Testing Gateway Theory: do cigarette prices affect illicit drug use?

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686 M. Beenstock, G. Rahav / Journal of Health Economics 21 (2002) 679–698 but whether incidental use of cigarettes increases the risk of subsequently using cannabis. Likewise, the question will be whether the incidental use of cannabis increases the risk of subsequently using hard drugs. Table 1 further indicates that the majority of illicit drug users stop using them, e.g. 62.1% of hard drug users had stopped. The table shows that the proportion of cigarette smokers who stop smoking is smaller than the proportion of stoppers among illicit drug users. The data are truncated because users may stop after the survey date. We have shown elsewhere (Beenstock and Rahav, 2000) that the data in the table understate the true rates of stopping, and that whereas the stopping hazard for cannabis is duration dependent, the stopping hazard for hard drugs is age dependent. We do not attach importance to alcohol as a gateway substance, because in Israel the cultural significance of alcohol is quite different from its significance in other western countries. Apart from the usual demographic variables, such as age, education, country of origin, and father’s country of origin, the surveys also contain data about religious practice, frequency of pub visits, and a range of economic variables. 3.2. Instrumental variables To identify the gateway effect of cigarettes on cannabis use we seek instruments, which affect the use of cigarettes without simultaneously affecting the use of cannabis. Tobacco taxes are uniform in Israel (except in Eilat where there is no VAT), hence we cannot implement Evans and Ringel’s (1999) idea. However, cigarette taxes have changed over time, as has the world price of tobacco. This suggests that the relative price of cigarettes may serve as a possible instrument for smoking. People who grew up when cigarettes were relatively cheap are more likely to smoke, given everything else, than people who grew up when cigarettes were expensive. In this case, randomization is by birth cohort and the price of cigarettes. The natural experiment consists of investigating whether birth cohorts who matured when cigarettes were relatively cheap were more prone to smoking, and as a consequence, were more prone to use cannabis. The crucial identifying restriction is that the price of cigarettes at the time when individual n was growing up affects the probability of him smoking them, but it does not affect the probability of using cannabis at a later date. There is no intertemporal substitution between cigarettes and cannabis; e.g. consumers do not plan to consume cannabis in the future as a result of an increase in the current price of cigarettes. In this sense, we assume consumers are myopic. If this were not the case the gateway effect would be inverted; when cigarette consumption falls cannabis consumption should increase. We show later that this does not happen in practice, and that cannabis consumption is not affected by cigarette prices, whereas cigarette consumption is so affected. This does not necessarily mean that there is no intratemporal substitution between cigarettes and cannabis. If an individual eventually happens to consume both cigarettes and cannabis a change in their relative price might induce him to alter his relative demand for cigarettes. Unfortunately, there are no systematic data for cannabis prices in Israel. Had they existed, however, we would have dated them at time t rather than time t − 1 because, according to gateway sequencing, cannabis initiation at time t−1 does not depend upon cannabis prices at a later date (time t) they would have constituted a further source of identifying information.
M. Beenstock, G. Rahav / Journal of Health Economics 21 (2002) 679–698 687 The approach may be extended to other variables with possibly identifying power. These include exposure to anti-smoking regulations such as the introduction of mandatory health warnings. Older birth cohorts, who were young before such regulations were introduced, are more likely to smoke, given other considerations, than younger birth cohorts. The accident of birth serves to randomize exposure to the regulatory environment. A third possible source of natural experimentation consists of the herd effect; the individual who happens to grow up when smoking is more prevalent may be more likely to smoke as a result of demonstration effects. Since the individual has no control over his environment, aggregate smoking patterns during the years of high risk exposure (say, aged 15–20 years) may serve to randomize individual smoking behavior. In Figs. 1 and 2 we use CBS data to plot the real price of cigarettes (as measured by the average price per packet deflated by the consumer price index) in Israel, and aggregate cigarette consumption per capita. The data indicate that cigarettes were relatively expensive in the 1960s, while per capita cigarette consumption was lower. Subsequently, cigarettes became cheaper and per capita cigarette consumption increased. 5 A person born in the early 1950s would have experienced relatively high cigarette prices in his teens, and a more smoke-free environment. By contrast, a person born in the 1970s would have experienced relatively low cigarette prices in his teens, and a less smoke-free environment. Controlling for other factors, the former is less likely to smoke than the latter, if indeed herd effects and the price of cigarettes affects smoking initiation. We use the data in Fig. 1 to calculate a weighted average of cigarette prices for each individual during his “impressionable” years. The weights are taken from the hazard function for smoking initiation (Fig. 3, taken from Beenstock and Rahav (2001)). This gives a higher weight in the ages 15–20 years, when the risk of smoking initiation is high, and smaller weights when the risk of smoking initiation is low. We apply a similar procedure to the data in Fig. 2. In this way, we calculate for each individual the personalized price of cigarettes and smoking environment. These variables are naturally randomized by birth year, cigarette prices and aggregate smoking behavior. This is similar to the approach taken by Douglas and Hariharan (1994) who used a narrower window (15–18 years) than ours. These variables are used as instrumental variables because they are independent of observed heterogeneity that might influence the propensity to smoke and use drugs. 4. Results We report two types of gateway test using the methodology of natural experimentation. In the first, we estimate the recursive model as specified in Section 2.2 using a bivariate probit procedure (RBP), and a two-stage logit (2SL) procedure. The second type of test refers to the relationship between smoking initiation and cannabis initiation. We apply the 5 Unfortunately, there are no systematic prevalence data. Since 1972, the Health Education Department at the Ministry of Health has occasionally commissioned surveys on smoking prevalence. These data have been analysed by Ben-Sira (e.g. Ben-Sira (1993)). They suggest that between 1972 and 1988 smoking prevalence was stable, but it fell during the 1990s.
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