Hostname: page-component-586b7cd67f-l7hp2 Total loading time: 0 Render date: 2024-11-23T23:25:27.453Z Has data issue: false hasContentIssue false
  • English
  • Français

Multiple Ideal Points: Revealed Preferences in Different Domains

Published online by Cambridge University Press:  09 March 2021

Scott Moser Open the ORCID record for Scott Moser [Opens in a new window] ,
Abel Rodríguez Open the ORCID record for Abel Rodríguez [Opens in a new window]  and
Chelsea L. Lofland
Scott Moser*
Affiliation:
Associate Professor, School of Politics and International Relations, University of Nottingham, Nottingham, UK. [email protected], URL: http://www.nottingham.ac.uk/~ldzsm2/
Abel Rodríguez
Affiliation:
Professor, Department of Statistics, University of California, Santa Cruz, 1156 High Street, Mailstop SOE2, Santa Cruz, CA95064, USA. [email protected], URL: http://soe.ucsc.edu/~abel
Chelsea L. Lofland
Affiliation:
Department of Statistics, University of California, Santa Cruz, 1156 High Street, Mailstop SOE2, Santa Cruz, CA95064, USA. [email protected], URL: https://ams.soe.ucsc.edu/people/clofland
*
Corresponding author Scott Moser
Get access Rights & Permissions [Opens in a new window]

Abstract

We extend classical ideal point estimation to allow voters to have different preferences when voting in different domains—for example, when voting on agricultural policy than when voting on defense policy. Our scaling procedure results in estimated ideal points on a common scale. As a result, we are able to directly compare a member’s revealed preferences across different domains of voting (different sets of motions) to assess if, for example, a member votes more conservatively on agriculture motions than on defense. In doing so, we are able to assess the extent to which voting behavior of an individual voter is consistent with a uni-dimensional spatial model—if a member has the same preferences in all domains. The key novelty is to estimate rather than assume the identity of “stayers”—voters whose revealed preference is constant across votes. Our approach offers methodology for investigating the relationship between the basic space and issue space in legislative voting (Poole 2007). There are several methodological advantages to our approach. First, our model allows for testing sharp hypotheses. Second, the methodology developed can be understood as a kind of partial-pooling model for item response theory scaling, resulting in less uncertainty of estimates. Related, our estimation method provides a principled and unified approach to the issue of “granularity” (i.e., the level of aggregation) in the analysis of roll-call data (Crespin and Rohde 2010; Roberts et al. 2016). We illustrate the model by estimating U.S. House of Representatives members’ revealed preferences in different policy domains, and identify several other potential applications of the model including: studying the relationship between committee and floor voting behavior; and investigating constituency influence and representation.

Keywords

ideal point estimationdimensionalitynon-parametric Bayesian methodsroll-callsmultiple comparisons
Type
Article
Information
Political Analysis , Volume 29 , Issue 2 , April 2021 , pp. 139 - 166
Copyright
© The Author(s) 2021. Published by Cambridge University Press on behalf of the Society for Political Methodology

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

Edited by Jeff Gill

Author’s note: Earlier version of this work were presented at the 2017 Midwest Political Science Association Annual Conference under the title “Comparing Revealed Preferences Across Multiple Types of Motions in the 83rd to 112th, U.S. House of Representatives.” This work has benefited from helpful comments from Marc Ratkovic, as well as from three anonymous referees. Results presented here can be reproduced at https://codeocean.com/capsule/5298256/.

References

Adler, E. S., and Wilkerson, J.. 2017. Congressional Bills Project [data file and codebook].Google Scholar
Albert, J. H., and Chib, S.. 1993. “Bayesian Analysis of Binary and Polychotomous Response.” American Statistical Association 88(422):669–679.CrossRefGoogle Scholar
Aldrich, J. H., Montgomery, J. M., and Sparks, D. B.. 2014. “Polarization and Ideology: Partisan Sources of Low Dimensionality in Scaled Roll Call Analyses.” Political Analysis 22(2):435–456.CrossRefGoogle Scholar
Anderson, S. E. 2012. “Policy Domain-Specific Ideology: When Interest Group Scores Offer More Insight.” Politics & Policy 40(6):1186–1202.CrossRefGoogle Scholar
Ansolabehere, S., Snyder, J. M. Jr., and Stewart, C. III. 2001. “The Effects of Party and Preferences on Congressional Roll-Call Voting.” Legislative Studies Quarterly 26(4):533–572.CrossRefGoogle Scholar
Antoniak, C. 1974. “Mixtures of Dirichlet Processes with Applications to Bayesian Nonparametric Problems.” Annals of Statistics 2:1152–1174.Google Scholar
Armstrong, H., Carter, C. K., Wong, K. F. K., and Kohn, R.. 2009. “Bayesian Covariance Matrix Estimation Using a Mixture of Decomposable Graphical Models.” Statistics and Computing 19(3):303–316.CrossRefGoogle Scholar
Asmussen, N., and Jo, J.. 2016. “Anchors Away: A New Approach for Estimating Ideal Points Comparable Across Time and Chambers.” Political Analysis 24(2):172–188.CrossRefGoogle Scholar
Bafumi, J., Gelman, A., Park, D. K., and Kaplan, N.. 2005 “Practical Issues in Implementing and Understanding Bayesian Ideal Point Estimation.” Political Analysis 13:171–87.CrossRefGoogle Scholar
Bakker, R., Jolly, S., Polk, J., and Poole, K.. 2014. “The European Common Space: Extending the Use of Anchoring Vignettes.” The Journal of Politics 76(4):1089–1101.CrossRefGoogle Scholar
Baumgartner, F. R., Breunig, C., Green-Pedersen, C., Jones, B. D., Mortensen, P. B., Nuytemans, M., and Walgrave, S.. 2009. “Punctuated Equilibrium in Comparative Perspective.” American Journal of Political Science 53(3):603–620.CrossRefGoogle Scholar
Baumgartner, F. R., and Jones, B. D.. 1993. Agendas and Instability in American Politics. Chicago: University of Chicago Press.Google Scholar
Benoit, K., and Laver, M.. 2012. “The Dimensionality of Political Space: Epistemological and Methodological Considerations.” European Union Politics 13(2):194–218.CrossRefGoogle Scholar
Binder, S. A. 1999. “The Dynamics of Legislative Gridlock, 1947–96.” American Political Science Review 93(3):519–533.CrossRefGoogle Scholar
Brennan, G., and Hamlin, A.. 1999. “On Political Representation.” British Journal of Political Science 29(1):109–127.CrossRefGoogle Scholar
Brown, R. D., Davis, J. M., Overby, L. M., Jr, C. E. S., and Holian, D. R.. 1997. “The Dynamics of Committee Outliers: Evidence from the House of Representatives, 1951–90.” The Journal of Legislative Studies 3(2):70–88.CrossRefGoogle Scholar
Cameron, C. M. 2000. Veto Bargaining: Presidents and the Politics of Negative Power. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Carmines, E. G., and Stimson, J. A.. 1986. “On the Structure and Sequence of Issue Evolution.” American Political Science Review 80(3):901–920.CrossRefGoogle Scholar
Carmines, E. G., and Stimson, J. A.. 1990. Issue Evolution: Race and the Transformation of American Politics. Princeton, NJ: Princeton University Press.Google Scholar
Carroll, R., Lewis, J. B., Lo, J., Poole, K. T., and Rosenthal, H.. 2009. “Comparing NOMINATE and IDEAL: Points of Difference and Monte Carlo Tests.” Legislative Studies Quarterly 34(4):555–591.CrossRefGoogle Scholar
Carroll, R., Lewis, J. B., Lo, J., Poole, K. T., and Rosenthal, H.. 2013. “The Structure of Utility in Spatial Models of Voting.” American Journal of Political Science 57(4):1008–1028.Google Scholar
Cattell, R. B. 1966. “The Scree Test for the Number of Factors.” Multivariate Behavioral Research 1(2) 245–276.CrossRefGoogle ScholarPubMed
Celeux, G. 1998. “Bayesian Inference for Mixture: The Label Switching Problem.” In COMPSTAT: Proceedings in Computational Statistics, edited by Payne, R. and Green, P., 227–232. New York: Springer.CrossRefGoogle Scholar
Clarke, K. A., and Primo, D. M.. 2012. A Model Discipline: Political Science and the Logic of Representations. Oxford: Oxford University Press.CrossRefGoogle Scholar
Clausen, A. 1973. How Congressmen Decide: A Policy Focus. New York: St. Martin’s Press.Google Scholar
Clausen, A. R., and Cheney, R. B.. 1970. “A Comparative Analysis of Senate-House Voting on Economic and Welfare Policy, 1953–1964.” American Political Science Review 64(1):138–152.CrossRefGoogle Scholar
Clausen, A. R., and Wilcox, C.. 1987. “Policy Partisanship in Legislative Leadership Recruitment and Behavior.” Legislative Studies Quarterly 1(2):243–263.CrossRefGoogle Scholar
Clinton, J., Jackman, S., and Rivers, D.. 2004. “The Statistical Analysis of Roll Call Data.” American Political Science Review 98(2):355–370.Google Scholar
Clinton, J. D. 2006. “Representation in Congress: Constituents and Roll Calls in the 106th House.” The Journal of Politics 68(2):397–409.CrossRefGoogle Scholar
Clinton, J. D., and Jackman, S.. 2011. “To Simulate or NOMINATE?” Legislative Studies Quarterly 34(4):593–621.CrossRefGoogle Scholar
Clinton, J., Jackman, S., and Rivers, D.. 2004. “The Statistical Analysis of Roll Call Data.” American Political Science Review 98(2):355–370.CrossRefGoogle Scholar
Cox, G. W., and McCubbins, M. D.. 1993. Legislative Leviathan: Party Government in the House. California Series on Social Choice and Political Economy. Berkeley: University of California Press.Google Scholar
Cox, G. W., and McCubbins, M. D.. 2005. Setting the Agenda: Responsible Party Government in the US House of Representatives. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Cox, G. W., and Poole, K. T.. 2002. “On Measuring Partisanship in Roll-Call Voting: The U.S. House of Representatives, 1877–1999.” American Journal of Political Science 46(3):477.Google Scholar
Crespin, M. H., and Rohde, D. W.. 2010. “Dimensions, Issues, and Bills: Appropriations Voting on the House Floor.” The Journal of Politics 72(4):976–989.CrossRefGoogle Scholar
Crook, S. B., and Hibbing, J. R.. 1985. “Congressional Reform and Party Discipline: The Effects of Changes in the Seniority System on Party Loyalty in the US House of Representatives.” British Journal of Political Science 15(2):207–226.CrossRefGoogle Scholar
Davis, O. A., Hinich, M. J., and Ordeshook, P. C.. 1970. “An Expository Development of a Mathematical Model of the Electoral Process.” American Political Science Review 64(2):426–448.Google Scholar
De Vries, C. E., and Marks, G.. 2012. “The Struggle over Dimensionality: A Note on Theory and Empirics.” European Union Politics 13(2):185–193.Google Scholar
Deering, C. J., and Smith, S. S.. 1997. Committees in Congress. New York: CQ Press.CrossRefGoogle Scholar
Denzau, A. T., and Mackay, R. J.. 1983. “Gatekeeping and Monopoly Power of Committees: An Analysis of Sincere and Sophisticated Behavior.” American Journal of Political Science 27(4):740–761.CrossRefGoogle Scholar
Dougherty, K. L., Lynch, M. S., and Madonna, A. J.. 2014. “Partisan Agenda Control and the Dimensionality of Congress.” American Politics Research 42(2):600–627.CrossRefGoogle Scholar
Dowding, K., Hindmoor, A., and Martin, A.. 2013. “The Policy Agendas Project: Reflections on Theory.” Chicago, IL: Social Science Research Network.Google Scholar
Dowding, K., Hindmoor, A., and Martin, A.. 2016. “The Comparative Policy Agendas Project: Theory, Measurement and Findings.” Journal of Public Policy 36(1):3–25.CrossRefGoogle Scholar
Duclos, J.-Y., Esteban, J., and Ray, D.. 2004. “Polarization: Concepts, Measurement, Estimation.” Econometrica 72(6):1737–1772.Google Scholar
Duff, J. F., and Rohde, D.W.. 2012. “Rules to Live by: Agenda Control and the Partisan Use of Special Rules in the House.” Congress & the Presidency 39(1):28–50.CrossRefGoogle Scholar
Egar, W. T. 2016. “Tarnishing Opponents, Polarizing Congress: The House Minority Party and the Construction of the Roll-Call Record.” Legislative Studies Quarterly 41(4):935–964.CrossRefGoogle Scholar
Enelow, J. M., and Hinich, M. J.. 1984. The Spatial Theory of Voting: An Introduction. Cambridge: Cambridge University Press.Google Scholar
Esteban, J.-M., and Ray, D.. 1994. “On the Measurement of Polarization.” Econometrica 62(4):819–851.Google Scholar
Gerrish, S. M., and Blei, D. M.. 2010. “The Ideal Point Topic Model: Predicting Legislative Roll Calls from Text.” In Proceedings of the Computational Social Science and the Wisdom of Crowds Workshop. Neural Information Processing Symposium, Citeseer.Google Scholar
Gerrish, S. M., and Blei, D. M.. 2012a. “How They Vote: Issue-Adjusted Models of Legislative Behavior.” In Advances in Neural Information Processing Systems 25, edited by Pereira, F., Burges, C. J. C., Bottou, L., and Weinberger, K. Q., 2753–2761. New York: Curran Associates, Inc.Google Scholar
Gerrish, S. M., and Blei, D. M.. 2012b. “The Issue-Adjusted Ideal Point Model.” Preprint, arXiv:1209.6004.Google Scholar
Geweke, J. 1992. “Evaluating the accuracy of sampling-based approaches to the calculations of posterior moments.” In Bayesian Statistics 4, edited by Bernardo, J. M., Berger, J., Dawid, A. P., and Smith, A. F. M., 641–649. Oxford: Oxford University Press.Google Scholar
Gopalan, R., and Berry, D. A.. 1998. “Bayesian Multiple Comparisons Using Dirichlet Process Priors.” Journal of the American Statistical Association 93(443):1130–1139.Google Scholar
Groseclose, T. 1994a. “Testing Committee Composition Hypotheses for the U.S. Congress.” The Journal of Politics 56(2):440–458.Google Scholar
Groseclose, T. 1994b. “The Committee Outlier Debate: A Review and a Reexamination of Some of the Evidence.” Public Choice 80(3):265–273.CrossRefGoogle Scholar
Harding, M. C. 2008. “Explaining the Single Factor Bias of Arbitrage Pricing Models in Finite Samples.” Economics Letters 99(1):85–88.CrossRefGoogle Scholar
Hurwitz, M. S., Moiles, R. J., and Rohde, D. W.. 2001. “Distributive and Partisan Issues in Agriculture Policy in the 104th House.” American Political Science Review 95(4):923–937.Google Scholar
Jackman, S. 2001. “Multidimensional Analysis of Roll Call Data via Bayesian Simulation: Identification, Estimation, Inference, and Model Checking.” Political Analysis 9(3):227–241.CrossRefGoogle Scholar
Jessee, S. A. 2012. Ideology and Spatial Voting in American Elections. Cambridge: Cambridge University Press.Google Scholar
Jessee, S. A., and Theriault, S. M.. 2014. “The Two Faces of Congressional Roll-Call Voting.” Party Politics 20(6):836–848.Google Scholar
Jochim, A. E., and Jones, B. D.. 2013. “Issue Politics in a Polarized Congress.” Political Research Quarterly 66(2):352–369.CrossRefGoogle Scholar
Jones, B. D., and Baumgartner, F. R.. 2005. The Politics of Attention: How Government Prioritizes Problems. Chicago: University of Chicago Press.Google Scholar
Koford, K. 1989. “Dimensions in Congressional Voting.” American Political Science Review 83(3):949–962.CrossRefGoogle Scholar
Krehbiel, K. 1990. “Are Congressional Committees Composed of Preference Outliers?” American Political Science Review 84(1):149–163.CrossRefGoogle Scholar
Krehbiel, K. 1998. Pivotal Politics: A Theory of U.S. Lawmaking. Chicago: University of Chicago Press.CrossRefGoogle Scholar
Krehbiel, K., Meirowitz, A., and Woon, J.. 2005. “Testing Theories of Lawmaking.” In Social Choice and Strategic Decisions, edited by Austen-Smith, D. and Duggan, J.. New York: Springer.Google Scholar
Lapinski, J. S. 2013. The Substance of Representation: Congress, American Political Development, and Lawmaking. Vol. 133. Princeton, NJ: Princeton University Press.Google Scholar
Lau, J. W., and Green, P. J.. 2007. “Bayesian Model-Based Clustering Procedures.” Journal of Computational and Graphical Statistics 16(3):526–558.CrossRefGoogle Scholar
Lauderdale, B. E., and Clark, T. S.. 2014. “Scaling Politically Meaningful Dimensions Using Texts and Votes.” American Journal of Political Science 58(3):754–771.CrossRefGoogle Scholar
Lee, D. J., and Schutte, R. A.. 2017. “Elite-Level Issue Dynamics: Assessing Perspectives on Party Issue Change.” Party Politics 23(3):205–219.CrossRefGoogle Scholar
Liu, C., Rubin, D. B., and Wu, Y. N.. 1998. “Parameter Expansion to Accelerate EM: The PX-EM Algorithm.” Biometrika 85(4):755–770.CrossRefGoogle Scholar
Lofland, C. L., Rodríguez, A., and Moser, S.. 2017. “Assessing Differences in Legislators’ Revealed Preferences: A Case Study on the 107th U.S. Senate.” Annals of Applied Statistics 11(1):456–479.CrossRefGoogle Scholar
Londregan, J. 1999. “Estimating Legislators’ Preferred Points.” Political Analysis 8(1):35–56.CrossRefGoogle Scholar
Lord, F. 1952. A Theory of Test Scores. Psychometric Monograph, Income Red. New York: Psychometric Society.Google Scholar
Martin, A. D., and Quinn, K. M.. 2002. “Dynamic Ideal Point Estimation via Markov Chain Monte Carlo for the U.S. Supreme Court, 1953–1999.” Political Analysis 10(2):134–153.Google Scholar
Mayhew, D. R. 1966. Party Loyalty among Congressmen: The Difference between Democrats and Republicans, 1947-1962. Cambridge, MA: Harvard University Press.Google Scholar
McCarty, N. M., and Poole, K. T.. 1995. “Veto Power and Legislation: An Empirical Analysis of Executive and Legislative Bargaining from 1961 to 1986.” Journal of Law, Economics and Organization 11:282–312.Google Scholar
McCarty, N. M., Poole, K. T., and Rosenthal, H.. 1997. Income Redistribution and the Realignment of American Politics. Washington: AEI Press.Google Scholar
McCarty, N. M., Poole, K. T., and Rosenthal, H.. 2001. “The Hunt for Party Discipline in Congress.” American Political Science Review 95(3):673–687.CrossRefGoogle Scholar
McCrone, D. J., and Kuklinski, J. H.. 1979. “The Delegate Theory of Representation.” American Journal of Political Science 23(2):278–300.CrossRefGoogle Scholar
Miler, K. 2016. “Legislative Responsiveness to Constituency Change.” American Politics Research 44(5):816–843.CrossRefGoogle Scholar
Miler, K. C. 2010. Constituency Representation in Congress: The View from Capitol Hill. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Miller, W. E., and Stokes, D. E.. 1963. “Constituency Influence in Congress.” American Political Science Review 57(1):45–56.Google Scholar
Moffett, K. W. 2012. “Parties and Procedural Choice in the House Rules Committee.” Congress & the Presidency 39(1):1–27.CrossRefGoogle Scholar
Moser, S., Rodriguez, A., and Lofland, C.. 2020a. “Multiple Ideal Points: Revealed Preferences in Different Domains.” Code Ocean V1:29. https://codeocean.com/capsule/0712643/tree/v1.Google Scholar
Moser, S., Rodriguez, A., and Lofland, C.. 2020b. “Replication Data for: Multiple Ideal Points: Revealed Preferences in Different Domains.” https://doi.org/10.7910/DVN/STH14F, Harvard Dataverse, V1, UNF:6:3I1dnh+PI0nvpGL0O3yXSA== [fileUNF].Google Scholar
Moser, S., Rodríguez, A., and Lofland, C. L.. 2019. “Polarization and Amendments: The Overlooked Role of Amendments in Explaining Increased Polarization.” Working Paper.Google Scholar
Neal, R. M. 2000. “Markov chain sampling methods for Dirichlet process mixture models.” Journal of Computational and Graphical Statistics 9(2):249–265.Google Scholar
Nokken, T. P. 2014. “Comparing Agenda Content and Roll-Call Behaviour in Regular and Lame-Duck Sessions of the House of Representatives, 1879–2010.” The Journal of Legislative Studies 20(4):430–450.Google Scholar
Peltzman, S. 1984. “Constituent Interest and Congressional Voting.” The Journal of Law & Economics 27(1):181–210.Google Scholar
Pitman, J. 1996. “Some Developments of the Blackwell-MacQueen Urn Scheme.” In Statistics, Probability, and Game Theory: Papers in Honor of David Blackwell, edited by Blackwell, D., Ferguson, T. S., Shapley, L. S., and MacQueen, J. B., 245–267. Lecture Notes-Monograph Series. New York: Institute of Mathematical Statistics.Google Scholar
Policy Agendas Project. 2017. Roll-Call Votes.Google Scholar
Poole, K. T. 2007. “Changing Minds? Not in Congress!” Public Choice 131(3–4):435–451.Google Scholar
Poole, K. T., and Romer, T.. 1993. “Ideology, ‘Shirking’, and Representation.” In The Next Twenty-Five Years of Public Choice, edited by Rowley, C., Schneider, F., and Tollison, R. D., 185–196. New York: Springer.CrossRefGoogle Scholar
Poole, K. T., and Rosenthal, H.. 1985. “A Spatial Model for Legislative Roll Call Analysis.” American Journal of Political Science 29(2):357–384.Google Scholar
Poole, K. T., and Rosenthal, H.. 1987. “Analysis of Congressional Coalition Patterns: A Unidimensional Spatial Model.” Legislative Studies Quarterly 12(1):55–75.CrossRefGoogle Scholar
Poole, K. T., and Rosenthal, H.. 1991. “Patterns of Congressional Voting.” American Journal of Political Science 35(1):228–278.Google Scholar
Poole, K. T., and Rosenthal, H.. 2000. Congress: A Political-Economic History of Roll Call Voting. Oxford: Oxford University Press.Google Scholar
Poole, K. T., and Rosenthal, H. L.. 2011. Ideology and Congress. New York: Transaction Publishers.Google Scholar
Poole, K. T., Rosenthal, H., and Koford, K.. 1991. “On Dimensionalizing Roll Call Votes in the US Congress.” American Political Science Review 85(3):955–976.CrossRefGoogle Scholar
Potoski, M., and Talbert, J.. 2000. “The Dimensional Structure of Policy Outputs: Distributive Policy and Roll Call Voting.” Political Research Quarterly 53(4):695–710.CrossRefGoogle Scholar
Pump, B. 2010. Beyond Roll Calls: Institutional Change and Partisanship in the US House of Representatives. SSRN Scholarly Paper ID 1580563. Rochester, NY: Social Science Research Network.Google Scholar
Rasch, G. 1960. Probabilistic Models for Some Intelligence and Attainment Tests. Studies in Mathematical Psychology. Copenhagen: Danish Institute for Educational Research.Google Scholar
Rivers, D. 2003. Identification of multidimensional item-response models. Technical report. Department of Political Science, Stanford University.Google Scholar
Robert, C. P., and Casella, G.. 2005. Monte Carlo Statistical Methods. 2nd edn. New York: Springer.Google Scholar
Roberts, J. M. 2010. “The Development of Special Orders and Special Rules in the U.S. House, 1881–1937.” Legislative Studies Quarterly 35(3):307–336.CrossRefGoogle Scholar
Roberts, J. M., and Smith, S. S.. 2003. “Procedural Contexts, Party Strategy, and Conditional Party Voting in the U.S. House of Representatives, 1971-2000.” American Journal of Political Science 47(2):305–317.CrossRefGoogle Scholar
Roberts, J. M., Smith, S. S., and Haptonstahl, S. R.. 2016. “The Dimensionality of Congressional Voting Reconsidered.” American Politics Research 44(5):794–815.Google Scholar
Scott, J. G., and Berger, J. O.. 2006. “An Exploration of Aspects of Bayesian Multiple Testing.” Journal of Statistical Planning and Inference 136(7):2144–2162.Google Scholar
Scott, J. G., and Berger, J. O.. 2010. “Bayes and Empirical-Bayes Multiplicity Adjustment in the Variable-Selection Problem.” The Annals of Statistics 38(5):2587–2619.Google Scholar
Shepsle, K. A., and Weingast, B. R.. 1987. “The Institutional Foundations of Committee Power.” American Political Science Review 81(1):85–104.CrossRefGoogle Scholar
Shor, B., Berry, C., and McCarty, N.. 2010. “A Bridge to Somewhere: Mapping State and Congressional Ideology on a Cross-Institutional Common Space.” Legislative Studies Quarterly 35(3):417–448.Google Scholar
Shor, B., and McCarty, N. M.. 2011. “The Ideological Mapping of American Legislatures.” American Political Science Review 105 03:530–551.CrossRefGoogle Scholar
Snyder, J. M. Jr., and Groseclose, T.. 2000. “Estimating Party Influence in Congressional Roll-Call Voting.” American Journal of Political Science 44(2):193–211.Google Scholar
Snyder, J. M. Jr. 1992a. “Committee Power, Structure-Induced Equilibria, and Roll Call Votes.” American Journal of Political Science 36(1):1–30.CrossRefGoogle Scholar
Snyder, J. M. Jr. 1992b. “Gatekeeping or Not, Sample Selection in the Roll Call Agenda Matters.” American Journal of Political Science 36(1):36–39.CrossRefGoogle Scholar
Stephens, M. 2000. “Dealing with Label Switching in Mixture Models.” Journal of the Royal Statistical Society: Series B (Statistical Methodology) 62(4):795–809.CrossRefGoogle Scholar
Stokes, D. E. 1963. “Spatial Models of Party Competition.” American Political Science Review 57(2):368–377.CrossRefGoogle Scholar
Sulfaro, V. A. 2000. “Sources of Structure in Congressional Behavior: The Influence of Ideology on Foreign and Domestic Policy Votes.” Southeastern Political Review 28(1):77–110.Google Scholar
Sulkin, T., Testa, P., and Usry, K.. 2015. “What Gets Rewarded? Legislative Activity and Constituency Approval.” Political Research Quarterly 68(4):690–702.CrossRefGoogle Scholar
Talbert, J. C., and Potoski, M.. 2002. “Setting the Legislative Agenda: The Dimensional Structure of Bill Cosponsoring and Floor Voting.” The Journal of Politics 64(3):864–891.Google Scholar
Theriault, S. M. 2008. Party Polarization in Congress.Cambridge: Cambridge University Press.Google Scholar
Treier, S. 2011. “Comparing Ideal Points across Institutions and Time.” American Politics Research 39(5):804–831.Google Scholar
Tsebelis, G. 1995. “Decision Making in Political Systems: Veto Players in Presidentialism, Parliamentarism, Multicameralism and Multipartyism.” British Journal of Political Science 25(3):289.Google Scholar
Vandoren, P. M. 1990. “Can We Learn the Causes of Congressional Decisions from Roll-Call Data?” Legislative Studies Quarterly 15(3):311.CrossRefGoogle Scholar
Weingast, B. R., and Marshall, W. J.. 1988. “The Industrial Organization of Congress; or, Why Legislatures, like Firms, Are Not Organized as Markets.” Journal of Political Economy 96(1):132–163.Google Scholar
Wilcox, C., and Clausen, A.. 1991. “The Dimensionality of Roll-Call Voting Reconsidered.” Legislative Studies Quarterly 16(3):393–406.Google Scholar
Supplementary material: PDF

Moser et al. supplementary material

Moser et al. supplementary material

Download Moser et al. supplementary material(PDF)
PDF 134.8 KB
Supplementary material: Link

Moser et al. Dataset

Dataset

https://doi.org/10.7910/DVN/STH14F
Link