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Data-Driven Estimation of Treatment Buffers in Hedonic Analysis: An Examination of Surface Coal Mines

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  • Luke G. Fitzpatrick
  • Christopher F. Parmeter

Abstract

In hedonic studies of how environmental disamenities influence house prices, the homes that are treated are typically unknown. We propose a new method for defining treatment buffers and apply our technique to disamenities that have thus far received little attention: surface coal mines. Our leave-one-out cross-validation approach identifies an optimal buffer of 2,300 m in two Appalachian counties at which effects dissipate. Hedonic regressions indicate that treated homes sell for 15.5% less than untreated homes. We supplement these results with nearest-neighbor covariate matching models and recover average treatment effects on the treated of 14.7% price reductions.

Suggested Citation

  • Luke G. Fitzpatrick & Christopher F. Parmeter, 2021. "Data-Driven Estimation of Treatment Buffers in Hedonic Analysis: An Examination of Surface Coal Mines," Land Economics, University of Wisconsin Press, vol. 97(3), pages 528-547.
    • Handle: RePEc:uwp:landec:v:97:y:2021:i:3:p:528-547
    Note: DOI: 10.3368/wple.97.3.090119-0126R1
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    More about this item

    JEL classification:

    • Q32 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation - - - Exhaustible Resources and Economic Development
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

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