Quality & Quantity

, Volume 47, Issue 3, pp 1687–1701 | Cite as

How similar are they? rethinking electoral congruence

  • Jason Wittenberg


Electoral continuity and discontinuity have been a staple of voting research for decades. Most researchers have employed Pearson’s r as a measure of congruence between two electoral outcomes across a set of geographic units. This paper argues that that practice should be abandoned. The correlation coefficient is a measure of linearity, not similarity, and is almost always the wrong measure. The paper recommends other quantities that better accord with what researchers usually mean by electoral persistence. Replications of prior studies in American and comparative politics demonstrate that the consequences of using r when it is inappropriate can be stark. In some cases what we think are continuities are actually discontinuities.


Elections Voting Continuity Similarity Correlation Concordance 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Achen C.H.: Measuring representation: perils of the correlation coefficient. American Journal of Political Science 21(4), 805–815 (1977)CrossRefGoogle Scholar
  2. Achen C.H., Shively W.P.: Cross-Level Inference. University of Chicago Press, Chicago (1995)Google Scholar
  3. Atkinson G., Nevill A.: Comment on the use of concordance correlation to assess the agreement between two variables. Biometrics 53(2), 775–777 (1997)Google Scholar
  4. Barnhart H.X., Haber M.J., Lin L.I.: An overview on assessing agreement with continuous measurements. Journal of Biopharmaceutical Statistics 17, 529–569 (2007)CrossRefGoogle Scholar
  5. Burnham W.D.: American voting behavior in the 1964 election. Midwest Journal of Political Science XII(1), 1–40 (1968)CrossRefGoogle Scholar
  6. Caramani D.: Elections in Western Europe Since 1815: Electoral Results by Constituencies. MacMillan, London (2000)Google Scholar
  7. Carrasco J.L., Jover L.: Estimating the generalized concordance correlation coefficient through variance components. Biometrics 59, 849–858 (2003)CrossRefGoogle Scholar
  8. Gimpel J.G., Schuknecht J.E.: Rethinking political regionalism in the American states. State Politics and Policy Quarterly 2(4), 325–352 (2002)CrossRefGoogle Scholar
  9. Green D.P., Palmquist B.: How stable is party identification?.   Political Behavior 16(4), 437–466 (1994)CrossRefGoogle Scholar
  10. Haber M., Barnhart H.X.: A general approach to evaluating agreement between two observers or methods of measurement from quantitative data with replicated measurements. Statistical Methods in Medical Research 17, 151–169 (2008)CrossRefGoogle Scholar
  11. Hamann K., Sgouraki-Kinsey B.: Re-entering electoral politics: reputation and party system change in Spain and Greece. Party Politics 5(1), 55–77 (1999)CrossRefGoogle Scholar
  12. Key V.O.: Southern Politics. A.A. Knopf, New York (1949)Google Scholar
  13. Key V.O. Jr., Munger F.: Social determinism and electoral decision: the case of Indiana. In: Burdick, E., Broadbeck, A.J. (eds) American Voting Behavior, pp. 281–299. Greenwood Press, Westport, CT (1959)Google Scholar
  14. King G.: How not to lie with statistics: avoiding common mistakes in quantitative political science. American Journal of Political Science 30(3), 666–687 (1986)CrossRefGoogle Scholar
  15. King G.: A Solution to the Ecological Inference Problem: Reconstructing Individual Behavior from Aggregate Data. Princeton University Press, Princeton (1997)Google Scholar
  16. King T.S., Chinchilli V.M.: Robust estimators of the concordance correlation coefficient. Journal of Biopharmaceutical Statistics 11(3), 83–105 (2001)CrossRefGoogle Scholar
  17. Levine M.V.: Standing political decisions and critical realignment: the pattern of Maryland politics, 1872–1948. Journal of Politics 38(2), 292–325 (1976)CrossRefGoogle Scholar
  18. Lin L.I.-K.: A concordance correlation coefficient to evaluate reproducibility. Biometrics 45, 255–268 (1989)CrossRefGoogle Scholar
  19. Lin L. I.-K.: A note on the concordance correlation coefficient. Biometrics 56, 324–325 (2000)CrossRefGoogle Scholar
  20. Linz J.J.: The new Spanish party system. In: Rose, R. (eds) Electoral Participation: A Comparative Analysis, pp. 101–189. Sage, Beverly Hills, CA (1980)Google Scholar
  21. Linz, J. J., De Miguel, J. M.: Hacia un análisis regional de las elecciones de 1936 en España. Revista Española De La Opinion Publica, No. 48 (Abril–Juno), pp. 27–68 (1977)Google Scholar
  22. Mainwaring S., Zoco E.: Political sequences and the stabilization of interparty competition. Party Politics 13(2), 155–178 (2007)CrossRefGoogle Scholar
  23. Maravall J.: The Transition to Democracy in Spain. Croom Helm, London & Canberra (1982)Google Scholar
  24. Mebane W.R. Jr., Sekhon J.S.: Robust estimation and outlier detection for overdispersed multinomial models of count data. American Journal of Political Science 48(2), 392–411 (2004)CrossRefGoogle Scholar
  25. Montes J.E., Mainwaring S., Ortega E.: Rethinking the Chilean party system. Journal of Latin American Studies 32, 795–824 (2000)CrossRefGoogle Scholar
  26. Morgenstern S., Pothoff R.F.: The components of elections: district heterogeneity, district-time effects, and volatility. Electoral Studies 24, 17–40 (2005)CrossRefGoogle Scholar
  27. Nickerson C.A.E.: A note on ‘a concordance correlation coefficient to evaluate reproducibility’. Biometrics 53, 1503–1507 (1997)CrossRefGoogle Scholar
  28. Rivera S.W.: Historical cleavages or transition mode? influences on the emerging party systems in Poland, Hungary, and Czechoslovakia. Party Politics 2(2), 177–208 (1996)CrossRefGoogle Scholar
  29. Robinson W.S.: The statistical measurement of agreement. American Sociological Review 22(1), 17–25 (1957)CrossRefGoogle Scholar
  30. Shaffer W.R., Caputo D.A.: Political continuity in Indiana presidential elections: an analysis based on the Key-Munger paradigm. Midwest Journal of Political Science 16(4), 700–711 (1972)CrossRefGoogle Scholar
  31. Shapiro I.: Problems, methods, and theories in the study of politics, or what’s wrong with political science and what to do about it. Political Theory 30, 596–619 (2002)CrossRefGoogle Scholar
  32. Taagepera R., Grofman B.: Mapping the indices of seats-votes disproportionality and inter-election volatility. Party Politics 9(6), 659–677 (2003)CrossRefGoogle Scholar
  33. Valenzuela S.J., Scully T.R.: Electoral choices and the party system in Chile: continuities and changes at the recovery of democracy. Comparative Political Studies 29(4), 511–527 (1997)Google Scholar
  34. Vonesh E.F., Chinchilli V.M., Pu K.: Goodness-of-fit in generalized nonlinear mixed-effect models. Biometrics 52, 572–587 (1996)CrossRefGoogle Scholar
  35. Wand J.N., Shotts K.W., Sekhon J.S., Mebane W.R. Jr., Herrron M.C., Brady H.E.: The butterfly did it: the aberrant vote for buchanan in palm beach county, Florida. American Political Science Review 95(4), 793–810 (2001)Google Scholar
  36. Wittenberg J.: Crucibles of Political Loyalty: Church Institutions and Electoral Continuity in Hungary. Cambridge University Press, Cambridge (2006)CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  1. 1.Department of Political ScienceUniversity of California, BerkeleyBerkeleyUSA

Personalised recommendations