Role of Causal Inference in IA

Takuya Nakaizumi ()
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Takuya Nakaizumi: Kanto Gakuin University

Chapter Chapter 8 in Impact Assessment for Developing Countries, 2022, pp 105-110 from Springer

Abstract: Abstract We discuss how evidence-based policy methods can be used in Impact Assessment, identifying causal inference among the EBPM methods. Causal inference shares the idea of comparing counterfactuals with facts, treatmment groups with control groups, and the former with cases where a regulation is introduced while latter with those where it is not. Additionally, causal inference is the preferred validation method, including randomized controlled trials (RCTs). By virtue of its universality, causal inference transcends time and space, and verification of a causal relationship is equivalent to demonstrating the validity of the rationale for introducing the proposed regulation.

Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:spr:conchp:978-981-19-5494-8_8

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DOI: 10.1007/978-981-19-5494-8_8

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