It came from the north: assessing the claim of Canada’s rising role as a global supplier of synthetic drugs

Abstract

The past decade saw increasing attention turned toward Canada as an active supplier of synthetic drugs to the U.S. and wider international market. Other than occasional drug seizures at border crossings and news stories, no systematic research has been conducted to verify or ascertain such claims. This study assesses the Canadian synthetic drugs market by using multiple sources of data and three methods (georeferencing, economic modeling, and chemical composition analysis) to establish the scope, scale, and structure of synthetic drugs production in Canada, with a particular focus on the province of Quebec. The study’s findings indicate that: 1) smuggling patterns at the country’s border are scattered with no indication of an organized or concentrated system of traffic; 2) synthetic drugs production is not high enough to substantiate a significant exportation potential; and 3) contradictions in the pricing and quality of synthetic drugs at the retail level indicate an unsophisticated and typically immature consumer market. Overall, the synthetic drugs market in Canada emerges as a decentralized, largely localized, and young phenomenon, thus, making it an unlikely significant source of supply or threat for the U.S. and beyond.

Appendix: An economic model to estimate the number of ATS labs

The basic outline consists of the recognition that these are businesses that are consequently subject to many of the same pressures facing legitimate enterprises. Illegal producers must make a rate of return that is at least as great as that which is received by other legitimate activities¹¹; additional risk from both competitors and from law enforcement must be compensated by a higher rate of return; and, producers have to pay people who work for the business a competitive wage whether in goods in kind or in cash.

It is possible to identify the rate of return (ρ) of the operation as the value of sales (Q) times the price (P) less costs (C) relative to total cost:

$$ \rho =\left(P\times Q-C\right)/C $$

(2)

But ATS lab operations also face operating risks not faced by legitimate businesses: they run the risk of losing their product from raids by the authorities. This is not the same kind of business risk faced by legitimate operators who may also lose their product due to fire, flood, and so forth. Illegal operators are not able to insure their equipment or product and that raises the risk. To model this risk, assume that the producer faces a probability, π, of losing his production. This means that the expected value of the production that is being brought to market is reduced by that risk to (1- π)xPxQ.

At the same time, we need to recognize that the rate of return faced by the producer must be augmented by the risk he bears. This means that the rate of return, ρ, should be augmented by the risk so that the correct measure of the return is ρ + π. This leads to an equation that permits identification of the size of the ATS production industry in Canada:

$$ \rho +\pi =\left[\left(1-\pi \right) xPxQ-C\right]/C $$

(3)

Equation 3 permits identification of the size of the industry. The probability of being discovered by police (‘busted’), π, can be calculated as B/T where B is the number of ATS lab “busts”, and T is the total number of labs. “B″ is known from police data. “T” is to be calculated. We know the rate of return to small businesses, ρ, as it has been the same for the past fifty years or so: 10 %. We use a figure of 50 % below in illustrating different estimate scenarios. We know the value of production for the average lab operation from police busts across the province. We can calculate the cost of operating an ATS lab. In terms of Eq. 2 above, we know the values of all the variables, ρ, P, Q, and C, and we know the number of “busts”, B. Eq. 2 can be solved for T, the total number of ATS labs.

Drug specific data on ATS seizures involves very small numbers, and some uncertainty in regards to actual drugs being produced. In their survey of synthetic drug production in B.C., Diplock et al. [13] reported that 27 of the 33 files analyzed involved methamphetamine labs, five were ecstasy labs, and one was a GHB lab. They note that 7 of the 27 methamphetamine labs were set up to produce ecstasy as well. The RCMP [37] reported that, among the 45 synthetic drug lab seizures in 2008, 12 were ecstasy labs and 21 were methamphetamine labs. Given the results presented in Diplock et al. [13], however, and the small number of labs involved in seizures annually, we are not confident enough in the distinction between the type of synthetic drug lab to produce drug specific estimates. With little data on ecstasy production available at current time, we make the assumption that the cost structure of ecstasy production is comparable to what is derived for methamphetamine below.

We derived a partial estimate of the cost structure of methamphetamine production.¹² It takes about 10–20 mg to have an effect in controlled conditions [20]. The assertion is that there are roughly 110 doses per ounce or 3.88 doses per gram. If we take the smaller amount, we have about 10 doses to the gram. If methamphetamine retails for $25 per quarter gram and $100 per gram, then one dose is $10. If you have 110 doses per ounce and 28 g/oz., then each gram yields an average hit of 250 mg. We assume that the total investment needed for a one ounce production of methamphetamine is approximately $200 plus the cost of anhydrous ammonia and the labor cost of production which should take the better part of a day (this is for a small lab since larger amounts are produced by labs and “super labs”.) The cooked product is diluted to become two to three ounces and sold for approximately $1500 an ounce, although this may vary by region. Labor costs and risks are not included in the assessment.

The value of a gram of methamphetamine is assumed to be worth $100, which is consistent with the UNODC [44] retail estimate. The wholesale price reported by UNODC is $22,086/kg. Following Eq. 3, with 50 ‘busts’ of methamphetamine labs and an assumption that the cost of producing an ounce of methamphetamine is $200 worth of materials plus another $200 in wages for the producer and another $100 for rent and protection, yields unrealistically small estimate of the number of labs outstanding. The number of doses produced in a small lab will nonetheless be substantial, amounting to revenue of $2800.

A more conservative approach to the economics of methamphetamine production leads to an estimate of the number of producers that is significantly greater. In particular, if we believe that the cost of production is higher than the simple value of the ingredients since there is an apartment to be rented, risk attached to the purchase of the materials, and the possibility of permanent injury during the process of production, combined with a higher rate of return required on the production process leads to an estimate of the number of ATS labs to about 1400. The assumptions are that the value of production is $100 per gram, that a return of 50 % is required, and that the cost of production is about $1800 an ounce. With 50 busts a year, this would imply a detection rate of 3.6 %, which would be 3 times lower than the rate for cannabis cultivation sites in Quebec [4, 5]. Decreasing the cost assumption to $1700 yields an estimate of 560 labs, for a detection rate of 9 %. Another $100 decrease produces an estimate of 350 labs (14 % detection rate). To refine this estimate and get a stronger sense of the number of labs, we need data from the larger labs so that their economies of scale and cost of production can be more systematically developed. In the absence of better data on ATS labs in Canada, a 560–1400 range appears to be plausible, especially given the amount of methamphetamine and ecstasy seized in 2007–2008 [44, 45].¹³

Table 4 illustrates how estimates are sensitive to a change in the cost parameter, which we make vary from $400 to $1800. This method also relies heavily on the number of labs detected – a significant change in the number of labs detected would produce a significant change in the prevalence estimate. Variations in costs across this range would lead to estimates of the number of labs (N) from a low of 64 to a high of 1400. The probability of discovery (π) also decreases radically (from 0.79 to 0.04) as the costs or estimated number of labs increases.