برآورد اثرات همسالان در مصرف سیگار نوجوانان در بیست و شش کشور اروپایی

Although it is widely believed that one of the key factors influencing whether an adolescent smokes or not is the smoking behaviour of his or her peers, empirical evidence on the magnitude of such peer effects, and even on their existence, is mixed. This existing evidence comes from a range of studies using a variety of country-specific data sources and a variety of identification strategies. This paper exploits a rich source of individual level, school-based, survey data on adolescent substance use across countries – the 2007 European Schools Survey Project on Alcohol and Other Drugs – to provide estimates of peer effects between classmates in adolescent smoking for 75,000 individuals across 26 European countries, using the same methods in each case. The results suggest statistically significant peer effects in almost all cases. These peer effects estimates are large: on average across countries, the probability that a ‘typical’ adolescent smokes increases by between.31 and.38 percentage points for a one percentage point increase in the proportion of classmates that smoke. Further, estimated peer effects in adolescent smoking are stronger intra-gender than inter-gender. They also vary across countries: in Belgium, for example, a one percentage point increase in reference group smoking is associated with a.16 to.27 percentage point increase in own smoking probability; in the Netherlands the corresponding increase is between.42 and.59 percentage points.

Tobacco smoking is the largest single cause of avoidable death in the EU, with 650,000 smoking-related deaths each year, many of which occur at well below average life expectancy (European Commission, 2010). Globally, almost five million premature deaths in the year 2000 were linked to smoking (Ezzati & Lopez, 2003). Most smokers begin to smoke in adolescence, with adolescent smoking a very strong predictor of later smoking (e.g. Merline et al., 2004 and Pierce and Gilpin, 1996). One way for policy makers to reduce the number of smoking-related deaths in the future – and also to improve adolescent health in the shorter term – is therefore to reduce the prevalence of smoking among adolescents now. Research that improves our understanding of why adolescents smoke can help effective policy design in this critical area.

This paper’s primary contribution to the literature is to show that estimates of peer effects in adolescent smoking generalise across countries: evidence is presented here of large and highly significant peer effects in adolescent smoking across 26 European countries and for almost all countries when estimated separately. Of course concerns remain about this kind of IV approach, e.g. if there is endogenous sorting into schools, despite its widespread use. And the results presented here don’t imply that peer effects in adolescent smoking will exist across all countries, across alternative reference groups (other than the school class), across other age groups, or across other behaviours. Having said that, the paper cites studies that show significant peer effects in adolescent smoking for the US (outside of the 26 country sample examined here), that have found peer effects where schools, classes or friends are taken as the reference group (e.g. Clark and Loheac, 2007, Powell et al., 2005 and Soetevent and Kooreman, 2007), and where evidence of peer effects has been found for other adolescent substance use behaviours (e.g. Clark and Loheac, 2007 and Gaviria and Raphael, 2001). Existing (single country) evidence also points to the existence of peer effects in smoking outside of this particular age group (e.g. Cutler & Glaeser, 2008). So the prospects for further generalisation look good. Both the ESPAD and the HBSC data sets would plausibly allow at least some of these extensions to be explored in further research.