IDEAS home Printed from https://ideas.repec.org/p/cep/ceedps/0132.html
   My bibliography  Save this paper

Valuing School Quality Using Boundary Discontinuities

Author

Listed:
  • Stephen Gibbons
  • Stephen Machin
  • Olmo Silva

Abstract

Existing research shows that house prices respond to local school quality as measured by average test scores. However, higher test scores could signal better quality teaching and academic value-added, or higher ability, sought-after intakes. In our research, we show decisively that value-added drives households' demand for good schooling. However, prior achievement - linked to the background of children in school - also matters. In order to identify these effects, we improve the boundary discontinuity regression methodology by matching identical properties across admissions authority boundaries; by allowing for boundary effects and spatial trends; by re-weighting our data towards transactions that are closest to district boundaries; by eliminating boundaries that coincide with major geographical features; and by submitting our estimates to a number of novel falsification tests. Our results survive this battery of experiments and show that a one-standard deviation change in either school average value-added or prior achievement raises prices by around 3%.

Suggested Citation

  • Stephen Gibbons & Stephen Machin & Olmo Silva, 2012. "Valuing School Quality Using Boundary Discontinuities," CEE Discussion Papers 0132, Centre for the Economics of Education, LSE.
  • Handle: RePEc:cep:ceedps:0132
    as

    Download full text from publisher

    File URL: http://cee.lse.ac.uk/ceedps/ceedp132.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. David Card & Martin D. Dooley & A. Abigail Payne, 2010. "School Competition and Efficiency with Publicly Funded Catholic Schools," American Economic Journal: Applied Economics, American Economic Association, vol. 2(4), pages 150-176, October.
    2. David Brasington & Donald R. Haurin, 2006. "Educational Outcomes and House Values: A Test of the value added Approach," Journal of Regional Science, Wiley Blackwell, vol. 46(2), pages 245-268, May.
    3. Gilles Duranton & Laurent Gobillon & Henry G. Overman, 2011. "Assessing the Effects of Local Taxation using Microgeographic Data," Economic Journal, Royal Economic Society, vol. 121(555), pages 1017-1046, September.
    4. Clapp, John M. & Nanda, Anupam & Ross, Stephen L., 2008. "Which school attributes matter? The influence of school district performance and demographic composition on property values," Journal of Urban Economics, Elsevier, vol. 63(2), pages 451-466, March.
    5. Patrick Bayer & Fernando Ferreira & Robert McMillan, 2007. "A Unified Framework for Measuring Preferences for Schools and Neighborhoods," Journal of Political Economy, University of Chicago Press, vol. 115(4), pages 588-638, August.
    6. Fack, Gabrielle & Grenet, Julien, 2010. "When do better schools raise housing prices? Evidence from Paris public and private schools," Journal of Public Economics, Elsevier, vol. 94(1-2), pages 59-77, February.
    7. Downes, Thomas A. & Zabel, Jeffrey E., 2002. "The impact of school characteristics on house prices: Chicago 1987-1991," Journal of Urban Economics, Elsevier, vol. 52(1), pages 1-25, July.
    8. Ian Davidoff & Andrew Leigh, 2008. "How Much do Public Schools Really Cost? Estimating the Relationship between House Prices and School Quality," The Economic Record, The Economic Society of Australia, vol. 84(265), pages 193-206, June.
    9. Stephanie Riegg Cellini & Fernando Ferreira & Jesse Rothstein, 2008. "The Value of School Facilities: Evidence from a Dynamic Regression Discontinuity Design," Working Papers 1104, Princeton University, School of Public and International Affairs, Education Research Section..
    10. Dennis N. Epple & Richard Romano, 2003. "Neighborhood Schools, Choice, and the Distribution of Educational Benefits," NBER Chapters, in: The Economics of School Choice, pages 227-286, National Bureau of Economic Research, Inc.
    11. Cushing, Brian J., 1984. "Capitalization of interjurisdictional fiscal differentials: An alternative approach," Journal of Urban Economics, Elsevier, vol. 15(3), pages 317-326, May.
    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. Stephen Gibbons & Susana Mourato & Guilherme Resende, 2014. "The Amenity Value of English Nature: A Hedonic Price Approach," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 57(2), pages 175-196, February.
    2. Masi, Barbara, 2018. "A ticket to ride: The unintended consequences of school transport subsidies," Economics of Education Review, Elsevier, vol. 63(C), pages 100-115.

    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. Gibbons, Stephen & Machin, Stephen & Silva, Olmo, 2013. "Valuing school quality using boundary discontinuities," Journal of Urban Economics, Elsevier, vol. 75(C), pages 15-28.
    2. Stephen Machin, 2011. "Houses and Schools: Valuation of School Quality through then Housing Market - EALE 2010 Presidential Address," CEP Occasional Papers 29, Centre for Economic Performance, LSE.
    3. Christian A. L. Hilber, 2017. "The Economic Implications of House Price Capitalization: A Synthesis," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 45(2), pages 301-339, April.
    4. Machin, Stephen, 2011. "Houses and schools: Valuation of school quality through the housing market," Labour Economics, Elsevier, vol. 18(6), pages 723-729.
    5. Oskari Harjunen & Mika Kortelainen & Tuukka Saarimaa, 2018. "Best Education Money Can Buy? Capitalization of School Quality in Finland," CESifo Economic Studies, CESifo, vol. 64(2), pages 150-175.
    6. Alexander W. Marré & Anil Rupasingha, 2020. "School quality and rural in‐migration: Can better rural schools attract new residents?," Journal of Regional Science, Wiley Blackwell, vol. 60(1), pages 156-173, January.
    7. Nguyen-Hoang, Phuong & Yinger, John, 2011. "The capitalization of school quality into house values: A review," Journal of Housing Economics, Elsevier, vol. 20(1), pages 30-48, March.
    8. Gibbons, Stephen & Machin, Stephen & Silva, Olmo, 2013. "Valuing school quality using boundary discontinuity," LSE Research Online Documents on Economics 45246, London School of Economics and Political Science, LSE Library.
    9. Ozhegov, Evgeniy & Kosolapov, Nikita & Pozolotina, Iuliia, 2017. "On dependence between housing value and school characteristics," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 47, pages 28-48.
    10. Fack, Gabrielle & Grenet, Julien, 2010. "When do better schools raise housing prices? Evidence from Paris public and private schools," Journal of Public Economics, Elsevier, vol. 94(1-2), pages 59-77, February.
    11. Imberman, Scott A. & Lovenheim, Michael F., 2016. "Does the market value value-added? Evidence from housing prices after a public release of school and teacher value-added," Journal of Urban Economics, Elsevier, vol. 91(C), pages 104-121.
    12. Chung, Il Hwan, 2015. "School choice, housing prices, and residential sorting: Empirical evidence from inter-and intra-district choice," Regional Science and Urban Economics, Elsevier, vol. 52(C), pages 39-49.
    13. Dhar, Paramita & Ross, Stephen L, 2012. "School district quality and property values: Examining differences along school district boundaries," Journal of Urban Economics, Elsevier, vol. 71(1), pages 18-25.
    14. Agarwal, Sumit & Rengarajan, Satyanarain & Sing, Tien Foo & Yang, Yang, 2016. "School allocation rules and housing prices: A quasi-experiment with school relocation events in Singapore," Regional Science and Urban Economics, Elsevier, vol. 58(C), pages 42-56.
    15. Depro, Brooks & Rouse, Kathryn, 2015. "The effect of multi-track year-round academic calendars on property values: Evidence from district imposed school calendar conversions," Economics of Education Review, Elsevier, vol. 49(C), pages 157-171.
    16. Hilber, Christian A. L., 2011. "The economics implications of house price capitalization a survey of an emerging literature," LSE Research Online Documents on Economics 58596, London School of Economics and Political Science, LSE Library.
    17. Xiaozhou Ding & Christopher Bollinger & Michael Clark & William H. Hoyt, 2020. "How Do School District Boundary Changes and New School Proposals Affect Housing Prices," CESifo Working Paper Series 8069, CESifo.
    18. Rajapaksa, Darshana & Gono, Marcel & Wilson, Clevo & Managi, Shunsuke & Lee, Boon & Hoang, Viet-Ngu, 2020. "The demand for education: The impacts of good schools on property values in Brisbane, Australia," Land Use Policy, Elsevier, vol. 97(C).
    19. Thompson, Paul N., 2016. "School district and housing price responses to fiscal stress labels: Evidence from Ohio," Journal of Urban Economics, Elsevier, vol. 94(C), pages 54-72.
    20. Constant I. Tra & Anna Lukemeyer & Helen Neill, 2013. "Evaluating The Welfare Effects Of School Quality Improvements: A Residential Sorting Approach," Journal of Regional Science, Wiley Blackwell, vol. 53(4), pages 607-630, October.

    More about this item

    Keywords

    House prices; school quality; boundary discontinuities;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • I20 - Health, Education, and Welfare - - Education - - - General
    • H75 - Public Economics - - State and Local Government; Intergovernmental Relations - - - State and Local Government: Health, Education, and Welfare
    • R21 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Housing Demand

    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:cep:ceedps:0132. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (). General contact details of provider: http://cee.lse.ac.uk/publications.htm .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.