Wednesday, November 16, 2011

 

Presidential Models Have Very Different Results for 2012

Eight months ago I began blogging extensively on economic statistical models predicting presidential election results. I was not the first to do so, and the recent back-and-forth between pundits, commentators, political scientists, and everyone in-between on which model is the best and whether campaigns matter demonstrates that I will not be the last to talk about them.

My purpose here is not to declare one side right or wrong (though my work indicates that I think Douglas Hibbs' real disposable income growth economic indicator is an imperfect best of the bunch). Rather, it is to point out the most important fact for 2012: the major difference between the well-known Abramowitz and Hibbs model.

Last week, Alan Abramowitz wrote that Nate Silver's model was too pessimistic about Barack Obama's chances for re-election. He cited his own model, which showed Obama garnering 52% under projected economic conditions and being a favorite in almost any economic scenario.

The interesting fact about this critique was Silver's model, which shows probable Republican nominee Mitt Romney to be a favorite at this point, is that it is actually not anywhere close to painting the worst outlook for the President. The Hibbs model forecasts, under most economic conditions, Obama losing by a wide margin (getting only about 44%).

Hibbs model, which has been noted as one of the better of many presidential prediction models (see the great Andrew Gelman), differs greatly form Abramowitz in a number of ways.

Abramowitz's model utilizes GDP growth in 2nd quarter of the presidential election year, presidential approval in the same 2nd quarter, and a dummy variable for whether the incumbent White House party has been in power for more than 1 term.

Hibbs' uses a weighted average (closer to the election matters more) of real disposable income per capita (i.e. how much money each person makes after taxes and inflation) and deaths in unprovoked military conflicts throughout the president's term.

Note the key differences for our sake between Hibbs and Abramowitz are the use of the "term of the party in power" and measurement of the economy. The term variable essentially gives a bonus to the president if his party is newly elected. One might imagine Obama receiving extra votes because some voters still blame Bush for the state of the economy.

My own amendment to Hibbs' model indicates that this "term" variable helps Obama gain about an extra 2% of the vote* given current economic conditions. But under these same conditions, an extra 2% does not even get Obama to 46.5% of the two-party vote. This is not anywhere close to the 52% of the two-party vote Abramowitz's model currently projects for the President.

Why the major variation in prediction? The most obvious answer is that these models are imperfect. They carry large in-dataset errors and even larger out-of-forecast (i.e. future data that model clearly cannot know) errors. Still, 52% vs. 46.5% (or near 44% in the case of Hibbs' original model) is a very large difference.

The main reason for the disparities between these models is that their economic measures are different. Abramowitz's GDP growth was 2.5% last quarter and is expected to be that in 2012. Hibbs' disposable income growth variable for the presidential term is likely not be all that greater than 0% and could easily be negative (as it is right now).

Put concretely, weighted disposable income growth says this economy is by far the 2nd worst for a presidential term since 1952, while GDP of the 2nd quarter of a presidential year says it is only 5th worst (just behind 2004). The charts below says it all.


If you believe GDP, the economy is far better than the one confronted by mind 2008 voters. If you believe disposable income growth, it is about as bad if not worse than the economy for 2008 voters.

So which is the correct economic measurement? Again, I lean towards disposable income (as it is the measurement that is felt by most voters), but I really am not sure there is a right answer one way or the other.

To me, this is the beauty of all of this quantification. In political prediction, there is always going to be two or more ways to measure something.

Many times, as was the case in 2008 and the economy, the measurements will point towards a similar conclusion. Sometimes, however, the measurements will point you towards diverging conclusions (see Nyhan and Montgomery for an intriguing way to combine forecasts).

In fact, I think this is a perfect example of when a campaign could matter. President Obama could use GDP to say the "economy is getting better", while the Republican could use disposable income to say "the economy is getting worse".

I say we let the campaigns make their case. 2012 should be fun.

*Abramowitz states that a party in control of the White House for more than 8 years would lose 4.4% of the vote vs. a party in for only 4 years. I find nearly the same effect for the term variable, if it is included in the formula. My 2% figure comes from whether the "term" variable is included at all, not that whether we include the variable and then code it differently (i.e. first vs second or more terms) as Abramowitz has.

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