Bayesian Structural Break Detection for the Identification of Effective Climate Policies
In this study, we introduce a Bayesian approach to detect structural breaks in panel data in the context of step-shift indicator saturated models. We focus on identifying the magnitude of the impact of climate policies with uncertain timing. Traditional methods for climate policy evaluation often rely on precise knowledge of when interventions occur, comparing outcomes… Continue reading Bayesian Structural Break Detection for the Identification of Effective Climate Policies