Regulatory Fit and Persuasion, p.
Regulatory Fit, Rhetorical Strategy, and Political Persuasion
Christopher D. Johnston
Department of Political Science
Duke University
Durham, NC 27708
christopher.johnston@duke.edu
Howard Lavine
Department of Political Science
University of Minnesota
Minneapolis, MN 55455
lavine@umn.edu
Paper prepared for the 2012 annual meeting of the Midwest Political Science Association, April
12th-15th, Chicago, IL.
1
Regulatory Fit and Persuasion, p.
2
Abstract
We argue that citizen dispositions influence the relative success of different rhetorical strategies
for persuasion, and thus function to constrain the behavior of elite actors in their attempts to win
support for favored outcomes. Drawing on the psychological concept of regulatory fit, we
propose that recent work on psychological dispositions and political preferences can be
understood in terms of functional matches between the regulatory focus of citizens (prevention
or promotion) and the framing of policies in terms of losses and gains (e.g. Cesario et al. 2004;
Higgins 1998). In two experiments that rely on several policy domains, we find that persuasion is
facilitated when a policy is framed so that it matches the chronic regulatory focus of the
individual. We also provide some support for the idea that regulatory fit orientations constrain
the advertising strategies of political campaigns. We conclude by considering the implications of
these results for elite campaign strategy, and for the potential to micro-target persuasive
communications on the basis of personality.
Regulatory Fit and Persuasion, p.
3
Fully understanding the political importance of framing requires considering the two-way street
of mutual interaction and influence among elites and mass publics. The common understanding
of framing as a top-down, elite-driven process should be replaced with a more complex view
whereby the beliefs and experiences of citizens affect what will resonate with them.
- Smith (2009)
A spate of recent research has shown that citizens’ stable psychological dispositions (e.g.
traits, goals, needs) exert a substantial influence on their political preferences, identifications,
and ideologies (e.g. Amodio et al. 2007; Carney et al. 2008; Hetherington and Weiler 2009;
Gerber et al. 2010; Jost et al. 2003; Mondak 2010; Settle et al. 2010). In a widely-read theoretical
integration of this literature, Jost, Glaser, Kruglanski and Sulloway (2003) argue that people
embrace political conservatism because it serves a variety of motivational needs, including the
reduction of “fear, anxiety, and uncertainty; [the avoidance of] change, disruption, and
ambiguity; and to explain, order, and justify inequality among groups and individuals” (p. 340).
From this point of view, political conservatism is simply a special case of motivated social
cognition.
In this research, we consider the broader political implications of such influence.
Specifically, we argue that individual psychological dispositions constrain elite behavior by
moderating the relative success of different rhetorical strategies on mass attitude change.
Drawing on the concept of regulatory fit (Higgins 2005), we hypothesize that associations
between psychological dispositions and political preferences emerge as a function of “matches”
between the chronic regulatory focus of the individual (prevention or promotion), and the
framing of policies in terms of losses or gains (Cesario et al. 2004; Higgins 1998). When the
message frame matches the individual’s regulatory focus, persuasion is enhanced. This suggests
the potential for elites to construct issue frames to fit the dispositional characteristics of an
intended audience, or, in other words, to engage in personality-based micro-targeting of political
Regulatory Fit and Persuasion, p.
4
messages. Such dynamics also imply a more powerful role for citizens in politics by suggesting
one way in which they may be more than vessels to be filled with elite opinion.
The remainder of the paper proceeds as follows: In the next section, we briefly touch on
recent studies linking psychological dispositions and political preferences, and suggest that this
work can be conceptually understood within the auspices of Higgins’ (1998) regulatory focus
framework. We then outline the concept of regulatory fit, and discuss its implications for
political persuasion. We test this framework with two experiments and aggregate (state-level)
data, and conclude with a discussion of the broader implications of the theory and empirical
findings.
Dispositional Influence on Political Preferences
Research on the role of stable individual differences on political preference draws on
several subfields in psychology, including personality (e.g. Carney et al. 2008; Gerber et al.
2010; Mondak 2010), social cognition (e.g. Hetherington and Weiler 2009; Jost et al. 2003),
cognitive neuroscience (e.g. Amodio et al. 2007; Oxley et al. 2008), and behavioral genetics (e.g.
Alford, Funk and Hibbing 2005; Settle et al. 2010). Within personality psychology, the strongest
effects on ideology are consistently found for the trait of openness to experience (which refers to
a preference for novelty and stimulation versus the routine and familiar). Within the social
cognitive literature, the need for non-specific cognitive closure (Kruglanski and Webster 1996;
an indicator of aversion to ambiguity and need for certainty), is a strong predictor of conservative
leanings (e.g. Chirumbolo et al. 2004; Thorisdottir and Jost 2011; Van Hiel, Pandelaere and
Duriez 2004). Neuroscientific studies have linked conservatism to both cognitive rigidity (i.e.
deficits in conflict monitoring; Amodio et al. 2007) and sensitivity to threatening visual and
Regulatory Fit and Persuasion, p.
5
auditory stimuli (Oxley et al. 2008; Smith et al. 2011). And within behavioral genetics, Settle et
al. (2010) have identified a specific gene associated with novelty seeking, a trait linked to
liberalism (Carney et al. 2008; Mondak 2010).
We believe it may be heuristically useful to subsume these empirical findings within a
single theoretical framework that preserves their commonalities, but offers more straightforward
guidance on the relevance of psychological predispositions to elite strategic behavior.
Specifically, we adopt Higgins’ (1998) regulatory focus theory (hereafter, RFT), which holds
that individuals chronically differ in the strategies by which hedonic principles (seeking pleasure
and avoiding pain) are employed in the self-regulation of affect, cognition, and behavior.
According to RFT, people either prefer a positive strategy focused on achieving gains (i.e., a
promotion focus) or a negative strategy focused on avoiding losses (i.e., a prevention focus).
Promotion-focused individuals attempt to maximize “hits” and minimize errors of omission,
whereas prevention-focused individuals attempt to maximize correct rejections and minimize
errors of commission.1 In this sense, promotion-focused individuals are oriented toward the
achievement of maximal goals such as hopes, wishes, and aspirations (i.e. ideals), while
prevention-focused individuals are oriented toward the achievement of minimal goals such as the
attainment of security and the fulfillment of duties and obligations (i.e. oughts).
The commonalities between regulatory focus and the work reviewed above should be
readily apparent. A promotion-focused strategy entails openness to error and failure, comfort
with risk-reward tradeoffs, and a relatively low need for security. Conversely, a preventionfocused strategy entails sensitivity to negative outcomes, an aversion to risk and loss, and a
1
It is important to note that regulatory focus is a general psychological principle, and thus operates both as a stable
individual difference and, potentially, as a contextually-induced state (Higgins 1999). We see this as an additional
advantage of this theoretical language, in contrast to, say, the “Big Five” which focuses on constructs unique to
personality psychology.
Regulatory Fit and Persuasion, p.
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relatively high need for security. The greater concern among prevention-focused (versus
promotion-focused) individuals with oughts (duties, obligations) is also consistent with recent
work indicating that conservatives ascribe greater importance than liberals to the moral
principles of in-group loyalty, submission to legitimate authority, and the protection of
culturally-evolved institutions (Haidt 2012; Haidt and Graham 2007).2
Regulatory Fit and Persuasion
Within the persuasion context, regulatory focus at the individual level operates by
moderating the appeal of messages framed in terms of either the gains to be achieved from a
recommended action, or losses to be incurred from not taking the action (see also Kahneman and
Tversky 1979). Promotion-focused individuals are characterized by eagerness for gains and
advancement, while prevention-focused individuals are characterized by their vigilance against
losses. As Higgins (1998: 31) explains, “individuals with a strong promotion focus should be
more motivated by incentives that are relevant to goals of accomplishment, whereas those with a
strong prevention focus should be more motivated by incentives that are relevant to goals of
safety” (p. 31).
Shah, Higgins and Friedman (1998) provided empirical support for RFT by examining
success in solving anagram problems conditional on chronic regulatory focus (promotion or
prevention) and the frame of a monetary incentive. In one condition, participants were informed
that they could earn a dollar (gain frame) if they solved 90 percent of the puzzles, while in a
2
Research also suggests that regulatory focus is strongly associated with asymmetrical activation in the frontal
cortex (FC). Specifically, prevention-focused individuals show chronically higher levels of activation in the right FC
relative to the left, and vice versa (Amodio et al. 2004). Asymmetric activation of the right FC is associated with a
preference for the familiar and secure, sensitivity to threatening imagery, behavioral inhibition, and avoidancerelated emotions. Asymmetric left FC activation, by contrast, is associated with lesser sensitivity to threatening
stimuli, behavioral activation, and approach-related emotions (see Harmon-Jones 2007 for a review).
Regulatory Fit and Persuasion, p.
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second condition participants were told they could avoid losing a dollar (loss frame) by not
missing more than 10 percent of the puzzles. The authors found that participants with a chronic
prevention focus performed better when exposed to the loss-focused monetary frame, whereas
those with a chronic promotion focus performed better when exposed to the gains-focused frame.
Cesario et al. (2004) extended RFT to persuasion by framing a message about an afterschool program either in terms of achieving gains (e.g. advancing children’s education) or
preventing losses (preventing more children from failing). They found that attitude change in the
direction of the message was enhanced when the frame of the message matched participants’
chronic regulatory focus. Work on persuasion in the political context similarly supports this
“functional matching” hypothesis (Lavine and Snyder 1996; Lavine et al. 1999). For example,
Lavine et al. (1999) found that citizens who are highly sensitive to threat (i.e. high authoritarians)
were more persuaded by a get out the vote message when it was framed in terms of potential
losses from non-voting than when it was framed in terms of the gains to be achieved by voting.
By contrast, citizens who are low in threat sensitivity (i.e., low authoritarians) responded more
favorably to a GOTV message when it was framed in terms of gains (than losses). In related
work, Kam and Simas (2010) found that dispositionally risk-averse individuals showed greater
loss aversion in a variety of prospect theory games. All of these results are consistent with Jost,
Federico and Napier’s (2009) hypothesis that linkages between stable psychological dispositions
and political preferences occur through a functional match between the motives and goals of the
former and the instrumental and symbolic content of the latter.
Regulatory Fit and Persuasion, p.
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The Present Studies
In the present research, we examine whether the effectiveness of persuasive
communications on policy proposals depends simultaneously on (1) whether the policy frame
highlights gains to be achieved or losses to be avoided; and (2) the chronic regulatory focus of
the individual with respect to promotion or prevention. In particular, we hypothesize that:
Those with a chronic prevention focus will be more persuaded by political
communications focusing on potential losses from failure to enact a policy than potential
gains from enacting a policy (H1).
Those with a chronic promotion focus will be more persuaded by political
communications focusing on potential gains from enacting a policy than potential losses
from failure to enact a policy (H2).
If these hypotheses receive support, individual differences in chronic regulatory focus may act to
constraint the capacity of elites to move public opinion in electoral contests. In particular, if such
dispositions cluster in political space, then elite actors have incentives to target their political
advertising strategies to the predominant psychological profile of a given media market. In this
paper, we examine the hypothesis that state-level differences in authoritarianism (Hetherington
and Weiler 2009; Lavine et al. 2002; Stenner 2005) act to create variation in the extent to which
political campaigns utilize positive- vs. negatively-toned advertisements – i.e., those that
highlight gains or losses – in House, Senate, Gubernatorial and Presidential elections. If, as
research amply shows (e.g., Lavine 2002), high authoritarians are more sensitive to threat than
their less authoritarian counterparts (and thus more likely to be chronically focused on losses
than gains), political campaigns should run more negatively-toned (i.e., prevention-focused)
advertising in high authoritarian states, and more positively-toned (i.e., promotion-focused)
advertising in less authoritarian states (H3).
Regulatory Fit and Persuasion, p.
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Persuasion Studies
Two experiments were conducted to test the hypothesis that the effectiveness of
persuasion depends on the conjunction of policy framing and individual differences in regulatory
focus. The main study consists of 907 respondents collected through Amazon.com’s Mechanical
Turk interface (see Appendix A for a description of the experimental procedure and descriptive
statistics). A small college-student replication was conducted with 89 undergraduates at Duke
University. The two studies are identical in design; we thus present them together. In both
studies, respondents were presented with policy statements on eight distinct issues. For each
issue, they were randomly assigned to receive one of three versions of a policy frame: control
(no frame), gains frame, or losses frame (each respondent thus participated in eight separate
experimental manipulations, and could be assigned to any of the three conditions for any issue).
The order of presentation of the issues was randomized across respondents. In a pre-treatment
survey, respondents completed demographic items, those pertaining to general political
knowledge, and a scale of six items measuring chronic regulatory focus.
Policy Treatments and Dependent Variable
Respondents were presented with eight policy statements representing a range of
ideological positions: government aid to help homeowners refinance underwater mortgages, tax
cuts for large businesses, increased spending on infrastructure, greater funding for charter
schools, required electronic verification of the citizenship of potential workers, greater spending
on public services, restrictions on foreign imports, and expiration of the Bush tax cuts for
wealthy individuals. For each issue, respondents were asked the following: “To what degree do
you support or oppose the following policy” (strongly, support somewhat, support a little, oppose
Regulatory Fit and Persuasion, p.
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a little, oppose somewhat, or oppose strongly)? As described above, respondents were randomly
assigned to receive one of three versions for each issue: a gain frame, a loss frame, or no frame.
The exact wording for all issues and conditions is shown in Table 1. As the table shows, the
frame manipulations are quite subtle, amounting to a change in a few words for each issue. The
dependent variable for all analyses reported below is policy support, which ranges from 1 to 6,
with higher values indicating greater support for the proposed policy.
Table 1. Policy Treatments
Issue
Control
Refinance
Federal aid to struggling
homeowners to refinance
their mortgages at the
current, lower rates
Tax Cuts
Additional tax cuts to large
businesses
Infrastructure
Increased investments in our
country’s infrastructure (e.g.
roads, bridges)
Charters
Increased funding for charter
schools (privately-owned, but
publically-funded high
schools that would compete
with current schools)
E-Verify
Requiring all businesses to
electronically verify the
legality of their workers’
citizenship status
Services
Imports
Bush Cuts
Increased investments in
public services such as
teachers, cops and
firefighters
Increased restrictions on
foreign imports
Allowing the Bush tax cuts to
expire for citizens making
more than $250,000 per year
Promotion
Prevention
Federal aid to struggling
homeowners to refinance their
mortgages at the current, lower
rates to help them achieve
financial stability
Additional tax cuts to large
businesses to promote the
hiring of additional workers
Increased investments to
improve the quality of our
country’s infrastructure (e.g.
roads, bridges)
Increased funding for charter
schools (privately-owned, but
publically-funded high schools
that would compete with
current schools) to incentivize
greater achievement in our
school systems
Requiring all businesses to
electronically verify the legality
of their workers’ citizenship
status to promote the hiring of
U.S. citizens
Federal aid to struggling
homeowners to refinance
their mortgages at the current,
lower rates to prevent them
from losing their homes
Additional tax cuts to large
businesses to prevent firing of
additional workers
Increased investments to
prevent the deterioration of
our country’s infrastructure
(e.g. roads, bridges)
Increased funding for charter
schools (privately-owned, but
publically-funded high
schools that would compete
with current schools) to
prevent further deterioration
of our school systems
Requiring all businesses to
electronically verify the
legality of their workers’
citizenship status to prevent
the hiring of non-U.S.
citizens
Increased investments in
public services to prevent
layoffs of teachers, cops and
firefighters
Increased restrictions on
foreign imports to protect
manufacturing from global
competition
Allowing the Bush tax cuts to
expire for citizens making
more than $250,000 per year
to prevent a larger budget
deficit
Increased investments in public
services to promote hiring of
teachers, cops and firefighters
Increased restrictions on
foreign imports to promote
domestic manufacturing in
global competition
Allowing the Bush tax cuts to
expire for citizens making more
than $250,000 per year to
achieve a smaller budget deficit
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Regulatory Focus
Respondents’ chronic regulatory focus (RF) was assessed with six items adapted from
Lockwood, Jordan and Kunda (2002). These items appear first in the survey; thus, a gap was
maintained in both time and thought between responses to the RF questions and the presentation
of the policy items. For each RF item, respondents were asked, “Now we will briefly describe
some people. Please indicate for each description whether that person is very much like you, like
you, somewhat like you, a little like you, not like you, or not at all like you.” The six items
included: “In general, I am focused on preventing negative events in my life,” “I am anxious that
I will fall short of my responsibilities and obligations,” “Overall, I am more oriented toward
preventing losses than I am toward achieving gains,” “In general, I am focused on achieving
positive outcomes in my life,” “Overall, I am more oriented toward achieving success than
preventing failure,” and “I frequently imagine how I will achieve my hopes and aspirations.”
Greater agreement with the first three items indicates a relative prevention focus, and greater
agreement with the last three items indicates a relative promotion focus. To remove variance
associated with idiosyncratic use of the common measurement instrument, we calculated
respondent-specific means across the items, and subtracted these from each of the six responses.
We used these mean-deviated responses to construct a composite RF scale (α = .65 for the
MTurk sample and .62 for the student sample). The scale was recoded to range from zero to one
prior to analysis with higher values indicating a greater prevention focus.
Analysis and Results
In each study, we regressed policy support on two dummy variables representing
membership in the two treatment conditions (with the unframed control group as the excluded
Regulatory Fit and Persuasion, p.
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category), RF, and the interaction of each treatment dummy with RF, using the OLS estimator.
To account for autocorrelation (inherent to within-subject designs), we clustered standard errors
by respondent.3 We expected to observe a negatively-signed interaction between RF and the
gains frame dummy (indicating a greater persuasive effect of gains frames for promotion- than
prevention-focused respondents), and a positively-signed interaction between RF and the loss
frame dummy (indicating a greater persuasive effect of loss frames for prevention- than
promotion-focused respondents).
The statistical results for both studies are shown in Appendix B. Graphical depictions are
shown in Figure 2a (MTurk Sample) and Figure 2b (undergraduate sample). The bars in each
figure represent the estimated level of policy support for each experimental condition, separately
for promotion- and prevention-focused respondents. The spikes represent 95% confidence
bounds on these estimates.
Results of MTurk Study. As Figure 2a shows, our hypotheses receive strong support in the
MTurk study. Among respondents with a promotion focus (i.e., those who scored at the 10th
percentile of the RF distribution), averaged policy support is highest in the frame highlighting
gains to be achieved from acting on the proposed policies (M=4.34, vs. 4.12 and 4.23 in the
control and loss conditions, respectively). By contrast, among respondents with a prevention
focus (i.e., those scoring at the 90th percentile of the RF distribution), averaged policy support is
highest in the frame highlighting losses to be avoided from enacting the proposed policies
(M=4.56, vs. 4.22 and 4.36 for the control and gain conditions, respectively).
The pattern of mean difference tests corresponds with expectations. For promotionfocused respondents, there was a significant effect for the gains treatment (vs. control; D=.21,
3
We replicated this analysis via restricted maximum likelihood, modeling the intercept as a function of individuallevel characteristics and a respondent-specific, normally distributed disturbance term. The results were largely
identical. The findings also remain identical with or without clustering the standard errors.
Regulatory Fit and Persuasion, p.
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SE=.10, p<.05), but not for the loss treatment (vs. control; D=.11, SE=.10, n.s.). Conversely, for
prevention-focused respondents, there was a significant effect for the loss treatment (vs. control;
D=.34, SE=.10, p<.05), but not the gain treatment (vs. control; D=.14, SE=.10, n.s.). In
substantive terms, framing a policy statement in terms of potential gains significantly heightened
persuasion (i.e., policy agreement) among promotion- but not prevention-focused respondents,
while framing a policy in terms of preventing potential losses significantly heightened persuasion
among prevention- but not promotion-focused respondents. This is exactly the pattern predicted
by theory.
Results of Replication Study. We turn now to the results from the undergraduate study,
which are shown in Figure 2b. As the figure shows, these results strongly replicate the main
study’s findings. Among promotion-focused respondents, policy support was highest in the gains
frame (M=4.41, vs. 3.90 and 4.11 in the control and loss conditions, respectively). By contrast,
among prevention-focused respondents, policy support was highest in the loss frame (M=4.39,
vs. 3.90 and 4.06 in the control and gain conditions, respectively). Once again, the pattern of
mean difference tests corresponds with expectations. For promotion-focused respondents, the
mean difference in policy support between the gains frame and the control condition is
statistically significant (D=.52, SE=.23, p<.05), while the difference between the loss frame and
the control condition is not (D=.21, SE=.24, n.s.). For prevention-focused respondents, the mean
difference in policy support between the loss frame and the control condition is statistically
significant (D=.47, SE=.23, p<.05), while the difference between the gain frame and the control
condition is not (D=.16, SE=.23, n.s.).
Regulatory Fit and Persuasion, p.
Figure 2A. Policy Support by Condition and Regulatory Focus
Prevention Focus (90%)
3.5
4
Policy Support
4.5
5
Promotion Focus (10%)
Promote
Control
Prevent
Promote
Control
Prevent
Notes: Data from undergrad sample. Bars are estimated levels of policy support. Spikes are 95% CIs.
Figure 2B. Policy Support by Condition and Regulatory Focus
Prevention Focus (90%)
3.5
4
Policy Support
4.5
5
Promotion Focus (10%)
Promote
Control
Prevent
Promote
Notes: Data from MTurk sample. Bars represent estimated policy support. Spikes are 95% CIs.
Control
Prevent
14
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Dispositional Clustering and Elite Behavior
The foregoing studies indicate that the effectiveness of a persuasive appeal depends on
the functional match between the chronic regulatory focus of the individual and the frame of a
message in terms of losses or gains. In this last empirical section, we extend our analysis to
examine whether these findings have any import for the political advertising strategies of elites
in Congressional, Gubernatorial, and Presidential elections. Specifically, if traits (e.g., RF,
authoritarianism) are both geographically clustered and perceived to moderate the effectiveness
of different types of ads (positive vs. negative tone), campaigns may choose to run a greater
proportion of negatively-toned ads in states where levels of a prevention (vs. a promotion) focus
(consciously or unconsciously understood) are perceived to be relatively high.
State-Level Authoritarianism
To obtain measures of state-level regulatory focus, we rely on four items used to measure
authoritarianism (Feldman and Stenner 1997; Hetherington and Weiler 2009; Stenner 2005).
These items are included in the 2000, 2004, and 2008 ANES studies, giving us enough data to
generate reasonably efficient estimates of the state-level parameters. Our method of estimation is
multilevel-regression and post-stratification (MRP; Gelman and Hill 2007; Lax and Phillips
2009; Park, Gelman and Bafumi 2006). MRP proceeds in two basic stages. First, individual-level
responses to the variable of interest (in this case, authoritarianism) are modeled as a function of
both individual and state-level predictors. The estimates from this model are then used to
generate predicted values of the dependent variable for every possible combination of predictors
(e.g., a white female between the ages of 18 and 29 with a high school degree residing in
Oklahoma). These predicted values can then be utilized to estimate state-level opinion by
Regulatory Fit and Persuasion, p.
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weighting the predicted value for each combination of predictors by the actual percentage of
people residing in a state with those characteristics, and then summing across these weighted
estimates (i.e. the post-stratification in MRP). This is the basic procedure we use to generate
state-level authoritarianism estimates.
First, we pooled the data from each of the ANES studies. Our individual-level predictors
included age (recoded into 4 categories, 18-29, 30-44, 45-64, and 65-up), the intersection of race
and gender (six categories corresponding to the intersection of male/female with black, Hispanic
and other), and education (four categories: high school degree or less, some college, college
degree, post-graduate degree). At the state level, we included the following predictors: per capita
income, proportion of the state’s vote that went to George W. Bush in 2004, a scale measuring
the multiculturalism of the state (XXXX), the % of the state’s population living in urban areas,
the state’ region, and the % of the state’s population with a high school diploma. The overall
model was estimated as follows (Y=Authoritarianism):
𝐴𝑔𝑒
𝑅𝑎𝑐𝑒,𝐺𝑒𝑛𝑑𝑒𝑟
𝐸𝑑𝑢𝑐
𝑆𝑡𝑎𝑡𝑒
𝑌𝑒𝑎𝑟
𝑦𝑖 = 𝛽 + 𝛼𝑗[𝑖] + 𝛼𝑘[𝑖]
+ 𝛼𝑙[𝑖]
+ 𝛼𝑚[𝑖]
+ 𝛼𝑛[𝑖]
,
𝐴𝑔𝑒
2
𝛼𝑗[𝑖] ~𝑁(0, 𝜎𝐴𝑔𝑒
), for j = 1 to 4,
𝑅𝑎𝑐𝑒,𝐺𝑒𝑛𝑑𝑒𝑟
2
𝛼𝑘[𝑖]
~𝑁(0, 𝜎𝑅𝑎𝑐𝑒,𝐺𝑒𝑛𝑑𝑒𝑟
), for k = 1 to 6,
𝐸𝑑𝑢𝑐
2
), for l = 1 to 4,
𝛼𝑙[𝑖]
~𝑁(0, 𝜎𝐸𝑑𝑢𝑐
𝑌𝑒𝑎𝑟
2
), for j = 1 to 3,
𝛼𝑛[𝑖]
~𝑁(0, 𝜎𝑌𝑒𝑎𝑟
𝑅𝑒𝑔𝑖𝑜𝑛
𝑆𝑡𝑎𝑡𝑒
𝛼𝑚[𝑖]
~𝑁 (𝛼𝑝[𝑚]
𝑅𝑒𝑔𝑖𝑜𝑛
2
+ ∑5𝑖=1 𝛾𝑖 ∗ 𝑥𝑖𝑚 , 𝜎𝑆𝑡𝑎𝑡𝑒
), where xi = State-Level Predictor ‘i’
2
𝛼𝑝[𝑚] ~𝑁(0, 𝜎𝑅𝑒𝑔𝑖𝑜𝑛
), for p = 1 to 5
Regulatory Fit and Persuasion, p.
17
To post-stratify, we utilize the 2000 Census’ 1% Public Use Micro-Data Sample, which gives
estimates of the proportion of each citizen “type” within each state. The final state-level
estimates of authoritarianism are calculated as:
4704
(1) ∑4704
𝑐=1 𝑁𝑐 ∗ 𝜃𝑐 / ∑𝑐=1 𝑁𝑐 , where Nc is the number of individuals in cell “c” within a given
state, and θc is the authoritarianism estimate for cell “c.”
State-level authoritarianism estimates are plotted in Figure X (the authoritarianism scale ranges
from zero to one).
.75
.8
Figure X. State-Level Authoritarianism Estimates
MS
LA
AR
.7
WV
KY SC AL
GA
.65
TN
.6
ND NM OH
.55
CT
MA CO
DC NH VT
HI
WI ID NV AZ
CA MN IA ME
MD NE NJ
KS
SD OK PA
MO RI IN
FL TX NC
NY IL DE
VA MI
WY MT
.5
AK UT OR
WA
As a “sanity-check” on these estimates, we examined the association between state-level
authoritarianism and a recent measure of state-level “racial animus” derived from analyses of
Google searches for racially charged words during the 2008 Presidential Election (StephensDavidowitz 2011). As Figure X indicates, there is a strong correspondence between the two
state-level variables, suggesting that our measure of aggregate authoritarianism is not without a
modicum of construct validity.
Regulatory Fit and Persuasion, p.
18
.75
.8
Figure X. Relationship between State-Level Authoritarianism and Prejudice
MS
R2 = .56
AR
AL
SC
.7
.65
GA
.6
NM
SD
.55
ID
HI
CO
.5
UT
MN
MT
WY
DC
DE
IL
VA
KSMD
NE
AZ ME
WI NV
IA CA
CT
NH
MA
OR AK
KY
WV
TN
NCFL
TX
IN MORI
OK
ND
LA
NY
NJ
OH
MI
PA
VT
.45
WA
20
40
60
State-Level Prejudice
80
100
Negativity of Campaign Advertising across States
To measure strategic elite behavior related to rhetorical strategy, we utilize data from the
Wisconsin Advertising Project at the University of Wisconsin (http://wiscadproject.wisc.edu/).
We were able to obtain data for 2000, 2002 and 2008.4 For each year, the project codes every ad
for House, Senate, Gubernatorial, and Presidential campaign with respect to “tone” (i.e., each ad
is coded as negative, positive, or “contrast”). To estimate the overall negativity of campaign ads
in each state (in each year), we divided the number of negative ads across all campaigns by the
total number of ads for that year. Our measure of state-level campaign negativity is thus the
proportion of all ads in a given state (within a given year) that were negative.5
4
The Wisconsin Advertising Project sent us a data disk for 2004, but it was unreadable. We have not yet received a
replacement.
5
Not all states have data for every year, and thus our analyses are restricted to those with available ads.
Regulatory Fit and Persuasion, p.
19
Analysis
To evaluate our hypothesis, we present scatter plots of advertising negativity against
state-level authoritarianism for each year. We include a loess curve for each plot, which gives a
locally-weighted picture of the relationship between the two variables. As the panels in Figure X
indicate, the results are mixed. In 2000, there appears to be a meaningful relationship between
state-level authoritarianism and the proportion of negative ads in each state. The loess line slopes
upward from about 15% negative ads to about 40% negative ads across the range of
authoritarianism. This visual association is reinforced by a significant and substantively strong
bivariate correlation (r=.42, p<.01). In 2002, the results are less clear, although there appears to
be some suggestion of a positive relationship (r=.23, p<.15). In 2008, however, we find no clear
evidence of any relationship between these variables (r=-.10, p>.45).
.4
.3
.2
.1
0
Proportion of Negative Ads
.5
Figure XX. Authoritarianism and Ad Negativity, 2000 Election
.5
.55
.6
.65
State-Level Authoritarianism
.7
.75
Regulatory Fit and Persuasion, p.
.4
.2
0
Proportion of Negative Ads
.6
Figure XX. Authoritarianism and Ad Negativity, 2002 Election
.5
.55
.6
.65
State-Level Authoritarianism
.7
.75
.7
.75
.6
.4
.2
0
Proportion of Negative Ads
.8
Figure XX. Authoritarianism and Ad Negativity, 2008 Election
.5
.55
.6
.65
State-Level Authoritarianism
Discussion and Conclusions
As psychologists have long noted, rationally equivalent descriptions of reality can be
framed in terms of either gains or losses (e.g., 10% unemployment vs. 90% employment;
Quattrone and Tversky 1982). Extensive work on prospect theory has shown that people are
generally more sensitive to losses than gains, and that social judgments are often responsive to
such framing effects (see Kahneman0 and Tversky 1979). Regulatory focus theory (RFT;
Higgins 1998, 1999) builds on prospect theory by proposing that stable individual differences
exist in the extent to which a person’s affect, cognition and behavior is motivated more by
20
Regulatory Fit and Persuasion, p.
21
achieving gains (a promotion focus) or avoiding losses (a prevention focus). In the present
research, we relied on RFT to examine two questions about mass and elite politics: (1) Are
individual differences in regulatory focus systematically related to the effectiveness of different
types of policy frames? (2) Does geographic clustering in regulatory focus orientation constrain
elite behavior in terms of campaign advertisement strategy?
In two experiments that relied on eight different issues, we found that functional matches
between individual dispositions and the framing of policy statements produce more persuasion
than functional mismatches. Specifically, promotion-focused individuals were persuaded by the
potential gains to be achieved from changes in public policy, whereas prevention-focused
individuals were not. Equally, prevention-focused individuals were persuaded by the potential
losses to be avoided by enacting a proposal, whereas promotion-focused were indifferent to such
communications. Moreover, we found some evidence that aggregated clusters of RF orientations
at the state level are linked to the degree of negativity in political advertising. In two of three
years of elections examined, “prevention-oriented” states received a greater proportion of
negative ads than “promotion-oriented” states.
We believe that regulatory focus can be understood as an umbrella concept in personality
with the potential to subsume a variety of dispositional factors that have been linked to political
orientation. As Jost et al. (2003) explain:
The promotion goals of accomplishment and advancement should naturally introduce a preference for
change over stability, insofar as advancement requires change. The prevention goals of safety and
security, on the other hand, should favor stability over change, to the extent that stability entails
predictability and hence psychological security and control…To the extent that political conservatism is
motivated, at least in part, by the desire for security and stability and the avoidance of threat and change,
situations inducing a prevention-oriented regulatory focus might also induce a conservative shift in the
general population.
What is appealing about regulatory focus is its emphasis on the abstract concepts of approach
and avoidance and pleasure and pain. Few principles in psychology are more basic than these
Regulatory Fit and Persuasion, p.
22
distinctions, and they are critical to understanding human behavior in a variety of domains,
including (as we have shown here), political persuasion. The fundamental nature of the
distinction between gain and loss has also pervaded other subfields of political science, including
the emphasis in political economy on risk aversion and political preference (e.g. Iversen 2005;
Moene and Wallerstein 2001). The RF framework thus may prove to provide an integration point
for two seemingly disparate literatures: the biological/psychological and the economic.
That RF orientations moderate the effectiveness of different types of persuasion strategies
has interesting implications for the strategies pursued by elites in policy and electoral contests. If
dispositions cluster in political space, whether concrete (e.g., geographical) or contrived (e.g.
opt-in networks such as TV and blogs), the opportunity for the microtargeting of political
messages exists, and the present results suggest advantages in aggregate persuasion to such
strategies. Future work should explore in greater depth the potential for elite micro-targeting on
the basis of personality.
Finally, our results speak to the literature on framing effects in political science. As
indicated by the epigraph to this paper, the framing literature has largely ignored individual-level
heterogeneity in the effectiveness of different types of frames. However, as citizens differ with
respect to the types of goals – promotion vs. prevention – that are both accessible and important
to them, frames focusing on gains vs. losses should be likely to attract differential levels of
cognitive scrutiny and positive evaluation (Avnet and Higgins 2006; Freitas and Higgins 2002;
Higgins 2005). A deeper understanding of the conditionalities of framing effects is therefore
critical, and while recent work has begun to address this question (Druckman 2001; 2004; Kam
and Simas 2010), much remains to be done. More generally, we hope that research on the joint
effects of individual differences in abstract goal priorities and message framing leads to a greater
Regulatory Fit and Persuasion, p.
understanding of the ways in which elites and citizens both constrain, and are constrained by,
one another.
23
Regulatory Fit and Persuasion, p.
24
APPENDIX A. DETAILS FOR MECHANICAL TURK EXPERIMENT
Mechanical Turk is a service that Amazon.com provides to those who are interested in
the performance of a large number of small tasks that require human judgment. Individuals
performing the tasks create a user profile on the site and are paid a fee for their services that
varies depending on the time, effort, and expertise involved in the task. Researchers post a
human intelligence task (HIT) to the Amazon site and offer payment rate per HIT. A link to our
survey was posted on this site, and advertised under the keywords “politics,” “survey,” “public
policy,” and “2012 election.” The description of the task read, “You will be asked to answer
several questions about yourself and watch and respond to a campaign ad.” Valid completions of
the survey were compensated $1.00. The effective hourly rate was estimated to be $7.26.
Summary statistics for the respondents are shown below.
Median Age
Male
Black
White
Mean Political Interest (1-5)
Mean Subjective Political Knowledge (1-5)
Mean Partisanship (1-7, higher=Rep)
Mean Ideology (1-7, higher=Con)
Mean Importance of Religion to Self (1-5)
Median Income
Mean Income
Median Education
Unemployed or Temporarily Laid Off
Student
Working Now
Central Tendencies and %s
28
60%
4%
81%
3.11
3.08
3.31
3.27
2.11
20K-30K
30K-40K
Some College
13%
24%
53%
Regulatory Fit and Persuasion, p.
APPENDIX B. OLS REGRESSION ESTIMATES (MTurk and Undergraduate Studies)
Variable
Promotion Condition
Prevention Condition
Promote X RF
Prevent X RF
Regulatory Focus
Constant
MTurk
.58 (.31)
.16 (.34)
-.53 (.64)
.41 (.64)
.02 (.41)
3.86 (.30)
Undergrad.
.22 (.13)
.07 (.14)
-.11 (.28)
.35 (.28)
.14 (.21)
3.88 (.11)
Subjects
Observations
R2
F(7,86) and F(7,686)
87
694
.01
2.48
907
7247
.01
8.03
25
Regulatory Fit and Persuasion, p.
26
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