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Forecasting the Presidency

From the Deseret News, September 4, 2012

You may have noticed there is a presidential election coming up.  The Republican Party met this past week in Tampa, Florida and officially nominated Mitt Romney as their candidate.  Democrats are meeting this week in Charlotte, North Carolina to renominate President Barack Obama.  Of course all that really matters is the counting of electoral college votes, and those will be decided on November 6th.

In the meantime, however, it is at least entertaining to try and predict which candidate will win.  There is no shortage of opinion, of course.  In the past week I have read that an Obama win is a sure thing, that Romney is sure to win, and that the election is too close to call.

Rational Expectations?

This article came out in the Deseret News on Tuesday, October 18th.

Last Monday the Nobel prize in economics was awarded to Tom Sargent and Chris Sims.  Both are well-known macroeconomists and both have worked on economic issues relevant to the 2008 recession and recovery.

Forecasting the future of the economy is tricky business.  For one thing it is very complicated, with millions of goods and services changing hands.  Another reason is that it is subject to changes in the economic environment that are not economic in nature; weather and politics being two good examples.  Forecasting how the economy will behave requires simplifying models that capture most of its features without adding too much complexity.  Over the years, economists have developed increasingly sophisticated ways of doing this.

By way of analogy consider the portion of U.S. Highway 6 that runs between Spanish Fork and Price.  I drive this stretch of road on occasion on my way to the San Rafael Swell.  The road goes up Spanish Fork Canyon, over Soldier Summit, and down Price Canyon.  It is necessarily winding and steep in many places.  Suppose you were tasked with forecasting the fate of a convoy of vehicles traveling over this road.

A simple first stab at the problem might involve using elementary physics.  The vehicles have given weights, they travel at certain speeds over different portions of the road, the road's gradient and curvature are known.  Based on this information you could, with some effort, derive a forecast for the progress of the convoy.

However, to improve your forecast, you might also consider the weather.  Unfortunately, the weather is changeable.  You have a general idea of conditions, but the specifics at each point on the road are not known.  Furthermore, these conditions can change unexpectedly.  You need to make a best guess and factor this into your forecast.  You will also need to update it as the convoy progresses and available information changes.  The same principle applies to other factors like the mechanical condition of the vehicles, and the mental condition of the drivers.

When you make your forecast you realize that it is only a best guess.  It is subject to change due to factors that are difficult to predict.

If you had some control over the highway or the vehicles you might be able to reduce the chances of a serious slowdown or pileup.  Suppose you had a radio controller that could uniformly boost or reduce the amount of fuel all the vehicles consume.  If conditions looked dangerous you could dial down consumption of gas, slow the convoy down, and reduce the chances of something bad happening. 

 

This type of forecasting and policy recommendation corresponds roughly to state-of-the-art economic forecasting prior to the introduction of Rational Expectations theory thirty to forty years ago.  Tom Sargent was an important contributor to that literature.  Chris Sims' contribution was to develop statistical techniques that identify how economic variables influence each other as time progresses.

When you cut back gas consumption you assumed this would make the cars go slower.  However, drivers are not automatons and they adjust their driving behavior based on the conditions they observe.  They do this by gathering all the relevant information they can: direct observation of the road through the windows, listening to the radio, talking with other drivers on cell phones, etc.  When things look dangerous, they slow down on their own.  If you dial down the gasoline flow, drivers will simply push harder on the accelerator to compensate and will maintain the speed they think is best.  .  Ignoring the responses of the drivers (decision makers) in the convoy (economy) to your manipulation of the gas flow (economic policy) gives bad forecasts.  Good forecasts will incorporate these rational responses.

The 2008 financial crisis and recession have been held up by some people as evidence that Rational Expectations is incorrect.  If decision makers are gathering information and processing it effectively, how could they have missed the subprime meltdown?  Why did they ignore the warnings of those who were warning against just such a meltdown at the time?

Go back to the convoy.  Suppose you have a fellow forecaster who believes the brakes on a large semi-truck are about to fail.  As the convoy makes each turn along the route he announces over the radio to all concerned that the semi is about to run out of control, tip over, and cause a massive pileup.  However, for the first several turns the brakes hold and the convoy continues on unharmed.  Eventually, everyone discounts his predictions of doom.  If the brakes finally do fail, it comes as big surprise to almost everyone.  Why did drivers not foresee the crash?  Why did they ignore the voice on the radio?  Because the problem was small, subtle, not readily apparent to anyone but an expert, and the exact moment of failure was largely random.

The problem is not that the forecasting methodology is wrong.  Rather, it is that unexpected or difficult to predict events can in some circumstances have huge consequences.  They are easy to see in hindsight, but not so easy to see before they happen.  One message the Nobel committee sent was that rational expectations is still an important piece of economic theory.

Authors

  • Richard W. Evans is an Assistant Professor of Economics at Brigham Young University

  • Jason DeBacker is an Assistant Professor of Economics at Middle Tennessee State University

  • Kerk L. Phillips is an Associate Professor of Economics at Brigham Young University