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Divided We Fall: Opposition Fragmentation and the Electoral Fortunes of Governing Parties

Published online by Cambridge University Press:  15 December 2009


This article introduces the concept of opposition fragmentation into the study of the determinants of election results. Empirical studies have demonstrated that anti-government economic voting is likely to take place where the clarity of responsibility (the degree to which voters can attribute policy responsibility to the government) is high. This argument is extended by focusing on the effects of the degree of opposition fragmentation in influencing the extent to which poor economic performance decreases the government’s vote share. With data from seventeen parliamentary democracies, it is shown that when there are fewer opposition parties, the relationship between economic performance and governing parties’ electoral fortune is stronger. Opposition fragmentation appears to be as strong a factor as the clarity of responsibility.

Research Article
Copyright © Cambridge University Press 2009

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1 See, for example, Rose, Richard and Mackie, Thomas T., ‘Incumbency in Government: Asset or Liability?’, in Daalder, Hans and Mair, Peter, eds, Western European Party Systems: Continuity and Change (Beverly Hills, Calif.: Sage Publications, 1983), pp. 115137.Google Scholar

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18 Laakso, Markku and Taagepera, Rein, ‘Effective Number of Parties: A Measure with Application to Western Europe’, Comparative Political Studies, 12 (1979), 327CrossRefGoogle Scholar. Since the sources of election results usually lump small parties into an ‘other’ category, we cannot precisely know which parties received how many seats. I used the method recommended by Taagepera to approximate the effective number of parties from incomplete data (see Taagepera, Rein, ‘Effective Number of Parties for Incomplete Data’, Electoral Studies, 16 (1997), 145151CrossRefGoogle Scholar).

19 The list of pre-electoral coalitions was obtained from Golder, Sona Nadenichek, The Logic of Pre-Electoral Coalition Formation (Columbus: The Ohio State University Press, 2006).Google Scholar

20 The data on this variable will be publicly available on the author’s website.

21 Anderson, , ‘Economic Voting and Political Context’Google Scholar; Bengtsson, , ‘Economic Voting’Google Scholar.

22 The correlation coefficient of the two variables is 0.630 in my data from seventeen democracies. Whether this number is high or low is a matter of personal judgement, yet my point is not on the empirical pattern but on the theoretical problem of using a variable of party system fragmentation when the interest is on opposition fragmentation.

23 Switzerland and the United States have sometimes been included in the literature, yet I chose to exclude them to focus only on parliamentary systems. Although France is not a pure parliamentary system, Lewis-Beck’s findings suggest that it can be treated as if it was a parliamentary system in the context of economic voting. Lewis-Beck, Michael S., ‘Who’s the Chef? Economic Voting under a Dual Executive’, European Journal of Political Research, 31 (1997), 315325CrossRefGoogle Scholar. The cases where a non-party cabinet existed before the election (Italy 1994 and 1996, Greece 1989 (November) and 1990, and Finland 1975) were excluded from the analysis. Also, elections that were held within one year after the previous elections were excluded (six cases) because those elections typically take place when the previous election did not produce a clear winner (for example, the February 1974 election in Britain) and the country needed another election to choose a governing party. Governments during such periods would not be held responsible for policy performances. Note that I repeated the analysis by including those observations and obtained comparable results (the detailed results are available upon request).

24 Powell, and Whitten, , ‘A Cross-National Analysis of Economic Voting’Google Scholar. I repeated my analysis by adding inflation rate and gross domestic product (GDP) growth rate, but the results remained unchanged (the detailed results are available upon request). The data for the unemployment rate were obtained from OECD’s website ( and missing values were filled from the Bulletin of Labour Statistics by the International Labour Office. The unemployment rate used is the average value of four quarters including the quarter the election took place, as used by Powell and Whitten.

25 Some may question whether the inclusion of this variable ‘overcontrols’ the model because the dependent variable is the change from the previous election to the current election. Yet, this is a standard configuration of a regression model in this line of research (see Powell, and Whitten, , ‘A Cross-National Analysis of Economic Voting’, p. 394).Google Scholar

26 Lijphart, Arend, Electoral Systems and Party Systems: A Study of Twenty-Seven Democracies, 1945–1990 (New York: Oxford University Press, 1994).CrossRefGoogle Scholar

27 Powell, and Whitten, , ‘A Cross-National Analysis of Economic Voting’.Google Scholar

28 The actual estimation was performed with the ‘xtpcse’ command with the ‘hetonly’ option in Stata version 9.2. The command ‘xtpcse’ estimates panel-corrected standard errors developed in Beck, Nathaniel and Katz, Jonathan N., ‘What to Do (and Not to Do) with Time-Series Cross-Section Data’, American Political Science Review, 89 (1995), 634647CrossRefGoogle Scholar. Using the ‘hetonly’ option, the model does not correct for contemporaneous correlation. This does not apply to my data, because the timing of elections is different in each country. More specifically, the panel-corrected standard errors method requires at least one time period common to all panels in order to estimate disturbance covariance for the correction of contemporaneous correlation. To check for a potential problem of contemporaneous correlation, I repeated the analysis while including dummy variables of decades. The results remained unchanged.

29 Bollen, K. A. and Jackman, R. W., ‘Regression Diagnostics: An Expository Treatment of Outliers and Influential Cases’, in J. Fox and J. S. Long, eds, Modern Methods of Data Analysis (Newbury Park, Calif.: Sage, 1990), pp. 257291.Google Scholar

30 The detailed results of the robustness checks are available upon request.

31 For example, the coefficient on UNEMP reported in the table is the marginal effect of UNEMP on the dependent variable only when ENOP is 0, which is outside the range of the ENOP variable. Likewise, since UNEMP is not 0 except for extraordinary circumstances, the reported coefficient and standard error of ENOP do not have any substantive meanings by themselves.

32 Friedrich, Robert J., ‘In Defense of Multiplicative Terms In Multiple Regression Equations’, American Journal of Political Science, 26 (1982), 797833CrossRefGoogle Scholar; Brambor, Thomas, Roberts Clark, William and Golder, Matt, ‘Understanding Interaction Models: Improving Empirical Analyses’, Political Analysis, 14 (2006), 6382CrossRefGoogle Scholar.

33 In the original ‘clarity’ variable, smaller values indicated higher clarity. In my analysis, I flipped the values for easier interpretation.

34 Since one standard deviation lower than the mean in the ENOP variable is below its lower limit, ENOP is kept at 1 (its lowest value) in Graph C.