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• 1. [Article] How Does Transportation Affordability Vary Among TODs, TADs, and Other Areas?

  Transit-oriented development (TOD) has gained popularity worldwide as a sustainable form of urbanism; it concentrates development near a transit station so as to reduce auto-dependency and increase ridership. ...

  Citation × Citation Citation Abstract Copy Title: How Does Transportation Affordability Vary Among TODs, TADs, and Other Areas? Author: Scheer, Brenda, Ewing, Reid, Park, Keunhyun, Khan, Shabnam Sifat Ara Year: 2017 Transit-oriented development (TOD) has gained popularity worldwide as a sustainable form of urbanism; it concentrates development near a transit station so as to reduce auto-dependency and increase ridership. Existing travel behavior studies in the context of TOD, however, are limited in terms of small sample size, inconsistent TOD classification methods, and failure to control for residential self-selection. Thus, this study has three research questions. First, how can we distinguish between Transit-oriented development (TOD) and Transit-adjacent development (TAD)? Second, how do travel behaviors vary between TODs and TADs? Third, how does transportation affordability vary between TODs and TADs? This study utilizes cluster analysis to classify station area types and propensity score matching to control residential self-selection. From cluster analysis with built-environment factors—density, diversity, and walkability—in a half-mile buffer, this study classifies existing station areas as TOD, TAD or Hybrid types. After controlling for residential self-selection, it shows that a TOD motivates its residents to walk more and take transit more while using personal vehicles less. The significant difference between TOD and TAD in both VMT and the number of auto trips demonstrates that TODs make the personal vehicle trips shorter and fewer. Travel behavior in the Hybrid type demonstrates the possibility of gradual and practical change. Finally, the percentage of household income spent on transportation is lower in TOD households than TAD households. This shows that a TOD household is likely to save enough money on vehicle ownership and use that, while it likely spends more on transit, the final result is a significantly lower financial burden from transportation. Title: How Does Transportation Affordability Vary Among TODs, TADs, and Other Areas? Author: Scheer, Brenda, Ewing, Reid, Park, Keunhyun, Khan, Shabnam Sifat Ara Year: 2017 Transit-oriented development (TOD) has gained popularity worldwide as a sustainable form of urbanism; it concentrates development near a transit station so as to reduce auto-dependency and increase ridership. Existing travel behavior studies in the context of TOD, however, are limited in terms of small sample size, inconsistent TOD classification methods, and failure to control for residential self-selection. Thus, this study has three research questions. First, how can we distinguish between Transit-oriented development (TOD) and Transit-adjacent development (TAD)? Second, how do travel behaviors vary between TODs and TADs? Third, how does transportation affordability vary between TODs and TADs? This study utilizes cluster analysis to classify station area types and propensity score matching to control residential self-selection. From cluster analysis with built-environment factors—density, diversity, and walkability—in a half-mile buffer, this study classifies existing station areas as TOD, TAD or Hybrid types. After controlling for residential self-selection, it shows that a TOD motivates its residents to walk more and take transit more while using personal vehicles less. The significant difference between TOD and TAD in both VMT and the number of auto trips demonstrates that TODs make the personal vehicle trips shorter and fewer. Travel behavior in the Hybrid type demonstrates the possibility of gradual and practical change. Finally, the percentage of household income spent on transportation is lower in TOD households than TAD households. This shows that a TOD household is likely to save enough money on vehicle ownership and use that, while it likely spends more on transit, the final result is a significantly lower financial burden from transportation. Close

• 2. [Article] When Cities Shrink, Affordability Does Too

  To better understand the real costs of housing and transportation in a declining urban context, NITC researchers implemented a household survey to determine whether the assumptions made in existing research ...

  Citation × Citation Citation Abstract Copy Title: When Cities Shrink, Affordability Does Too Author: Ganning, Joanna, Tighe, Jenna Rosie Year: 2017 To better understand the real costs of housing and transportation in a declining urban context, NITC researchers implemented a household survey to determine whether the assumptions made in existing research literature and in the LAI regarding household expenditures and transportation accessibility hold true when analyzing shrinking cities—generally, cities characterized by a long-term loss in occupied housing units. The project was led by Joanna Ganning of Cleveland State University, who has conducted previous research into shrinking cities with the support of the NITC program. Title: When Cities Shrink, Affordability Does Too Author: Ganning, Joanna, Tighe, Jenna Rosie Year: 2017 To better understand the real costs of housing and transportation in a declining urban context, NITC researchers implemented a household survey to determine whether the assumptions made in existing research literature and in the LAI regarding household expenditures and transportation accessibility hold true when analyzing shrinking cities—generally, cities characterized by a long-term loss in occupied housing units. The project was led by Joanna Ganning of Cleveland State University, who has conducted previous research into shrinking cities with the support of the NITC program. Close

• 3. [Article] What Do We Know About Location Affordability in U.S. Shrinking Cities?

  In late 2013, the Department of Housing and Urban Development (HUD) launched the Location Affordability Index (LAI) portal. Their dataset uses models to estimate typical amount households spend on housing ...

  Citation × Citation Citation Abstract Copy Title: What Do We Know About Location Affordability in U.S. Shrinking Cities? Author: Ganning, Joanna, Tighe, Jenna Rosie Year: 2017 In late 2013, the Department of Housing and Urban Development (HUD) launched the Location Affordability Index (LAI) portal. Their dataset uses models to estimate typical amount households spend on housing and transportation at the block group level, and calculates “H + T Affordability,” the percent of household income spent on these items. In our previous research, we analyzed 81 shrinking cities to determine how location affordability differs across various neighborhoods. Our results suggest that households in declining neighborhoods, as compared to stable or redeveloping neighborhoods, face the greatest H + T affordability challenges in shrinking cities. Furthermore, in declining neighborhoods, virtually all of the additional affordability challenges encountered can be accounted for by differences in transportation affordability rather than housing. Since there is virtually no research to either validate or suggest bias in the LAI data, and a declining neighborhood in a shrinking city presents both a relatively common yet entirely dissimilar context to the norm, we feel that this data should be carefully calibrated to, and tested for, this setting to ensure that appropriate and efficient policy follow. In this report, we present the results of two research phases: a strictly quantitative first stage in which the LAI is disassembled and reassembled, taking stock of assumptions, methods, and accuracy. This work finds that the LAI generally over-estimates housing costs, but more for renters and more in metropolitan areas. Estimations of transportation cost burdens are built largely from unreliable data and using models which cannot be replicated, leading us to conclude that these cost burden estimates may not be reliable. In the second research phase, which is survey-based, we gather household-level data from 12 Census tracts in Cleveland, Ohio, to estimate household housing and transportation costs and cost burdens and gain a clearer sense of budget trade-offs where costs are unaffordable. The survey results support the first research stage. The LAI over-estimates housing costs for these neighborhoods by approximately 17% and transportation costs by approximately 126%, meaning the LAI estimates for transportation are not reliable. By and large, households trade essentials, investing, and paying bills (at all or in full) to cover their costs in housing and transportation. Title: What Do We Know About Location Affordability in U.S. Shrinking Cities? Author: Ganning, Joanna, Tighe, Jenna Rosie Year: 2017 In late 2013, the Department of Housing and Urban Development (HUD) launched the Location Affordability Index (LAI) portal. Their dataset uses models to estimate typical amount households spend on housing and transportation at the block group level, and calculates “H + T Affordability,” the percent of household income spent on these items. In our previous research, we analyzed 81 shrinking cities to determine how location affordability differs across various neighborhoods. Our results suggest that households in declining neighborhoods, as compared to stable or redeveloping neighborhoods, face the greatest H + T affordability challenges in shrinking cities. Furthermore, in declining neighborhoods, virtually all of the additional affordability challenges encountered can be accounted for by differences in transportation affordability rather than housing. Since there is virtually no research to either validate or suggest bias in the LAI data, and a declining neighborhood in a shrinking city presents both a relatively common yet entirely dissimilar context to the norm, we feel that this data should be carefully calibrated to, and tested for, this setting to ensure that appropriate and efficient policy follow. In this report, we present the results of two research phases: a strictly quantitative first stage in which the LAI is disassembled and reassembled, taking stock of assumptions, methods, and accuracy. This work finds that the LAI generally over-estimates housing costs, but more for renters and more in metropolitan areas. Estimations of transportation cost burdens are built largely from unreliable data and using models which cannot be replicated, leading us to conclude that these cost burden estimates may not be reliable. In the second research phase, which is survey-based, we gather household-level data from 12 Census tracts in Cleveland, Ohio, to estimate household housing and transportation costs and cost burdens and gain a clearer sense of budget trade-offs where costs are unaffordable. The survey results support the first research stage. The LAI over-estimates housing costs for these neighborhoods by approximately 17% and transportation costs by approximately 126%, meaning the LAI estimates for transportation are not reliable. By and large, households trade essentials, investing, and paying bills (at all or in full) to cover their costs in housing and transportation. Close

• 4. [Article] Do TODs Make a Difference?

  In this report, we present research that measures the outcomes of TOD areas in relation to their metropolitan area controls with respect to (1) jobs by sector; (2) housing choice for household types based ...

  Citation × Citation Citation Abstract Copy Title: Do TODs Make a Difference? Author: Nelson, Arthur C., Miller, Matt, Eskic, Dejan, Kim, Keuntae, Ewing, Reid, Liu, Jenny H., Berggren, Matt, Mumuni, Zakari Year: 2015 In this report, we present research that measures the outcomes of TOD areas in relation to their metropolitan area controls with respect to (1) jobs by sector; (2) housing choice for household types based on key demographic characteristics; (3) housing affordability based on transportation costs; and (4) job-worker balance as a measure of accessibility. Prior literature has not systematically evaluated TOD outcomes in these respects with respect to light rail transit (LRT), commuter rail transit (CRT), bus rapid transit (BRT), and streetcar transit (SCT) systems. Our analysis helps close some of these gaps. We apply our analysis to 23 fixed-guideway transit systems operating in 17 metropolitan areas in the South and West that have one or more of those systems. We find: (1) Most TOD areas gained jobs in the office, knowledge, education, health care and entertainment sectors, adding more than $100 billion in wages capitalized over time; (2) In assessing economic resilience associated with LRT systems, jobs continued to shift away from TOD areas before the Great Recession, the pace slowed during the recession but reversed during recovery, leading us to speculate that LRT TOD areas may have transformed metropolitan economies served by LRT systems; (3) Rents for offices, retail stores and apartments were higher when closer to SCT systems, had mixed results with respect LRT systems, but were mostly lower with respect to CRT systems (our BRT sample was too small to evaluate); (4) SCT systems performed best in terms of increasing their TOD-area shares of metropolitan population, households and householders by age, housing units, and renters with BRT systems performing less well while LRT and CRT systems experienced a much smaller shift in the share of growth; (5) Household transportation costs as a share of budgets increase with respect to distance from LRT transit stations to seven miles, suggesting the proximity to LRT stations reduces total household transportation costs; (6) Emerging trends that may favor higher-wage jobs locating in TOD areas over time than lower- or middle-wage jobs, perhaps because TOD areas attract more investment which requires more productive, higher-paid labor to justify the investment; and (7) The share of workers who commute 10 minutes or less to work increases nearly one-half of 1 percent for each half-mile their resident block group is to an LRT transit station, capping at a gain of 1.3 percent, which is not a trivial gain. Our report summarizes case studies of 23 transit systems and three journal articles based on our research. Title: Do TODs Make a Difference? Author: Nelson, Arthur C., Miller, Matt, Eskic, Dejan, Kim, Keuntae, Ewing, Reid, Liu, Jenny H., Berggren, Matt, Mumuni, Zakari Year: 2015 In this report, we present research that measures the outcomes of TOD areas in relation to their metropolitan area controls with respect to (1) jobs by sector; (2) housing choice for household types based on key demographic characteristics; (3) housing affordability based on transportation costs; and (4) job-worker balance as a measure of accessibility. Prior literature has not systematically evaluated TOD outcomes in these respects with respect to light rail transit (LRT), commuter rail transit (CRT), bus rapid transit (BRT), and streetcar transit (SCT) systems. Our analysis helps close some of these gaps. We apply our analysis to 23 fixed-guideway transit systems operating in 17 metropolitan areas in the South and West that have one or more of those systems. We find: (1) Most TOD areas gained jobs in the office, knowledge, education, health care and entertainment sectors, adding more than $100 billion in wages capitalized over time; (2) In assessing economic resilience associated with LRT systems, jobs continued to shift away from TOD areas before the Great Recession, the pace slowed during the recession but reversed during recovery, leading us to speculate that LRT TOD areas may have transformed metropolitan economies served by LRT systems; (3) Rents for offices, retail stores and apartments were higher when closer to SCT systems, had mixed results with respect LRT systems, but were mostly lower with respect to CRT systems (our BRT sample was too small to evaluate); (4) SCT systems performed best in terms of increasing their TOD-area shares of metropolitan population, households and householders by age, housing units, and renters with BRT systems performing less well while LRT and CRT systems experienced a much smaller shift in the share of growth; (5) Household transportation costs as a share of budgets increase with respect to distance from LRT transit stations to seven miles, suggesting the proximity to LRT stations reduces total household transportation costs; (6) Emerging trends that may favor higher-wage jobs locating in TOD areas over time than lower- or middle-wage jobs, perhaps because TOD areas attract more investment which requires more productive, higher-paid labor to justify the investment; and (7) The share of workers who commute 10 minutes or less to work increases nearly one-half of 1 percent for each half-mile their resident block group is to an LRT transit station, capping at a gain of 1.3 percent, which is not a trivial gain. Our report summarizes case studies of 23 transit systems and three journal articles based on our research. Close

• 5. [Article] National Study of BRT Development Outcomes

  Bus rapid transit (BRT) is poised to become the “next big thing” in public transit. From virtually no systems a generation ago, there are now 19 lines operating with at least seven under construction and ...

  Citation × Citation Citation Abstract Copy Title: National Study of BRT Development Outcomes Author: Nelson, Arthur C., Ganning, Joanna Year: 2015 Bus rapid transit (BRT) is poised to become the “next big thing” in public transit. From virtually no systems a generation ago, there are now 19 lines operating with at least seven under construction and more than 20 in the planning stages. BRT is gaining popularity because of its combination of low capital cost and potential for high levels of benefits. But are BRT systems effective in attracting development? To answer this and many more trending BRT questions, the Metropolitan Research Center (MRC) reviewed multiple studies using data from the United States Census Bureau, Longitudinal Employer-Household Dynamics, and CoStar data in a quasi-experimental, compare-and-contrast research design to compare jobs, population and households, and housing units before and after BRT station construction relative to control stations and the stations’ metropolitan context. Our units of analysis will be 2010 census blocks and their assemblages as data allow within 0.25 mile buffers. The final products of the MRC’s research include case studies of each BRT and meta-assessments of whether and to what extent BRT systems attract development. Some of the studies answer the following questions: What are the effects of BRT on sectoral employment change in the United States? How does BRT affect housing location affordability? What is the relationship between BRT and its surrounding area’s wagerelated job change? These answers can provide MPOs with information to aid in the decision-making process in terms of economic development and transportation planning options. Title: National Study of BRT Development Outcomes Author: Nelson, Arthur C., Ganning, Joanna Year: 2015 Bus rapid transit (BRT) is poised to become the “next big thing” in public transit. From virtually no systems a generation ago, there are now 19 lines operating with at least seven under construction and more than 20 in the planning stages. BRT is gaining popularity because of its combination of low capital cost and potential for high levels of benefits. But are BRT systems effective in attracting development? To answer this and many more trending BRT questions, the Metropolitan Research Center (MRC) reviewed multiple studies using data from the United States Census Bureau, Longitudinal Employer-Household Dynamics, and CoStar data in a quasi-experimental, compare-and-contrast research design to compare jobs, population and households, and housing units before and after BRT station construction relative to control stations and the stations’ metropolitan context. Our units of analysis will be 2010 census blocks and their assemblages as data allow within 0.25 mile buffers. The final products of the MRC’s research include case studies of each BRT and meta-assessments of whether and to what extent BRT systems attract development. Some of the studies answer the following questions: What are the effects of BRT on sectoral employment change in the United States? How does BRT affect housing location affordability? What is the relationship between BRT and its surrounding area’s wagerelated job change? These answers can provide MPOs with information to aid in the decision-making process in terms of economic development and transportation planning options. Close

• 6. [Article] Impact of Bike Facilities on Residential Property Prices

  As many cities are investing in street improvement or transportation infrastructure upgrade projects to provide better bike access or more complete bike networks, the economic value of bike infrastructure ...

  Citation × Citation Citation Abstract Copy Title: Impact of Bike Facilities on Residential Property Prices Author: Shi, Wei Year: 2017 As many cities are investing in street improvement or transportation infrastructure upgrade projects to provide better bike access or more complete bike networks, the economic value of bike infrastructure and bike facilities remains an area where many practitioners, planners and policy makers are seeking more conclusive evidence. Using residential property values as indicators of consumer preferences for bicycle infrastructure, this study focuses on advanced bike facilities which represent higher levels of bike priority or bike infrastructure investments that have been shown to be more desirable to a larger portion of the population. Estimating ordinary least squares hedonic pricing models and spatial autoregressive hedonic models separately for single and multi-family properties, we find that proximity to advanced bike facilities (measured by distance) has significant and positive effects on all residential property values, highlighting household preferences for high quality bike infrastructure. Furthermore, we also show that the extensiveness of the bike network (measured by density) is a positive and statistically significant contributor to the property prices for all residential property types, even after controlling for proximity to bike facilities and other property, neighborhood and transaction characteristics. Finally, estimated coefficients are applied to assess property value impacts of a proposed Portland “Green Loop” signature bike infrastructure concept, illustrating the importance of considering both accessibility and extensiveness of bike facility networks. Title: Impact of Bike Facilities on Residential Property Prices Author: Shi, Wei Year: 2017 As many cities are investing in street improvement or transportation infrastructure upgrade projects to provide better bike access or more complete bike networks, the economic value of bike infrastructure and bike facilities remains an area where many practitioners, planners and policy makers are seeking more conclusive evidence. Using residential property values as indicators of consumer preferences for bicycle infrastructure, this study focuses on advanced bike facilities which represent higher levels of bike priority or bike infrastructure investments that have been shown to be more desirable to a larger portion of the population. Estimating ordinary least squares hedonic pricing models and spatial autoregressive hedonic models separately for single and multi-family properties, we find that proximity to advanced bike facilities (measured by distance) has significant and positive effects on all residential property values, highlighting household preferences for high quality bike infrastructure. Furthermore, we also show that the extensiveness of the bike network (measured by density) is a positive and statistically significant contributor to the property prices for all residential property types, even after controlling for proximity to bike facilities and other property, neighborhood and transaction characteristics. Finally, estimated coefficients are applied to assess property value impacts of a proposed Portland “Green Loop” signature bike infrastructure concept, illustrating the importance of considering both accessibility and extensiveness of bike facility networks. Close