Abstract
It is conventional to speak of voting as “habitual.” But what does this mean? In psychology, habits are cognitive associations between repeated responses and stable features of the performance context. Thus, “turnout habit” is best measured by an index of repeated behavior and a consistent performance setting. Once habit associations form, the response can be cued even in the absence of supporting beliefs and motivations. Therefore, variables that form part of the standard cognitive-based accounts of turnout should be more weakly related to turnout among those with a strong habit. We draw evidence from a large array of ANES surveys to test these hypotheses and find strong support.
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Notes
There is a subtle point here regarding the role of goals and motivations in the affective intelligence theory. This theory states that once habits form, the behavior may continue independent of the presence of the original motivations that encouraged habit formation. However, the emotional surveillance system constantly checks the degree to which automatic behavioral scripts are facilitating the achievement of desired goals. It is when behaviors no longer lead to expected outcomes that anxiety increases and habits are broken. Thus, unlike our theory, goals and motivations are still crucial in the affective intelligence theory, albeit one step removed from the kinds of direct cognitive reasoning in standard behavioral and rational-choice models of turnout.
It might be possible to hypothesize the existence of two kinds of non-voters. First, there may be individuals who make a conscious and deliberate decision every Election Day to abstain. It could be argued that such individuals could develop a habit of abstention. But there are also the second type of non-voters who are simply unaware and inattentive. These individuals would be only vaguely aware of the election, and their non-voting behavior would not be the result of any intentional decision. However, our current theoretical presentation and empirical analysis remains silent about the role of habitual non-voting because our measures do not allow us to discriminate between these two types of individuals. In any case, there is little, if any, evidence to suggest that a large amount of non-voting is a result of intentional abstention rather than passive inaction.
We have run our model on all available presidential election years, but only report the years with validated turnout. The results for other years are available on request.
Because of a concern for consistency in coding, we did not use the ANES cumulative file.
See Aldrich et al. (2007) for further analyses of some of these alternatives. Note that the choice among these various measures does not affect the results of the tests of our hypotheses.
See the online Appendix for a lengthier discussion of these issues.
Full model specifications for all years are available upon request. We note that this is not quite the exact hypothesis test for interactive hypotheses, but we will demonstrate that below.
Estimates were made using the Zelig program in R v2.9. All control variables were set at their actual data points, and the 95% CI represent the estimate of first differences averaged across all respondents in a given year. This method of examining an interactive model follows the suggestion of Brambor et al. (2006).
All results were conducted in MPLUS v4.2 using a WLSMV estimator and a probit link function. A full discussion of the SEM analysis used here is presented in the online Appendix.
We estimate a fixed effects model, that is, we include dummy variables to control for year effects. These results do not include the additional control variables in the Rosenstone–Hansen model. Those are included below.
It might be possible to take this idea even further and divide the population into four groups based on the two dichotomous indicators of context stability and repeated behavior. However, it is unclear what patterns we would expect to see amongst the intermediate categories (stable context but inconsistent voters versus unstable context and consistent voters). As a robustness check, this would seem to add more confusion than clarity. Moreover, the differences between coefficient estimates become increasingly difficult to discriminate as sample sizes in each group shrink and confidence intervals increase.
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Acknowledgments
The authors are extremely grateful to Chris Achen, Rick Hoyle, Michael MacKuen, Abigail Panter, and Eric Plutzer. We are particularly grateful to Ashley Taylor for her assistance with early data analyses. A previous version of this paper was presented at the 2008 Annual Meeting of the Midwest Political Science Association. Montgomery received funding from a National Science Foundation Graduate Research Fellowship.
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Survey Question Appendix
Survey Question Appendix
Income
Question wording varied from year to year, but this variable is always coded as family income. In the early years of the time-series (1958–1966) the question focused on the family’s expected income for this year. Afterwards the question focused on the family income in the previous year. Coding: 0 if 1–16th percentile, 0.25 if 17th–33rd percentile, 0.50 if 34th–67th percentile, 0.75 if 68th–95th percentile, 1 if 96th–100th percentile.
Coded using variables v580501, v640269, v660235, v720420, v742549, v763507, v800686, v700388, v941404, P023149.
Education
Question wording has varied from year to year, but for most of the time series it is possible to construct stable categories. Coding: 0 if 8 grades or less, 0.25 if 9–12 grades with no diploma or equivalency, 0.50 if 12 grades, diploma, or equivalency, 0.75 if some college, 1 if college degree or higher.
For 1994, the 1992 panel data was used. For the 2002 year, the 2000 response was used. Individuals who reported having community college or junior college degrees were coded as 0.75.
Coded using variables v580478, v640196, v660197, v720300, v700269, v742423, v763398, v800445, v941209, P023131.
Unemployed
Questions that asked about employment status of respondent wording changed somewhat from year to year. From 1958 to 1966 this data was only collected about the head of the household rather than the respondent. Coding: 1 if unemployed, 0 otherwise.
Coded using variables v580479, v640202, v660199, v700275, v720306, v742443, v763409, v800515, v941216, P025183.
Age
Coding: Age in years.
Age Squared
Coding: The square of the above response.
External Efficacy
Question wording: “Now I’d like to read some of the kinds of things people tell us when we interview them. Please tell me whether you agree or disagree with these statements.” “I don’t think public officials care much what people like me think.” “People like me don’t have any say about what the government does.” Coding: for each item, coded 0 if agree, 1 if disagree, then summed and rescaled to zero–one interval.
Internal Efficacy
Question wording: “Sometimes politics and government seem so complicated that a person like me can’t really understand what’s going on.” Coding: 0 if agree, 1 if disagree.
Duty
Question wording: “If a person doesn’t care how an election comes out then that person shouldn’t vote in it.” Coding: 0 if agree, 1 if disagree. We note here that this variable does not appear in the final Rosenstone–Hansen mode, but we wished to include it in this analysis. In future versions of this paper this variable may not be included.
Strength of Party Identification
Question wording: “Generally speaking, do you usually think of yourself as a Republican, a Democrat, and Independent, or what?” (If Republican or Democrat) “Would you call yourself a strong (Republican/Democrat) or not very strong?” (If independent, other, or no preference) “Do you think of yourself as closer to the Republican or Democratic party?” Coding: 0 if independent or apolitical, 0.33 if independent leaning toward a party, 0.67 if a weak partisan, 1 if a strong partisan.
Affect for Party
Question wording: “Is there anything in particular you like about the Republican party?” “Is there anything in particular you dislike about the Republican party?” “Is there anything in particular you like about the Democratic party?” “Is there anything in particular you dislike about the Democratic party?” Coding: the absolute value of the difference between two sums, coded to the zero–one interval: the sum of Democratic party “likes” and Republican party “dislikes” minus the sum of Democratic party “dislikes” and Republican party “likes.” For the 2002 respondents, their responses from 2000 were used. For 1974 respondents, their responses from the 1972 surveys were used.
Care
Question wording (Presidential year): “Generally, speaking, would you say that you personally care a good deal which party wins the presidential election this fall, or don’t you care very much which party wins?” Question wording (Mid-term): “Now I’d like to talk with you a bit about the elections which took place this fall. As you know, representatives to the Congress in Washington were chosen in this election from congressional districts all around the country. How much would you say that you personally cared about the way the elections to congress came out: very much, pretty much, not very much, or not at all?” Coding: 1 if care a good deal, pretty much, or very much. 0 otherwise (including non-response).
Wording does change somewhat from year to year. This variable was coded using variables v580312, v640020, v660063, v700164, v720029, v742026, v763030, v800061, v940209, P023007.
Affect for Candidate
Question wording: “Is there anything in particular you like about [the appropriate Republican candidate]?” “Is there anything in particular you dislike about [the appropriate Republican candidate]?” “Is there anything in particular you like about [the appropriate Democratic candidate]?” “Is there anything in particular you dislike about [the appropriate Democratic candidate]?” Coding: the absolute value of the difference between two sums, coded to the zero–one interval: the sum of Democratic candidate “likes” and Republican candidate “dislikes” minus the sum of Democratic candidate “dislikes” and Republican candidate “likes.”
Church
Question wording (1952–1968): “Would you say you go to church regularly, often seldom, or never?” Coding: 0 if never, 0.33 if seldom, 0.67 if often, 1 if regularly. Question wording (1970–2002): “Would you say you go to (church/synagogue) every week, almost every week, once or twice a month, a few times a year, or never?” Coding: 0 if never, 0.33 if a few times a year, 0.67 if once or twice a month, 1 if every week or almost every week. In 1994 an experimental version of this question appeared, so 1992 responses were used instead.
Years in Community
Question wording: “How long have you lived here in your present (city/town)?” Coding: actual number of years. When respondent chose “all of my life” their age was imputed here. When this variable was used on the right hand side, it is transformed using a natural logarithm to induce normality.
Contacted
Question wording: “The political parties try to talk to as many people as they can to get them to vote for their candidates. Did anyone from one of the political parties call you up or come around and talk to you about the campaign? Which party was that?” Coding: 0 if not contacted, 1 if contacted.
South
Observed by interviewer. Coding: 1 if lives in Alabama, Arkansas, Florida, Georgia, Louisiana, Mississippi, North Carolina, South Carolina, Tennessee, Texas, or Virginia, 0 otherwise.
Border
Observed by interviewer. Coding: 1 if lives in Missouri, Kentucky, Maryland, Oklahoma, or West Virginia, 0 otherwise.
Black
The question wording on race and ethnicity have probably changed more throughout the ANES time-series than any other variable here. Throughout most of the time-series blacks, “negro”, or African-American is presented as one option. Coding: 1 if black, 0 otherwise. In the 2002 survey respondents were allowed to mark multiple racial and ethnic categories. All respondents who marked more than three categories were coded as missing and otherwise were coded as 1 if any of their choices included black or African-American.
Hispanic
This variable is missing for 1958. In the early years of the time series (1964) the best we were able to do was include the “other” category (coding: 1 if other, 0 otherwise) as this seemed to be the category that shifted most when Hispanic options were added in 1966. From 1966 until 1976 respondents were given the option to identify themselves as Mexican–American or Puerto Rican (coding: 1 if Mexican or Puerto Rican and 0 otherwise). For 1980 and 1994 ethnicity was coded separately and all those of Hispanic origin are coded as 1, and respondents were coded as 0 otherwise. In 2002 multiple choices were allowed, and we followed the analogous scheme as described in the “black” variable above.
Race and ethnicity variables were coded using variables, v580469, v640183, v660237, v720425, v742554, v763513, v800721, v800722, v700391, v941435, v941419, P023150.
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Aldrich, J.H., Montgomery, J.M. & Wood, W. Turnout as a Habit. Polit Behav 33, 535–563 (2011). https://doi.org/10.1007/s11109-010-9148-3
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DOI: https://doi.org/10.1007/s11109-010-9148-3