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What The Senator Prefers, What the Senator Proposes: A Statistical Model To Estimate the Location Of the Policy Proposal And The Status Quo In Roll Call Votes

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Abstract:

Congress scholars have produced a number of statistical procedures to estimate the preferences of legislators in roll call voting. In order to test current theoretical models of spatial voting, however, it is also necessary to obtain proper estimates of the location of the proposal and of the status quo. In this paper we extend recent research on ideal point estimation to provide a plausible location for the proposal and the status quo in roll call data. We show that there is often sufficient information to significantly narrow the area where the proposal and the status quo reside. We exemplify our modeling strategy through the use of simulations and roll call data from the 107th U.S. Senate.

Most Common Document Word Stems:

estim (106), propos (99), model (94), 1 (89), vote (83), locat (75), legisl (74), 0 (61), inform (60), 2 (56), paramet (54), status (52), quo (51), point (50), j (50), true (50), senat (47), c (46), ideal (41), bill (34), p (32),

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Ideal Point, Roll Call Vote, Bayesian MCMC, Congress
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Name: American Political Science Association
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MLA Citation:

Calvo, Ernesto. and Kaplan, Noah. "What The Senator Prefers, What the Senator Proposes: A Statistical Model To Estimate the Location Of the Policy Proposal And The Status Quo In Roll Call Votes" Paper presented at the annual meeting of the American Political Science Association, Marriott Wardman Park, Omni Shoreham, Washington Hilton, Washington, DC, Sep 01, 2005 <Not Available>. 2008-12-12 <http://www.allacademic.com/meta/p40227_index.html>

APA Citation:

Calvo, E. F. and Kaplan, N. , 2005-09-01 "What The Senator Prefers, What the Senator Proposes: A Statistical Model To Estimate the Location Of the Policy Proposal And The Status Quo In Roll Call Votes" Paper presented at the annual meeting of the American Political Science Association, Marriott Wardman Park, Omni Shoreham, Washington Hilton, Washington, DC Online <APPLICATION/PDF>. 2008-12-12 from http://www.allacademic.com/meta/p40227_index.html

Publication Type: Conference Paper/Unpublished Manuscript
Review Method: Peer Reviewed
Abstract: Congress scholars have produced a number of statistical procedures to estimate the preferences of legislators in roll call voting. In order to test current theoretical models of spatial voting, however, it is also necessary to obtain proper estimates of the location of the proposal and of the status quo. In this paper we extend recent research on ideal point estimation to provide a plausible location for the proposal and the status quo in roll call data. We show that there is often sufficient information to significantly narrow the area where the proposal and the status quo reside. We exemplify our modeling strategy through the use of simulations and roll call data from the 107th U.S. Senate.

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Associated Document Available American Political Science Association
Associated Document Available Political Research Online

Document Type: application/pdf
Page count: 33
Word count: 7080
Text sample:
What the Senator Proposed: a statistical exercise to identify the location of the proposal and the status quo in Roll Call votes Ernesto Calvo University of Houston University of Houston ecalvo@uh.edu Noah Kaplan University of Houston University of Houston nkaplan@uh.edu First Draft Abstract: Congress scholars have produced a number of statistical procedures to estimate the preferences of legislators in roll call voting. In order to test current theoretical models of spatial voting however it is also necessary to obtain
Political Analysis 10(2):134-153. Poole Keith. 2005. Spatial Models of Parliamentary Voting. New York: Cambridge University Press 2005. Poole Keith Howard Rosenthal. 1997. Congress: A Political-Economic History of Roll Call Voting. New York: Oxford University Press. R Development Core Team. 2003. R: A Language and Environment for Statistical Computing. Vienna Austria: R. Foundation for statistical Computing. Available at http://www.R-Project.org. 32 Rasch George. 1980. Probabilistic Models for Some Intelligence and Attainment Tests. Chicago: University of Chicago Press. Spegelhalter David Andrew Thomas


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