Some mergers work better than others, and the question of why has been a
subject of intense interest to researchers. Are firms that are similar better
merger candidates? Gerard Hoberg, assistant professor of finance, and Gordon
Phillips, Bank of America Professor of Finance, recently developed much richer
data to understand firm relatedness and more accurately predict merger success
Financial research has historically focused on the numbers in company
filings—the accounting statements. But the words which compose the vast bulk of
those documents have been virtually ignored. Hoberg and Phillips used
Web-crawling techniques to examine the vocabulary in the filings of all publicly
traded companies over a ten-year period—over 50,000 filings—through the
Securities and Exchange Commission’s Electronic Data Gathering, Analysis, and
Retrieval system (EDGAR).
Hoberg and Phillips represent this information in a 3-d format that looks
like a globe. Every product developed by every firm that filed 10Ks through
EDGAR is represented at a point on that globe—with congested clusters at points
where many products exist, and empty places where no products exist. This
geometric representation of the product space allows researchers to measure the
degree to which firms are related in a much more precise manner. “What we have
that other metrics for relatedness don’t, is that we know where every firm is in
a well defined space, and so we know the degree of relatedness as well as the
direction.,” says Hoberg.
With this data, Hoberg and Phillips analyzed how similarity and competition
affect mergers. Existing studies of merger pairs measure similarity by asking if
both firms reside within the standard industrial classification (SIC) codes used
in company filings to the SEC. Hoberg and Phillips find that most merger pairs
are far more similar than other methods of classification would suggest. Even
merger pairs with different SIC codes generally had a high degree of similarity
with each other.
One of the benefits of the model is its ability to show the similarity
between firms not in the same industry. The authors cite a merger between
Antheon, a firm that produces military intelligence technologies, and General
Dynamics, which is a traditional military firm that makes ships and tanks. Past
ways of measuring similarity would have labeled this merger pair as dissimilar
because their SIC codes are different. But the similarity that drove this
successful merger was the fact that both firms work with the military.
It is new products that generate the profits in such mergers. What is the new
product here? “Probably classified,” says Hoberg. “But I can guess that if you
had access to real-time intelligence and you could link it into the technology
aboard military equipment, the military could have a much better, quicker
response to crises. Now General Dynamics can sell the military a more integrated
product that would have more value.”
Hoberg and Phillips found that firms were more likely to merge with partners
whose language describing their assets was similar. These mergers were more
likely to result in increased stock returns, longer-term gains in cash flow and
higher growth in their product descriptions—evidence of new products being
Mergers were most successful, and resulted in improved profit margins, when a
firm merged with a target that was similar to itself, but different enough from
its rivals to differentiate its product offerings. Firms with a higher potential
for unique products, as captured by patents, copyrights and trademarks, are more
likely to be involved in acquisitions.
Gordon Phillips sums up the research, saying, "Managers frequently cite
synergies for a motivation for mergers. However existing research has not been
able to find existence or benefits of synergies. Our research shows that many
related mergers do produce increased cash flows and new products that will
benefit firms and their shareholders."
Hoberg and Phillips re-draw their Variable Industry Classification sphere
every year. That enables them to see the product space evolving as companies
merge and new products are created.
“Product Market Synergies and Competition in Mergers and Acquisitions: A Text
Based Analysis” is forthcoming from the Review of Financial Studies.
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