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Nonparametric identification and estimation of dynamic treatment effects for survival data in a regression discontinuity design

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Treatment assignment in the survival literature is often assumed to be allocated simultaneously and independently of prospective treatment gains. This paper relaxes these restrictions by introducing dynamic treatment assignment for… Click to show full abstract

Treatment assignment in the survival literature is often assumed to be allocated simultaneously and independently of prospective treatment gains. This paper relaxes these restrictions by introducing dynamic treatment assignment for survival data in a regression discontinuity design. Conditional on a pretreatment duration, we identify two survival functions of the remaining potential durations under treatment and no treatment. Conditional treatment effects can be identified by the difference between the integrals of the two functions, and we aggregate conditional treatment effects over pretreatment durations to identify unconditional ones. Accordingly, nonparametric estimates are proposed.

Keywords: dynamic treatment; treatment; data regression; survival data; regression discontinuity; treatment effects

Journal Title: Economics Letters
Year Published: 2019

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