OECD, 2nd Task Force Meeting on Charting Illicit Trade - Jeannie Cameron
A CASE FOR PROXY INDICATORS TO MEASURE ILLICIT TRADE
JEANNIE CAMERON & GRETCHEN PETERS
Co-Chairs of the OECD Taskforce on Charting the Illicit Trade in
Environmentally Sensitive Goods and Wildlife
OECD – Paris, 5-7 March 2014
TASKFORCE ACTIVITIES 2013
Establishment and composition of the Taskforce
APEC Pathfinder Conference, Bangkok, September 2013
UNOTC Workshop, Vienna, December 2013
Emergence of Proxy Indicators as our proposed measurement methodology
Verification of our approach by the OECD Statistics Department
THE PROBLEM WITH MEASURING ILLICIT TRADE
Do we need an alternative form of measurement?
Direct measurement has limitations - it is not necessarily accurate, precise and nor is it
likely to be replicable etc.
Primary data on the amount of illicit trade is normally collected through enforcement
activity, which is then translated into its $USD equivalent.
The raw data is usually in the form of “quantity” (kg., people, carats) and “frequency” –
the number of illegal trades in a time period.
The data is collected by a combination of random sampling at ports and selective
sampling of planned interventions.
The reliability of the data is seldom, (if ever) tested by co-investigators and the precision
is questionable as the range in estimates is often larger than the lower value of the
This problem is particularly acute with a subject matter as diverse at Wildlife/EST.
that impact illicit trade generally
For the purpose of rating a country or a region “at risk” of illicit activity, it can be
useful to consider independent variables that tend to heighten or reduce
opportunities for organised crime to occur.
Measuring these independent variables can help policy-makers and donor nations
rate whether a certain region or country is more or less likely to have high levels of
organised crime occurring.
For the purpose of this project, our group identified the following independent
variables which can have an impact on illicit trade generally:
Level of budget to prevent illicit trade
Relative strength or weakness of laws, banking
Relative strength or independence of judiciary
Capacity of law enforcement / police (this relates to
Presence of insurgency / terrorism
Presence of UN and/or other foreign peace
keeping or stability operations
High levels of scarcity, unemployment, health
of commercial economy
Porous borders, coastline
Geographic location (along transit route,
near a major consumer nation)
specifically impacting illicit trade in ESG/wildlife
We also examined independent variables that could make an impact on ESG/Wildlife
Levels of domestic consumption of the illicit commodity
Presence of licensed trade (domestic and/or international)
Tax revenue generated
Relative strength or weakness of wildlife/ESG laws
Relative strength or weakness of services protecting natural areas, such as parks
Levels of cooperation among law enforcement agencies (police, customs, wildlife, forestry, fisheries, etc.)
Existence of wildlife enforcement networks, inter-agency task forces, national environmental task forces
(INTERPOL NESTs) as a measure.
Presence of wildlife and/or ESG (such as hardwoods, minerals, fish)
Not an alternative, but a complementary form of measurement
What is a proxy? It is an indicator ‘linked’ to a particular illicit trade/activity
rather than correlated with it. It can reveal whether illicit trade is rising or falling in
a particular area.
Proxy statistics are typically used in systems where primary data is difficult to obtain
with any certainty or where the outcome is difficult to define.
For a proxy statistic to be useful it needs to be correlated (positive or negative) with
the independent variable of interest, but does not necessarily need to be
dependent or causal.
Advantages of this approach (a) concerned with prevention rather than
enforcement – enforcement is important but after the horse has bolted (b) Proxy
indicators shed more light on social harms than direct measurement when used to
measure illicit trade.
Examples: Timber, Mining, Fishing, Waste, Wildlife
LIMITATIONS OF THE USE OF PROXIES
The best we can hope is that proxies will be a lead or a lag indicator to the
scale, scope or trend of illicit trade. This in itself might add a useful tool to
policy makers to gain a quick and reliable indicator of the outcome from a
change in policy or resource deployment.
To be clear, the use of a proxy for illicit trade is unlikely to provide an accurate
absolute measurement of illicit trade.
CAN LICENCING BE A PROXY FOR ILLICIT TRADE?
The amount of licenced trade in any time period is not in itself a very
interesting variable as it contains both licit and illicit activity. But, if we find
that there is a correlation between “the number of licences issued” and the
“amount of illicit trade” we will have found a proxy.
TESTING THE PROXY HYPOTHETHIS
Using experts in each field, those with specialist knowledge of potential proxy indicators, to draw up
the list of proxies which are then validated by local people and practitioners
To test the value of a particular proxy for illicit trade we propose a test to confirm
they are statistically correlated using existing data gathered over a minimum of 3
We would have to acquire a minimum of three separate paired data sets gathered
over a period of time sufficient to generate significant number of data points and
use a statistical test to establish correlation – but not dependence or causality.
The results of this test will then determine the merit in exploring this approach
further. One way to explore the use of the proxy further would be to conduct a
blind test on additional sets of paired data.
The clandestine and opportunistic nature of illicit trade makes it difficult to gather
data and the lack of proven models of illicit trade make it difficult to test hypotheses
and validate data. There is the prospect, that certain proxies can help policy makers
measure the rate of illicit trade. A statistical test for correlation is suggested as a
means to establish the proxy.
MEASUREMENT FRAMEWORK TO MONITOR THE EFFECTIVENESS
OF ANTI-CORRUPTION POLICIES