Skip to main content Accessibility help

The Instability of Partisanship: An Analysis of the 1980 Presidential Election

  • Richard A. Brody and Lawrence S. Rothenberg


Scholars have long assigned a key role to party identification as an explanation of voting behaviour. In doing so, they have assumed that individuals' partisan affiliations remain unchanged for long periods of time. But is partisanship sufficiently stable to justify this assumption? At the very least, to be considered a long-term force party identification cannot change during an election. Yet the intra-election stability of party affiliations has been accepted on faith, rather than examined empirically.

Our analysis tests this assumption by looking at the evolution of partisanship over the course of the 1980 election. We find that many citizens do alter their partisanship over a single electoral period. These changes in party identification follow a systematic - and not a random - pattern. Both cognitive and affective factors account for this intra-election partisan lability. These findings suggest that much of the previous research on voting behaviour has been seriously misspecified.



Hide All

1 On party identification as a long-term force, see Converse, P. E., ‘The Concept of the Normal Vote’, in Campbell, A., Converse, P. E., Miller, W. E. and Stokes, D. E., Elections and the Political Order (New York: John Wiley & Sons, 1968).

2 Key, V. O. Jr., and Munger, F., ‘Social Determinism and Electoral Decision: The Case of Indiana’, in Burdick, E. and Brodbeck, A. J., eds, American Voting Behavior (New York: Free Press of Glencoe, 1959).

3 See Burnham, W. D., Critical Elections and the Mainsprings of American Democracy (New York: W. W. Norton, 1970).

4 Campbell, A., Gurin, G. and Miller, W. E., The Voter Decides (Evanston, Ill.: Row-Peterson, 1954). p. 89.

5 Converse, P. E., ‘Public Opinion and Voting Behavior’, in Greenstein, F. I. and Polsby, N. W., eds. Handbook of Political Science, Volume 4 (Reading, Mass.: Addison-Wesley, 1975), p. 117.

6 The requirement of stability in the strength component has always appeared somewhat paradoxical, since the creators of this measure lead us to expect that individuals' identification will strengthen over their life-cycles. Converse resolves this apparent contradiction by showing that the expected increment to the strength component over a brief period – such as that covered by the extant national panel data sets – will be indistinguishable from sampling and measurement error. In other words, we can ignore life-cycle increases in strength when considering whether party identification exhibits the required individual-level stability. See Campbell, A., Converse, P. E., Miller, W. E. and Stokes, D. E., The American Voter (New York: John Wiley & Sons, 1960); Converse, P. E., The Dynamics of Party Support (Beverly Hills, Calif: Sage Publications, 1976), p. 46.

7 Converse, P. E. and Markus, G. B., ‘Plus ça change…: The New CPS Election Study Panel’, American Political Science Review, 73 (1979), 3249, p. 46; Converse, P. E., ‘The Nature of Belief Systems in Mass Publics’, in Apter, D., ed., Ideology and Discontent (New York: Free Press of Glencoe. 1964).

8 Dreyer, E. C., ‘Change and Stability in Party Identification’, Journal of Politics, 35 (1973), 712–22.

9 Dobson, D., and Meeter, D. A., ‘Alternative Markov Models for Describing Change in Party Identification’, American Political Science Review, 18 (1974), 487500; Dobson, D., and Angelo, D. St., ‘Party Identification and the Floating Vote: Some Dynamics’, American Journal of Political Science, 69 (1973), 481–90; Brody, R. A., ‘Stability and Change in Party Identification: Presidential to Off-Years’, paper delivered at the annual meeting of the American Political Science Association (1977).

10 These calculations do not include people classified as pure independents in the initial wave of the panel.

11 Brody, R. A., ‘Change and Stability in the Components of Party Identification’, DAE News, APSA, 13 (1977), 1318.

12 See Markus, G. B. and Converse, P. E., ‘A Dynamic Simultaneous Equation Model of Electoral Choice’, American Political Science Review, 73 (1979), 1055–70, p. 1060; see also Page, B. I. and Jones, C. C., ‘Reciprocal Effects of Policy Preferences, Party Loyalties and the Vote’, American Political Science Review, 73 (1979), 1071–89; Fiorina, M. P., Retrospective Voting in American National Elections (New Haven, Conn.: Yale University Press, 1981).

13 Franklin, Charles H. and Jackson, John E., ‘The Dynamics of Party Identification’, American Political Science Review, 77 (1983), 957–73; Franklin, Charles H., ‘Party Identification and Party Realignment’, paper delivered at the annual meeting of the American Political Science Association, 1986.

14 Franklin, and Jackson, , ‘The Dynamics of Party Identification’, p. 969.

15 The data used in this study were gathered by the National Election Study and the Center for Political Studies at the University of Michigan and were made available through the Inter-University Consortium for Political and Social Research. Neither NES/CPS nor the ICPSR are responsible for our use and interpretation of this information.

16 Even this figure is inflated, since we do not distinguish between those who say that they have no preference for any of the parties and those who describe themselves as pure independents.

17 See Zeller, R. A. and Carmines, E. G., Measurement in the Social Sciences: The Link Between Theory and Data (Cambridge: Cambridge University Press, 1980), pp. 63–7.

18 By contrast, Lazarsfeld et al. hypothesized that only political opinions change during an election season. See Lazarsfeld, P., Berelson, B. and Gaudet, H., The People's Choice, 3rd edn (New York: Columbia University Press, 1968).

19 Unfortunately, we cannot distinguish between these two possibilities with a single intraelection panel. We would need to follow our respondents for a period after the election long enough for any ephemeral activation effects to wear off.

20 Converse, , ‘The Nature of Belief Systems’; Converse, P. E., ‘Attitudes and Non-Attitudes: Continuation of a Dialogue’, in Tufte, E. R., ed., The Quantitative Analysis of Social Problems (Reading, Mass: Addison-Wesley, 1970).

21 Converse, P. E., ‘Comment: The Status of Non-Attitudes’, American Political Science Review, 68 (1974), 650–60.

22 Converse, unlike Dreyer, would not treat party identification as a belief that is highly subject to the problem of non-attitudes. Quite the contrary – he considers it the best example of a real political attitude. Nevertheless, since he does not offer a theory of partisan change in the short-run, there is no reason not to use his model to check for random response. See Dreyer, , ‘Change and Stability in Party Identification’; Converse, and Markus, , ‘Plus ça change…: The New CPS Election Study Panel’.

23 Converse, , ‘Comment: The Status of Non-Attitudes’, pp. 650–60.

24 Our measures of directional stability exclude leaning independents; only strong and weak identifiers are analysed.

25 See Brody, , ‘Stability and Change in Party Identification: Presidential to Off-Years’; Franklin, and Jackson, , ‘The Dynamics of Party Identification’.

26 See Fiorina, , Retrospective Voting in American National Elections, pp. 84105.

27 In decomposing the dependent variable, i.e. the measure of partisanship, we depart from the practice followed by Franklin and Jackson, who dismiss intransitivities in the seven-point, party identification scale as inconsequential. We are more impressed than they with the potential for heterogeneity, that is, for a different intra-election dynamic for different party-strength groups. Accordingly, and to explore potential heterogeneity, we have decomposed the measure of partisanship. See Franklin, and Jackson, , ‘The Dynamics of Party Identification’, p. 962.

28 In adopting this coding scheme, we assume that leaning independents are partisans and that the party identification scale is monotonic. While we do the former with little hesitation, we adopt the latter assumption with a great deal of trepidation. Although it is necessary to assume monotonicity in our analysis, we recognize that our measure will be unreliable and our findings will tend toward statistical insignificance to the extent that this assumption is violated. On classifying leaning independents as partisans, see Keith, B., Magleby, D., Nelson, C., Orr, E., Westlye, M. and Wolfinger, R., ‘The Myth of the Independent Voter’, paper delivered at the annual meeting of the American Political Science Association, 1977; and Brody, , ‘Stability and Change in Party Identification: Presidential to Off-Years’.

29 We recognize that we do not distinguish between personal and sociotropic evaluation of economic conditions. In the present study, we are less concerned about the etiology of system blame than about its effects. We believe that it is possible to assess the effects of economic satisfaction or dissatisfaction on partisanship irrespective of whether the judgement is personally or socially located. On the distinction between personal and sociotropic evaluations, see Sniderman, P. M. and Brody, R. A., ‘Coping: The Ethic of Self-Reliance’, American Journal of Political Science, 21 (1977), 501–21; Kinder, D. R. and Kiewiet, R. D., ‘Sociotropic Polities’, British Journal of Political Science, 11 (1981), 129–61.

30 See Hertel, B. R., ‘Minimizing Error Variance Introduced by Missing Data Routines in Survey Analysis’, Sociological Methods and Research, 4 (1976), 459–74.

31 See McKelvey, R. D. and Zavonia, W., ‘A Statistical Model for the Analysis of Ordinal Level Dependent Variables’, Journal of Mathematical Sociology, 4 (1975), 103–20.

32 The potential existence of some (although not all) individuals in the electorate who randomly change their partisan identification makes estimating a simultaneous recursive structure unfeasible: voters making random changes might alter their party identifications and then re-evaluate their political world to make it more consistent. Consequently, specifying a simultaneous recursive system would tend to yield artificially strong evidence that short-term electoral forces influence partisan change; instead we choose a conservative approach that reduces the probability of finding evidence for rejecting the null hypotheses.

33 See Weisberg, H., ‘Towards a Reconceptualization of Party Identification’, paper delivered at the annual meeting of the Midwest Political Science Association, 1978; Brody, R. A., ‘Measures of Party Identification in the 1979 Pilot Study’, a Report to the Board of Overseers of the National Elections Project, 1979.

34 Because of estimation problems with our probit analysis, the interaction term for nomination preference was subsequently dropped.

35 We had no a priori expectations about the directions the estimated coefficients for our interaction terms should take. We assume that estimates in the same direction as that predicted for the whole sample signify that Republicans are influenced more heavily than Democrats by the factor in question (since scores for Republicans were multiplied by one to form the interaction term). Similarly, estimates in the opposite direction suggest that Democrats are more strongly affected.

36 Our sample includes only forty-six strong identifiers who changed their identification in the P2 to P3 period. Consequently, the finding that party evaluations alone are significant is not much of a surprise.

37 It has been suggested that party assessments may be also measuring party identification. But if this is conceptually true, then party evaluations at P1 and P2 should not have any influence on changes in party identification in P2 and P3 respectively, i.e., change in party identification cannot be a function of party identification at a prior period. Thus, it is reasonable for both conceptual and empirical reasons to treat party evaluations as reflections of substantive forces and not as party identification.

38 When comparative party assessments are evaluated for the entire sample (not shown), even clearer evidence is found for the hypothesis that they are surrogates for other substantive forces. However, the results in Table 6 also demonstrate that if our other independent variables were used to form an instrument for party evaluations, the resulting measure would be highly unreliable because the level of explained variation ranges only between 10 and 30 per cent. These low R2 coefficients are not surprising given the small sample sizes and our approach to handling missing values. None the less, because of them we eschew an instrumental variable strategy.

39 Ideally, we would employ a multiple indicator approach to measure the underlying, short-term, substantive electoral forces. As it is not yet feasible to do so with limited dependent variables, we must leave this task to future analyses. On multiple indicators, see Joreskog, K. G. and Sorbom, D., LISREL V: Analysis of Linear Structural Relationships in Maximum Likelihood and Least Squared Methods (Uppsala, Sweden: University of Uppsala, Department of Statistics, 1981).

40 Of the strong partisans, 81.7 per cent and 82.7 per cent claim that they are concerned with the election's outcome in the P1 and P2 periods respectively; for other identifiers, these figures are 40.9 per cent and 46.0 per cent.

41 On the normal vote model see Converse, , ‘The Nature of Belief Systems in Mass Publics’; Miller, A., ‘Normal Vote Analysis: Sensitivity to Change Over Time’, American Journal of Political Science, 23 (1979), 406–25.

Even if we follow Achen's advice and replace normal vote analysis with regression-based approaches, we still need to know the best way to incorporate the long-term component into the model. See Achen, C., ‘The Bias in Normal Vote Estimates’, Political Methodology, 6 (1979), 343–55.

* Department of Political Science, Stanford University; Divison of Humanities and Social Sciences, California Institute of Technology. An earlier version of this article was presented at the Annual Meeting of the American Political Science Association, Chicago, 1983.

The Instability of Partisanship: An Analysis of the 1980 Presidential Election

  • Richard A. Brody and Lawrence S. Rothenberg


Altmetric attention score

Full text views

Total number of HTML views: 0
Total number of PDF views: 0 *
Loading metrics...

Abstract views

Total abstract views: 0 *
Loading metrics...

* Views captured on Cambridge Core between <date>. This data will be updated every 24 hours.

Usage data cannot currently be displayed