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Peer influences on adolescent alcohol consumption: evidence using an instrumental variables/fixed effect approach

Abstract

In order to address empirical difficulties in research examining peer effects in alcohol consumption, I use instrumental variables/fixed effects methodology that compares students in different grades within the same school who face a different set of classmate decisions. Within this context, I suggest that alcohol availability in classmates’ homes and classmates’ parents’ alcohol abuse can be used as instruments. Results indicate that a 10% increase in the proportion of classmates who drink increases the likelihood an individual drinks by five percentage points. This paper also provides evidence of peer effects in problem drinking, such as binge drinking and drunkenness.

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Notes

  1. See also the recent discussion between Cohen-Cole and Fletcher (2008a, 2008bb) and Christakis and Fowler (2007) and Fowler and Christakis (2008) for examinations of peer influences on weight status. See Cohen-Cole and Fletcher (2008c) for an example where one can estimate large “social effects” for outcomes where the true social effect is zero, such as the transmission of height. The authors argue that weak empirical models commonly employed in the literature can produce these results.

  2. The assumption of the relevant reference group is also an important difficulty with social interactions research. I follow the literature in assuming that classmates are a relevant reference group, although other researchers have assumed larger types of reference groups (e.g. city blocks by Case and Katz 1991).

  3. If all families choose schools based on time-invariant school characteristics, then controlling for school fixed effects controls for the main source of selection into schools.

  4. Hoxby (2000) and others have pointed out that contextual effects that are non-linear could imply distributional consequences of changing the composition of schools.

  5. Norton et al. (1998) focuses on younger students and defines peer groups at the neighborhood level rather than the school level. There is also a complementary research area examining peer influences on alcohol consumption of college students (Sacerdote 2001; Kremer and Lavy 2003; DeSimone 2007). See also Kooreman (2007).

  6. Gaviria and Raphael (2001) and others argue that this approach is valid because, “...students are less exposed to the family background of their school peers than they are exposed to the family background of peers residing in the same neighborhood.”

  7. The authors compared individuals who were recent movers versus those who were immobile to examine the potential bias from the endogeneity of school and found relatively large differences—a difference of nearly 16% in the estimated endogenous effect coefficient in the case of drinking.

  8. McEwan (2003) uses a similar approach with data from Chile on educational achievement for middle-schoolers.

  9. Manski (1995, p.136) states, “Of course one cannot simply specify a dynamic model and claim that the problem of inference on social effects has been resolved. Dynamic analysis is meaningful only if one has reason to believe that the transmission of social effects follows the assumed temporal pattern.” Clark and Loheac also note that they must also assume that behavior is not in a steady state equilibrium in order to use their approach.

  10. Clark and Loheac (2007) report that the correlation between the one-year lagged peer drinking measure and contemporaneous measure is 0.43.

  11. Increasing the proportion of male peer group members who drink by 25% is predicted to increase own-drinking participation by 4.5%.

  12. This paper is similar in spirit to Hanushek et al. (2003) and Hoxby (2000) who use administrative data from Texas to examine peer effects in educational achievement. Important differences include the use of non-administrative data that includes rich family-level information as well as the examination of risky behaviors decisions rather than academic achievement. Using survey data rather than administrative data allows me to have broad geographic coverage, increasing the generalizeabilty of the results, as well as the ability to examine risky behaviors that are not included in school administrative data. Bifulco et al. (2011) use the same data but focus on the effects of peer characteristics (e.g. racial composition) rather than peer behaviors.

  13. See Udry (2003) for full description of the Add Health data set. Also see for further information: http://www.cpc.unc.edu/projects/addhealth.

  14. In order to keep 3,000 students whose parent did not complete the separate parental survey, I impute family income and maternal education and create a dummy variable for missing parental data.

  15. The exact wording of the question was, “During the past 12 months, on how many days did you drink alcohol?”

  16. The Add Health Picture Vocabulary Test (AHPVT) is a computerized, abridged version of the Peabody Picture Vocabulary Test-Revised (PPVT-R). The AHPVT is a test of hearing vocabulary, designed for persons aged 2 1/2 to 40 years old who can see and hear reasonably well and who understand standard English to some degree. Each test included a set of practice, or pretest items, followed by a series of test items arranged in order of increasing difficulty. The respondent was asked to listen to the word spoken by the interviewer and to select the picture on the plate that he or she believed best illustrated the meaning of the stimulus word. Once the response was entered into the computer, the program indicated the next plate to use in the test. In addition, the computer program determined test results automatically. These test results were not made available to the interviewer or to the respondent.” The test scores are standardized by age. Some psychologists interpret PVT scores as a measure of verbal IQ. Information on the test is provided online at http://www.cpc.unc.edu/projects/addhealth/files/w3cdbk/w3doc.zip.

  17. See Averett et al. (2011).

  18. The survey question is: “Is alcohol easily available to you in your home?” The responses are “yes” or “no”.

  19. Previous research has used variation in multiple cohorts’ peer characteristics within a school to examine the effects of peer characteristics (but not outcomes) on individual outcomes, where the coefficient of interest is δ rather than α (e.g. Hoxby 2000; Hanushek et al. 2003; Lavy and Schlosser 2007; Bifulco et al. 2011).

  20. One potential weakness of the grademates’ alcohol availability instrument is that, in principle, it could have direct effects on the consumption patterns of a student though providing direct alcohol access. For example, some grademates are also friends. However, the grademates’ parental alcohol status measure should not have a similar problem. The over identification tests shown below suggest similar results regardless of the instrument used, which reduces the concern with the availability instrument, However, this potential limitation with the instrument should be considered when evaluating the results.

  21. Results stratified by race and gender are available upon request.

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Acknowledgements

The author thanks two anonymous reviewers, Kitt Carpenter, Jeff DeSimone, Andrew Francis, David Frisvold, Dave Marcotte, Sara Markowitz, and seminar participants at Emory University, University of Maryland-Baltimore County, and the 2008 Southern Economic Association Meetings for very helpful comments.

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Correspondence to Jason M. Fletcher.

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Responsible editor: Erdal Tekin

This research uses data from Add Health, a program project directed by Kathleen Mullan Harris and designed by J. Richard Udry, Peter S. Bearman, and Kathleen Mullan Harris at the University of North Carolina at Chapel Hill and funded by grant P01-HD31921 from the Eunice Kennedy Shriver National Institute of Child Health and Human Development, with cooperative funding from 23 other federal agencies and foundations. Special acknowledgment is due Ronald R. Rindfuss and Barbara Entwisle for assistance in the original design. Information on how to obtain the Add Health data files is available on the Add Health website (http://www.cpc.unc.edu/addhealth). No direct support was received from grant P01-HD31921 for this analysis.

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Fletcher, J.M. Peer influences on adolescent alcohol consumption: evidence using an instrumental variables/fixed effect approach. J Popul Econ 25, 1265–1286 (2012). https://doi.org/10.1007/s00148-011-0365-9

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Keywords

  • Peer effects
  • Social interactions
  • Alcohol consumption

JEL Classification

  • I12
  • I20