Impact of federal drug law enforcement on the supply of heroin in Australia

Abstract

Aims: To conduct an empirical investigation of the efficacy of law enforcement in reducing heroin supply in Australia. Specifically, this paper addresses the question of whether heroin purity levels in the Australian Capital Territory (ACT) could be predicted by heroin seizures at the national level by the Australian Federal Police (AFP) in the preceding year. Design: We considered two forms of evidence. First, a Bayesian Markov Chain Monte Carlo (MCMC) change-point model was used to discover (a) if there was a substantial increase in heroin seizures by the AFP, (b) when the increase began and (c) whether it occurred after increased funding to the Australian Federal Police for the purpose of drug law enforcement. Second, standard time-series methods were used to ascertain whether fluctuations in heroin seizure weights or the frequency of large-scale seizures after the aforementioned changes in seizure levels predicted fluctuations in heroin purity levels in the ACT after autocorrelation had been removed from the purity series. Findings: A Bayesian MCMC change-point model supported the hypothesis that heroin seizures rapidly increased about a year before the estimated decline in heroin purity and after the increased funding of AFP. The autoregression models suggested that 10-20% of the variance in the residuals of the heroin purity series was predicted by appropriately lagged residuals of the seizure-number and log-weight series, after autocorrelation had been removed. Conclusion: The overall results are consistent with the hypothesis that large-scale heroin seizures by the AFP reduce street-level heroin supply a year or so later, although the short-term dynamics suggest an 'opponent' response to residual fluctuations in seizures. To our knowledge, this is first time a connection has been identified between large-scale heroin seizures and street-level supply.