Testing for peer effects using genetic data

Citation

Cawley, John; Han, Euna; Kim, Jiyoon; & Norton, Edward C. (2017). Testing for peer effects using genetic data. NBER Health Economics Program Meeting. Cambridge, MA.

Abstract

Estimating peer effects is notoriously difficult because of the reflection problem and the endogeneity of peer group formation. Cawley, Han, Kim, and Norton test for peer effects in obesity in a novel way that addresses these challenges. They address the reflection problem by using the alter's genetic risk score for obesity, which is a significant predictor of obesity, is determined prior to birth, and cannot be affected by the behavior of others. They address the endogeneity of peer group formation by examining peers who are not chosen: full siblings. Using data from the National Longitudinal Survey of Adolescent Health, the researchers find evidence of positive peer effects in weight and obesity; having a sibling with a high genetic predisposition raises one's risk of obesity, even controlling for one's own genetic predisposition to obesity. Implications of the findings include that peer effects may be an explanation for continued worldwide increases in weight, and that, because of social multipliers, the cost-effectiveness of obesity treatment and prevention programs may have been underestimated.

URL

http://conference.nber.org/confer/2017/HEs17/summary.html

Reference Type

Conference proceeding

Book Title

NBER Health Economics Program Meeting

Author(s)

Cawley, John
Han, Euna
Kim, Jiyoon
Norton, Edward C.

Year Published

2017

City of Publication

Cambridge, MA

Reference ID

8129