IDEAS home Printed from https://ideas.repec.org/a/taf/houspd/v27y2017i1p80-97.html

Seasonal Variation in Family Homeless Shelter Usage

Author

Listed:
  • Gregg Colburn

Abstract

Seasonal surges in family homeless shelter usage occur in numerous communities around the United States. These surges are significant because they may place demands on shelter systems, require families to use lower quality shelter facilities, or impose significant costs on the municipalities that provide shelter services. This study uses empirical data from Hennepin County, Minnesota, to provide explanations for the seasonality of family homeless shelter usage. The results suggest that multiple factors may contribute to the surge, but that families with school-age children are the primary driver of seasonal increases in the family shelter population. This study provides initial findings that may help to improve the targeting of homelessness prevention resources.

Suggested Citation

  • Gregg Colburn, 2017. "Seasonal Variation in Family Homeless Shelter Usage," Housing Policy Debate, Taylor & Francis Journals, vol. 27(1), pages 80-97, January.
    • Handle: RePEc:taf:houspd:v:27:y:2017:i:1:p:80-97
    DOI: 10.1080/10511482.2016.1158200
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/10511482.2016.1158200
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/10511482.2016.1158200?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. L. Rachel Ngai & Silvana Tenreyro, 2014. "Hot and Cold Seasons in the Housing Market," American Economic Review, American Economic Association, vol. 104(12), pages 3991-4026, December.
    2. L. Rachel Ngai & Silvana Tenreyro, 2009. "In brief: Hot and cold seasons in the housing market," CentrePiece - The magazine for economic performance 274, Centre for Economic Performance, LSE.
    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. Scott Greeves, 2023. "Tracking Trash: Understanding Patterns of Debris Pollution in Knoxville’s Urban Streams," Sustainability, MDPI, vol. 15(24), pages 1-13, December.

    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. Bracke, Philippe, 2013. "How long do housing cycles last? A duration analysis for 19 OECD countries," Journal of Housing Economics, Elsevier, vol. 22(3), pages 213-230.
    2. Chao He & Randall Wright & Yu Zhu, 2015. "Housing and Liquidity," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 18(3), pages 435-455, July.
    3. Masanori Kashiwagi, 2014. "Sunspots and Self-Fulfilling Beliefs in the U.S. Housing Market," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 17(4), pages 654-676, October.
    4. Boragan Aruoba & Morris Davis & Randall Wright, 2016. "Homework in Monetary Economics: Inflation, Home Production, and the Production of Homes," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 21, pages 105-124, July.
    5. Genesove, David & Han, Lu, 2012. "Search and matching in the housing market," Journal of Urban Economics, Elsevier, vol. 72(1), pages 31-45.
    6. Charles Ka Yui Leung & Joe Cho Yiu Ng, 2018. "Macro Aspects of Housing," GRU Working Paper Series GRU_2018_016, City University of Hong Kong, Department of Economics and Finance, Global Research Unit.
    7. Philippe Bracke & Silvana Tenreyro, 2021. "History Dependence in the Housing Market," American Economic Journal: Macroeconomics, American Economic Association, vol. 13(2), pages 420-443, April.
    8. Nicolas Bonneton & Christopher Sandmann, 2023. "Non-Stationary Search and Assortative Matching," CRC TR 224 Discussion Paper Series crctr224_2023_465v2, University of Bonn and University of Mannheim, Germany, revised Feb 2025.
    9. Stefan Seifert & Christoph Kahle & Silke Hüttel, 2021. "Price Dispersion in Farmland Markets: What Is the Role of Asymmetric Information?," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(4), pages 1545-1568, August.
    10. Philippe Bracke, 2013. "House Prices and Rents: Micro Evidence from a Matched Dataset in Central London_x0003_," ERSA conference papers ersa13p112, European Regional Science Association.
    11. repec:esx:essedp:717 is not listed on IDEAS
    12. Nicolas Bonneton & Christopher Sandmann, 2025. "Non‐Stationary Search and Assortative Matching," Econometrica, Econometric Society, vol. 93(5), pages 1635-1662, September.
    13. Conefrey, Thomas & Whelan, Karl, 2012. "Supply, Demand and Prices in the US Housing Market," Research Technical Papers 08/RT/12, Central Bank of Ireland.
    14. repec:bof:bofrdp:urn:nbn:fi:bof-201510061415 is not listed on IDEAS
    15. Gaetano Lisi, 2013. "Can the Mortensen-Pissarides Model Match the Housing Market Facts?," Journal of Economics and Econometrics, Economics and Econometrics Society, vol. 56(2), pages 78-92.
    16. Bielecki, Marcin & Stähler, Nikolai, 2022. "Labor Tax Reductions In Europe: The Role Of Property Taxation," Macroeconomic Dynamics, Cambridge University Press, vol. 26(2), pages 419-451, March.
    17. Halket, Jonathan R & Pignatti, Matteo, 2012. "Housing tenure choices with private information," Economics Discussion Papers 8961, University of Essex, Department of Economics.
    18. Soosung Hwang & Youngha Cho & Jinho Shin, 2017. "Does illiquidity matter in residential properties?," Applied Economics, Taylor & Francis Journals, vol. 49(1), pages 1-20, January.
    19. Hodula, Martin & Pfeifer, Lukáš & Ngo, Ngoc Anh, 2025. "Easing of borrower-based measures: Evidence from Czech loan-level data," Journal of Banking & Finance, Elsevier, vol. 178(C).
    20. Òscar Jordà & Moritz Schularick & Alan M. Taylor, 2019. "The Total Risk Premium Puzzle," NBER Working Papers 25653, National Bureau of Economic Research, Inc.
    21. Halket, Jonathan & Pignatti Morano di Custoza, Matteo, 2015. "Homeownership and the scarcity of rentals," Journal of Monetary Economics, Elsevier, vol. 76(C), pages 107-123.
    22. Gabrovski, Miroslav & Ortego-Marti, Victor, 2019. "The cyclical behavior of the Beveridge Curve in the housing market," Journal of Economic Theory, Elsevier, vol. 181(C), pages 361-381.

    More about this item

    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:taf:houspd:v:27:y:2017:i:1:p:80-97. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/RHPD20 .

    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.