Interpreting economic data is difficult enough for
even the most trained practitioner, let alone those less
skilled. You see, in many instances the quality of
reported statistics both in the U.S. and abroad is
suspect at best. More often than not, those closely
watched numbers represent only best-guess
estimates and are frequently subject to revision.
Moreover, despite the inherent level of uncertainty in
the numbers, many media outlets appear to find one
rule widely applicable: never let the facts get in the
way of a good story.
Granted, I’m not breaking new ground here. Even
the Federal Reserve (the Fed)—with all of its
information gathering ability—often finds itself relying
on less than complete information and, as such, goes
to great lengths to inform investors of that very fact.
That said, in response to the Fed’s and others’
concerns, governments and private data services
around the world are implementing programs to
improve the accuracy, timeliness and usefulness of
the statistical samples so critical to policy decisions.
However, as I see it, the problem is that most, if not
all, of the methodologies employed arguably capture
data on traditional economic activity that, while useful,
bears little resemblance to the evolving economies of
the 21st century.
For example, consider just two of the growing
number of factors that affect investors’ ability to
ascertain economic reality from the data.
- Globalization - An ever-increasing proportion
of trade and investment decisions are now
made on a multinational level. How should
such transactions be captured in the data?
Conventional methods seem inadequate or
unrealistic as businesses off-shore, outsource
and contract components on a global basis. In
essence, capacity utilization is no longer
limited by geographical location.
- Intellectual Capital - Most data-gathering
methodologies are constructed to track the
production and movement of physical goods.
In that an ever-increasing amount of economic
activity relies on software,
telecommunications, financial services and
intellectual capital, how can investors be
certain that such activity is properly detailed,
reported and interpreted?
Yet investors can’t ignore the role data plays—it
shapes market opinion. Therefore, I suggest investors
gain an understanding on how to properly use it. My
practical guide to evaluating the utility of statistical
data includes consideration of these five factors:
(1) Is it relevant? What does the data reveal about
established trends in the economy? Does the data
represent the status quo or a change? And if it’s a
change, is it imminent, gradual, expected or
unexpected?
(2) Is it timely? To be of any use, the data must be
current.
(3) Is it readily available? While the government
does produce volumes of statistical data, a vast
amount is only available through obscure sources.
The discovery of gems of information may make for
interesting academic studies more so than
appropriate investment guidance.
(4) Is it reliable? Any statistical series that moves
erratically is of little use in the short run. While the
number may be interesting to the press, it usually has
little value to investors.
(5) And perhaps most importantly: What does it
mean in perspective? All too often, investors neglect
to consider that data expressed in percentage terms
is sometimes less meaningful than when considered
in absolute magnitude.
Statistical noise is part and parcel of the
investment landscape. However, as I see it, the astute
investor understands just because the noise level is
elevated does not pre- ordain that it is correct.
This material has been prepared using sources of information generally believed to be reliable. No representation can be made as to its
accuracy. The forecasts and opinions in this piece are not necessarily those of Van Kampen, and may not actually come to pass. Information
in this report does not pertain to any Van Kampen product and is not a solicitation for any product.
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