Hibbs, one of the original economy-and-elections guys, writes:
The number of House seats won by the presidents party at midterm elections is well explained by three pre-determined or exogenous variables: (1) the number of House seats won by the in-party at the previous on-year election, (2) the vote margin of the in-partys candidate at the previous presidential election, and (3) the average growth rate of per capita real disposable personal income during the congressional term. Given the partisan division of House seats following the 2008 on-year election, President Obamas margin of victory in 2008, and the weak growth of per capita real income during the rst 6 quarters of the 111th Congress, the Democrats chances of holding on to a House majority by winning at least 218 seats at the 2010 midterm election will depend on real income growth in the 3rd quarter of 2010. The data available at this writing indicate the that Democrats will win 211 seats, a loss of 45 from the 2008 on-year result that will put them in the minority for the 112th Congress.
Although this essay features some predictions about likely outcomes of the 2010 election for the US House of Representatives, the underlying statistical model is meant to be structural or causal and is not targeted on forecasting accuracy.
The model presented in this essay is designed to explain midterm House election outcomes in terms of systematic predetermined and exogenous factors rather than to deliver optimal predictions. For that reason the model does not include trend terms or polling measurements of the publics political sentiments and voting intentions of the sort populating forecasting equations.
I defer to Hibbs entirely on the political economy, but I would like to make one small methodological point. Hibbs writes:
Most statistical models of aggregate House election outcomes focus exclusively on vote shares going to the major parties. . . . But aggregate votes are mainly of academic interest. What really matters politically is the partisan division of seats, and that is the object of attention here.
I think Hibbs is missing the point here. Even if your sole goal is to forecast seats, I think the most efficient way to do this is to forecast national vote trends, and then apply the national swing to each district, correcting for incumbency and uncontestedness where appropriate. See here for further discussion of this point. Or you could go even further and use the fundamentals (for example, local economic conditions and demographic trends) to modify your vote forecast at the regional and state levels.
I mean, sure, it’s ok to forecast seats directly. It’s simple, clear, and less effort than forecasting votes and then doing the district-by-district work of transmuting vote swings to expected seat swings. But it’s nothing to be proud of–it’s certainly not better than modeling votes, then seats.
But I don’t want to end with that criticism, which is (as noted above) minor. The real point is the connection between the economy and the vote, and on that topic Hibbs has interesting things to say.