APR303755 by Juan Pardo

American Politics Research http://apr.sagepub.com

Do You See What I See? Perceptions of Party Differences and Voting Behavior Craig Goodman and Gregg R. Murray American Politics Research 2007; 35; 905 DOI: 10.1177/1532673X07303755 The online version of this article can be found at: http://apr.sagepub.com/cgi/content/abstract/35/6/905

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Do You See What I See? Perceptions of Party Differences and Voting Behavior

Craig Goodman Gregg R. Murray Texas Tech University, Lubbock

We approach the issues of partisanship and voting behavior by focusing specifically on a seldom-studied group—the substantial proportion of citizens who see little to no important differences between the major parties. Motivated by the heuristics and burgeoning behavioral economics literatures, we conclude that party cues help reduce uncertainty for voters. More specifically, for voters lacking these cues, we expect that there will be a bias toward the incumbent candidate or party, which is motivated by the desire to decrease the potential costs of postdecision regrets. Similarly, we expect that these individuals are likely to delay choosing between candidates and may abstain from voting altogether, which is driven by a shortage of justifications on which to base the decision. We develop measures of perceived party differences based on symbolic and operational differences using data from the American National Election Study and find significant support for our hypotheses in the context of presidential elections. Keywords: party identification; political parties; voting; elections; heuristics; partisan cues; behavioral economics; partisanship

olitical activists such as Ralph Nader argue that there are few meaningful differences between Republicans and Democrats in contemporary American politics, but the party platforms adopted every 4 years tell a different story. At the aggregate level, growing levels of elite polarization (Brewer & Stonecash, 2007; Fiorina, Abrams, & Pope, 2005; Hetherington, 2001; Poole & Rosenthal, 1997) have contributed to each party’s adopting more distinctive policy positions and greater emphasis on mobilizing base supporters (Abramson, Aldrich, & Rohde, 2006; Pomper, 2005). However, whereas political elites become increasingly polarized, a substantial mass of American citizens do not perceive any significant differences between the parties and seem to agree with Nader. American National Election Study (ANES) data from 1952 to 2004 reveal that on average, 37% of Americans 905 Downloaded from http://apr.sagepub.com by Juan Pardo on November 14, 2007 © 2007 SAGE Publications. All rights reserved. Not for commercial use or unauthorized distribution.

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do not perceive differences between Democrats and Republicans in presidential election years, despite a significant decline in 2004. This phenomenon is even more pronounced for midterm elections, as an average of 46% of Americans do not perceive differences between the major parties during the same time period. For many Americans, partisanship is the most important predictor of political behavior, and there is empirical evidence suggesting that the effect of partisanship has increased (Bartels, 2000). If partisanship is an important predictor of political behavior, but Americans do not perceive differences between the parties, this presents us with a puzzle. How constructive is partisanship for political decision making? To address this question, we explore the political behavior of citizens who do not perceive significant differences between the major parties. In particular, we focus on the vote choice and the timing of voting decisions of these citizens in an effort to better understand why party cues are a valuable heuristic for voters. Drawing on the burgeoning literature in behavioral economics, we conclude that party cues help reduce uncertainty for voters. For voters lacking these cues, we suggest that there will be a bias toward the incumbent party, which is motivated by the desire to decrease the potential costs of postdecision regret. Similarly, we suggest that voters who do not perceive party differences are likely to delay choosing between candidates and may abstain from voting altogether, which is driven by the emotional costs imposed by uncertainty resulting from a shortage of justifications on which to base the decision. As such, our investigation proceeds as follows. In the next section, we provide the theoretical foundations for our argument by discussing the role of partisanship as a heuristic and the effects of uncertainty in decision-making processes. We then detail our hypotheses and the operationalization of our variables. The results of our empirical analyses follow. We conclude with a discussion of the results and the significant implications these results have for understanding voting behavior in the United States.

Heuristics and Decision Making Elections in the United States provide citizens with an important opportunity to choose their government representatives and influence the direction of public policies. Americans are asked to vote more often and make more political choices than citizens in most other democracies, and for even the most informed citizens this process can be complex. Given the complicated issues that voters face at both the national and the state levels, it makes sense

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that most voters look for some kind of shortcut because it is often irrational to invest the time and effort necessary to be well informed on most political issues (Downs, 1957; Riker & Ordeshook, 1968). However, social cognition research has offered a mechanism through which democracy may endure the complexities of the political process and challenges of less-than-ideal citizens. Research in heuristics theory suggests that everyone has and uses decision-making shortcuts, which serve to compensate for a lack of knowledge and to manage the overwhelming flow of information. According to Lau and Redlawsk (2001), heuristics can be thought of as “problem-solving strategies (often employed automatically or unconsciously)” (p. 952) that regulate information-processing requirements and prevent them from exceeding cognitive capacity. Heuristic processing is vital because the alternative is decision-making paralysis, which would result from a lack of appropriate information on which to base a decision, or an overwhelmed cognitive process, which would treat all new information as unique. Much to the relief (and sometimes concern) of those apprehensive about the viability of democracy, there is substantial evidence that political decisions are subject to heuristic processing (e.g., Brady & Sniderman, 1985; Hamill, Lodge, & Blake, 1985; Kam, 2005; Lau & Redlawsk, 2001; Lodge & Hamill, 1986; Lupia, 1994; McDermott, 2005, 2006; Mondak, 1993; Ottati, 1990; Rahn, 1993; Scholz & Lubell, 1998; Sniderman, Hagen, Tetlock, & Brady, 1986). In his seminal work, Downs (1957) argued that voters reduce the cost of voting by relying on informational shortcuts disseminated by trusted experts and those with greater knowledge who share the voters’ political goals. The most prominent political heuristic that citizens use when making decisions is party affiliation (Lau & Redlawsk, 2001). Campbell, Converse, Miller, and Stokes (1960) argued that voters tend to develop a psychological attachment to one of the major parties, and this provides them with a lens through which to evaluate political events and political actors. Rahn (1993) found that the public stereotypes the parties with “rich cognitive categories containing not only policy information but group alliances, trait judgments, specific examples of group members, and performance assessments” (p. 474). This provides citizens with a shortcut to decision making, therefore reducing the time and effort required to evaluate their political environment. It also suggests that party cues enable citizens to clarify their political choices and vote in a rational, informed manner without investing a lot of resources to educate themselves (Calvert, 1985; McKelvey & Ordeshook, 1986; for a critique of the accuracy of political cues, see Bartels, 1996; Kuklinski & Hurley, 1994; Lau & Redlawsk, 2001). Through

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these cues, voters can assess the histories of the behavior of the political parties, which can then be used to anticipate the behavior of each partyâ&#x20AC;&#x2122;s candidates if elected to office. This greatly simplifies the informational demands placed on voters, particularly those motivated by issues. Instead of evaluating each individual candidate, the voter evaluates the two common brands of candidates and chooses the brand that is most appealing (Aldrich, 1995; Cox & McCubbins, 1993; Snyder & Ting, 2002). Also, there is considerable evidence that partisan cues are strong and important to voter decision making (e.g., Lau & Redlawsk, 2001; Rahn, 1993). Furthermore, the affective attachment party identifiers feel may motivate them to participate as a manifestation of party support in otherwise unattractive political activities (Verba, Nie, & Kim, 1978). What happens, then, when cues are not available to distinguish between the parties? The literature on nonpartisan elections provides some indication of the consequences when this information is institutionally deprived. One consequence is that voters depend on other types of cues. For example, in nonpartisan elections, voters have been found to take cues from racial or ethnic identification (Lineberry & Fowler, 1967; Pomper, 1966; Squire & Smith, 1988), name recognition or incumbency (Jacobson, 2004; Jewell & Breaux, 1988; Lineberry & Fowler, 1967; Schaffner, Streb, & Wright, 2001), and group endorsements (Lupia, 1994). Another consequence is that turnout is depressed (Lineberry & Fowler, 1967; Schaffner et al., 2001). Studies of nonpartisan judicial elections suggest that a consequence of the lack of party cues about state supreme court candidates is unstructured voting decisions (Dubois, 1979; Squire & Smith, 1988), an increase in the number of voters who held no opinion on an election (Squire & Smith, 1988), a significant shift in vote preference (Squire & Smith, 1988), and an increase in idiosyncratic results (Dubois, 1979). Furthermore, in the absence of party labels in statewide nonjudicial races, survey respondents with less education were less likely to express a vote preference, and respondents who did have a vote preference were less capable of structuring their vote choice by partisanship (Schaffner & Streb, 2002).

Why Cues Matter Although there is ample evidence that partisan cues matter, the discussion about why they matter remains unsettled. That is, why does the lack of party cues decrease the probability that a person will vote or increase the probability that a person will vote for the incumbent or recognized name? One potentially fruitful approach resides in the literature on behavioral economics and,

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more broadly, judgment and decision making. The rationalâ&#x20AC;&#x201C;emotional model of decision avoidance portrays decision making as a process in which choices are driven by the calculation of expected probabilities and outcomes, which in turn are subject to anticipatory emotions that influence affective goals (Anderson, 2003). Among other things, this perspective asserts that satisfactory decisions require reasons or justifications. When those reasons or justifications are absent, citizens face more uncertainty, and the consequence is an inability to make a decision in anticipation of an increased probability of postdecisional regret. Similarly, perceiving only small differences between alternatives increases preference uncertainty, and citizens will defer making a decision (Dhar, 1997). Furthermore, individuals who are presented with similarly attractive alternatives tend to desire additional alternatives, and those who are presented with weak alternatives tend to extend the search for better ones (Tversky & Shafir, 1992). In the end, this model asserts that preference uncertainty is an important contributor to selection difficulty. And selection difficulty, in turn, causes decision avoidance manifested by a preference for the status quo and/or choice deferral or refusal. Preference for the status quo has been associated with increased emotional costs related to regret (Anderson, 2003). Respondents attempt to reduce or avoid the emotional costs of postdecisional regret by choosing the alternative that represents the status quo (Inman & Zeelenberg, 2002). This alternative constitutes the choice with which, often, individuals already have had a tolerable experience or, if there is no previous experience, with which they assume they will have a tolerable experience in the future. In vote choice, this model implies a bias toward the incumbent candidate or party in the absence of party cues. That is, the lack of partisan cues reduces the potential reasons an individual has to vote for a challenger and, therefore, increases the probability and potential cost of postdecisional regret if voting for the challenger. This leads an individual to attempt to reduce the probability of postdecisional regret by voting for the candidate with which she or he has probably had a tolerable experience, the incumbent. Of course, this implication is consistent with votersâ&#x20AC;&#x2122; tendencies in nonpartisan elections to turn to cues from name recognition or incumbency to make their vote choices (Jacobson, 2004; Jewell & Breaux, 1988; Lineberry & Fowler, 1967; Schaffner et al., 2001). On the other hand, choice deferral has been associated with increased emotional costs related to the difficulty of justifying a decision under conflict (Tversky & Shafir, 1992), the desire to avoid negative emotions generated by making trade-offs between alternatives (Luce, 1998), and the effort required to overcome the uncertainty caused by choosing between similar alternatives (Dhar, 1997). This reasoning comports well with the calculus of

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voting. Very simply, the model of decision avoidance implies that the lack of perceived differences between the major parties (i.e., justifications for a vote choice) increases selection difficulty and, therefore, the emotional costs of voting, which by the logic of the calculus of voting decreases the probability that an individual will vote. Heuristics and behavioral economic theories, then, may provide important leverage on our understanding of voting behavior. Using this approach, we expect that incumbent-party candidates enjoy an advantage among voters who do not perceive significant differences between the parties because those voters fall back on other cues such as name recognition or tolerable experience with the status quo. We also expect that voters who do not perceive differences are more likely to defer or even avoid (i.e., abstain) the vote decision as the uncertainty increases selection difficulty and, therefore, the emotional costs of voting.

Data and Methods To evaluate our research questions, we rely on data from ANES for the years 1984 to 2004.1 Following the rational–emotional model of decision avoidance, we focus on uncertainty in the decision-making process, which we capture by measuring the differences respondents perceive between the major parties.2 Our measures of perceived differences fall into two categories: operational and symbolic.3 Operational differences between the parties include specific characteristics they exhibit that distinguish one from the other, such as competing positions on important issues. Symbolic differences capture the abstract feelings individuals have toward the parties and system of partisanship. This conception of differences encompasses Rahn’s (1993) stereotypes that involve information pertaining to policy positions as well as judgments about considerations such as party traits and performance. In some sense, these two conceptions can be thought of as indications of uncertainty caused by a lack of factual knowledge of party differences (operational) and by attitudes about the lack of party differences (symbolic). Our measure of perceived symbolic differences is the question “Do you think there are any important differences in what the Republicans and Democrats stand for?”4 A respondent who indicates that there are no important differences is coded 0, whereas an individual who indicates that there are important differences is coded 1. Our measure of perceived operational differences is an additive index of the differences between the placement of the major parties relative to each other on scales concerning government

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spending, defense spending, and party ideology.5 For example, the government spending question is Some people think the government should provide fewer services, even in areas such as health and education, in order to reduce spending. Other people feel that it is important for the government to provide many more services even if it means an increase in spending. Where would you place the Democratic [Republican] Party on this scale?

The index of operational differences ranges from scores of 0 to 3 (mean = 2.3, standard deviation = 1.0). Respondents who place the parties at different points of the scale are coded 1, whereas those who place the parties at the same point are coded 0.6 We then sum the three items to create an additive index ranging from 0 to 3, with higher numbers indicating that the respondent perceives more operational differences between the parties. Although we might expect that citizens will have consistent views (i.e., perceptions of symbolic and operational differences or vice versa), the extant work in public opinion (Zaller, 1992) suggests this might be an unreasonable expectation. To capture this differentiated effect, we also create three indicator variables that are structured for comparison to respondents who perceive both operational and symbolic differences. The first indicator variable represents respondents who see neither operational nor symbolic differences, the second represents respondents who see symbolic but not operational differences, and the third represents the reverseâ&#x20AC;&#x201D;respondents who see operational but not symbolic differences. In each case, the indicator variable is coded 1 for the specified type of respondent and 0 otherwise. To create this structure and for ease of interpretation and consistency with the symbolic differences variable, we restructure the operational differences variable for these measures into the dichotomous form. Respondents who have a score of 2 or 3 on the operational differences index are coded 1, and 0 otherwise. We begin with the distributions of our primary independent variables. From a sample of 5,157 respondents, 25% perceived no symbolic differences between the major parties, whereas 7% perceived zero operational differences, and another 17% perceived only one operational difference. In terms of the differentiated variables, those perceiving both types of differences comprise 61% of the sample, and those perceiving neither comprise 9%. On the other hand, those discerning operational but not symbolic differences constitute 16% of respondents, and those discerning symbolic but not operational differences constitute 14%.

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So, who are the people who see no differences? Table 1 indicates that they tend to have substantively and statistically less education, income, interest in the elections, political knowledge, media exposure, and external efficacy. For example, 35% of respondents with only a high school education see no symbolic differences, whereas only 15% of those with a college degree perceived no symbolic differences. Similarly, 12% of those with only a high school education see no operational differences, whereas only 2% of those with a college degree see none. Conversely, about half of those with only a high school education perceive the maximum number of operational differences, whereas 7 out of 10 of those with a college degree perceive them as well. In terms of other characteristics, women, those who live in the South, and those who identify as independents or apolitical are less likely to see differences. Furthermore, those who believe that both parties will handle the most important problem the same and those who care less about who wins the election are less likely to perceive differences. On the other hand, there appear to be no substantive differences by age, race or ethnicity, or trust in the government. An initial look at the primary relationships of interest indicates that the perception of differences between the parties plays a nontrivial role in voting behaviors. Bivariate analyses suggest that respondents who perceived no operational differences were three times more likely to abstain than those who perceived the maximum differences (49% vs. 15%, χ2 = 177.21, p < .001), whereas those who perceived no symbolic differences were more than twice as likely to abstain as their counterparts (37% vs. 16%, χ2 = 167.94, p < .001). Similarly, though less dramatically, those who perceived no operational differences were more likely to vote for the incumbent candidate or party than those who perceived the maximum differences (58% vs. 51%, χ2 = 8.84, p = .03) as were those who perceived no symbolic differences (53% vs. 50%, χ2 = 3.79, p = .05). Given these meaningful bivariate relationships, next we model voters’ support for the incumbent presidential candidate or party and vote choice deferral or avoidance to examine more fully the effects of not perceiving differences between the parties.

Voting for the Incumbent We turn first to the decision of voters to support the incumbent president and follow a model that is similar to the one employed by Nadeau and Lewis-Beck (2001). Scholars have been analyzing the factors that contribute to the likelihood of an incumbent presidential candidate’s winning reelection since the ANES started collecting survey data on public attitudes. We expect

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Table 1 Who Are They? Perceptions of Differences by Selected Demographics and Attitudes (in percentages)

Education High school or less Some college College degree Income 0-33 percentile 34-67 percentile 68-100 percentile Sex Female Male Region South Non-South Partisanship strength Independent/apolitical Strong partisan Party handling most important problem Same Not same Interest in election Not much Very interested Political knowledge Low Average High Media exposure No media All media External efficacy Low Medium High Care who wins Not much Cares

No Symbolic Differences

No Operational Differences

Maximum (3) Operational Differences

35 22 15

12 5 2

49 62 71

31 25 20

10 7 3

52 59 68

28 22

8 5

55 66

28 24

9 6

54 62

45 16

29 4

34 65

41 17

10 4

53 66

38 17

18 4

42 69

39 29 16

17 8 2

37 51 71

38 10

11 2

49 81

31 25 21

9 7 5

55 58 64

44 21

13 5

47 62

Note: All cross-tabulations are statistically significant, p < .05.

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that incumbent-party candidates enjoy an advantage among voters who do not perceive significant differences between the parties because those voters fall back on other incumbent-advantaging cues such as name recognition or tolerable experience with the status quo to make their vote choice. Following this, our first hypothesis is Hypothesis 1: When respondents perceive no difference between the major parties, they will be more likely to vote for the incumbent candidate or party in the case of an open-seat presidential election.

There is often a close correspondence between economic performance and the fortunes of the incumbent party (Abramson, Aldrich, & Rohde, 2003). Although debate continues about which economic evaluations are salient, the bottom line is quite simple: If voters believe that the economy is performing well, they can use this informational shortcut (Downs, 1957; Popkin, 1994) to simplify their decision-making process. Although there is evidence of a strong retrospective component to the voting decision (Fiorina, 1981), there is also evidence that voters engage in prospective voting (MacKuen, Erikson, & Stimson, 1992). Nadeau and Lewis-Beck (2001) incorporate the retrospective and prospective economic dynamics of the vote decision in their model. They argue that when economic evaluations are above average, the incumbent party benefits. We seek to build on these analyses by incorporating information on the extent to which citizens differentiate between the Democrats and the Republicans. Our dependent variable in Model 1 is the respondent’s self-reported presidential vote; respondents who voted for the incumbent or incumbent party are coded 1, and 0 otherwise. The independent variables include individual-level measures of evaluations of retrospective and prospective economic performance (better coded 1, same coded 0, and worse coded –1), a dummy variable indicating the presence of a sitting incumbent in the race that is interacted with each of the two economic evaluations, and a dummy variable indicating the incumbent party (Democrat coded 1, Republican coded –1) with interactions with a dummy variable for race (non-White coded 1, White coded 0) and party identification (7-point scale with strong Democrat coded 3 and strong Republican coded –3). Following Nadeau and Lewis-Beck (2001), we expect retrospective and prospective evaluations of the economy to be associated positively with voting for the incumbent or incumbent party, incumbent party to be negatively associated; the incumbentparty interactions with party identification and race to be positively associated; and the no-incumbent interaction with retrospective economic evaluation

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to be positively associated and the interaction with prospective economic evaluation to be negatively associated. It is important to note that we present two specifications each for our dependent variables of incumbent vote and vote choice deferral: a maineffects model and a differentiated-effects model. The main-effects models specify the dichotomous measure of perceived symbolic differences and the ordinal measure of operational differences. The differentiated-effects models specify, in place of the main-effects variables, indicator variables for those who see neither symbolic nor operational differences, those who see symbolic but not operational differences, and those who see operational but not symbolic differences. The pertinent comparison group in the differentiatedeffects models is composed of those respondents who see both symbolic and operational differences. In Table 2, we present our empirical results (probit estimates) for the incumbent presidential vote. The only noteworthy inconsistency between our findings and those of Nadeau and Lewis-Beck (2001) is the interaction between the measure of no incumbent running and future economic assessment, which is not statistically significant in our results. Although we feel this finding is inconsequential to this research, we believe one explanation may be the changing role of economic assessment between the different time frames (1984-2004 compared to Nadeau and Lewis-Beck’s [2001] 1956-1996). Given this confirmation of the basic relationships, the results reported in Table 2 tell an important story. Model 1a, the main-effects model, suggests that the lack of perceived operational differences plays a significant role in people’s decision to vote for the incumbent. More specifically, although the symbolic differences measure is not significant, the negative sign on the operational differences variable indicates that a change from perceiving no operational differences to perceiving the maximum operational differences decreases the probability of voting for the incumbent candidate or party from 0.71 to 0.60.7 We note that the marginal effect is statistically significant at p < .001. In Model 1b, the differentiated-effects model, the positive sign on the variable indicating the perception of symbolic differences but not operational differences implies that these respondents are 9 percentage points (0.60 to 0.69) more likely to vote for the incumbent than the comparison group composed of those who perceive both types of differences. In the same model, the positive sign on the measure indicating respondents who see neither symbolic nor operational differences suggests that those respondents are 11 percentage points (0.60 to 0.71) more likely to vote for the incumbent than those in the comparison group. We note that the marginal effects are statistically significant at p ≤ .001. In all, these results support

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Table 2 Incumbent Vote Model Model 1a Symbolic differences Operational differences No symbolic/no operational

–.053 (.055) –.100** (.026) —

No symbolic/yes operational

—

Yes symbolic/no operational

—

Retrospective economy Prospective economy No incumbent president No Incumbent × Retrospective No Incumbent × Prospective Incumbent party Party identification Race Party Identification × Incumbent Party Race × Incumbent Party Constant N χ2 Log-likelihood Correctly classified Proportional reduction in error

.529** (.044) .152** (.049) –.127* (.055) –.280** (.069) –.093 (.077) –.190** (.033) .030* (.013) –.006 (.073) .532** (.013) .408** (.073) .405** (.075) 5,157 3,907.09 –1,620.25 88% 76%

Model 1b — — .301** (.080) .071 (.066) .247** (.076) .531** (.044) .150** (.049) –.134* (.055) –.284** (.069) –.088 (.077) –.195** (.033) .030* (.013) –.006 (.074) .532** (.013) .409** (.073) .064** (.047) 5,157 3,908.06 –1,619.76 88% 76%

Note: Coefficients are maximum likelihood estimates for a probit model; standard errors are in parentheses. *p < .05, two-tailed. **p < .01, two-tailed.

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Hypothesis 1 and suggest that the lack of perceived differences between the parties plays a significant role in respondentsâ&#x20AC;&#x2122; vote choice by increasing the probability that they will vote for the incumbent candidate or party.8

Choosing to Participate (or Not) Next, we suggest that the absence of perceived differences between the major parties has implications for the length of time for which a voter defers candidate choice or, more broadly, the voterâ&#x20AC;&#x2122;s determination to avoid the decision by permanently deferring (i.e., abstaining). We believe that voters who do not perceive differences are more likely to defer the vote decision or to avoid the decision by abstaining as the uncertainty increases selection difficulty and, therefore, the emotional costs of voting. As such, our second hypothesis is Hypothesis 2: When respondents perceive no difference between the major parties, they will be more likely to defer their vote choice decisions until closer to election day or to avoid choosing altogether by abstaining.

Given that avoiding or permanently deferring the vote choice is a decision not to turn out, we believe that a model of turnout is an appropriate mechanism through which to examine vote choice deferral or avoidance. Previous research finds that a combination of individual- and macro-level factors influences turnout. The most prominent individual-level characteristic is partisanship, as those with stronger party identification are more likely to vote (Campbell et al., 1960). In addition to partisanship, political knowledge and interest as well as demographic variables such as age, education, wealth, and political efficacy are positively associated with the likelihood of voting (e.g., Rosenstone & Hansen, 1993; Verba & Nie, 1972; Wolfinger & Rosenstone, 1980). The political context also affects the decision to vote. Party contact and personal canvassing (Gerber & Green, 2000; Hillygus, 2005; Rosenstone & Hansen, 1993), contact by political elites (Rosenstone & Hansen, 1993; Verba, Schlozman, & Brady, 1995), and close races (Jacobson, 2004; Rosenstone & Hansen, 1993) are associated with increased levels of voter turnout. Although Alvarez (1998) argued that voters who are uncertain are less supportive of presidential candidates and Abramson et al. (2003) found that voters who are neutral between the parties are equally likely to support the incumbent or the opposition party, voters who are unsure about the parties typically are not addressed in these analyses. We seek to extend these analyses by incorporating information on the extent to which citizens perceive differences between the two major parties.

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We turn first to a number of bivariate results to gain some intuition about the characteristics of respondents who do not perceive differences between the major parties and their self-reported turnout to vote. That is, how do those who do not see differences and do not vote differ from those who do not see differences but do vote? Table 3 indicates that those who failed to perceive differences and abstained tended to have less education, income, interest in the election, political knowledge, media exposure, external efficacy, and interest in who wins. For example, 75% of those who saw no symbolic differences and abstained held a high school degree or less compared to 52% of those who saw no symbolic differences but voted. Similarly, 69% of those who saw no operational differences and abstained were in the lowest income percentile versus 47% of those who saw no operational differences but voted. There is also evidence that these respondents tended to be younger, independent or apolitical, and non-White; there was also an indication that they tended to have less trust in government and to reside in the South. On the other hand, there appear to be no substantive differences by sex or belief in which party will handle the most important problem. Broadly speaking, these results suggest that voters and nonvoters who do not perceive differences between the major parties are similar to voters and nonvoters in general (e.g., Rosenstone & Hansen, 1993; Verba & Nie, 1972; Wolfinger & Rosenstone, 1980), which highlights the independent effect of failing to perceive differences on voting behavior. The model we use to test the vote choice deferral and avoidance hypothesis is similar to Rosenstone and Hansenâ&#x20AC;&#x2122;s (1993) turnout model. Our dependent variable captures the time period when respondents decided who they would support in the election. That is, respondents who knew for whom they were going to vote all along (i.e., deferred least) are coded 1, and respondents who abstained (i.e., avoided the choice and permanently deferred) are coded 7. The intervening decision points are when the candidate announced (coded 2), during the convention (coded 3), during the postconvention period (coded 4), during the last 2 weeks (coded 5), and on election day (coded 6). The independent variables include measures of income, education, age, race or ethnicity, homeownership, church attendance, years in the community (logged), residence in the South, work status, internal and external political efficacy, strength of party identification, party and presidential affect, contact from a party, perceptions of closeness of the election, and the actual closeness of the election. Because the perception of no differences between the major parties may be a proxy for a lack of political knowledge or political interest, we also include controls for these constructs. Following Rosenstone and Hansen, we expect residence in the South, the squared-age

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Table 3 Who Are They? No Perceived Differences and Turnout (in percentages)

Education High school or less Some college College degree Income 0-33 percentile 34-67 percentile 68-100 percentile Region South Non-South Partisanship strength Independent/apolitical Strong partisan Interest in election Not much Very interested Political knowledge Low Average High Media exposure No media All media External efficacy Low Medium High Care who wins Not much Cares Trust in government Low High Age 17-24 65+ Race White Other

No Symbolic Differences

No Operational Differences

Abstained

Voted

Abstained

Voted

75 19 6

52 27 20

84 13 3

65 23 12

54 33 13

33 34 33

69 26 6

47 30 23

40 60

33 67

ns ns

27 11

13 24

44 6

27 22

47 12

18 29

57 8

26 25

64 29 7

19 45 36

71 25 4

38 46 16

20 4

7 8

22 1

10 1

47 36 17

32 37 31

55 33 12

37 34 30

56 44

28 72

57 43

27 73

ns ns

38 26

28 22

18 16

5 20

15 15

9 20

68 32

81 19

69 31

80 20

Note: All cross-tabulations are statistically significant, p < .05, unless noted as not significant (ns).

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term, and non-White race or ethnicity to be positively associated with deferral or avoidance, whereas we expect the remaining independent variables to be negatively associated. The empirical results (ordered probit estimates) of our vote choice deferral or avoidance model appear in Table 4. The only noteworthy inconsistency is an opposite sign on the indicator for Black respondents, which we believe is inconsequential to this research. Our results, then, are largely consistent with those of Rosenstone and Hansen (1993), and the empirical results in Table 4 suggest that the lack of perceived differences between the parties plays a significant role in peopleâ&#x20AC;&#x2122;s vote deferral and avoidance. The negatively signed coefficient on the symbolic differences variable in the main-effects model (Model 2a) suggests that respondents who see little to no symbolic difference between the major parties are more likely to defer longer or even abstain, whereas those who see a useful difference are less likely to defer or abstain. Translating the ordered probit coefficients into predicted probabilities indicates that the change in probability that an individual will abstain increases from .15 when seeing differences to .19 when not, a pattern that is consistent although less substantial for respondents who make their vote decisions in the latter part of the campaign season (i.e., last 2 weeks and on election day). Alternatively, the change in probability that an individual will know all along for whom to vote (i.e., defer least) decreases from .13 when seeing differences to .10 when not, whereas it also decreases for those who decide at the time of candidate announcement from .23 to .20. We note that all of these marginal effects are statistically significant at p â&#x2030;¤ .02 even when controlling for political interest and knowledge. The results in the differentiated-effects model (Model 2b) also indicate that deferral and avoidance are related to the perception of difference. In Model 2b, the positive coefficients for those individuals who perceive neither symbolic nor operational differences and those individuals who perceive operational but not symbolic differences indicate that these citizens are more likely to defer or avoid their vote decisions when contrasted with the comparison group composed of those who see symbolic and operational differences. The change in probability that an individual will abstain increases from .15 for the comparison group to .20 for individuals who saw neither symbolic nor operational differences (.19 for those who see operational but no symbolic differences). Again, this pattern is consistent for similar respondents who make their vote decisions in the last 2 weeks and on election day. Alternatively, the change in probability that an individual will know all along for whom to vote decreases from .13 for the comparison group to .10 for individuals who see neither symbolic nor operational differences (also .10 for

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Table 4 Ordered Probit Analysis: Deferring or Avoiding Making a Decision in the Presidential Campaign Model 2a

Model 2b —

No symbolic/no operational

–.163** (.046) –.009 (.021) —

No symbolic/yes operational

—

Yes symbolic/no operational

—

Symbolic differences Operational differences

Income Education Employed Contact Age Age2 Internal efficacy External efficacy Strength of party identification Party affect Care who wins Presidential affect Community years Church attendance Homeowner

–.048* (.022) –.080** (.027) –.075 (.051) –.161** (.044) –.009 (.007) .000 (.000) .002 (.023) .000 (.000) –.185** (.022) –.013 (.011) –.393** (.053) –.065** (.009) –.026 (.017) –.033** (.013) –.233** (.049)

— .182** (.065) .143* (.056) –.022 (.057) –.049* (.022) –.081** (.027) –.075 (.051) –.158** (.044) –.009 (.007) .000 (.000) .002 (.023) .000 (.000) –.185** (.022) –.014 (.011) –.393** (.053) –.065** (.009) –.027 (.017) –.033** (.013) –.232** (.049) (continued)

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Table 4 (continued)

Perceived closeness Actual closeness South Black Hispanic Interest in election Political knowledge Cut 1 Cut 2 Cut 3 Cut 4 Cut 5 Cut 6 n χ2 Log-likelihood Correctly classified Proportional reduction in error

Model 2a

Model 2b

.025 (.048) –.016** (.003) .057 (.043) –.232** (.066) .182* (.090) –.101** (.033) –.164** (.025) –4.372 (0.195) –3.614 (0.193) –3.276 (0.192) –2.791 (0.191) –2.392 (0.190) –2.212 (0.189) 3,063 1,062.22 –5,147.36 34% 14%

.025 (.048) –.016** (.003) .058 (.043) –.233** (.066) .183* (.090) –.102** (.033) –.165** (.025) –4.207 (0.202) –3.448 (0.200) –3.110 (0.200) –2.625 (0.198) –2.227 (0.197) –2.053 (0.197) 3,063 1,062.52 –5,147.21 34% 14%

Note: Coefficients are maximum likelihood estimates for an ordered probit model; standard errors are in parentheses. *p < .05, two-tailed. **p < .01, two-tailed.

those who see operational but not symbolic differences), whereas it also decreases for those who decide at candidate announcement (i.e., defer somewhat) from .23 for the comparison group to .20 for those seeing neither difference (also .20 for those who see operational but not symbolic differences). We note that all of these marginal effects are statistically significant at p ≤ .04 even when controlling for political interest and knowledge.

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Figure 1 Marginal Effects of Perceiving No Differences on Length of Deferral 0.06

Change in Predicted Probability byLength of Deferral

0.05 Symbolic (main)

0.04

No Sym/No Op (differentiated) 0.03

No Sym/Yes Op (differentiated)

0.02 0.01 0.00 -0.01 -0.02 -0.03 -0.04 -0.05 All Along

Announce

Convention

Post-Conv

Last 2 Weeks

Elect Day

Abstain

Decision Time (Defer Longer?)

Figure 1 provides consolidated evidence from the main-effects and differentiated-effects models that vote decision deferral and avoidance are related to the perception of differences between the major parties. That is, it suggests that not perceiving differences increases the probability that a citizen will decide for whom to vote in the latter part of the election season, whereas it decreases the probability that a citizen will decide earlier in the season. In all, these results support Hypothesis 2 and suggest that the lack of perceived differences between the parties plays a significant role in respondentsâ&#x20AC;&#x2122; deferral or avoidance of the vote decision.

Discussion and Conclusion Broadly speaking, these results suggest that the absence of perceptions of party differences has nontrivial implications for peopleâ&#x20AC;&#x2122;s voting behavior. These findings suggest that individuals who see little to no difference between

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the major parities are more likely to vote for the incumbent candidate or party and are more likely to defer their vote decision or even to avoid it altogether by abstaining. More specifically, the differentiated-effects models indicate that the impact of discerning neither symbolic nor operational differences is robust. Those who discern neither difference are more likely to vote for incumbents and are more likely to defer their vote decisions than those who discern both symbolic and operational differences. Furthermore, the differentiated-effects models suggest that differentiating respondents, those who perceive one type of difference but not the other, are more likely to vote for the incumbent candidate or party (Model 1b) and are more likely to defer (Model 2b) than those who perceive both types of differences. The lack of perceived differences, as well, plays a specific and meaningful role in the maineffects models. Model 1a suggests that operational differences matter for people’s decision to vote for the incumbent or not, whereas Model 2a suggests that it is symbolic differences that are important for the decision to defer or not. Our empirical results suggest that different factors (i.e., perceived symbolic and operational differences) matter to respondents when choosing to participate. We believe that the decision to vote may be subject to symbolic differences that reflect a gut feeling about politics and the system of partisanship. However, once voters have made the choice to participate, the perceived differences between the parties—the operational differences—exert a greater effect and serve as one justification for the vote choice. The fields of behavioral economics and judgment and decision making seem to provide a useful theoretical framework for why partisan cues matter and, more specifically, why the lack of partisan cues increases the probability that individuals will vote for the incumbent or defer or avoid their vote decisions. The results presented here support the proposed explanation of why this may be the case. That is, the rational–emotional model of decision avoidance asserts that satisfactory decisions require justifications. When those justifications are absent, individuals face more preference uncertainty and, therefore, more important, an increased probability of postdecisional regret. People attempt to reduce the probability of this regret by deferring the decision or avoiding it altogether. The model of decision avoidance implies, then, that the lack of perceived differences between the major parties increases selection difficulty and, therefore, the emotional costs of voting that by the logic of the calculus of voting decreases the probability that an individual will vote. Similarly, individuals may be able to reduce the probability of postdecisional regret by choosing the alternative with which they already have had a tolerable experience or, if there is no previous experience, with which they assume they will have a tolerable experience. In vote choice, this

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model implies a bias toward the incumbent candidate or party in the absence of party cues. That is, the lack of partisan cues reduces the potential justifications an individual has to vote for a challenger and, therefore, increases the probability and potential cost of postdecisional regret if voting for the challenger. This leads the voter to attempt to reduce the probability of postdecisional regret by voting for the candidate with which she or he has probably had a tolerable experience, the incumbent. Broadly speaking, then, the lack of partisan cues increases selection difficulty, which increases the cost of both voting in general (leading to decision deferral and avoidance) and voting for a challenger (leading to increased support for the incumbent). Our results raise a number of interesting questions to be addressed in future research. Primarily, who are these people who do not perceive differences between the major parties? The bivariate relationships reported in Table 1 suggest that they tend to have lower socioeconomic status, interest in the elections, political knowledge, media exposure, and external efficacy, but the substantive import of the results reported here call for a more thorough analysis of who they are. For example, what is the nature of the missing information? Do these individuals fail to demand differentiating political information, or are they overwhelmed by and/or unable to process effectively the supply of complicated information swirling about the political environment? To further understand these individuals, what differentiates them in terms of their political behavior? For instance, why do some of them turn out on election day whereas others do not? Why do some of them vote for the incumbent and others do not? Are these people more likely to vote for minor party or independent candidates? Are they more likely to participate by other means such as through interest groups? These and many more questions become viable given the significance of the attitudes reported here. In all, the results suggest that a lack of perceived differences between the major parties plays a theoretically, substantively, and statistically significant role in peopleâ&#x20AC;&#x2122;s voting behavior. Compared to citizens who perceive differences between the major parties, citizens who discern little to no difference are more likely to defer their vote decisions or even abstain and are more likely to vote for the incumbent candidate or party. Although the scholarship on nonpartisan elections speaks to the importance of party cues from an institutional perspective, our findings speak to their importance from an attitudinal perspective. Importantly, the two perspectives yield similar results. Our findings and those of scholars of nonpartisan elections suggest that the absence of partisan information affects voting behavior. Whether partisan information is limited by institutional barriers or by the perceptions of citizens, the lack of partisan information seems to affect voter choices meaningfully.

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Appendix Description of Variables Alphabetical listing of dependent and independent variables, including references, when appropriate, to variable numbers (with prefix VCF) from the American National Election Study 1948-2004 Cumulative Data File. Dependent Variables Model 1: Vote for incumbent presidential candidate/party (1) or not (0). Derived from VCF0705 and Incumbent Party. Model 2: Vote deferral or avoidance coded deferred least (1) to permanently deferred/abstained (7). Derived from VCF0712 and VCF0702. Primary Independent Variables: Operational differences: Index constructed from the following: Comparison between the parties in government spending: “Some people think the government should provide fewer services, even in areas such as health and education, in order to reduce spending. Other people feel that it is important for the government to provide many more services even if it means an increase in spending. Where would you place the Democratic Party [VCF0541, Republican Party VCF0542] on this scale?” coded reduce spending a lot (1) to increase spending a lot (7). Comparison between the parties in defense spending: “Some people believe that we should spend much less money for defense. Others feel that defense spending should be greatly increased. Where would you place the Democratic Party [VCF0549, Republican Party VCF0550] on this scale?” coded greatly decrease spending (1) to greatly increase spending (7). Comparison between the parties in political ideology: “Here is a seven-point scale on which the political views that people might hold are arranged from extremely liberal to extremely conservative. Where would you place the Democratic Party [VCF0503, Republican Party VCF0504]?” coded extremely liberal (1) to extremely conservative (7). Symbolic differences: “Do you think there are any important differences in what the Republicans and Democrats stand for?” coded yes (1) or no (0). VCF0501. Secondary Independent Variables Age: VCF0101. Church attendance: never (0) to every week (4). VCF0130. Close election (actual): Absolute value of the difference in percentage of the vote received by the Democratic and Republican presidential candidates. Close election (perception): Respondent believes presidential race will be close (1) or not (0). VCF0714. Contacted by party: A major party contacted the respondent (1) or not (0). VCF9030A.

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Education: Grade school or less (1), high school (2), some college (3), college or advanced degree (4). VCF0110. Efficacy (external): Index constructed from “People like me don’t have any say about what the government does” and “I don’t think public officials care much what people like me think” coded least (0) to most efficacious (100). VCF0648. Efficacy (internal): “Sometimes politics and government seem so complicated that a person like me can’t really understand what’s going on” coded low (0: agree) to high efficacy (2: disagree). VCF0614. Employed: Currently working (1) or not (0). VCF0116. Gender (female): Female (1) or male (0). VCF0104. Homeowner: Homeowner (1) or not (0). VCF0146. Income: Family income by categories of increasing percentiles. VCF0114. Incumbent party: Party of sitting president coded Democratic (1) and Republican (–1). Interest in outcome: Respondent cares a good deal who wins the election (1) or not (0). VCF0311. Interest in the election: Respondent is/was very much interested (3), somewhat interested (2), or not much interested (1). VCF0310. Media exposure: Media types exposed to coded no media (0) to all media (4). VCF0728. No incumbent: No incumbent running for re-election (1) or not (0). Following Nadeau and Lewis-Beck (2001), no incumbent ran in 1976, 1988, and 2000. Party affect: Absolute value of respondent’s net affect toward major parties coded neutral (0) to maximum Democrat/Republican (10). VCF0322. Party handling most important problem: Handle it the same (0) or other (1). VCF9012. Party identification: Strong Republican (–3) to strong Democrat (3). VCF0301. Party identification strength: Apolitical/independent (1), leaning independent (2), weak partisan (3), and strong partisan (4). VCF0305. Political knowledge: Interviewer observation of respondent’s general level of information about politics coded very low (1) to very high (5) following Zaller (1992). VCF00050b. Presidential affect: Absolute value of respondent’s net affect toward major party presidential candidates coded neutral (0) to maximum Democrat/ Republican (10). VCF0409. Prospective economic evaluation: Respondent’s assessment of national economy over next year coded worse (–1) to better (1). VCF0872. Race/ethnicity (Black): Black respondent (1) or other (0). VCF0106A. Race/ethnicity (Hispanic): Hispanic respondent (1) or other (0). VCF0106A. Region (South): Resides in South (1) or non-South (0). South is the 11 secession states: Alabama, Arkansas, Florida, Georgia, Louisiana, Mississippi, North Carolina, South Carolina, Tennessee, Texas, and Virginia. VCF0113. Retrospective economic evaluation: Respondent’s assessment of national economy over past year coded worse (–1) to better (1). VCF0870.

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Trust in government: Index coded least trusting of government (0) to most trusting (100). VCF0656. Years in community: natural log of VCF9001.

Notes 1. The items that compose one of our primary independent variables, operational differences, were not asked until 1984. As a result, we limit our analysis to the years 1984 to 2004 (American National Election Study [ANES], 1995-2000). 2. This focus on uncertainty in the decision-making process is conceptually distinct from political independence, which is associated with party identification and the psychological attachment to a party. It is conceivable, though, that political independence may contribute to or be affected by uncertainty in the decision-making process. 3. For a similar conceptualization of symbolic and operational differences, see the treatment of operational and symbolic ideology (Free & Cantril, 1967; Robinson & Fleishman, 1984; Stimson, 2004). 4. This question has been asked since 1952 and is item VCF0501 in the 1948-2004 ANES cumulative data file. 5. These placement scales have been asked together in the ANES since 1984 and are identified in the cumulative data file as items VCF0541/VCF0542 (government spending), VCF0549/VCF0550 (defense spending), and VCF0503/VCF0504 (party ideology). We focus on these three measures because they were asked consistently from 1984 to 2004, unlike some of the other placement scales such as womenâ&#x20AC;&#x2122;s equal role in society, which was asked only twice during the time frame, and because they often tap the most salient issues in presidential campaigns. 6. We do not distinguish whether respondents have placed the parties correctly because we believe that perception of differences is more important than correct political knowledge. Furthermore, respondents were asked this battery of questions only if they had placed themselves on the 7-point scale. A closer examination of the data reveals that on each of the items used to construct our measure of operational differences, the percentage of respondents who placed both themselves and the parties ranged from 74% (government services/spending) to 80% (liberal/conservative ideology). As such, we believe it is reasonable to conclude that nonresponse is not biasing our results. 7. We tried an alternative coding for our operational differences variable to account for the magnitude of the differences that respondents perceive. In the alternative coding, we coded a respondent as seeing an operational difference for a particular measure if her or his placement of the parties exceeded the mean difference perceived by all respondents. For example, the mean difference on the placement of the parties for government services and spending was 2.3, so a respondent whose absolute difference was greater than 2.3 was coded 1, and 0 otherwise. We repeated this for the other two measures that composed the operational differences index. The regression results were nearly identical to the original model using the alternative coding. 8. We estimated an alternative model in which the feeling thermometer for the incumbent party candidate served as the dependent variable. This dependent variable provides more observations, but the results are substantively similar. Although the coefficient for symbolic differences is negative and statistically significant, the coefficient for operational differences remains negative and statistically significant. Given the important differences between attitudes and behaviors, in this case we believe it is reasonable to focus on the more behaviorally oriented vote choice measure.

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Craig Goodman is an assistant professor of political science at Texas Tech University. His research investigates congressional organization and procedures. Gregg R. Murray is an assistant professor of political science at Texas Tech University. His research focuses on the psychology of political behavior.