Hostname: page-component-586b7cd67f-g8jcs Total loading time: 0 Render date: 2024-11-28T07:52:12.909Z Has data issue: false hasContentIssue false
  • English
  • Français

Estimating Voter Preference Distributions from Individual-Level Voting Data

Published online by Cambridge University Press:  04 January 2017

Jeffrey B. Lewis
Jeffrey B. Lewis*
Affiliation:
Politics Department, Princeton University, Princeton, NJ 08544-1012. e-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

This paper presents a method for inferring the distribution of voter ideal points on a single dimension from individual-level binary choice data. The statistical model and estimation technique draw heavily on the psychometric literature on test taking and, in particular, on the work of Bock and Aitkin (1981) and are similar to several recent methods of estimating legislative ideal points (Londregan 2000; Bailey 2001). I present Monte Carlo results validating the method. The method is then applied to determining the partisan and ideological basis of support for presidential candidates in 1992 and to U.S. mass and congressional partisan realignment on abortion policy since 1973.

Type
Research Article
Information
Political Analysis , Volume 9 , Issue 3 , January 2001 , pp. 275 - 297
Copyright
Copyright © 2001 by 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.)

References

Abrams, B. A., and Butkiewicz, J. L. 1995. “The Influence of State-Level Economic-Conditions on the 1992 US Presidential-Election.” Public Choice 85(1): 1–10.Google Scholar
Abramson, Paul R., Aldrich, John H., Paolino, Phillip, and Rohde, David W. 1995. “3rd-Party and Independent Candidates in American Politics—Wallace, Anderson and Perot.” Political Science Quarterly 110(3): 349–367.Google Scholar
Adams, Greg D. 1997. “Abortion: Evidence of an Issue Evolution.” American Journal of Political Science 41(3): 718–737.Google Scholar
Alvarez, R. Michael, and Nagler, Jonathan. 1995. “Economics Issues and the Perot Candidacy—Voter Choice in the 1992 Presidential-Election.” American Journal of Political Science 39(3): 714–744.CrossRefGoogle Scholar
Bailey, Michael. 2001. “Ideal Point Estimation with a Small Number of Votes.” Political Analysis 9(3): 192–210.Google Scholar
Black, Duncan. 1958. The Theory of Committees and Elections. Cambridge, England: Cambridge University Press.Google Scholar
Bock, R. Darrell, and Aitken, Murray. 1981. “Marginal Maximum Likelihood Estimation of Item Parameters: Application of the EM Algorithm.” Psychometrika 46(4): 443–459.Google Scholar
Burnham, Walter Dean. 1979. Critical Elections and the Mainsprings of American Politics. New York: W. W. Norton.Google Scholar
Carmines, Edward O., and Stimson, James A. 1989. Issue Evolution: Race and the Transformation of American Politics. Princeton, NJ: Princeton University Press.Google Scholar
Ceaser, James W., and Busch, Andrew. 1993. Upside Down and Inside Out: The 1992 Elections and American Politics. Boulder, CO: Rowman & Littlefield.Google Scholar
Converse, Phillip, and Markus, Gregory A. 1979. “Ca Plus Change … The New CPS Election Study Panel.” American Political Science Review 73(1): 32–49.Google Scholar
Dempster, A. P., Laird, N. M., and Rubin, D. B. 1977. “Maximum Likelihood Estimation from Incomplete Data via the EM Algorithm.” Journal of the Royal Statistical Society, Series B 39(1): 1–38.Google Scholar
Downs, Anthony. 1957. An Economic Theory of Democracy. New York: Harper & Row.Google Scholar
Gerber, Elisabeth R., and Lewis, Jeffrey B. 2000. “Representing Heterogeneous Districts,” Presented at the 2000 American Political Science Association Meetings, Washington, DC.Google Scholar
Groseclose, Timothy J. 1994. “The Committee Outlier Debate: A Review and a Reexamination of Some of the Evidence.” Public Choice 80: 265–273.Google Scholar
Haberman, Shelby J. 1977. “Maximum Likelihood Estimation in Exponential Response Model.” Annals of Statistics 6(5): 815–841.Google Scholar
Heckman, James J., and Snyder, James M. 1997. “Linear Probability Models of the Demand for Attributes with an Empirical Application to Estimating the Preferences of Legislators.” Rand Journal of Economics 28: S142–S169.Google Scholar
Hinich, Melvin J., and Enelow, James M. 1984. The Spatial Theory of Voting: An Introduction. Cambridge, England: Cambridge University Press.Google Scholar
Holian, D. B., Krebs, T. B., and Walsh, M. H. 1997. “Constituency Opinion, Ross Perot, and Roll-Call Behavior in the US House: The Case of the NAFTA.” Legislative Studies Quarterly 22(3): 369–392.Google Scholar
Hotelling, H. 1929. “Stability in Competition.” Economic Journal 39: 41–57.Google Scholar
Jackman, Simon. 2000. “Estimation and Inference Are Missing Data Problems.” Political Analysis 8(4): 307–332.Google Scholar
Key, V. O. 1955. “A Theory of Critical Elections.” Journal of Politics 17(1): 3–18.Google Scholar
Knack, S. 1997. “The Reappearing American Voter: Why Did Turnout Rise in ‘92?” Electoral Studies 16(1): 17–32.CrossRefGoogle Scholar
Lacy, Dean, and Burden, Barry C. 1999. “The Vote-Stealing and Turnout Effects of Ross Perot in the 1992 US “presidential.” American Journal of Political Science 43(1): 233–255.Google Scholar
Lahda, Krishna K. 1991. “A Spatial Model of Legislative Voting with Perceptual Error.” Public Choice 68: 151–174.Google Scholar
Lewis, Jeffrey B. 2001. “Technical Appendix and Ancillary Materials for ‘Estimating Voter Preference Distributions from Individual-Level Voting Data.'” Available at the Political Analysis web site.Google Scholar
Londregan, John. 2000a. “Estimating Legislators’ Preferred Points.” Political Analysis 8: 35–56.Google Scholar
Londregan, John B. 2000b. Legislative Institutions and Ideology in Chile. Cambridge, England: Cambridge University Press.Google Scholar
Londregan, John, and Snyder, James M. 1994. “Comparing Committee and Floor Preferences.” Legislative Studies Quarterly 19(2): 233–265.Google Scholar
Lord, Fredrick M. 1962. “Estimating Norms by Item-Sampling.” Educational and Psychological Measurement 22(2): 259–267.CrossRefGoogle Scholar
Mislevy, Robert J. 1984. “Estimating Latent Distributions.” Psychometrika 49(3): 359–381.Google Scholar
Mislevy, Robert J., Beaton, Albert E., Kaplan, Bruce, and Sheehan, Kathleen M. 1992. “Estimating Population Characteristics from Sparse Matrix Samples of Item Responses.” Journal of Educational Measurement 29(2): 144–161.Google Scholar
Neyman, J., and Scott, Elizabeth L. 1948. “Consistent Estimates Based on Partially Consistent Observations.” Econometrics 16(1): 1–32.Google Scholar
Owen, D., and Dennis, J. 1996. “Anti-Partyism in the USA and Support for Ross Perot.” European Journal of Political Research 29(3): 383–400.Google Scholar
Patz, Richard J., and Junker, Brian W. 1999. “A Straightforward Approach to Markov Chain Monte Carlo Methods for Item Response Models.” Journal of Educational and Behavioral Statistics 24(2): 146–178.Google Scholar
Peltzman, Sam. 1985. “Constituent Interest and Congressional Voting.” Journal of Law & Politics 27: 181–210.Google Scholar
Poole, Keith T. 2000. “Nonparametric Unfolding of Binary Choice Data.” Political Analysis 8(3): 211–237.CrossRefGoogle Scholar
Poole, Keith T., and Rosenthal, Howard. 1997. Congress: A Political-Economic History of Roll Call Voting. Oxford: Oxford University Press.Google Scholar
Southwell, P. L., and Everest, M. J. 1998. “The Electoral Consequences of Alienation: Nonvoting and Protest Voting in the 1992 Presidential Race.” Social Science Journal 35(1): 43–51.CrossRefGoogle Scholar
Stroud, A. H., and Secrest, Don. 1966. Gaussian Quadrature Formulas. Englewood Cliffs, NJ: Prentice-Hall.Google Scholar
Thorson, G. R., and Stambough, S. J. 1995. “Anti-incumbency and the 1992 Elections—The Changing Face of Presidential Coattails.” Journal of Politics 57(1): 210–220.Google Scholar