413047-Underground-Commercial-Sex-Economy

its components. That is, instead of relying on absolute numbers (such as the number of participants in the
underground commercial sex economy), we can use relative information of the form, “The underground
commercial sex economy in Atlanta is 10 percent bigger today than five years ago.” We believe relative
information can be more reliable.
There are two types of relative information that we sought to use: cross-city comparisons and over-time
comparisons. If we have two time periods, eight cities, and three items (sex, drugs, and weapons), then we
need 2 x 8 x 3 = 48 pieces of relative information. Through our interviews, we were able to obtain relative
information on the underground commercial sex economy from pimp interviews. We believed many
pimps would be able to say, on the basis of their experience, something to the effect of “The underground
commercial sex market in Atlanta increased by 20 percent between 2003 and 2007.” Similarly, since
many pimps operated in multiple cities, we believed that interviews would be able to provide judgments
such as, “In 2007, the underground commercial sex market in Miami was twice what it was in Denver.”
However, this information alone is not enough to estimate the actual sizes of the underground
commercial sex markets in any of the cities at any of the points of time. Because the underground
economy is made up of different types of activities, to estimate the size of each component, we need
relative information about each component. In other words, we need analogous information on the drug
and weapons markets. To obtain this information, we rely on proxy variables. Formally, we require that
proxies are proportional to the underlying activity. This is best demonstrated by an example. For instance,
if the number of drug-related emergency room visits in Dallas is 30 percent higher than that in Seattle, it
might imply that the drug market in Dallas is 30 percent larger than that in Seattle. If we have enough
pieces of relative information (specifically, 48 of them) and estimates of the total size of the underground
economy (using methods developed by past researchers), then we can calculate the total size of the
underground commercial sex economy, the illicit drug market, and the illicit weapons market in each city
during each year.
This was our original proposed methodology; however, we soon encountered several key challenges. First,
our original plan involved using methods of past researchers to estimate the size of the underground
economy. Unfortunately, upon closer inspection, it was clear that these approaches required data and
assumptions that were only viable for national-level analyses. While a large and well-developed literature
has sought to estimate the size of the underground economy, we found no studies that did so at the local
level, nor any studies that had proposed methods that could be used for this.
Instead, we decided to rely on a dataset maintained by the Board of Governors of the Federal Reserve
System. This dataset includes currency distributions and collections through a number of locations
around the country. The idea was that this subnational data on currency could be used to estimate the
cash in circulation for areas surrounding each of our eight cities. With estimates of total currency in
circulation, we could add a fourth item: “other uses of cash.” We would need to identify a proxy for this
fourth item, but other than requiring us to collect 2 x 8 x 4 = 64 pieces of relative information instead of
48, this would have a minimal impact on our approach. There was one important implication. Since we
would base our estimates on currency calculations, we would be restricted to only studying the cash-based
illicit markets for sex, drugs, and guns. Extensive interviews with UCSE experts and stakeholders and
relevant research suggested that this was not a major limitation.
We believed that the necessary data from the Federal Reserve could be obtained through a Freedom of
Information Act (FOIA) request. Unfortunately, our request (and subsequent appeal) was denied.
Therefore, we chose to adapt national-level data to localities. We calculated the national ratio of currency
in circulation (throughout the country) to gross domestic product (GDP). Adjusting for population, we
applied this ratio to city-level GDP, available from the Bureau of Economic Analysis. This yields an
estimate of currency in circulation for each metropolitan area in our sample.
With estimates on total currency for each city in our sample, we needed information on the relative size of
the various underground economies (as well as on other uses of cash 32 ). Our original approach involved
32 “Other” uses of cash include legal economies and underground economies, excluding sex, drugs, and weapons (e.g., fake goods,
money laundering).
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