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 (online 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.