Smart sanctions and the US government's use of the best company data to measure them

By Alistair King, content manager, Bureau van Dijk

When Russia seized power in Crimea in 2014 the West was criticised in certain quarters for what some commentators felt was a toothless military response.

As a politically neutral company information provider, we won't argue the rights and wrongs of what happened, or offer an opinion on either side's actions.

But often overlooked is that hefty economic sanctions were imposed. One of the most common strategies governments take to force other countries' hands, their efficacy is sometimes questioned. But methods are evolving. Blunt, country-wide sanctions are making way for "smart", targeted sanctions of individuals and entities, aimed at limiting economic "collateral damage".

And perhaps most intriguing for business- and compliance-minded people is whether the economic impact on these targets can be measured – that, and the tricky exercise of identifying who you should or shouldn't be doing business with because of direct or indirect sanctions on them.

The first question is also gaining traction at the US State Department. So much so that back in 2014 researchers from its Office of the Chief Economist (OCE) first met Tom Baskind, head of the government team in our Washington, DC office, to discuss collaboration.

At that stage the main issue was whether our global Orbis database of more than 200 million private and public companies could provide some of the detailed, structured data needed to produce an important academic report – or "Working Paper" – that the OCE had recently commissioned.

The answer is that it could, and the statistical analysis it facilitated is very watertight.

As well as demonstrating the power of Bureau van Dijk's databases in identifying sanctioned entities and individuals across international borders, the study that arose from their extremely rigorous work makes fascinating reading.

In this blog post, we'll take a look at their key findings and the data behind them, leaving you with an opportunity to download the full working paper and a better idea of how we can help you in your own sanctions research.

Background and headline discovery

Measuring smartness: understanding the economic impact of targeted sanctions is the result of collaboration between two academics: Dr Daniel P. Ahn, Deputy Chief Economist at the US Department of State and Professorial Lecturer at the Johns Hopkins School of Advanced International Studies, and Dr Rodney D. Ludema, Associate Professor of Economics at Georgetown University.

Ultimately with the White House as its key target audience, Ahn and Ludema's paper set out to provide "empirical estimates of the impact of targeted sanctions, focusing on the case of sanctions deployed by the United States and the European Union against Russia after its intervention in Ukraine in 2014 as a natural experiment".

To achieve this they needed to use "detailed firm-level data," which is where Bureau van Dijk's Beau Richardson stepped in to help in 2015, following earlier meetings with Vice President, Tom Baskind.

Ahn, who joined the project the same year, was already familar with Bureau van Dijk from his time at Harvard Business School, and he worked with Richardson and others to scope out a number of data-related tasks, including blending Bureau van Dijk information with various internal and external sources cited in the paper.

Based on analysing several years' worth of rich, structured data on Orbis, Ahn and Ludema concluded that "the average sanctioned company or associated company loses about one-third of its operating revenue, over one-half of its asset value, and about one-third of its employees relative to their non-sanctioned peers".

How did they do this and what's the context?

Smartness: an overview

In the introduction to their study, Ahn and Ludema point out that "[w]hile broad economic sanctions and trade embargoes have long been used as instruments of foreign policy, targeted sanctions focusing on specific individuals, entities, and transactions are relatively new".

Highlighting how the US and EU targeted a select list of Russian individuals and companies in March 2014, which escalated over the next two years, they explain that their study focuses on these developments, taking into account the significant confounding variable of fluctuating oil prices.

They emphasise that "[w]hether sanctions will ultimately accomplish [their intended] goals is a key question but is beyond the scope of this paper" but that "[u]nderstanding the impact of these targeted sanctions is essential to assessing their efficacy".

So their "paper uses pre- and post-sanctions data to measure the actual effect of sanctions and counter-sanctions from the macroeconomic shock".

Continue Ahn and Ludema in their paper: "To measure the 'smartness' of the sanctions' impact, we proceed in two steps. First, we examine whether the sanctions hit in the intended targets. We do this using data on individual firms from Bureau van Dijk's Orbis database."

And "Second, we examine the collateral damage. In particular, we consider [the] impact [of] the sanctions on Russian GDP and on its imports from the EU," which we won't dwell on in this blog post.

How Orbis data helped in their analysis

With respect to the Russia-Ukraine crisis, the paper splits sanctions into two broad categories:
  • SDN Sanctions: Blocking sanctions against individuals and entities on the List of Specially Designated Nationals and Blocked Persons (SDN) List
  • SSI Sanctions: Sectoral sanctions against entities operating in the financial, energy, and defense sectors of the Russian economy listed on the Sectoral Sanctions Identification (SSI) List

Orbis enables positive entity and individual identification, flagging up those that match names on these officially published sanctions lists. It holds detailed financials, as used as the basis of this study. And it carries information on directors, ownership structures and ownership percentages, that last dataset being crucial for determining controlling ownership according to OFAC's "50% rule". (OFAC – or the Office of Foreign Asset Control – is, of course, an agency of the US Department of Treasury, illustrating the cross-departmental nature of this subject.)


Much of which explains Ahn and Ludema's reliance on the database:

"[W]e track a universe of 78,381 companies [on Orbis]," their paper states.

"These include 433 specific companies identified as being sanctioned in Section III [of the paper] that are also present in the BvD database. The remainder is a control group of peer companies, constructed by collecting all companies that share the same home country and sector of business operation as the sanctioned companies in the global BvD database.

"For each company, we track its home country location, sector of business operation (according to the 4-digit NAICs code specification), and its total Operating Revenue, Total Assets, and Number of Employees for the years 2013, 2014, and 2015. We also track the status of the firm, whether it remains active or whether it has become bankrupt, liquidated or dissolved, or changed to some other non-active status."

We'll leave the empirical methodology, as outlined in Section IV of the paper, for those who download the paper. But we can confirm that it outlines a robust, data-dependent analysis that backs up the paper's bold conclusions and will open your eyes to this growing area of research.

We're delighted but unsurprised that our Orbis database played such a strong part in this important work.

Read the full working paper

Click to download your copy of Measuring smartness: understanding the economic impact of targeted sanctions. The paper contains:
  • A detailed introduction, setting the context of the research
  • A thorough literature review
  • A useful discussion of different types of international sanction and lists that publish sanctioned entities and individuals
  • An explanation of the paper's methodology
  • Charts and graphs to add further context
Download the paper.
 
 

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