The Price of Illicit Drugs: 1981 through the - The White House

Corresponding predicted real prices per pure gram for this set of nominal expenditures were
obtained by deflating and then inverting these predicted mean amounts. The average retail price
(in 2000 dollars) for a given city and quarter was then obtained as the weighted average of the set
of 10 prices, with weights coming from the DUF-based cocaine and heroin price distributions
described above. For a given quarter, the 30 city means were then multiplied by their respective
DAWN weights and the sum of these contributions provided a weighted estimate for the mean
price and mean purity in the U.S. for that quarter. The national results are show in Table 5 and
Figures 2 and 5.
5. A Model for Purity
Given sufficient data, we could have estimated the mean purity for each city in each quarter by its
sample mean. For a given quarter, a weighted average of these 30 city (29 large U.S. cities and the
Rest of U.S.) sample means would have provided a sensible quarterly estimate for the mean purity
in the U.S. for that quarter. However, given 30 cities and 78 quarters, this would require 2,340
sample means for each level of distribution for each drug, and this requirement goes well beyond
the resources of the STRIDE database. For each level of distribution for cocaine, Table A10
contains the percentages of these cell means that do not have data. This section describes a
feasible alternative to simple tabulations.
In order to estimate 2,340 cell means from a database containing less than 2,340 cells of data,
some form of modeling is necessary. The linear model provides a straightforward possibility:
E(purity itj ) = + city i + time t (3)
V(purity itj ) = 2 (4)
However, both of these specifications are implausible for the purity data. First, the mean purity
must lie in the unit interval, but (3) does not impose this restriction. Second, the variance of purity
depends on its mean (it is higher around 0.5 than 0.9), but this is not embodied in (4). The first
problem was particularly important for our data, as the linear model gave impossible estimates for
purity for several cities in several quarters. We avoided both problems by working with a quasi-
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