tag:blogger.com,1999:blog-4111898318552745320.post8871294781686260617..comments2024-01-15T02:56:56.912-05:00Comments on CCPSBlog: Updated Democratic Superdelegate Predictions: Introducing New Variables and Subtracting OthersBrian Schaffnerhttp://www.blogger.com/profile/11810834587978662058noreply@blogger.comBlogger7125tag:blogger.com,1999:blog-4111898318552745320.post-12274435062820333742022-08-30T06:17:20.916-04:002022-08-30T06:17:20.916-04:00Grreat postGrreat postInsect Pest Control Yuba Cityhttps://www.insect-pest-control.com/us/bug-exterminator-california/insect-pest-control-yuba-city.shtmlnoreply@blogger.comtag:blogger.com,1999:blog-4111898318552745320.post-17075889800570261612008-05-09T19:18:00.000-04:002008-05-09T19:18:00.000-04:00It makes sense that you can't easily find a plausi...It makes sense that you can't easily find a plausible exclusion in the binary candidate choice model so as to identify the parameters of the commitment (selection) equation. That's probably why the Heckman selection model has problems converging.<BR/><BR/>However, you might consider an ordered probit model (oprobit in Stata), where Obama = +1, uncommitted = 0, and Clinton = -1. (As you know, these ordinal values are arbitrary.) This would be an alternative way of using all the information you have, including the fact that some delegates are uncommitted. In fact, you could run the oprobit model on the data post Super-Tuesday and compare the results with an oprobit model run on the most recent data. The comparison would show how the range of the underlying latent variable has narrowed. You would also have an interesting metric of how "close" an uncommitted delegate is to either candidate.<BR/><BR/>fianchetto, Providence RIAnonymousnoreply@blogger.comtag:blogger.com,1999:blog-4111898318552745320.post-12235140391186232042008-05-09T05:33:00.000-04:002008-05-09T05:33:00.000-04:0070% seems quite good in terms of choosing who will...70% seems quite good in terms of choosing who will endorse whom. However, I'm curious of how well your prediction margins have been?<BR/><BR/>You said you have 70% accuracy on over 100 predictions. So, what was your predicted margin among those >100 vs the actual margin? If exactly half the 30% wrong predictions were Clinton and the other half were for Obama, then your predicted margin would've been exactly correct, even though you got there the wrong way.J.J. Emersonhttps://www.blogger.com/profile/06005635061756895272noreply@blogger.comtag:blogger.com,1999:blog-4111898318552745320.post-66148645899998808012008-05-07T23:06:00.000-04:002008-05-07T23:06:00.000-04:00Thanks for the comments everyone. For those who ha...Thanks for the comments everyone. <BR/><BR/>For those who have been following this, I have actually been generating these models since shortly after Super Tuesday.<BR/><BR/>You see the first predictions here:<BR/>http://ccpsblog.blogspot.com/2008/02/predicting-who-democratic.html<BR/><BR/>To answer the question about self selection, my previous models were Heckman Probit Selection models. This worked pretty well for a while, but recently the test of rho was not even close to being statistically significance and Stata was having issues estimating the model at all. This could very well be because I don't have all the variables necessary to correctly specify the selection stage, but whatever the reason, I decided to go back to a more simple model.<BR/><BR/>As for splitting the sample, I have not done this. However, since I began generating predictions, over 100 superdelegates who were previously undeclared endorsed either Clinton or Obama, and the model did get 70% of those correct. <BR/><BR/>Here is a link outlining the methodology I was using previously. <BR/>http://ccpsblog.blogspot.com/2008/02/unpledged-superdelegate-predictions.html<BR/><BR/>Finally, Mike3550's idea about another variable capturing the potential change in dynamics after March 4th is a good idea and I may try this in the next iteration.<BR/><BR/>You can also see some answers to questions posed by other readers here:<BR/>http://ccpsblog.blogspot.com/2008/04/answering-questions-about-superdelegate.htmlBrian Schaffnerhttps://www.blogger.com/profile/11810834587978662058noreply@blogger.comtag:blogger.com,1999:blog-4111898318552745320.post-72852290827461056722008-05-07T22:38:00.000-04:002008-05-07T22:38:00.000-04:00Great Write up. Dang Crappy Luck for you though. R...Great Write up. Dang Crappy Luck for you though. Right off the bat you BLow Heath Shuler. You should have asked me I could have told you he would vote for the winner of his district and that that would be Hillary. Maybe take him out of the chart.TINAandRONhttps://www.blogger.com/profile/14577178445315529208noreply@blogger.comtag:blogger.com,1999:blog-4111898318552745320.post-67531610659948301342008-05-07T20:38:00.000-04:002008-05-07T20:38:00.000-04:00I haven't seen the formal write-up of your model, ...I haven't seen the formal write-up of your model, so you may well have responded to these two comments already:<BR/><BR/>1. I assume that you ran a binary choice model on the sample of already committed superdelegates, and then used the resulting parameter estimates to predict the choices of the remaining uncommitted delegates. But did you take into account the real possibility that the remaining uncommitted delegates are different? To address this issue, you would have to run an ancillary "commitment" equation and then use the results of the ancillary equation to compute a "self-selection" correction factor in your binary choice model. As you probably know, this is the standard problem of self-selection in labor economics and other fields.<BR/><BR/>2. Did you attempt to validate your model by splitting your sample? That is, did you attempt to derive your estimates from half of the superdelegates and then see if the resulting model correctly predicted the choices of the superdelegates in the other half of the sample?<BR/><BR/>Thanks,<BR/><BR/>Fianchetto, Providence RIAnonymousnoreply@blogger.comtag:blogger.com,1999:blog-4111898318552745320.post-36504426384644880132008-05-06T16:30:00.000-04:002008-05-06T16:30:00.000-04:00I have thoroughly enjoyed your analysis of the rac...I have thoroughly enjoyed your analysis of the race and predicting superdelegates. I had one question about the models since you mention the importance of the variable indicating whether superdelegates made their endorsement before or after Super Tuesday. I wonder what would happen if you added a second dummy variable indicating that the endorsement came after Clinton's win in Ohio. To capture the dynamics of the race, it seemed like Clinton was the early favorite, Obama was the "insurgent" candidate with most of the momentum after Super Tuesday and Clinton has gained (or at least neutralized) Obama's momentum following the Ohio primary. <BR/><BR/>Although there might not be enough observations of endorsements after the Ohio primary to come up with stable estimates, it seems like there might be a different calculus now for the remaining superdelegates than those who endorsed between Super Tuesday and Ohio.<BR/><BR/>Thanks again for posting all of this!mike3550https://www.blogger.com/profile/09621465191508532187noreply@blogger.com