September 2, 2010
At the outset of this project we decided that, to understand what was happening with the price of
food regionally and globally, we would investigate the price movements of a number of key
agricultural commodities (wheat, rice, corn etc) in those countries that we had identified as
important, as determined by the country’s geopolitical significance, role in the world food
markets or whether it was, or had the potential to, experience a food ‘crisis’. Our thinking was
that crosschecking that ground-up price data against our top-down understanding of the physical
developments of the actual commodity (i.e., production, consumption, trade and reserves) — in
keeping with STRATFOR’s view of economics — we’d be able to better understand why food
prices were increasing, and should be able to determine why countries were ‘at risk’, or would be
soon.
We ran into a number of practical problems that complicated our task, particularly our ability to
ascertain and compare countries’ situations:

The definition of ‘food’ varies per region, as do particular foods’ relative importance to a
country’s economy (in terms of citizens’ spending as a percent of total income, on that
food, and/or in terms of the foods’ importance to citizens’ diet).

The dodgy, incomplete, out-of-date or non-existent data sets neither made us less than
completely uncomfortable with our assessments, nor were they strong enough to
reconcile (seemingly?) conflicting data points, stories or intelligence.

How do we define what constitutes a ‘problem’ for a country
As explained above, we initially approached the question from a very top-down macro sense, the
approach. We began our examination at the highest level—30,000 feet— and tried to work down
from there— (1) we began with a commodity (2) identified the countries in our sample for which
that country was most important, (3) found the P, C, T and R, and (4) then checked this, as best
we could, against our price data. However, (1), (2) and (3) only took us down to 10,00 feet, and
even when we checked it against reliable ground-level data, we still couldn’t know what was
happening between those last ten thousand feet. Obscured by the proverbial clouds, we could not
understand when, where or how a food crisis would occur because we didn’t know (a) what was
driving prices, (b) what would constitute a crisis in that country, or (c) if there were a crisis, if
we’d even care.
We’re going to approach this question in a different manner. This will require a degree of
creativity and imagination on behalf of our AOR teams, but it will greatly simplify our task.
Myself and the research team will of course be available to discuss any specific questions that
you have or that may arise.
Essentially, we want to ‘begin at the end of the maze’, in the sense that instead of relying on the
data to suggest crisis potentials, we want to just imagine what a food crisis—that STRATFOR
would care about— in a country would look like, and then we just have to look at whether those
conditions are being met. In other words, we’re looking for the sufficient conditions that would
either precipitate an event or chain or events that STRATFOR would necessarily care about.
Standalone event: since, for example, Beijing food prices rising 50% will always be important,
we would then just look for prices moving towards that threshold, leaving behind all the intricate
complexity of what drives food prices where in which country when.
Chain event: similarly, while we may not necessarily care if food prices in Cambodia rise
substantially, but if it leads to militant activity that spills over in Thailand, we would care about
that.
By imagining our own food crises, we will essentially already know all the ‘right answers’, we
just need to look for events to be moving towards our sufficient condition, or the ‘showing of
work’, if you will. It will not only enable us to potentially identify events that would normally be
lost to the fog in those remaining 10,000 feet, but also the narrowing of scope will enable us to
greatly increase the precision of the project.
As a first step, I would just like the AORs to start thinking about what the most probable ‘food
crises’ would look like.
The research department and I are working together on creating a ‘questionnaire’ that will help to
further inform how we think about the conditions sufficient for a crises.