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

Author

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  • Matias D. Cattaneo
  • Rocio Titiunik
  • Ruiqi Rae Yu

Abstract

Boundary discontinuity designs are used to learn about causal treatment effects along a continuous assignment boundary that splits units into control and treatment groups according to a bivariate location score. We analyze the statistical properties of local polynomial treatment effect estimators employing location information for each unit. We develop pointwise and uniform estimation and inference methods for both the conditional treatment effect function at the assignment boundary as well as for transformations thereof, which aggregate information along the boundary. We illustrate our methods with an empirical application. Companion general-purpose software is provided.

Suggested Citation

  • Matias D. Cattaneo & Rocio Titiunik & Ruiqi Rae Yu, 2025. "Estimation and Inference in Boundary Discontinuity Designs: Location-Based Methods," Papers 2505.05670, arXiv.org, revised Oct 2025.
    • Handle: RePEc:arx:papers:2505.05670
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    Cited by:

    1. Philipp Alexander Schwarz & Oliver Schacht & Sven Klaassen & Johannes Oberpriller & Martin Spindler, 2025. "Effect Identification and Unit Categorization in the Multi-Score Regression Discontinuity Design with Application to LED Manufacturing," Papers 2508.15692, arXiv.org, revised Oct 2025.
    2. Li, Zikai, 2025. "Unrequited Love: Estimating the Electoral Effect of a Place-based Green Subsidy with a 2D Regression Discontinuity Design," SocArXiv s4nje_v1, Center for Open Science.

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