The economics and econometrics of gene-environment interplay

Pietro Biroli; Titus Galama; Stephanie von Hinke; Hans van Kippersluis; Cornelius A Rietveld; Kevin Thom

doi:10.48550/arXiv.2203.00729

The economics and econometrics of gene-environment interplay

Pietro Biroli^*, Titus Galama, Stephanie von Hinke, Hans van Kippersluis, Cornelius A Rietveld, Kevin Thom

^*Corresponding author for this work

Research output: Contribution to journal › Article (Academic Journal) › peer-review

Abstract

We discuss how to estimate the interplay between genes (nature) and environments (nurture), with an empirical illustration of the moderating effect of school-starting age on one’s genetic predisposition towards educational attainment. We argue that gene–environment (G × E) studies can be instrumental for (i) assessing treatment effect heterogeneity, (ii) testing theoretical predictions, and (iii) uncovering mechanisms, thereby improving understanding
of how (policy) interventions affect population subgroups. Empirically, we find that being old-for-grade and having a higher genetic propensity for education benefits children on assessment tests as they progress through school. In this setting, families appear to increase genetic inequalities while schools seem to reduce them.

Original language	English
Article number	rdaf034
Journal	Review of Economic Studies
Early online date	11 Jun 2025
DOIs	https://doi.org/10.48550/arXiv.2203.00729 https://doi.org/10.1093/restud/rdaf034
Publication status	E-pub ahead of print - 11 Jun 2025

Research Groups and Themes

ECON CEPS Education
ECON Applied Economics
ECON CEPS Data
ECON CEPS Health

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10.48550/arXiv.2203.00729Licence: CC BY-NC-ND
10.1093/restud/rdaf034Licence: CC BY-NC

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title = "The economics and econometrics of gene-environment interplay",

abstract = "We discuss how to estimate the interplay between genes (nature) and environments (nurture), with an empirical illustration of the moderating effect of school-starting age on one{\textquoteright}s genetic predisposition towards educational attainment. We argue that gene–environment (G × E) studies can be instrumental for (i) assessing treatment effect heterogeneity, (ii) testing theoretical predictions, and (iii) uncovering mechanisms, thereby improving understanding of how (policy) interventions affect population subgroups. Empirically, we find that being old-for-grade and having a higher genetic propensity for education benefits children on assessment tests as they progress through school. In this setting, families appear to increase genetic inequalities while schools seem to reduce them.",

author = "Pietro Biroli and Titus Galama and \{von Hinke\}, Stephanie and \{van Kippersluis\}, Hans and Rietveld, \{Cornelius A\} and Kevin Thom",

year = "2025",

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AU - Biroli, Pietro

AU - Galama, Titus

AU - von Hinke, Stephanie

AU - van Kippersluis, Hans

AU - Rietveld, Cornelius A

AU - Thom, Kevin

PY - 2025/6/11

Y1 - 2025/6/11

N2 - We discuss how to estimate the interplay between genes (nature) and environments (nurture), with an empirical illustration of the moderating effect of school-starting age on one’s genetic predisposition towards educational attainment. We argue that gene–environment (G × E) studies can be instrumental for (i) assessing treatment effect heterogeneity, (ii) testing theoretical predictions, and (iii) uncovering mechanisms, thereby improving understanding of how (policy) interventions affect population subgroups. Empirically, we find that being old-for-grade and having a higher genetic propensity for education benefits children on assessment tests as they progress through school. In this setting, families appear to increase genetic inequalities while schools seem to reduce them.

AB - We discuss how to estimate the interplay between genes (nature) and environments (nurture), with an empirical illustration of the moderating effect of school-starting age on one’s genetic predisposition towards educational attainment. We argue that gene–environment (G × E) studies can be instrumental for (i) assessing treatment effect heterogeneity, (ii) testing theoretical predictions, and (iii) uncovering mechanisms, thereby improving understanding of how (policy) interventions affect population subgroups. Empirically, we find that being old-for-grade and having a higher genetic propensity for education benefits children on assessment tests as they progress through school. In this setting, families appear to increase genetic inequalities while schools seem to reduce them.

U2 - 10.48550/arXiv.2203.00729

DO - 10.48550/arXiv.2203.00729

M3 - Article (Academic Journal)

SN - 0034-6527

JO - Review of Economic Studies

JF - Review of Economic Studies

M1 - rdaf034

ER -

The economics and econometrics of gene-environment interplay

Abstract

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