IDEAS home Printed from https://ideas.repec.org/p/fip/fedpwp/15-36.html
   My bibliography  Save this paper

Gentrification and residential mobility in Philadelphia

Author

Listed:
  • Lei Ding
  • Eileen Divringi
  • Jackelyn Hwang

Abstract

Gentrification has provoked considerable debate and controversy about its effects on neighborhoods and the people residing in them. This paper draws on a unique large-scale consumer credit database to examine the mobility patterns of residents in gentrifying neighborhoods in the city of Philadelphia from 2002 to 2014. We find significant heterogeneity in the effects of gentrification across neighborhoods and subpopulations. Residents in gentrifying neighborhoods have slightly higher mobility rates than those in nongentrifying neighborhoods, but they do not have a higher risk of moving to a lower-income neighborhood. Moreover, gentrification is associated with some positive changes in residents? financial health as measured by individuals? credit scores. However, when more vulnerable residents (low-score, longer-term residents, or residents without mortgages) move from gentrifying neighborhoods, they are more likely to move to lower-income neighborhoods and neighborhoods with lower values on quality-of-life indicators. The results reveal the nuances of mobility in gentrifying neighborhoods and demonstrate how the positive and negative consequences of gentrification are unevenly distributed.

Suggested Citation

  • Lei Ding & Eileen Divringi & Jackelyn Hwang, 2015. "Gentrification and residential mobility in Philadelphia," Working Papers 15-36, Federal Reserve Bank of Philadelphia.
  • Handle: RePEc:fip:fedpwp:15-36
    as

    Download full text from publisher

    File URL: https://www.philadelphiafed.org/-/media/frbp/assets/working-papers/2015/wp15-36r.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. McKinnish, Terra & Walsh, Randall & Kirk White, T., 2010. "Who gentrifies low-income neighborhoods?," Journal of Urban Economics, Elsevier, vol. 67(2), pages 180-193, March.
    2. Helms, Andrew C., 2003. "Understanding gentrification: an empirical analysis of the determinants of urban housing renovation," Journal of Urban Economics, Elsevier, vol. 54(3), pages 474-498, November.
    3. Ellen, Ingrid Gould & O'Regan, Katherine M., 2011. "How low income neighborhoods change: Entry, exit, and enhancement," Regional Science and Urban Economics, Elsevier, vol. 41(2), pages 89-97, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Michael E. Porter, 2016. "Inner-City Economic Development," Economic Development Quarterly, , vol. 30(2), pages 105-116, May.
    2. Joseph Gibbons & Atsushi Nara & Bruce Appleyard, 2018. "Exploring the imprint of social media networks on neighborhood community through the lens of gentrification," Environment and Planning B, , vol. 45(3), pages 470-488, May.
    3. H. Shellae Versey & Serene Murad & Paul Willems & Mubarak Sanni, 2019. "Beyond Housing: Perceptions of Indirect Displacement, Displacement Risk, and Aging Precarity as Challenges to Aging in Place in Gentrifying Cities," IJERPH, MDPI, vol. 16(23), pages 1-21, November.
    4. Winifred Curran, 2018. "‘Mexicans love red’ and other gentrification myths: Displacements and contestations in the gentrification of Pilsen, Chicago, USA," Urban Studies, Urban Studies Journal Limited, vol. 55(8), pages 1711-1728, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Edlund, Lena & Machado, Cecilia & Sviatschi, Maria, 2015. "Bright Minds, Big Rent: Gentrification and the Rising Returns to Skill," IZA Discussion Papers 9502, Institute of Labor Economics (IZA).
    2. Atuesta, Laura H. & Hewings, Geoffrey J.D., 2019. "Housing appreciation patterns in low-income neighborhoods: Exploring gentrification in Chicago," Journal of Housing Economics, Elsevier, vol. 44(C), pages 35-47.
    3. Edlund, Lena & Machado, Cecilia & Sviatschi, Maria, 2015. "Bright Minds, Big Rent: Gentrification and the Rising Returns to Skill," IZA Discussion Papers 9502, Institute of Labor Economics (IZA).
    4. Nilsson, Isabelle & Delmelle, Elizabeth, 2018. "Transit investments and neighborhood change: On the likelihood of change," Journal of Transport Geography, Elsevier, vol. 66(C), pages 167-179.
    5. Cody Hochstenbach & Wouter PC van Gent, 2015. "An anatomy of gentrification processes: variegating causes of neighbourhood change," Environment and Planning A, , vol. 47(7), pages 1480-1501, July.
    6. Davis, Jenna, 2021. "How do upzonings impact neighborhood demographic change? Examining the link between land use policy and gentrification in New York City," Land Use Policy, Elsevier, vol. 103(C).
    7. Munneke, Henry J. & Womack, Kiplan S., 2015. "Neighborhood renewal: The decision to renovate or tear down," Regional Science and Urban Economics, Elsevier, vol. 54(C), pages 99-115.
    8. Meltzer, Rachel & Ghorbani, Pooya, 2017. "Does gentrification increase employment opportunities in low-income neighborhoods?," Regional Science and Urban Economics, Elsevier, vol. 66(C), pages 52-73.
    9. Elizabeth Delmelle & Isabelle Nilsson, 2020. "New rail transit stations and the out-migration of low-income residents," Urban Studies, Urban Studies Journal Limited, vol. 57(1), pages 134-151, January.
    10. Tim Winke, 2021. "Housing affordability sets us apart: The effect of rising housing prices on relocation behaviour," Urban Studies, Urban Studies Journal Limited, vol. 58(12), pages 2389-2404, September.
    11. Jeremy Auerbach & Christopher Blackburn & Hayley Barton & Amanda Meng & Ellen Zegura, 2020. "Coupling data science with community crowdsourcing for urban renewal policy analysis: An evaluation of Atlanta’s Anti-Displacement Tax Fund," Environment and Planning B, , vol. 47(6), pages 1081-1097, July.
    12. Dragan, Kacie & Ellen, Ingrid Gould & Glied, Sherry, 2020. "Does gentrification displace poor children and their families? New evidence from medicaid data in New York City," Regional Science and Urban Economics, Elsevier, vol. 83(C).
    13. Berrebi, Simon J. & Watkins, Kari E., 2020. "Who’s ditching the bus?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 136(C), pages 21-34.
    14. Lance Freeman & Adele Cassola & Tiancheng Cai, 2016. "Displacement and gentrification in England and Wales: A quasi-experimental approach," Urban Studies, Urban Studies Journal Limited, vol. 53(13), pages 2797-2814, October.
    15. Devajyoti Deka, 2017. "Benchmarking gentrification near commuter rail stations in New Jersey," Urban Studies, Urban Studies Journal Limited, vol. 54(13), pages 2955-2972, October.
    16. Ingrid Gould Ellen & Keren Mertens Horn & Katherine M. O’Regan, 2013. "Why Do Higher-income Households Choose Low-income Neighbourhoods? Pioneering or Thrift?," Urban Studies, Urban Studies Journal Limited, vol. 50(12), pages 2478-2495, September.
    17. Lei Ding & Jackelyn Hwang, 2016. "The Consequences of Gentrification: A Focus on Residents’ Financial Health in Philadelphia," Working Papers 16-22, Federal Reserve Bank of Philadelphia.
    18. Zawadi Rucks-Ahidiana, 2021. "Racial composition and trajectories of gentrification in the United States," Urban Studies, Urban Studies Journal Limited, vol. 58(13), pages 2721-2741, October.
    19. Waights, Sevrin, 2018. "Does gentrification displace poor households? An ‘identification-via-interaction’ approach," LSE Research Online Documents on Economics 88691, London School of Economics and Political Science, LSE Library.
    20. Christopher Rick & Jeehee Han & Spencer Shanholtz & Amy Ellen Schwartz, 2022. "Examining the Link Between Gentrification, Children’s Egocentric Food Environment, and Obesity," Center for Policy Research Working Papers 245, Center for Policy Research, Maxwell School, Syracuse University.

    More about this item

    Keywords

    Gentrification; Residential mobility; Credit scores; Displacement;
    All these keywords.

    JEL classification:

    • D14 - Microeconomics - - Household Behavior - - - Household Saving; Personal Finance
    • J11 - Labor and Demographic Economics - - Demographic Economics - - - Demographic Trends, Macroeconomic Effects, and Forecasts
    • J6 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers
    • R23 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Regional Migration; Regional Labor Markets; Population

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:fip:fedpwp:15-36. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Beth Paul (email available below). General contact details of provider: https://edirc.repec.org/data/frbphus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.