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.
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. 115–137.
2 Mueller, John E., ‘Presidential Popularity from Truman to Johnson’, American Political Science Review, 64 (1970), 18–34.
3 Paldam, Martin, ‘The Distribution of Election Results and the Two Explanations of the Cost of Ruling’, Europrean Journal of Political Economy, 2 (1986), 5–24.
4 Kramer, Gerald H., ‘Short-term Fluctuations in U.S. Voting Behavior, 1896–1964’, American Political Science Review, 65 (1971), 131–143. In a related line of research that originates from Mueller and Goodhart and Bhansali, scholars have examined the impact of economic variables on the executive’s popularity rate (see Mueller, ‘Presidential Popularity’; and Goodhart, C. A. E. and Bhansali, R. J., ‘Political Economy’, Political Studies, 18 (1970), 43–106).
5 For example, Paldam, Martin, ‘A Preliminary Survey of the Theories and Findings on Vote and Popularity Functions’, Europrean Journal of Political Research, 9 (1981), 181–199; Lewis-Beck, Michael S., Economics and Elections: The Major Western Democracies (Ann Arbor: University of Michigan Press, 1988); Høst, Viggo and Paldam, Martin, ‘An International Element in the Vote? A Comparative Study of Seventeen OECD Countries, 1948–85’, European Journal of Political Research, 18 (1990), 221–239; Paldam, Martin, ‘How Robust Is the Vote Function? A Study of Seventeen Nations over Four Decades’, in Helmut Norpoth, Michael S. Lewis-Beck and Jean-Dominique Lafay, eds, Economics and Politics: The Calculus of Support (Ann Arbor: University of Michigan Press, 1991), pp. 9–31.
6 For example, Remmer, Karen L., ‘The Political Impact of Economic Crisis in Latin America in the 1980s’, American Political Science Review, 85 (1991), 777–800; Remmer, Karen L., ‘The Political Economy of Elections in Latin America, 1981–1991’, American Political Science Review, 87 (1993), 393–407; Pacek, Alexander C., ‘Macroeconomic Conditions and Electoral Politics in East Central Europe’, American Journal of Political Science, 38 (1994), 723–744; Fidrmuc, Jan, ‘Economics of Voting in Post-Communist Countries’, Electoral Studies, 19 (2000), 197–217; Pacek, Alexander C. and Radcliff, Benjamin, ‘The Political Economy of Competitive Elections in the Developing World’, American Journal of Political Science, 39 (1995), 745–759; Wilkin, Sam, Haller, Brandon and Norpoth, Helmut, ‘From Argentina to Zambia: A World-Wide Test of Economic Voting’, Electoral Studies, 16 (1997), 301–316.
7 Bingham Powell, G. and Whitten, Guy D., ‘A Cross-National Analysis of Economic Voting: Taking Account of the Political Context’, American Journal of Political Science, 37 (1993), 391–414, p. 391.
8 Lewis-Beck, , Economics and Elections, pp. 108–109.
9 Powell, and Whitten, , ‘A Cross-National Analysis of Economic Voting’.
10 For example, Whitten, Guy D. and Palmer, Harvey D., ‘Cross-National Analysis of Economic Voting’, Electoral Studies, 18 (1999), 49–67; Chappell, Henry W. Jr and Gonçalves Veiga, Linda, ‘Economics and Elections in Western Europe: 1960–1997’, Electoral Studies, 19 (2000), 183–197; Royed, Terry J., Leyden, Kevin M. and Borrelli, Stephen A., ‘Is “Clarity of Responsibility” Important for Economic Voting? Revisiting Powell and Whitten’s Hypothesis’, British Journal of Political Science, 30 (2000), 669–698; Bengtsson, Åsa, ‘Economic Voting: The Effect of Political Context, Volatility and Turnout on Voters’ Assignment of Responsibility’, European Journal of Political Research, 43 (2004), 749–767.
11 For example, Anderson, Christopher J., Blaming the Government: Citizens and the Economy in Five European Democracies (Armonk, N.Y.: Sharpe, 1995) ); Anderson, Christopher J., ‘Economic Voting and Political Context: A Comparative Perspective’, Electoral Studies, 19 (2000), 151–170; Nadeau, Richard, Niemi, Richard G. and Yoshinaka, Antoine, ‘A Cross-National Analysis of Economic Voting: Taking Account of the Political Context Across Time and Nations’, Electoral Studies, 21 (2002), 403–423; Anderson, Cameron D., ‘Economic Voting and Multilevel Governance: A Comparative Individual-Level Analysis’, American Journal of Political Science, 50 (2006), 449–463; Duch, Raymond M. and Stevenson, Randolph T., The Economic Vote: How Political and Economic Institutions Condition Election Results (New York: Cambridge University Press, 2008).
12 Duch, and Stevenson, , The Economic Vote, p. 26.
13 Powell, and Whitten, , ‘A Cross-National Analysis of Economic Voting’.
14 Duch, and Stevenson, , The Economic Vote, pp. 293–308.
15 Sartori, Giovanni, Parties and Party Systems: A Framework for Analysis (New York: Cambridge University Press, 1976); Alan Ware, Political Parties and Party Systems (Oxford: Oxford University Press, 1996), p. 173.
16 Roberts, Kenneth M. and Wibbels, Erik, ‘Party Systems and Electoral Volatility in Latin America: A Test of Economic, Institutional, and Structural Explanations’, American Political Science Review, 93 (1999), 575–590.
17 Roberts, and Wibbels, , ‘Party Systems and Electoral Volatility’, p. 583.
18 Laakso, Markku and Taagepera, Rein, ‘Effective Number of Parties: A Measure with Application to Western Europe’, Comparative Political Studies, 12 (1979), 3–27. 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), 145–151).
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).
20 The data on this variable will be publicly available on the author’s website.
21 Anderson, , ‘Economic Voting and Political Context’; Bengtsson, , ‘Economic Voting’.
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), 315–325. 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’. 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 (www.SourceOECD.org) 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).
26 Lijphart, Arend, Electoral Systems and Party Systems: A Study of Twenty-Seven Democracies, 1945–1990 (New York: Oxford University Press, 1994).
27 Powell, and Whitten, , ‘A Cross-National Analysis of Economic Voting’.
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), 634–647. 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. 257–291.
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), 797–833; Brambor, Thomas, Roberts Clark, William and Golder, Matt, ‘Understanding Interaction Models: Improving Empirical Analyses’, Political Analysis, 14 (2006), 63–82.
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.
* Department of Political Science, University of North Texas (email: firstname.lastname@example.org). Earlier versions of this article were presented at the Midwest Political Science Association Conference, Chicago, 2004, and the Japanese Association of Electoral Studies, Tokyo, 2004. The author would like to thank the participants of the panels at these conferences, Mark Jones, Bill Jacoby, Eric Chang, Burt Monroe, Wonjae Hwang, Andrew Enterline, Akitaka Matsuo and also anonymous referees for their helpful comments and suggestions on the various stages of this research.
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