Applying causal machine learning to assess and improve cleantech policy design

Abstract

Effective cleantech policy, such as subsidies and carbon pricing, requires understanding how interventions shape environmental and socioeconomic outcomes. We discuss how causal machine learning can compare alternative policy scenarios and reveal where, how and for whom policies work to support targeted, evidence-based design.