Stuffed Shirts vs. 'Skins: An Econometric Critic Tells How to Predict the Presidential Race
Graham, Edward M., The International Economy
For nearly two hundred years, journalists and other pundits have sought a rule of thumb (or two) that might accurately predict the outcome of U.S. presidential elections. Since 2000, this search must be informed by two important events: First, the possible breakdown of the venerable and highly accurate Washington Redskins standard. For fifteen straight elections, the Redskins accurately predicted the outcome of U.S. presidential elections: A win in their last home game of the regular season prior to the election indicated that the incumbent party would retain the White House. Alas, this failed to be the case in 2000; in their last home game, the Redskins crushed the hapless St. Louis Cardinals, and had the predictive power of the Redskins standard stood, Al Gore should have won the election.
But, now of course we have a complication: There are many who still say that Al Gore actually did win this election, or at least did so in the normal sense of "win." Thus, even though it is George W. Bush who sits in the White House, perhaps the predictive power of the Redskins standard was never meant to handle election irregularities in the state of Florida and weird Supreme Court decisions whereby a loser emerges as the winner. So, maybe, the Redskins standard indeed is a perfect role of thumb. On this, we might note that in the 2004 season, in their last home game before the election, the hapless Red skins will be hosting the mighty Green Bay Packers. Is the fate of George Bush in the hands of returning Redskins Coach Joe Gibbs? And even so, does this likely defeat for the Washington football club foretell the election of John Kerry?
The second event for election watchers was a move toward economic determinism, with Clinton's campaign motto "It's the economy, stupid" as emblem. The academic experts picked up on this trend. Yale University economist Ray C. Fair published a book in 2002 that uses econometric techniques to investigate all sorts of things, including but not limited to outcomes of U.S. presidential elections. (1) Fair's methodologies are claimed to have very general applicability; indeed, he also investigates whether people are likely to have extramarital affairs. (On this, he concludes "yes".) On presidential election outcomes, he concludes that, statistically speaking, only two factors really matter: (1) which party is in power: the incumbent is likely to be returned to off]cc unless his party was in charge of the Oval Office for "too long" (i.e., three or more terms); and (2) whether the economy is improving or deteriorating just prior to the election. The latter factor would seem to be more heavily weighted than the former, such that, if one indeed is looking for a rule of thumb, Clinton's aphorism is a good guide.
Fair indeed has predicted since publication of his book that, given the U.S. economy is likely to continue to be on an upward tick for the remainder of this year and that Bush the Junior has been in office for only one term, the odds are overwhelming that Bush will be returned to the White House. Could it be that we need not wait to see the likely outcome of the 'Skins game? We should instead bet on an econometric model?
Let's start by noting that there are some problems associated with hypothesis testing via econometric methods. Ideally, to do statistical testing, one needs for everything to be held constant except for the causal variables being tested. For a physicist, this is relatively easy: one devises an experiment where everything but that which is to be tested is controlled so that all else indeed is, as best as one can do, held equal. Even then, to make sure that random errors of control or measurement do not contaminate his or her results, the physicist runs the experiment multiple times. Alas, even so, the outcome can be inconclusive although more often than not, the physicist does return results that yield something like the truth.
In the social sciences, however, life is much harder because it is impossible to test most hypotheses via controlled experiments. …