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Research ArticleArticle

Identifying Sibling Influence on Teenage Substance Use

Joseph G. Altonji, Sarah Cattan and Iain Ware
Journal of Human Resources, January 2017, 52 (1) 1-47; DOI: https://doi.org/10.3368/jhr.52.1.0714-6474R1
Joseph G. Altonji
Joseph G. Altonji is Thomas Dewitt Cuyler Professor of Economics at Yale University and a Research Associate at NBER. Sarah Cattan is a Senior Research Economist at the Institute for Fiscal Studies. Iain Ware is a Principal at Bain Capital. The authors are grateful to the referees, Jerome Adda, Monica Deza, Greg Duncan, Patrick Kline, Amanda Kowalski, Costas Meghir, Robert T. Michael, and participants in seminars at UC Berkeley, Brigham Young University, University of Chicago, The European Institute, MIT, New York University, the NLSY97 conference at the Bureau of Labor Statistics (May 2008), NBER Health 2009 Summer Institute, the Institute for Fiscal Studies, UC San Diego, the SOLE/EALE 2010 Meetings, Stanford University, the University of Toronto, and Yale University for valuable comments.
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Sarah Cattan
Joseph G. Altonji is Thomas Dewitt Cuyler Professor of Economics at Yale University and a Research Associate at NBER. Sarah Cattan is a Senior Research Economist at the Institute for Fiscal Studies. Iain Ware is a Principal at Bain Capital. The authors are grateful to the referees, Jerome Adda, Monica Deza, Greg Duncan, Patrick Kline, Amanda Kowalski, Costas Meghir, Robert T. Michael, and participants in seminars at UC Berkeley, Brigham Young University, University of Chicago, The European Institute, MIT, New York University, the NLSY97 conference at the Bureau of Labor Statistics (May 2008), NBER Health 2009 Summer Institute, the Institute for Fiscal Studies, UC San Diego, the SOLE/EALE 2010 Meetings, Stanford University, the University of Toronto, and Yale University for valuable comments.
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Iain Ware
Joseph G. Altonji is Thomas Dewitt Cuyler Professor of Economics at Yale University and a Research Associate at NBER. Sarah Cattan is a Senior Research Economist at the Institute for Fiscal Studies. Iain Ware is a Principal at Bain Capital. The authors are grateful to the referees, Jerome Adda, Monica Deza, Greg Duncan, Patrick Kline, Amanda Kowalski, Costas Meghir, Robert T. Michael, and participants in seminars at UC Berkeley, Brigham Young University, University of Chicago, The European Institute, MIT, New York University, the NLSY97 conference at the Bureau of Labor Statistics (May 2008), NBER Health 2009 Summer Institute, the Institute for Fiscal Studies, UC San Diego, the SOLE/EALE 2010 Meetings, Stanford University, the University of Toronto, and Yale University for valuable comments.
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Abstract

We assess the extent to which the large sibling correlations in substance use are causal. Our primary approach is based on a joint dynamic model of the behavior of older and younger siblings that allows for family specific effects, individual specific heterogeneity, and state dependence. We use the model to simulate the dynamic response of substance use to the behavior of the older sibling. Overall, we find that substance use is affected by the example of older siblings but only a small fraction of the sibling correlation is causal.

  • Received July 2014.
  • Accepted September 2015.
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Journal of Human Resources: 52 (1)
Journal of Human Resources
Vol. 52, Issue 1
1 Jan 2017
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Identifying Sibling Influence on Teenage Substance Use
Joseph G. Altonji, Sarah Cattan, Iain Ware
Journal of Human Resources Jan 2017, 52 (1) 1-47; DOI: 10.3368/jhr.52.1.0714-6474R1

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Identifying Sibling Influence on Teenage Substance Use
Joseph G. Altonji, Sarah Cattan, Iain Ware
Journal of Human Resources Jan 2017, 52 (1) 1-47; DOI: 10.3368/jhr.52.1.0714-6474R1
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  • Article
    • Abstract
    • I. Introduction
    • II. Literature Review
    • III. The NLSY97 Data
    • IV. Sibling Correlations in Substance Use
    • V. A Joint Dynamic Probit Model of Substance Use and Sibling Influences
    • VI. Results for the Joint Dynamic Probit Model
    • VII. A Joint Dynamic Ordered Probit Model with Many Categories
    • VIII. Using Correlated Random Effects Regression to Estimate the Sibling Effect
    • IX. Conclusion
    • Acknowledgments
    • Appendix
    • Footnotes
    • References
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