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CORRUPTION

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Interview with Raymond Baker<br />

International Affairs Forum<br />

dividends, or sending dividend payments abroad.<br />

What it can do in its trade relationships with its<br />

parent is to misprice trade, either overpricing<br />

an import, so that it pays an extra amount to<br />

the parent company, or underpricing something<br />

it is exporting to the parent, in order to shift<br />

value to the parent. It is the over-invoicing and<br />

under-invoicing of imports and exports that<br />

gives traders the ability to move money at will.<br />

This enables the muddying of capital and trade<br />

transactions, in order to facilitate the flow of<br />

resources out of emerging markets in developing<br />

countries.<br />

What are the impacts to developing countries<br />

as a result of illicit financial flows?<br />

In my opinion, there is nothing more damaging<br />

to developing countries than the loss of massive<br />

amounts of revenue that are bleeding abroad.<br />

It directly impacts poverty and it is inadequately<br />

addressed. It means that the economy does not<br />

have as much money in it as it would otherwise<br />

have and that governments do not have as much<br />

tax revenue as they would otherwise have. Illicit<br />

financial flows also contribute to inequality of<br />

income and the growth of that inequality. It has<br />

all the negative effects that you can imagine from<br />

massive amounts of monies draining. And, in<br />

most cases, they are drained permanently out of<br />

emerging markets and developing countries.<br />

Much of your work centers on data collection,<br />

research, and analysis of illicit financial<br />

flows. What issues have you experienced<br />

trying to obtain good, reliable data for your<br />

research?<br />

We take a couple of approaches to this. First,<br />

we base our analysis entirely on data filed by<br />

governments with the IMF. We also use UN<br />

Comtrade data, broken down by countries and<br />

commodity groups. However, there can be errors<br />

in this data, such as statistical errors. There can<br />

be intentional holes left in the data, and so forth.<br />

Imperfections in the data can reduce the level of<br />

illicit flows that we measure, or increase the level<br />

of illicit flows that we measure. As previously<br />

mentioned, we think that if we had perfect<br />

data, the data would show more than a trillion<br />

dollars are flowing out of emerging market in<br />

developing countries. The reason for this is that<br />

there are a lot of things not included in the data<br />

that is provided by governments to the IMF. For<br />

example, cash transactions and across border<br />

cash transactions that are used by drug dealers,<br />

human traffickers, and counterfeiters, do not<br />

show up in official statistics.<br />

Secondly, none of the misinvoicing of services<br />

and intangibles shows up in the data because<br />

the IMF does not compile data on the trade of<br />

services and intangibles. That is estimated to<br />

be about twenty-five to twenty-eight percent of<br />

global trade.<br />

Furthermore, in the business of misinvoicing, if<br />

the misinvoicing is agreed to by the buyer and<br />

the seller in a transaction, and that misinvoicing<br />

is included in the invoice that is exchanged<br />

between the buyer and the seller, it does not<br />

show up in our data. The only misinvoicing that<br />

shows up in our data, is where it has been reinvoiced.<br />

In other words, the seller sends the<br />

invoice to, for example, a tax haven entity, which<br />

re-invoices at a higher or lower amount and<br />

sends the invoice onto the buyer. But where the<br />

misinvoicing is agreed to, between the buyer<br />

and the seller, and it’s simply the original invoice<br />

is manipulated, this also does not show up in<br />

our data. So there are a lot of elements of both<br />

the corrupt departmental and the commercial<br />

components that don’t show up in our data. We<br />

believe that if we had better data on those, the<br />

numbers would be considerably higher.<br />

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