Regime and Treatment Effects in Duration Models: Decomposing Expectation and Transplant Effects on the Kidney Waitlist

TL;DR

This paper introduces a causal decomposition framework to analyze how initial regimes and treatments influence duration outcomes, applied to kidney transplant waitlist survival, revealing behavioral effects linked to blood type.

Contribution

It develops a dynamic potential outcomes framework and assumptions to decompose effects of regimes and treatments on duration outcomes, with a novel application to kidney transplant data.

Findings

AB blood type candidates have higher pre-transplant mortality

Behavioral factors, not biological differences, drive this mortality difference

Framework enables separating effects for different population groups

Abstract

This paper proposes a causal decomposition framework for settings in which an initial regime randomization influences the timing of a treatment duration. The initial randomization and treatment affect in turn a duration outcome of interest. Our empirical application considers the survival of individuals on the kidney transplant waitlist. Upon entering the waitlist, individuals with an AB blood type, who are universal recipients, are effectively randomized to a regime with a higher propensity to rapidly receive a kidney transplant. Our dynamic potential outcomes framework allows us to identify the pre-transplant effect of the blood type, and the transplant effects depending on blood type. We further develop dynamic assumptions which build on the LATE framework and allow researchers to separate effects for different population substrata. Our main empirical result is that AB blood type candidates display a higher pre-transplant mortality. We provide evidence that this effect is due to behavioural changes rather than biological differences.