The following links contain the dataset and the STATA program used to generate the econometric estimates found in this post.

Data: Election Outcomes and Economic Peformance (1996)

STATA Program: Election Outcomes and Economic Performance

This blog post replicates the analysis of the relationship between economic performance and election outcomes done by Fair (1996). The regression model will be used to predict the likelihood that President Obama is reelected based on several important political and economic variables identified in the analysis. Outlined below are the variables, data, and regression model predictions. These estimates suggest that president Obama will lose the next election by a narrow margin receiving 49.4 % of the popular vote.

**VARIABLES**

The model will use several variables to predict the percentage of votes going to democratic presidential candidates (**demvote**) based on important political and economic factors. The variables are:

**incum** = takes on a value of 1 if a democrat is the incumbent and -1 if the incumbent is republican

**partyWH** = takes on a value of 1 if a democrat is in the Whitehouse and -1 otherwise

**gnews** = number of quarters,from first 15 quarters of incumbent presidency, where per capita output was above 2.9

** inf** = average annual inflation rate in the first 15 quarters of incumbent presidency

There are also several interaction terms between the variable partyWH and gnews and inf that are used in the regression model

**SUMMARY STATISTICS**

The summary statistics show that democrats have received a little more than 49% of the vote in the last 21 presidential elections. This has ranged between 36 t0 62% over the period under observation.

**MODEL**

The model that will be used will be a simple linear regression model with the variable presented in the summary statistics.

**RESULTS**

The model explains about 65% of the variability in the percentage of votes going to democrats in a presidential election in the United States. There is a small and statistically insignificant reduction in votes going to democrats control the Whitehouse. Democratic incumbents have a 5% point advantage when they are the incumbents during the election. The interaction between democratic control of the Whitehouse and good economic news is favorable for the democrats. Every quarter of good economic growth in the first 15 quarters of a democratic presidency translates into nearly a 1% point advantage during the next election. The effect inflation during a first 15 quarters of a democratic presidency has nearly the opposite effect of robust economic growth, decreasing the percentage of democratic votes by .8% points for every 1% increase in average inflation during a democratically controlled Whitehouse. .

**INFERENCE AND PREDICTIONS**

Using this model Fair (1996) was able to predict Bill Clinton’s presidential re-election within 4% points. Given the current condition and relying on the model estimated above: we have a democratic president in the Whitehouse who is running for his second term, zero quarters with economic growth above 2.9% and and average inflation rate of 1.7% one would predict that president Obama would receive 49.4 % of the popular vote. According to these estimates Obama would lose the popular vote and most likely the election if economic conditions don’t improve.

**RESPONSE TO QUESTIONS/OBSERVATIONS ABOUT POST
**

Is this prediction statistically different from a draw? Can the inclusion of unemployment change the overall model predictions given the abnormally high levels we are currently experiencing? I will be looking into these questions shortly.

Given a relatively mild inflationary pressures in the US economy at the moment, I’m not sure how robust (in economic terms) the correlation between inflation and voter preference would be in the upcoming election. Would be interesting to see the same model run with respect to unemployment and underemployment measures. I would also presume that the elasticities vary quite a bit across the country accounting for regions that are traditional democratic or republican strongholds.

Good observations. I will run the model with unemployment figures and see how things look and update the post.

Why are the incum and partywh variables not dummy variables? It makes little sense to me why it would be 1 or -1 and not 1 or 0. Interesting though, I must say. I also just found your blog and what I’ve read so far looks very promising.

Typically one codes a covariate as (1 or -1) if you believe that this variable has similar but opposite effects on the dependent variable. The assumption is that having a Republican in the Whitehouse would have the exact opposite effect on the share of democratic votes than if a Democrat where in the Whitehouse. I suppose there is probably a way of testing whether or not a dummy variable as opposed to a (1 or -1) covariate would be appropriate. I would need to investigate that further. Thank you for your comments.