Who Is Responsible for the Gender Gap? The Dynamics of Men’s and Women’s Democratic Macropartisanship,1950

Abstract

I argue the gender gap is a function of men and women changing their partisanship as they seek the best representation of their gendered social identity from the political parties. Specifically, shifts in the parties due to party realignments and shifts in the composition of parties’ congressional delegations have provided individuals with a clearer signal on which to base their partisan attachments. Men and women have responded differently to these signals and developed different political identities over the past seventy years, resulting in the gender gap in partisanship. To test this theory, I have constructed an innovative macro-level dataset of men’s and women’s partisan attachments on a quarterly basis between 1950 and 2012. I use a Seemingly Unrelated Regression framework to estimate patterns of men’s and women’s Democratic macropartisanship and whether particular factors contribute to the gender gap by having different effects on men’s and women’s partisanship. The results are consistent with my theoretical expectations, highlighting how symbolic images shape partisan attachments, and demonstrate the gender gap is a function of changes in both men’s and women’s macropartisanship.

Keywords

gender gap partisanship elite cues

The gender gap first garnered publicity in the aftermath of the 1980 presidential election. Subsequent research has identified differences in men’s and women’s opinions, ideology, knowledge, and partisanship (Huddy, Cassese, and Lizotte 2008; Ondercin and Jones-White 2011). Initially heralded as a success of the second wave of the women’s movement, these gender gaps were mainly attributed to changes in women’s political behavior (Abzug 1984; Smeal 1984). Further analyses, however, suggest the gender gap may be less about women’s behavior than it is about men’s behavior (Kaufmann and Petrocik 1999; Norrander 1999). Despite a robust body of scholarship on the gender gap, we do not have a clear understanding of the origins of the gender gap in partisanship, or whether the gap is a function of men leaving the Democratic Party or women growing more Democratic.

This article addresses these shortcomings by analyzing the dynamics of men’s and women’s partisanship separately from 1950 to 2012. Drawing on research that claims partisan attachments are driven by social identities (Green, Palmquist, and Schickler 2002), I argue the gender gap is a function of men and women changing their partisanship as they seek the best representation of their gendered social identity from the political parties. Specifically, changes in the parties due to party realignments and shifts in the composition of the congressional delegations have provided individuals with a clearer signal on which to base their partisan attachments. Men and women have responded to these signals and developed different political identities over the past seventy years, resulting in the gender gap in partisanship.

This article makes four contributions. First, it furthers our understanding of macro political behavior by examining the political dynamics of subgroups in the electorate. Social identities, such as sex, divide and structure the electorate.¹ Moreover, these divisions have important political implications for electoral politics (Diekman and Schneider 2010; Schaffner 2005). By understanding how sex structures partisan attachments over time, we gain insight into electoral changes. Second, this paper provides a more complete theoretical explanation of the gender gap. While occasionally acknowledging that men’s behavior may form the gap, existing research largely has theorized about the gap from the perspective of women’s political behavior. The theory proposed here accounts for changes in both men’s and women’s political behavior and the political parties. Third, the data used in this analysis allow for a better empirical understanding of the gender gap. I have constructed an innovative macro-level dataset of men’s and women’s partisan attachments on a quarterly basis between 1950 and 2012. Having data on men’s and women’s partisanship at this level of aggregation is crucial to understanding the gender gap because the gender gap is fundamentally a macro-level phenomenon. Finally, most studies of the gender gap focus on the period after 1980, overlooking earlier movement in men’s and women’s partisanship. Analyzing men’s and women’s macropartisanship over time allows us to better understand movements in partisanship that are not election specific and provides a clearer picture of the origins of the gender gap than analyzing the gap in vote choice. Because party realignments and changes in the aggregate affiliations of the electorate are slow to evolve (Brewer and Stonecash 2009; Petrocik 1981), the sixty-two years of data analyzed here provide unique leverage for understanding the long-term dynamics of men’s and women’s partisanship. My findings indicate that both men and women contribute to the formation of the gender gap by adjusting their partisanship in response to the composition of party elites.

In the next two sections, I review the relevant literature on the gender gap and outline my theoretical expectations. I then provide an overview of the unique dataset assembled for this project and the modeling approach. The following section presents tests of the expectations over the entire time period, before 1980, and after 1980. These results demonstrate that the gender gap in partisanship largely formed as men and women responded to changes in the composition of the party elites. These findings imply, among other things, early scholarship that viewed the gender gap as a result of the second wave of the US women’s movement was partially correct. The increase in women’s representation in the Democratic Party, along with Southern realignment, sent cues to the mass public about the representation of social identities that led to the formation and growth of the gender gap. I conclude with a brief discussion of some of the implication of my argument and findings.

The Gender Gap

Despite decades of research on the gender gap, we have a limited understanding of what drives differences in men’s and women’s political behavior for four reasons. First, the vast majority of research on the gender gap tends to be election-centric. That is, most analyses are done post-election and explain the gender gap in vote choice as a function of the salient issues and the characteristics of the voters in particular elections. With respect to the role of issues, men and women have held different opinions concerning the use of force domestically and abroad, social welfare, the environment, and the size and scope of government for decades (Barnes and Cassese 2017; Huddy, Cassese, and Lizotte 2008; Lizotte 2016). These differences are stable and robust across electoral contexts and have been linked to the gender gap in vote choice (Chaney, Alvarez, and Nagler 1998). In addition to issue positions, the salience of the issues also appears to matter. For example, while simple differences on social welfare issues appear to explain the gender gap in 1992, it is the salience of social welfare issues to male voters that matters in 1996 (Kaufmann and Petrocik 1999).

Electorates’ demographic characteristics also are commonly used to explain the gender gap in vote choice. Carroll’s (1988) classic thesis argues the gender gap is a function of women’s growing economic and psychological independence from men as a result of increased workforce participation. Women’s workforce participation increases their tendency to vote for Democratic presidential candidates (Manza and Brooks 1998). Moreover, differences in the issue positions discussed above largely have been attributed to women’s role in society and increased autonomy (Diekman and Schneider 2010; Howell and Day 2000).

These studies are informative, but their focus on elections has limited our understanding of the origins and dynamics of the gender gap in two ways. One, analyses of vote choice identify issue differences as a central explanatory factor of the gender gap, but the differences in men’s and women’s opinions across issues have remained relatively stable (Kellstedt, Peterson, and Ramirez 2010). Accordingly, the focus on issues fails to help us understand why the gap has grown over time. Two, election outcomes do not simply materialize; rather, they are products of dynamics occurring between elections (Erikson, MacKuen, and Stimson 2002). Studies of vote choice offer only a limited examination of the sources of the gender gap in partisanship. Partisan attachments fundamentally shape the voting decisions of the electorate (Lewis-Beck et al. 2008) and the gender gap in vote choice (Kaufmann and Petrocik 1999). An additional by-product of the election-centric nature of gender gap studies has been the focus on post-1980 elections. This focus overlooks the fact that gender gaps existed before the 1980 presidential election (Norrander 2008). We, therefore, need to examine men’s and women’s partisan attachments between elections and expand the temporal scope of our research to understand the origins of the gender gap.

A second limiting factor of existing research is its level of analysis. The gender gap is an aggregate phenomenon. The vast majority of research that seeks to understand what factors cause the gender gap, though, is focused on the individual (for exceptions, see Box-Steffensmeier, De Boef, and Lin 2004; Norrander 1999). Important individual-level processes contribute to the gender gap (Diekman and Schneider 2010); however, how dynamics at the aggregate-level shape these individual-level processes is poorly understood.

Third, and somewhat paradoxically, analyses of the gender gap itself limit our ability to identify the source of the gap. The gender gap is a function of both men’s and women’s political behavior. Indeed, the gender gap could emerge and/or grow due to any of the following processes. First, men’s partisanship could change while women’s partisanship remains the same. Second, women’s partisanship could change and men’s partisanship could stay the same. Third, both men’s and women’s partisanship could change in the same direction but with different magnitudes. Fourth, men’s and women’s partisanship could change in opposite directions. Therefore, analyzing men’s and women’s aggregate partisanship separately is necessary to identify and understand the processes underlying the gender gap.

Finally, the theoretical discussion of the role the political parties play in the formation and maintenance of the gender gap is limited. Initial reports of the gender gap suggested the gap was a function of changes occurring within the parties (Abzug 1984; Smeal 1984), but subsequent studies found little support for this claim (Mansbridge 1985). Important changes have occurred within the parties regarding policy positions and who makes up the parties-in-government (Wolbrecht 2000). The lack of attention to the political parties suggests we are missing an important piece of the puzzle for understanding the origins of the gender gap.

This paper addresses the four shortcomings of existing research on the gender gap in two ways. First, I develop a theoretical explanation of the gender gap that focuses on how both men and women adjust their partisan attachments in response to changes in the political parties. Second, I estimate patterns of men’s and women’s macropartisanship between 1950 and 2012.²

Sex, Representation, and Party Realignments

Gender shapes experiences, expectations, and interests and, consequently, influences the US political system in a multitude of ways (Beckwith 2014; Iversen and Rosenbluth 2010; Ritter 2008). Furthermore, men’s and women’s social identities are fundamentally linked to their sex and form the basis of their partisan identification (Green, Palmquist, and Schickler 2002). This theory implies the gender gap’s formation is at least partially a result of men and women adjusting their partisan preferences based on the representation of their gendered social identity in the political parties.

Individuals select the party that they perceive to best reflect and represent their salient social identities (Green, Palmquist, and Schickler 2002). Moreover, the electorate looks for cues from the political parties regarding representation (Levendusky 2010; Philpot 2007).³ I argue changes in the parties as a result of party realignments and changes in the sex composition of congressional delegations have produced clearer signals for voters regarding the representation of their gendered social identities over time. These changes coincided with social and demographic shifts that realigned the substantive interests of men and women with the interests of other social groups found within the respective parties.

The relationship between sex and the political parties has changed greatly over the past several decades. Party differences, as a result of issue evolutions, have emerged around abortion and other women’s issues (Adams 1997; Wolbrecht 2000). Arguably, the largest change between the political parties and sex concerns who is elected to represent the parties-in-government. The number of women in elected office has increased dramatically over the past several decades, but more so in the Democratic Party. In the 1950s and 1960s, there were slightly more female Republican officials than female Democratic officials (Wolbrecht 2000). Starting in the 1970s, trends shifted, and the number of women elected from the Democratic Party has increased at a greater rate in the US Congress and state legislatures (Crowder-Meyer and Lauderdale 2014; Sanbonmatsu 2002).

The changes in the sex composition of the parties-in-government increasingly provide a clearer signal to individuals about the representation of their gendered social identities by the parties. Two complementary mechanisms lead men and women to view the political parties as representing different gender identities. First, descriptive representation increases the visibility of women in politics, leading to increases in women’s engagement and political participation (Atkeson 2003; Campbell and Wolbrecht 2006). Moreover, women candidates also influence the behavior of men (Wolak 2015). Descriptive representation provides a visible cue to the electorate about the representation of social identities. As women are more likely to see their gendered identity reflected in the composition of the Democratic Party elites, they will be attracted to the Democratic Party. At the same time, men will be less likely to see their gender identity reflected in elites of the Democratic Party, causing their identification with the Democratic Party to decline.⁴

Second, descriptive representation leads to substantive or policy representation. Women in elected office are fundamental for the representation of women’s interests (Swers 2002). Women seeing women elected predominately from the Democratic Party should shape their perceptions of shared interest with the Democratic Party. Women, therefore, should be drawn to the Democratic Party based on descriptive representation and expectations of better substantive representation. At the same time, men are less likely to see their interests in the Democratic Party and should become less likely to identify with the Democratic Party.

Party realignments also have shaped images of who the parties represent. The New Deal realignment resulted in an expansion of the federal government that implemented social welfare programs geared toward helping the less fortunate in society and reducing inequality. Over time, these social programs have become increasingly associated with minority interests (Gilens 1999; Kinder 1996). Accordingly, the perception of the Democratic Party changed slowly to one dominated by minority interests. While often not considered part of the New Deal coalition, our perception of the Democratic Party has evolved to incorporate women and their interests. As the Democratic Party has incorporated a more heterogeneous mix of groups, men as a social group, and in particular white men, have found less of a connection with the Democratic Party. As a result, the winning coalition of the Republican Party contains more men. This explanation fits with the finding that men’s attitudes about social welfare spending have become an increasingly important determinant of partisanship (Kaufmann and Petrocik 1999).

The policies resulting from the New Deal are also relevant to women, but not in the same way as they are for men. Women tend to be more supportive of social welfare policies than men (Barnes and Cassese 2017; Huddy, Cassese, and Lizotte 2008). Social changes in the institution of marriage and women’s workforce participation greatly changed women’s relationship with government (Iversen and Rosenbluth 2010). The policy goals and ideas of the Democratic Party are more in line with the policy preferences and goals of women (Iversen and Rosenbluth 2010). Thus, we should see increases in women’s Democratic macropartisanship as the social welfare function of government expands and as women take on new roles, such as paid employment.

While rarely acknowledged in work on the gender gap, changes in women’s position in society are not independent of changes in men’s position and role in society. Men in the labor force interact with women more often and are more likely to have wives or mothers that participate in the paid labor force. Men’s experiences with women in the workforce may lead them to develop greater sympathy for the challenges women face, resulting in more feminist attitudes by men (Banaszak and Plutzer 1993). However, women’s workforce participation and greater independence can be seen as a threat to men’s economic power and privilege (Iversen and Rosenbluth 2010), causing men to shift their partisan attachments away from the Democratic Party toward the more traditional, conservative rhetoric of the Republican Party. It, therefore, is unclear how women’s workforce participation should influence men’s Democratic macropartisanship.

Southern realignment continues to shape partisan politics. The solid Democratic majority found in the states of the Confederacy has vanished in both the mass electorate and elected officials. Due to changes within the parties over issues of race, whites in the South fled the Democratic Party (Carmines and Stimson 1989). Women in the South were much slower than men to change their partisan attachments, creating a gender gap in partisanship (Norrander 1999; Ondercin 2013). Not only did Southern realignment shift regional party attachments, but it further aligned the interests of the Democratic Party with those of minorities. I expect that the signal sent regarding representation of interests should have the largest influence on men and lead to further declines in their Democratic partisanship.

Southern realignment’s effect on women’s partisanship is less clear because of the cross-cutting influences of regional, gender, and racial identities. Ondercin (2013) highlights these cross-pressures in her analysis of Southern white women’s political attitudes. She finds that Southern white women are less likely to identify with the Democratic Party than non-Southern white women but more likely to identify with the Democratic Party than Southern white men. In addition, Southern white women are more likely to identify with the Republican Party than both Southern and non-Southern white men. Thus, women’s Democratic partisanship over time could react to Southern realignment in three ways. First, we could see a decrease in Democratic Party identification as Southern realignment causes men and women to move away from the Democratic Party. However, given existing research, we would expect this effect to be smaller for women. Second, we could see no aggregate influence of Southern realignment because cross-pressuring identities could cause any effect to wash out. Or third, we could observe increasing Democratic partisanship among women as they interpret the realignment as a signal that the Democratic Party better represents minorities and women.

Finally, political and economic evaluations explain changes in partisan attachments, especially at the macro-level (Erikson, MacKuen, and Stimson 2002). Such evaluations influence short-term fluctuations and can have enduring effects on macropartisanship. It is unclear, though, exactly how economic and political evaluations contribute to the gender gap in partisanship. There is considerable evidence that men and women evaluate politics and the economy differently. Gender gaps in partisanship and vote choice extend to gender gaps in presidential approval (Gilens 1988). Men and women also tend to evaluate government performance on social welfare and military issues differently (Fite, Genest, and Wilcox 1990; Gilens 1988). In addition, regardless of which party holds the White House, women tend to offer more negative evaluations of the economy, a driving force behind differences in presidential approval (Clarke et al. 2005).

Based on the preceding paragraphs, Table 1 provides an overview of my expectations regarding men’s and women’s partisan attachments.

Table 1.

Summary of Theoretical Expectations for Democratic Macropartisanship.

	Men	Women
Party difference in women’s representation	↓	↑
Southern realignment	↓	↑↓
New Deal realignment	↓	↑
Women’s workforce participation	↑↓	↑
Economic evaluations	↑↓	↑↓
Political evaluations	↑↓	↑↓

Measurement

Assessing men’s and women’s partisan attachments requires two dependent variables: men’s Democratic macropartisanship and women’s Democratic macropartisanship. I calculate men’s and women’s Democratic macropartisanship as the proportion of Democrats among Democratic, Republican, and independent identifiers for men and women, respectively. The dependent variables are quarterly time series from 1950 to 2012 constructed from Gallup surveys archived at the Roper Center for Public Opinion. Overall, 1,579 Gallup surveys contributed to the quarterly estimates. Men’s and women’s Democratic partisanship were calculated for each survey and then aggregated, weighted based on the surveys’ sample sizes. The Gallup surveys allow for the creation of a longer time series with more frequent observations than other commonly used surveys. The online appendix discusses the use of Gallup surveys to measure partisanship, descriptive statistics for men’s and women’s partisanship and explanatory variables used in the analyses, and the sources for the explanatory variables.

The quarterly measures of men’s and women’s Democratic macropartisanship are displayed in Figure 1. One of the most striking characteristics of Figure 1 is the shared movement between men’s and women’s partisanship from 1950 to 2012. This suggests the same underlying process(es) might cause changes to men’s and women’s partisanship. The early gender gap was slow to emerge, with small differences evolving over several decades. The average difference between men’s and women’s partisanship was less than 1 percentage point and not in a consistent direction in the 1950s. During the 1960s, men’s and women’s partisanship grew apart slightly, with differences averaging about 2.3 percent. Importantly, despite these differences being small, after 1963, women’s Democratic Party identification has always been higher than men’s Democratic Party identification.

Figure 1.

Men’s and Women’s Democratic Macropartisanship, Quarterly 1950–2012.

During the 1970s, the difference between men’s and women’s party identification grew by about a point, averaging 3.4 percent. As we would expect based on our current understanding of the gender gap, at the end of the 1970s, men’s and women’s Democratic partisan attachments diverged further as men moved away from the Democratic Party at a faster rate than women. Notable given the conventional wisdom, the gender gap in partisanship existed and was persistent before the 1980 presidential election. The gap has continued to widen each subsequent decade, averaging 5.2 percent in the 1980s, 6.8 percent in the 1990s, 8.5 percent in the 2000s, and 11.7 percent between 2010 and 2012. During these later decades, the growth in the gap appears to be caused by increasing women’s Democratic partisanship and decreasing men’s Democratic partisanship. Overall, Figure 1 suggests that the gender gap in partisanship is a function of movement in men’s and women’s partisan attachments.

Explanatory Variables

Party difference of women’s representation is designed to capture the increasing presence and visibility of women in the Democratic Party’s congressional delegation, which acts as a signal to individuals about the representation of gendered interests. The party difference in women’s representation is calculated by subtracting the proportion of women in the Republican delegation in Congress from the proportion of women in the Democratic delegation in Congress. Party difference takes into account the relative presence of women from the Democratic and Republican Parties and the relative visibility of women in each party delegation.

I use per capita government expenditures on social benefits in constant 1995 US dollars (social spending) to proxy the policy changes associated with the New Deal realignment. The increased role the government plays in economic and social policies has been the defining feature of the New Deal realignment (Brewer and Stonecash 2009), with the Democratic Party associated with its social welfare policies. Thus, the actual changes in social welfare benefits provided by the federal government should be related to changes in perceptions of the Democratic Party. Moreover, the expansion of the government’s social welfare benefits is tied to larger social changes for women (Iversen and Rosenbluth 2010). Women’s workforce participation captures changing demographic patterns that have shifted women’s and men’s interests. It is measured as the seasonally adjusted civilian labor force participation rate for women. Southern realignment identifies the changing composition of the Democratic Party and is measured as the proportion of Democrats in the Southern delegation to the US Congress.

Finally, I control for economic and political evaluations that could influence partisanship. Economic evaluations are measured using the Michigan Consumer Sentiment Index (consumer sentiment). This index is available quarterly beginning in 1952, with a few quarters missing early in the series. Missing data were interpolated by using the average of the two time points before and after the missing observation. I multiplied the series by −1 during Republican presidential administrations to adjust for differing effects.⁵ Political evaluations are modeled using presidential approval from Gallup surveys. The influence of the economy is purged from the approval measure by regressing consumer sentiment on the presidential approval series and using the residuals. The approval series is also recoded based on presidential administrations, and the first quarter of a new presidency is dropped to account for changes in presidential administrations.

Model Specification

The empirical analysis in this paper focuses on three questions. What factors influence men’s Democratic macropartisanship? What factors affect women’s Democratic macropartisanship? Are these effects different for men and women and, therefore, contributing to the formation of the gender gap? To answer these questions, my analysis relies on a Seemingly Unrelated Regression (SUR) framework. The SUR is a system of equations; in this case, one equation for men’s partisanship and one equation for women’s partisanship. The main advantage of the SUR framework, for my purpose, is that it allows for a direct test of whether a given factor has a significantly different effect on men’s partisanship than it does on women’s partisanship.

Before estimating the SUR, we need to consider two issues associated with the dynamic data generating process for each variable. First, each variable, or univariate time series, can be generated by multiple temporal processes. For example, the univariate series of men’s partisanship is a random or stochastic process. However, there are multiple dynamic processes that influence how exogenous shocks at time t influence observations of the variable at t + 1. These dynamic components can be identified using a basic Box-Jenkins Auto-Regressive Integrated Moving Average or ARIMA(p,I,q) model.⁶ Second, the temporal data-generating process for each variable may be different. For instance, changes at time t to social spending are permanently integrated into the series, impacting future values of social spending, while changes in approval at time t have a diminishing influence on future values of approval. When univariate dynamics or series with different dynamic processes are not properly modeled, there is an increased risk of spurious results (Box-Steffensmeier et al. 2014; Enders 2008). To address these issues, each univariate series is filtered using an ARIMA(p,I,q) model to produce stochastic “white noise” residuals. The series that results from the filtering process represents pure innovations that can be explained by other variables. As Box-Steffensmeier et al. (2014, p. 27) explain, this process gives us “confidence that any time series properties of the data will not account for any observed correlation between the covariates and the dependent variable.” Information about the ARIMA(p,I,q) modeling of each univariate time series can be found in the online appendix.

The preceding section offers theoretical expectations regarding how the covariates are related to men’s and women’s partisanship. However, theory is rarely precise enough to specify the temporal dynamics of these relationships. For example, I expect that the party difference in women’s representation should influence men’s and women’s partisanship, but I do not know whether a change in party difference at time t will influence men’s partisanship at time t or influence men’s partisanship at some future time (e.g., t + 1)? This creates a challenge: including too many lags could introduce unnecessary multicollinearity into the model and reduce its efficiency, while including too few lags could mean mischaracterizing the relationship between the dependent and independent variable. For each independent variable, multiple specifications of lag lengths were tested. Lag lengths were determined by balancing three criteria: model parsimony, the Akaike information criteria (AIC), and the Bayesian information criteria (BIC). Among these criteria, model parsimony was privileged.

Results

I begin by estimating the bivariate relationships between partisanship and each independent variable because many of the series are moderately correlated.⁷ After assessing the relationship between the covariates and men’s and women’s partisanship between 1950 and 2012, I analyze these relationships during the periods before the 1980 election and after the 1980 election. It is important to understand how these relationships differ during these respective time periods given the prominence of the 1980 election in the literature on the gender gap and the patterns in Figure 1. I then turn to a multivariate specification of the models, again conducting analyses over the entire time period and before and after 1980.

The tables in this section present the effect of a 1 standard deviation change in the independent variable on men’s and women’s partisanship and the difference of the effects. The full regression results can be found in the online appendix. Given that some variables contain multiple lags, reporting the effects allows us to efficiently assess the total influence a covariate has on the partisan attachments of men and women.

The bivariate results reported in Table 2 indicate that party difference in women’s representation plays an important role in shaping the gender gap in partisanship. Over the entire time period (Panel A), men’s Democratic partisanship significantly declines as more women are elected and compose the Democratic congressional delegation. Party difference has a positive effect on women’s Democratic partisanship but fails to reach traditional levels of statistical significance. More important, though, as Democratic women become a more visible part of the Democratic Party, men and women move in opposite directions, significantly contributing to the gender gap in partisanship (Panel A, Column 3).

Table 2.

Effects on Men’s and Women’s Democratic Partisanship—Bivariate Models.

	Men	Women	Difference
	(90% CI)	(90% CI)	(90% CI)
Panel A: complete time period 1950–2012
Party difference	−0.30*	0.10	−0.40**
Party difference	[−0.58, −0.001]	[−0.19, 0.39]	[−0.13, −0.08]
Southern realignment	0.79**	0.45**	0.34
Southern realignment	[0.41, 1.17]	[0.08, 0.83]	[−0.04, 0.72]
Social spending	0.16	0.12	0.04
Social spending	[−0.05, 0.38]	[−0.01, 0.33]	[−0.09, 0.22]
Women’s workforce participation	0.21**	0.02	0.18
Women’s workforce participation	[0.04, 0.38]	[−0.15, 0.19]	[−0.05, 0.42]
Consumer sentiment	0.20	0.11	0.09
Consumer sentiment	[−0.02, 0.42]	[−0.99, 1.21]	[−1.02, 1.21]
Approval	0.34	0.42*	−0.08
Approval	[−0.04, 0.72]	[0.05, 0.79]	[−0.41, 0.26]
Panel B: 1950–1980
Party difference	0.05	0.38	−0.34
Party difference	[−0.45, 0.55]	[−0.01, 0.79]	[−0.78, 0.10]
Southern realignment	0.70**	0.86**	−0.15
Southern realignment	[0.02, 1.39]	[0.13, 1.57]	[−0.79, 0.49]
Social spending	0.06	0.92**	−0.86**
Social spending	[−0.43, 0.56]	[0.31, 1.07]	[−1.40, −0.31]
Women’s workforce participation	0.31**	−0.13	0.44**
Women’s workforce participation	[0.10, 0.52]	[−0.34, 0.08]	[0.16, 0.73]
Consumer sentiment	0.06	0.20**	−0.14
Consumer sentiment	[−0.03, 0.14]	[0.08, 0.32]	[−0.26, −0.02]
Approval	0.11*	0.10*	0.02
Approval	[0.01, 0.21]	[0.01, 0.18]	[−0.10, 0.15]
Panel C: 1981–2012
Party difference	−0.17	0.22*	0.39**
Party difference	[−0.39, 0.04]	[0.02, 0.42]	[−0.69, −0.10]
Southern realignment	0.72**	0.28*	0.44**
Southern realignment	[0.41, 1.04]	[0.03, 0.52]	[0.14, 0.74]
Social spending	−0.17	−0.26	0.1
Social spending	[−0.62, 0.30]	[−0.54, 0.005]	[−0.34, 0.54]
Women’s workforce participation	0.37**	−0.15	0.52**
Women’s workforce participation	[0.06, 0.66]	[−0.43, 0.13]	[0.10, 0.93]
Consumer sentiment	−0.09**	−0.05	−0.05
Consumer sentiment	[−0.15, −0.04]	[−0.11, 0.02]	[−0.12, 0.01]
Approval	0.005	0.06*	−0.06
Approval	[−0.07, 0.08]	[0.004, 0.12]	[−0.13, 0.02]

Confidence intervals (CIs) were calculated via simulation.

Indicates significance at .90 level with a two-tailed test. **Indicates significance at .95 level with a two-tailed test.

Panel B of Table 2 reports results for men’s and women’s partisanship before 1980. The influence of party difference on women’s representation is positive and statistically insignificant for both men and women during this early time period. Panel C of Table 2 reports effects after 1980. The effect of party difference on men’s partisanship is negative, but statistically insignificant. However, the influence of party difference on women’s partisanship is positive and statistically significant. Moreover, the difference between the effects of party difference on men’s and women’s partisanship is significant. Thus, women’s increasing visibility in the Democratic Party appears to influence both men’s and women’s partisanship. The party difference in representation has slowly caused men to move away from the Democratic Party over several decades. More recently, the increased presence of women in the Democratic congressional delegation has caused women to move toward the Democratic Party. These findings support the theoretical expectation that men and women use the composition of the party-in-government as a cue regarding which party best represents their gendered interests.

Southern realignment shapes both men’s and women’s Democratic partisanship. For the period 1950–2012, men’s and women’s partisanship are significantly related to the changing makeup of the South’s congressional delegation. The difference between these effects for men and women, though, is not statistically significant. An analogous relationship is found before 1980, as both men and women respond to Southern realignment in a similar fashion. After 1980, men’s and women’s partisanship is moving in the same direction due to Southern realignment; however, the effect is considerably smaller for women, making the difference between men and women statistically significant in this time period. The influence of Southern realignment matches the theoretical expectation that groups in the electorate respond to changes in the composition of party elites.

Increases in social spending have a positive effect on both men’s and women’s partisanship between 1950 and 2012, but the effect is not statistically significant. Before the 1980 election, increased social spending contributes to the gender gap even though it is associated with increases in both men’s and women’s Democratic partisanship. This is because social spending has a significantly larger effect on women’s partisanship, contributing to the early formation of the gender gap. After 1980, social spending is not significantly related to men’s partisanship, women’s partisanship, or the gap.

The effects of women’s workforce participation are mixed. Over the entire time period, women’s workforce participation is positive and significantly associated with increased men’s Democratic Party identification. The effect is negative and insignificant for women’s partisanship, and the difference in the effects is not statistically significant. Before 1980, though the effect of women’s workforce participation on Democratic partisanship is positive and significant for men, the difference in effects across sex is significant. Similarly, after 1980, women’s workforce participation has a positive and significant effect on men’s partisanship and a negative but insignificant effect on women’s partisanship. Importantly, the difference in the effects of women’s workforce participation on men’s and women’s partisanship is significant after 1980. Thus, women’s workforce participation contributes to the gender gap and does so largely through its influence on men’s partisanship.

Neither consumer sentiment nor approval appears to influence the gender gap in partisanship. Consumer sentiment is positive and significantly related to women’s partisanship before 1980 (Panel B). However, the difference in its effects across sex is never statistically significant. Approval is positive and significantly related to men’s and women’s partisanship before 1980 and women’s after 1980. The difference in its effects on men’s and women’s partisanship, though, is never statistically significant.

Table 3 reports the effects of a 1 standard deviation increase in the independent variables on men’s and women’s partisanship with the multivariate specifications. Consistent with the bivariate analyses and theoretical expectations, the increased visibility of women as part of the Democratic Party’s congressional delegation has contributed to the gender gap. During the full time period (Table 3, Panel A), men’s Democratic Partisanship is negatively related to increases in the party difference in women’s representation, while women’s Democratic partisanship has a positive and statistically significant relationship with party difference. Before 1980, men’s and women’s partisanship is positively and significantly related to women’s increased presence in the Democratic Party’s congressional delegation, but the effects are very similar. After 1980, the effect of the party difference on men’s partisanship becomes negative and statistically significant. In addition, the effect of the party difference on women’s partisanship is positive and statistically significant. As men’s and women’s partisanship moves in the opposite directions after 1980, the difference in the effects is statistically significant. The increased presence and visibility of women in the Democratic Party, therefore, has contributed to the growth of the gender gap.

Table 3.

The Effects on Men’s and Women’s Democratic Partisanship—Multivariate Models.

	Men	Women	Difference
	(90% CI)	(90% CI)	(90% CI)
Panel A: complete time period 1950–2012
Party difference	−0.06	0.19*	−0.25
Party difference	[−0.23, 0.12]	[0.01, 0.36]	[−0.49, 0.01]
Southern realignment	0.71**	0.47**	0.23
Southern realignment	[0.41, 1.00]	[0.17, 0.77]	[−0.10, 0.59]
Social spending	−0.001	−0.001	−0.10
Social spending	[−0.19, 0.28]	[−0.09, 0.38]	[−0.31, 0.11]
Women’s workforce participation	−0.001	−0.001	−0.001
Women’s workforce participation	[−0.01, 0.004]	[−0.01, 0.01]	[−0.01, 0.01]
Consumer sentiment	0.15	0.21	−0.05
Consumer sentiment	[−0.06, 0.38]	[−0.08, 0.49]	[−0.32, 0.22]
Approval	0.19	−0.04	0.24
Approval	[−0.20, 0.58]	[−0.45, 0.34]	[−0.11, 0.60]
Panel B: 1950–1980
Party difference	0.38*	0.40*	−0.03
Party difference	[0.03, 0.74]	[0.07, 0.74]	[−0.36, 0.32]
Southern realignment	0.68**	1.34**	−0.66**
Southern realignment	[0.27, 1.09]	[0.79, 1.89]	[−1.21, −0.12]
Social spending	−0.22	0.07	−0.29
Social spending	[−0.62, 0.18]	[−0.33, 0.48]	[−0.84, 0.25]
Women’s workforce participation	0.01	0.01	0.003
Women’s workforce participation	[−0.01, 0.03]	[−0.01, 0.03]	[−0.01, 0.02]
Consumer sentiment	−0.05	0.34**	−0.39
Consumer sentiment	[−0.34, 0.25]	[0.06, 0.62]	[−0.83, 0.05]
Approval	0.79**	−0.03	0.82**
Approval	[0.27, 1.30]	[−0.34, 0.27]	[0.21, 1.44]
Panel C: 1981–2012
Party difference	−0.25*	0.24*	−0.49**
Party difference	[−0.47, −0.04]	[0.03, 0.44]	[−0.79, −0.18]
Southern realignment	0.62**	0.16	0.46**
Southern realignment	[0.29, 0.95]	[−0.10, 0.41]	[0.15, 0.79]
Social spending	−0.28*	−0.26	−0.01
Social spending	[−0.55, −0.004]	[−0.54, 0.01]	[−0.27, 0.24]
Women’s workforce participation	0.01	0.004	0.003
Women’s workforce participation	[−0.01, 0.03]	[−0.02, 0.03]	[−0.01, 0.02]
Consumer sentiment	−0.47**	−0.41**	−0.05
Consumer sentiment	[−0.73, −0.21]	[−0.67, −0.15]	[−0.30, 0.18]
Approval	0.14	0.01	0.13
Approval	[−0.20, 0.50]	[−0.25, 0.27]	[−0.20, 0.47]

Confidence intervals (CIs) were calculated via simulation.

Indicates significance at .90 level with a two-tailed test. **Indicates significance at .95 level with a two-tailed test.

The multivariate results provide further evidence that Southern realignment contributed to the formation of the gender gap. In all time periods, men’s and women’s partisanship are positively related to Southern realignment. This implies that both men’s and women’s Democratic partisanship declined as Democrats made up less of the Southern delegation. The effect is statistically significant for all time periods, except for women after 1980. The difference in effects is significant before 1980, with women being more likely to move away from the Democratic Party than men. After 1980, the reduced effects of Southern realignment on women’s partisanship results in the significant difference, with men being more likely to move away from the Democratic Party. Thus, while Southern realignment reduced both men’s and women’s partisanship, it contributes to the gender gap after 1980 through larger effects on men’s partisan attachments.

Social spending and women’s workforce participation have little effect on men’s and women’s partisanship or the gender gap in the multivariate analyses. The effect of social spending is only significant for men’s partisanship after 1980. In addition, none of the differences in the effects of social spending are statistically significant. Similarly, the effects of women’s workforce participation on men’s and women’s partisanship are statistically insignificant in each of the multivariate models. Moreover, none of the differences are statistically significant.

Consumer sentiment does not contribute to the formation of the gender gap. Over the full time period, consumer sentiment is positively related to men’s and women’s partisanship, but none of the effects or the difference in effects are statistically significant. Before 1980, it is negatively related to men’s partisanship and positively and significantly related to women’s partisanship. The difference is not statistically significant. After 1980, consumer sentiment is negatively related to both men’s and women’s partisanship, but, again, the effects and the difference in effects are insignificant.

There is some evidence presidential approval contributes to the gender gap. Across all specifications of the multivariate model, men’s partisanship is positively related to approval and is statistically significant before 1980. Approval is negatively but insignificantly related to women’s Democratic partisanship over the entire time period and before 1980. The difference in the effects of approval on men’s and women’s partisanship is statistically significant prior to 1980. Thus, men’s and women’s differing reactions to presidents contribute to the size of the gender gap before 1980.

Discussion and Conclusion

Examining the dynamics of men’s and women’s partisanship separately between 1950 and 2012 provides us with a better understanding of how, when, and why the gender gap emerged and changes over time. Previous research on the gender gap largely theorized about the gap from the perspective of women’s political behavior and did not take into account changes within the political parties. In contrast, I offer a theory that accounts for shifting partisan attachments of men and women based on changes within the parties. This theoretical framework helps explain how changes in both men’s and women’s partisanship have contributed to the formation and growth of the gender gap over time. My argument also accounts for transformations within the political parties. Changes in the composition of party elites have sent messages to the electorate about whose interests the parties represent. My findings highlight the influence of the composition of party elites on mass party identification and are consistent with the parties signaling interests to groups and groups seeking representation of those interests in the parties. Furthermore, the empirical analyses demonstrate that men’s and women’s behavior contribute to the gender gap. Women’s visibility and presence in the Democratic Party’s congressional delegation, compared with the Republican Party, influences both women’s and men’s partisanship, while Southern realignment mainly influences men’s partisanship. Thus, the gender gap in partisanship is a function of changes in both men’s and women’s partisanship.

The results concerning the sex composition of the congressional delegations suggest initial accounts of the gender gap as a product of the second wave of the women’s movement were on to something. Many second wave social movement organizations started programs to increase women’s representation in government in the wake of the failure to ratify the Equal Rights Amendment and in response to the lack of action by the political parties (Barasko 2004; Pimlott 2010). Initially, these efforts were nonpartisan or bipartisan. However, changes in the relationships among feminism, social conservatism, and the political parties changed the political opportunity structure (Freeman 1986; Wolbrecht 2000). These transformations resulted in the women’s movement disproportionately influencing the election of Democratic women compared with Republican women. Thus, by changing the composition of the party elite, the women’s movement contributed to the formation and growth of the gender gap in partisanship.

The theoretical argument and findings concerning both women’s representation and Southern realignment reinforce the importance of political elites’ influence on mass political behavior (Carsey and Layman 2006; Levendusky 2010; Stimson 2015). I argue that two mechanisms related to descriptive representation send cues to the electorate regarding representation of social identities. First, the electorate uses the visual image of the party elites as a signal about whose social identities are best represented by the political parties. Second, voters use descriptive representation to make inferences about the policy agendas of the parties. Testing these different mechanisms is beyond the scope of this article. Further research is needed to understand better what information the masses receive from the political elite.

There are mixed results concerning the influence of the New Deal (social spending). In the bivariate models, social spending showed a significant relationship between either men’s or women’s partisanship and some contribution to the gender gap. However, these relationships fall below traditional levels of significance in the fully specified models. The results for social spending are somewhat surprising given the prominence of this explanation for the gender gap in the United States (Kaufmann and Petrocik 1999) and cross-nationally (Iversen and Rosenbluth 2010). However, there are multiple reasons why my findings might differ from previous scholarship. First, Kaufmann and Petrocik’s (1999) findings are based on a much shorter time period. Attitudinal differences on social welfare spending largely explain the differences in partisanship and vote choice in 1992, but the salience of this issue accounts for the difference in 1996. Thus, Kaufmann and Petrocik’s (1999) findings may be a product of the particular electoral contexts in 1992 and 1996, and not systemic long-run relationships between social welfare attitudes and partisanship. Second, Kaufmann and Petrocik (1999) examine attitudes toward social welfare spending, not actual social welfare spending. This may be a case where attitudes are not related to actual policy outcomes. Unfortunately, attitudinal measures do not exist on a quarterly basis back to 1950. Third, Kaufmann and Petrocik analyze the behavior of individuals, while my analyses focus on the aggregate.

I find weak support for the influence of women’s workforce participation on the gender gap. While this result does not fit with the theoretical expectation, it does fit with Box-Steffensmeier, De Boef, and Lin’s (2004) finding that women’s involvement in the workforce does not influence the gender gap in partisanship. Perhaps one of the reasons why there is little support at the aggregate level for women’s workforce participation is that aggregate measures do not capture the many ways that women’s involvement in the paid labor force are gendered (Iversen and Rosenbluth 2010). For instance, women are more likely to be concentrated in different occupations than men. These “pink collar” jobs tend to have lower wages and be less stable. Further research is needed to analyze whether and how women’s workforce participation influences women’s and men’s political behavior.

While this paper is largely about differences in men’s and women’s partisan attachments, the similarity in men’s and women’s partisanship is notable. A considerable degree of the movement in men’s and women’s Democratic macropartisanship is shared. This analysis indicates men and women have similar reactions to changes in economic and political evaluations. However, there is some evidence that these relationships might vary across subgroups in the electorate. How sex conditions political and economic evaluations and how these reactions contribute to the gender gap is a topic for future research.

The analysis and theory presented here highlight the importance of gender as a social identity that structures men’s and women’s political behavior. Moreover, the dynamic and persistent nature of changes in men’s and women’s behavior suggest gender will continue to be a major feature of electoral politics. Focusing on gender as a politically relevant social identity does not mean that it is the only relevant social identity. Rather, gender intersects with many social identities, such as race and class, that structure the political attitudes and behavior of the electorate. Furthermore, changes within the parties have important implications for the representation of multiple social identities. Additional research is needed to fully understand how these party dynamics influence representation and macro-party identification.

Footnotes

Acknowledgements

The author would like to thank Suzie Linn, Suzan Welch, Lee Ann Banaszak, Janet Box-Steffensmeier, Jeff Carter, Mike Henderson, Conor Dowling, Jon Winburn, and the members of the Gender and Political Psychology Writing Group for feedback on this project. I also want to thank Brad Dickerson and David Isles for their help with collecting the Gallup data.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Notes

Supplemental Material

Replication data are located at https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/04ZLGN. for this article is available with the manuscript on the PRQ website.

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Supplementary Material

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Who Is Responsible for the Gender Gap? The Dynamics of Men’s and Women’s Democratic Macropartisanship,1950–2012

Abstract

Keywords

The Gender Gap

Sex, Representation, and Party Realignments

Measurement

Explanatory Variables

Model Specification

Results

Discussion and Conclusion

Footnotes

Acknowledgements

Declaration of Conflicting Interests

Funding

Notes

Supplemental Material

References

Supplementary Material