Estimation and Inference in Boundary Discontinuity Designs: Distance-Based Methods

Matias Cattaneo, Rocio Titiunik, Ruiqi and Yu
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Rocio Titiunik: Rae
Ruiqi: Rae

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Abstract: We study the statistical properties of nonparametric distance-based (isotropic) local polynomial regression estimators of the boundary average treatment effect curve, a key causal functional parameter capturing heterogeneous treatment effects in boundary discontinuity designs. We present necessary and/or sufficient conditions for identification, estimation, and inference in large samples, both pointwise and uniformly along the boundary. Our theoretical results highlight the crucial role played by the ``regularity'' of the boundary (a one-dimensional manifold) over which identification, estimation, and inference are conducted. Our methods are illustrated with simulated data. Companion general-purpose software is provided.

Date: 2025-10
New Economics Papers: this item is included in nep-ecm and nep-inv
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