Replication data for: Lawmaking and Roll Calls
Harvard Dataverse (Africa Rice Center, Bioversity International, CCAFS, CIAT, IFPRI, IRRI and WorldFish)
View Archive InfoField | Value | |
Title |
Replication data for: Lawmaking and Roll Calls
|
|
Identifier |
https://doi.org/10.7910/DVN/S3NH2W
|
|
Creator |
Joshua D. Clinton
|
|
Publisher |
Harvard Dataverse
|
|
Description |
Replication data and code forthcoming The ability to generate theories of lawmaking has not been matched by an ability to evaluate the success of these theories for explaining legislative reality. The principal problem in testing lawmaking theories is that many analysts use roll call votes -- or various measures based on roll call votes -- when, in fact, these votes are partly a cause and partly a consequence of the very things the theories seek to explain. This leads to erroneous substantive conclusions and characterizations. I show how embedding the theoretical predictions of the party gatekeeping and majoritarian theories of lawmaking within a statistical model used to estimate ideal points yields a straightforward test; if the gridlock interval measured using votes on policies predicted by the theories is nonzero, the theory is false. Implementing the test reveals little support for either theory |
|
Date |
2007
|
|