Dr. Joshua Tauberer of GovTrack has posted Even Better Bill Prognosis: Now with Real Probabilities, on the GovTrack Blog.
In this post, Dr. Tauberer describes the new probability-of-passage figure added to GovTrack’s bill prognosis feature. According to the post:
For the data wonks out there, the new prognosis is based on a logistic regression model. The model predicts a bill’s success based on the following binary factors:
- the title of the bill (such as if it is a bill to name a post office)
- whether the sponsor is a member of the majority party (in the House or Senate as appropriate)
- whether the sponsor is the chair, ranking member, or a member (if majority party) of a committee that the bill has been referred to
- if any cosponsor is the chair or ranking member (most senior minority party member) of a committee the bill has been referred to
- if there are 3-5 cosponsors of the bill serving on a committee the bill has been referred to
- if the bill has a cosponsor from both parties
- if the bill’s sponsor is in the majority party and at least 1/3rd of the cosponsors are from the minority party
Success is for bills if they are enacted and for resolutions if they successfully reach the end of their life cycle (simple resolutions passed, concurrent resolutions passed by both chambers, joint resolutions enacted). [...]
Dr. Tauberer has also posted the following request:
Anyone have ideas for more factors to consider for predicting which bills will pass?
For more information, please see Dr. Tauberer’s post, or contact him on Twitter at @JoshData.