Methodology ........................................................................................................................................... 8 Limitations of the Study ........................................................................................................................... 9 Benefits of the Current ACE Commuter Rail System ................................................................................. 10 Methodology and Data Sources ............................................................................................................ 10 Operational Benefits Estimates ............................................................................................................. 11 Upgrades and Expansion of the ACE Commuter Rail System .................................................................... 14 Description ............................................................................................................................................. 14 The Need for ACE System Expansion ..................................................................................................... 15 Trends in County-‐to-‐County Migration .............................................................................................. 15 Growth in Regional Commuting ........................................................................................................ 16 Trends in Peak Traffic Levels .............................................................................................................. 18 Regional Economic Benefits of ACE System Expansion ............................................................................. 20 Construction Impact Estimates .............................................................................................................. 20 Operational Benefit Estimates ............................................................................................................... 22 Benefits of Attracting Additional Residents to Stanislaus and Merced Counties .................................. 24 Benefits to the San Joaquin Valley and its Residents of Providing Access to Broader Labor Markets ...... 26 Growth in Sector Employment .............................................................................................................. 26 Wage Differentials within the Region .................................................................................................... 27 Population Growth and Job Opportunities ............................................................................................ 29 Contrasting Demographics: San Joaquin Valley vs. South Bay .................................................................. 30 Demographics of Current ACE Ridership ............................................................................................... 30 Demographics of Potential Commuters on the Proposed East Branch of the ACE Line ........................ 31 Implications for Obtaining Cap and Trade Funds for Project Finance ................................................... 32 TSI, OCTOBER 2014, REGIONAL ECONOMIC IMPACT OF ACE RAIL EXPANSION 1 Funding Purposes .............................................................................................................................. 32 Likelihood of Acquiring Cap and Trade Funds for ACE Expansion ..................................................... 32 Literature review: Do commuter rail systems create economic value in the communities they serve? ... 33 Literature Reviewed and Method of Analysis ........................................................................................ 33 Literature Findings on the Economic Effect of Commuter Light or Heavy Rail ...................................... 34 Discussion .............................................................................................................................................. 37 Conclusions ................................................................................................................................................ 39 References ................................................................................................................................................. 40 Scholarly Articles ................................................................................................................................... 40 Data Sources .......................................................................................................................................... 42 Appendix A: literature review detail .......................................................................................................... 44 TSI Abstracted Studies ........................................................................................................................... 44 Supplemental Abstracts of Commuter Rail Economic Effect Studies .................................................... 53 TSI, OCTOBER 2014, REGIONAL ECONOMIC IMPACT OF ACE RAIL EXPANSION 2 L IS T O F T A B L E S Table 1: Net Savings on Driving Costs for Commuters Currently Using the ACE Line Table 2: Value of Time Savings for those Currently Using the ACE Line to Commute to W ork Table 3: Value of Greenhouse Gas Reductions from Current ACE Line Operations (Based on Sam pled Trips and Trip Lengths) Table 4: Annual Value per ACE Commuter Rail Trip: Current System Table 5: Net County-‐to-‐County M igration: 2006-‐2010 Table 6: County-‐to-‐County Com m uting for Counties Served by the W estern ACE Line: 2006-‐10 and the Percentage Change from 2000 Table 7: County-‐to-‐County Com m uting on the Proposed Eastern ACE Line: 2006-‐10 and the Percentage Change from 2000 Table 8: County-‐to County Commuting from the Proposed Eastern ACE Line to the W estern Line and the Proposed Link with BART: 2006-‐10 and the Percentage Change from 2000 Table 9: Projected Growth in Average Peak Traffic Volumes: I-‐205, I-‐580, and I-‐238: 2020 and 2035 Table 10: 2012 Traffic Volum es on Other Highways at Regional County Borders Table 11: Capital Expenditures by Year and Industry Sector (M illions of 2014 Dollars) Table 12: Total Impacts of the ACE Capital Spending Program on Regional Output, Income, Employment, and Local Tax Revenues (2014 Dollars) Table 13: Value of the Existing ACE System 2015-‐2025 (2014 Dollars) Table 14: Value of the Upgraded and Expanded ACE System: W eekday Trips 2020-‐2025 (2014 Dollars) Table 15: Difference in the Value of Upgraded and Expanded W eekday Service and Existing Service: 2020 -‐2024 (2014 Dollars) Table 16: Value of W eekend Service and Connections to High Speed Rail: 2025 (2014 Dollars) Table 17: Value of Attracting New Commuters to Stanislaus and M erced Counties: per 100 Commuters by Occupation (2014 Dollars) Table 18: Sector Employment Growth by M SA: 2008-‐2012 Table 19: Forecasted Employment Growth by M SA: 2010-‐2020 TSI, OCTOBER 2014, REGIONAL ECONOMIC IMPACT OF ACE RAIL EXPANSION 3 Table 20: 2013 Average Annual W ages by M SA for Selected Occupations Table 21: Forecasted Employment Growth Relative to Forecasted Population Growth: by M SA 2010-‐2020 Table 22: Demographics for Cities with ACE Stations or Proposed Stations (2008-‐12 data) Table 23: Population Growth Forecasts for Counties in the M SA’s affected by Present or Future ACE Service Table 24: Summary of Economic Effects of Commuter, Light, or Heavy Rail TSI, OCTOBER 2014, REGIONAL ECONOMIC IMPACT OF ACE RAIL EXPANSION 4 E X E C U T IV E S U M M A R Y Introduction The Altamont Corridor Express (ACE) provides passenger service between the cities of Stockton and San Jose, with several stops in between. The system runs four trains daily between Monday and Friday. The trains depart from Stockton in the morning between 4:20 A.M. and 7:05 A.M. and from San Jose in the afternoon between 3:35 P.M. and 6:38 P.M. Annual ridership on the current system is expected to increase to 1.33 million by 2015, and to 1.52 million and 1.69 million in 2020 and 2025, respectively. There are a number of projects in the planning stages to upgrade system reliability and capacity, and to expand services to residents in Stanislaus and Merced counties. The purpose of this study is to estimate the benefits to the region of undertaking the planned investments in ACE system upgrades and expansion. The approach is to estimate the benefits associated with an expanded system, including the economic impact of the needed construction activity and equipment purchases, and to compare the estimated benefits with those provided by the current system. Even with no upgrades or system expansion, the benefits of the current system will increase with additional ridership, but with system expansion, ridership in future years will be significantly higher than it would be with the no-‐build option. Estimated Economic Value and Impacts Time Structures’ calculated the total economic value of the current ACE system and that of the expanded and upgraded system. The difference in economic value (additional commute savings, commuter’s work, and CO2 reductions) between the expanded system and the existing system is estimated to be $144.84 million for the 2020-‐24 period. The ACE system upgrades and service extensions proposed for 2020-‐ 2025 increase that difference to $433.0 million for the five-‐year period beginning in 2025. System expansion results in additional annual savings on commuter costs alone estimated to be $25.94 million in 2020, increasing to $65.92 million in 2025. The economic impacts of the $912.24 million ($228 million, or 25 percent of which will be locally funded) in construction and equipment required for system upgrades and expansion are estimated using the IMPLAN input-‐output model. Construction activities are concentrated in two periods: 2017-‐2019 and 2021-‐2023. Four measures of economic impact are used: gross business revenues, total income to area businesses and their workers, total employment, and state and local tax revenues. We estimate that gross business revenues will be increased by $1.09 billion, while income to local businesses and their employees will be increased by $564.83 million. The planned construction and equipment spending will also generate $37.15 million in state and local tax revenues. A total of 5,716 jobs will be created during the seven-‐year capital expenditure program, with average annual employment at 817 full-‐ and part-‐time jobs. Employment is expected to peak at over 1,400 in 2018 and over 1,500 in 2022. The difference in economic value of the expanded and upgraded system and the existing system is the measure of the economic value of the ACE capital expenditure program. It is the sum of the operational benefits—reduced commute cost, value of work done on the train, and the value of reduced carbon emissions—and the regional income impacts of the construction and equipment expenditures necessary to achieve ACE service goals. The total economic value through the year 2029 is $1.14 billion. Another benefit, quantified but not included in the $1.14 billion total, is the spending impact of new area residents who commute to the Bay Area. Projections of population growth, county-‐to-‐county TSI, OCTOBER 2014, REGIONAL ECONOMIC IMPACT OF ACE RAIL EXPANSION 5 migration, and future employment growth by Metropolitan Statistical Area indicate that future workers in the Bay Area are going to increasingly reside elsewhere. Whether that is in the northern San Joaquin Valley or surrounding counties depends on the cost of commuting from their chosen residence to their place of work. Contra Costa, Solano, and Yolo counties are currently attracting residents working outside those counties. Depending on the occupation and average annual wage, each Bay Area employee attracted to Stanislaus or Merced counties will contribute a particular level of spending to the area, generating revenues for local businesses. For the average of a cross-‐section of occupations, each 100 Bay Area commuters residing in the area (Stanislaus and Merced counties) will generate $4.55 million in gross business revenues, $3.16 million in income to local businesses and their employees, $0.364 million in state and local taxes, and 36 jobs for area residents. Potential Impacts not Quantified Currently, the percentage of vehicles removed from area highways by ACE during traffic peaks is relatively small, but it is not insignificant, and is likely to reduce travel times for those remaining on the highways. Unfortunately, it would take complex modeling—beyond the scope of this report—to calculate the effect on commute times. We can say that if all peak hour commuters on I-‐580 experience a ten minute reduction in their commute time each way, then at the current hourly wage rate and at 2010 peak traffic levels, those twenty minutes are worth over $70,000 per day, or $19 million annually. The lower cost of land and labor in the San Joaquin Valley is likely to attract a growing number of employers, thus reducing regional wage differentials. By expanding the ACE system to Modesto and Merced, the switching of transportation modes by area commuters will be reinforced and provide disproportionately large air quality benefits to the valley. Our literature review indicates that residential and multifamily property values are likely to increase. This academic literature review provides perspective on our formal calculations of the economic value of proposed ACE commuter rail extension. It also addresses some additional issues we were unable to quantify. Where there is overlap, the findings provide strong support for TSI’s economic analysis. The overview of the more detailed literature analysis which is included in Appendix A, encompasses a variety of economic analyses and methodologies, all of which are included in an effort to gain broad understanding of how complex, interacting municipal, social, and other factors can affect economic outcomes. • • • • • • Home property values were positively affected in the great majority of cases. Apartment building value or rents tended to increase the closer the structure was to a station. Commercial Property Values or new Business formation did not show a clear effect, increasing in some studies but either staying the same or decreasing in others. Economic Aggregation and Interregional Benefits including job generation are shown to occur in the most recent studies but are complex processes that do not always yield positive results.. Generation of Tax Revenues was found to be an effect of building commuter rail systems, particularly when housing and positive job impacts occurred. Vehicle Miles Driven decreased but due to population growth these savings could have been swamped by increased numbers of cars being driven. TSI, OCTOBER 2014, REGIONAL ECONOMIC IMPACT OF ACE RAIL EXPANSION 6 • Overall these findings are in agreement with, and provide updates to, a comprehensive 2001 review of transit-‐oriented development (TOD) commissioned by the California Department of Transportation, developed by Robert Cervero, Ferrell and Murphy (2002), from the Institute of Urban and Regional Development, University of California Berkeley. TSI, OCTOBER 2014, REGIONAL ECONOMIC IMPACT OF ACE RAIL EXPANSION 7 IN T R O D U C T IO N The ACE Commuter Rail System The Altamont Corridor Express (ACE) provides passenger service between the cities of Stockton and San Jose, with stops at Lathrop, Tracy, Vasco Road, Livermore, Pleasanton, Centerville/Freemont, Levi’s Stadium/Great America, and Santa Clara. The system runs four trains daily between Monday and Friday. The trains depart from Stockton in the morning between 4:20 A.M. and 7:05 A.M. and from San Jose in the afternoon between 3:35 P.M. and 6:38 P.M. Annual ridership on the current system is expected to increase to 1.33 million by 2015, and to 1.52 million and 1.69 million in 2020 and 2025, respectively. Proposed Upgrades and Expansion There are a number of projects in the planning stages to upgrade system reliability and capacity, and to expand services to residents in areas outside those served by the current system. Projects designed to increase reliability include building new and upgraded sidings, track realignment, and building new rail connections. System expansion is planned in stages, with service to Modesto added before 2020. At the time of the extension of service to Modesto, the system is planning to add two additional daily trains, bringing the total to six on weekdays. Plans include extension to Merced by 2025 and an increase to ten weekday trains daily. Service will also be extended to weekends, with the operation of six trains. Purpose of the Study The purpose of this study is to estimate the benefits to the region of undertaking the planned investments in ACE system upgrades and expansion. The approach is to estimate the benefits associated with an expanded system, including the economic impact of the needed construction activity, and to compare the estimated benefits with those provided by the current system. Even with no upgrades or system expansion, the benefits of the current system will increase with additional ridership, but with system expansion, ridership in future years will be significantly higher than it would be with the no-‐build option. Methodology Where possible, the benefits are quantified and expressed in dollar terms. For construction impacts, direct construction spending is entered into the IMPLAN input-‐output model for the five-‐counties included in the expanded ACE service area. This approach allows us to estimate the total impact of construction activity on the regional economy in terms of gross business revenues, income to businesses and workers, state and local tax revenues, and employment. The IMPLAN model is also employed to estimate the impact on the San Joaquin Valley economy of increased access by new valley residents to higher paying jobs in the Bay Area. In this case the IMPLAN model includes just Stanislaus, and Merced counties. This report section involves some conditional analysis that examines the total economic impact of a hypothetical number of new valley residents choosing to move to the area and accessing jobs in particular occupations in the Bay Area. The report also includes a dollar estimate for the value of the ACE system to commuters and the regional environment (in terms of greenhouse gas emissions). The value to commuters is based on savings on the cost of driving vs. the cost of commuting on the ACE system and the value of work done while riding the train. Although the value of reduced emissions of greenhouse gases does not accrue TSI, OCTOBER 2014, REGIONAL ECONOMIC IMPACT OF ACE RAIL EXPANSION 8 directly to commuters, the economic value of the estimated reduction is included as part of the value of a train trip. Limitations of the Study Incomplete accounting of costs. Operation and maintenance costs are not included. ACE rail ticket costs are accounted for in the commuter cost savings calculations as they are subtracted from the cost of driving to equivalent destinations. Construction costs of planned system upgrades and expansion are included, but the local income impact is a benefit that exceeds the local capital contribution. Other potential costs imposed on residents are not included. Nor is there a complete accounting of benefits. There are many benefits described below that we were unable to quantify. Our approach could be described as picking the low hanging fruit, while pointing out what may be the larger ones higher up. The likely positive impact on area property values, the avoided cost of adding new lanes to existing freeways, the amenity value of being able to travel with less stress, the value and regional productivity impacts of local access to broader labor markets, and other benefits are not quantified in this study. There are additional values that, with the appropriate data, could be quantified and are a part of the economic value of existing and expanded commuter rail service. These include the value of commuter rail to residents who continue to drive. Expanded use of rail reduces highway traffic, particularly during traffic peaks, and reduces driving time and accident risk for those choosing to remain in their cars. Those benefits may be significant, but cannot be estimated without knowing the number of drivers removed from each congested highway at each time interval, and how that affects drive times along all highway segments. Another benefit that was not quantified, and may be significant, is the impact of new rail stations and additional traffic at existing stations on the value of land within the affected communities. A discussion of this factor is included in the literature review section. That report section also includes discussion of other issues including whether acquiring rail service is development-‐inducing, and whether that development also attracts new businesses and jobs to the area. We also address the issue of project funding, specifically the question of whether Cap-‐and-‐Trade funds will be available for construction or operation phases of the project. There are a number of programs providing direct funding for the dual purposes of reducing carbon emissions and promoting sustainable development in disadvantaged communities. In order to address this question we examine area demographics and the degree to which they qualify the project for receipt of funding from available program allocations The last section of the report is a review of the scholarly literature on the impacts of commuter and light rail in the regions served by the systems. The review addresses a number of issues, but focuses on those which we were unable to reliably quantify. TSI, OCTOBER 2014, REGIONAL ECONOMIC IMPACT OF ACE RAIL EXPANSION 9 B E N E F IT S O F T H E C U R R E N T A C E C O M M U T E R R A IL S Y S T E M Methodology and Data Sources Benefits of the current ACE system are estimated for a single train trip and for the system as a whole (eight one-‐way train trips). The benefits are calculated on an annual basis and include: Net Savings on driving costs, calculated as the cost of driving minus the cost of commuting on the ACE Line. • Time saved over driving the same distance for passengers on the existing ACE commuter rail line. • The value of work done during commuting—work that would be impossible to do if driving from the same residence area to work destination. • The value of CO2 reductions due to shifting from automobile travel to commuter rail. Net savings on driving costs are estimated using the driving times at the midpoint of the departure and arrival times for each of the train routes sampled. Driving times are derived from the 511 Travel Website, for city-‐to-‐city freeway driving times for cities containing ACE stations.1 A total of twelve train routes are included in the sample, constituting just over 19 percent of total annual train trips. Rail commuter times are taken directly from the ACE schedule.2 The cost per mile of driving is the 2014 cost per mile from AAA, adjusted for the average number of passengers per vehicle.3 • Time saved for rail commuters was calculated from the driving time minus the rail commuting times. The calculated time differential was minimal, but due to data limitations, the estimate is unreliable. The approach used underestimates the actual time savings for both modes of travel. For drivers it excludes the driving time from residence to freeway entrance, freeway exit to destination, and the time and cost to park. For rail commuters the elapsed times from residence to station, waiting for a train, and from arrival to ultimate destination are also excluded. Possible delays due to incidents are also excluded from the calculated time savings. Responses on the ACE ridership surveys indicate that 36.9 percent of riders work while riding the train. Others engage in various activities including communicating through email or cell phone, reading, etc. While no attempt is made to determine the value of the essentially recreational or social activities, the methodology places a value on the time spent on work. As is typical of studies of this type, an hour of work is valued at the average wage rate. Carbon Dioxide reductions are calculated from the shift in transportation modes: from driving to commuter rail. Emissions per mile and the impacts of slower driving speeds are combined with data on reduced miles of driving to calculate the annual reduction in CO2 emissions resulting from ACE ridership. 1 http://traffic.511.org/ http://www.acerail.com/ 3 https://www.google.com/search?sourceid=navclient&aq=&oq=AAA+cost+per+mile+&ie=UTF-‐ 8&rlz=1T4WQIA_enUS566US567&q=aaa+cost+per+mile+2014&gs_l=hp..0.0l5.0.0.0.9427...........0.ng6Xrwguj6c 2 TSI, OCTOBER 2014, REGIONAL ECONOMIC IMPACT OF ACE RAIL EXPANSION 10 Operational Benefits Estimates Table 1 contains the estimated annual savings in driving costs. Automobile trips are defined as the one-‐way mileage between the sampled cities. Miles per average trip is the average for the sampled city-‐to-‐city trips between locations with ACE stations, adjusted downward for the average number of passengers per vehicle (1.1567) for Alameda, San Joaquin, and Santa Clara counties.4 Cost per mile is the 2014 AAA estimate, while annual trips are from the total of ACE westbound and eastbound rail trips. Current Ace riders work while riding the train and that work is valued at $12.5 million annually. Current ACE riders save $11.8 million each year on commuting costs The row for commuter rail includes the weighted average ticket cost per one-‐way trip and the number of one-‐way trips. The weighted average ticket cost is calculated from the ratio of one-‐way, round-‐trip and 20-‐ticket purchases made by ACE riders and summarized in the ACE ridership surveys, but excludes the impact of employer subsidies. The third entry is the daily cost: the product of the cost per trip times the number of trips. The annual cost is the cost per trip times the number of rail trips per year. The annual ticket cost for ACE riders totals $6.9 million, while if they traveled the same distance by auto, the cost would have been $18.7 million. The annual savings on travel cost is the difference, or $11.85 million. Table 1: Net Savings on Driving Costs for Commuters Currently Using the ACE Line Auto Use Miles per Average Cost per Cost per Trip Trips per Year Annual Cost Trip* Mile** Driving Miles 26.06 $0.59 $15.43 1,213,680 $18,726,411 Commuter Rail Ticket Price per Trips per Daily Cost Trips per Year Annual Cost Trip*** Day $5.67 4,668 $26,457 1,213,680 $6,878,833 Annual Net Savings for Commuters $11,847,578 * Calculated as average freeway miles weighted by the city-‐to-‐city proportion of commuter rail trips **http://newsroom.aaa.com/tag/driving-‐cost-‐per-‐mile/ ***Calculated according to the proportion of city-‐to-‐city trips and the proportion of ticket types purchased by riders All trip data including number of passengers, on-‐and off-‐stations, and types of tickets purchased are from the ACE rider surveys The value of time savings for commuters on the ACE Line is the sum of the hours saved on commuting and the number of hours worked during train travel. While the former is relatively small—a total of just over two hours per year for all riders—the amount of work done while riding the train is significant. The 4 http://www.sjcog.org/DocumentCenter/View/44 TSI, OCTOBER 2014, REGIONAL ECONOMIC IMPACT OF ACE RAIL EXPANSION 11 rider survey indicated that 36.9 percent of riders worked while on the train. Valuing that work time at the average hourly wage for workers in the San Jose-‐Sunnyvale-‐Santa Clara MSA—the destination of the majority of commuters—gives a total value for the time available, and used for work, at $12.53 million annually. Table 2 contains the results of these calculations. The other 62.1 percent of the riders are engaged in other pursuits including communicating with friends and family via phone or email, listening to music, reading, sleeping, or otherwise occupying their time, the majority of which can be classified as recreational or social activities. The approach used here places no value on the fact that rail travel allows riders the ability to spend time in these ways. Studies of the value of leisure time ordinarily attribute a value to an hour of leisure equal to some proportion of the hourly wage rate, generally around one-‐third. However, the time riding on a train is not equivalent to unconstrained leisure time, and can’t be compared to the value of leisure time spent for travel for pleasure, hiking, and other leisure pursuits. Of course, that does not mean that this time has no value— just that it cannot be estimated using currently available techniques. Table 2: Value of Time Savings for those Currently Using the ACE Line to Commute to W ork Travel Time Saved per Day (Hours)* On-‐Train Work Time per Day** Total Additional Hours for Work per Day Value per Hour*** Value per Day Annual Value 1.94 1,396.81 1,398.75 $34.45 $48,187 $12,528,574 * Savings on travel time is calculated from the weighted average of train travel time minus the freeway travel time between the same cities. It does not include travel time to and from freeway exists, nor does it include travel time to and from train stations. **36.9 percent of surveyed riders stated that they primarily work while riding the train to and from work. Generally the value of leisure is calculated as one-‐third of the wage rate, but in this case leisure activities are limited on the train, and no value is assumed for these hours. ***Mean hourly wage rate, all occupations, San Jose-‐Sunnyvale-‐Santa Clara MSA, the workplace destination for most commuters. http://www.bls.gov/oes/current/oes_ca.htm Another benefit not quantified in this study is the spillover effect from transportation mode switching. When commuters choose to travel by train, the resulting reduction in peak hourly traffic reduces commute times for those choosing to continue to use private vehicles. Currently, the percentage of vehicles removed from area highways by ACE during traffic peaks is relatively small, but it is not insignificant, and is likely to reduce travel times for those remaining on the highways. Unfortunately, it would take complex modeling—beyond the scope of this report—to calculate the effect on commute times. But, even if commute times are reduced by a small amount, the dollar benefit would be very large. For example, if all peak hour commuters on I-‐580 experience a ten minute reduction in their commute time each way, then at the current hourly wage rate and at 2010 peak traffic levels, those twenty minutes are worth over $70,000 per day, or $19 million annually. TSI, OCTOBER 2014, REGIONAL ECONOMIC IMPACT OF ACE RAIL EXPANSION 12 The value of carbon dioxide emissions reductions is calculated from vehicle miles avoided and the difference in emissions by mode of travel. The average commuter trip is 30.15 miles and the availability of the ACE system avoids 4,668 trips per day (2014). Daily trips are calculated by multiplying the miles per trip times the number of daily trips. Annual miles are the number of vehicle miles avoided through mode switching to the Current operation ACE system and are the daily miles times the number of days the of the ACE system system operates, adjusted for the average number of passengers per vehicle. reduces annual carbon dioxide Total carbon dioxide emissions per mile are based on avoided vehicle miles, relative emissions per passenger mile for automobile emissions by and commuter rail travel, and the impact on automobile emissions 10,322 metric tons from travel at slower speeds on congested highways. The annual reduction in carbon dioxide emissions totals 10,322 metric tons. At a value of $20 per metric ton, the annual value of the avoided carbon dioxide emissions is $206,434. The results of those calculations are contained in Table 3. Table 3: Value of Greenhouse Gas Reductions from Current ACE Line Operations (Based on Sam pled Trips and Trip Lengths) Total Driving Miles Saved per trip per Day Total Trips per Day Total Miles per Day Total Miles per Year Average Passengers per Auto* Vehicle miles saved Automobile CO2 Emissions (Average Driving Conditions) in Grams per Mile** 30.15 4,668 140,727 36,589,076 1.1566943 31,632,452 371 Adjustment Factor for Driving under Congested Road Conditions*** 1.1369863 Total Emissions Avoided with Current Operation of ACE Rail System (Metric Tons) 10,322 Annual Value @ $20 per Metric Ton**** $206,434 *Average for Alameda, San Joaquin, and Santa Clara Counties http://www.sjcog.org/DocumentCenter/View/44 **www.buses.org/files/ComparativeEnergy.pdf ***http://www.uctc.net/access/35/access35_Traffic_Congestion_and_Grenhouse_Gases.shtml ****Over the last two years CO2 emissions offsets have commanded prices ranging from $11.60 to $21.30 per metric ton. http://calcarbondash.org/?gclid=CNHIgN_y4cACFdGCfgods74ASg The total value of current ACE commuter rail service is the sum of the four categories of benefits: the savings in commuter costs, the value of savings on travel time and on-‐train work time, and the value of carbon dioxide emission reductions. The total value is $24.58 million for the eight one-‐way ACE routes. The value per one-‐way route is just over three million dollars (Table 4). TSI, OCTOBER 2014, REGIONAL ECONOMIC IMPACT OF ACE RAIL EXPANSION 13 Table 4: Annual Value per ACE Commuter Rail Trip: Current System Category of Savings or Value Total Annual Net Savings in Commuting Costs Annual Value of Additional Work Time (On-‐Train Work Hours plus Time Savings for Commuters) Annual Value of CO2 Reductions @ $20 per Metric Ton Total Annual Value of Current ACE Commuter Rail Service Total Annual Value of Current ACE Commuter Rail Service per One-‐Way Train Trip Dollar Value $11,847,578 $12,528,574 $206,434 $24,582,587 $3,072,823 Over time we can expect these values to rise. Unless matched by fare increases, commuter cost savings will increase with increases in ridership (up to train capacity), the cost of fuel and other elements of driving cost. The value of on-‐train work will rise with increased ridership and increases in average hourly wage rates. The amount of travel time saved with mode switching will increase beyond current levels as automobile travel time increases with rising peak traffic volumes. Lengthier commute times will also lead to further increases in carbon dioxide emissions per mile as highway speeds are further reduced during peak commute hours. Each one-‐way ACE train trip currently results in annual benefits of more than three million dollars UPGRADES AND EXPANSION OF THE ACE COMMUTER RAIL SYSTEM Description The ACE line is contemplating major upgrades for, and expansion of its existing system. Described in ACE Forward documents, the upgrades and service extensions include track improvements on the existing line to increase reliability and extending service to Modesto by 2018, and to Merced by 2022. Plans call for the new eastern branch of the system to be linked to the existing line at Lathrop, and it is possible that the western portion of the line will be connected to BART at Livermore. In addition, plans call for a connection between California High Speed Rail trains and the ACE system at Merced. By 2018 it is expected that the system will be running six trains (up from the four currently) on weekdays. With service extended to Merced in 2022, a total of ten trains will be operating during the week, with six also operating on weekends. The planned upgrades and extensions will require a considerable amount of investment in structures, rail line, rolling stock, and other equipment. The newly opened eastern line involves planned new stations at Ripon, Modesto, Turlock, and Merced. Livingston or Atwater is under consideration for another station. TSI, OCTOBER 2014, REGIONAL ECONOMIC IMPACT OF ACE RAIL EXPANSION 14 The Need for ACE System Expansion T re nds in C o unty -‐ to -‐ C o unty M i g r a ti o n Examination of migration data among the counties in the region reveals two important trends. First, net migration is generally from west to east. Contra Costa, San Joaquin, Merced, and Stanislaus counties have all gained population due to west-‐to-‐east migration. San Mateo County is the only county to the west that has seen positive net migration within the region, but that net gain is exclusively due to in-‐ migration from San Francisco. Second, although net migration is from west to east, there is still significant regional movement into Alameda, San Francisco, and San Mateo counties. That is probably due to those employed in higher paying occupations moving nearer to their jobs. Those are the individuals who can afford the high cost of housing, thus eliminating the long commutes from Contra Costa and other counties to the east and north. This migration pattern, in combination with forecasts of future job growth that favor the western counties, point to an acceleration of east-‐to-‐west commuting. The increased volume of commuters will inevitably lead to increased traffic congestion and increasingly lengthy commute times. Thus, expansion of the ACE line into the San Joaquin Valley and linking the current system with BART can be seen as one means to mitigate the negative externalities arising from market forces in the region. Data on relative housing prices for cities in the region are presented in other sections of this report (Table 22). The important issue to be addressed here is that the difference in housing prices and rents between cities to the west and those in the San Joaquin Valley is likely a major reason for the growth in commuting. Another reason, addressed in detail elsewhere in this report, is the large wage differential between Bay Area MSA’s and those in the valley. Over time it can be expected that those differences will decrease somewhat as rising demand for housing in the valley drives up local housing costs. Another possible change is that the lower cost of land and labor in the San Joaquin Valley will attract a growing number of employers, thus reducing regional wage differentials. However, while those changes may eventually slow the growth in east-‐to-‐west commuting, they will not have enough of an effect that the need for additional transportation infrastructure is negated. County-‐to-‐county net migration data for all counties in the region is included in Table 5. The initial county of residence is indicated by the county titles in the top row, while the destination county is the county in the left-‐hand column. Total migration within the region is shown in the last row and each entry is the sum of the column entries. A negative sum indicates net out migration to other counties in the region. TSI, OCTOBER 2014, REGIONAL ECONOMIC IMPACT OF ACE RAIL EXPANSION 15 Table 5: Net County-‐to-‐County M igration: 2006-‐2010 To: From: Alameda Contra Costa Merced Alameda Merced 0 Contra Costa 5,156 297 San Francisco -‐3,606 San Joaquin 2,068 -‐5,156 0 112 -‐2,584 21 -‐297 -‐112 0 -‐87 San Francisco San Joaquin San Mateo 3,606 2,584 87 -‐2,068 -‐21 1,003 San Santa Mateo Clara -‐1,003 -‐1,855 689 -‐547 180 36 -‐80 -‐1,154 393 0 335 4,866 -‐1,100 -‐82 -‐36 -‐335 0 1403 80 -‐4,866 213 Santa Clara Stanislaus 1,855 547 1,154 1,100 15 -‐689 -‐180 -‐393 82 Net migration -‐1,746 9,377 1,301 -‐10,296 -‐1,403 Stanislaus -‐213 15 -‐141 0 -‐1,096 157 1,096 0 1,004 141 -‐157 -‐1,004 0 2,829 3,106 -‐6,741 2,200 http://www.census.gov/hhes/migration/data/acs/county-‐to-‐county.html G ro wth in R e gio nal C o m m uting County-‐to-‐county commute data is available for the years 2000 (U.S. Census and California EDD) and 2006-‐10 from the American Communities Survey. In spite of the impact of the recession on the area economy, commuting from San Joaquin County to Alameda and Santa Clara increased significantly, with increases of 30.91% and 12.89 percent, respectively. Commuting in the opposite direction also increased, but from relatively low levels, while commuting from Alameda to Santa Clara decreased over the same years. Table 6: County-‐to County Commuting for Counties Served by the W estern ACE Line: 2006-‐10 and the Percentage Change from 2000 To: Alameda (2006-‐10) Alameda (%) San Joaquin (2006-‐10) San Santa Clara Joaquin (2006-‐10) (%) From: Alameda na na 1,856 31.17% San Joaquin 26,121 30.91% na na Santa Clara 38,339 3.58% 497 106.22% http://www.labormarketinfo.edd.ca.gov/Links_to_LMI_by_County_Area.html http://www.census.gov/hhes/commuting/ 64,696 7,954 na Santa Clara (%) -‐7.14% 12.89% na There has been even more marked growth in commuting between the counties in the San Joaquin Valley. Between 2000 and 2006-‐10 there was a 51.2 percent increase in the number of commuters traveling from San Joaquin County to Stanislaus County. For the same years there was a 22.49 percent TSI, OCTOBER 2014, REGIONAL ECONOMIC IMPACT OF ACE RAIL EXPANSION 16 increase in the number commuting out of San Joaquin County to Stanislaus County, and a 13.78 percent increase south to Merced County. The number of commuters for 2006-‐10 and the percentage growth from 2000 in county-‐to-‐county commuting within the San Joaquin Valley are contained in Table 7. Table 7: County-‐to-‐County Com m uting on the Proposed Eastern ACE Line: 2006-‐10 and the Percentage Change from 2000 To: Merced (2006-‐ 10) Merced (%) San Joaquin (2006-‐10) San Joaquin (%) From: Merced na na 1,610 61.32% San Joaquin 424 160.12% na na Stanislaus 5,646 13.78% 17,140 22.49% http://www.labormarketinfo.edd.ca.gov/Links_to_LMI_by_County_Area.html http://www.census.gov/hhes/commuting/ Stanislaus (2006-‐10) Stanislaus (%) 10,053 10,040 na 13.89% 51.20% na With the proposed link to the ACE system at Lathrop and potentially to BART in the city of Livermore, commuting from San Joaquin Valley communities to various destinations in the Bay Area becomes increasingly attractive. There has already been significant growth in commuting from San Joaquin County to Alameda County (30.91 percent); to Santa Clara County (12.89 percent), and to San Francisco and San Mateo Counties (71.31 percent). Commuting from Merced County to the Bay Area has also seen substantial growth, although from a smaller base level in 2000. Commuting from Merced County to Alameda County increased by 28.84 percent, while increases of 20.85 percent and 103.03 percent in out-‐commuting occurred into Santa Clara, and San Francisco and San Mateo counties, respectively. Table 8: County-‐to County Commuting from the Proposed Eastern ACE Line to the W estern Line and the Proposed Link with BART: 2006-‐10 and the Percentage Change from 2000 To: Alameda (2006-‐10) Alameda (%) Santa Santa Clara San Francisco Clara (%) and San (2006-‐10) Mateo (2006-‐ 10) From: Merced 755 28.84% 4,168 20.85% San 26,121 30.91% 7,954 12.89% Joaquin Stanislaus 8,198 19.85% 3,983 4.21% http://www.labormarketinfo.edd.ca.gov/Links_to_LMI_by_County_Area.html http://www.census.gov/hhes/commuting/ TSI, OCTOBER 2014, REGIONAL ECONOMIC IMPACT OF ACE RAIL EXPANSION San Francisco and San Mateo (%) 469 4,502 103.03% 71.31% 2,021 22.48% 17 With employment growth accelerating after 2010 there has probably been considerable growth in county-‐to-‐county commuting over the last three years. The divergence between Bay Area population growth and projected job growth will only contribute to future increases in regional commute traffic. T re nds in Pe ak T raffic Le ve ls A 2011 study prepared for SJCOG includes projections of Without expansion traffic volumes on Highways I-‐205, I-‐580 (various segments) and I-‐238. These projections are for traffic levels that can be of the ACE system, expected with business as usual, including the no-‐build traffic on I-‐280 and option for the ACE line. Morning westbound traffic on some I-‐205 is expected to portions of I-‐580 is projected to increase by 25 to 30 percent increase by 68% to between 2010 and 2020, and as much as 75 percent by 2035. For other segments of I-‐580 2010-‐2035 traffic increases range 75% by 2035 from 58.3 percent to 65.8 percent. Similar percentage increases in peak traffic can be expected for I-‐ 205. These projections, including three of the six segments included in the SJCOG study, are presented in Table 9. Table 9: Projected Growth in Average Peak Traffic Volumes: I-‐205, I-‐580, and I-‐238: 2020 and 2035 Highway I-‐205 Segment na 2010 AM Westbound 4,255 PM Eastbound 4,453 2020 AM Westbound 5,732 PM Eastbound 5,589 Percentage AM Westbound 34.71% Change PM Eastbound 25.51% 2010-‐20 2035 AM Westbound 7,170 PM Eastbound 7,002 Percentage AM Westbound 68.51% Change PM Eastbound 57.24% 2010-‐35 http://www.sjcog.org/DocumentCenter/View/44 I-‐580 A 6,883 6,372 8,666 8,045 25.90% 26.26% I-‐580 D 6,763 4,898 8,841 6,321 30.73% 29.05% I-‐580 G 5,715 7,194 7,307 8,508 27.86% 18.27% I-‐238 na 9,546 5,621 10,156 6,296 6.39% 12.01% 12,035 10,812 74.85% 69.68% 10,706 7,164 58.30% 46.26% 9,479 10,426 65.86% 44.93% 11,387 7,672 19.29% 36.49% TSI, OCTOBER 2014, REGIONAL ECONOMIC IMPACT OF ACE RAIL EXPANSION 18 Table 10 contains Caltrans 2012 data for peak hourly traffic levels and average daily traffic (AADT) on other highways connecting counties in the region. The highest peak hourly traffic volumes for that year were recorded on Highway 880 at the Alameda/Santa Clara county line (15,600) and on Highway 99 at the San Joaquin/Stanislaus county line (9,600) Table 10: 2012 Traffic Volumes on Other Highways at Regional County Borders Route Description 5 MERCED/STANISLAUS COUNTY LINE 5 MERCED/STANISLAUS COUNTY LINE 5 STANISLAUS/SAN JOAQUIN COUNTY LINE 5 STANISLAUS/SAN JOAQUIN COUNTY LINE 99 MERCED/STANISLAUS COUNTY LINE 99 MERCED/STANISLAUS COUNTY LINE 99 STANISLAUS/SAN JOAQUIN COUNTY LINE 99 STANISLAUS/SAN JOAQUIN COUNTY LINE 120 SAN JOAQUIN/STANISLAUS COUNTY LINE 120 SAN JOAQUIN/STANISLAUS COUNTY LINE 165 MERCED/STANISLAUS COUNTY LINE 165 MERCED/STANISLAUS COUNTY LINE 880 SANTA CLARA/ALAMEDA COUNTY LINE 880 SANTA CLARA/ALAMEDA COUNTY LINE http://traffic-‐counts.dot.ca.gov/ Back Peak Hour Back Peak Month 4,050 39,000 4,750 41,500 5,300 9,600 118,000 1,350 14,000 1,950 27,500 15,600 202,000 197,000 10,700 27,500 15,600 109,000 14,000 1,950 14,900 61,000 118,000 1,350 10,700 37,500 64,000 9,600 109,000 37,000 41,500 5,300 64,000 Ahead AADT 39,000 4,750 37,500 67,000 Ahead Peak AADT 3,700 Ahead Peak Hour 37,000 Back AADT 14,900 202,000 197,000 TSI, OCTOBER 2014, REGIONAL ECONOMIC IMPACT OF ACE RAIL EXPANSION 19 R E G IO N A L E C O N O M IC B E N E F I T S O F A C E S Y S T E M E X P A N S IO N Construction Impact Estimates Construction costs (2014 dollars) for extending the ACE system to Modesto and to upgrade the existing system are expected to total $353 million. Construction spending for this phase of the project is expected to take place during the years 2017 through 2019. The addition of two trains to the system will also require the purchase of additional rolling stock, at a cost of $57 million in 2018 and $60.5 million in 2020 (Option 1 cost assumptions). The extension to Merced and additional upgrades to the 2020 system will require another $381 million in capital expenditures. Plans call for these expenditures to take place over three years, from 2021 through 2023. The addition of two more trains within the same time frame will require the purchase of another $60.5 million in rolling stock in 2022 (Option 1 cost assumptions). All capital spending impacts on the five-‐county regional economy are estimated using the IMPLAN input-‐ output model. The IMPLAN model estimates the total economic impact of a given level of direct spending in a particular industry sector. The model then estimates the total impact—the sum of direct, indirect, and induced economic activity. Indirect spending is derived from the industry-‐to-‐industry matrix and the indirect impact is the result of input (materials, intermediate goods, etc.) purchases from other businesses located within the region. Induced economic activity is the result of the spending of the additional income earned by workers and businesses from direct and indirect spending. It is expected that the local share of the ACE capital expenditure program will be 25 percent, or $228 million, with the remainder derived from state and federal sources. Therefore, it is reasonable to include only 75 percent of the estimated impact-‐-‐-‐ the portion not funded from within the region. The reasoning is that if local funds are not spent on this project, then they could be spent on another project within the region. Assuming a similar impact per dollar for the spending alternative, then the local funds spent on ACE capital projects have no impact on the regional economy. Pro posed ACE constructio n will generate an ad ditional $564.83 million in income to businesses and their emp loyees with in the region We present four measures of the estimated economic impact of ACE system capital spending program: output (gross business revenues for regional businesses), total value added (income of regional businesses and their employees), employment (full-‐ and part-‐time), and local tax revenues. Each of these estimates is generated by the IMPLAN model. Table 11 includes estimated direct expenditures (in millions of 2014 dollars) for all construction expenditures and rail equipment purchases that are part of the ACE capital program, allocated to the year in which they will be incurred. Table 12 entries are 75 percent of the estimated impacts on output, income, employment, and state and local tax revenues, also by year. For the years of construction and equipment purchases, the ACE capital program will increase regional gross business revenues by $1.09 billion. However, gross business revenues are not an accurate measure of the local economic impact since they double count input purchases from other area businesses. The best measure of local benefits is the income earned by TSI, OCTOBER 2014, REGIONAL ECONOMIC IMPACT OF ACE RAIL EXPANSION 20 businesses and their employees, or total income. The $564.83 million increase in income includes additional wages, profits, rental income, property income, and indirect business taxes. Table 11: Capital Expenditures by Year and Industry Sector (M illions of 2014 Dollars) Year 2017 2018 2019 2020 2021 2022 2023 Totals Rail & Grade Crossing Construction Stations and Maintenance Facility Construction Signal System Construction Rail Cars and Engines (Option 1) $62.31 $124.61 $62.31 $0.00 $74.20 $148.40 $74.20 $546.02 $8.75 $17.50 $8.75 $0.00 $2.50 $5.00 $2.50 $45.00 $17.26 $34.51 $17.26 $0.00 $18.55 $37.10 $18.55 $143.22 $0.00 $57.00 $0.00 $60.50 $0.00 $60.50 $0.00 $178.00 Another benefit measure of the ACE capital program is total employment. Total employment for the 2017-‐2023 period of the ACE capital program is 5,716 full-‐ and part-‐time jobs. However, this figure requires some interpretation. It is not a measure of continuous employment; that is, it is not 5,716 workers employed full-‐ or part-‐time for the full seven years of the capital expenditure program. It is the total number of individuals who will be employed at some point in the construction process, including those who are employed in industries supplying inputs to the construction sector, and those employed due to expanded retail purchases by those whose incomes have increased as a result of the additional construction activity. The best way to interpret this estimate is that those seven years of construction activity at the projected levels will generate an additional 5,716 person-‐years of work within the region. Table 12: Total Impacts of the ACE Capital Spending Program on Regional Output, Income, Employment, and Local Tax Revenues (2014 Dollars) Year 2017 2018 2019 2020 2021 2022 2023 Totals Output: Gross Business Revenues $107,863,626 $277,990,542 $107,863,626 $66,086,474 $116,600,764 $299,288,001 $116,600,764 $1,092,293,797 Income: Wages, Profit, Rent, Interest, Property Income, and Indirect Business Taxes $57,676,317 $141,769,801 $59,976,708 $23,155,989 $64,774,602 $152,705,193 $64,774,602 $564,833,211 Employment: in Person-‐Years of Employment State & Local Taxes 621 1,418 621 187 671 1,528 671 5,716 $3,812,547 $9,369,636 $3,812,547 $1,851,663 $4,112,577 $10,076,816 $4,112,577 $37,148,363 TSI, OCTOBER 2014, REGIONAL ECONOMIC IMPACT OF ACE RAIL EXPANSION 21 ACE system upgrad es an d service extension s prop osed for 2020 are valued at $144.84 million Operational Benefit Estimates In this section we compare the value of the upgraded and expanded ACE system with that of the existing system. The value is calculated as the sum of savings on commuter costs, the value of work done while riding the train, and the value of carbon dioxide emissions reductions. The increase in value per commuter rail trip over time is a function of increased travel distance as the system is expanded into the San Joaquin Valley, rising real wages (two percent annually), and an increase in the value of a metric ton of carbon from $20 in 2015, to $25 in 2020, and to $30 in 2025. In each case, the estimated value per trip is multiplied by the estimated number of annual trips (ACE projections 2014) to arrive at the total value of the specified rail system. Miles per trip are from Table 1, and for the upgraded and expanded service, are increased to 2020 and 2025 by the same percentages used by ACE in its projections. Tables 13 and 14 contain the estimated values for weekday service on the existing, and upgraded and expanded systems, respectively. Table 13: Value of the Existing ACE System 2015-‐2025 (2014 Dollars) Year Commute Cost Value of Work Savings per done per Rider* Rider** Value of CO2 Reductions per Trip*** Total Value per Trip Annual Trips Annual Value 2015 $9.76 $10.32 $0.17 $20.25 1,327,900 $ 26,896,065 2020 $9.76 $11.40 $0.21 $21.37 1,515,500 $ 32,388,530 2025 $9.76 $12.58 $0.26 $22.60 1,648,000 $ 37,245,239 *Assumes that commuter rail ticket prices increase at the same rate as driving costs **Assumes the average inflation-‐adjusted wage rate increases by two percent annually ***Assumes an increase in CO2 value per metric ton to $25 in 2020 and $30 in 2025 Table 14: Value of the Upgraded and Expanded ACE System : W eekday Trips 2020-‐2025 (2014 Dollars) Year Commute Cost Savings per Rider* Value of Work done per Rider** Value of CO2 Reductions per Trip*** Total Value per Trip Annual Trips Annual Value 2020 $11.18 $13.05 $0.24 $24.48 2,321,500 $56,823,220 2025 $13.13 $16.93 $0.34 $30.41 2,528,550 $76,892,960 *Assumes that commuter rail ticket prices increase at the same rate as driving costs **Assumes the average inflation-‐adjusted wage rate increases by two percent annually ***Assumes an increase in CO2 value per metric ton to $25 in 2020 and $30 in 2025 Table 15 contains the estimated difference in the value of the upgraded and expanded ACE, and the existing system for the five-‐year period, 2020 through 2024. This is the difference in the value of weekday service only, since weekend service and connections to high speed rail and BART are not TSI, OCTOBER 2014, REGIONAL ECONOMIC IMPACT OF ACE RAIL EXPANSION 22 expected to affect ridership much before 2025. The difference grows over those years since growth in the number of riders is expected to be higher on the upgraded and expanded system. The total incremental value added by the system upgrades and extension to Modesto is $144.84 million for the five-‐year period. Table 15: Difference in the Value of Upgraded and Expanded W eekday Service and Existing Service: 2020 -‐2024 (2014 Dollars) Year Value: Existing System Value: Upgraded and Expanded System Difference 2020 2021 2022 2023 2024 $32,388,530 $32,752,683 $33,120,931 $33,493,320 $33,869,895 $165,625,358 $56,823,220 $59,344,082 $61,976,778 $64,726,268 $67,597,735 $310,468,083 $24,434,690 $26,591,399 $28,855,846 $31,232,949 $33,727,840 $144,842,725 5-‐year totals By 2025 ACE is expected to offer expanded service. In addition to increasing weekday service to ten daily trains (that impact is included in the Table 14 total), ACE plans to offer weekend service, and potentially could provide connections to BART at Livermore, and to high speed rail at Merced. The weekend service will be operated with six trains. Each of these services add additional riders, and therefore, have value not captured in Table 14. The values per trip on the expanded service differ ACE system upgrades depending on the assumed purpose. For weekend service, and service extensions it assumed that the purpose is strictly recreational and no value is assigned to work done on the train. The same proposed for2020-‐ 2025 assumptions apply to riders connecting to high speed rail. are valued at $433 For those using the BART connection on weekdays, it is million for the five-‐year assumed that they are as likely to work on the train as are weekday riders on the existing system (36.9 percent). period beginning in Riders using that connection are assigned to weekday and 2025. weekend travel according to the relative number of trains operating during those periods. With six trains on weekends and ten on weekends, that implies that 62.5 percent of the passengers ride on weekdays and 37.5 percent on weekends. Therefore, the $24.06 value per trip is the weighted average of the value of weekend trips ($13.18) and weekday trips ($30.41). Each of the trips resulting from expanded services is assumed to be the same length as that used to calculate annual value in Table 14. The 2025 value of expanded weekend and connection service totals $36.69 million. Adding that amount to the 2025 value for weekdays in Table 14, gives us a total estimated value of $114.18 million. The difference between that value and the 2025 value of the existing system is $76.93 million. Ridership projections are not available for the years after 2025, but it is likely that the rate of growth for the upgraded and expanded system will continue to be higher than for the existing system. If we use TSI, OCTOBER 2014, REGIONAL ECONOMIC IMPACT OF ACE RAIL EXPANSION 23 the relative rates of growth for weekday service to project future ridership, applying it to all elements of service expansion, then the gap in annual values widens. Using this approach, the added value of the upgrades and service expansion totals $433.0 million for the five-‐year period beginning in 2025. Table 16: Value of W eekend Service and Connections to High Speed Rail: 2025 (2014 Dollars) Service Total Value per Trip Annual Trips Annual Value Weekend Service $13.48 1,845,000 $24,867,278 HSR Connection $13.48 298,550 $4,023,916 BART Connection* $24.06 348,800 $8,392,307 Totals 2,492,350 *Assumes weekend trips are 60% of weekday trips for the BART connection $37,283,502 Benefits of Attracting Additional Residents to Stanislaus and Merced Counties Projected regional levels of county-‐to-‐county migration and commuting in conjunction with future population and employment growth estimates lead to the inevitable conclusion that the requirements of Bay Area labor market will be increasingly dependent on in-‐commuting. Where those new commuters live depends on a number of factors including the cost and convenience of commuting from their place of residence to their place of employment. The counties able to attract those new residents will benefit from the expenditure within the local economy of the higher incomes earned in the Bay Area. In this section of the report we examine the benefit to Stanislaus and Merced counties associated with attracting these new residents. Table 17 contains the estimated benefits per 100 new residents who move to the area that includes Stanislaus and Merced counties. These estimates are presented for five occupations, with annual average Bay Area salaries ranging from $38,820 to $105,430. For each of the occupations the average wage is entered into the household sector income range containing the average for that occupation. This is important since, because those with higher incomes tend to spend a smaller percentage of their incomes, the impact per dollar of added income is smaller. The local impacts to the resident counties are measured in terms of output (gross business revenues), Income (earnings by employers and their workers), employment, and state and local taxes. The average impact for all occupations per 100 new residents commuting to the Bay Area is $6.74 million in output, $4.55 million in income, $0.36 million in state and local taxes, and 36 part-‐ and full-‐time jobs. TSI, OCTOBER 2014, REGIONAL ECONOMIC IMPACT OF ACE RAIL EXPANSION 24 Table 17: Value of Attracting New Commuters to Stanislaus and M erced Counties: per 100 Commuters by Occupation (2014 Dollars) Occupation Bay Area Average Wages per 100 Commuters Output Income Computer and Mathematical Occupations $105,430 $10,543,000 $6,886,692 $5,131,357 58 $588,436 Education, Training , and Library $58,823 $5,882,333 $4,004,389 $2,688,700 31 $312,281 Healthcare Support $38,820 $3,882,000 $2,798,645 $1,889,398 21 $216,666 Office and Administrative Support $44,623 $4,462,333 $3,217,024 $2,171,851 25 $249,056 Business and Financial Operations $89,477 $8,947,667 $5,844,620 $3,907,219 45 $455,123 Average $67,435 $6,743,467 $4,550,274 $3,157,705 36 $364,313 State & Local Taxes TSI, OCTOBER 2014, REGIONAL ECONOMIC IMPACT OF ACE RAIL EXPANSION Employment 25 B E N E F IT S T O T H E S A N JO A Q U IN V A L L E Y A N D IT S R E S ID E N T S O F P R O V I D I N G A C C E S S T O B R O A D E R L A B O R M A R K E T S Growth in Sector Employment Access to labor markets in the MSA’s to the west of the San Joaquin Valley will provide significant benefits to valley residents. While population growth is projected to be highest in the San Joaquin Valley, the California Employment Development Department (EDD) forecast of MSA job growth places the fastest growth rates in the Bay Area. That is particularly true of those sectors paying the highest wages. For example, the San Jose-‐Sunnyvale-‐Santa Clara MSA added 15,100 jobs in professional and business services between 2008 and 2012, while San Joaquin, Stanislaus, and Merced counties combined lost 2,700 jobs in that sector over the same interval (Table 18). Table 18: Sector Employment Growth by M SA: 2008-‐2012 Region (MSA or MD) San Jose-‐ Sunnyvale-‐ Santa Clara Construction* Manufacturing Trade, Transportation & Utilities Information Services -‐9,600 -‐10,800 -‐5,700 San Francisco-‐ San Mateo-‐ Redwood City -‐8,800 -‐6,100 -‐2,200 Alameda County Stockton MSA Modesto Merced -‐16,000 -‐6,900 -‐9,000 -‐3,800 -‐3,400 500 -‐2,800 -‐1,900 700 -‐800 -‐900 400 10,500 8,300 -‐2,500 -‐300 -‐900 -‐300 Financial Services -‐1,000 -‐9,600 -‐2,600 -‐1,900 -‐700 -‐200 Professional & Business Services 100 19,500 4,200 -‐1,100 -‐1,500 -‐100 Education & Health 15,100 9,100 5,900 800 2,300 900 Leisure & Hospitality 4,400 8,300 2,400 -‐500 -‐600 -‐300 Government -‐6,400 -‐3,400 -‐9,700 -‐4,300 -‐1,300 *For Modesto and Merced construction employment includes logging and mining http://www.labormarketinfo.edd.ca.gov/Links_to_LMI_by_Metropolitan_Area.html 900 That disparity in job growth is expected to grow with the ongoing economic recovery. Table 19 contains EDD forecasts for job growth by sector for regional MSA’s. According to that forecast, by 2020 the San Jose-‐Sunnyvale-‐Santa Clara MSA can expect to see and additional 44,100 jobs in business and professional services by 2020 (over 2010 levels), and a total of 192,500 additional jobs in all sectors. It is expected that the San Francisco-‐San Mateo-‐Redwood City MSA will see even stronger job growth, with 57,300 additional jobs in professional and business services and total job growth of 196,000 jobs over and above 2010 employment levels. Those estimates of job growth contrast sharply with the forecast TSI, OCTOBER 2014, REGIONAL ECONOMIC IMPACT OF ACE RAIL EXPANSION 26 for San Joaquin Valley MSA’s. By 2020 the combined MSA’s for Stockton, Modesto, and Merced are expected to add just 8,200 jobs in professional and business services, and a total of 81,600 jobs. Table 19: Forecasted Employment Growth by M SA: 2010-‐2020 Region (MSA or MD) Construction* 11,100 San Francisco-‐ San Mateo-‐ Redwood City 8,600 Manufacturing 26,500 8,300 3,700 400 7,200 600 Trade, Transportation & Utilities Information Services Financial Services 23,800 24,800 25,300 14,100 2,300 2,500 20,000 13,900 700 100 100 0 4,800 3,600 8,100 1,100 400 200 Professional & Business Services 44,100 57,300 39,900 4,200 3,900 1,000 Education and Health Leisure & Hospitality 33,000 21,600 22,600 7,700 1,600 1,600 18,100 28,100 18,600 4,100 2,600 1,200 7,400 7,400 12,900 3,300 2,100 1,900 Total including 192,500 196,000 158,600 41,900 28,600 Self-‐Employed For Modesto and Merced construction employment includes logging and mining http://www.labormarketinfo.edd.ca.gov/Links_to_LMI_by_Metropolitan_Area.html 11,300 Government San Jose-‐ Sunnyvale-‐ Santa Clara Oakland-‐ Fremont-‐ Hayward Stockton Modesto Merced 13,700 2,200 3,700 600 Wage Differentials within the Region The differences between San Joaquin Valley MSA’s and those in the Bay Area are not only dissimilarities in employment opportunities. There is also a significant difference in wage rates across all occupational categories. Table 20 contains average annual wage rates for selected occupations. This 2013 data from the Bureau of Labor Statistics highlights the significant difference between wage rates within the region. For computer and mathematical occupations in the San Jose-‐Sunnyvale-‐Santa Clara MSA, the average annual wage rate is $115,870. The average is slightly lower for the other Bay Area MSA’s, ranging from $96,640 to $103,780. Jobs in the same occupational category for those employed in the San Joaquin Valley range from $68,620 to $76,460. Similar wage differentials exist in other occupational categories, particularly in categories with higher average wages. Bay area wages for high paying occupations are higher than those in the San Joaquin Valley by 30 to 47 percent. For those in the middle of the salary range including education, healthcare TSI, OCTOBER 2014, REGIONAL ECONOMIC IMPACT OF ACE RAIL EXPANSION 27 support, transportation, production workers, community and social welfare, and office and administrative support, the wage differentials range from 9 to 30 percent, with most around 20 percent. Table 20: 2013 Average Annual W ages by M SA for Selected Occupations Region (MSA or MD) Computer and Mathematical Occupations San Jose-‐ San Francisco-‐ Sunnyvale-‐ San Mateo-‐ Santa Clara Redwood City Oakland-‐ Fremont-‐ Hayward Stockton MSA Modesto Merced $115,870 $103,780 $96,640 $68,620 $76,460 $69,980 Community and Social Services $58,250 $54,030 $55,050 $51,740 $47,530 $50,000 Education, Training , and Library $57,630 $58,770 $60,070 $53,620 $53,010 $55,640 Healthcare Practitioners and Technical Occupations Healthcare Support $107,140 $110,580 $104,680 $85,280 $96,840 $76,880 $36,720 $41,060 $38,680 $29,880 $31,210 $28,240 Food Preparation and Service $23,680 $26,870 $22,670 $22,080 $22,140 $21,720 Office and Administrative Support $44,850 $46,140 $42,880 $36,190 $34,610 $32,140 Production Workers $39,450 $40,440 $40,720 $34,570 $33,370 $32,540 Transportation and Materials Moving $35,070 $41,580 $40,130 $34,330 $34,410 $32,790 Business and Financial Operations $90,560 $94,790 $83,080 $66,330 $63,040 $61,650 $108,060 $99,440 $98,230 $80,350 $74,890 $81,020 Architecture and Engineering http://www.bls.gov/oes/current/oessrcma.htm TSI, OCTOBER 2014, REGIONAL ECONOMIC IMPACT OF ACE RAIL EXPANSION 28 Population Growth and Job Opportunities Forecasted regional population growth in the San Joaquin Valley counties through 2020 is the highest in the five-‐county proposed ACE service area. In addition, forecasted job growth is the lowest in those areas expected to see the highest population growth. Within the region it is expected that there will be a significant imbalance between the number of new residents and available jobs. The entries in Table 21 highlight what is really an emerging opportunity for present and future residents of the San Joaquin Valley. In the San Jose-‐Sunnyvale-‐Santa Clara and San Francisco-‐San Mateo-‐Redwood City MSA’s it is expected that there will be more jobs created in those areas than new residents of all ages. Clearly that implies that the required employees will need to come from somewhere outside the included counties, and commute into the area. A similar conclusion holds for the Oakland-‐Fremont-‐Hayward MSA, as the number of new jobs created is equal to 83 percent of the number of new residents. Access to those higher paying jobs for those new and existing residents of the San Joaquin Valley, with the appropriate education and training, depends on having the infrastructure available to support the commute into the Bay Area. The linkage between the ACE system and BART at Livermore is an important part of that infrastructure. Table 21: Forecasted Employment Growth Relative to Forecasted Population Growth: by M SA 2010-‐2020 Region (MSA, MD, or County) Definition Population Change 2010-‐ 2020 San Jose-‐Sunnyvale-‐ Santa Clara Employment Change 2010-‐ 2020 Santa Clara and 108,397 192,500 San Benito counties San Francisco-‐San San Francisco, 72,998 196,000 Mateo-‐Redwood City San Mateo, and Marin counties Oakland-‐Fremont-‐ Alameda and 190,156 158,600 Hayward Contra Costa counties Stockton San Joaquin 124,257 41,900 County Modesto Stanislaus 73,951 28,600 County Merced Merced County 45,439 11,300 Population forecasts from http://www.dof.ca.gov/research/demographic/ Employment growth forecasts from http://www.labormarketinfo.edd.ca.gov/Links_to_LMI_by_Metropolitan_Area.html 1.78 2.69 0.83 0.34 0.39 0.25 TSI, OCTOBER 2014, REGIONAL ECONOMIC IMPACT OF ACE RAIL EXPANSION Employment Change/Pop. Change 29 C O N T R A S T IN G D E M O G R A PH IC S : S A N JO A Q U I N V AL L E Y V S . S O U T H B A Y Demographics of Current ACE Ridership The 2014 ACE ridership surveys provide a detailed snapshot of the demographic characteristics of current ACE commuters. Generally, with the exception of educational levels, the demographics of the ridership match up fairly closely with those of the cities (summarized in Table 22) currently served by the ACE system. Forty-‐eight percent of the riders are non-‐white, while the range for the region’s cities is from 25.4 percent to 67.2 percent. Sixty-‐three percent of ACE riders have completed at least four years of college, an education level higher than for any city currently served by the system. As is the case with the cities served, the riders typically are members of households with incomes well above the California median. Eighty-‐four percent of ACE riders are from households with annual incomes above $60,000, while the annual household income of 70 percent exceed $80,000. With the exception of the city of Stockton, cities served by the existing ACE system (western upgrade) have annual household income for 2008-‐12 that is above the state median level. For Fremont it approached $100,000 and for Pleasanton it was over $118,000. With the exception of Ripon, cities that will be served by the eastern extension to Merced have levels of household income below the state median. Table 22: Demographics for Cities with ACE Stations or Proposed Stations(2008-‐12 data) City Median Home Prices: Owner Occupied Median Household Income Travel Time to Work (min.) Poverty Rate (%) % non-‐ white % with B.A. Degree or Higher Air Quality Index Western Upgrade Fremont $605,100 $99,169 29.4 5.8% 67.2% 49.5% Lathrop $199,400 $62,255 37.9 7.4% 58.6% 11.7% Livermore $490,800 $97,375 28.7 5.3% 25.4% 37.5% Manteca $225,700 $62,411 32 9.7% 37.6% 14.9% Pleasanton $723,300 $118,129 29.4 4.6% 33.0% 55.5% San Jose $575,100 $81,349 25.6 11.7% 57.2% 37.2% Santa Clara $618,600 $92,198 21.3 9.0% 55.0% 50.5% Stockton $178,900 $47,246 26.4 23.3% 37.0% 17.5% Tracy $272,600 $75,259 40.3 9.6% 47.3% 21.2% California $383,900 $61,400 27.1 15.3% 42.4% 30.5% Eastern Extension Atwater $139,300 $41,317 21.9 27.2% 34.6% 12.0% Livingston $168,900 $43,887 21.5 19.9% 59.7% 5.6% Merced $150,200 $38,253 21.6 27.0% 53.2% 15.3% Modesto $186,000 $49,205 25.3 19.5% 35.0% 18.3% Ripon $302,200 $73,925 27.1 9.3% 20.3% 29.6% Turlock $214,600 $52,974 22.5 15.7% 30.2% 23.3% Air Quality Index http://www.usa.com/rank/california-‐state-‐-‐air-‐quality-‐index-‐-‐city-‐rank.htm All other data http://quickfacts.census.gov/qfd/states/06000.html 41.5 46.6 39.4 47.1 39.3 42.7 42.8 46.6 46.4 n.a. 58.8 58.6 61 51 48.9 57.4 TSI, OCTOBER 2014, REGIONAL ECONOMIC IMPACT OF ACE RAIL EXPANSION 30 Demographics of Potential Commuters on the Proposed East Branch of the ACE Line While those currently utilizing the ACE system tend to have both high incomes and be highly educated, that is not necessarily the case when service is extended to the San Joaquin Valley. With the exception of Ripon, those cities served by the expansion of the ACE system to the San Joaquin Valley have significantly lower household income compared to most cities served by the current system. In addition, average educational levels are lower than for the cities served by the current system, with only the city of Ripon having a population where more than 25 percent of the residents have completed a college degree. The average for the state of California is 30.5 percent. The other demographic that distinguishes San Joaquin Valley cities from those currently served by the ACE system is air quality. The worst air quality among cities currently receiving ACE service is in Manteca with an air quality index (AQI) of 47.1. For cities to be connected via the eastern branch of ACE, all have an AQI well above (a higher number implies worse air quality) that of Manteca. The AQI range for cities on the ACE eastern branch is from 48.9 (Ripon) to 61.0 (Merced). Table 23: Population Growth Forecasts for Counties in the M SA’s affected by Present or Future ACE Service County Population Change: 2010-‐2020 Annual Percentage Growth Rate Alameda 94,968 0.61% Merced 45,439 1.65% San Francisco 46,534 0.56% San Joaquin 124,257 1.68% San Mateo 27,834 0.38% Santa Clara 103,469 0.56% Stanislaus 73,951 1.35% Marin* -‐1,370 -‐0.05% San Benito** 4,928 0.86% Contra Costa*** 95,188 0.87% * Part of the San Francisco-‐San Mateo-‐Redwood City MSA * *Part of the San Jose-‐Sunnyvale-‐Santa Clara MSA ***Part of the Oakland-‐Freemont-‐Hayward MSA http://www.dof.ca.gov/research/demographic/ TSI, OCTOBER 2014, REGIONAL ECONOMIC IMPACT OF ACE RAIL EXPANSION 31 The populations of San Joaquin, Stanislaus, and Merced counties are projected to grow at significantly higher rates than those to the west. The California Department of Finance projects population growth rates for the northern San Joaquin Valley counties ranging from 1.35 percent (Stanislaus) to 1.68 percent (San Joaquin). For counties served by the current ACE system (excluding San Joaquin) annual rates of population growth are expected to range from 0.56 percent (Santa Clara) to 0.61 percent (Alameda). Differences in population growth and area demographics lead to the conclusion that expanding the ACE system to the San Joaquin Valley will serve an increasingly large population, with income and educational levels below the state median. In addition, by expanding the ACE system to Modesto and Merced, the switching of transportation modes by area commuters will provide disproportionately large air quality benefits. Implications for Obtaining Cap and Trade Funds for Project Finance Cap-‐and-‐Trade funds available for fiscal year 2014-‐15 are expected to total $832 million. Under the allocation formula enacted by SB 535 and AB 1532, 25 percent of those funds are to be allocated towards investments that help achieve greenhouse gas emissions reduction goals, while benefiting disadvantaged communities (ARB 2014). Qualification as a disadvantaged community is based on a combination of demographic measures including income and environmental quality. Under this ranking system, a large number of census tracts in the northern San Joaquin Valley qualify in the top 15 percent (tentatively considered to be the threshold for eligibility) of those eligible for Cap-‐and-‐Trade project funding. F u n d i n g P u r p o s e s There are three funding programs—all included under the Sustainable Communities and Clean Transportation program—that could potentially contribute funds to financing construction and/or operation of the ACE system expansion. For fiscal year 2014-‐15, $25 million is available through the California Transportation Agency and local transit agencies for funding low carbon transit operations. An additional $25 million is available through the California Department of Transportation and the California Transportation Commission for the Transit and Intercity Rail Capital Program. The largest share of transportation funding (with the exception of the allocation to high speed rail) is administered through the California Air Resources Board for low carbon transportation, with a fiscal year 2014-‐15 allocation of $200 million. These funding levels are likely to increase substantially in the future as transportation is included in Cap-‐and-‐Trade. L i k e l i h o o d o f A c q u i r i n g C a p a n d T r a d e F u n d s f o r A C E E x p a n s i o n Based on the relative share of census tracts in the top 15 percent of those defined as disadvantaged, the San Joaquin Valley should receive a significant share of the funding under the transit categories mentioned in the previous section. Of course, there are other census tracts in the southern part of the valley and to the east of Los Angeles and San Diego that qualify on the same demographic basis. For that reason it is impossible to provide a prediction as to the actual dollar amount ACE upgrade and expansion will receive from Cap-‐and-‐Trade funds. TSI, OCTOBER 2014, REGIONAL ECONOMIC IMPACT OF ACE RAIL EXPANSION 32 L IT E R A T U R E R E V IE W : D O C O M M U T E R R A IL S Y ST E M S C R E A T E E C O N O M IC V A L U E IN T H E C O M M U N IT IE S TH E Y S E R V E? This section of the report provides an overview of the literature that addresses the question as to whether commuter rail creates economic value in the communities they serve. The analysis is based on the results of fifty-‐eight scholarly studies on the economic benefits of commuter and light rail systems. These studies examine many of the issues we were unable to quantify in other sections of this report. This academic literature review also provides perspective on our formal calculations on whether the proposed ACE commuter rail extension is likely to add to the economic value of the communities through which it passes. (The detailed study is appended as Attachment 1: Literature Review Detail.) Data gleaned from the literature naturally fall into seven major economic categories plus miles traveled. These eight categories are: • Home property values • Apartment building values or rents • Commercial property values or new business generation • Commuter rail as an amenity • Planning and Implementation • Economic aggregation and interregional benefits including job generation • Generation of taxes • Vehicle miles driven We extended our search beyond California commuter rail studies to other states to provide a comprehensive a look at the issues involved. This overview encompasses a variety of economic analyses and methodologies, all of which were included in an effort to gain broad understanding of how complex interacting municipal, social and other factors can affect economic outcomes. Literature Reviewed and Method of Analysis A search of peer reviewed academic journals, regional government studies, and other major publications yielded 58 data-‐based studies on commuter rail economic benefits. These were either abstracted (articles published between 2001 and 2014) or were abstracted by TSI and reported in tables in two journal articles (published prior to 2001) (see pages X-‐X below). Here are some sources: The Journal of Planning Literature; Transportation Research; empirical economic studies contracted for by regional planning agencies; policy documents produced by state agencies such as California’s Air Resources Board; those produced by Federal Agencies like Transportation Research Board of the National Academies; independent think tanks like the California Public Policy Institute; the Mineta National Transit Research Consortium; and various national industry associations such as the Public Transportation Association and the National Association of Realtors. (See Attachment 1 for the results and literature citations.) Knowing that study abstracts report the most significant findings, we were able to use this information to generate a broadly simplified but complex overview of the economic effects of commuter rail. Studies were sorted by the kind of economic value being studied (the nine categories reported here) and by whether the introduction of commuter rail resulted in increases, no change, or decreases in TSI, OCTOBER 2014, REGIONAL ECONOMIC IMPACT OF ACE RAIL EXPANSION 33 economic outcomes. Of course, innumerable variables affect these outcomes. Some studies reported significant variations by city, income, and job characteristics, making it difficult to speak to a single outcome. These were treated carefully by reporting them as varies by city or other significant factors. We caution the reader that this is a qualitative literature review where sorting was done by hand and outcomes reported here may overlook many methodological issues including sample size, the validity of combined tests of significance and so on. We depend instead on the care and objectivity of the original study reviewers. Furthermore we lump together all locations irrespective of geographic significance. Some cities like Portland and San Francisco were studied more than once. In the end we came to believe that study results may have been influenced by historical decade-‐based variations in urban development. We dealt with this wrinkle by grouping studies into two groups based on publication date: 1990-‐1999 (26 studies) and 2000-‐2014 (34 studies) (Table 24). Table 24: Summary of Economic Effects of Commuter, Light, or Heavy Rail Economic Effects of Commuter Light or Heavy Rail : Predominant Findings Reported for 58 Studies * Time Period Published: 2000-‐2014 Economic Value: Issue: Home Property V alues Apartment Building V alues or Rents Commercial Property V alues or new Business formation Commuter Rail as an Amenity Government Planning and Implementation Economic Aggregation and Interregional Benefits i ncluding job generation Generate Taxes Vehicle Miles Driven Elevated Rail Line Total by Economic V alue Category Time Period Published: 1990-‐1999 Economic Value: Varies by City, Stay the income or Job Increase same Decrease Characteristics 8 6 1 2 1 1 Mixed or Varies by City Stays the or Job Increase same Decrease Characteristics 11 2 3 2 3 1 1 1 2 4 2 1 4 1 1 19 2 0 6 9 17 3 4 *Sources: TSI e dited a bstracts for this s tudy a s l isted a nd drew upon: Qisheng Pan, The i mpacts of a n urban l ight rail s ystem on residential property values: a case s tudy of the Houston METRORail transit l ine. Transportation Planning a nd Technology, 2 013 Vol. 3 6, No. 2 , 1 45169 http://dx.doi.org/10.1080/03081060.2012.739311 a ccessed:9-‐1 -‐1 4; a nd The ARC Effect: How Better Transit boosts home values and l ocal economies , Regional Plan Association, J uly 2 010. http://www.rpa.org/pdf/RPA-‐The-‐ARC-‐Effect-‐Appendices.pdf a ccessed 9 -‐1 014. 2 Literature Findings on the Economic Effect of Commuter Light or Heavy Rail Both time periods show positive financial outcomes across multiple categories plus a reduction in vehicle miles driven. But results are not uniform; the most interesting studies distributed outcomes across all three categories: increase, decrease, and stayed the same. Economic results can be positive and/or negative depending on locale and other intervening factors such as resident income and job characteristics. Studies published during the most recent block of time, 2000-‐14, were much more likely to report benefits than studies from 1990-‐1999. The more recent studies also recognize how other factors affect outcomes. Reasons behind the differences in these two groups could be due to progress in the study of urban-‐suburban development generally, improved research methods, or variations in how cities are developing. TSI, OCTOBER 2014, REGIONAL ECONOMIC IMPACT OF ACE RAIL EXPANSION 34 Turning to each of the eight key economic components and to changes in motor vehicle miles drives, we find that: • Home property values were positively affected in the great majority of cases. The amount of the increase may vary by: type of commuter rail (lower for light rail) distance from the station or tracks, the income of the community (may go down in higher income communities but up for lower income housing), level of noise (strong negative in non-‐urban communities but not in urban communities with high levels of noise already), lower impact of a recession on housing values with residential areas with the most access being the most resistant; gentrification is positively affected; • Apartment building value or rents tended to increase the closer the structure was to a station. • Commercial Property Values or new Business formation did not show a clear affect increasing in some studies but either staying the same or decreasing in others. Various intervening factors play a significant role such as: the relationship can be positive or modest or non-‐existent being especially influenced by city building and other regulations; how new the commercial buildings are; if there is a significant entertainment center and shopping available at the station or close in making the station a destination; and if parking is available. • Commuter rail as an amenity making a positive contribution to economic value depends on such factors as: speed of the train; the distance covered by the track (longer is better); Millennial travelers like commuter rail if the latest high speed web based amenities are built-‐in; the commute is to a job; in some cases lower income commuters are benefited the most; and the station has convenient multimodal links. • Government Planning and Implementation cycle may track with increasing housing values through all stages if it is the right project for the community. • Economic Aggregation and Interregional Benefits including job generation are shown to occur in the most recent studies but are complex processes that could fail. o A meta-‐analysis of 300 US metropolitan areas found that adding about 4 seats to rails and buses per 1,000 residents produced 320 more employees per square mile in the central city travel to—an increase of 19%. Adding 85 rail miles delivered a 7% increase in employment. A 10% expansion in transit service (additional seats or rail miles) produced a wage increase of between $53 and $194 per worker per year in the city center. This produced an estimated total wage increase ranging between $1.5 million and $1.8 billion per metropolitan area. On average, across all the metro areas in the study, expanding transit service produced an economic benefit via agglomeration of roughly $45 million a year — with that figure ranging between $1.5 million and $1.8 billion based on the size of the city (Chatman, and Nolan 2014). o A study of the potential economic impact of the New Haven-‐Hartford-‐Springfield commuter rail line found that it could stimulate an estimated increase of $50 million in economic output per year in the Expanded Knowledge. Commuter train operation could result in the creation of about 249 jobs with an average wage of $34,000 in the Expanded Knowledge Corridor. Service operations were predicted to increase regional economic output by almost $15 million per year and regional income tax revenues by about $1.2 million per year. An additional $152 million in economic activity could be created. The public investment could result in more than 600 new jobs during TSI, OCTOBER 2014, REGIONAL ECONOMIC IMPACT OF ACE RAIL EXPANSION 35 • • construction activities and more than 250 permanent new jobs from operating expenditures (Foster, 2006). o At an industry cluster level, existing clusters in the Minneapolis–St. Paul metropolitan region showed significant industry sector-‐to-‐sector differences. These differences reveal the poor level of transit access to some economic sectors and the need for automobile ownership to reliably access these jobs (Tilahun and Fan 2014). o In a study modeling multiple California computer rail projects outcomes it was found that job-‐development patterns make a difference for transit ridership but that residential patterns are less important. In particular they find that while some station openings did boost employment, others didn’t, and that on average no boost occurred. Employment growth increased most around stations located in higher-‐density areas. Existing zoning patterns and fiscal incentives, though favoring commercial over residential development, have not resulted in employment growth around new transit stations. Furthermore, most transit oriented policies discouraged commercial development relative to residential development near transit (Kolko, 2011). Generate Taxes was found to be an effect of building commuter rail systems, particularly when housing and aggregate effects occurred. Vehicle Miles Driven decreased but due to population growth these savings could have been swamped by increased numbers of cars being driven. Overall these findings are in agreement with, and provide updates to, a comprehensive 2001 review of transit-‐oriented development (TOD) commissioned by the California Department of Transportation, developed by Robert Cervero, Ferrell and Murphy (2002), from the Institute of Urban and Regional Development, University of California Berkeley. The following ten points quoted below summarize their findings. 1. Provide mobility choices. By creating “activity nodes” linked by transit, TOD provides important mobility options, very much needed in congested metropolitan areas. This also allows young people, the elderly, people who prefer not to drive, and those who don’t own cars the ability to get around. 2. Increase public safety. By creating active places that are busy though the day and evening and providing “eyes on the street,” TOD helps increase safety for pedestrians, transit-‐users, and many others. 3. Increase transit ridership. TOD improves the efficiency and effectiveness of transit service investments by increasing the use of transit near stations by 20 to 40 percent, and up to five percent overall at the regional level. 4. Reduce rates of vehicle miles traveled (VMT). Vehicle travel in California has increased faster than the state’s population for years. TOD can lower annual household rates of driving 20-‐40 percent for those living, working, and/or shopping within transit station areas. 5. Increase households’ disposable income. Housing and transportation are the first and second largest household expenses, respectively. TOD can free-‐up disposable income by reducing the need for more than one car and reducing driving costs, saving $3,000-‐$4,000 per year. 6. Reduce air pollution and energy consumption rates. By proving safe and easy pedestrian access to transit, TOD allows households to lower rates of air pollution and energy consumption. Also, TODs can help households reduce rates of greenhouse gas emissions by 2.5 to 3.7 tons per year. TSI, OCTOBER 2014, REGIONAL ECONOMIC IMPACT OF ACE RAIL EXPANSION 36 7. Conserve resource lands and open space. Because TOD consumes less land than low-‐density, auto-‐oriented growth, it reduces the need to covert farmland and open spaces to development. 8. Play a role in economic development. TOD is increasingly used as a tool to revitalize aging downtowns and declining urban neighborhoods, and to enhance tax revenues for local jurisdictions. 9. Contribute to more affordable housing. TOD can add to the supply of affordable housing. It was recently estimated that housing costs for land and structures can be significantly reduced through more compact growth patterns. 10. Decrease local infrastructure costs. TOD can reduce costs for water, sewage and roads to local governments and property owners by up to 25 percent. Discussion Again, the summary table presented here is, for the most part, derived from study abstracts. It is not the reflection of a meta-‐study that would draw together data from all studies, perform various secondary analyses, etc., to arrive at more precise and reliable findings. Nevertheless, counting key results, sorted by category, does point out issues and suggest a way forward for policy discussions and decisions. This discussion starts by briefly looking into what is known about commuters generally augmenting our ACE commuter data reported elsewhere in this report, moving to the perceptions of future commuters. The success of the ACE extension project depends to an important degree on not only immediate economic benefit but also on the likelihood that commuters will select the train for transport now and in the future to maintain those benefits. What factors need to be maximized to get them on board? A group of McGill University researches in Montreal asked: Which mode of travel provides the happiest commute? In Montreal commuter train riders are much more satisfied with rail transit commutes than all other modes—automobile, bus, bicycle -‐-‐ except walking. Time taken to commute was less important for train riders and walkers because they enjoyed the commute itself (St-‐Louis, et al. 2014). "Super-‐commuter" is a term for the person who works in the central county of a given metropolitan area but lives beyond the boundaries of that metropolitan area, commuting long distances to work. What is known about this phenomenon? (1) City labor sheds (where workers live) are expanding rapidly which means super-‐commuter growth rates are far outpacing workforce growth rates. (2) As of 2009, super-‐commuters accounted for 13% of the workforce in both Dallas and Harris (Houston) counties in Texas. (3) Exceptional growth in super-‐ commuting is occurring in the following cities: Dallas-‐Ft. Worth to Houston, Austin and San Antonio to Houston, Northern California to Los Angeles, and Boston to Manhattan. (4) Super-‐commuters tend to be young (under 29 years old) and are more likely to be middle class than the average worker. (5) These days, metropolitan regional growth is due to new city relationships where “twin cities” stretch 100-‐200 miles away from one another rather than 20 to 40 miles (Moss and Quing 2012). The “Demographics of Current ACE Ridership” are very consistent with this profile and align with expected changes due to increased San Joaquin Valley ridership. These findings align with those from a national poll of Millennial attitudes toward public transportation. Members of the Millennial Generation were born between 1982 and 2003. They are 40% African American, Latino, and Asian or racially-‐mixed, and 60% white aligning well with the current and future ACE ridership ethnic profile. They view public transportation options as best for creating favorable digital socializing opportunities and for connecting face-‐to-‐face with their social communities. Public TSI, OCTOBER 2014, REGIONAL ECONOMIC IMPACT OF ACE RAIL EXPANSION 37 transportation also allows them work as they travel, a trend noted by 40% of those polled. Reasons and motivations for selecting transportation of choice are: 46% reported a need to save money; 46% noted convenience; 44% want exercise; and 35% say they live in a community where it just makes more sense to use transit. Some of these factors don’t align with the current ACE ridership but do align with the expected ridership from the San Joaquin Valley. In future public transport systems, Millennials would like to see: 1) 61% more reliable systems, 2) 55% real-‐time updates in train departure and arrival schedules, 3) 55% Wi-‐Fi or 3G/4G wherever they go, 4) 44% a more user-‐friendly and intuitive travel experience including fully leveraging technology with real-‐time transit applications that connect users with community amenities; and smartphone fare payment (Sakaria and Stehfest 2013). Combining our list of consumer satisfaction factors -‐-‐ such as access to fast trains with net oriented amenities that connect to jobs a significant distance away -‐-‐ with our analysis of economic components and factors that contribute to economic success, we see a highly nuanced, complex planning and construction schedule undertaking. Clearly, decisions must be placed within a local station-‐by-‐station context relative to the appropriate mix of train amenities and distance to jobs to achieve economic success. Local planning issues such as route choice into and through a city, the location of stations relative to the income of neighborhoods and mix of housing or apartments. Equally important is the consideration of whether a particular station should be a cultural and shopping destination with adequate parking and multimodal interfaces. TSI, OCTOBER 2014, REGIONAL ECONOMIC IMPACT OF ACE RAIL EXPANSION 38 C O N C L U S IO N S Upgrading and Expanding the ACE rail system will generate significant economic value in the five-‐county service region. Capital expenditure plans call for $912.24 million in spending on new rail construction, structures, signal systems, and rolling stock. It is likely that no more than 25 percent, or $228 million of that funding will come from local sources. The capital expenditures, spread over a seven-‐year period from 2017 through 2023, will generate an additional $1.09 billion in gross business revenues within the region, with $564.83 million of that amount accruing as income to local businesses and their employees. A total of 5,716 person-‐years of employment will result from that activity, and state and local government will receive an additional $37.15 million in tax revenues. The economic value was estimated for the expanded system. Expansion will increase both the number of riders and the average mileage of a typical trip. The value was assumed to consist of three components: savings on commute costs, the value of work done while commuting, and the value of reduced carbon emissions. The total value for the 2020 through 2024 period was estimated at $144.84 million, while the value from further expansion and ridership by 2025 increased the five-‐year economic value to $433.0 million for 2025 through 2029. Therefore the total economic value for the first ten years of expanded service is $577.84 million. Adding that amount to the impact of construction on local income results in a total estimated regional benefit of $1.14 billion through 2029. Beyond the year 2030 average annual operational benefits will exceed $100 million. There are many potential benefits that we were unable to quantify in this report. Increased ridership results in less peak-‐hour traffic, reducing drive times for those choosing to continue commuting by automobile. Also the reduction in traffic reduces road maintenance costs and the number, and thus the economic cost imposed by accidents. In the long-‐run, continued growth in traffic on area highways will require the construction of additional lanes, at a significant cost in terms of both dollars and the disruption of traffic during the construction period. None of these benefits are included in the estimates. Other potential benefits are discussed in the literature review contained in the preceding report section. Among those benefits excluded from out analysis are (1), positive impacts on property values, (2), job-‐ creating aspects of regional integration, (3), new business creation, (4), increased local tax revenues, and (5), the productivity enhancing effects of a broader labor market. Because there is such a diversity of opinion as to the value of these benefits, we did not attempt to quantify them in this study. The majority of the studies examined concluded that they are positive, yet there was a considerable range of estimates in the literature, and frequently the magnitude of a given estimate was too site-‐specific to apply to the case of ACE expansion. TSI, OCTOBER 2014, REGIONAL ECONOMIC IMPACT OF ACE RAIL EXPANSION 39 R E F E R E N C E S Scholarly Articles Atkinson-‐Palombo, Carol (2010). Comparing the Capitalization Benefits of Light-‐Rail Transit and Overlay Zoning for Single-‐Family Houses and Condos by Neighborhood Type in Metropolitan Phoenix, Arizona. Urban Studies, October 2010, v. 47, iss. 11, pp. 2409-‐26. Bartholomew, Keith and Reid Ewing (2011). Hedonic Price Effects of Pedestrian-‐ and Transit-‐Oriented Development. Journal of Planning Literature February 1, 2011 26: 18-‐34. Becker, Sofia (2013). The New Real Estate Mantra. Center for Neighborhood Technology for the National Association of Realtors. http://www.apta.com/resources/statistics/Documents/NewRealEstateMantra.pdf Accessed: 9-‐3-‐14. Bekka, Khalid (2010). Haverhill-‐Plaistow MBTA Commuter Rail Extension Benefit-‐Cost Analysis. HDR Company, prepared for the Rockingham Planning Commission, NH. https://www.dot.state.oh.us/engineering/OTEC/2010%20Presentations/18E-‐Bekka.pdf http://www.plaistow.com/Pages/PlaistowNH_BOS/BenefitCostAnalysisMemo.pdf Accessed: 9-‐1-‐14. Boarnet, Marlon, Hsin-‐Ping Hsu, Susan Handy (2011). Draft Policy Brief: Impact of Jobs-‐Housing Balance on Passenger Vehicle Use and Greenhouse Gas Emissions Based on a Review of the Empirical Literature. Policy Brief, Air Resources Board. http://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=19&cad=rja&uact=8&ved=0CD0Q FjAIOAo&url=http%3A%2F%2Farb.ca.gov%2Fcc%2Fsb375%2Fpolicies%2Fjhbalance%2Fjhbalance_brief.p df&ei=7gAGVP3vIYf3yQT4tIKQCQ&usg=AFQjCNHLQqtzdm9EQxq0fT_TzMJgNeQ9Gg Accessed: 9-‐2-‐14. Cervero, Robert (1994). Rail Transit and Joint Development. Journal of the American Planning Association 60, 1 (1994): 83-‐94. Cervero, Robert. and Landis, J. (1997). Twenty-‐Years of the Bay Area Rapid Transit System: Land Use and Development Impacts. Transportation Research A, Vol. 31, No. 4, pp. 309-‐333. Cervero, Robert, Christopher Ferrel, and Steven Murphy (2002). Transit-‐Oriented Development and Joint Development in the United States: A Literature Review. Transit Cooperative Research Program, Transportation Research Board of the National Academies, October 2002, number 52. Chatman, Daniel and Robert Nolan (2014). Transit Service, Physical Agglomeration and Productivity in US Metropolitan Areas, Urban Studies. 3-‐5-‐2014. http://usj.sagepub.com/content/early/2013/08/01/0042098013494426 Accessed: 9-‐4-‐14. Golub, Aron, Subhrajit Guhathakurta and Bharath Sollapuram (2012). Spatial and Temporal Capitalization Effects of Light Rail in Phoenix: From Conception, Planning, and Construction to Operation. Journal of Planning Education and Research December 1, 2013 33: 395-‐410. Foster, Paul (2006). The Economic Impact of the Proposed New-‐Haven-‐Hartford-‐Springfield Commuter Rail Line. Pioneer Valley Planning Commission, Regional Information Center. TSI, OCTOBER 2014, REGIONAL ECONOMIC IMPACT OF ACE RAIL EXPANSION 40 http://oldsite.pvpc.org/PVPC/resources/infopolicycenter/EconomicImpactBriefingFinal.pdf Accessed: 9-‐ 1-‐14. Grube-‐Cavers, Annelise, and Zachary Patterson (2014). Urban rapid rail transit and gentrification in Canadian urban centers: A survival analysis approach. Urban Studies March 18, 2014 0: 0042098014524287v1-‐42098014524287. Accessed: 8-‐28-‐14. Hess, Daniel Baldwin and Almeida, Tangerine Maria (2007). Impact of Proximity to Light Rail Rapid Transit on Station-‐Area Property Values in Buffalo, New York. Urban Studies, May 2007, v. 44, issue 5-‐6, pp. 1041-‐68. Kolko, Jed (2011). Making the Most of Transit: Density, Employment Growth, and Ridership around New Stations. Public Policy Institute of California. Landis, John and David Loutzenheiser (1995). BART Access and Office Building Performance. Working Paper UCTS No. 309, September 1995, Department of City and Regional Planning, Institute of Urban and Regional Development, University of California Berkeley. http://www.uctc.net/papers/309.pdf Accessed: 9-‐2-‐2014. Michaelson, Juliette (2010). The ARC Effect: How Better Transit Boosts Home Values and Local Economies, Regional Plan Association, New Jersey, July 2010. http://www.rpa.org/pdf/RPA-‐The-‐ARC-‐ Effect-‐Appendices.pdf Accessed 9-‐1014. Moss, Mitchell and Carson Qing (2012). The Emergence of the “Super-‐Commuter”. Monograph, Rudin Center for Transportation, New York University Wagner School of Public Service, February 2012. http://wagner.nyu.edu/files/rudincenter/supercommuter_report.pdf Accessed: 9-‐3-‐14. Nasri, Arefeh and Lei Zhang (2014). The Analysis of Transit-‐Oriented Development (TOD) in Washington, D.C. and Baltimore Metropolitan Areas. Transport Policy, Volume: 32, 3, pp 172-‐179. Noland, Robert, Daniel Chatman, and Nicholas Kelien (2014). Transit Access and the Agglomeration of New Firms: A Case Study of Portland and Dallas (2014). Mineta National Transit Research Consortium. http://transweb.sjsu.edu/PDFs/research/1145-‐transit-‐access-‐and-‐firm-‐births-‐portland-‐dallas.pdf Accessed 8-‐14-‐14. Petheram, Susan, Arthur Nelson, Matt Miller, and Reid Ewing (2013). Use of the Real Estate Market in Salt Lake County, Utah, by Light Rail Station Distance. Transportation Research Record: Journal of the Transportation Research Board, No. 2357, Transportation Research Board of the National Academies, Washington, D.C., 2013, pp. 95–99. Accessed: 9-‐2-‐14. Qisheng, Pan (2012). The Impacts of an Urban Light Rail System on Residential Property Values: A Case Study of the Houston Metrorail Transit Line. Transportation Planning and Technology, 2013 Vol. 36, No. 2, 145 169 http://dx.doi.org/10.1080/03081060.2012.739311 accessed: 9-‐1-‐14. Sakaria, Neela and Natalie Stehfest (2013). Millennials & Mobility: Understanding the Millennial Mindset. Latitude Research for the Transportation Research Board, Public Transportation Association, 2013. TSI, OCTOBER 2014, REGIONAL ECONOMIC IMPACT OF ACE RAIL EXPANSION 41 http://www.apta.com/resources/reportsandpublications/Documents/APTA-‐Millennials-‐and-‐ Mobility.pdf Accessed: 9-‐3-‐14. Shepard, Stephen (2010). Economic Benefits of Housatonic Railroad Passenger Service. Center for Creative Community Development, Williamstown, MA. http://www.nwctedc.com/HTMLobj-‐ 450/SHEPPARD_REPORT.PDF Accessed 8/28/14 St-‐Louis, Evelyne, Kevin Manaugh, Dea Van Lierop, and Ahmed El-‐Geneidy (2014). The Happy Commuter: A Comparison of Commuter Satisfaction across Modes. Transportation Research Part F: Traffic Psychology and Behavior, Volume 26, Part A, September 2014, Pages 160–170. http://www.sciencedirect.com/science/article/pii/S1369847814001107 Accessed: 9-‐1-‐14. Terplan, Egon, and Lesley Miller (2009). Megaregions and Americas Economic Recovery. The Urbanist, Issue 485, September 2009. http://www.spur.org/publications/article/2009-‐09-‐01/job-‐sprawl-‐ megaregion Accessed: 9-‐2-‐14. Thompson, G. and I. Audirac (2000). Types of Transit-‐Oriented Development that Matter to Light Rail. Conference paper, Light Rail: Investment for the Future. 8th Joint Conference on Light Rail Transit, Dallas, Texas. http://trid.trb.org/view.aspx?id=671505 Accessed: 8-‐28-‐14. Tilahun, Nebiyou and Yingling Fan (2014). Transit and Job Accessibility: An Empirical Study of Access to Competitive Clusters and Regional Growth Strategies for Enhancing Transit Accessibility. Transport Policy, vol. 33, May 2014, pages 17-‐25. Data Sources AAA, https://www.google.com/search?sourceid=navclient&aq=&oq=AAA+cost+per+mile+&ie=UTF-‐ 8&rlz=1T4WQIA_enUS566US567&q=aaa+cost+per+mile+2014&gs_l=hp..0.0l5.0.0.0.9427...........0.ng6Xr wguj6c, 2014 driving cost per mile, Accessed Sept. 2014 Altamont Corridor Express, http://www.acerail.com/, Ticket prices and train schedules, Accessed Sept. 2014 Altamont Corridor Express, Various documents including future ridership, construction and equipment cost estimates, and passenger surveys, Supplied by email from Brent Ogden, Vice President U.S.-‐ Transportation Altamont Corridor Express, ACE Forward, Status Report presented to CVRWG, August 22, 2014 Bureau of Labor Statistics, California Occupational Wages, 2013, http://www.bls.gov/oes/current/oes_ca.htm, Accessed Sept. 2014 California Carbon Dashboard, Carbon prices in California, http://calcarbondash.org/?gclid=CNHIgN_y4cACFdGCfgods74ASg, Accessed Sept. 2014 California Department of Finance, Population projections, 2010-‐2060, http://www.dof.ca.gov/research/demographic/, Accessed Sept. 2014 TSI, OCTOBER 2014, REGIONAL ECONOMIC IMPACT OF ACE RAIL EXPANSION 42 California Department of Transportation, Traffic volumes on California highways, 2013, http://traffic-‐ counts.dot.ca.gov/, Accessed Sept 2014 California Employment Development Department, Links to LMI by county: employment data and 2000 county-‐to-‐county commute data, http://www.labormarketinfo.edd.ca.gov/Links_to_LMI_by_County_Area.html, Accessed Sept. 2014 California Employment Development Department, Links to LMI by MSA: employment and employment growth projections, http://www.labormarketinfo.edd.ca.gov/Links_to_LMI_by_Metropolitan_Area.html, Accessed Sept. 2014 SJCOG, Final Report for: I-‐580 Interregional Multi-‐Modal Corridor Study, August 12, 2011, http://www.sjcog.org/DocumentCenter/View/44 U.C. Transportation Center, Traffic congestion and Greenhouse Gases, Fall 2008, http://www.uctc.net/access/35/access35_Traffic_Congestion_and_Grenhouse_Gases.shtml USA.com, California air quality index, http://www.usa.com/rank/california-‐state-‐-‐air-‐quality-‐index-‐-‐city-‐ rank.htm, Accessed Sept. 2014 U.S. Census, County-‐to-‐county migration flows: 2008-‐12, http://www.census.gov/hhes/migration/data/acs/county_to_county_mig_2008_to_2012.html, Accessed Sept 2014 U.S. Census, County-‐to county commuting flows, 2006-‐10, http://www.census.gov/hhes/commuting/, Accessed Sept 2014 U.S. Census, Quickfacts for California cities and counties, http://quickfacts.census.gov/qfd/states/06000.html, Accessed Sept. 2014 TSI, OCTOBER 2014, REGIONAL ECONOMIC IMPACT OF ACE RAIL EXPANSION 43 A P P E N D I X A : L I T E R A T U R E R E V IE W D E T A IL This literature review along with the three accompanying reviews, is a systematic look at the current literature on the economic effects of commuter rail public transport systems. This overview points to multiple potential benefits and troublesome issues that might be addressed to ensure success the proposed ACE extension. Because the populations studied were drawn from across the United States further research specific to the Great Valley region would help further refine the conclusions and suggestions made in our following analysis. TSI reviewed and abstracted 27 studies of commuter rail public transport system economic impact studies, the majority of which were published after 2005. These abstracts are organized by category below. Following are two tables of study abstracts, the majority of which were done prior to 2000. TSI Abstracted Studies o Study Characteristics and Limitations: o o o o o While different findings of the effects of commuter rail are attributable, in part, to local contextual factors (e.g., station designs, softness of local real-‐estate markets) and timing (e.g., whether the market was on an upswing or downswing), they also reflect differences in methodologies (e.g., simple matched pairs, repeat sales ratios, and hedonic price models) and measurements (Cervero, 1997). Sorting this out leaves questions and soft conclusions due to missing data. Length of track was not always reported but it can affect induced economic value, for example, a shorter track has less induced value. But outcomes are inconclusive in the case where a 41 mile Atlanta line increased prices for lower income residential properties but decreased them for higher income properties (Cervero, 2003). Population density was not always addressed. The economic impact of commuter rail in suburban settings may be disproportionately affected by noise issues when compared with urban settings where the ambient noise levels are higher (Cervero, 2003). Age of structures was not always controlled for. The built out quality of commercial projects may be newer the closer they are to new transit stations, which can create higher leasing rates than those for older commercial structures at older stations. Theses inconsistencies lead to variations in economic impact unrelated to the consumer rail system (Landis and Loutzenheiser, 1995). It is extremely difficult to separate the influence of market forces from the effects of planning efforts or political priorities independent of transportation issues themselves, making it difficult to examine the impact of light rail systems (Cervero and Landis 1997). o What are the Social Characteristics of Long-‐Distance Commuters? o A national poll of members of the Millennial Generation -‐ those born between 1982 and 2003 -‐ reported their attitudes toward [all modalities of] transit system use. (Nation-‐ wide, 40% of Millennials are African American, Latino, and Asian or racially-‐mixed which is a marked difference in racial mix compared with the 25% composition found in the earlier two older generations.) Public transportation options are considered the best for creating environments favorable to digital socializing and among the most likely ways to TSI, OCTOBER 2014, REGIONAL ECONOMIC IMPACT OF ACE RAIL EXPANSION 44 o o connect users with their communities. It allows them work as they travel, a trend noted by 40% of those polled. Reasons and motivations for transportation include: 46% reported a need to save money; 46% noted convenience; 44% want exercise; and 35% say they live in a community where it just makes more sense to use transit. Millennials would transit to address in the next ten years: 1) 61% more reliable systems, 2) 55% real-‐time updates, 3) 55% Wi-‐Fi or 3G/4G wherever they go, 4) 44% a more user-‐friendly and intuitive travel experience including fully leveraging technology with real-‐time transit applications that connect users with community amenities; smartphone fare payment (Sakaria and Stehfest 2013). "Super-‐commuter" is a term for the person who works in the central county of a given metropolitan area but lives beyond the boundaries of that metropolitan area, commuting long distances. Major characteristics are: (1) city labor sheds (where workers live) are expanding rapidly with the super-‐commuter growth rates far outpacing workforce growth rates. (2) As of 2009, super-‐commuters accounted for 13% of the workforce in both Dallas and Harris (Houston) counties in Texas. (3) Exceptional growth in super-‐ commuting is occurring in the following cities: Dallas-‐Ft. Worth to Houston, Austin and San Antonio to Houston, Northern California to Los Angeles, and Boston to Manhattan. (4) Super-‐commuters tend to be young (under 29 years old) and are more likely to be middle class than the average worker. (5) These days metropolitan regional growth is due to new city relationships where “twin cities” stretch 100-‐200 miles away from one another rather than 20 to 40 miles (Moss and Quing 2012). A large scale travel survey found that about 84% of pedestrians, 83% of train commuters and 81% of cyclists are significantly more satisfied than drivers, metro and bus users with their mode of commuting. Perceptions that the commute has value other than arriving at a destination significantly increases satisfaction for all modes (St-‐Louis, et al. 2014). o Do Property Values Increase as a Result of Planning and Implementing Transit Systems? How Important are Transportation Amenities for Increasing Property Value? o o o Proximity to light rail transit stations positively affects property values which can begin to appear before a system even opens for operation. Housing markets exhibit different value increases at different stages of the transportation planning and construction process (Golub, et al., 2012). The impact of a new light rail system on single family housing values in Charlotte, North Carolina increased from 1997 to 2008, the period spanning the pre-‐planning, planning, construction and operation phases of the light rail system. This increase in value continued as elements of the system became operational (Hess and Almeida, 2007). Recent consumer surveys and demographic analyses have indicated a growing market for pedestrian-‐ and transit-‐designed amenity development. This market shift should be reflected in the prices people are willing to pay for those amenities. In fact, the literature confirms that these market shifts are being capitalized into real estate prices which demonstrates that the amenity-‐based elements of transit-‐designed development is playing an important positive role in urban land markets, independent of the accessibility benefits provided by transit (Bartholomew and Ewing, 2011). TSI, OCTOBER 2014, REGIONAL ECONOMIC IMPACT OF ACE RAIL EXPANSION 45 o Are Property Values Effected by Proximity to Light-‐ or Heavy-‐Rail Commuter Systems? o o The majority of existing studies find positive impacts of transit rail on residential property values. However, the positive effects are sometimes weak and vary with income, distance to local job centers, and proximity to rail stations, etc. The research also shows that light rail has lesser significant effects on residential property values than heavy rail and commuter rail. Nevertheless, the opening of a light rail line does have significant positive effects on residential property values, findings which are consistent with earlier studies. Distances to rail stations effect residential property values. Without controlling for the effects of other variables such as the distance to job centers, population density, and job density, studies show that the existence of light rail service has positive effects on residential properties located within three miles of rail stations. The significantly positive effects may come from increased access to regional employment, but job sector makes a difference. Access to occupations associated with information services, education services, and public administration have significant positive effects while job access to entertainment and professional services has significant negative effects. Job access to other sectors does not have significant effects on residential property values (Pan 2012). One analysis investigated how well residential properties located in proximity to commuter and light-‐rail have maintained their values as compared with residential properties without transit access between 2006 and 2011 in five regions: Boston, Chicago, Minneapolis-‐St. Paul, Phoenix, and San Francisco. Across the study regions, the transit shed outperformed the region as a whole by 41.6 percent. In all of the regions the drop in average residential sales prices within the transit shed was smaller than in the region as a whole or the non-‐transit area. Boston station areas outperformed the region the most (129%), followed by Minneapolis-‐St. Paul (48%), San Francisco and Phoenix (37%), and Chicago (30%). Transit type had an effect on the resilience of property values, which benefited more from transit that was well connected and had a higher frequency of service. Stations with higher levels of transit access saw the most price resilience within and across regions. No consistent trends have emerged with regard to residential property type. In addition to more resilient residential property values, households living in transit sheds had better access to jobs and lower average transportation costs than the region as a whole. (Becker, 2013). o What is the Effect of Commuter Transit Systems on Single Family Home Property Values? o A statistical analysis of the effect of three recent improvements to NJ TRANSIT’s rail system on home values predicts that a new project, the ARC – a new commuter rail tunnel to Midtown Manhattan – could add a cumulative $18 billion to home values within two miles of NJ TRANSIT and Metro-‐North Port Jervis and Pascack Valley train stations. TSI, OCTOBER 2014, REGIONAL ECONOMIC IMPACT OF ACE RAIL EXPANSION 46 o o o o o o o o An Hedonic price modeling of 45,000 home sales within two miles of train stations shows that three earlier improvements to the NJ TRANSIT rail system – Midtown Direct Service on the Morris & Essex Line, the Montclair Connection for the Montclair-‐Boonton Line and Secaucus Junction for the Pascack Valley and Main/Bergen/Port Jervis Lines – increased the value of nearby homes by an average of nearly $23,000 per home (in 2009 dollars). Homes within walking distance of train stations gained the most value – up to $34,000. Value appreciations were less significant farther from stations. Cumulatively, these three projects boosted home values by $11 billion. This represents $250 million a year in new property tax revenue for municipalities. A detailed comparison of the trip time reductions provided by these three projects with the trip time reductions expected from the new ARC tunnel project reveals that ARC could raise home values by an average of $19,000 per home, and up to $29,000 for homes within one-‐half mile of stations. Cumulatively for all ARC projects, home values could be boosted by $18 billion, and generate $375 million a year in new property tax revenue for municipalities. This is significant as growing tax bases relieve pressure for municipalities to increase tax rates (Michaelson, 2010). A study of three large Canadian cities found that proximity of rail transit (and proximity to other gentrifying census tracts) have a statistically significant effect on gentrification in two of the three cities analyzed (Grube-‐Cavers and Patterson, 2014). A Phoenix light-‐rail study found that rail impacts differ by housing and neighborhood type. Amenity-‐dominated mixed-‐use neighborhoods—predominantly walk-‐and-‐ride communities—experience an increase in premiums of 6% for single-‐family houses and over 20% for condos. The latter was boosted an additional 37% by overlay zoning. However, residential neighborhoods—predominantly park-‐and-‐ride communities— experience no capitalization benefits for single-‐family houses (Atkinson-‐Palombo, 2010). A 1993 study of residential properties near the 14.5-‐mile Lindenwold Line in Philadelphia concluded that access to rail created an average housing value premium of 6.4% (Voith, 1993). Residential properties near the Miami Metrorail system concluded that proximity to rail stations induced little or no increase in housing values (Gatzlaff and Smith, 1993). A study of Portland’s MAX light-‐rail system found positive land-‐value effects only within a 500-‐meter walking distance of stations (Al-‐Moisand, et al., 1993). Workman and Broad’s 1997 study of the light-‐rail that served Portland and the heavy-‐ rail that served Oakland suburbs found the value of residential property within a few blocks of rail stops were lower than those five or six blocks away. A BART study found no loss of value for single-‐family homes within 300 meters of BART stations in San Francisco. The same study, however, recorded a huge negative effect for commuter-‐rail services: in 1990, homes within 300 meters of CalTrain stations sold at an average discount of $51,000. And in the case of San Jose’s light-‐rail system, the same study found that -‐ controlling for other factors -‐ single-‐family homes within 300 meters of stations were worth around $31,000 less than equivalent properties beyond transit’s immediate impact zone (Landis et al., 1994). The Housatonic Railroad is considering an extension of passenger rail service to connect the Metro North Railroad south and west of Danbury, Connecticut, and extend it north TSI, OCTOBER 2014, REGIONAL ECONOMIC IMPACT OF ACE RAIL EXPANSION 47 through parts of Fairfield and Litchfield County, Connecticut and onward to Pittsfield, Massachusetts. This study predicts an increase in total economic output for the region. Specific to home property values though, those located within a few miles of the railroad passenger stations were expected to increase modestly, generating between $310 million and $619 million in additional wealth for property owners (Shepard, 2010). o What is the Effect of Commuter Transit Systems on Apartment Residential Property Value? o When structural, neighborhood, and location characteristics were controlled for, a positive relationship emerges between proximity of TRAX stations and rental apartment building values. This relationship extends 1.25 miles but not beyond (Petheram, Nelson, Miller, and Ewing, 2013). o Is there a Significant Cost Saving with Commuter Rail Construction and Operation as Compared with the Addition of Freeway Lanes? o A study of the costs of constructing the Haverhill-‐Plaistow NH,MBTA commuter line found it to be cheaper than adding additional highway capacity using data from the March 2007 Financial & Economic Benefits Report for the Austin-‐San Antonia Commuter Rail Project. Construction cost savings for two additional freeway lanes within the 112-‐ mile Austin-‐San Antonio corridor is approximately $380 million (assuming ROW is available and commuter rail uses existing rail infrastructure). Furthermore a commuter rail project is cheaper to maintain than two additional freeway lanes of 112 miles each. These freeway costs are estimated at $9.9 million per year which, as compared with rail maintenance, show a total savings of $275 million cumulatively through 2030 (Bekka, 2010). o Do Commuter Rail Systems Reduce Congestion, Traffic and Fatal Automobile Accidents? o o Analysis of vehicle miles traveled by Washington, D.C. and Baltimore residents in transit-‐ oriented development areas show that the availability of rail transit reduced vehicle miles of travel by around 38% in Washington, D.C. and 21% in Baltimore. (Nasri, 2014). The Housatonic Railroad (already spoken to) is anticipated to reduce demand on automobile traffic on local and regional roadways, saving nearly $1.4 million during the first decade of the project. The availability of passenger rail service and anticipated levels of demand will reduce fatal automobile accidents, saving the lives of an expected 8 persons and reducing associated costs of fatal accidents by $7.2 million during the first decade of the project (Shepard, 2010). o What is the Effect of Elevated Commuter Rails Systems on Residential Property Values? o In higher income areas in Atlanta elevated rails depressed residential values (Nelson 1992). TSI, OCTOBER 2014, REGIONAL ECONOMIC IMPACT OF ACE RAIL EXPANSION 48 o In Chicago residential property values adjacent to elevated rails increased 20%; a greater increase than for more than those located ½ mile away. The quality of rail service (high in Chicago) and availability of parking close to station (restricted in downtown Chicago) may account for the difference between Atlanta (above bullet) and Chicago (Lin 2002). o What is the General Economic Effect of Commuter Rail Systems on Regional Property Values? o o o o o o Preliminary to the Haverhill-‐Plaistow NH commuter rail extension, a cost/benefit study was conducted to evaluate light vs commuter rails. This study showed a consistently higher positive impact on the property value of commuter rail compared with light rail (14% higher) and heavy railway/Metro stations. There was an average property value benefit of 3% for every 250m closer than the effect of light rail stations; and a larger catchment area – i.e. a wider service range – than other transit types2030 (Bekka, 2010). A cost-‐benefit study was conducted of the Haverhill-‐Plaistow NH commuter rail extension showing total benefits to be $83.7 million, when discounted by 7 percent. The present value of total costs associated with this project is $35.6 million, compared to the net present value of $48.1 million. The benefit-‐cost ratio is 2.3 at 7 percent and 3.9 at a 3 percent discount rate. Estimated total benefits for the project is $310.4 million breaking down as follows: $155.3 million from a reduction in congestion; $87.8 million in benefits to new users; $45.6 million from a reduction in car accidents; $11.3 million in benefits to existing users, $10 million in environmental benefits; and $0.3 in pavement maintenance savings (Bekka, 2010). This research examines whether new firms are more likely to form near rail transit stations. Two relatively new light-‐rail systems in Portland, Oregon, and in Dallas, Texas form the basis for analysis using time-‐series data on the births and deaths of business firms from 1991 through 2008. Results showed that newly formed firms tend to cluster around stations in the Portland region but not in the Dallas region. There is a much stronger association between transit proximity and new firm birth in the Portland region compared with the Dallas-‐Ft. Worth region. In both regions, however, births of larger firms tend to be associated with greater proximity to transit stations, perhaps reflecting the greater agglomeration benefits that they receive. Different planning and zoning criteria in Portland versus those in Dallas may explain the relative success of Portland in achieving clusters of smaller new firms near transit (Nolan, Chatman, and Klein, 2014). BART, using repeat-‐sales data, found no evidence that rail’s presence increased commercial property values around a suburban station and two inner-‐city stops over the long term (Falcke, 1978). Office with in mile of Atlanta’s MART station leased for less (Bollinger et al., 1998). A study of the Dallas Area Rapid Transit (DART) light-‐rail system compared differences in land values of matched pairs of “comparable” retail and office properties – some near DART and others not. Between 1994 and 1998, the average value of retail and office properties near DART stops increased by 37% and 14%, respectively; for “control” parcels, the averages were 7.1% and 3.7%.(Weinstein and Clower, 1999). TSI, OCTOBER 2014, REGIONAL ECONOMIC IMPACT OF ACE RAIL EXPANSION 49 o A study of Santa Clara County’s light-‐rail system found that properties within a half-‐mile of stations commanded rent premiums but and those that were closer -‐-‐ a quarter to a half mile away -‐-‐ were worth even more (Weinberger, 2001). o A recent study found value premiums for commuter rail system that exceeded 100% for commercial parcels near commuter-‐rail stops in healthy business districts of Santa Clara County, but not elsewhere. Benefits were recorded for one of the County’s commuter-‐ rail systems (CalTrain that connects San Jose and San Francisco), but not the other (Altamont Commuter Express, or ACE, that links the Silicon Valley to pockets of affordable housing in the Central Valley). (Cervero and Duncan, 2002). o The Sylmar Metrolink station in Santa Clarita opened in 1994 and the nearby “Montage at Village Green” housing development opened six years later in 2000. Whereas most TODs focusing on housing are “mixed-‐use developments” incorporating some commercial space, the Montage was exclusively a housing development (Moses et al., 2009). But many businesses were located between the station and the housing development. Data from the NETS database reveals that employment growth accompanying Sylmar development included small businesses across numerous industries, including grocery wholesaling, light manufacturing, construction, and real estate brokerage. The Sylmar example shows that employment can grow around new stations even when the station TOD strategy emphasizes residential development (Kolko, 2011). • Does Planning for the Integration of Commercial Development into Transit Stations have an Economic Effect? o o o Targeting the development of commercial development, local government can form special districts that relax parking and density requirements producing synergies with rail stations increasing commercial activity (Nelson 1999). The joint development and physical integration of rail and commercial projects showed higher average net premiums (7% to 9%), lower vacancy rates, and faster absorption of new leasable space (Cervero, 1994). BART helped concentrate office development in San Francisco as part of an extensive downtown redevelopment effort that included planning for BART. Redevelopment cleared land for modern offices at key Bart station location. San Francisco officials have adopted a succession of public policies, including restricting the amount of office space aimed at concentrating office development in the downtown area and preventing intrusion into residential areas. But for offices near Bart stations in the East Bay and other San Francisco areas, as of 1993, office space near BART stations did not command any sort of systematic rent premium when compared with space elsewhere (Landis and Loutzenheiser, 1995). TSI, OCTOBER 2014, REGIONAL ECONOMIC IMPACT OF ACE RAIL EXPANSION 50 • Does Commuter Rail Service Increase Tax and Other State or Local Government Revenues? o • The Housatonic Railroad is considering a proposed extension of passenger rail service that would connect with the Metro North Railroad south and west of Danbury, Connecticut, and extend north through parts of Fairfield and Litchfield County, Connecticut and then onwards to Pittsfield, Massachusetts. The extension is expected to increase total economic output in this region providing Connecticut and Massachusetts state governments, and local governments in the region with nearly $29.5 million in additional tax revenues during the first decade of the project. During the first decade the region would generate an additional $55 million in Federal tax revenues (Shepard, 2010). Do Commuter Rail Systems that Support Job Commuting and Inter-‐Regional Housing have Agglomeration Economic Effect on the Regions? o o o o Over the past few decades, employers have followed residents to the suburbs as the share of jobs in central cities has declined. In fact, most workers now live in one suburb and work in another, rather than commute back to central city (Terplan, et al. 2009). The Housatonic Railroad regional extension described above could increase total economic output in the region. The increase during the first decade of the project would total an excess of $625 million dollars in additional goods and services produced and sold in the region (Shepard, 2010). In 2014, statistics were used to quantify agglomeration based on the relationship between transit expansion, labor market accessibility and economic growth. Data for this meta-‐ analysis came from 300 US metropolitan areas. It was found that adding about 4 seats to rails and buses per 1,000 residents produced 320 more employees per square mile in the central city—an increase of 19%. Adding 85 rail miles delivered a 7% increase. A 10% expansion in transit service (additional seats or rail miles) produced a wage increase of between $53 and $194 per worker per year in the city center. This produced an estimated total wage increase ranging between $1.5 million and $1.8 billion per metropolitan area. The gross metropolitan product rose between 1 and 2 percent. Firms and households likely received unanticipated agglomeration benefits from transit-‐induced densification and growth. On average, across all the metro areas in the study, expanding transit service produced an economic benefit via agglomeration of roughly $45 million a year — with that figure ranging between $1.5 million and $1.8 billion based on the size of the city. Big cities stand to benefit more simply because they have more people sharing the transit infrastructure. They also tend to have more of the traffic that cripples agglomeration in the absence of transit (Chatman, and Nolan 2014). A study of the potential economic impact of the New Haven-‐Hartford-‐Springfield commuter rail line was conducted. The total capital investment was estimated to be about $206 million, or $52 million per year for four years. Over the four years of various construction activities, the public investment could be expected to result in 529 jobs paying an average annual wage of $55,000 and 97 jobs in the rest of Massachusetts and Connecticut combined. The investment could stimulate an estimated increase of $50 million in economic output per year in the Expanded Knowledge Corridor with increases above $7 million each in TSI, OCTOBER 2014, REGIONAL ECONOMIC IMPACT OF ACE RAIL EXPANSION 51 o o o o Massachusetts and Connecticut. The capital expenditures were expected to produce $5 million per year in additional income tax revenues across the three regions. The operation of the commuter rail would result in the creation of about 249 jobs with an average wage of $34,000 in the Expanded Knowledge Corridor, with about 35 additional jobs in the other two regions combined. Service operations were predicted to increase regional economic output by almost $15 million per year and regional income tax revenues by about $1.2 million per year. The necessary capital costs and the operating expenditures for the first 10 years of operation total $306 million compared with a total increase of $458 million in economic output. Thus an additional $152 million in economic activity could be created. The public investment could result in more than 600 new jobs during construction activities and more than 250 permanent new jobs from operating expenditures. Using 1994 and 1993 studies of the increase in single-‐family residence value located in a community with a rail station and applying this premiums to residences within a half mile of proposed NHHS stations it was found that implementation of the commuter rail will likely increase the value of existing residential property by between $437 million and $490 million (Foster, 2006). Transit to existing industry clusters in the Minneapolis–St. Paul (MSP) metropolitan region has significant industry sector-‐to-‐sector differences. These differences highlight both the poor level of transit access to some economic sectors and the need for automobile ownership to reliably access jobs. Using scenario analysis, the authors found that a strategy focusing growth along transit-‐ways, particularly the growth of jobs along transit-‐way corridors, will achieve the best regional transit accessibility gains (Tilahun and Fan 2014). A direct demand model for transit-‐oriented development (TOD) in the Sacramento region found that sprawl, TOD-‐Light, TOD-‐Heavy, and travel to downtown scenarios would increase daily linked trips by 9%, 50%, 69% and 203%, respectively. However, none of the alternatives would reduce automobile use by much. Model outcomes indicate that job-‐ development patterns make a difference for transit ridership and residential patterns are less important. Also, whereas being close to suburban jobs will increase transit patronage, the managers of suburban retail and suburban centers still will look to the automobile for most of their customers (Thompson and Audirac 2000). The relationship between jobs-‐housing balance and vehicle miles traveled (VMT) is mixed. Some studies find no statistically significant relationship between jobs-‐housing balance measures. The studies that found a relationship between jobs-‐housing ratios and VMT typically found effects in the same range whether attention was focused on commute VMT or all VMT, and whether the jobs-‐housing balance ratio was adjusted for skill match or not. The evidence from the most recent studies the impact of jobs-‐housing balance is statistically significant with a 0.29 to 0.35 percent reduction in VMT for a 1 percent improvement in jobs-‐housing balance (Boarnet, et al., 2011). Looking across the 200-‐plus transit stations that opened in California from 1992 to 2006, we find that these new stations were located in areas with high residential density and very high employment density. Yet the opening of new stations was not accompanied by an increase in average employment growth in the areas immediately surrounding these stations (relative to comparison areas), either when the stations opened or several years afterward. Employment around new stations varied widely: employment growth increased near 18 new stations and decreased near 20, relative to comparison areas, with the largest increases in areas that had higher residential and employment density prior to the station opening. For the rest of the stations, the difference between employment growth around TSI, OCTOBER 2014, REGIONAL ECONOMIC IMPACT OF ACE RAIL EXPANSION 52 the station and in the comparison areas before and after the station opening was not statistically significant. In short, we find an absence of any boost to employment growth associated with the opening of new transit stations, on average. Employment growth increased most around stations located in higher-‐density areas. Existing zoning patterns and fiscal incentives, though favoring commercial over residential development, have not resulted in employment growth around new transit stations. Furthermore, most TOD policies discourage commercial development relative to residential development near transit. In California, residential density is higher than the national average and rising, but employment density is lower than the national average and falling (Kolko, 2011). Supplemental Abstracts of Commuter Rail Economic Effect Studies • Abstracts of research compiled by Juliette Michaelson, Juliette (2010). TSI, OCTOBER 2014, REGIONAL ECONOMIC IMPACT OF ACE RAIL EXPANSION 53 • Abstracts of research compiled by Qisheng Pan (2013). TSI, OCTOBER 2014, REGIONAL ECONOMIC IMPACT OF ACE RAIL EXPANSION 54
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