When I regress Obama's closing price on the daily adjusted closing price of the S&P 500 and a time variable, I find Obama's re-election odds and the S&P 500 are positively correlated, and the correlation coefficient is highly significant. You can also see the R-squared is quite high.
regress obamaclose spadjclose time
Source | SS df MS Number of obs = 105
-------------+------------------------------ F( 2, 102) = 165.51
Model | 750.217165 2 375.108582 Prob > F = 0.0000
Residual | 231.172684 102 2.26639886 R-squared = 0.7644
-------------+------------------------------ Adj R-squared = 0.7598
Total | 981.389849 104 9.43644085 Root MSE = 1.5055
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obamaclose | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
spadjclose | .0552766 .0040307 13.71 0.000 .0472816 .0632716
time | .0329881 .0051778 6.37 0.000 .0227178 .0432583
_cons | -18.34905 5.368125 -3.42 0.001 -28.9967 -7.7014
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That's something of a dog bites man result, since it just says voters want a good economy. Now I regress Obama's closing prices on inflation expectations (as measured by 5-year TIPS spreads) and a time variable. The correlation is positive and highly significant. This result is not shocking, but it does suggest that perhaps Obama should favor more expansionary monetary policy.
regress obamaclose inflex time
Source | SS df MS Number of obs = 105
-------------+------------------------------ F( 2, 102) = 151.93
Model | 734.747095 2 367.373548 Prob > F = 0.0000
Residual | 246.642753 102 2.41806621 R-squared = 0.7487
-------------+------------------------------ Adj R-squared = 0.7438
Total | 981.389849 104 9.43644085 Root MSE = 1.555
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obamaclose | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
inflex | 16.75131 1.285248 13.03 0.000 14.20203 19.30059
time | .0411078 .005171 7.95 0.000 .0308512 .0513643
_cons | 23.92947 2.415287 9.91 0.000 19.13876 28.72018
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Now I regress Obama's re-election odds on the S&P and inflation expectations and a time variable. Both S&P and inflation expectations have positive coefficients and are highly significant. I think this result is interesting, because it says that even controlling for the value of the stock market, monetary expansion helps Obama's re-election chances. The explanation might be that expansionary monetary policy (in our current circumstances) helps the economy more than just by making us wealthier, but it also improves the employment situation, and though those two outcomes are related they are not identical.
regress obamaclose spadjclose inflex time
Source | SS df MS Number of obs = 105
-------------+------------------------------ F( 3, 101) = 123.57
Model | 771.255054 3 257.085018 Prob > F = 0.0000
Residual | 210.134794 101 2.08054252 R-squared = 0.7859
-------------+------------------------------ Adj R-squared = 0.7795
Total | 981.389849 104 9.43644085 Root MSE = 1.4424
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obamaclose | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
spadjclose | .0332366 .0079343 4.19 0.000 .017497 .0489762
inflex | 7.788602 2.449327 3.18 0.002 2.929797 12.64741
time | .0351098 .0050057 7.01 0.000 .0251799 .0450397
_cons | -3.55992 6.934249 -0.51 0.609 -17.3156 10.19576
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In conclusion, Obama should be listening to the Sumners of the world and seek more expansionary monetary policy.
Here's a scatter plot of Obama's closing prices and inflation expectations:
Here's a scatter plot of Obama's closing prices and inflation expectations:
(Data from Intrade, Yahoo Finance, and Treasury.gov.)
UPDATE: Justin Murphy has a different take on this data.
UPDATE 2: Since this post has gotten some attention, I updated the data a bit. The graph below shows a scatter plot of Obama's closing % on intrade vs. inflation expectations (as measured by 5 year Treasury rates minus 5 year TIPS) for all of 2012 up to and including September 14, 2012. It's the same as the graph in the previous post, but it has about 9 and a half months of data instead of 6 months of data.
One potential confound (maybe not a big issue in this case) is path dependency-- the voters might like a result in general (e.g. low unemployment) but not like certain ways of achieving it.
ReplyDeleteA good example is health care costs- most people like cheaper health insurance but many people do not like insurance mandates, even if they thought they make health care cheaper.
This means we need a little caution in going from the correlations you describe to predictions about how voters will react if Obama pursues a different monetary policy.
Thanks for the comment. That's a good point. PR is a big part of policymaking. Fortunately for Obama, the Fed would be implementing the monetary expansion, not Obama, so it might be easier to do politically. He's responsible in the sense of putting good people at the Fed, but it is independent to some degree. Some bloggers (including Brad DeLong) have complained that Obama has not put enough of his political capital into putting good people at the Fed, and so some seats were left vacant for quite a while. Obviously, the Republicans don't always make things easy for him, but maybe he could've put some pro-monetary stimulus Republicans at the Fed, like Mankiw.
ReplyDeleteWould you make this data available? I wonder what happens if you use first differences or use VAR instead of OLS? I wouldn't mind playing with this...
ReplyDeleteI've emailed you the data. Thanks for your interest.
ReplyDelete