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

Luke G. Fitzpatrick and Christopher F. Parmeter


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.


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