Testing identification conditions of LATE in fuzzy regression discontinuity designs

A-Tier
Journal: Journal of Econometrics
Year: 2024
Volume: 241
Issue: 1

Authors (3)

Hsu, Yu-Chin (Academia Sinica) Shiu, Ji-Liang (not in RePEc) Wan, Yuanyuan (not in RePEc)

Score contribution per author:

1.341 = (α=2.01 / 3 authors) × 2.0x A-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

This paper derives testable implications of the identifying conditions for the local average treatment effect in fuzzy regression discontinuity designs. We show that the testable implications of these identifying conditions are a finite number of inequality restrictions on the observed data distribution. We then propose a specification test for the testable implications and show that the proposed test controls the size and is asymptotically consistent. We apply our test to several fuzzy regression discontinuity designs in the literature.

Technical Details

RePEc Handle
repec:eee:econom:v:241:y:2024:i:1:s0304407624000848
Journal Field
Econometrics
Author Count
3
Added to Database
2026-02-02