the heterogeneity of southern white distinctivenesssmw2150/stevenwhite--heterogeneityapr.pdfthe...
TRANSCRIPT
The Heterogeneity of Southern White Distinctiveness
Steven White∗
Forthcoming at American Politics Research
∗Thanks to Robert Shapiro, Justin Phillips, Jeffrey Lax, Robert Erikson, and the anonymous reviewersfor helpful comments. Thanks also to the Columbia University Economics Department for providing accessto their computing cluster.
Abstract This paper documents and assesses subregional variation among white south-
erners in presidential voting behavior and a variety of issue attitudes. I demonstrate that
whites in the South remain consistently distinct from those in the rest of the nation, but
heterogeneously so: whites in the Deep South are generally far more conservative than their
Peripheral South neighbors. I also assess how the region’s disproportionate concentration of
born-again Christians can confound assessments of regional and state coefficients when prop-
erly accounted for in regression models. By demonstrating the continuing distinctiveness of
the white South, the significant variation present within the region, and the interrelationship
of region and religion, these results have theoretical and methodological implications for the
study of American politics.
In 2000 and 2004, the Democratic candidate for president received none of the South’s 153
Electoral College votes. Many liberals in turn advocated that the Democratic Party “whistle
past Dixie” and shift its focus to friendlier territory in the West (Schaller, 2006). Yet in 2008,
Barack Obama won Virginia, North Carolina, and Florida, suggesting Democrats might have
a chance in the region after all. However, this improved showing was not consistent across the
South. Many of the few areas where Obama performed worse than John Kerry among white
voters were in the Deep South. In some states, like Alabama, his share of the white vote
was barely half that of Kerry’s, with only about one in ten white voters casting their ballot
for Obama (New York Times, 2008). The broader context behind all this was the polarizing
presidency of George W. Bush, a former governor of the largest southern state and one of
the most famous born-again Christians in American political history.1 This confluence of
factors is directly related to debates about the role of regionalism in contemporary American
politics.
In this paper, I offer an empirical assessment of southern white conservatism in the
twenty-first century. In doing so, I test certain conventional theories of southern politics, as
well as introduce a few new ones. Scholars have long argued for the general distinctiveness
of the South (Key, 2006 [1949]; Black and Black, 1987, 2002; Kousser, 2010). Some have
further argued for distinguishing between the more peripheral parts of the region and the
deeper, more genuinely “southern” areas – but this line of reasoning has recently come
under attack (Ibid.; for the critique, see Shafer and Johnston, 2006). In this paper, I test
the validity of these distinctions in the twenty-first century using large-N datasets that
allow for more fine-grained analysis than prior research. I also offer one significant new
addition to the literature on the South: an initial assessment of the relationship between
the disproportionate concentration of white born-again Christians in the South and the
supposed distinctiveness of the region. In effect, this is an assessment of the distinction
between composition – differences due to the greater concentration of certain demographic
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groups or religious identities in a given area – and what might very roughly be called culture
– that difference which remains after compositional differences are accounted for.2
I argue that the white South remains distinct in the twenty-first century, but the Deep
South still especially so. As such, I push back against arguments that the South no longer
merits attention in its own right, as well as arguments that subregional variation has subsided
over time to the point where it can be ignored. I further argue, however, that regionalism and
religion are too often intricately bound up in the South that care must be taken to distinguish
between them. Properly accounting for this greater concentration lowers the estimate of the
southern effect on certain culture wars issues, especially policy-specific questions about gay
marriage and abortion. However, the southern effect remains generally robust elsewhere.
Overall, then, I argue for a social scientific understanding of southern white heterogeneity.
The South is a distinctive region that is itself internally varied in a complex, but ultimately
understandable, manner; it is also a uniquely Evangelical region that is shaped by this
concentration of a particular religious identification in some issue areas, but not in others.
By demonstrating the continuing significance of the South and the substantial variation
within the region – and integrating the study of born-again Christian religious identification
firmly into the study of southern white attitudes – these results have clear implications
for studies of regionalism in American politics, as well as the role of religion in individual
attitudes.
Background and Literature Review
A few explanatory notes are in order regarding the study of the South in general, the study of
southern whites in particular, and the focus on religion rather than other factors impacting
southern white attitudes and behavior.
First, why the South but not some other region? This paper looks at the South in
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comparison to a general non-southern category, which can lend itself to easy critique: Why
the South, but not the West, as the key area of interest? Why the generalized non-South
as the comparison group, rather than a series of comparisons to a range of other regional
categories? Why care about the difference between the Deep South and Peripheral South
without similar regard to differences between New England and the Middle Atlantic? I offer
three reasons: (1) despite the long history of attention to the unique role of the South in
American politics, there has been increasing debate about whether this is still merited –
and I argue that it is; (2) Peripheral South states like Virginia and Florida were among the
top “tipping point” states in the 2012 election, according to websites like FiveThirtyEight
– suggesting an increased importance of at least parts of the region to the Electoral College
strategies of presidential campaigns; and (3) one article can necessarily only focus on so much,
and I choose the South for the prior reasons. This justification is necessarily imperfect, but
I argue the choice is merited.
Second, why white southerners rather than the South as a whole? I argue the focus
on whites is justified for a number of reasons. Rather than explaining variation in all of
the South, I am particularly interested in white conservatism. This grounds the analysis in
a subject that can be explored in an article-length manner. Doing analytic justice to the
varied types of distinctiveness of both white and black southern attitudes would require a
lengthier manuscript. However, there are also more substantive reasons. Southern whites are
an increasingly core part of the Republican Party, and as a diversifying electorate provides
electoral benefits for Democrats, the political attitudes of southern whites will be the subject
of renewed debate and interest. As such, a careful, empirical assessment of where southern
white distinctiveness stands in the twenty-first century is warranted.
Finally, why a focus on religion rather than other factors affecting southern distinctive-
ness? In particular, there is a strong literature on the relationship between white attitudes
and racial context. Key’s (2006 [1949]) racial threat hypothesis has been analyzed in great
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depth, and recent scholarship has affirmed the centrality of race in southern political devel-
opment. Valentino and Sears, for example, demonstrate the existence of a strong relationship
between white racial conservatism and partisan identification in the region (2005). Focusing
on the white southern shift to the Republican Party, Hood et al. (2012) point to increases in
black voter mobilization – rather than population size, per se – as the key factor in pushing
southern whites towards the GOP. They caution that scholars ignoring racial dynamics “do
so at their own risk” (Ibid., 13).
I want to be clear that I agree with this scholarship on the importance of race in southern
politics. I focus on religion instead for a couple of reasons. The recent scholarship just noted
has done an exemplary job of demonstrating the significance of race in shaping white southern
attitudes. I want to make a complementary, rather than critical, point about the role of
religion. I argue scholars of religion and politics have not properly assessed the degree to
which the South’s disproportionate concentration of white Evangelicals impacts assessments
of regional distinctiveness.3 By bringing a new dataset to bear on the relationship between
white southern distinctiveness and religion, my goal is to rigorously assess precisely this
relationship, as well as offer an assessment of the degree to which the Deep/Peripheral
divide remains important.
The South has long been a distinctive region in American politics. Key described in
great detail a one-party “solid South” defined to a large degree by racial politics, especially
the maintenance of Jim Crow (2006 [1949]). Since then a two-party South has emerged –
see Lamis (1988) for a book-length treatment – with the white South increasingly going
Republican. Black and Black distinguish between two “great white switches,” the first – in
presidential voting habits of southern whites – accompanying Barry Goldwater’s Deep South
victories in 1964, with the second – in partisan identification of southern whites – coming in
the middle of Ronald Reagan’s presidency (2002, p. 4). The Democratic Party’s southern
constituency has changed dramatically. “A party originally created by racist southern white
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men to enhance and maintain their perceived interests has now become the political home
of African Americans, liberal and moderate whites, and Hispanics,” as Merle Black puts
it (2004, p. 1001). Fitting with Abramowitz and Saunders’s (1998) description of the
increasing fit between ideology and partisanship in the electorate, white conservatives in the
South became Republicans. Naturally enough, by 2000 the number of southern whites in the
American National Election Studies (ANES) survey who considered themselves Republicans
finally edged past the fifty percent mark, while only one in three considered themselves
Democrats (Knuckey, 2006, p. 57).
Contemporary political scientists are split on whether the South remains meaningfully
different from the rest of the United States, and if so how it does. First, given the significant
amount of political change in the postwar South, the degree to which the South as a whole
remains distinct is debated. Bartels (2000) suggests there no longer exists regional variation
in the relationship between partisanship and presidential vote choice. However, Hillygus and
Shields find that, despite recent arguments that the South is losing its historical distinctive-
ness, in the 2000 election, “the voting calculus of Southern voters differs from the rest of the
electorate” (2008, p. 507). They argue that not only are southerners more conservative, but
this conservatism plays a larger role in individual-level decision-making (Ibid., p. 516-518).
Similarly, scholars of southern politics continue to make a compelling case that southern
attitudes still differ in a way that matters for studies of American politics more generally
(Cotter, Shaffer, and Breaux, 2006; Breaux and Shaffer, 2012).
Hillygus and Shields – like much of the literature in American politics – treat the South
as one homogeneous region, a second issue I address. This decision is generally made with-
out explicit theoretical rationale. A notable exception is Shafer and Johnston (2006), who
directly attack the idea of dividing the South into subregions. They argue the Peripheral
South’s growth has led to it becoming “the South” more generally, while the Deep South’s
demographic decline has left it “a residual” (Ibid., p. 133). In his review of the southern
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politics subfield, however, Kousser rejects this critique in strong terms, declaring it “unwar-
ranted” (2010, p. 377). A second goal of this paper is to assess precisely the utility of such
subregional distinction in contemporary attitudes and behavior.
I also examine the role of religious identification in shaping these regional distinctions.
While much of the academic literature on religion and American politics falls into the “cul-
ture war” debate (Hunter, 1991; McConkey, 2001; Fiorina et al., 2006) – which in political
science has tended to relate to debates about partisan polarization and red states versus
blue states (Abramowitz and Saunders, 2008; Fiorina et al., 2008) – recent work in sociology
provides a more in-depth look at the effects of specific religious beliefs. Lewis and Huyser
de Bernardo (2010), for instance, study Evangelicals and argue denominational tradition is
a better predictor of political attitudes while self-identification as an Evangelical is a better
predictor of partisanship. Froese et al. (2008) use General Social Survey (GSS) data to
argue that belief in a punitive God leads to a tension between religious faith and support
for civil liberties. Such beliefs relate to the literature on authoritarianism (e.g., Altemeyer,
1996), which political scientists have recently started to analyze as part of the debate about
polarization in American public opinion (Hetherington and Weiler, 2009).
Political scientists have also started to more seriously consider the role of religious identi-
fication. Barker et al. (2008) argue that as belief in biblical authority increases, so too does
the salience of foreign policy issues relative to domestic ones. Other work has challenged con-
ventional media narratives about the political ramifications of the Christian Right. Claassen
and Povtak (2010), for example, use ANES data to demonstrate that increased voter turnout
of Evangelicals in 2004 was not a function of campaign dynamics – the conventional story
suggests the Bush reelection team was especially adept at turning out these voters – but
rather was simply the latest in a long-term trend driven by demographic change among
Evangelicals.
Born-again Christians believe that eternal salvation requires a “born-again” conversion
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experience. Until the mid-1970s, most Americans who did not themselves identify as born-
again had never heard of the term. Jimmy Carter’s 1976 campaign for president brought the
term to mainstream discourse for the first time. During the campaign, Carter, a Baptist,
casually mentioned to New York Times chief religion reporter Kenneth Briggs that he was
a born-again Christian. Many in the mainstream news media were unfamiliar with the
term; indeed, “[n]o one was sure that a presidential candidate should be talking about such
things as private ‘born-again’ experiences and conversions.” Yet the term “could hardly have
been more familiar or less controversial to evangelical Christians” (Martin, 1996, p. 149).
While the Democratic Carter can be credited with bringing white Evangelicals into the
political mainstream, the group trended strongly Republican starting with Ronald Reagan.
Evangelicalism and southern politics have become increasingly intertwined since then. The
Southern Baptist Convention (SBC) came to play an increasingly strong role in southern
politics, starting particularly in 1979 when theologically and politically conservative forces
began to take control of the institution. This coincided with increasing influence of the SBC
in the southern Republican Party (Smith 1997).4
Such religious identification is not randomly distributed across the country. Figure 1
plots the percentage of whites in each state that identified as born-again in 2004. While 40
percent of white Americans overall call themselves born-again Christians, this mean value
obscures the vast range. Connecticut and Mississippi represent the two extremes, with
only 12 percent of Connecticut whites identifying as born-again Christians, compared to 78
percent in Mississippi. The graph also demonstrates clear regional clustering. Five of the
ten least born-again states are in New England and four others are in northern states like
New York and New Jersey (heavily Mormon Utah is fifth). By contrast, seven of the ten
most born-again states are in the South, with the other three being the southern border
states of Oklahoma, Kentucky, and West Virginia. The top three spots are clustered in
the Deep South in particular – Mississippi, South Carolina, and Alabama – with the more
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conservative Peripheral South states – Arkansas and Tennessee – coming in fourth and fifth.
In general, then, it is unlikely that a randomly selected white person in New England is
a born-again Christian, while it is unlikely a randomly selected white person in the Deep
South is not a born-again Christian. Attention to the disproportionate concentration of born-
again Christians in the southern states links the work of political scientists with sociologists of
religion, a combination that might prove useful to the theoretical concerns of both disciplines.
Hypotheses
The last section hinted at potential inquiries, but here I state them as testable hypotheses:
H1. White southerners are more conservative than their non-southern counterparts.
Southern political history provides ample reasons to suspect the region might still be quite
unique in American politics (Key, 2006 [1949]; Black and Black, 1987, 2002; Hillygus and
Shields, 2008; Kousser, 2010), yet some have suggested economic development, migration
from outside the region, and other factors have led to a decline of southern distinctiveness
(Shafer and Johnston, 2006). Hypothesis 1 assesses the relevance of the region considered
as a whole.
H2. Whites in the Deep South are more conservative than their Peripheral South counter-
parts.
The Deep South is poorer, more racially heterogeneous, and less economically developed
than the Peripheral South. There is reason to believe subregional variation might exist, but
scholars disagree over whether it remains meaningful (Kousser, 2010) or not (Shafer and
Johnston, 2006). Hypothesis 2 addresses this disagreement.
H3. Whites in the individual Deep South states are more conservative than those in the
individual Peripheral South states when examined one-by-one.
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The division between Deep and Peripheral South states is standard in the study of the region,
yet it is generally asserted as inductively plausible (Key, 2006 [1949], p. 669; Black and Black,
1987, p. 14) rather than properly tested. Hypothesis 3 looks at the actual empirical patterns
to assess whether the individual Deep South states are generally more conservative than the
individual Peripheral South states. State-level analysis of this sort is relatively uncommon,
but can be useful to scholars interested in the constitutive parts of regions (for a relatively
recent example of state-level analysis, see Brace et al., 2002).
H4. The effect of identifying as a born-again Christian is homogeneous nationally.
If the effect is homogeneous, then exploring its influence on southern distinctiveness is a
straightforward affair. If, however, it varies by state, then exploring the confluence of region
and religion requires a more interactive approach.
H5. Disproportionate concentration of born-again Christians in the southern states con-
founds assessments of regional distinctiveness when properly controlled for, lowering
estimates of the regional effect.
Identification as a born-again Christian is not widely used as a standard demographic control.
Hypothesis 5 assesses the implications of this methodological neglect.
Definitions, Data, and Methods
Before testing these hypotheses, I first address a few relevant methodological issues.
Definitions
The first question in the study of the South in American politics is how to define the region.
I define the South as the following eleven states: Alabama, Arkansas, Florida, Georgia,
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Louisiana, Mississippi, North Carolina, South Carolina, Tennessee, Texas, and Virginia.
This is the classic definition used by Key (2006 [1949]: 11) and the one most widely used
in southern politics scholarship today (e.g., Hillygus and Shields 2008; Mickey 2008; Hood
et al. 2012). I use it for both historical and practical reasons. Historically, these are the
eleven states of the former Confederacy, making them a logical grouping. Practically, using
the standard definition of the region allows this paper to more easily build on the work of
previous scholars, particularly those who have divided these eleven states into their Deep
South and Peripheral South subregions.5
To explore subregional variation, I distinguish between the Deep South (Alabama, Geor-
gia, Louisiana, Mississippi, and South Carolina) and the Peripheral South (Arkansas, Florida,
North Carolina, Tennessee, Texas, and Virginia). This is the traditional breakdown in the
southern politics literature (Key, 2006 [1949], p. 669; Black and Black, 1987, p. 14). Beyond
its intellectual lineage, the breakdown represents significant historical differences. The Deep
South states have much larger black populations than the relatively whiter Peripheral South,
although both regions are well above the national average. Key noted the Peripheral South
states were far more accepting of the 1944 Smith v. Allwright case outlawing the white
primary (2006 [1949], p. 669). The five Deep South states were Barry Goldwater’s only
victories in his 1964 presidential campaign other than his home state of Arizona. In general,
the Peripheral South states have long been more influenced by the rest of the nation than
the Deep South.
I define born-again Christian status as solely a matter of self-identification. If a respon-
dent answers yes to the question, “Do you consider yourself an evangelical or born-again
Christian?,” then I assume they are. This is similar to the conception of partisanship de-
scribed by Green et al. (2002) in that it is grounded in emotional attachment (indeed,
they even compare their definition of partisanship to religion [Ibid., p. 6]). Similarly, Lewis
and Huyser de Bernardo argue that “being an evangelical may be a foundational social-
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psychological identity that, similar to party identity, influences them beyond their denomi-
national affiliation” (2010, p. 124). This identity is at least as strong – and perhaps stronger
– than partisan identification.
Data
I use the 2004 and 2008 National Annenberg Election Survey (NAES) data.6 The 2004 study
consists of a national rolling cross-section of 81,422 interviews conducted between October
2003 and November 2004; the 2008 study consists of 57,967 interviews conducted between
December 2007 and November 2008. The sampling procedure is random digit dialing. In
combination, these two aspects of the data – RDD and large sample size – mean the data
is generally representative at the state level, unlike, for example, the ANES cluster sample.
Since my interest is in state-level variation, this is a significant strength. Although the 2008
data is more timely, I also utilize the 2004 data for two reasons: first, certain questions of
substantive interests were not asked in 2008; and second, a much smaller percentage of the
2008 sample was asked the born-again Christian identification question, making analysis of
Hypotheses 4-5 more difficult at smaller subnational levels.
I analyze the following dependent variables of interest to scholars of public opinion and
political behavior: in 2004, vote choice (1=Bush, 0=Kerry), group affect measures of Mus-
lims, gay organizations, and feminist organizations (0-10 scale, where 0=very favorable and
10=very unfavorable), support for an anti-gay marriage constitutional amendment (1=sup-
port, 0=oppose or neutral), support for an abortion ban (1=support, 0=oppose or neutral),
whether Iraq was worth it (1=yes, 0=no), and support for “more free trade agreements like
NAFTA” (1=favor, 0=oppose or neutral); in 2008, vote choice (1=McCain, 0=Obama),
preferences for abortion availability (1=no restrictions, 2=available but with more limits,
3=not available except for rape, incest, or health reasons, 4=never available), support for
gay marriage or civil unions (1=full marriage rights, 2=civil unions or domestic partnerships,
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3=no legal recognition), whether Iraq was worth it (1=yes, 0=no), and support for “more
free trade agreements like NAFTA” (1=favor, 0=oppose or neutral). Variables are coded so
that conservative responses are higher.7
Dependent variables were selected with certain criteria in mind. I include vote choice
because voter behavior is itself a special concern for political scientists. I look at issues of
interest to social conservatives, as these might be especially salient in the region. I also give
preference to questions asked in both years. I finally try to utilize questions that were asked
to as many respondents as possible. Many questions of interest were only asked for a limited
time period, which does not leave a sufficiently large N for state-level analysis. While I would
prefer to analyze a more general economic question, for example, the free trade question was
asked for a much longer period than similar questions about the minimum wage or labor
organizing (which do not come with a sufficient N for state-level analysis).
Methods
My main explanatory variables of interest for Hypothesis 1-3 are region- and state-level
dummy variables. I estimate three models for each dependent variable with these terms
specified in slightly different ways to provide assessments of my hypotheses: a single South
dummy variable (model 1); Deep South and Peripheral South dummy variables (model 2);
and dummy variables for each of the 11 southern states (model 3). For models 1-3, the
base category is the non-South. To better isolate regional and state effects, I control for
partisanship (dummy variables for Republicans and Democrats, where independents are the
base category), ideology (a 5-point scale from very liberal to very conservative), age, gender
(dummy variable for female), household income, and education (dummy variables for high
school or less and college degree, where some college is the base category). I limit my analysis
to whites because of my theoretical objectives. Doing so narrows the scope of the paper – I
am analyzing white Americans, not Americans as a whole – but this allows me to hold race
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constant to better isolate the independent effects of region and religion.
A significant southern dummy variable in model 1 supports Hypothesis 1. A comparison
of models 1 and 2 tests Hypothesis 2 that the Deep South is significantly different than the
Peripheral South. This subregional distinctiveness hypothesis is supported when the Deep
South term is larger than the Peripheral South and general South terms. I also conduct a
test of the difference between the Deep and Peripheral South terms. If they are significantly
different, this provides statistical confirmation of subregional distinctiveness. I also use
Akaike’s Information Criterion (AIC) to assess model fit. The AIC formula penalizes the
inclusion of additional parameters, so if the inclusion of two regional terms instead of one
nonetheless produces a lower value, the subregional model can be considered a better fit.
A comparison of models 2 and 3 assesses Hypothesis 3, whether the Deep vs. Peripheral
division arbitrarily obscures the actual state-level variation, by looking at effects for each
individual state.
I treat the group affect measures as continuous variables and estimate these models
using OLS regression (this analysis is also replicated using ordered probit models, which
are presented in Table 8 of the online appendix). Binary dependent variables are estimated
using logistic regression. For the gay marriage and abortion questions in 2008, I allow for the
qualitative nature of the ordered categories by using ordered probit models. Tables 1-4 report
the results of the regional and subregional models. The state-level models are presented in
the online appendix (Tables 5-7). To provide more substantive meanings when discussing
the results, I also calculate marginal effects for the logit models. Each marginal effect is
the change in probability associated with that variable when all other explanatory variables
are held constant.8 The variables of theoretical interest are dummy variables: the marginal
effect is the discrete change from zero to one, making substantive interpretation rather
straightforward. I calculate changes in probabilities for shifts to theoretically interesting
categories for the ordered probit models.
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To assess Hypothesis 4, whether the effect of being a born-again Christian varies by state
or is homogeneous nationally, I estimate multilevel models where the dependent variables
used in the previous section (2004 data only because of sample size issues) are modeled as
a function of born-again status and the intercepts and slopes are allowed to vary by state.
The same controls are used as before. Multilevel models can be understood as “extensions
of regression in which data are structured in groups and coefficients can vary by group”
(Gelman and Hill, 2007, p. 237). The group here is state, which allows for estimates in
which the effect of born-again identification is allowed to have differential effects in each of
the states. The 95 percent confidence intervals are generated by simulating the model 1,000
times and cutting off 2.5 percent at each end of the distribution (Ibid., p. 142).
For Hypothesis 5, I compare results from the 2004 models estimated with and without
a born-again Christian control variable. Hypothesis 5 is supported if the regional coeffi-
cients are substantively different when the born-again Christian term is included – in other
words, if part of regional distinctiveness is simply driven by the region’s greater share of a
particular demographic characteristic: born-again Christian self-identification. However, if
controlling for this does not meaningfully change the regional terms, then claims of regional
distinctiveness are robust even controlling for differential levels of religious identification.
Results
I present the results in the order of the stated hypotheses.
H1: Do South/non-South differences still exist?
Assessment: Yes.
The standard southern dummy variable is significant in every single area, except for two: the
feminist organizations group affect measure in 2004 and the free trade deals question in 2008.
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Overall, Hypothesis 1 receives very substantial support: southern whites are very much still
different than their counterparts elsewhere in the nation (Tables 1-4). I discuss the precise
estimates in the next subsection, as they are more theoretically useful in comparison to the
coefficients obtained for Deep and Peripheral South variables.
H2: Is the Deep South different than the Peripheral South?
Assessment: Yes.
In 2008, white southerners were 14 percent more likely to vote for McCain over Obama
overall, but there is substantial variation. Those in the Deep South were 25 percent more
likely to support McCain, compared to only 9 percent for Peripheral South residents, a
marginal effect almost three times the size. In 2004, white southerners were 10 percent more
likely to support Bush over Kerry, but when the South is divided into its Deep and Peripheral
subregions the coefficients again diverge. Being from the Deep South is associated with a
16 percent increase in the probability of voting for Bush, while being from the Peripheral
South is associated with an 8 percent increase. Both terms are statistically significant and
substantively meaningful, but the Deep South term is double the size of the Peripheral South
term, and is 6 percentage points higher than the effect estimated in a single-South model.
These results clearly affirm the analytical value of distinguishing between the Deep and
Peripheral South in studies of presidential voting behavior.9
For social issues, this trend continues for issues related to gay rights and assessments of
Muslims, but interestingly a bit less so for feminist issues. For the gay marriage question
in 2008, southerners overall were 10 percent more likely to move from category 2 to 3 (from
support for civil unions, a “moderate” stance, to no support for any legal recognition of gay
and lesbian relationships). In the Deep South, the number is 15 percent, compared to 8
percent in the Peripheral South. For the abortion question, the South is statistically but not
especially substantively more conservative. Stronger resistance to abortion access emerges
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in the Deep South, but the difference is not huge. Turning to 2004, southerners overall were
4 percent more likely to support a constitutional amendment banning gay marriage, while
the probabilities are 7 percent in the Deep South and 3 percent in the Peripheral South –
just over twice the size. For the abortion ban question that year, being from the South is
associated with just a one percent increase in the probability of supporting a ban, while
in model 2 being from the Deep South is associated with a 5 percent increase, whereas
the Peripheral South effect is not statistically significant. The 2004 survey also includes
group affect questions. Significant subregional variation exists in assessments of Muslims.
The South coefficient is significant in model 1, but in model 2 the Deep South coefficient
is notably larger. Whites in the Deep South are more negatively disposed toward Muslims
than whites in the Peripheral South. A similar pattern emerges for assessments of gay
organizations. The South coefficient in model 1 is significant, but the Deep South term in
model 2 is larger.10 However, the patterns abruptly stop for assessments of feminist groups.
None of the regional terms are significant in either model specification.
Because research on regional variation in foreign policy attitudes is “limited and some-
what dated” (Cotter, Shaffer, and Breaux, 2006, p. 189; see Hero [1965] for an older analysis),
I next consider attitudes toward the Iraq war. There is a literature suggesting southerners
possess a “culture of honor” (Nisbett and Cohen, 1996), which might lead to more militaris-
tic foreign policy preferences. Wyatt-Brown examines this in crises ranging from the Civil
War to the war in Iraq, arguing that the war in Iraq was actually justified by a southern
president using religious themes, rather than themes related to national honor (2005, p.
447). Attention to survey evidence of white southern foreign policy attitudes can elucidate
such scholarship from a different vantage point.
White southerners were 7 percent more likely to say Iraq was worth it in 2008, but the
Deep South marginal effect is 11 percent compared to 6 percent in the Peripheral South. In
2004, the marginal effect of being from the South is a 6 percent increase in the probability
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of thinking the war was worth it, but the marginal effect of being from the Deep South is a
10 percent increase in probability, while the marginal effect in the Peripheral South is only
4 percent. The regional trends seem to be robust over time for the Iraq question, not just a
function of the electoral climate.11
I finally look at attitudes toward free trade, an economic issue supported by conservatives
generally but often opposed by those with lower levels of education, something that could
plausibly create an ideological tension among southerners. The South also has a complex
history with trade policy. In Key’s time period, the South was “the area with the most
intense attachment to free trade,” at least among congressmen (2006 [1949], p. 353). There
is no regional or subregional southern distinctiveness for the free trade question in 2008.
The 2004 results are not much stronger. In model 1, being from the South is associated
with a statistically significant but substantively small 1 percent decrease in the probability
of supporting more free trade deals. In model 2, the results suggest this is driven by the
Deep South: its marginal effect is a 2 percent decrease, while the Peripheral South term is
not statistically significant. However, the AIC value is actually higher in model 2 and a test
of the difference between the subregional terms is not statistically significant. Hypotheses
1 and 2 are not supported when the dependent variable is preferences for more free trade
deals.
H3: Do state-by-state patterns match subregional division?
Assessment: Yes, with a few interesting exceptions.
The state dummy variables largely act according to the Deep/Peripheral division, providing
general support for Hypothesis 3 overall. Space concerns prevent going through each model
in detail, but I discuss a few interesting results (see Tables 5-7 in online appendix).
The largest state effects for 2008 presidential vote choice are in the Deep South, with the
estimate for Louisiana at an especially large 37 percent. The smallest marginal effects are
17
for North Carolina, at 10 percent, and Florida and Virginia, where there is not a statistically
significant difference from the rest of the nation. This provides face validity, as these were
the three southern states Barack Obama won in 2008, and North Carolina was the closest.
The state-level effects for the abortion questions are complex. For the question in 2008,
the strongest opposition is present in Mississippi and Louisiana. Being from Florida, inter-
estingly, is associated with a more liberal attitude. The state-level variation for the abortion
question in 2004 is especially revealing. There is a positive increase in probability of sup-
porting a ban in Alabama, Arkansas, Louisiana, Mississippi, and Tennessee; a decrease in
probability in Florida and Virginia; and no effect for Georgia, North Carolina, South Car-
olina, and Texas. For the abortion variable, then, the Deep/Peripheral breakdown does not
quite capture the nuances. The Peripheral South coefficient is effectively pulled down by
negative effects in Florida and Virginia and the lack of any significant effect in Texas, its
largest state. By contrast, whites in Tennessee and Arkansas are closer to their Deep South
neighbors. For the feminist organizations group affect measure, only the state of Mississippi
stands out in the analysis as being uniquely anti-feminist.
None of the Peripheral South states are statistically significant in themselves in the
models analyzing the 2004 Iraq question, with one exception. It is that the sizable effect
in Texas alone makes the Peripheral South term significant in model 2. None of the other
Peripheral South states are themselves individually distinguishable from the non-southern
base category, meaning in 2004 there wasn’t so much a Peripheral South effect as a Texas
one. North Carolina joins Texas in the 2008 dataset, but overall the biggest effects are
throughout the Deep South and Texas. The association of the Iraq war with Bush, the
former Texas governor, probably plays some role in this.
There is some interesting complexity in the free trade question that further nuances the
results from the first two models. Rather than grouping together regionally, the estimated
state coefficients vary widely in statistical significance and in sign. In the 2004 data, espe-
18
cially clear patterns emerge: In Alabama, Mississippi, North Carolina, and Tennessee, whites
are less likely to support free trade deals than whites in the non-South. However, in Florida,
Georgia, and Texas, whites are slightly more likely to support more free trade deals than
non-southerners. Finally, the effect in Arkansas, Louisiana, South Carolina, and Virginia is
not statistically significant. There is, in other words, not a consistently conservative direc-
tion in the effect of being from a southern state on free trade attitudes, but rather a mix
of no effect, a conservative effect, and what might be labeled a populist effect. In the 2008
data, North Carolina, Mississippi, and Tennessee remain in the more populist, anti-free trade
camp, but point estimates for the other southern states are not statistically significant.12
H4: Is born-again Christian identification consistent nationally?
Assessment: Yes, with minor exceptions.
Overall, Hypothesis 4 is very strongly supported. For 5 of the 8 dependent variables in
2004 – vote choice, the gay organizations group affect measure, gay marriage, Iraq, and
free trade – there is a homogeneous effect that is constant across the states.13 There is
typically a significant effect of being a born-again Christian, but the confidence intervals
overlap. White born-again Christians are more likely to vote for the Republican presidential
nominee, support the war in Iraq, and oppose gay rights – and less likely to support free
trade deals – but not in a way that varies with region.14
The three remaining dependent variables present a small amount of variation. Graphs
of the effect on these variables are presented in Figures 4-6 of the online appendix, with
the point estimates for the 11 southern states presented first, followed by the rest of the
states in alphabetical order. The plotted coefficients represent the impact of born-again
identification in each state, while the horizontal lines are 95% confidence intervals. There is
a heterogeneous effect of born-again Christianity that is stronger in the South in the Muslims
group affect model. Born-again Christian self-identification has a bigger impact on whites in
19
states like Alabama, Mississippi, South Carolina, and Tennessee than it does in California,
New York, Vermont, and Wisconsin, although in most states “in the middle” the effect is
statistically indistinguishable. There is also some state-level variation for the feminist groups
and abortion ban models, but with no coherent regional or ideological pattern. In the feminist
groups model, born-again Christian identification has a stronger effect in West Virginia than
Vermont, but the effect is also bigger than Vermont in New York and New Jersey. What
could possibly distinguish these three disparate states from Vermont is unclear. However, it
is again the case that the effect in most of the states is statistically similar. The effect in
the abortion ban model is actually mostly homogeneous, but the point estimate in Arizona
is statistically distinguishable from smaller point estimates in Arkansas and Louisiana. Yet
this is an exception from the general lack of differentiation.
Overall, with a small number of exceptions, Hypothesis 4 is supported. The effect of born-
again Christian identification on white attitudes is largely consistent regardless of region.
H5: Does the concentration of born-again Christians in the South
confound the regional effect?
Assessment: For social issues, yes. However, the impact is not substantial across
other issue areas.
The strongest support for Hypothesis 5 is generally in social issues – especially on the policy
questions related to abortion and gay marriage – and changes are most noticeable at the state
level. There is also some effect in the vote choice model, again especially at the state level.
Other issue areas are generally more robust, suggesting the disproportionate concentration
of born-again Christians in the South is not substantially altering the southern effect in those
issues overall.
I use graphs to compare the point estimates in each of the model specifications (Kastellec
20
and Leoni 2007). Figures 2-3 plot the changes in the OLS and logit estimates of the regional
(models 1 and 2) and state (model 3) coefficients with the addition of the born-again control
variable. The vertical lines represent 95% confidence intervals, allowing for some assessment
of whether the differences are statistically meaningful. The black dots are the coefficients
from the previous section; the white dots are the new coefficients. With the born-again
Christian term included, the statistical patterns in the South and Deep/Peripheral models
remain consistent for 4 of the 8 dependent variables. For vote choice, Iraq, and the Muslims
and gay organizations group affect measures, the Deep South still has the largest coefficient,
the AIC is still lower in model 2, and a test of the difference between the subregional terms
remains statistically significant. For feminist organizations, none of these hold – the same as
in the previous section. Yet there are significant changes of the substantive interpretations
at many points. Interesting regional changes are present in the free trade models (the
Deep South term loses its slight statistical significance), the gay marriage models (a test of
the difference between the Deep and Peripheral South is no longer statistically significant),
and the abortion ban models (now the Peripheral South term is larger and statistically
significant, while the Deep South term is not statistically significant, making it an outlier
from the general pattern).
The most interesting changes occur at the state level. Whites in the ten southern states
other than Florida were previously estimated to be more likely to vote for Bush or approve of
his job performance than whites outside the region, but when a born-again Christian variable
is included in the model, the effects in Arkansas, North Carolina, Tennessee, and Virginia
become statistically insignificant as well. The Peripheral South term remains significant
because Texas remains significant. There appears to be, then, a serious confounding influence
of state effects versus religion effects in many of the Peripheral South states, something missed
in the subregional model. This is significant for two reasons. First, it shows the potential
of the subregional terms to obscure the precise pattern of state-level variation. Second, it
21
shows the incredible potential of a single additional control variable – born-again Christian
self-identification – to substantially alter the results.
In the Iraq models, the coefficient on Louisiana loses its statistical significance, leaving
only Alabama, Georgia, South Carolina, and Texas in the significant column. While the
non-Texas Peripheral South states were originally statistically insignificant and remain so,
the (insignificant) point estimates get smaller – in some cases negative – and this leads to the
Peripheral South term in model 2 becoming statistically insignificant. The effect in Texas
alone can no longer drive the Peripheral South term to significance at the subregional level.
For the trade variable, the Alabama and Florida coefficients lose their significance, while
South Carolina moves from insignificant to negative and significant, joining the populist
category along with Mississippi, North Carolina, and Tennessee. Now only being from
Georgia and Texas is associated with a more pro-free trade position.
Even more substantial changes of sign and interpretation occur in the state-level models
for social issues. Due to space constrains, this analysis is placed in the online appendix.
Conclusion
This paper demonstrates the continuing significance of the South for studies of white public
opinion and voting behavior, the utility of subregional divisions within the South, and the
complicated role of born-again Christian identification in this disproportionately Evangelical
region. To summarize the results, the support for Hypotheses 1-5 is as follows: The general
southern distinctiveness hypothesis, H1, is strongly supported, as is the subregional variation
hypothesis, H2. The state-by-state hypothesis, H3, is likewise supported overall, although
there are a few interesting exceptions. The born-again homogeneity hypothesis, H4, is gen-
erally supported. The born-again regional concentration hypothesis, H5, is supported for
social issues, but the impact of the additional control is smaller for most other issue areas.
22
These results have numerous implications for the broader study of American politics. One
implication is that the common inclusion of a South/non-South dummy variable is effectively
a weighted average of extremely significant Deep South variation watered down by the far
less distinct Peripheral South. One way of framing this is that if by “the South” analysts
mean traditional southern areas like Mississippi or Alabama rather than, for instance, the
northern Virginia suburbs of DC or the retirement communities of Florida, a South dummy
variable blends the very southern respondents of Biloxi with the perhaps southern-in-name-
only respondents of Arlington, downplaying the sizable differences in comparing the Deep
South to the rest of the nation. The Deep/Peripheral South division is not perfect, but
it is much better than a single-South term when datasets allow for it. Arguments that
southern distinctiveness is irrelevant, or that meaningful variation no longer exists within
the South, are misguided. It is true that many parts of the Peripheral South are becoming
less “southern” and more national in their political and economic outlooks. Yet it is likewise
true that this is generally not happening in the Deep South. The former has profound
implications for electoral politics, while the latter is of substantial theoretical interest to
scholars of public opinion and identity.
Second, this paper also suggests political scientists should think more about born-again
Christianity. Those interested in the South should ask whether they are more interested in a
bivariate or multivariate definition of what constitutes distinctiveness. In other words, is the
question whether the South is different overall, or rather whether it is different controlling
for its greater concentration of particular demographic characteristics, like born-again self-
identification? This paper remains agnostic on this question, but the results suggest it
requires consideration. Beyond this, considering the link between religious identification and
other issues might also prove enlightening to American politics scholars more generally.
More broadly, this analysis can serve as an empirical middle ground between two seem-
ingly contradictory phenomena: the Democrats’ southern struggles in 2004 and the strong
23
showing of Barack Obama in many of the Peripheral South states in 2008. The Democratic
Party nominee for president will not be winning the Electoral College votes of Mississippi or
Alabama anytime soon. But what Schaller (2006) and many journalistic accounts missed –
but the Obama campaign did not – is the diversity of the South. Even if the Democrats are
unlikely to start winning the Electoral College votes of the Deep South, the party is already
winning them in the Peripheral South. Whether this continues to occur will be decided
by an array of variables beyond the scope of this paragraph. But the differentiation of the
Peripheral South from the Deep South provides an electoral opportunity for the Democratic
Party that many overlooked.
24
Notes
1Regarding the latter point, what I think is most important is that Bush talked explicitly and openly
about his Evangelical faith and how it informed his politics. Previous prominent born-again Christians like
Jimmy Carter were more private regarding their faith.
2“Culture” is a dangerous analytical category, but I use it here for lack of a better term.
3For analyses using older data, see Ellison and Musick (1993) and Powers et al. (2003).
4There is, of course, a tension between how close to the Religious Right a candidate can be in the
primary and their probability of winning a general election in a more moderate electorate. For data on this,
see Bullock and Smith (2005).
5The case for a broader definitions of the region can be made, especially for historical studies. See Farhang
and Katznelson (2005) and Springer (2011) for good articulations of this argument. However, in this paper
I adhere to the Key-inspired 11-state definition more common to contemporary public opinion studies.
6This dataset is available online from the Annenberg Public Policy Center of the University of Pennsyl-
vania.
7I code support for free trade as “conservative,” as this is the position taken by the Republican Party
8The base categories for the dummy variables are: independent, some college, male; linear predictors are
set at their means; and other dummy variables in the regional/state sets are set to 0 when computing each
regional/state effect. One can always quibble with the specific values at which the controls are set, but the
overall substantive interpretation of the marginal effects is not significantly changed by other specifications.
9The AIC value is lower for model 2 and a test of the difference between the two subregional terms is
highly statistically significant for both years.
10For all dependent variables mentioned in this paragraph so far, the AIC value is lower for model 2 and
a test of the difference between the subregional terms is statistically significant.
11For both years, the AIC value is lower for model 2 and a test of the difference between the subregional
terms is statistically significant.
12The number of observations available for this question in 2008 is about a third the size of what is available
in the 2004 data, making it difficult to conjecture about change over time vs. sample size issues.
13Recall that the 2008 data is not used here due to the much smaller portion of the sample asked the
born-again question.
14These null results are not shown, but are available upon request from the author.
25
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Tables and Graphs
Table 1: Logit Models: Presidential Vote Choice, Gay Marriage, Abortion
Vote Choice Vote Choice Gay Marriage AbortionBush 2004 McCain 2008 2004 20041 2 1 2 1 2 1 2
South 0.46∗∗∗ 0.59∗∗∗ 0.18∗∗∗ 0.09∗∗∗
(0.05) (0.07) (0.02) (0.03)Deep 0.78∗∗∗ 1.21∗∗∗ 0.27∗∗∗ 0.25∗∗∗
(0.08) (0.13) (0.04) (0.04)Peripheral 0.34∗∗∗ 0.39∗∗∗ 0.14∗∗∗ 0.02
(0.05) (0.08) (0.03) (0.03)Ideology 1.02∗∗∗ 1.02∗∗∗ 1.01∗∗∗ 1.00∗∗∗ 0.62∗∗∗ 0.62∗∗∗ 0.81∗∗∗ 0.81∗∗∗
(0.03) (0.03) (0.03) (0.03) (0.01) (0.01) (0.01) (0.01)Democrat -1.85∗∗∗ -1.85∗∗∗ -1.70∗∗∗ -1.70∗∗∗ -0.22∗∗∗ -0.22∗∗∗ -0.18∗∗∗ -0.17∗∗∗
(0.05) (0.05) (0.07) (0.07) (0.03) (0.03) (0.03) (0.03)Republican 2.22∗∗∗ 2.22∗∗∗ 1.77∗∗∗ 1.78∗∗∗ 0.55∗∗∗ 0.55∗∗∗ 0.62∗∗∗ 0.62∗∗∗
(0.06) (0.06) (0.08) (0.08) (0.03) (0.03) (0.03) (0.03)Female 0.01 0.01 -0.09 -0.08 -0.16∗∗∗ -0.16∗∗∗ 0.08∗∗∗ 0.08∗∗∗
(0.04) (0.04) (0.06) (0.06) (0.02) (0.02) (0.02) (0.02)Age -0.01∗∗∗ -0.01∗∗∗ 0.00 0.00 0.00 0.00 -0.01∗∗∗ -0.01∗∗∗
(0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00)Income 0.06∗∗∗ 0.06∗∗∗ 0.06∗∗∗ 0.06∗∗∗ -0.02∗∗∗ -0.02∗∗∗ -0.10∗∗∗ -0.10∗∗∗
(0.01) (0.01) (0.02) (0.02) (0.01) (0.01) (0.01) (0.01)High School 0.05 0.04 0.10 0.10 0.12∗∗∗ 0.12∗∗∗ 0.25∗∗∗ 0.25∗∗∗
(0.05) (0.05) (0.08) (0.08) (0.03) (0.03) (0.03) (0.03)College -0.39∗∗∗ -0.39∗∗∗ -0.28∗∗∗ -0.28∗∗∗ -0.26∗∗∗ -0.26∗∗∗ -0.13∗∗∗ -0.13∗∗∗
(0.05) (0.05) (0.08) (0.08) (0.03) (0.03) (0.03) (0.03)Constant -3.11∗∗∗ -3.09∗∗∗ -3.43∗∗∗ -3.44∗∗∗ -2.31∗∗∗ -2.31∗∗∗ -2.93∗∗∗ -2.93∗∗∗
(0.13) (0.13) (0.20) (0.20) (0.07) (0.07) (0.07) (0.07)
Pseudo R2 .47 .47 .45 .46 .11 .11 0.14 0.14AIC 15402 15380 7185 7152 51842 51835 45766 45743Log lik. -7691 -7679 -3582 -3565 -25911 -25907 -22873 -22861N 20984 20984 9485 9485 42910 42910 43900 43900
Standard errors in parentheses. ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001
30
Table 2: Logit Models: Iraq, Free Trade
Iraq Iraq Free Trade Free Trade2004 2008 2004 2008
1 2 1 2 1 2 1 2
South 0.22∗∗∗ 0.32∗∗∗ -0.06∗ -0.08(0.03) (0.04) (0.02) (0.04)
Deep 0.43∗∗∗ 0.48∗∗∗ -0.09∗ -0.15(0.06) (0.08) (0.04) (0.08)
Peripheral 0.15∗∗∗ 0.27∗∗∗ -0.05 -0.06(0.04) (0.05) (0.03) (0.05)
Ideology 0.66∗∗∗ 0.65∗∗∗ 0.73∗∗∗ 0.73∗∗∗ -0.01 -0.01 -0.05∗ -0.05∗
(0.02) (0.02) (0.02) (0.02) (0.01) (0.01) (0.02) (0.02)Democrat -0.83∗∗∗ -0.83∗∗∗ -0.89∗∗∗ -0.89∗∗∗ -0.05 -0.05 -0.04 -0.04
(0.04) (0.04) (0.06) (0.06) (0.03) (0.03) (0.05) (0.05)Republican 1.32∗∗∗ 1.32∗∗∗ 1.15∗∗∗ 1.15∗∗∗ 0.29∗∗∗ 0.29∗∗∗ 0.41∗∗∗ 0.41∗∗∗
(0.04) (0.04) (0.05) (0.05) (0.03) (0.03) (0.05) (0.05)Female -0.06∗ -0.06∗ 0.03 0.03 0.20∗∗∗ 0.20∗∗∗ -0.05 -0.05
(0.03) (0.03) (0.04) (0.04) (0.02) (0.02) (0.04) (0.04)Age -0.02∗∗∗ -0.02∗∗∗ -0.01∗∗∗ -0.01∗∗∗ -0.02∗∗∗ -0.02∗∗∗ -0.01∗∗∗ -0.01∗∗∗
(0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00)Income 0.04∗∗∗ 0.04∗∗∗ 0.02 0.02∗ 0.04∗∗∗ 0.04∗∗∗ 0.06∗∗∗ 0.06∗∗∗
(0.01) (0.01) (0.01) (0.01) (0.01) (0.01) (0.01) (0.01)High School 0.01 0.01 0.01 0.00 0.02 0.02 0.02 0.02
(0.04) (0.04) (0.05) (0.05) (0.03) (0.03) (0.06) (0.06)College -0.37∗∗∗ -0.37∗∗∗ -0.18∗∗∗ -0.19∗∗∗ 0.38∗∗∗ 0.38∗∗∗ 0.55∗∗∗ 0.55∗∗∗
(0.04) (0.04) (0.05) (0.05) (0.03) (0.03) (0.05) (0.05)Constant -1.40∗∗∗ -1.39∗∗∗ -2.53∗∗∗ -2.53∗∗∗ 0.18∗∗ 0.18∗∗ -0.24 -0.24
(0.09) (0.09) (0.13) (0.13) (0.06) (0.06) (0.13) (0.13)
Pseudo R2 .23 .23 .26 .26 .03 .03 .04 .04AIC 28586 28568 15438 15434 52454 52455 14399 14400Log lik. -14283 -14273 -7709 -7706 -26217 -26217 -7190 -7189N 26998 26998 15717 15717 39062 39062 10864 10864
Standard errors in parentheses. ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001
31
Table 3: OLS Models: Group Affect Measures (2004)
Muslims Gay Orgs. Feminist Orgs.1 2 1 2 1 2
South 0.37∗∗∗ 0.49∗∗∗ 0.02(0.04) (0.04) (0.04)
Deep 0.58∗∗∗ 0.74∗∗∗ 0.09(0.07) (0.06) (0.06)
Peripheral 0.28∗∗∗ 0.40∗∗∗ -0.00(0.04) (0.04) (0.04)
Ideology 0.26∗∗∗ 0.26∗∗∗ 1.11∗∗∗ 1.11∗∗∗ 0.86∗∗∗ 0.86∗∗∗
(0.02) (0.02) (0.02) (0.02) (0.02) (0.02)Democrat -0.06 -0.06 -0.28∗∗∗ -0.28∗∗∗ -0.48∗∗∗ -0.48∗∗∗
(0.05) (0.05) (0.04) (0.04) (0.04) (0.04)Republican 0.27∗∗∗ 0.27∗∗∗ 0.68∗∗∗ 0.68∗∗∗ 0.61∗∗∗ 0.61∗∗∗
(0.04) (0.04) (0.04) (0.04) (0.04) (0.04)Female -0.37∗∗∗ -0.37∗∗∗ -0.58∗∗∗ -0.58∗∗∗ -0.36∗∗∗ -0.36∗∗∗
(0.04) (0.04) (0.03) (0.03) (0.03) (0.03)Age 0.01∗∗∗ 0.01∗∗∗ 0.02∗∗∗ 0.02∗∗∗ 0.01∗∗∗ 0.01∗∗∗
(0.00) (0.00) (0.00) (0.00) (0.00) (0.00)Income -0.05∗∗∗ -0.05∗∗∗ -0.10∗∗∗ -0.10∗∗∗ -0.01 -0.01
(0.01) (0.01) (0.01) (0.01) (0.01) (0.01)High School 0.45∗∗∗ 0.44∗∗∗ 0.57∗∗∗ 0.56∗∗∗ 0.04 0.04
(0.05) (0.05) (0.04) (0.04) (0.04) (0.04)College -0.45∗∗∗ -0.45∗∗∗ -0.60∗∗∗ -0.59∗∗∗ -0.29∗∗∗ -0.29∗∗∗
(0.04) (0.04) (0.04) (0.04) (0.04) (0.04)Constant 3.77∗∗∗ 3.78∗∗∗ 2.11∗∗∗ 2.11∗∗∗ 2.29∗∗∗ 2.29∗∗∗
(0.10) (0.10) (0.10) (0.10) (0.10) (0.10)
Adjusted R2 .07 .07 .29 .29 .20 .20AIC 94048 94034 106314 106294 95084 95084N 20120 20120 22603 22603 20872 20872
Standard errors in parentheses. ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001
32
Table 4: Ordered Probit Models:Gay Marriage, Abortion (2008)
Gay Marriage Abortion.1 2 1 2
South 0.26∗∗∗ 0.09∗∗∗
(0.02) (0.01)Deep 0.39∗∗∗ 0.22∗∗∗
(0.03) (0.02)Peripheral 0.22∗∗∗ 0.04∗
(0.02) (0.02)Ideology 0.48∗∗∗ 0.48∗∗∗ 0.44∗∗∗ 0.44∗∗∗
(0.01) (0.01) (0.01) (0.01)Democrat -0.09∗∗∗ -0.09∗∗∗ -0.14∗∗∗ -0.14∗∗∗
(0.02) (0.02) (0.02) (0.02)Republican 0.36∗∗∗ 0.36∗∗∗ 0.23∗∗∗ 0.23∗∗∗
(0.02) (0.02) (0.02) (0.02)Female -0.19∗∗∗ -0.19∗∗∗ 0.02 0.02
(0.01) (0.01) (0.01) (0.01)Age 0.01∗∗∗ 0.01∗∗∗ -0.00∗∗∗ -0.00∗∗∗
(0.00) (0.00) (0.00) (0.00)Income -0.06∗∗∗ -0.06∗∗∗ -0.08∗∗∗ -0.08∗∗∗
(0.00) (0.00) (0.00) (0.00)High School 0.26∗∗∗ 0.26∗∗∗ 0.19∗∗∗ 0.19∗∗∗
(0.02) (0.02) (0.02) (0.02)College -0.16∗∗∗ -0.16∗∗∗ -0.11∗∗∗ -0.11∗∗∗
(0.02) (0.02) (0.02) (0.02)
Cut 1 1.16∗∗∗ 1.16∗∗∗ 0.36∗∗∗ 0.36∗∗∗
(0.04) (0.04) (0.04) (0.04)
Cut 2 2.25∗∗∗ 2.25∗∗∗ 1.02∗∗∗ 1.02∗∗∗
(0.05) (0.05) (0.04) (0.04)
Cut 3 2.33∗∗∗ 2.34∗∗∗
(0.04) (0.04)
AIC 55129 55100 74572 74529Log lik. -27553 -27538 -37274 -37252N 30318 30318 32218 32218
Standard errors in parentheses. ∗ p < 0.05, ∗∗ p < 0.01,∗∗∗ p < 0.001
33
0 25% 50% 75% 100%
MSSCALARTNOKKYGANCWVTXMOINLAKSSDVANMOHORWAIAWYFLMTMINEIDCONDAZMNILCAPAMEWIMDNVDENHNYNJVTUTDCMARICT
Figure 1: Each point represents the proportion of the white population in the 48 continentalstates plus D.C. self-identifying as born-again Christian in 2004. The dotted line representsthe national average of 40 percent.
34
Vote Choice: Bush
-0.5 0.5 1.5 2.5
VA
TX
TN
SC
NC
MS
LA
GA
FL
AR
AL
Peripheral
Deep
South
Born AgainMuslims
-0.5 0.5 1.5 2.5
VA
TX
TN
SC
NC
MS
LA
GA
FL
AR
AL
Peripheral
Deep
South
Born Again
Gay Orgs.
-0.5 0.5 1.5 2.5
VA
TX
TN
SC
NC
MS
LA
GA
FL
AR
AL
Peripheral
Deep
South
Born AgainFeminist Orgs.
-0.5 0.5 1.5 2.5
VA
TX
TN
SC
NC
MS
LA
GA
FL
AR
AL
Peripheral
Deep
South
Born Again
No Born Again ControlWith Born Again Control
Figure 2: How Controlling for Born-Again Christianity Changes Regional Coefficients
35
Gay Marriage
-0.5 0.5 1.5 2.5
VA
TX
TN
SC
NC
MS
LA
GA
FL
AR
AL
Peripheral
Deep
South
Born AgainAbortion
-0.5 0.5 1.5 2.5
VA
TX
TN
SC
NC
MS
LA
GA
FL
AR
AL
Peripheral
Deep
South
Born Again
Free Trade
-1.5 -0.5 0.5 1.5
VA
TX
TN
SC
NC
MS
LA
GA
FL
AR
AL
Peripheral
Deep
South
Born AgainIraq
-0.5 0.5 1.5 2.5
VA
TX
TN
SC
NC
MS
LA
GA
FL
AR
AL
Peripheral
Deep
South
Born Again
No Born Again ControlWith Born Again Control
Figure 3: How Controlling for Born-Again Christianity Changes Regional Coefficients
36
Online Appendix
This section contains online material supplementing the manuscript text, including:
• Figures for the multilevel modeling results
• More detailed state-by-state analysis of Hypothesis 5
• Regression tables for the state models
• Results of the group affect models using ordered probit rather than OLS
37
Figures for multilevel model results
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WYWI
WVWAVTUTSDRIPA
OROKOHNDNYNMNJNHNVNEMTMOMNMI
MAMDMEKYKSIAINILID
DCDECTCOCAAZ
VATXTNSCNCMSLAGAFLARAL
Figure 4: State Level Variation in Effect of Born-Again Christian Identification
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OROKOHNDNYNMNJNHNVNEMTMOMNMI
MAMDMEKYKSIAINILID
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Figure 5: State Level Variation in Effect of Born-Again Christian Identification
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Abortion Ban
−0.5 0.5 1.5 2.5
WYWI
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OROKOHNDNYNMNJNHNVNEMTMOMNMI
MAMDMEKYKSIAINILID
DCDECTCOCAAZ
VATXTNSCNCMSLAGAFLARAL
Figure 6: State Level Variation in Effect of Born-Again Christian Identification
40
Detailed state-by-state analysis of Hypothesis 5
For the Muslims group affect measure, the Texas coefficient loses its statistical significance in
the model with the born-again term, joining Florida and Louisiana. In the gay organizations
model, the Virginia and Texas coefficients lose their significance, again joining Florida and
Louisiana. There is, additionally, some significant change in interpretation of the coefficients
in the gay organizations models among the terms that remain significant, with some coef-
ficients being significantly altered by the presence of the born-again Christian control. At
the regional level, the South coefficient loses about 43 percent of its original size, dropping
from .49 to .28. This is reflected in the subregional coefficients as well, with the Deep South
coefficient moving from .74 to .42 (a 41 percent decrease) and the Peripheral South coeffi-
cient moving from .40 to .22 (a 45 percent decrease). At the state level, similarly substantial
changes in point estimates occur for every state except Florida. While some would focus
on the consistency of statistical significance only, substantive interpretation matters as well:
a reader trying to assess the impact of the regional variable on attitudes would make an
inflated assessment of the regional term’s impact without the born-again control variable.
When adding a single additional variable causes the coefficient on the variable of theoretical
interest to be cut by nearly half, model specification takes on additional significance.
Finally, the two policy issues offer perhaps the most interesting changes. For the anti-
gay marriage amendment variable, the coefficients on the majority of states lose their initial
statistical significance: whites in Georgia, Louisiana, North Carolina, South Caroline, Ten-
nessee, and Texas are now not statistically different than the rest of the nation. The Vir-
ginia and Florida coefficients are not significant in either model. Only the effects in Alabama,
Arkansas, and Mississippi remain robust with the addition of the born-again control variable.
And even in these states, the logit coefficients decrease by 55 percent, 48 percent, and 45
percent, respectively. The marginal effects decrease from 9 percent to 4 percent in Alabama,
11 percent to 6 percent in Arkansas, and 14 percent to 8 percent in Mississippi.15 State and
41
regional effects on this issue appear to be heavily influenced by born-again Christianity.
While the pattern of change – from conservative to insignificant – is consistent in the gay
marriage models, the changes in the abortion ban models are far more complex. While all
states move noticeably to the left – with the exception of Florida, which barely changes – the
end result depends on where the state effect started in the previous model specification. The
coefficients on Alabama, Mississippi, South Carolina, and Tennessee – previously significant
in the conservative direction – become statistically insignificant. The coefficients on Georgia,
North Carolina, and Texas – previously statistically insignificant – become significant in the
liberal direction, with new estimated marginal effects of -5 percent, -4 percent, and -3 percent,
respectively. Arkansas and Louisiana remain statistically significant in the conservative
direction, but less so – moving from +12 percent to + 7 percent and +8 percent to +7
percent, respectively. Finally, Florida and Virginia remain statistically significant in the
liberal direction, with Virginia becoming significantly more liberal, moving from -3 percent
to -8 percent, and Florida moving from -3 to -5 percent.
42
State regression tables
Table 5: Logit Models
Bush McCain Marriage Abortion Iraq Iraq Trade Trade2004 2008 2004 2004 2004 2008 2004 2008
AL 0.66∗∗∗ 1.18∗∗∗ 0.38∗∗∗ 0.41∗∗∗ 0.61∗∗∗ 0.21 -0.20∗ -0.25(0.16) (0.26) (0.08) (0.08) (0.13) (0.15) (0.08) (0.15)
AR 0.59∗∗ 0.74∗∗ 0.46∗∗∗ 0.63∗∗∗ 0.21 0.36 -0.08 0.36(0.20) (0.28) (0.10) (0.11) (0.14) (0.18) (0.11) (0.18)
FL 0.12 0.20 0.03 -0.20∗∗∗ 0.06 0.12 0.12∗ 0.06(0.09) (0.14) (0.05) (0.06) (0.07) (0.09) (0.05) (0.09)
GA 0.81∗∗∗ 0.97∗∗∗ 0.20∗∗ 0.06 0.44∗∗∗ 0.54∗∗∗ 0.14∗ -0.02(0.13) (0.21) (0.07) (0.07) (0.10) (0.13) (0.07) (0.13)
LA 1.00∗∗∗ 2.50∗∗∗ 0.24∗ 0.44∗∗∗ 0.31∗ 0.77∗∗∗ -0.08 -0.07(0.20) (0.37) (0.09) (0.10) (0.13) (0.17) (0.10) (0.19)
MS 1.10∗∗∗ 1.13∗ 0.56∗∗∗ 0.61∗∗∗ 0.28 0.59∗ -0.52∗∗∗ -0.66∗
(0.32) (0.44) (0.13) (0.12) (0.18) (0.24) (0.13) (0.27)NC 0.27∗ 0.43∗ 0.13∗ 0.04 0.14 0.32∗∗ -0.61∗∗∗ -0.47∗∗∗
(0.12) (0.17) (0.06) (0.07) (0.09) (0.11) (0.06) (0.12)SC 0.57∗∗ 0.78∗∗ 0.18∗ 0.05 0.42∗∗ 0.32 -0.17 -0.05
(0.19) (0.27) (0.09) (0.09) (0.13) (0.17) (0.09) (0.17)TN 0.31∗ 0.46∗ 0.28∗∗∗ 0.25∗∗∗ 0.01 0.31∗ -0.38∗∗∗ -0.38∗∗
(0.14) (0.20) (0.07) (0.07) (0.10) (0.13) (0.07) (0.14)TX 0.62∗∗∗ 0.68∗∗∗ 0.16∗∗∗ 0.06 0.35∗∗∗ 0.46∗∗∗ 0.16∗∗∗ 0.10
(0.10) (0.15) (0.05) (0.05) (0.07) (0.09) (0.05) (0.09)VA 0.25∗ 0.05 0.07 -0.20∗∗ 0.02 0.08 0.11 0.00
(0.12) (0.17) (0.07) (0.07) (0.09) (0.12) (0.07) (0.12)Constant -3.09∗∗∗ -3.44∗∗∗ -2.31∗∗∗ -2.93∗∗∗ -1.39∗∗∗ -2.53∗∗∗ 0.20∗∗ -0.23
(0.13) (0.20) (0.07) (0.07) (0.09) (0.13) (0.06) (0.13)
Pseudo R2 .47 .46 .11 .15 .24 .26 .03 .04AIC 15377 7140 51823 45662 28566 15434 52298 14382Log lik. -7669 -3550 -25891 -22811 -14263 -7697 -26129 -7171N 20984 9485 42910 43900 26998 15717 39062 10864
Standard errors in parentheses. ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001. Control variables notshown due to space constraints.
43
Table 6: OLS Models: Group Affect Measures (2004)
Muslims Gay Orgs. Fem. Orgs.
AL 0.73∗∗∗ 1.11∗∗∗ 0.24(0.14) (0.13) (0.13)
AR 0.71∗∗∗ 1.40∗∗∗ 0.31(0.17) (0.17) (0.16)
FL 0.12 -0.08 -0.14(0.08) (0.08) (0.08)
GA 0.47∗∗∗ 0.51∗∗∗ 0.03(0.11) (0.11) (0.10)
LA 0.26 0.26 -0.10(0.16) (0.15) (0.15)
MS 1.11∗∗∗ 1.46∗∗∗ 0.38∗
(0.21) (0.19) (0.19)NC 0.39∗∗∗ 0.65∗∗∗ -0.01
(0.10) (0.10) (0.10)SC 0.64∗∗∗ 0.73∗∗∗ 0.05
(0.15) (0.14) (0.14)TN 0.65∗∗∗ 0.87∗∗∗ -0.04
(0.12) (0.11) (0.11)TX 0.18∗ 0.39∗∗∗ 0.11
(0.08) (0.07) (0.07)VA 0.22∗ 0.24∗ -0.06
(0.11) (0.11) (0.10)Constant 3.77∗∗∗ 2.09∗∗∗ 2.29∗∗∗
(0.10) (0.10) (0.10)
Adjusted R2 .07 .30 .20AIC 94015 106172 95086N 20120 22603 20872
Standard errors in parentheses. ∗ p < 0.05,∗∗ p < 0.01, ∗∗∗ p < 0.001. Control variablesnot shown due to space constraints.
44
Table 7: Ordered Probit Models:Gay Marriage, Abortion (2008)
Marriage Abortion
AL 0.57∗∗∗ 0.31∗∗∗
(0.06) (0.05)AR 0.72∗∗∗ 0.32∗∗∗
(0.07) (0.06)FL -0.02 -0.15∗∗∗
(0.03) (0.03)GA 0.21∗∗∗ 0.08
(0.05) (0.04)LA 0.34∗∗∗ 0.40∗∗∗
(0.06) (0.05)MS 0.61∗∗∗ 0.39∗∗∗
(0.09) (0.07)NC 0.35∗∗∗ 0.10∗∗
(0.04) (0.03)SC 0.43∗∗∗ 0.08
(0.06) (0.05)TN 0.47∗∗∗ 0.22∗∗∗
(0.05) (0.04)TX 0.24∗∗∗ 0.09∗∗
(0.03) (0.03)VA 0.15∗∗∗ -0.03
(0.04) (0.04)
Cut 1 1.18∗∗∗ 0.36∗∗∗
(0.04) (0.04)
Cut 2 2.28∗∗∗ 1.02∗∗∗
(0.05) (0.04)
Cut 3 2.35∗∗∗
(0.04)
AIC 54917 74401Log lik. -27437 -37178N 30318 32218
Standard errors in parentheses. ∗ p < 0.05,∗∗ p < 0.01, ∗∗∗ p < 0.001. Control variablesnot shown due to space constraints.
45
Ordered probit models for group affect measures
The next page contains a version of the group affect measure models (OLS versions presented
in Tables 3 and 6) using an ordered probit specification instead. The results are robust, so
I have kept the easier to interpret OLS results in the main text.
46
Table 8: Ordered Probit Models: Group Affect Measures (2004)
Muslims (2004) Gay Orgs. (2004) Feminist Orgs. (2004)1 2 3 1 2 3 1 2 3
South 0.15∗∗∗ 0.21∗∗∗ 0.01(0.02) (0.02) (0.02)
DS 0.24∗∗∗ 0.32∗∗∗ 0.04(0.03) (0.03) (0.03)
PS 0.12∗∗∗ 0.16∗∗∗ 0.00(0.02) (0.02) (0.02)
AL 0.31∗∗∗ 0.49∗∗∗ 0.11(0.06) (0.06) (0.06)
AR 0.28∗∗∗ 0.61∗∗∗ 0.14∗
(0.07) (0.07) (0.07)FL 0.05 -0.03 -0.06
(0.03) (0.03) (0.03)GA 0.19∗∗∗ 0.21∗∗∗ 0.01
(0.05) (0.05) (0.05)LA 0.11 0.11 -0.05
(0.07) (0.06) (0.06)MS 0.46∗∗∗ 0.71∗∗∗ 0.16
(0.09) (0.09) (0.08)NC 0.16∗∗∗ 0.28∗∗∗ -0.00
(0.04) (0.04) (0.04)SC 0.27∗∗∗ 0.32∗∗∗ 0.03
(0.06) (0.06) (0.06)TN 0.26∗∗∗ 0.37∗∗∗ -0.02
(0.05) (0.05) (0.05)TX 0.07∗ 0.16∗∗∗ 0.05
(0.03) (0.03) (0.03)VA 0.09∗ 0.09∗ -0.03
(0.05) (0.04) (0.05)Ideology 0.11∗∗∗ 0.11∗∗∗ 0.11∗∗∗ 0.46∗∗∗ 0.46∗∗∗ 0.45∗∗∗ 0.37∗∗∗ 0.37∗∗∗ 0.37∗∗∗
(0.01) (0.01) (0.01) (0.01) (0.01) (0.01) (0.01) (0.01) (0.01)Democrat -0.02 -0.02 -0.02 -0.11∗∗∗ -0.11∗∗∗ -0.11∗∗∗ -0.21∗∗∗ -0.21∗∗∗ -0.21∗∗∗
(0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02)Republican 0.11∗∗∗ 0.11∗∗∗ 0.11∗∗∗ 0.28∗∗∗ 0.28∗∗∗ 0.28∗∗∗ 0.26∗∗∗ 0.26∗∗∗ 0.26∗∗∗
(0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02)Female -0.15∗∗∗ -0.15∗∗∗ -0.15∗∗∗ -0.23∗∗∗ -0.23∗∗∗ -0.23∗∗∗ -0.16∗∗∗ -0.16∗∗∗ -0.16∗∗∗
(0.02) (0.02) (0.02) (0.01) (0.01) (0.01) (0.01) (0.01) (0.01)Age 0.01∗∗∗ 0.01∗∗∗ 0.01∗∗∗ 0.01∗∗∗ 0.01∗∗∗ 0.01∗∗∗ 0.00∗∗∗ 0.00∗∗∗ 0.00∗∗∗
(0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00)Income -0.02∗∗∗ -0.02∗∗∗ -0.02∗∗∗ -0.04∗∗∗ -0.04∗∗∗ -0.04∗∗∗ -0.00 -0.00 -0.00
(0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00)High School 0.18∗∗∗ 0.18∗∗∗ 0.18∗∗∗ 0.24∗∗∗ 0.24∗∗∗ 0.24∗∗∗ 0.02 0.02 0.02
(0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02)College -0.19∗∗∗ -0.19∗∗∗ -0.19∗∗∗ -0.24∗∗∗ -0.24∗∗∗ -0.24∗∗∗ -0.12∗∗∗ -0.12∗∗∗ -0.12∗∗∗
(0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.02)
AIC 77679 77665 77647 85712 85689 85557 85665 85666 85667Log lik.N 20120 20120 20120 22603 22603 22603 20872 20872 20872
Standard errors in parentheses. ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001. Cutpoints redacted for space, but available upon request.
47