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"High"-School: The Relationship between Early Marijuana Use and Educational Outcomes

  • Deborah A. Cobb-Clark


    (Melbourne Institute of Applied Economic and Social Research, The University of Melbourne; and Institute for the Study of Labor (IZA))

  • Sonja C. Kassenboehmer


    (Melbourne Institute of Applied Economic and Social Research, The University of Melbourne; and Institute for the Study of Labor (IZA))

  • Trinh Le

    (Department of Economics, The University of Waikato)

  • Duncan McVicar

    (Queen's University Management School, Queen's University, Belfast)

  • Rong Zhang

    (Melbourne Institute of Applied Economic and Social Research, The University of Melbourne)

We use unique survey data linked to nearly a decade of administrative welfare data to examine the relationship between early marijuana use (at age 14 or younger) and young people’s educational outcomes. We find evidence that early marijuana use is related to educational penalties that are compounded by high-intensity use and are larger for young people living in families with a history of welfare receipt. The relationships between marijuana use and both high school completion and achieving a university entrance score appear to stem from selectivity into the use of marijuana. In contrast, early marijuana use is associated with significantly lower university entrance score for those who obtain one and we provide evidence that this effect is unlikely to be driven by selection. Collectively, these findings point to a more nuanced view of the relationship between adolescent marijuana use and educational outcomes than is suggested by the existing literature.

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Paper provided by Melbourne Institute of Applied Economic and Social Research, The University of Melbourne in its series Melbourne Institute Working Paper Series with number wp2013n38.

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Length: 41pp
Date of creation: Oct 2013
Date of revision:
Handle: RePEc:iae:iaewps:wp2013n38
Contact details of provider: Postal: Melbourne Institute of Applied Economic and Social Research, The University of Melbourne, Victoria 3010 Australia
Phone: +61 3 8344 2100
Fax: +61 3 8344 2111
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  1. Tetsuji Yamada & Michael Kendix & Tadashi Yamada, 1993. "The Impact of Alcohol Consumption and Marijuana Use on High School Graduation," NBER Working Papers 4497, National Bureau of Economic Research, Inc.
  2. Pinka Chatterji, 2006. "Illicit drug use and educational attainment," Health Economics, John Wiley & Sons, Ltd., vol. 15(5), pages 489-511.
  3. Stephen Pudney, 2003. "The Road to Ruin? Sequences of Initiation to Drugs and Crime in Britain," Economic Journal, Royal Economic Society, vol. 113(486), pages C182-C198, March.
  4. Ai, Chunrong & Norton, Edward C., 2003. "Interaction terms in logit and probit models," Economics Letters, Elsevier, vol. 80(1), pages 123-129, July.
  5. Simon Burgess & Karen Gardiner & Carol Propper, 2001. "Growing Up: School, family and area influences on adolescents later life chances," CASE Papers case49, Centre for Analysis of Social Exclusion, LSE.
  6. Roebuck, M. Christopher & French, Michael T. & Dennis, Michael L., 2004. "Adolescent marijuana use and school attendance," Economics of Education Review, Elsevier, vol. 23(2), pages 133-141, April.
  7. van Ours, Jan C. & Williams, Jenny, 2009. "Why parents worry: Initiation into cannabis use by youth and their educational attainment," Journal of Health Economics, Elsevier, vol. 28(1), pages 132-142, January.
  8. Charles Register & Donald Williams & Paul Grimes, 2001. "Adolescent Drug Use and Educational Attainment," Education Economics, Taylor & Francis Journals, vol. 9(1), pages 1-18.
  9. James Heckman, 2011. "Policies to foster human capital," Educational Studies, Higher School of Economics, issue 3, pages 73-137.
  10. Daniel F. McCaffrey & Rosalie Liccardo Pacula & Bing Han & Phyllis Ellickson, 2010. "Marijuana use and high school dropout: the influence of unobservables," Health Economics, John Wiley & Sons, Ltd., vol. 19(11), pages 1281-1299.
  11. Edward C. Norton & Hua Wang & Chunrong Ai, 2004. "Computing interaction effects and standard errors in logit and probit models," Stata Journal, StataCorp LP, vol. 4(2), pages 154-167, June.
  12. Jeremy W. Bray & Gary A. Zarkin & Chris Ringwalt & Junfeng Qi, 2000. "The relationship between marijuana initiation and dropping out of high school," Health Economics, John Wiley & Sons, Ltd., vol. 9(1), pages 9-18.
  13. Joseph G. Altonji & Todd E. Elder & Christopher R. Taber, 2000. "Selection on Observed and Unobserved Variables: Assessing the Effectiveness of Catholic Schools," NBER Working Papers 7831, National Bureau of Economic Research, Inc.
  14. Cobb-Clark, Deborah A. & Ryan, Chris & Sartbayeva, Anastasia, 2009. "Taking Chances: The Effect of Growing Up on Welfare on the Risky Behavior of Young People," IZA Discussion Papers 4095, Institute for the Study of Labor (IZA).
  15. Aizer, Anna, 2004. "Home alone: supervision after school and child behavior," Journal of Public Economics, Elsevier, vol. 88(9-10), pages 1835-1848, August.
  16. Michael T. French & Ioana Popovici, 2011. "That instrument is lousy! In search of agreement when using instrumental variables estimation in substance use research," Health Economics, John Wiley & Sons, Ltd., vol. 20(2), pages 127-146, 02.
  17. Jonathan Gruber, 2001. "Risky Behavior among Youths: An Economic Analysis," NBER Books, National Bureau of Economic Research, Inc, number grub01-1, December.
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