Factor-augmented Bayesian treatment effects models for panel outcomes

2021/03/01 by Helga Wagner, Wagner, Helga, Sylvia Frühwirth‐Schnatter +3
Decision Sciences · Health Professions · Mathematics · #Advanced Causal Inference Techniques #FOS: Computer and information sciences #Global Health Care Issues #Methodology (stat.ME) #demographic modeling and climate adaptation

paper · pdf · doi:10.48550/arxiv.2103.00977

openalex publication_date 2021/03/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

We propose a new, flexible model for inference of the effect of a binary treatment on a continuous outcome observed over subsequent time periods. The model allows to seperate association due to endogeneity of treatment selection from additional longitudinal association of the outcomes and hence unbiased estimation of dynamic treatment effects. We investigate the performance of the proposed method on simulated data and employ it to reanalyse data on the longitudinal effects of a long maternity leave on mothers' earnings after their return to the labour market.

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