Randomized Experiments in Continuous Time: A LATE for Continuous-Time Program Evaluations

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We develop a general framework for estimating causal effects in continuous time using randomized experiments. We consider a setting where individuals have outcomes, treatments, and instruments that vary over time. We define the potential outcomes and the causal effects in continuous time, and we specify the assumptions for identifying the local average treatment effect (LATE) using an instrument. We show that the LATE in continuous time can be identified as a difference of ratios of conditional expectations.
We introduce relevant identification and estimation results. We present extensions of the approach for heterogeneous treatment effects, multiple treatments or instruments, as well as nonparametric or semiparametric models. Our framework allows researchers and policymakers to design and evaluate interventions that vary over time in complex settings.

Opoku-Agyemang, Kweku (2023). "Randomized Experiments in Continuous Time: A LATE for Continuous-Time Program Evaluations." Development Economics X Paper Model Twenty-Two. 

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