Re: [MLUG - DISCUSSION] [POLITICS] another cool graph from Krugman

[Mike Miller <EMAIL:PROTECTED>]

On Fri, 9 May 2008, Jonathan King wrote:

> On Thu, May 8, 2008 at 2:25 PM, Mike Miller <EMAIL:PROTECTED> wrote:
> > This does make it look bad for the Republicans:
> >
> >  http://krugman.blogs.nytimes.com/2008/05/07/phase-two/
>
> How do you figure? This plots results for the past 14 elections. 
> Incumbent parties have won 7, and the opposition has won 7.
>
> Winning an election is a categorical result. This skanky Pearson's r 
> stuff predicting vote share misses the point. The real question is 
> simply this: if you have only a set of binary data point (here, 14 of 
> them), what decision rule can I create that will best discriminate 
> winners from losers.

Skanky?


> As I mentioned, incumbency provides exactly zero information.
>
> I cannot find any simple cut-point for election-year income growth that 
> gives me significant predictive power for the outcome of the election.
>
> I can come up with a rule of the following form: If growth is greater 
> than about 4%, then the incumbent party wins, or if growth is less than 
> 2% then the challenger wins; otherwise, it's a coin flip. This is not a 
> very satisfying predictive rule.

There you go.  You did it.  Isn't our income growth currently down around 
1%?  I'm not easily finding data, but one thing I found showed a growth of 
1% in the last quarter of 2007 with 1% increase in consumer price index, 
which means to me 0% income growth.


> Another rule is: the incumbent party wins unless there is an unpopular 
> war or an impeachment. That predicts 11 of 14 elections (misses only 
> 1992, 1960, and 1980). If you rephrase that to "military/diplomatic 
> debacle or impeachment" then you predict 12 of 14 elections (missing 
> only 1992 and 1960).

That also looks bad for the Republicans.


> Of course, I am data-mining here (as is everybody else, but I digress). 
> In any case, the last rule suggests there is a better than 80% chance 
> that the GOP will lose in November. But I don't believe it for a second. 
> There really just isn't enough data here to build any kind of useful 
> model.

OK but at least you can't say that you have no reason to think otherwise.

Mike

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