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You Decide: Can we predict the economic future?
Story Date: 10/26/2012
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Source: Dr. Mike Walden, NCSU COLLEGE OF AG & LIFE SCIENCES, 10/26/12
I’m often asked to be a fortune-teller. Not the kind that uses the
stars or cards to predict personal relationships and happiness.
Instead, I’m asked to predict the economy, on everything from growth
to types of jobs to the stock market highs and lows. People think that
because I have a Ph.D. behind my name and because I’ve been at my
teaching gig for 35 years, I must be able to see things in the
economic future that others can’t.
Let me be the first to say I’m totally flattered when asked for my
forecasts. And, like most of my colleagues, I certainly have forecasts
and am willing to give them. Yet I always say to take my or any
economist’s projections not with a grain of salt, but with a ton!
Indeed, when I give forecasts, I always include some unpredictable yet
looming factor that might occur that could make my forecasts wrong.
That way I’ll have an excuse. Or I use the tactic (jokingly) given by
an economist long ago to never give a number and a date together. That
is, I can predict unemployment will reach 5 percent, but I won’t say
when.
I hope you realize I’ve been having fun with this topic, but it really
is a serious issue. Businesses, government and even households have to
make economic forecasts in order to plan successfully for the future.
For example, a county government has to make forecasts about the real
estate market and property tax revenues in order to plan a school
construction program.
Or like most states, the State of North Carolina is required to have a
balanced budget. Therefore, in order to know how much it can spend
next year, the state must have some prediction of the future condition
of the economy because that will largely determine the amount of tax
revenues.
The problem is that economic predictions -- even from professionals
like me -- sometimes (often!) are way off. Clearly the best recent
example is the housing crash, one of the most devastating economic
calamities in our history. In the opinions of most economists, the
housing crash is the major factor behind the deep recession we’ve been
through and the subsequent slow recovery.
And yet most economists, including yours truly, missed it. To my
credit, I am on record as saying the housing boom, which preceded the
crash, couldn’t be sustained. I simply couldn’t see average house
prices rising forever at 13 or 14 percent annual rates, as they did in
the mid-2000s.
But I thought those rates would gradually slow to the historic average
of 3 to 4 percent annually. Never did I see house price changes
turning negative, resulting in the average home losing one-third of
its value in the last five years.
So what makes economic forecasting so difficult? One reason is we’re
dealing with humans. Unlike my friends in the physical sciences
(chemistry, physics, etc.), who can run controlled experiments where
they can isolate factors and see if “A” causes “B,” we can’t do that
in economics. We can’t control for all the myriad of factors
influencing economic decision-making, even everyday decision-making
like what kinds of foods to purchase.
Another issue, quite frankly, is that economists in general aren’t
willing to take big chances in predicting major changes in the
economy’s path. Part of the reason is that we rarely see gigantic
swings in the economy’s direction. The broadest measure of our economy
-- gross domestic product (GDP) -- usually moves in a range of minus 1
percent for a low to 3 percent for a high. While making a prediction
outside that range will get an economist acclaim if correct, in the
vast majority of cases, it will be wrong. So inertia is a strong force
for economists, just as it is for others.
Maybe the simplest reason why economic forecasting is hard is because
forecasting the forces driving the economy is hard. For example, by
their nature, most discoveries, inventions and innovations are
unpredictable. The development and application of the microchip began
the revolution in information technology, which many compare to the
previous agricultural and industrial revolutions as game changers in
our economy. Yet who could have predicted 70 years ago the microchip’s
development?
Right now there are exciting innovations occurring in energy,
nutrition, robotics, nanotechnology and even manufacturing (3D and
“additive” manufacturing) that could completely restructure our and
the world’s economies. If and when these innovations materialize as
practical applications, they could spawn whole new industries and
expand or shrink others.
The realization of economic unpredictability creates an educational
challenge. If we don’t know where the economy will be in 10 years
along with the kinds of jobs that will be needed, how can we design
course offerings, fields of study and occupational training at our
universities, colleges and high schools? Do we need to worry about
today’s training being obsolete in a few years? What does this imply
for the debate between a broad, general curriculum versus specific,
occupationally focused training? And can technologically based
education (on-line courses, training “apps”) help shift educational
programs rapidly?
I can’t predict the answers to these queries (remember, I’m an
economist!). However, they’re some of the most thought-provoking
questions facing us. You decide how we’ll get the answers.
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