[논문 리뷰] The Economics and Econometrics of Gene-Environment Interplay

Pietro Biroli, T. J. Galama외 4명|Bristol Research (University of Bristol)|2022. 03. 01.

Intergenerational and Educational Inequality Studies인용 수 21

한 줄 요약

이 논문은 genetic data가 경제 분석에 어떻게 통합되어 gene–environment (G×E) interplay를 연구하는지 검토하고, G×E의 stylized economic model을 제시하며, polygenic indices 및 관련 genetic measures를 사용한 실증 연구를 위한 실무 가이드를 제공한다.

ABSTRACT

Economists and social scientists have debated the relative importance of nature (one's genes) and nurture (one's environment) for decades, if not centuries. This debate can now be informed by the ready availability of genetic data in a growing number of social science datasets. This paper explores the potential uses of genetic data in economics, with a focus on estimating the interplay between nature (genes) and nurture (environment). We discuss how economists can benefit from incorporating genetic data into their analyses even when they do not have a direct interest in estimating genetic effects. We argue that gene--environment (GxE) studies can be instrumental for (i) testing economic theory, (ii) uncovering economic or behavioral mechanisms, and (iii) analyzing treatment effect heterogeneity, thereby improving the understanding of how (policy) interventions affect population subgroups. We introduce the reader to essential genetic terminology, develop a conceptual economic model to interpret gene-environment interplay, and provide practical guidance to empirical researchers.

연구 동기 및 목표

• Introduce key concepts and recent developments in gene–environment (G×E) interplay for economics.
• Explain how genetic data can inform economic theory testing, mechanism identification, and treatment-effect heterogeneity analyses.
• Develop an economic model illustrating how genetic and environmental factors interact through endogenous behavioral choices.
• Provide practical guidance on measuring G and E, interpreting G×E effects, and empirical pitfalls.

제안 방법

• Present a stylized economic model of a behavioral choice with genetics and environment to generate G×E interplay.
• Derive optimal choice conditions and discuss reinforcement or substitution in responses to G and E.
• Decompose G×E into multiple pathways including production-function interactions and choice-mediated effects.
• Linearize a simple empirical specification to show how endogenous effort affects observed G×E relations.
• Illustrate the welfare relevance of G×E through a formal comparison between outcomes and welfare effects.
• Detail measurement of G via polygenic indices and explain GWAS-based approaches to genotyping.

실험 결과

연구 질문

• RQ1 How do genetic factors (G) and environmental factors (E) jointly influence economic outcomes through endogenous choices?
• RQ2 Under what conditions do G×E interactions arise in production, costs, or behavior, and how do these translate into observed outcomes?
• RQ3 What are the mechanisms by which G×E interplay operates, and how can economic theory guide empirical modeling and interpretation?
• RQ4 What is the relationship between G×E effects on observable outcomes and G×E effects on individual welfare in the presence of endogenous choices?

주요 결과

• G×E interplay can arise via production-function interactions, choice complementarity, and endogenously driven behavioral responses.
• Endogenous choices can generate nonlinear and higher-order terms (e.g., G², E², G×E) in the data-generating process even if the underlying production function is simple.
• Environmental or genetic factors can reinforce or substitute for each other depending on how marginal benefits and costs of effort vary with E and G.
• G×E analyses can test theory, uncover mechanisms, and assess treatment-effect heterogeneity across population subgroups.
• Policy implications depend on welfare-level G×E effects, which may differ in sign or magnitude from observed outcome-level G×E effects due to cost and behavioral channels.