This paper examines the binary recurrent outcome "teenage smoking" within a statistical modelling paradigm. The proposed statistical modelling relates smoking to a set of explanatory variables, which include subjective as well as objective measures. In order to assess the degree to which explanatory variables influence smoking, an adequate statistical model must handle the possibility that substantial variation between respondents will be due to omitted variables, multicollinearity and past behaviour. An earlier paper, using a secondary cross-sectional data source, concluded that an investigation of smoking needs to be based on longitudinal data using appropriate statistical modelling. The same data source provided observations on young adults over a period of 2 years. For comparison purposes, the same cross-sectional model was fitted to the longitudinal data. The results suggest there may be substantial heterogeneity due to omitted variables in the data and complex inter-relationships between observed explanatory variables leading to underestimation. Longitudinal data provide additional flexibility to control for omitted variables and are necessary to investigate dynamic social processes such as smoking. The results from our analysis suggest that the effects of variables reported in the literature on teenage smoking may be overestimated. For example, the role of peer pressure may not be as clear as it has been made out to be.