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Smoking initiation: Peers and personality

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  • Chih‐Sheng Hsieh
  • Hans van Kippersluis

Abstract

Social interactions are widely recognized to play an important role in smoking initiation among adolescents. In this paper, we hypothesize that emotionally stable, conscientious individuals are better able to resist peer pressure in the uptake of smoking. We exploit detailed friendship nominations in the US Add Health data, and extend the Spatial Autoregressive (SAR) model to deal with (i) endogenous peer selection, and (ii) unobserved contextual effects, in order to identify heterogeneity in peer effects with respect to personality. The results indicate that peer effects in the uptake of smoking are predominantly affecting individuals who are emotionally unstable. That is, emotionally unstable individuals are more vulnerable to peer pressure. This finding not only helps understanding heterogeneity in peer effects, but additionally provides a promising mechanism through which personality affects later life health and socioeconomic outcomes.

Suggested Citation

  • Chih‐Sheng Hsieh & Hans van Kippersluis, 2018. "Smoking initiation: Peers and personality," Quantitative Economics, Econometric Society, vol. 9(2), pages 825-863, July.
    • Handle: RePEc:wly:quante:v:9:y:2018:i:2:p:825-863
    DOI: 10.3982/QE615
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    Cited by:

    1. Giulietti, Corrado & Vlassopoulos, Michael & Zenou, Yves, 2023. "When reality bites: Local deaths and vaccine take-up," European Economic Review, Elsevier, vol. 156(C).
    2. Hoshino, Tadao & Yanagi, Takahide, 2023. "Treatment effect models with strategic interaction in treatment decisions," Journal of Econometrics, Elsevier, vol. 236(2).
    3. Aliaksandr Amialchuk & Onur Sapci, 2022. "The long‐term health effects of initiating smoking in adolescence: Evidence from a national longitudinal survey," Health Economics, John Wiley & Sons, Ltd., vol. 31(4), pages 597-613, April.
    4. Attanasio, Orazio & Blundell, Richard & Conti, Gabriella & Mason, Giacomo, 2020. "Inequality in socio-emotional skills: A cross-cohort comparison," Journal of Public Economics, Elsevier, vol. 191(C).
    5. Yann Bramoullé & Habiba Djebbari & Bernard Fortin, 2020. "Peer Effects in Networks: A Survey," Annual Review of Economics, Annual Reviews, vol. 12(1), pages 603-629, August.
    6. Pablo Brañas-Garza & Lorenzo Ductor & Jaromir Kovarik, 2022. "The role of unobservable characteristics in friendship network formation," ThE Papers 22/08, Department of Economic Theory and Economic History of the University of Granada..
    7. repec:ags:aaea22:335614 is not listed on IDEAS
    8. Chih‐Sheng Hsieh & Lung‐Fei Lee & Vincent Boucher, 2020. "Specification and estimation of network formation and network interaction models with the exponential probability distribution," Quantitative Economics, Econometric Society, vol. 11(4), pages 1349-1390, November.
    9. Hsieh, Chih-Sheng & Lin, Xu, 2024. "Gender and racial disparities in altruism in social networks," Regional Science and Urban Economics, Elsevier, vol. 108(C).
    10. Tiziano Arduini & Alberto Bisin & Onur Özgür & Eleonora Patacchini, 2019. "Dynamic Social Interactions and Health Risk Behavior," NBER Working Papers 26223, National Bureau of Economic Research, Inc.
    11. Bin Huang & Rong Zhu, 2020. "Peer effects of low-ability students in the classroom: evidence from China’s middle schools," Journal of Population Economics, Springer;European Society for Population Economics, vol. 33(4), pages 1343-1380, October.
    12. Konstantinidi, Antri & Kourtellos, Andros & Sun, Yiguo, 2023. "Social threshold regression," Journal of Econometrics, Elsevier, vol. 235(2), pages 2057-2081.
    13. Gupta, Abhimanyu, 2023. "Efficient closed-form estimation of large spatial autoregressions," Journal of Econometrics, Elsevier, vol. 232(1), pages 148-167.
    14. Chih‐Sheng Hsieh & Xu Lin, 2021. "Social interactions and social preferences in social networks," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(2), pages 165-189, March.
    15. Zhu, Yanli & Han, Xiaoyi & Chen, Ying, 2020. "Bayesian estimation and model selection of threshold spatial Durbin model," Economics Letters, Elsevier, vol. 188(C).
    16. Blas A. Marin-Lopez & David Jimenez-Gomez & José-María Abellán-Perpiñán, 2022. "Behavioral Economics in the Epidemiology of the COVID-19 Pandemic: Theory and Simulations," IJERPH, MDPI, vol. 19(15), pages 1-23, August.
    17. Rose, C.; & Williams, J.; & Bretteville-Jensen, A.L.;, 2024. "Do Peers Support or Subvert Recovery from Substance Use Disorders," Health, Econometrics and Data Group (HEDG) Working Papers 24/18, HEDG, c/o Department of Economics, University of York.
    18. Josten, Cecily & Lordan, Grace, 2020. "The interaction between personality and health policy: Empirical evidence from the UK smoking bans," Economics & Human Biology, Elsevier, vol. 38(C).
    19. Vardges Hovhannisyan & Vahé Heboyan & Magdana Kondaridze, 2024. "An empirical assessment of effectiveness of the US tobacco control policies: a smoothed instrumental variables quantile regression approach," Empirical Economics, Springer, vol. 67(2), pages 465-493, August.
    20. Gupta, Abhimanyu & Kokas, Sotirios & Michaelides, Alexander & Minetti, Raoul, 2025. "Networks and information in credit markets," Journal of Corporate Finance, Elsevier, vol. 94(C).
    21. Heboyan, Vahé & Hovhannisyan, Vardges & Bakhtavoryan, Rafael, 2023. "A Comprehensive Analysis of Tobacco Control Policies within a Smoothed Instrumental Variables Quantile Regression Framework," 2023 Annual Meeting, July 23-25, Washington D.C. 335614, Agricultural and Applied Economics Association.
    22. Patacchini, Eleonora & Hsieh, Chih-Sheng & Lin, Xu, 2019. "Social Interaction Methods," CEPR Discussion Papers 14141, C.E.P.R. Discussion Papers.
    23. Müller, Nathalie & Fallucchi, Francesco & Suhrcke, Marc, 2024. "Peer effects in weight-related behaviours of young people: A systematic literature review," Economics & Human Biology, Elsevier, vol. 53(C).

    More about this item

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior

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