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

680 M. Beenstock, G. Rahav / Journal of Health Economics 21 (2002) 679–698
Gateway Theory was originally developed in the 1970s by Kandel (1975). She observed
that there is a systematic sequencing in the use of psychoactive substances which runs from
alcohol and cigarettes, then to cannabis, and finally to “hard” drugs such as cocaine, heroin
and LSD. Cigarettes are a “gateway” to cannabis, which in turn is a “gateway” to hard drugs.
Of course not all cigarette smokers go on to use cannabis, and it should be noted that not
all cannabis consumers first smoked cigarettes. Nevertheless, cigarette smokers are more
likely to use cannabis subsequently than non-smokers. A similar juxtaposition applies to
cannabis and hard drugs; cannabis users are more likely to use hard drugs eventually than
non-users of cannabis, but not all hard drug consumers used cannabis first.
The scientific literature on Gateway Theory is too vast to be reviewed here. However,
it splits into two broad camps. One camp (e.g. O’Donnell and Clayton, 1982) regards the
gateway effect to be causal or generative. According to this view cigarette smoking induces
cannabis use, and cannabis use induces hard drug consumption. This implies that if smoking
were restricted there would be less use of cannabis. It also implies that if cannabis were
legalized there would be more use of hard drugs. It is obvious how this causal interpretation
of Gateway Theory has been grist to the mill of the anti liberalization lobby. The rival camp
(e.g. Baumrind, 1983) views the gateway effect to be merely predictive or even descriptive.
Economists will recognize this as Granger causality; due to systematic sequencing cigarette
consumption may help predict cannabis consumption, and cannabis consumption may help
predict hard drug consumption. However, Granger causality does not imply causality itself
and has no implications for policy.
The longstanding debate about Gateway Theory revolves around the identification problem.
Does the fact that cigarette smokers are more likely to go onto use cannabis result
from unobserved heterogeneity, i.e. people with a greater susceptibility to smoke cigarettes
also have a greater susceptibility to consume cannabis, or does it result from a treatment
effect, i.e. exposure to cigarettes (the treatment) induces cannabis use (the outcome)? The
vast number of empirical papers on Gateway Theory have not resolved the identification
problem.
One way to resolve this identification problem is to apply the methodology of natural
experimentation, which in the present context seeks to randomize cigarette smoking so that
its causal effect on subsequent use of cannabis is identified. We use the data for Israel to
apply the methodology, and follow Evans and Ringel (1999) who study the effect of smoking
on birth weights by using cigarette price data to randomize smoking behavior. They use
cross section data and randomize cigarette smoking by exploiting differential tax rates on
cigarettes in the US. Pacula (1998) too uses cross section data to identify the gateway effect
of alcohol by exploiting differential tax rates on alcohol in the US.
Natural experiments in econometrics usually exploit cross section differences in instrumental
variables. A methodological innovation in our approach to natural experimentation
consists of exploiting time series data rather than cross section data. We do so because
there are no cross sectional or geographical differences in cigarette prices (or other potential
instruments) in Israel. However, there has been extensive variation in the real price of
cigarettes over time. People who grew up when cigarettes were cheap are more likely to
smoke than people who grew up when they were expensive. Because individuals do not
chose their year of birth or the price of cigarettes and other variables we have the basis of
a natural experiment.