Electoral Institutions and Democratic Legitimacy

Electoral Institutions and Democratic Legitimacy Abstract The Voting Rights Act of 1965 was widely heralded as a solution to persistently high levels of Black political alienation and cynicism. But despite the importance of the Voting Rights Act for the political representation of historically marginalized groups, little is known about how citizens protected by key provisions of the Act viewed democratic institutions. Integrating insights from the policy feedback literature with studies on the relationship between electoral institutions and attitudes toward government, we predict that the voting protections embedded in the Voting Rights Act led to more favorable attitudes toward government among affected communities. Analyses of data from 1972 to 1998 show that Black citizens in jurisdictions covered by Section 5 of the Voting Rights Act, the preclearance provision, exhibited consistently higher levels of trust in government and more positive perceptions of governmental responsiveness. However, we find no evidence that preclearance was associated with similar patterns among whites. Our results may have especially important contemporary relevance given recent controversies over changes to state and local election laws. Legal scholars, historians, political scientists, public officials, and community activists argue that the Voting Rights Act of 1965 (VRA) was among the most important legislative enactments of the twentieth century. According to Issacharoff (2013, p. 95), the Voting Rights Act “was pivotal in bringing black Americans to the broad currents of political life—a transformation that shook the foundations of Jim Crow, triggered the realignment of partisan politics, and set the foundations for the election of an African American president.” The VRA contributed to increased voter registration and turnout among Blacks and linguistic minorities (Tate 1993; Jones-Correa 2005; Fraga 2016) and improved descriptive (e.g., Grofman and Handley 1991; Lien et al. 2007) and substantive (e.g., Whitby and Gilliam 1991; Lublin 1997; Whitby 2000) representation of people of color. In this paper, we study the consequences of the VRA for public opinion. Prior to the VRA, political mistrust, alienation, and cynicism were significantly higher among Blacks than whites (e.g., Aberbach and Walker 1970; Abramson 1983). Black political attitudes, including orientations toward the political system, have been shaped by historical legacies of slavery, the failures of Reconstruction, and Jim Crow (e.g., Dawson 1994), which may explain relatively low perceptions of legitimacy among Blacks a half-century ago.1 Successful efforts by civil rights leaders and activists to secure guaranteed voting rights from the federal government, however, may have significantly reshaped attitudes toward government among members of historically marginalized groups. We offer two main contributions to the study of public opinion and race. First, while existing research devotes significant attention to how descriptive relationship affects political attitudes among racial minority groups (e.g., Gay 2002; Marschall and Shah 2007), we focus on how attitudes toward government are shaped by perceptions of democratic legitimacy. Just as trust in government is shaped by electoral (e.g., Rahn and Rudolph 2005) and governing institutions (e.g., Marschall and Shah 2007), political inclusion is an important determinant of how citizens feel about their government. Second, we integrate insights from research on policy feedback (see, e.g., Soss 1999; Campbell 2003; Weaver and Lerman 2010; Erikson and Stoker 2011) with the study of electoral institutions. Our argument predicts that individuals affected by the provisions of the VRA developed more favorable attitudes toward government because of the opportunities it provided for political inclusion. We test our argument in the context of the preclearance requirement outlined in Section 5 of the VRA. This provision prohibited certain jurisdictions from changing election laws without federal approval and provided security for the voting rights of historically marginalized groups living in those areas. Data from the American National Election Studies conducted from 1972 to 1998 show that Black citizens living in counties subject to federal preclearance reported significantly higher levels of trust in government, evaluations of government responsiveness, and approval of political institutions. These results are robust to a number of model specifications and empirical strategies. Moreover, we find no discernible evidence that preclearance had an effect on white political attitudes. Our findings have important implications for how democratization and electoral institutions affect attitudes toward the state. Electoral Institutions, Political Representation, and Attitudes toward Government The maintenance of democratic political institutions requires both diffuse and specific support. Diffuse support characterizes the public’s respect for and recognition of the political authority vested in institutions, while specific support refers to the public’s evaluations of incumbent political authorities (Easton 1975). These two dimensions of support make it possible for citizens to be personally upset by, for instance, the behavior of incumbent legislators (specific support) but still respect the authority of Congress to make the nation’s laws (diffuse support). Diffuse support thus helps maintain political institutions even in the face of dissatisfaction with particular political officials. Earlier scholarship has found that feelings of political alienation and alienation are associated with lower levels of support both for incumbent officeholders as well as the system as a whole (Citrin et al. 1975). We argue that the protection of voting rights in democracies affects citizens’ attitudes toward government. As Levi (1998, p. 90) argued, “The belief in government fairness requires the perception that all relevant interests have been considered, that the game is not rigged.” Electoral institutions play a key role in structuring beliefs in fairness and the representation of interests. By prescribing the “rules of the game,” electoral institutions affect citizens’ ability to participate in politics, influence election outcomes, and affect government policymaking. When electoral institutions and the outcomes they generate are perceived as biased, the public is likely to express greater disapproval of both the officeholders and the government system more generally.2 Our argument posits a feedback loop that links citizens’ political inclusion to their attitudes toward government. Just as participation in social welfare programs (e.g., Soss 1999), the criminal justice system (e.g., Weaver and Lerman 2010), and the Vietnam draft (e.g., Erikson and Stoker 2011) affects political attitudes and behaviors, citizens are likely to view government as legitimate to the extent they can influence it. Policies that expand or restrict voting access shape the ability of citizens to express political voice, and with them citizens’ affective orientations toward government. This argument builds upon several strands of related research. For instance, local districting and electoral institutions have been shown to affect government trust among historically marginalized groups (e.g., Rahn and Rudolph 2005), largely because these institutions shape the opportunities for residents to meaningfully effect political change in their communities. Research in comparative politics finds that government trust in post-communist nations was higher in societies that protected individual liberties (Mishler and Rose 1997, 2001), while other kinds of political institutions, including the nature of party (Miller and Listhaug 1990) and electoral systems (Banducci, Donovan, and Karp 1999), are also associated with government evaluations. Similarly, electoral fraud and corruption, which may reduce citizens’ perceptions that they can influence the political system, are associated with decreased levels of trust in government (e.g., McCann and Dominguez 1998). Across these diverse literatures, electoral and political institutions affect citizens’ evaluations of government based on how these institutions create opportunities for political inclusion and representation. When electoral institutions are changed, as in the case of the VRA, individuals can update their attitudes about government based on their own political inclusion. Thus, when election policies change, an individual’s evaluations toward government are more positive (negative) if the policies provide that person with enhanced (reduced) political inclusion, and remain stable if the policies have no implications for her level of political inclusion. This expectation contrasts with a sociotropic perspective rooted in core values such as equality or egalitarianism (e.g., Feldman 1988). The sociotropic perspective suggests that individual attitudes toward government respond to changes to electoral institutions based on whether the policy changes expand or reduce political inclusion generally, irrespective of the specific implications for the individual’s political inclusion. Electoral Institutions and the Voting Rights Act Prior to the VRA, electoral institutions including poll taxes and literacy tests limited opportunities for political participation among Blacks and language minorities (Davidson 1992). For instance, only about a quarter of eligible Blacks registered to vote in the middle of the twentieth century (Garrow 1978). Civil rights leaders focused their attention on voting rights during the early 1960s and pressed the Kennedy and Johnson administrations to guarantee voting rights to all eligible Americans. By prohibiting electoral institutions—formal or informal—that produced racial disparities in ballot access, civil rights leaders argued that the VRA would provide greater political power to Blacks (and language-minority groups, with the 1975 amendments). The elimination of restrictive electoral provisions was therefore expected to improve representation for Blacks and other historically marginalized groups and generate more positive evaluations of government. Several of the VRA’s provisions specifically address ballot access and electoral rules. Legal scholars argue that the combination of Section 4(b) and Section 5 is its critical component (MacCoon 1979; Motomura 1983). Section 5 requires certain jurisdictions with a history of voter disenfranchisement to receive federal approval before changing election laws or voting procedures, and Section 4(b) identifies these jurisdictions. The coverage formula specified in Section 4(b) originally identified jurisdictions that used a test or device in the November 1964 presidential election, and in which less than half of the jurisdiction’s eligible citizens were registered or voted in the November 1964 election.3 Thus, while the VRA guaranteed ballot access to all citizens nationwide, it offered the strongest protections to residents of communities that were subject to preclearance. An important body of research credits the VRA with increasing Black voter registration and turnout (Tate 1993) and improving Black descriptive and substantive political representation (Schuit and Rogowski 2017).4 Scholars have devoted less attention to studying how the VRA may have affected how citizens evaluated government. According to our argument, the electoral protections in the VRA should increase Black citizens’ evaluations of political institutions, elected officials, and government more generally by enhancing Blacks’ perceptions of representation and political inclusion. In earlier work, Abramson (1983) finds that Black citizens typically exhibited lower levels of trust in government than whites, and that the size and direction of the gap varied with the federal government’s efforts to ensure racial equality, but does not focus specifically on the VRA. Previous research on the attitudinal consequences of the VRA has instead focused mostly on the effects of Section 2(b), which prohibits minority vote dilution when drawing electoral districts and led to the creation of majority-minority districts and increased descriptive representation. However, scholars have found limited effects of descriptive representation on attitudes toward government. In one of the most important studies on this topic, Gay (2002) finds little evidence that trust in government or perceptions of Congress among Blacks are affected by descriptive representation.5 To the extent the VRA affected attitudes toward government, therefore, it seems unlikely to have done so through Section 2(b). In contrast, our argument predicts that Sections 4(b) and 5 are more likely to have implications for Black political attitudes. Moreover, these provisions may have affected perceptions of political inclusion apart from citizens’ knowledge about the particulars of the electoral institutions used in their local communities. Local organizations and entrepreneurial candidates used the provisions of the VRA to galvanize and mobilize local Black communities in the aftermath of its passage,6 and activities such as these could have raised visibility about federal electoral protections. Contemporary debates over voting access often focus on whether such provisions have disproportionate effects across groups, particularly among racial and ethnic lines, and underscore the importance of documenting the effects of the VRA. Research on voter identification requirements, however, finds that these laws have little effect on citizens’ perceptions of vote fraud (Ansolabehere and Persily 2008), and raises questions about whether restrictions such as these affect other dimensions of public opinion. Thus, understanding how voting protections influence Black attitudes toward government may also provide important insight into the potential effects of contemporary electoral reforms. Data and Methods We study the effects of the VRA on attitudes toward government using the American National Election Studies from 1972 to 1998. We use this time span because federal preclearance under Section 4(b) of the VRA was generally applied at the county level and the county indicators in the ANES are restricted after 1998.7 Our primary analyses focus specifically on Black respondents and in the comparison between Black and white respondents. Unfortunately, very small sample sizes for other minority groups in many of these surveys preclude comparison. In addition, small samples of Black respondents in earlier versions of the ANES limit our ability to include respondents from those years in our analyses. Although this is an obvious limitation of our ability to identify baseline attitudes among Blacks prior to the Act’s passage in 1965, it does not diminish the importance of the analyses. As our discussion above highlighted, Black citizens living in jurisdictions identified by Section 4(b) had greater federal protection against discriminatory election laws because those jurisdictions were required to receive federal preclearance before modifying their electoral laws or voting procedures. An ideal scenario would randomly assign individuals to geographic locations that were or were not covered by the preclearance provisions. However, the coverage formula in Section 4(b) was not randomly assigned to jurisdictions across the country; in fact, the government argued in South Carolina v. Katzenbach and Shelby v. Holder that Congress had reverse-engineered the coverage formula to identify areas with “reliable evidence” of voting discrimination. Thus, we compared individuals’ attitudes based on whether they lived in a jurisdiction that was subject to the preclearance requirement. Based on the geographic information provided about respondents’ locations in the ANES, we identified whether respondents lived in a county that was subject to the preclearance requirement. Counties constituted the vast majority of jurisdictions subject to preclearance, and we suspect our empirical approach represents a conservative strategy for reasons we detail below. All else equal, Black respondents living in counties subject to preclearance should express more positive attitudes toward government than Black respondents living in jurisdictions that were not subject to preclearance.8 We do not expect to observe differences in attitudes toward government on the basis of preclearance among whites, who were generally not subject to the patterns of disenfranchisement in jurisdictions covered by Section 5. While observational research designs like this confront unavoidable challenges due to endogeneity, this concern weighs against finding a positive relationship between preclearance and attitudes toward government. If the coverage formula was applied to the jurisdictions with the most egregious histories of voter discrimination, residents of those jurisdictions should have the most negative attitudes toward government. When comparing attitudes among respondents who live in covered and noncovered jurisdictions, then, we would find a negative relationship between coverage and evaluations of government. It is considerably more difficult to envision a scenario in which endogeneity would explain a positive relationship between coverage and government attitudes, and thus the results that follow may underestimate the effect of preclearance. Our key independent variable, VRA Coverage, is an indicator for whether the ANES respondent lived in a county that was covered by the preclearance requirement as a result of the original Voting Rights Act of 1965 or any of its later amendments, or on the basis of whether it was covered under the bail-in provision.9 In the absence of random assignment, we rely on two key sources of variation to identify the effect of the VRA. Though the coverage formula specified in Section 4(b) identified jurisdictions that were subject to preclearance, this list of covered jurisdictions has changed over the years due to the “bail-in” and “bail-out” provisions. The bail-in provision is specified in Section 3(c) and allows federal courts to subject jurisdictions that fall outside the coverage formula in Section 4(b) to the preclearance requirement if the jurisdiction has enacted voting laws that are racially discriminatory.10 The bail-out provision in Section 4(a) allowed jurisdictions to seek exemption from preclearance if they had not used a voting test or device with discriminatory intent and by showing registration and turnout rates among majority and minority citizens.11 These provisions produced temporal variation in the counties subject to preclearance. Though we report results for a variety of dependent variables, we begin our analyses using the ANES measure of trust in government. Our measure of trust is government is based on the traditional question “How much of the time do you think you can trust the government in Washington to do what is right?” Over the past forty years, the question has generally been asked on a three-point scale that ranges from “some of the time” (1) to “just about always” (3), though some respondents volunteered that they trust government “none of the time.” To facilitate interpretation, we code trust in government dichotomously, where responses of trusting government “most of the time” or “just about always” are coded 1, and other responses are coded zero. The trust in government questions were “designed to tap the basic evaluative orientations toward the national government” (Stokes 1962, p. 64). The more trustworthy citizens perceive government to be, the more likely they are to comply with and consent to its demands and regulations (Tyler 1990). Greater trust benefits elected officials and political institutions by “provid[ing] leaders more leeway to govern effectively and institutions a larger store of support regardless of the performance of those running the government” (Hetherington 1998, p. 803). Figure 1 below compares the level of trust in government among Black respondents who did (solid line) and did not (dotted line) live in areas that were subject to the preclearance provision. With only two exceptions (1984 and 1998), trust in government was higher among Black respondents who lived in areas subject to federal preclearance. Moreover, aggregating over the entire time period, Black respondents living in preclearance jurisdictions reported significantly higher levels of trust than Blacks who did not (difference = .09; p < .01). These raw data provide preliminary support for the hypothesis that the VRA influenced perceptions of democratic legitimacy. Figure 1. View largeDownload slide The Voting Rights Act, federal preclearance, and trust in government, 1972–1998. Black respondents only, American National Election Studies. Plot shows the percentages of Black respondents who indicated they trusted the government to do what was right “most of the time” or “just about always.” The size of the points is proportional to sample size. Figure 1. View largeDownload slide The Voting Rights Act, federal preclearance, and trust in government, 1972–1998. Black respondents only, American National Election Studies. Plot shows the percentages of Black respondents who indicated they trusted the government to do what was right “most of the time” or “just about always.” The size of the points is proportional to sample size. Statistical Models To examine the effect of the preclearance requirement on attitudes toward government, we estimate a series of logistic regressions. The unit of analysis is an individual survey respondent i living in county j in year t, and the main dependent variable is the Trust in government measure described above.12 Generally speaking, our statistical model takes the form  Pr(yijt=1)=logit−1[β0+β1VRA Coveragejt+β2 Blacki+β3(VRA Coveragejt×Blacki)+XijtΩ+Dt+εijt], (1) where yi is respondent i’s degree of trust in government; VRA Coverage is an indicator for whether respondent i’s county j was subject to the preclearance provision under the VRA in year t; Black indicates whether the survey respondent identified as Black or African American; X is a matrix of potential confounding variables that may also be associated with trust in government, which are described below, and with the corresponding coefficient estimates contained in Ω; Dt indicates the year of survey administration to account for any year-specific differences in government trust; and β0 and εijt are constant and error terms, respectively. All data in the analyses are weighted to national population parameters and standard errors are clustered on county-years. Equation (1) allows us to evaluate our main hypothesis in two complementary ways. Primarily, a positive coefficient for the interaction term (β3) between VRA Coverage and Black would indicate that the preclearance provision of the VRA contributed to higher levels of trust in government among Black respondents. This specification also allows us to conduct a placebo test by comparing the effects of VRA Coverage between Black and white respondents. Given that the preclearance provision was targeted specifically to communities that had historically low levels of registration and turnout among people of color, we do not expect an association between preclearance and attitudes toward government among white respondents. Thus, the coefficient estimate (β1) for VRA Coverage should be close to zero, which would indicate that the preclearance provision had little effect among white respondents, while positive and statistically significant results for the interaction term would provide evidence that preclearance affected attitudes primarily among Blacks. However, our conclusions remain unchanged if our models include only respondents who identify as Black or African American (see the Supplementary Materials). We consider two sources of potential confounders: individual-level characteristics that may be associated with trust in government (e.g., education level, an indicator for female respondents, and age), and county-level covariates that were likely correlated with whether a particular county was subject to preclearance (two variables based on the 1964 presidential election: Democratic vote share13 and turnout14). We also accounted for the percentage of the county nonwhite and urban populations.15 Each measurement was taken prior to passage of the 1965 VRA. Finally, we include an indicator for counties located in the South as defined by the Census.16 We point out that the model excludes several individual and contextual characteristics that are identified by previous literature as potential predictors of trust, including partisanship, whether an individual reported being mobilized, level of political interest, and whether Black respondents are represented by a coracial legislator. Each of these characteristics was likely affected by the VRA, and including these variables in our models could introduce unknown degrees of post-treatment bias (though the results with these characteristics are reported in the Supplementary Materials). Results Table 1 displays estimates of the relationship between federal preclearance and trust in government. The first column reports coefficients from a simple model in which Trust in government is regressed on VRA Coverage, Black, its interaction, and the year-specific indicators. The model reported in column (2) accounts for education, sex, and age, and column (3) reports results when the county-level variables are included. Table 1. Logistic regressions predicting trust in government   Model 1  Model 2  Model 3  coef.  (s.e.)  coef.  (s.e.)  coef.  (s.e.)  Intercept  0.22*  (0.10)  0.17  (0.09)  0.11  (0.09)  Black  -0.59*  (0.07)  -0.58*  (0.07)  -0.57*  (0.07)  VRA coverage  0.02  (0.05)  0.01  (0.05)  0.02  (0.06)  Black x VRA coverage  0.48*  (0.12)  0.51*  (0.12)  0.52*  (0.12)  Education      0.07*  (0.02)  0.07*  (0.02)  Female      -0.02  (0.03)  -0.02  (0.03)  Age      -0.02*  (0.01)  -0.02*  (0.01)  Democratic vote share, 1964          0.13  (0.17)  Democratic vote share, 1964 (squared)          0.11  (0.45)  Voter turnout, 1964          0.11  (0.25)  Nonwhite population, 1960          -0.46  (0.24)  Urban population, 1960          0.00  (0.06)  South          0.15*  (0.05)  N  21,777  21,777  21,777  Clusters  1,477  1,477  1,477  Log-likelihood  -14,184.89  -14,168.45  -14,161.04  χ2  673.31*  692.87*  724.13*  Change in Pr(yijt = 1)  0.10*  (0.02)  0.11*  (0.02)  0.11*  (0.03)    Model 1  Model 2  Model 3  coef.  (s.e.)  coef.  (s.e.)  coef.  (s.e.)  Intercept  0.22*  (0.10)  0.17  (0.09)  0.11  (0.09)  Black  -0.59*  (0.07)  -0.58*  (0.07)  -0.57*  (0.07)  VRA coverage  0.02  (0.05)  0.01  (0.05)  0.02  (0.06)  Black x VRA coverage  0.48*  (0.12)  0.51*  (0.12)  0.52*  (0.12)  Education      0.07*  (0.02)  0.07*  (0.02)  Female      -0.02  (0.03)  -0.02  (0.03)  Age      -0.02*  (0.01)  -0.02*  (0.01)  Democratic vote share, 1964          0.13  (0.17)  Democratic vote share, 1964 (squared)          0.11  (0.45)  Voter turnout, 1964          0.11  (0.25)  Nonwhite population, 1960          -0.46  (0.24)  Urban population, 1960          0.00  (0.06)  South          0.15*  (0.05)  N  21,777  21,777  21,777  Clusters  1,477  1,477  1,477  Log-likelihood  -14,184.89  -14,168.45  -14,161.04  χ2  673.31*  692.87*  724.13*  Change in Pr(yijt = 1)  0.10*  (0.02)  0.11*  (0.02)  0.11*  (0.03)  Source.—American National Election Studies, 1972–1998. Entries are logistic regression coefficients with standard errors in parentheses, clustered on county-year. The dependent variable is measured by responses to the question “How much of the time do you think you can trust the government in Washington to do what is right?,” where responses of “most of the time” and “just about always” are coded 1 and other responses are coded 0. Indicators for year are also included but not reported. *p < .05 (two-tailed tests). View Large Table 1. Logistic regressions predicting trust in government   Model 1  Model 2  Model 3  coef.  (s.e.)  coef.  (s.e.)  coef.  (s.e.)  Intercept  0.22*  (0.10)  0.17  (0.09)  0.11  (0.09)  Black  -0.59*  (0.07)  -0.58*  (0.07)  -0.57*  (0.07)  VRA coverage  0.02  (0.05)  0.01  (0.05)  0.02  (0.06)  Black x VRA coverage  0.48*  (0.12)  0.51*  (0.12)  0.52*  (0.12)  Education      0.07*  (0.02)  0.07*  (0.02)  Female      -0.02  (0.03)  -0.02  (0.03)  Age      -0.02*  (0.01)  -0.02*  (0.01)  Democratic vote share, 1964          0.13  (0.17)  Democratic vote share, 1964 (squared)          0.11  (0.45)  Voter turnout, 1964          0.11  (0.25)  Nonwhite population, 1960          -0.46  (0.24)  Urban population, 1960          0.00  (0.06)  South          0.15*  (0.05)  N  21,777  21,777  21,777  Clusters  1,477  1,477  1,477  Log-likelihood  -14,184.89  -14,168.45  -14,161.04  χ2  673.31*  692.87*  724.13*  Change in Pr(yijt = 1)  0.10*  (0.02)  0.11*  (0.02)  0.11*  (0.03)    Model 1  Model 2  Model 3  coef.  (s.e.)  coef.  (s.e.)  coef.  (s.e.)  Intercept  0.22*  (0.10)  0.17  (0.09)  0.11  (0.09)  Black  -0.59*  (0.07)  -0.58*  (0.07)  -0.57*  (0.07)  VRA coverage  0.02  (0.05)  0.01  (0.05)  0.02  (0.06)  Black x VRA coverage  0.48*  (0.12)  0.51*  (0.12)  0.52*  (0.12)  Education      0.07*  (0.02)  0.07*  (0.02)  Female      -0.02  (0.03)  -0.02  (0.03)  Age      -0.02*  (0.01)  -0.02*  (0.01)  Democratic vote share, 1964          0.13  (0.17)  Democratic vote share, 1964 (squared)          0.11  (0.45)  Voter turnout, 1964          0.11  (0.25)  Nonwhite population, 1960          -0.46  (0.24)  Urban population, 1960          0.00  (0.06)  South          0.15*  (0.05)  N  21,777  21,777  21,777  Clusters  1,477  1,477  1,477  Log-likelihood  -14,184.89  -14,168.45  -14,161.04  χ2  673.31*  692.87*  724.13*  Change in Pr(yijt = 1)  0.10*  (0.02)  0.11*  (0.02)  0.11*  (0.03)  Source.—American National Election Studies, 1972–1998. Entries are logistic regression coefficients with standard errors in parentheses, clustered on county-year. The dependent variable is measured by responses to the question “How much of the time do you think you can trust the government in Washington to do what is right?,” where responses of “most of the time” and “just about always” are coded 1 and other responses are coded 0. Indicators for year are also included but not reported. *p < .05 (two-tailed tests). View Large The results are quite consistent across each model. The coefficients for VRA Coverage are very small in magnitude and not statistically distinguishable from zero, providing no evidence of an association between preclearance and trust in government among whites. The coefficients for Black are negative and statistically significant, indicating that Black respondents who lived in areas not subject to preclearance reported significantly lower levels of trust relative to whites. More importantly, the coefficients for the interaction between VRA Coverage and Black were consistently positive and statistically significant, indicating that federal preclearance significantly increased trust in government among Black respondents. The magnitudes of the coefficients for the interaction term, moreover, are nearly identical to those for Black. This finding indicates that while there was a significant Black-white gap in trust in jurisdictions not covered by preclearance, there was no such gap in preclearance counties. The bottom panel of Table 1 reports the substantive magnitudes of VRA Coverage on trust. The row labeled Change in Pr(yijt =1) displays the increase in the predicted probability of reporting trust in government among Black respondents living in counties subject to preclearance. These estimates were generated by holding constant the values of all other covariates and comparing the predicted probability of reporting trust in government among respondents who were and were not living in areas covered by the preclearance provision. The entries in parentheses report the standard errors associated with these increased probabilities. Across the three models, VRA Coverage is associated with a significant increase—between 10 and 11 percentage points—in the probability of trusting government among Black constituents. We find some evidence of an association between trust in government and our control variables. Respondents with higher levels of education reported greater trust, while trust decreased with age. Women were less likely to report trust in government, but this relationship is not statistically significant. Respondents living in counties with higher nonwhite populations in 1960 were less likely to report trust in government, while individuals in the South reported higher trust in government. The coefficients are not statistically significant for 1964 Democratic presidential vote share or its quadratic, 1964 voter turnout, or urban percentage of the 1960 population. These results are robust across a range of additional supplementary analyses. While jurisdictions subject to federal preclearance were distributed across the nation, they were disproportionately concentrated in the South. Thus, we reestimated our models when limiting our analyses to respondents living in Southern states. As mentioned above, we also estimated models that accounted for other potential confounding variables that were likely also affected by the VRA, including mobilization, party identification, political interest, and representation by a Black legislator. In addition, models were estimated that included as covariates income (which is missing for several thousand respondents and thus omitted from the models above) and respondents’ perceptions of racial discrimination (measures that are available for only four of the ANES years under study17). We also estimated models that allowed the coefficients for the individual-level covariates to vary across Black and white respondents. Moreover, rather than including our county-level variables as controls, they were used as instruments for federal preclearance in an instrumental variables framework. Finally, we used genetic matching (Diamond and Sekhon 2013) to address concerns about common support and identified counties that were not subject to preclearance but were otherwise similar to counties that were subject to preclearance on the basis of the county-level variables described above and whether counties were located in the South. After preprocessing the data, we reestimated the models shown above. Across all these additional analyses, the evidence supports our results in Table 1.18 In addition, though a full examination is beyond the scope of this paper, we note that our argument does not apply solely to Black Americans. Indeed, the VRA extended protections to other historically marginalized groups, including language minorities. The Supplementary Materials show that these results extend to nonwhites in general and Latino/as in particular. We are reluctant to overinterpret these results because the samples of Latino/as are quite small, particularly prior to the mid-1980s. However, this preliminary analysis provides evidence that the VRA increased trust in government among members of other protected groups living in jurisdictions subject to the preclearance provision. Evaluations of Government Responsiveness We explore the robustness of our results above by examining the relationship between VRA preclearance and several other system-level evaluations of government. Specifically, if preclearance helped secure perceptions of political inclusion, the guarantee of voting rights should have feedback effects on how individuals perceive American elections. We study how respondents evaluate the relationship between elections and government responsiveness, and expect that Black respondents living in preclearance jurisdictions would have more positive assessments of the capacity for elections to produce political change, as civil rights leaders hoped. We evaluate three additional indicators found in the ANES. The first, Government, is measured using respondents’ answers to the question “How much attention do you feel the government pays to what the people think when it decides what to do?” The second indicator, Elections, links elections to government performance by gauging respondents’ answers to the question “How much do you feel that having elections makes the government pay attention to what the people think?” The third indicator, Legislators, reports responses to the question “How much attention do you think most Congressmen pay to the people who elect them when they decide what to do in Congress?”19 Each question addresses some dimension of respondents’ assessments that the country’s electoral system helps provide effective representation. Responses to these questions were used to create the dependent variables, which were coded 1 if respondents answered “a good deal” and 0 if respondents answered “some” or “not much.”20 Logit models were estimated with these dependent variables and the same independent variables used in the full model in table 1. As shown in table 2, the patterns are consistent with the results in table 1. Across the three dependent variables, the preclearance provision significantly increased perceptions of responsiveness among Black respondents. As the bottom row of the table indicates, the magnitude of these relationships was between seven and 12 percentage points. Again, no systematic evidence exists that preclearance was associated with heightened perceptions of responsiveness among whites. Interestingly, the results do indicate that Black respondents living in preclearance areas had substantially more positive assessments of electoral institutions than white respondents, whether or not they lived in preclearance jurisdictions. Table 2. Logistic regressions predicting evaluations of government responsiveness   Government  Elections  Legislators  coef.  (s.e.)  coef.  (s.e.)  coef.  (s.e.)  Intercept  -2.43*  (0.13)  -0.41*  (0.10)  -1.78*  (0.16)  Black  0.03  (0.10)  -0.06  (0.08)  -0.17  (0.13)  VRA coverage  0.10  (0.09)  0.08  (0.08)  0.07  (0.10)  Black x VRA coverage  0.51*  (0.15)  0.40*  (0.13)  0.38#  (0.23)  Education  0.23*  (0.03)  0.19*  (0.02)  0.25*  (0.03)  Female  -0.30*  (0.05)  -0.11*  (0.03)  -0.18*  (0.06)  Age  0.09*  (0.01)  0.06*  (0.01)  0.06*  (0.02)  Democratic vote share, 1964  0.00  (0.26)  0.15  (0.21)  0.48  (0.37)  Democratic vote share, 1964 (squared)  0.02  (0.65)  0.44  (0.53)  0.59  (0.83)  Voter turnout, 1964  0.16  (0.37)  0.19  (0.30)  0.24  (0.39)  Nonwhite population, 1960  -0.31  (0.30)  -0.36  (0.30)  -0.31  (0.39)  Urban population, 1960  0.21*  (0.08)  0.07  (0.06)  0.01  (0.11)  South  0.18*  (0.08)  0.03  (0.07)  0.14  (0.09)  N  16,838  15,679  7,952  Clusters  1,134  1,035  486  Log-likelihood  -6,960.32  -11,520.30  -4,617.52  χ2  271.70*  292.47*  138.65*  Change in Pr(yijt = 1)  0.08*  (0.02)  0.12*  (0.03)  0.07#  (0.04)    Government  Elections  Legislators  coef.  (s.e.)  coef.  (s.e.)  coef.  (s.e.)  Intercept  -2.43*  (0.13)  -0.41*  (0.10)  -1.78*  (0.16)  Black  0.03  (0.10)  -0.06  (0.08)  -0.17  (0.13)  VRA coverage  0.10  (0.09)  0.08  (0.08)  0.07  (0.10)  Black x VRA coverage  0.51*  (0.15)  0.40*  (0.13)  0.38#  (0.23)  Education  0.23*  (0.03)  0.19*  (0.02)  0.25*  (0.03)  Female  -0.30*  (0.05)  -0.11*  (0.03)  -0.18*  (0.06)  Age  0.09*  (0.01)  0.06*  (0.01)  0.06*  (0.02)  Democratic vote share, 1964  0.00  (0.26)  0.15  (0.21)  0.48  (0.37)  Democratic vote share, 1964 (squared)  0.02  (0.65)  0.44  (0.53)  0.59  (0.83)  Voter turnout, 1964  0.16  (0.37)  0.19  (0.30)  0.24  (0.39)  Nonwhite population, 1960  -0.31  (0.30)  -0.36  (0.30)  -0.31  (0.39)  Urban population, 1960  0.21*  (0.08)  0.07  (0.06)  0.01  (0.11)  South  0.18*  (0.08)  0.03  (0.07)  0.14  (0.09)  N  16,838  15,679  7,952  Clusters  1,134  1,035  486  Log-likelihood  -6,960.32  -11,520.30  -4,617.52  χ2  271.70*  292.47*  138.65*  Change in Pr(yijt = 1)  0.08*  (0.02)  0.12*  (0.03)  0.07#  (0.04)  Source.—American National Election Studies, 1972–1998. Entries are logistic regression coefficients with standard errors in parentheses, clustered on county-year. The dependent variable is measured by responses to the question “How much of the time do you think you can trust the government in Washington to do what is right?,” where responses of “most of the time” and “just about always” are coded 1 and other responses are coded 0. Indicators for year are also included but not reported. #p < .10; *p < .05 (two-tailed tests). View Large Table 2. Logistic regressions predicting evaluations of government responsiveness   Government  Elections  Legislators  coef.  (s.e.)  coef.  (s.e.)  coef.  (s.e.)  Intercept  -2.43*  (0.13)  -0.41*  (0.10)  -1.78*  (0.16)  Black  0.03  (0.10)  -0.06  (0.08)  -0.17  (0.13)  VRA coverage  0.10  (0.09)  0.08  (0.08)  0.07  (0.10)  Black x VRA coverage  0.51*  (0.15)  0.40*  (0.13)  0.38#  (0.23)  Education  0.23*  (0.03)  0.19*  (0.02)  0.25*  (0.03)  Female  -0.30*  (0.05)  -0.11*  (0.03)  -0.18*  (0.06)  Age  0.09*  (0.01)  0.06*  (0.01)  0.06*  (0.02)  Democratic vote share, 1964  0.00  (0.26)  0.15  (0.21)  0.48  (0.37)  Democratic vote share, 1964 (squared)  0.02  (0.65)  0.44  (0.53)  0.59  (0.83)  Voter turnout, 1964  0.16  (0.37)  0.19  (0.30)  0.24  (0.39)  Nonwhite population, 1960  -0.31  (0.30)  -0.36  (0.30)  -0.31  (0.39)  Urban population, 1960  0.21*  (0.08)  0.07  (0.06)  0.01  (0.11)  South  0.18*  (0.08)  0.03  (0.07)  0.14  (0.09)  N  16,838  15,679  7,952  Clusters  1,134  1,035  486  Log-likelihood  -6,960.32  -11,520.30  -4,617.52  χ2  271.70*  292.47*  138.65*  Change in Pr(yijt = 1)  0.08*  (0.02)  0.12*  (0.03)  0.07#  (0.04)    Government  Elections  Legislators  coef.  (s.e.)  coef.  (s.e.)  coef.  (s.e.)  Intercept  -2.43*  (0.13)  -0.41*  (0.10)  -1.78*  (0.16)  Black  0.03  (0.10)  -0.06  (0.08)  -0.17  (0.13)  VRA coverage  0.10  (0.09)  0.08  (0.08)  0.07  (0.10)  Black x VRA coverage  0.51*  (0.15)  0.40*  (0.13)  0.38#  (0.23)  Education  0.23*  (0.03)  0.19*  (0.02)  0.25*  (0.03)  Female  -0.30*  (0.05)  -0.11*  (0.03)  -0.18*  (0.06)  Age  0.09*  (0.01)  0.06*  (0.01)  0.06*  (0.02)  Democratic vote share, 1964  0.00  (0.26)  0.15  (0.21)  0.48  (0.37)  Democratic vote share, 1964 (squared)  0.02  (0.65)  0.44  (0.53)  0.59  (0.83)  Voter turnout, 1964  0.16  (0.37)  0.19  (0.30)  0.24  (0.39)  Nonwhite population, 1960  -0.31  (0.30)  -0.36  (0.30)  -0.31  (0.39)  Urban population, 1960  0.21*  (0.08)  0.07  (0.06)  0.01  (0.11)  South  0.18*  (0.08)  0.03  (0.07)  0.14  (0.09)  N  16,838  15,679  7,952  Clusters  1,134  1,035  486  Log-likelihood  -6,960.32  -11,520.30  -4,617.52  χ2  271.70*  292.47*  138.65*  Change in Pr(yijt = 1)  0.08*  (0.02)  0.12*  (0.03)  0.07#  (0.04)  Source.—American National Election Studies, 1972–1998. Entries are logistic regression coefficients with standard errors in parentheses, clustered on county-year. The dependent variable is measured by responses to the question “How much of the time do you think you can trust the government in Washington to do what is right?,” where responses of “most of the time” and “just about always” are coded 1 and other responses are coded 0. Indicators for year are also included but not reported. #p < .10; *p < .05 (two-tailed tests). View Large The results shown in table 2 suggest that the VRA helped create more positive evaluations of government among Black citizens by guaranteeing the right to vote in places where such guarantees had been largely absent. The results further implicate the role of elections specifically as a mechanism through which citizens can influence government. By ensuring ballot access, the VRA generated more favorable perceptions of democratic legitimacy among traditionally marginalized groups. Perceptions of Political Inclusiveness As noted earlier, federal preclearance may have increased citizens’ feelings of political inclusion by guaranteeing voting access. We study this potential mechanism using responses to the question “Would you say the government is pretty much run by a few big interests looking out for themselves (coded 0) or that it is run for the benefit of all the people (coded 1)?” Though the question wording may not be ideal for testing perceptions of political inclusion, it does tap into respondents’ perceptions of whether government serves the mass public, including themselves. If the VRA helped create the perception of increased political inclusion, Black respondents living in areas subject to preclearance should be more likely than other Black respondents to believe that government is run for the benefit of all people. The results are shown below in table 3. The coefficient for the interaction between VRA Coverage and Black is again positive and statistically significant, indicating that Black respondents living in areas subject to federal clearance were more likely to report feeling that government is responsive to all people compared with Black respondents living in areas that were not covered by preclearance. The constituent term for VRA Coverage is not statistically significant and provides no evidence of a similar relationship among whites. The bottom panel of the table indicates that Black respondents in preclearance areas were about 11 percentage points more likely to report that government was run for the benefit of all the people rather than just a few big interests. Table 3. Logistic regressions predicting perceptions of political inclusion   Government run for benefit of all people  coef.  (s.e.)  Intercept  -0.28*  (0.10)  Black  -0.24*  (0.08)  VRA coverage  0.07  (0.07)  Black x VRA coverage  0.45*  (0.18)  Education  0.05*  (0.02)  Female  0.01  (0.03)  Age  -0.06*  (0.01)  Democratic vote share, 1964  0.22  (0.20)  Democratic vote share, 1964 (squared)  0.41  (0.56)  Voter turnout, 1964  -0.21  (0.30)  Nonwhite population, 1960  -0.58*  (0.28)  Urban population, 1960  0.15*  (0.07)  South  0.17*  (0.06)  N  19,075  Clusters  1,353  Log-likelihood  -11,880.36  χ2  416.08*  Change in Pr(yijt = 1)  0.11*  (0.03)    Government run for benefit of all people  coef.  (s.e.)  Intercept  -0.28*  (0.10)  Black  -0.24*  (0.08)  VRA coverage  0.07  (0.07)  Black x VRA coverage  0.45*  (0.18)  Education  0.05*  (0.02)  Female  0.01  (0.03)  Age  -0.06*  (0.01)  Democratic vote share, 1964  0.22  (0.20)  Democratic vote share, 1964 (squared)  0.41  (0.56)  Voter turnout, 1964  -0.21  (0.30)  Nonwhite population, 1960  -0.58*  (0.28)  Urban population, 1960  0.15*  (0.07)  South  0.17*  (0.06)  N  19,075  Clusters  1,353  Log-likelihood  -11,880.36  χ2  416.08*  Change in Pr(yijt = 1)  0.11*  (0.03)  Source.—American National Election Studies, 1972–1998. Entries are logistic regression coefficients with standard errors in parentheses, clustered on county-year. The dependent variable is measured by responses to the question “Would you say the government is pretty much run by a few big interests looking out for themselves (0) or that it is run for the benefit of all the people (1)?” Indicators for year are also included but not reported. *p < .05 (two-tailed tests). View Large Table 3. Logistic regressions predicting perceptions of political inclusion   Government run for benefit of all people  coef.  (s.e.)  Intercept  -0.28*  (0.10)  Black  -0.24*  (0.08)  VRA coverage  0.07  (0.07)  Black x VRA coverage  0.45*  (0.18)  Education  0.05*  (0.02)  Female  0.01  (0.03)  Age  -0.06*  (0.01)  Democratic vote share, 1964  0.22  (0.20)  Democratic vote share, 1964 (squared)  0.41  (0.56)  Voter turnout, 1964  -0.21  (0.30)  Nonwhite population, 1960  -0.58*  (0.28)  Urban population, 1960  0.15*  (0.07)  South  0.17*  (0.06)  N  19,075  Clusters  1,353  Log-likelihood  -11,880.36  χ2  416.08*  Change in Pr(yijt = 1)  0.11*  (0.03)    Government run for benefit of all people  coef.  (s.e.)  Intercept  -0.28*  (0.10)  Black  -0.24*  (0.08)  VRA coverage  0.07  (0.07)  Black x VRA coverage  0.45*  (0.18)  Education  0.05*  (0.02)  Female  0.01  (0.03)  Age  -0.06*  (0.01)  Democratic vote share, 1964  0.22  (0.20)  Democratic vote share, 1964 (squared)  0.41  (0.56)  Voter turnout, 1964  -0.21  (0.30)  Nonwhite population, 1960  -0.58*  (0.28)  Urban population, 1960  0.15*  (0.07)  South  0.17*  (0.06)  N  19,075  Clusters  1,353  Log-likelihood  -11,880.36  χ2  416.08*  Change in Pr(yijt = 1)  0.11*  (0.03)  Source.—American National Election Studies, 1972–1998. Entries are logistic regression coefficients with standard errors in parentheses, clustered on county-year. The dependent variable is measured by responses to the question “Would you say the government is pretty much run by a few big interests looking out for themselves (0) or that it is run for the benefit of all the people (1)?” Indicators for year are also included but not reported. *p < .05 (two-tailed tests). View Large Figure 2 summarizes the results from tables 1 through 3, and contrasts the relationship between preclearance and attitudes toward government for Black and white respondents. The plotted points display the predicted increase in the probability of providing a positive response to each of the dependent variables shown on the y-axis as a function of preclearance. The x-axis displays these increased probabilities in percentage points, where positive numbers indicate that preclearance is associated with more favorable attitudes toward government. Black respondents are shown with the darker circles, and white respondents are shown with gray circles. The horizontal lines are the 95 percent confidence intervals associated with the estimates. The dashed vertical line at zero indicates where these points would fall under the null hypothesis of no association between federal preclearance and attitudes toward government. Figure 2. View largeDownload slide Federal preclearance and attitudes toward government among Blacks and whites, 1972–1998. The x-axis shows the increased probability (in percentage points) of providing a favorable attitude toward government for each dependent variable among respondents living in areas subject to federal preclearance under the Voting Rights Act. Positive numbers indicate that preclearance is associated with more favorable attitudes, and negative numbers indicate that preclearance is associated with less favorable attitudes. The plotted points are the predicted increases in the probability of providing positive evaluations, and the horizontal lines are the 95 percent confidence intervals associated with these estimates. Figure 2. View largeDownload slide Federal preclearance and attitudes toward government among Blacks and whites, 1972–1998. The x-axis shows the increased probability (in percentage points) of providing a favorable attitude toward government for each dependent variable among respondents living in areas subject to federal preclearance under the Voting Rights Act. Positive numbers indicate that preclearance is associated with more favorable attitudes, and negative numbers indicate that preclearance is associated with less favorable attitudes. The plotted points are the predicted increases in the probability of providing positive evaluations, and the horizontal lines are the 95 percent confidence intervals associated with these estimates. Across all five dependent variables, the predicted difference in attitudes among Black respondents is positive, and both statistically and substantively larger than the predicted change in attitudes among white respondents. Moreover, none of the predicted differences in attitudes among white respondents is statistically distinguishable from zero. Thus, while there is considerable evidence that Black political attitudes were responsive to the efforts of Congress and the federal government to secure voting rights, no evidence exists of such an association among whites. In combination, the results presented here indicate that the provisions of the VRA significantly increased perceptions of democratic legitimacy among Black citizens. Consistent with our argument, Black respondents who lived in areas with the strongest voting rights protections were significantly more likely to report positive evaluations of government and electoral institutions compared with Blacks living in jurisdictions without preclearance. Further, there is no association between preclearance and government attitudes among whites. Conclusion Scholarly accounts of Black attitudes toward government in the 1950s, 1960s, and 1970s routinely emphasized the elevated levels of distrust, cynicism, and alienation (see Walton 1985). By all accounts, the struggle for civil rights achieved a resounding victory with the Voting Rights Act of 1965, which guaranteed ballot access to all citizens and put into place a variety of protections to ensure that those rights were not infringed. Our findings build upon research on the effects of the VRA on Black voter registration and turnout and descriptive representation, and suggest that the guarantee of political inclusion helped reduce Black political alienation and increased affective evaluations of government. Our findings complement other research on the attitudinal consequences of other provisions of the VRA. Increases in the number of Black elected officials over the past half-century, which stemmed in part from the creation of new majority-minority districts pursuant to voting rights jurisprudence, were widely posited to increase the linkages between Black citizens and government. However, the findings in the literature are decidedly mixed (e.g., Gay 2002; Tate 2003; Scherer and Curry 2010). Our research suggests that while descriptive representation and other consequences of the VRA may well have important implications for normatively desirable attitudinal outcomes, the security of voting rights itself plays an important role in shaping Black citizens’ orientations toward and evaluations of democratic institutions. Consistent with other research on the importance of procedural fairness (e.g., Tyler, Casper, and Fisher 1989), attitudes toward government depend upon not only whom is elected but also whether an individual feels their right to participation in the selection process is guaranteed. By design, however, the findings presented here have important limitations. Though we estimated a wide range of statistical models and conducted numerous empirical checks and placebo tests, these data do not permit us to conclusively identify a causal relationship between the preclearance provision in the VRA and political attitudes. However, neither limitation is cause for dispensing with the importance of the findings. Moreover, the focus of this study is limited primarily to Black Americans due to relatively small samples of Asian Americans, Latino/as, and other groups in the ANES. Given the central role the VRA has played in American politics for a half-century, further research is needed to understand the effects its specific provisions have had on the political inclusion of historically marginalized groups. Importantly, though, our research design does not allow us to distinguish the effects of the passage of new policy from those generated by its implementation. It is therefore unclear whether the enactment of new voter ID laws (for instance) would be sufficient to reduce government evaluations or whether such relationships would not be observed until these laws produced material changes in the political representation of Black communities. Consequently, changes to election laws may not produce immediate and dramatic effects on public opinion but instead may cumulate over time. Additional research is needed to understand how policy feedback effects are produced in these contexts and identify their implications for policymakers. Supplementary Data Supplementary data are freely available at Public Opinion Quarterly online. The authors thank the Office of Undergraduate Research and the Department of Political Science at Washington University in St. Louis for generous research support. Chris Elmendorf, Jim Gibson, Andrew Reeves, Maya Sen, and Doug Spencer provided helpful comments. This is one in a series of papers by the authors, and the ordering of authors’ names reflects the principle of rotation. An earlier version of this paper was presented at the 2016 Annual Meeting of the Midwest Political Science Association. Appendix Data The data used in this study are taken from the American National Election Studies Time Series Cumulative File, 1948–2012 (The American National Election Studies 2010). The surveys were conducted by the University of Michigan and were supported by the National Science Foundation (SBR-9707741, SBR-9317631, SES-9209410, SES-9009379, SES-8808361, SES-8341310, SES-8207580, and SOC77-08885). The study population is the American electorate, and eligible voters are the sample universe. The ANES uses a probability sample of adult citizens, which is designed to be representative of the target population (US adults 18 years and older). The data used in this research were collected via face-to-face and telephone interviews and mail surveys. The sample sizes and AAPOR RR1 response rates for each survey wave are below (American Association for Public Opinion Research 2016): Year  N  RR1 (%)  Year  N  RR1 (%)  1972  2705  75.0  1986  2176  67.7  1974  1575  70.0  1988  2040  70.5  1976  2248  70.4  1990  1980  70.6  1978  2304  68.9  1992  1126  74.0  1980  1614  71.8  1994  1036  72.1  1982  1418  72.3  1996  398  59.8  1984  2257  72.1  1998  1281  63.8  Year  N  RR1 (%)  Year  N  RR1 (%)  1972  2705  75.0  1986  2176  67.7  1974  1575  70.0  1988  2040  70.5  1976  2248  70.4  1990  1980  70.6  1978  2304  68.9  1992  1126  74.0  1980  1614  71.8  1994  1036  72.1  1982  1418  72.3  1996  398  59.8  1984  2257  72.1  1998  1281  63.8  View Large Year  N  RR1 (%)  Year  N  RR1 (%)  1972  2705  75.0  1986  2176  67.7  1974  1575  70.0  1988  2040  70.5  1976  2248  70.4  1990  1980  70.6  1978  2304  68.9  1992  1126  74.0  1980  1614  71.8  1994  1036  72.1  1982  1418  72.3  1996  398  59.8  1984  2257  72.1  1998  1281  63.8  Year  N  RR1 (%)  Year  N  RR1 (%)  1972  2705  75.0  1986  2176  67.7  1974  1575  70.0  1988  2040  70.5  1976  2248  70.4  1990  1980  70.6  1978  2304  68.9  1992  1126  74.0  1980  1614  71.8  1994  1036  72.1  1982  1418  72.3  1996  398  59.8  1984  2257  72.1  1998  1281  63.8  View Large Question Wording DEPENDENT VARIABLES How much of the time do you think you can trust the government in Washington to do what is right—just about always, most of the time, only some of the time? (None of the time/never; Some of the time; Most of the time; Just about always) Over the years, how much attention do you feel the government pays to what the people think when it decides what to do—a good deal, some, or not much? (Not much; Some; A good deal) How much do you feel that having elections makes the government pay attention to what the people think—a good deal, some, or not much? (Not much; Some; A good deal) How much attention do you think most Congressmen pay to the people who elect them when they decide what to do in Congress—a good deal, some, or not much? (Not much; Some; A good deal) Would you say the government is pretty much run by a few big interests looking out for themselves or that it is run for the benefit of all the people? (Few big interests; Benefit of all) INDEPENDENT VARIABLES Female—coded from respondent’s sex (male = 0; female = 1) Black—coded from respondent’s race (not black = 0; black = 1) Education—coded from respondent’s educational attainment (no high school degree = 1; high school degree, no college = 2; some college = 3; four-year college degree or more = 4) Age—coded from respondent’s reported birth year Footnotes 1 The historical legacies of slavery have also shaped white political attitudes among whites (Acharya, Blackwell, and Sen 2016). 2 Citizens may also use motivated reasoning and related processes to evaluate government and political figures. For instance, citizens who support their political officials may view those officials as responsive to their political interests and values (e.g., Lenz 2012). Our analysis cannot rule out this possibility. However, it is relatively uncontroversial to say that in the context of our analysis of the VRA, attitudes toward government among historically marginalized groups had been structured by generations of institutional and political inequalities rather than by those groups’ decisions to oppose government and hold more negative attitudes as a result. 3 Subsequent revisions to the VRA expanded these dates to include the 1968 and 1972 presidential elections. 4 The remainder of the paper focuses mostly on the effect of the VRA on Blacks, although our argument also applies to other historically marginalized groups whose political representation may have also been affected by the VRA. 5 This is not to say that descriptive representation is not an important political goal. As Tate (2003) shows, Blacks prefer increased minority representation to color-blind congressional districting. 6 For instance, see Morrison’s (1987) account of an aldermanic primary election in Mississippi in 1969. 7 Replicating our analyses using congressional districts rather than counties as the relevant geographic units for assigning preclearance coverage generates identical patterns of findings to those reported here. 8 As one might expect, the vast majority (90 percent) of Black respondents in our sample from states subject to preclearance lived in Southern states. The remaining 10 percent were predominantly from New York. Sample sizes of Black respondents in states with preclearance requirements are as follows: Alabama (189), Arizona (8), Connecticut (3 in preclearance areas; 33 not in preclearance areas), Georgia (340), Louisiana (84), Mississippi (14), North Carolina (27 in preclearance areas; 98 not in preclearance areas), New York (82 in preclearance areas; 128 not in preclearance areas), South Carolina (15), Texas (152 under preclearance; 16 not subject to preclearance), and Virginia (60). 9 We relied primarily on Hancock and Tredway (1985) to identify covered jurisdictions, supplemented with information available on the Department of Justice website; http://www.justice.gov/crt/about/vot/misc/sec_4.php and http://www.justice.gov/crt/about/vot/sec_5/covered.php (accessed July 9, 2014). 10 For instance, the states of Alaska, Arizona, and Texas were subject to preclearance beginning in 1975 due to the bail-in provision. 11 Between 1984 and 1998, dozens of jurisdictions successfully bailed out of preclearance coverage. For a list, see https://www.justice.gov/crt/section-4-voting-rights-act (accessed April 19, 2016). 12 Our substantive findings are robust to estimating ordered logistic regression and multinomial logistic regression using the original response options. For ease of interpretation, however, we present results using logistic regression. 13 We also include its quadratic to account for the possibility that assignment to preclearance decreased for some values of Democratic vote share before increasing once the values of this variable pass a certain threshold. This could indicate, for instance, that while preclearance was generally less likely to be assigned to increasingly Democratic constituencies, this relationship could reverse among counties with extremely high levels of support for Democrats—such as those in the South. 14 These data come from ICPSR study #8611, “Electoral Data for Counties in the United States: Presidential and Congressional Races, 1840–1972.” 15 These data come from ICPSR study #2896, “Historical, Demographic, Economic, and Social Data: The United States, 1790–2002.” 16 These states include AL, AR, DE, DC, FL, GA, KY, LA, MD, MS, NC, OK, SC, TN, TX, VA, and WV. 17 We measured perceptions of racial discrimination with responses to the question “Generations of slavery and discrimination have created conditions that make it difficult for blacks to work their way out of the lower class.” Both this question and our measure of trust were asked of respondents in 1988, 1990, 1992, and 1994. 18 These tables are shown in tables A.1 through A.5 in the Supplementary Materials. The interaction term in the matching analysis is positive and relatively large in magnitude but falls short of statistical significance, possibly due to the substantial decrease in sample size and statistical power. 19 While not all of these questions explicitly reference the federal government, respondents were likely primed to answer these questions with the federal government in mind because they were administered after respondents received the following prompt: “People have different ideas about the government in Washington. These ideas don’t refer to Democrats or Republicans in particular, but just to the government in general.” 20 Similar results were obtained when coding both “a good deal” and “some” as 1, and “not much” as zero, and when estimating linear, multinominal, and ordinal models. For consistency with the other analyses, the binary dependent variable was used. References Aberbach, Joel D., and Jack L. Walker. 1970. “ Political Trust and Racial Ideology.” American Political Science Review  64: 1199–1 219. Google Scholar CrossRef Search ADS   Abramson, Paul R. 1983. Political Attitudes in America: Formation and Change . San Francisco: W. H. Freeman and Company. Acharya, Avidit, Matthew Blackwell, and Maya Sen. 2016. “ The Political Legacy of American Slavery.” Journal of Politics  78: 621– 41. Google Scholar CrossRef Search ADS   American Association for Public Opinion Research. 2016. Standard Definitions: Final Dispositions of Case Codes and Outcome Rates for Surveys , 9th ed. Ansolabehere, Stephen, and Nathaniel Persily. 2008. “ Vote Fraud in the Eye of the Beholder: The Role of Public Opinion in the Challenge to Voter Identification Requirements.” Harvard Law Review  121: 1737– 74. Banducci, Susan A., Todd Donovan, and Jeffrey A. Karp. 1999. “ Proportional Representation and Attitudes about Politics: Results from New Zealand.” Electoral Studies  18: 533– 55. Google Scholar CrossRef Search ADS   Campbell, Andrea L. 2003. How Policies Make Citizens: Senior Political Activism and the American Welfare State . Princeton, NJ: Princeton University Press. Google Scholar CrossRef Search ADS   Citrin, Jack, Herbert McClosky, J. Merrill Shanks, and Paul M. Sniderman. 1975. “ Personal and Political Sources of Political Alienation.” British Journal of Political Science  5: 1– 31. Google Scholar CrossRef Search ADS   Davidson, Chandler. 1992. “ The Voting Rights Act: A Brief History.” In Controversies in Minority Voting: The Voting Rights Act in Perspective , edited by B. Grofman and C. Davidson, pp. 7– 34. Washington, DC: Brookings Institution Press. Dawson, Michael C. 1994. Behind the Mule: Race and Class in African-American Politics . Princeton, NJ: Princeton University Press. Diamond, Alexis, and Jasjeet S. Sekhon. 2013. “ Genetic Matching for Estimating Causal Effects: A General Multivariate Matching Method for Achieving Balance in Observational Studies.” Review of Economics and Statistics  95: 932– 45. Google Scholar CrossRef Search ADS   Easton, David. 1975. “ A Re-Assessment of the Concept of Political Support.” British Journal of Political Science  5: 435– 57. Google Scholar CrossRef Search ADS   Erikson, Robert S., and Laura Stoker. 2011. “ Caught in the Draft: The Effects of Vietnam Draft Lottery Status on Political Attitudes.” American Political Science Review  105: 221– 37. Google Scholar CrossRef Search ADS   Feldman, Stanley. 1988. “ Structure and Consistency in Public Opinion: The Role of Core Beliefs and Values.” American Journal of Political Science  32: 416– 40. Google Scholar CrossRef Search ADS   Fraga, Bernard L. 2016. “ Redistricting and the Causal Impact of Race on Voter Turnout.” Journal of Politics  78: 19– 34. Google Scholar CrossRef Search ADS   Garrow, David J. 1978. Protest at Selma: Martin Luther King, Jr., and the Voting Rights Act of 1965 . New Haven, CT: Yale University Press. Gay, Claudine. 2002. “ Spirals of Trust? The Effect of Descriptive Representation on the Relationship between Citizens and Their Government.” American Journal of Political Science  46: 717– 32. Google Scholar CrossRef Search ADS   Grofman, Bernard, and Lisa Handley. 1991. “ The Impact of the Voting Rights Act on Black Representation in Southern State Legislatures.” Legislative Studies Quarterly  16: 111– 28. Google Scholar CrossRef Search ADS   Hancock, Paul F., and Lora L. Tredway. 1985. “ The Bailout Standard of the Voting Rights Act: An Incentive to End Discrimination.” Urban Lawyer  17: 379– 425. Hetherington, Marc J. 1998. “ The Political Relevance of Political Trust.” American Political Science Review  92: 791– 808. Google Scholar CrossRef Search ADS   Issacharoff, Samuel. 2013. “ Beyond the Discrimination Model on Voting.” Harvard Law Review  127: 95– 126. Jones-Correa, Michael. 2005. “ Language Provisions Under the Voting Rights Act: How Effective Are They?” Social Science Quarterly  85: 549– 64. Google Scholar CrossRef Search ADS   Lenz, Gabriel S. 2012. Follow the Leader?  Chicago: University of Chicago Press. Google Scholar CrossRef Search ADS   Levi, Margaret. 1998. “ A State of Trust.” In Trust and Governance , edited by V. Braithwaite and M. Levi, pp. 77– 101. New York: Russell Sage Foundation. Lien, Pei-te, Dianne M. Pinderhughes, Carol Hardy-Fanta, and Christine M. Sierra. 2007. “ The Voting Rights Act and the Election of Nonwhite Officials.” PS: Political Science & Politics  40: 489– 94. Google Scholar CrossRef Search ADS   Lublin, David. 1997. The Paradox of Representation: Racial Gerrymandering and Minority Influence in Congress . Princeton, NJ: Princeton University Press. MacCoon, John P. 1979. “ The Enforcement of the Preclearance Requirement of Section 5 of the Voting Rights Act of 1965.” Catholic University Law Review  29: 107– 28. Marschall, Melissa, and Paru R. Shah. 2007. “ The Attitudinal Effects of Minority Incorporation: Examining the Racial Dimensions of Trust in Urban America.” Urban Affairs Review  42: 629– 58. Google Scholar CrossRef Search ADS   McCann, James A., and Jorge I. Dominguez. 1998. “ Mexicans React to Electoral Fraud and Political Corruption: An Assessment of Public Opinion and Voting Behavior.” Electoral Studies  17: 483– 503. Google Scholar CrossRef Search ADS   Miller, Arthur H., and Ola Listhaug. 1990. “ Political Parties and Confidence in Government: A Comparison of Norway, Sweden and the United States.” British Journal of Political Science  20: 357– 89. Google Scholar CrossRef Search ADS   Mishler, William, and Richard Rose. 1997. “ Trust, Distrust and Skepticism: Popular Evaluations of Civil and Political Institutions in Post-Communist Societies.” Journal of Politics  59: 418– 51. Google Scholar CrossRef Search ADS   Mishler, William, and Richard Rose. 2001. “ What Are the Origins of Political Trust? Testing Institutional and Cultural Theories in Post-Communist Societies.” Comparative Political Studies  34: 30– 62. Google Scholar CrossRef Search ADS   Morrison, Minion K. C. 1987. Black Political Mobilization, Leadership, Power and Mass Behavior . Albany: State University of New York Press. Motomura, Hiroshi. 1983. “ Preclearance Under Section 5 of the Voting Rights Act.” North Carolina Law Review  61: 189– 246. Rahn, Wendy M., and Thomas J. Rudolph. 2005. “ A Tale of Political Trust in American Cities.” Public Opinion Quarterly  69: 530– 60. Google Scholar CrossRef Search ADS   Scherer, Nancy, and Brett Curry. 2010. “ Does Descriptive Race Representation Enhance Institutional Legitimacy? The Case of the U.S. Courts.” Journal of Politics  72: 90– 104. Google Scholar CrossRef Search ADS   Schuit, Sophie, and Jon C. Rogowski. 2017. “ Race, Representation, and the Voting Rights Act.” American Journal of Political Science  61: 513– 26. Google Scholar CrossRef Search ADS   Soss, Joe. 1999. “ Lessons of Welfare: Policy Design, Political Learning, and Political Action.” American Political Science Review  93: 363– 80. Google Scholar CrossRef Search ADS   Stokes, Donald E. 1962. “ Popular Evaluations of Government: An Empirical Assessment.” In Ethics and Bigness: Scientific, Academic, Religious, Political, and Military , edited by H. Cleveland and H. D. Lasswell, pp. 61– 72. New York: Harper and Brothers. Tate, Katherine. 1993. From Protest to Politics: The New Black Voters in American Elections . Cambridge, MA: Harvard University Press. Tate, Katherine. 2003. Black Faces in the Mirror: African Americans and Their Representatives in the U.S. Congress . Princeton, NJ: Princeton University Press. The American National Election Studies. 2010. Time Series Cumulative Data File. Stanford University and the University of Michigan. www.electionstudies.org. Tyler, Tom R. 1990. Why People Obey the Law: Procedural Justice, Legitimacy, and Compliance . New Haven, CT: Yale University Press. Tyler, Tom R., Jonathan D. Casper, and Bonnie Fisher. 1989. “ Maintaining Allegiance toward Political Authorities: The Role of Prior Attitudes and the Use of Fair Procedures.” American Journal of Political Science  33: 629– 52. Google Scholar CrossRef Search ADS   Walton, HanesJr. 1985. Invisible Politics: Black Political Behavior . Albany: State University of New York Press. Weaver, Vesla, and Amy Lerman. 2010. “ Political Consequences of the Carceral State.” American Political Science Review  104: 817– 33. Google Scholar CrossRef Search ADS   Whitby, Kenny J. 2000. The Color of Representation: Congressional Behavior and Black Interests . Ann Arbor: University of Michigan Press. Whitby, Kenny J., and Franklin D. Gilliam. 1991. “ A Longitudinal Analysis of Competing Explanations for the Transformation of Southern Congressional Politics.” Journal of Politics  53: 504– 18. Google Scholar CrossRef Search ADS   © The Author(s) 2018. Published by Oxford University Press on behalf of the American Association for Public Opinion Research. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Public Opinion Quarterly Oxford University Press

Electoral Institutions and Democratic Legitimacy

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Abstract

Abstract The Voting Rights Act of 1965 was widely heralded as a solution to persistently high levels of Black political alienation and cynicism. But despite the importance of the Voting Rights Act for the political representation of historically marginalized groups, little is known about how citizens protected by key provisions of the Act viewed democratic institutions. Integrating insights from the policy feedback literature with studies on the relationship between electoral institutions and attitudes toward government, we predict that the voting protections embedded in the Voting Rights Act led to more favorable attitudes toward government among affected communities. Analyses of data from 1972 to 1998 show that Black citizens in jurisdictions covered by Section 5 of the Voting Rights Act, the preclearance provision, exhibited consistently higher levels of trust in government and more positive perceptions of governmental responsiveness. However, we find no evidence that preclearance was associated with similar patterns among whites. Our results may have especially important contemporary relevance given recent controversies over changes to state and local election laws. Legal scholars, historians, political scientists, public officials, and community activists argue that the Voting Rights Act of 1965 (VRA) was among the most important legislative enactments of the twentieth century. According to Issacharoff (2013, p. 95), the Voting Rights Act “was pivotal in bringing black Americans to the broad currents of political life—a transformation that shook the foundations of Jim Crow, triggered the realignment of partisan politics, and set the foundations for the election of an African American president.” The VRA contributed to increased voter registration and turnout among Blacks and linguistic minorities (Tate 1993; Jones-Correa 2005; Fraga 2016) and improved descriptive (e.g., Grofman and Handley 1991; Lien et al. 2007) and substantive (e.g., Whitby and Gilliam 1991; Lublin 1997; Whitby 2000) representation of people of color. In this paper, we study the consequences of the VRA for public opinion. Prior to the VRA, political mistrust, alienation, and cynicism were significantly higher among Blacks than whites (e.g., Aberbach and Walker 1970; Abramson 1983). Black political attitudes, including orientations toward the political system, have been shaped by historical legacies of slavery, the failures of Reconstruction, and Jim Crow (e.g., Dawson 1994), which may explain relatively low perceptions of legitimacy among Blacks a half-century ago.1 Successful efforts by civil rights leaders and activists to secure guaranteed voting rights from the federal government, however, may have significantly reshaped attitudes toward government among members of historically marginalized groups. We offer two main contributions to the study of public opinion and race. First, while existing research devotes significant attention to how descriptive relationship affects political attitudes among racial minority groups (e.g., Gay 2002; Marschall and Shah 2007), we focus on how attitudes toward government are shaped by perceptions of democratic legitimacy. Just as trust in government is shaped by electoral (e.g., Rahn and Rudolph 2005) and governing institutions (e.g., Marschall and Shah 2007), political inclusion is an important determinant of how citizens feel about their government. Second, we integrate insights from research on policy feedback (see, e.g., Soss 1999; Campbell 2003; Weaver and Lerman 2010; Erikson and Stoker 2011) with the study of electoral institutions. Our argument predicts that individuals affected by the provisions of the VRA developed more favorable attitudes toward government because of the opportunities it provided for political inclusion. We test our argument in the context of the preclearance requirement outlined in Section 5 of the VRA. This provision prohibited certain jurisdictions from changing election laws without federal approval and provided security for the voting rights of historically marginalized groups living in those areas. Data from the American National Election Studies conducted from 1972 to 1998 show that Black citizens living in counties subject to federal preclearance reported significantly higher levels of trust in government, evaluations of government responsiveness, and approval of political institutions. These results are robust to a number of model specifications and empirical strategies. Moreover, we find no discernible evidence that preclearance had an effect on white political attitudes. Our findings have important implications for how democratization and electoral institutions affect attitudes toward the state. Electoral Institutions, Political Representation, and Attitudes toward Government The maintenance of democratic political institutions requires both diffuse and specific support. Diffuse support characterizes the public’s respect for and recognition of the political authority vested in institutions, while specific support refers to the public’s evaluations of incumbent political authorities (Easton 1975). These two dimensions of support make it possible for citizens to be personally upset by, for instance, the behavior of incumbent legislators (specific support) but still respect the authority of Congress to make the nation’s laws (diffuse support). Diffuse support thus helps maintain political institutions even in the face of dissatisfaction with particular political officials. Earlier scholarship has found that feelings of political alienation and alienation are associated with lower levels of support both for incumbent officeholders as well as the system as a whole (Citrin et al. 1975). We argue that the protection of voting rights in democracies affects citizens’ attitudes toward government. As Levi (1998, p. 90) argued, “The belief in government fairness requires the perception that all relevant interests have been considered, that the game is not rigged.” Electoral institutions play a key role in structuring beliefs in fairness and the representation of interests. By prescribing the “rules of the game,” electoral institutions affect citizens’ ability to participate in politics, influence election outcomes, and affect government policymaking. When electoral institutions and the outcomes they generate are perceived as biased, the public is likely to express greater disapproval of both the officeholders and the government system more generally.2 Our argument posits a feedback loop that links citizens’ political inclusion to their attitudes toward government. Just as participation in social welfare programs (e.g., Soss 1999), the criminal justice system (e.g., Weaver and Lerman 2010), and the Vietnam draft (e.g., Erikson and Stoker 2011) affects political attitudes and behaviors, citizens are likely to view government as legitimate to the extent they can influence it. Policies that expand or restrict voting access shape the ability of citizens to express political voice, and with them citizens’ affective orientations toward government. This argument builds upon several strands of related research. For instance, local districting and electoral institutions have been shown to affect government trust among historically marginalized groups (e.g., Rahn and Rudolph 2005), largely because these institutions shape the opportunities for residents to meaningfully effect political change in their communities. Research in comparative politics finds that government trust in post-communist nations was higher in societies that protected individual liberties (Mishler and Rose 1997, 2001), while other kinds of political institutions, including the nature of party (Miller and Listhaug 1990) and electoral systems (Banducci, Donovan, and Karp 1999), are also associated with government evaluations. Similarly, electoral fraud and corruption, which may reduce citizens’ perceptions that they can influence the political system, are associated with decreased levels of trust in government (e.g., McCann and Dominguez 1998). Across these diverse literatures, electoral and political institutions affect citizens’ evaluations of government based on how these institutions create opportunities for political inclusion and representation. When electoral institutions are changed, as in the case of the VRA, individuals can update their attitudes about government based on their own political inclusion. Thus, when election policies change, an individual’s evaluations toward government are more positive (negative) if the policies provide that person with enhanced (reduced) political inclusion, and remain stable if the policies have no implications for her level of political inclusion. This expectation contrasts with a sociotropic perspective rooted in core values such as equality or egalitarianism (e.g., Feldman 1988). The sociotropic perspective suggests that individual attitudes toward government respond to changes to electoral institutions based on whether the policy changes expand or reduce political inclusion generally, irrespective of the specific implications for the individual’s political inclusion. Electoral Institutions and the Voting Rights Act Prior to the VRA, electoral institutions including poll taxes and literacy tests limited opportunities for political participation among Blacks and language minorities (Davidson 1992). For instance, only about a quarter of eligible Blacks registered to vote in the middle of the twentieth century (Garrow 1978). Civil rights leaders focused their attention on voting rights during the early 1960s and pressed the Kennedy and Johnson administrations to guarantee voting rights to all eligible Americans. By prohibiting electoral institutions—formal or informal—that produced racial disparities in ballot access, civil rights leaders argued that the VRA would provide greater political power to Blacks (and language-minority groups, with the 1975 amendments). The elimination of restrictive electoral provisions was therefore expected to improve representation for Blacks and other historically marginalized groups and generate more positive evaluations of government. Several of the VRA’s provisions specifically address ballot access and electoral rules. Legal scholars argue that the combination of Section 4(b) and Section 5 is its critical component (MacCoon 1979; Motomura 1983). Section 5 requires certain jurisdictions with a history of voter disenfranchisement to receive federal approval before changing election laws or voting procedures, and Section 4(b) identifies these jurisdictions. The coverage formula specified in Section 4(b) originally identified jurisdictions that used a test or device in the November 1964 presidential election, and in which less than half of the jurisdiction’s eligible citizens were registered or voted in the November 1964 election.3 Thus, while the VRA guaranteed ballot access to all citizens nationwide, it offered the strongest protections to residents of communities that were subject to preclearance. An important body of research credits the VRA with increasing Black voter registration and turnout (Tate 1993) and improving Black descriptive and substantive political representation (Schuit and Rogowski 2017).4 Scholars have devoted less attention to studying how the VRA may have affected how citizens evaluated government. According to our argument, the electoral protections in the VRA should increase Black citizens’ evaluations of political institutions, elected officials, and government more generally by enhancing Blacks’ perceptions of representation and political inclusion. In earlier work, Abramson (1983) finds that Black citizens typically exhibited lower levels of trust in government than whites, and that the size and direction of the gap varied with the federal government’s efforts to ensure racial equality, but does not focus specifically on the VRA. Previous research on the attitudinal consequences of the VRA has instead focused mostly on the effects of Section 2(b), which prohibits minority vote dilution when drawing electoral districts and led to the creation of majority-minority districts and increased descriptive representation. However, scholars have found limited effects of descriptive representation on attitudes toward government. In one of the most important studies on this topic, Gay (2002) finds little evidence that trust in government or perceptions of Congress among Blacks are affected by descriptive representation.5 To the extent the VRA affected attitudes toward government, therefore, it seems unlikely to have done so through Section 2(b). In contrast, our argument predicts that Sections 4(b) and 5 are more likely to have implications for Black political attitudes. Moreover, these provisions may have affected perceptions of political inclusion apart from citizens’ knowledge about the particulars of the electoral institutions used in their local communities. Local organizations and entrepreneurial candidates used the provisions of the VRA to galvanize and mobilize local Black communities in the aftermath of its passage,6 and activities such as these could have raised visibility about federal electoral protections. Contemporary debates over voting access often focus on whether such provisions have disproportionate effects across groups, particularly among racial and ethnic lines, and underscore the importance of documenting the effects of the VRA. Research on voter identification requirements, however, finds that these laws have little effect on citizens’ perceptions of vote fraud (Ansolabehere and Persily 2008), and raises questions about whether restrictions such as these affect other dimensions of public opinion. Thus, understanding how voting protections influence Black attitudes toward government may also provide important insight into the potential effects of contemporary electoral reforms. Data and Methods We study the effects of the VRA on attitudes toward government using the American National Election Studies from 1972 to 1998. We use this time span because federal preclearance under Section 4(b) of the VRA was generally applied at the county level and the county indicators in the ANES are restricted after 1998.7 Our primary analyses focus specifically on Black respondents and in the comparison between Black and white respondents. Unfortunately, very small sample sizes for other minority groups in many of these surveys preclude comparison. In addition, small samples of Black respondents in earlier versions of the ANES limit our ability to include respondents from those years in our analyses. Although this is an obvious limitation of our ability to identify baseline attitudes among Blacks prior to the Act’s passage in 1965, it does not diminish the importance of the analyses. As our discussion above highlighted, Black citizens living in jurisdictions identified by Section 4(b) had greater federal protection against discriminatory election laws because those jurisdictions were required to receive federal preclearance before modifying their electoral laws or voting procedures. An ideal scenario would randomly assign individuals to geographic locations that were or were not covered by the preclearance provisions. However, the coverage formula in Section 4(b) was not randomly assigned to jurisdictions across the country; in fact, the government argued in South Carolina v. Katzenbach and Shelby v. Holder that Congress had reverse-engineered the coverage formula to identify areas with “reliable evidence” of voting discrimination. Thus, we compared individuals’ attitudes based on whether they lived in a jurisdiction that was subject to the preclearance requirement. Based on the geographic information provided about respondents’ locations in the ANES, we identified whether respondents lived in a county that was subject to the preclearance requirement. Counties constituted the vast majority of jurisdictions subject to preclearance, and we suspect our empirical approach represents a conservative strategy for reasons we detail below. All else equal, Black respondents living in counties subject to preclearance should express more positive attitudes toward government than Black respondents living in jurisdictions that were not subject to preclearance.8 We do not expect to observe differences in attitudes toward government on the basis of preclearance among whites, who were generally not subject to the patterns of disenfranchisement in jurisdictions covered by Section 5. While observational research designs like this confront unavoidable challenges due to endogeneity, this concern weighs against finding a positive relationship between preclearance and attitudes toward government. If the coverage formula was applied to the jurisdictions with the most egregious histories of voter discrimination, residents of those jurisdictions should have the most negative attitudes toward government. When comparing attitudes among respondents who live in covered and noncovered jurisdictions, then, we would find a negative relationship between coverage and evaluations of government. It is considerably more difficult to envision a scenario in which endogeneity would explain a positive relationship between coverage and government attitudes, and thus the results that follow may underestimate the effect of preclearance. Our key independent variable, VRA Coverage, is an indicator for whether the ANES respondent lived in a county that was covered by the preclearance requirement as a result of the original Voting Rights Act of 1965 or any of its later amendments, or on the basis of whether it was covered under the bail-in provision.9 In the absence of random assignment, we rely on two key sources of variation to identify the effect of the VRA. Though the coverage formula specified in Section 4(b) identified jurisdictions that were subject to preclearance, this list of covered jurisdictions has changed over the years due to the “bail-in” and “bail-out” provisions. The bail-in provision is specified in Section 3(c) and allows federal courts to subject jurisdictions that fall outside the coverage formula in Section 4(b) to the preclearance requirement if the jurisdiction has enacted voting laws that are racially discriminatory.10 The bail-out provision in Section 4(a) allowed jurisdictions to seek exemption from preclearance if they had not used a voting test or device with discriminatory intent and by showing registration and turnout rates among majority and minority citizens.11 These provisions produced temporal variation in the counties subject to preclearance. Though we report results for a variety of dependent variables, we begin our analyses using the ANES measure of trust in government. Our measure of trust is government is based on the traditional question “How much of the time do you think you can trust the government in Washington to do what is right?” Over the past forty years, the question has generally been asked on a three-point scale that ranges from “some of the time” (1) to “just about always” (3), though some respondents volunteered that they trust government “none of the time.” To facilitate interpretation, we code trust in government dichotomously, where responses of trusting government “most of the time” or “just about always” are coded 1, and other responses are coded zero. The trust in government questions were “designed to tap the basic evaluative orientations toward the national government” (Stokes 1962, p. 64). The more trustworthy citizens perceive government to be, the more likely they are to comply with and consent to its demands and regulations (Tyler 1990). Greater trust benefits elected officials and political institutions by “provid[ing] leaders more leeway to govern effectively and institutions a larger store of support regardless of the performance of those running the government” (Hetherington 1998, p. 803). Figure 1 below compares the level of trust in government among Black respondents who did (solid line) and did not (dotted line) live in areas that were subject to the preclearance provision. With only two exceptions (1984 and 1998), trust in government was higher among Black respondents who lived in areas subject to federal preclearance. Moreover, aggregating over the entire time period, Black respondents living in preclearance jurisdictions reported significantly higher levels of trust than Blacks who did not (difference = .09; p < .01). These raw data provide preliminary support for the hypothesis that the VRA influenced perceptions of democratic legitimacy. Figure 1. View largeDownload slide The Voting Rights Act, federal preclearance, and trust in government, 1972–1998. Black respondents only, American National Election Studies. Plot shows the percentages of Black respondents who indicated they trusted the government to do what was right “most of the time” or “just about always.” The size of the points is proportional to sample size. Figure 1. View largeDownload slide The Voting Rights Act, federal preclearance, and trust in government, 1972–1998. Black respondents only, American National Election Studies. Plot shows the percentages of Black respondents who indicated they trusted the government to do what was right “most of the time” or “just about always.” The size of the points is proportional to sample size. Statistical Models To examine the effect of the preclearance requirement on attitudes toward government, we estimate a series of logistic regressions. The unit of analysis is an individual survey respondent i living in county j in year t, and the main dependent variable is the Trust in government measure described above.12 Generally speaking, our statistical model takes the form  Pr(yijt=1)=logit−1[β0+β1VRA Coveragejt+β2 Blacki+β3(VRA Coveragejt×Blacki)+XijtΩ+Dt+εijt], (1) where yi is respondent i’s degree of trust in government; VRA Coverage is an indicator for whether respondent i’s county j was subject to the preclearance provision under the VRA in year t; Black indicates whether the survey respondent identified as Black or African American; X is a matrix of potential confounding variables that may also be associated with trust in government, which are described below, and with the corresponding coefficient estimates contained in Ω; Dt indicates the year of survey administration to account for any year-specific differences in government trust; and β0 and εijt are constant and error terms, respectively. All data in the analyses are weighted to national population parameters and standard errors are clustered on county-years. Equation (1) allows us to evaluate our main hypothesis in two complementary ways. Primarily, a positive coefficient for the interaction term (β3) between VRA Coverage and Black would indicate that the preclearance provision of the VRA contributed to higher levels of trust in government among Black respondents. This specification also allows us to conduct a placebo test by comparing the effects of VRA Coverage between Black and white respondents. Given that the preclearance provision was targeted specifically to communities that had historically low levels of registration and turnout among people of color, we do not expect an association between preclearance and attitudes toward government among white respondents. Thus, the coefficient estimate (β1) for VRA Coverage should be close to zero, which would indicate that the preclearance provision had little effect among white respondents, while positive and statistically significant results for the interaction term would provide evidence that preclearance affected attitudes primarily among Blacks. However, our conclusions remain unchanged if our models include only respondents who identify as Black or African American (see the Supplementary Materials). We consider two sources of potential confounders: individual-level characteristics that may be associated with trust in government (e.g., education level, an indicator for female respondents, and age), and county-level covariates that were likely correlated with whether a particular county was subject to preclearance (two variables based on the 1964 presidential election: Democratic vote share13 and turnout14). We also accounted for the percentage of the county nonwhite and urban populations.15 Each measurement was taken prior to passage of the 1965 VRA. Finally, we include an indicator for counties located in the South as defined by the Census.16 We point out that the model excludes several individual and contextual characteristics that are identified by previous literature as potential predictors of trust, including partisanship, whether an individual reported being mobilized, level of political interest, and whether Black respondents are represented by a coracial legislator. Each of these characteristics was likely affected by the VRA, and including these variables in our models could introduce unknown degrees of post-treatment bias (though the results with these characteristics are reported in the Supplementary Materials). Results Table 1 displays estimates of the relationship between federal preclearance and trust in government. The first column reports coefficients from a simple model in which Trust in government is regressed on VRA Coverage, Black, its interaction, and the year-specific indicators. The model reported in column (2) accounts for education, sex, and age, and column (3) reports results when the county-level variables are included. Table 1. Logistic regressions predicting trust in government   Model 1  Model 2  Model 3  coef.  (s.e.)  coef.  (s.e.)  coef.  (s.e.)  Intercept  0.22*  (0.10)  0.17  (0.09)  0.11  (0.09)  Black  -0.59*  (0.07)  -0.58*  (0.07)  -0.57*  (0.07)  VRA coverage  0.02  (0.05)  0.01  (0.05)  0.02  (0.06)  Black x VRA coverage  0.48*  (0.12)  0.51*  (0.12)  0.52*  (0.12)  Education      0.07*  (0.02)  0.07*  (0.02)  Female      -0.02  (0.03)  -0.02  (0.03)  Age      -0.02*  (0.01)  -0.02*  (0.01)  Democratic vote share, 1964          0.13  (0.17)  Democratic vote share, 1964 (squared)          0.11  (0.45)  Voter turnout, 1964          0.11  (0.25)  Nonwhite population, 1960          -0.46  (0.24)  Urban population, 1960          0.00  (0.06)  South          0.15*  (0.05)  N  21,777  21,777  21,777  Clusters  1,477  1,477  1,477  Log-likelihood  -14,184.89  -14,168.45  -14,161.04  χ2  673.31*  692.87*  724.13*  Change in Pr(yijt = 1)  0.10*  (0.02)  0.11*  (0.02)  0.11*  (0.03)    Model 1  Model 2  Model 3  coef.  (s.e.)  coef.  (s.e.)  coef.  (s.e.)  Intercept  0.22*  (0.10)  0.17  (0.09)  0.11  (0.09)  Black  -0.59*  (0.07)  -0.58*  (0.07)  -0.57*  (0.07)  VRA coverage  0.02  (0.05)  0.01  (0.05)  0.02  (0.06)  Black x VRA coverage  0.48*  (0.12)  0.51*  (0.12)  0.52*  (0.12)  Education      0.07*  (0.02)  0.07*  (0.02)  Female      -0.02  (0.03)  -0.02  (0.03)  Age      -0.02*  (0.01)  -0.02*  (0.01)  Democratic vote share, 1964          0.13  (0.17)  Democratic vote share, 1964 (squared)          0.11  (0.45)  Voter turnout, 1964          0.11  (0.25)  Nonwhite population, 1960          -0.46  (0.24)  Urban population, 1960          0.00  (0.06)  South          0.15*  (0.05)  N  21,777  21,777  21,777  Clusters  1,477  1,477  1,477  Log-likelihood  -14,184.89  -14,168.45  -14,161.04  χ2  673.31*  692.87*  724.13*  Change in Pr(yijt = 1)  0.10*  (0.02)  0.11*  (0.02)  0.11*  (0.03)  Source.—American National Election Studies, 1972–1998. Entries are logistic regression coefficients with standard errors in parentheses, clustered on county-year. The dependent variable is measured by responses to the question “How much of the time do you think you can trust the government in Washington to do what is right?,” where responses of “most of the time” and “just about always” are coded 1 and other responses are coded 0. Indicators for year are also included but not reported. *p < .05 (two-tailed tests). View Large Table 1. Logistic regressions predicting trust in government   Model 1  Model 2  Model 3  coef.  (s.e.)  coef.  (s.e.)  coef.  (s.e.)  Intercept  0.22*  (0.10)  0.17  (0.09)  0.11  (0.09)  Black  -0.59*  (0.07)  -0.58*  (0.07)  -0.57*  (0.07)  VRA coverage  0.02  (0.05)  0.01  (0.05)  0.02  (0.06)  Black x VRA coverage  0.48*  (0.12)  0.51*  (0.12)  0.52*  (0.12)  Education      0.07*  (0.02)  0.07*  (0.02)  Female      -0.02  (0.03)  -0.02  (0.03)  Age      -0.02*  (0.01)  -0.02*  (0.01)  Democratic vote share, 1964          0.13  (0.17)  Democratic vote share, 1964 (squared)          0.11  (0.45)  Voter turnout, 1964          0.11  (0.25)  Nonwhite population, 1960          -0.46  (0.24)  Urban population, 1960          0.00  (0.06)  South          0.15*  (0.05)  N  21,777  21,777  21,777  Clusters  1,477  1,477  1,477  Log-likelihood  -14,184.89  -14,168.45  -14,161.04  χ2  673.31*  692.87*  724.13*  Change in Pr(yijt = 1)  0.10*  (0.02)  0.11*  (0.02)  0.11*  (0.03)    Model 1  Model 2  Model 3  coef.  (s.e.)  coef.  (s.e.)  coef.  (s.e.)  Intercept  0.22*  (0.10)  0.17  (0.09)  0.11  (0.09)  Black  -0.59*  (0.07)  -0.58*  (0.07)  -0.57*  (0.07)  VRA coverage  0.02  (0.05)  0.01  (0.05)  0.02  (0.06)  Black x VRA coverage  0.48*  (0.12)  0.51*  (0.12)  0.52*  (0.12)  Education      0.07*  (0.02)  0.07*  (0.02)  Female      -0.02  (0.03)  -0.02  (0.03)  Age      -0.02*  (0.01)  -0.02*  (0.01)  Democratic vote share, 1964          0.13  (0.17)  Democratic vote share, 1964 (squared)          0.11  (0.45)  Voter turnout, 1964          0.11  (0.25)  Nonwhite population, 1960          -0.46  (0.24)  Urban population, 1960          0.00  (0.06)  South          0.15*  (0.05)  N  21,777  21,777  21,777  Clusters  1,477  1,477  1,477  Log-likelihood  -14,184.89  -14,168.45  -14,161.04  χ2  673.31*  692.87*  724.13*  Change in Pr(yijt = 1)  0.10*  (0.02)  0.11*  (0.02)  0.11*  (0.03)  Source.—American National Election Studies, 1972–1998. Entries are logistic regression coefficients with standard errors in parentheses, clustered on county-year. The dependent variable is measured by responses to the question “How much of the time do you think you can trust the government in Washington to do what is right?,” where responses of “most of the time” and “just about always” are coded 1 and other responses are coded 0. Indicators for year are also included but not reported. *p < .05 (two-tailed tests). View Large The results are quite consistent across each model. The coefficients for VRA Coverage are very small in magnitude and not statistically distinguishable from zero, providing no evidence of an association between preclearance and trust in government among whites. The coefficients for Black are negative and statistically significant, indicating that Black respondents who lived in areas not subject to preclearance reported significantly lower levels of trust relative to whites. More importantly, the coefficients for the interaction between VRA Coverage and Black were consistently positive and statistically significant, indicating that federal preclearance significantly increased trust in government among Black respondents. The magnitudes of the coefficients for the interaction term, moreover, are nearly identical to those for Black. This finding indicates that while there was a significant Black-white gap in trust in jurisdictions not covered by preclearance, there was no such gap in preclearance counties. The bottom panel of Table 1 reports the substantive magnitudes of VRA Coverage on trust. The row labeled Change in Pr(yijt =1) displays the increase in the predicted probability of reporting trust in government among Black respondents living in counties subject to preclearance. These estimates were generated by holding constant the values of all other covariates and comparing the predicted probability of reporting trust in government among respondents who were and were not living in areas covered by the preclearance provision. The entries in parentheses report the standard errors associated with these increased probabilities. Across the three models, VRA Coverage is associated with a significant increase—between 10 and 11 percentage points—in the probability of trusting government among Black constituents. We find some evidence of an association between trust in government and our control variables. Respondents with higher levels of education reported greater trust, while trust decreased with age. Women were less likely to report trust in government, but this relationship is not statistically significant. Respondents living in counties with higher nonwhite populations in 1960 were less likely to report trust in government, while individuals in the South reported higher trust in government. The coefficients are not statistically significant for 1964 Democratic presidential vote share or its quadratic, 1964 voter turnout, or urban percentage of the 1960 population. These results are robust across a range of additional supplementary analyses. While jurisdictions subject to federal preclearance were distributed across the nation, they were disproportionately concentrated in the South. Thus, we reestimated our models when limiting our analyses to respondents living in Southern states. As mentioned above, we also estimated models that accounted for other potential confounding variables that were likely also affected by the VRA, including mobilization, party identification, political interest, and representation by a Black legislator. In addition, models were estimated that included as covariates income (which is missing for several thousand respondents and thus omitted from the models above) and respondents’ perceptions of racial discrimination (measures that are available for only four of the ANES years under study17). We also estimated models that allowed the coefficients for the individual-level covariates to vary across Black and white respondents. Moreover, rather than including our county-level variables as controls, they were used as instruments for federal preclearance in an instrumental variables framework. Finally, we used genetic matching (Diamond and Sekhon 2013) to address concerns about common support and identified counties that were not subject to preclearance but were otherwise similar to counties that were subject to preclearance on the basis of the county-level variables described above and whether counties were located in the South. After preprocessing the data, we reestimated the models shown above. Across all these additional analyses, the evidence supports our results in Table 1.18 In addition, though a full examination is beyond the scope of this paper, we note that our argument does not apply solely to Black Americans. Indeed, the VRA extended protections to other historically marginalized groups, including language minorities. The Supplementary Materials show that these results extend to nonwhites in general and Latino/as in particular. We are reluctant to overinterpret these results because the samples of Latino/as are quite small, particularly prior to the mid-1980s. However, this preliminary analysis provides evidence that the VRA increased trust in government among members of other protected groups living in jurisdictions subject to the preclearance provision. Evaluations of Government Responsiveness We explore the robustness of our results above by examining the relationship between VRA preclearance and several other system-level evaluations of government. Specifically, if preclearance helped secure perceptions of political inclusion, the guarantee of voting rights should have feedback effects on how individuals perceive American elections. We study how respondents evaluate the relationship between elections and government responsiveness, and expect that Black respondents living in preclearance jurisdictions would have more positive assessments of the capacity for elections to produce political change, as civil rights leaders hoped. We evaluate three additional indicators found in the ANES. The first, Government, is measured using respondents’ answers to the question “How much attention do you feel the government pays to what the people think when it decides what to do?” The second indicator, Elections, links elections to government performance by gauging respondents’ answers to the question “How much do you feel that having elections makes the government pay attention to what the people think?” The third indicator, Legislators, reports responses to the question “How much attention do you think most Congressmen pay to the people who elect them when they decide what to do in Congress?”19 Each question addresses some dimension of respondents’ assessments that the country’s electoral system helps provide effective representation. Responses to these questions were used to create the dependent variables, which were coded 1 if respondents answered “a good deal” and 0 if respondents answered “some” or “not much.”20 Logit models were estimated with these dependent variables and the same independent variables used in the full model in table 1. As shown in table 2, the patterns are consistent with the results in table 1. Across the three dependent variables, the preclearance provision significantly increased perceptions of responsiveness among Black respondents. As the bottom row of the table indicates, the magnitude of these relationships was between seven and 12 percentage points. Again, no systematic evidence exists that preclearance was associated with heightened perceptions of responsiveness among whites. Interestingly, the results do indicate that Black respondents living in preclearance areas had substantially more positive assessments of electoral institutions than white respondents, whether or not they lived in preclearance jurisdictions. Table 2. Logistic regressions predicting evaluations of government responsiveness   Government  Elections  Legislators  coef.  (s.e.)  coef.  (s.e.)  coef.  (s.e.)  Intercept  -2.43*  (0.13)  -0.41*  (0.10)  -1.78*  (0.16)  Black  0.03  (0.10)  -0.06  (0.08)  -0.17  (0.13)  VRA coverage  0.10  (0.09)  0.08  (0.08)  0.07  (0.10)  Black x VRA coverage  0.51*  (0.15)  0.40*  (0.13)  0.38#  (0.23)  Education  0.23*  (0.03)  0.19*  (0.02)  0.25*  (0.03)  Female  -0.30*  (0.05)  -0.11*  (0.03)  -0.18*  (0.06)  Age  0.09*  (0.01)  0.06*  (0.01)  0.06*  (0.02)  Democratic vote share, 1964  0.00  (0.26)  0.15  (0.21)  0.48  (0.37)  Democratic vote share, 1964 (squared)  0.02  (0.65)  0.44  (0.53)  0.59  (0.83)  Voter turnout, 1964  0.16  (0.37)  0.19  (0.30)  0.24  (0.39)  Nonwhite population, 1960  -0.31  (0.30)  -0.36  (0.30)  -0.31  (0.39)  Urban population, 1960  0.21*  (0.08)  0.07  (0.06)  0.01  (0.11)  South  0.18*  (0.08)  0.03  (0.07)  0.14  (0.09)  N  16,838  15,679  7,952  Clusters  1,134  1,035  486  Log-likelihood  -6,960.32  -11,520.30  -4,617.52  χ2  271.70*  292.47*  138.65*  Change in Pr(yijt = 1)  0.08*  (0.02)  0.12*  (0.03)  0.07#  (0.04)    Government  Elections  Legislators  coef.  (s.e.)  coef.  (s.e.)  coef.  (s.e.)  Intercept  -2.43*  (0.13)  -0.41*  (0.10)  -1.78*  (0.16)  Black  0.03  (0.10)  -0.06  (0.08)  -0.17  (0.13)  VRA coverage  0.10  (0.09)  0.08  (0.08)  0.07  (0.10)  Black x VRA coverage  0.51*  (0.15)  0.40*  (0.13)  0.38#  (0.23)  Education  0.23*  (0.03)  0.19*  (0.02)  0.25*  (0.03)  Female  -0.30*  (0.05)  -0.11*  (0.03)  -0.18*  (0.06)  Age  0.09*  (0.01)  0.06*  (0.01)  0.06*  (0.02)  Democratic vote share, 1964  0.00  (0.26)  0.15  (0.21)  0.48  (0.37)  Democratic vote share, 1964 (squared)  0.02  (0.65)  0.44  (0.53)  0.59  (0.83)  Voter turnout, 1964  0.16  (0.37)  0.19  (0.30)  0.24  (0.39)  Nonwhite population, 1960  -0.31  (0.30)  -0.36  (0.30)  -0.31  (0.39)  Urban population, 1960  0.21*  (0.08)  0.07  (0.06)  0.01  (0.11)  South  0.18*  (0.08)  0.03  (0.07)  0.14  (0.09)  N  16,838  15,679  7,952  Clusters  1,134  1,035  486  Log-likelihood  -6,960.32  -11,520.30  -4,617.52  χ2  271.70*  292.47*  138.65*  Change in Pr(yijt = 1)  0.08*  (0.02)  0.12*  (0.03)  0.07#  (0.04)  Source.—American National Election Studies, 1972–1998. Entries are logistic regression coefficients with standard errors in parentheses, clustered on county-year. The dependent variable is measured by responses to the question “How much of the time do you think you can trust the government in Washington to do what is right?,” where responses of “most of the time” and “just about always” are coded 1 and other responses are coded 0. Indicators for year are also included but not reported. #p < .10; *p < .05 (two-tailed tests). View Large Table 2. Logistic regressions predicting evaluations of government responsiveness   Government  Elections  Legislators  coef.  (s.e.)  coef.  (s.e.)  coef.  (s.e.)  Intercept  -2.43*  (0.13)  -0.41*  (0.10)  -1.78*  (0.16)  Black  0.03  (0.10)  -0.06  (0.08)  -0.17  (0.13)  VRA coverage  0.10  (0.09)  0.08  (0.08)  0.07  (0.10)  Black x VRA coverage  0.51*  (0.15)  0.40*  (0.13)  0.38#  (0.23)  Education  0.23*  (0.03)  0.19*  (0.02)  0.25*  (0.03)  Female  -0.30*  (0.05)  -0.11*  (0.03)  -0.18*  (0.06)  Age  0.09*  (0.01)  0.06*  (0.01)  0.06*  (0.02)  Democratic vote share, 1964  0.00  (0.26)  0.15  (0.21)  0.48  (0.37)  Democratic vote share, 1964 (squared)  0.02  (0.65)  0.44  (0.53)  0.59  (0.83)  Voter turnout, 1964  0.16  (0.37)  0.19  (0.30)  0.24  (0.39)  Nonwhite population, 1960  -0.31  (0.30)  -0.36  (0.30)  -0.31  (0.39)  Urban population, 1960  0.21*  (0.08)  0.07  (0.06)  0.01  (0.11)  South  0.18*  (0.08)  0.03  (0.07)  0.14  (0.09)  N  16,838  15,679  7,952  Clusters  1,134  1,035  486  Log-likelihood  -6,960.32  -11,520.30  -4,617.52  χ2  271.70*  292.47*  138.65*  Change in Pr(yijt = 1)  0.08*  (0.02)  0.12*  (0.03)  0.07#  (0.04)    Government  Elections  Legislators  coef.  (s.e.)  coef.  (s.e.)  coef.  (s.e.)  Intercept  -2.43*  (0.13)  -0.41*  (0.10)  -1.78*  (0.16)  Black  0.03  (0.10)  -0.06  (0.08)  -0.17  (0.13)  VRA coverage  0.10  (0.09)  0.08  (0.08)  0.07  (0.10)  Black x VRA coverage  0.51*  (0.15)  0.40*  (0.13)  0.38#  (0.23)  Education  0.23*  (0.03)  0.19*  (0.02)  0.25*  (0.03)  Female  -0.30*  (0.05)  -0.11*  (0.03)  -0.18*  (0.06)  Age  0.09*  (0.01)  0.06*  (0.01)  0.06*  (0.02)  Democratic vote share, 1964  0.00  (0.26)  0.15  (0.21)  0.48  (0.37)  Democratic vote share, 1964 (squared)  0.02  (0.65)  0.44  (0.53)  0.59  (0.83)  Voter turnout, 1964  0.16  (0.37)  0.19  (0.30)  0.24  (0.39)  Nonwhite population, 1960  -0.31  (0.30)  -0.36  (0.30)  -0.31  (0.39)  Urban population, 1960  0.21*  (0.08)  0.07  (0.06)  0.01  (0.11)  South  0.18*  (0.08)  0.03  (0.07)  0.14  (0.09)  N  16,838  15,679  7,952  Clusters  1,134  1,035  486  Log-likelihood  -6,960.32  -11,520.30  -4,617.52  χ2  271.70*  292.47*  138.65*  Change in Pr(yijt = 1)  0.08*  (0.02)  0.12*  (0.03)  0.07#  (0.04)  Source.—American National Election Studies, 1972–1998. Entries are logistic regression coefficients with standard errors in parentheses, clustered on county-year. The dependent variable is measured by responses to the question “How much of the time do you think you can trust the government in Washington to do what is right?,” where responses of “most of the time” and “just about always” are coded 1 and other responses are coded 0. Indicators for year are also included but not reported. #p < .10; *p < .05 (two-tailed tests). View Large The results shown in table 2 suggest that the VRA helped create more positive evaluations of government among Black citizens by guaranteeing the right to vote in places where such guarantees had been largely absent. The results further implicate the role of elections specifically as a mechanism through which citizens can influence government. By ensuring ballot access, the VRA generated more favorable perceptions of democratic legitimacy among traditionally marginalized groups. Perceptions of Political Inclusiveness As noted earlier, federal preclearance may have increased citizens’ feelings of political inclusion by guaranteeing voting access. We study this potential mechanism using responses to the question “Would you say the government is pretty much run by a few big interests looking out for themselves (coded 0) or that it is run for the benefit of all the people (coded 1)?” Though the question wording may not be ideal for testing perceptions of political inclusion, it does tap into respondents’ perceptions of whether government serves the mass public, including themselves. If the VRA helped create the perception of increased political inclusion, Black respondents living in areas subject to preclearance should be more likely than other Black respondents to believe that government is run for the benefit of all people. The results are shown below in table 3. The coefficient for the interaction between VRA Coverage and Black is again positive and statistically significant, indicating that Black respondents living in areas subject to federal clearance were more likely to report feeling that government is responsive to all people compared with Black respondents living in areas that were not covered by preclearance. The constituent term for VRA Coverage is not statistically significant and provides no evidence of a similar relationship among whites. The bottom panel of the table indicates that Black respondents in preclearance areas were about 11 percentage points more likely to report that government was run for the benefit of all the people rather than just a few big interests. Table 3. Logistic regressions predicting perceptions of political inclusion   Government run for benefit of all people  coef.  (s.e.)  Intercept  -0.28*  (0.10)  Black  -0.24*  (0.08)  VRA coverage  0.07  (0.07)  Black x VRA coverage  0.45*  (0.18)  Education  0.05*  (0.02)  Female  0.01  (0.03)  Age  -0.06*  (0.01)  Democratic vote share, 1964  0.22  (0.20)  Democratic vote share, 1964 (squared)  0.41  (0.56)  Voter turnout, 1964  -0.21  (0.30)  Nonwhite population, 1960  -0.58*  (0.28)  Urban population, 1960  0.15*  (0.07)  South  0.17*  (0.06)  N  19,075  Clusters  1,353  Log-likelihood  -11,880.36  χ2  416.08*  Change in Pr(yijt = 1)  0.11*  (0.03)    Government run for benefit of all people  coef.  (s.e.)  Intercept  -0.28*  (0.10)  Black  -0.24*  (0.08)  VRA coverage  0.07  (0.07)  Black x VRA coverage  0.45*  (0.18)  Education  0.05*  (0.02)  Female  0.01  (0.03)  Age  -0.06*  (0.01)  Democratic vote share, 1964  0.22  (0.20)  Democratic vote share, 1964 (squared)  0.41  (0.56)  Voter turnout, 1964  -0.21  (0.30)  Nonwhite population, 1960  -0.58*  (0.28)  Urban population, 1960  0.15*  (0.07)  South  0.17*  (0.06)  N  19,075  Clusters  1,353  Log-likelihood  -11,880.36  χ2  416.08*  Change in Pr(yijt = 1)  0.11*  (0.03)  Source.—American National Election Studies, 1972–1998. Entries are logistic regression coefficients with standard errors in parentheses, clustered on county-year. The dependent variable is measured by responses to the question “Would you say the government is pretty much run by a few big interests looking out for themselves (0) or that it is run for the benefit of all the people (1)?” Indicators for year are also included but not reported. *p < .05 (two-tailed tests). View Large Table 3. Logistic regressions predicting perceptions of political inclusion   Government run for benefit of all people  coef.  (s.e.)  Intercept  -0.28*  (0.10)  Black  -0.24*  (0.08)  VRA coverage  0.07  (0.07)  Black x VRA coverage  0.45*  (0.18)  Education  0.05*  (0.02)  Female  0.01  (0.03)  Age  -0.06*  (0.01)  Democratic vote share, 1964  0.22  (0.20)  Democratic vote share, 1964 (squared)  0.41  (0.56)  Voter turnout, 1964  -0.21  (0.30)  Nonwhite population, 1960  -0.58*  (0.28)  Urban population, 1960  0.15*  (0.07)  South  0.17*  (0.06)  N  19,075  Clusters  1,353  Log-likelihood  -11,880.36  χ2  416.08*  Change in Pr(yijt = 1)  0.11*  (0.03)    Government run for benefit of all people  coef.  (s.e.)  Intercept  -0.28*  (0.10)  Black  -0.24*  (0.08)  VRA coverage  0.07  (0.07)  Black x VRA coverage  0.45*  (0.18)  Education  0.05*  (0.02)  Female  0.01  (0.03)  Age  -0.06*  (0.01)  Democratic vote share, 1964  0.22  (0.20)  Democratic vote share, 1964 (squared)  0.41  (0.56)  Voter turnout, 1964  -0.21  (0.30)  Nonwhite population, 1960  -0.58*  (0.28)  Urban population, 1960  0.15*  (0.07)  South  0.17*  (0.06)  N  19,075  Clusters  1,353  Log-likelihood  -11,880.36  χ2  416.08*  Change in Pr(yijt = 1)  0.11*  (0.03)  Source.—American National Election Studies, 1972–1998. Entries are logistic regression coefficients with standard errors in parentheses, clustered on county-year. The dependent variable is measured by responses to the question “Would you say the government is pretty much run by a few big interests looking out for themselves (0) or that it is run for the benefit of all the people (1)?” Indicators for year are also included but not reported. *p < .05 (two-tailed tests). View Large Figure 2 summarizes the results from tables 1 through 3, and contrasts the relationship between preclearance and attitudes toward government for Black and white respondents. The plotted points display the predicted increase in the probability of providing a positive response to each of the dependent variables shown on the y-axis as a function of preclearance. The x-axis displays these increased probabilities in percentage points, where positive numbers indicate that preclearance is associated with more favorable attitudes toward government. Black respondents are shown with the darker circles, and white respondents are shown with gray circles. The horizontal lines are the 95 percent confidence intervals associated with the estimates. The dashed vertical line at zero indicates where these points would fall under the null hypothesis of no association between federal preclearance and attitudes toward government. Figure 2. View largeDownload slide Federal preclearance and attitudes toward government among Blacks and whites, 1972–1998. The x-axis shows the increased probability (in percentage points) of providing a favorable attitude toward government for each dependent variable among respondents living in areas subject to federal preclearance under the Voting Rights Act. Positive numbers indicate that preclearance is associated with more favorable attitudes, and negative numbers indicate that preclearance is associated with less favorable attitudes. The plotted points are the predicted increases in the probability of providing positive evaluations, and the horizontal lines are the 95 percent confidence intervals associated with these estimates. Figure 2. View largeDownload slide Federal preclearance and attitudes toward government among Blacks and whites, 1972–1998. The x-axis shows the increased probability (in percentage points) of providing a favorable attitude toward government for each dependent variable among respondents living in areas subject to federal preclearance under the Voting Rights Act. Positive numbers indicate that preclearance is associated with more favorable attitudes, and negative numbers indicate that preclearance is associated with less favorable attitudes. The plotted points are the predicted increases in the probability of providing positive evaluations, and the horizontal lines are the 95 percent confidence intervals associated with these estimates. Across all five dependent variables, the predicted difference in attitudes among Black respondents is positive, and both statistically and substantively larger than the predicted change in attitudes among white respondents. Moreover, none of the predicted differences in attitudes among white respondents is statistically distinguishable from zero. Thus, while there is considerable evidence that Black political attitudes were responsive to the efforts of Congress and the federal government to secure voting rights, no evidence exists of such an association among whites. In combination, the results presented here indicate that the provisions of the VRA significantly increased perceptions of democratic legitimacy among Black citizens. Consistent with our argument, Black respondents who lived in areas with the strongest voting rights protections were significantly more likely to report positive evaluations of government and electoral institutions compared with Blacks living in jurisdictions without preclearance. Further, there is no association between preclearance and government attitudes among whites. Conclusion Scholarly accounts of Black attitudes toward government in the 1950s, 1960s, and 1970s routinely emphasized the elevated levels of distrust, cynicism, and alienation (see Walton 1985). By all accounts, the struggle for civil rights achieved a resounding victory with the Voting Rights Act of 1965, which guaranteed ballot access to all citizens and put into place a variety of protections to ensure that those rights were not infringed. Our findings build upon research on the effects of the VRA on Black voter registration and turnout and descriptive representation, and suggest that the guarantee of political inclusion helped reduce Black political alienation and increased affective evaluations of government. Our findings complement other research on the attitudinal consequences of other provisions of the VRA. Increases in the number of Black elected officials over the past half-century, which stemmed in part from the creation of new majority-minority districts pursuant to voting rights jurisprudence, were widely posited to increase the linkages between Black citizens and government. However, the findings in the literature are decidedly mixed (e.g., Gay 2002; Tate 2003; Scherer and Curry 2010). Our research suggests that while descriptive representation and other consequences of the VRA may well have important implications for normatively desirable attitudinal outcomes, the security of voting rights itself plays an important role in shaping Black citizens’ orientations toward and evaluations of democratic institutions. Consistent with other research on the importance of procedural fairness (e.g., Tyler, Casper, and Fisher 1989), attitudes toward government depend upon not only whom is elected but also whether an individual feels their right to participation in the selection process is guaranteed. By design, however, the findings presented here have important limitations. Though we estimated a wide range of statistical models and conducted numerous empirical checks and placebo tests, these data do not permit us to conclusively identify a causal relationship between the preclearance provision in the VRA and political attitudes. However, neither limitation is cause for dispensing with the importance of the findings. Moreover, the focus of this study is limited primarily to Black Americans due to relatively small samples of Asian Americans, Latino/as, and other groups in the ANES. Given the central role the VRA has played in American politics for a half-century, further research is needed to understand the effects its specific provisions have had on the political inclusion of historically marginalized groups. Importantly, though, our research design does not allow us to distinguish the effects of the passage of new policy from those generated by its implementation. It is therefore unclear whether the enactment of new voter ID laws (for instance) would be sufficient to reduce government evaluations or whether such relationships would not be observed until these laws produced material changes in the political representation of Black communities. Consequently, changes to election laws may not produce immediate and dramatic effects on public opinion but instead may cumulate over time. Additional research is needed to understand how policy feedback effects are produced in these contexts and identify their implications for policymakers. Supplementary Data Supplementary data are freely available at Public Opinion Quarterly online. The authors thank the Office of Undergraduate Research and the Department of Political Science at Washington University in St. Louis for generous research support. Chris Elmendorf, Jim Gibson, Andrew Reeves, Maya Sen, and Doug Spencer provided helpful comments. This is one in a series of papers by the authors, and the ordering of authors’ names reflects the principle of rotation. An earlier version of this paper was presented at the 2016 Annual Meeting of the Midwest Political Science Association. Appendix Data The data used in this study are taken from the American National Election Studies Time Series Cumulative File, 1948–2012 (The American National Election Studies 2010). The surveys were conducted by the University of Michigan and were supported by the National Science Foundation (SBR-9707741, SBR-9317631, SES-9209410, SES-9009379, SES-8808361, SES-8341310, SES-8207580, and SOC77-08885). The study population is the American electorate, and eligible voters are the sample universe. The ANES uses a probability sample of adult citizens, which is designed to be representative of the target population (US adults 18 years and older). The data used in this research were collected via face-to-face and telephone interviews and mail surveys. The sample sizes and AAPOR RR1 response rates for each survey wave are below (American Association for Public Opinion Research 2016): Year  N  RR1 (%)  Year  N  RR1 (%)  1972  2705  75.0  1986  2176  67.7  1974  1575  70.0  1988  2040  70.5  1976  2248  70.4  1990  1980  70.6  1978  2304  68.9  1992  1126  74.0  1980  1614  71.8  1994  1036  72.1  1982  1418  72.3  1996  398  59.8  1984  2257  72.1  1998  1281  63.8  Year  N  RR1 (%)  Year  N  RR1 (%)  1972  2705  75.0  1986  2176  67.7  1974  1575  70.0  1988  2040  70.5  1976  2248  70.4  1990  1980  70.6  1978  2304  68.9  1992  1126  74.0  1980  1614  71.8  1994  1036  72.1  1982  1418  72.3  1996  398  59.8  1984  2257  72.1  1998  1281  63.8  View Large Year  N  RR1 (%)  Year  N  RR1 (%)  1972  2705  75.0  1986  2176  67.7  1974  1575  70.0  1988  2040  70.5  1976  2248  70.4  1990  1980  70.6  1978  2304  68.9  1992  1126  74.0  1980  1614  71.8  1994  1036  72.1  1982  1418  72.3  1996  398  59.8  1984  2257  72.1  1998  1281  63.8  Year  N  RR1 (%)  Year  N  RR1 (%)  1972  2705  75.0  1986  2176  67.7  1974  1575  70.0  1988  2040  70.5  1976  2248  70.4  1990  1980  70.6  1978  2304  68.9  1992  1126  74.0  1980  1614  71.8  1994  1036  72.1  1982  1418  72.3  1996  398  59.8  1984  2257  72.1  1998  1281  63.8  View Large Question Wording DEPENDENT VARIABLES How much of the time do you think you can trust the government in Washington to do what is right—just about always, most of the time, only some of the time? (None of the time/never; Some of the time; Most of the time; Just about always) Over the years, how much attention do you feel the government pays to what the people think when it decides what to do—a good deal, some, or not much? (Not much; Some; A good deal) How much do you feel that having elections makes the government pay attention to what the people think—a good deal, some, or not much? (Not much; Some; A good deal) How much attention do you think most Congressmen pay to the people who elect them when they decide what to do in Congress—a good deal, some, or not much? (Not much; Some; A good deal) Would you say the government is pretty much run by a few big interests looking out for themselves or that it is run for the benefit of all the people? (Few big interests; Benefit of all) INDEPENDENT VARIABLES Female—coded from respondent’s sex (male = 0; female = 1) Black—coded from respondent’s race (not black = 0; black = 1) Education—coded from respondent’s educational attainment (no high school degree = 1; high school degree, no college = 2; some college = 3; four-year college degree or more = 4) Age—coded from respondent’s reported birth year Footnotes 1 The historical legacies of slavery have also shaped white political attitudes among whites (Acharya, Blackwell, and Sen 2016). 2 Citizens may also use motivated reasoning and related processes to evaluate government and political figures. For instance, citizens who support their political officials may view those officials as responsive to their political interests and values (e.g., Lenz 2012). Our analysis cannot rule out this possibility. However, it is relatively uncontroversial to say that in the context of our analysis of the VRA, attitudes toward government among historically marginalized groups had been structured by generations of institutional and political inequalities rather than by those groups’ decisions to oppose government and hold more negative attitudes as a result. 3 Subsequent revisions to the VRA expanded these dates to include the 1968 and 1972 presidential elections. 4 The remainder of the paper focuses mostly on the effect of the VRA on Blacks, although our argument also applies to other historically marginalized groups whose political representation may have also been affected by the VRA. 5 This is not to say that descriptive representation is not an important political goal. As Tate (2003) shows, Blacks prefer increased minority representation to color-blind congressional districting. 6 For instance, see Morrison’s (1987) account of an aldermanic primary election in Mississippi in 1969. 7 Replicating our analyses using congressional districts rather than counties as the relevant geographic units for assigning preclearance coverage generates identical patterns of findings to those reported here. 8 As one might expect, the vast majority (90 percent) of Black respondents in our sample from states subject to preclearance lived in Southern states. The remaining 10 percent were predominantly from New York. Sample sizes of Black respondents in states with preclearance requirements are as follows: Alabama (189), Arizona (8), Connecticut (3 in preclearance areas; 33 not in preclearance areas), Georgia (340), Louisiana (84), Mississippi (14), North Carolina (27 in preclearance areas; 98 not in preclearance areas), New York (82 in preclearance areas; 128 not in preclearance areas), South Carolina (15), Texas (152 under preclearance; 16 not subject to preclearance), and Virginia (60). 9 We relied primarily on Hancock and Tredway (1985) to identify covered jurisdictions, supplemented with information available on the Department of Justice website; http://www.justice.gov/crt/about/vot/misc/sec_4.php and http://www.justice.gov/crt/about/vot/sec_5/covered.php (accessed July 9, 2014). 10 For instance, the states of Alaska, Arizona, and Texas were subject to preclearance beginning in 1975 due to the bail-in provision. 11 Between 1984 and 1998, dozens of jurisdictions successfully bailed out of preclearance coverage. For a list, see https://www.justice.gov/crt/section-4-voting-rights-act (accessed April 19, 2016). 12 Our substantive findings are robust to estimating ordered logistic regression and multinomial logistic regression using the original response options. For ease of interpretation, however, we present results using logistic regression. 13 We also include its quadratic to account for the possibility that assignment to preclearance decreased for some values of Democratic vote share before increasing once the values of this variable pass a certain threshold. This could indicate, for instance, that while preclearance was generally less likely to be assigned to increasingly Democratic constituencies, this relationship could reverse among counties with extremely high levels of support for Democrats—such as those in the South. 14 These data come from ICPSR study #8611, “Electoral Data for Counties in the United States: Presidential and Congressional Races, 1840–1972.” 15 These data come from ICPSR study #2896, “Historical, Demographic, Economic, and Social Data: The United States, 1790–2002.” 16 These states include AL, AR, DE, DC, FL, GA, KY, LA, MD, MS, NC, OK, SC, TN, TX, VA, and WV. 17 We measured perceptions of racial discrimination with responses to the question “Generations of slavery and discrimination have created conditions that make it difficult for blacks to work their way out of the lower class.” Both this question and our measure of trust were asked of respondents in 1988, 1990, 1992, and 1994. 18 These tables are shown in tables A.1 through A.5 in the Supplementary Materials. 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Published: Mar 31, 2018

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