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Valuing School Quality Using Boundary Discontinuities

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  • 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
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    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

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