Did the Civil Rights Movement Have a Direct Impact on Public Policy? Evidence from the Passage of State Fair Housing Laws, 1959-1965* Anthony S. Chen and Robin Phinney Gerald R. Ford School of Public Policy University of Michigan E-mail: [email protected] September 24, 2004 [APPROXIMATELY 10,500 WORDS, INCLUDING TABLES AND REFERENCES] * Working Paper No. 04-005, Gerald R. Ford School of Public Policy. Direct correspondence to Anthony S. Chen, School of Public Policy, University of Michigan, Ann Arbor, 48109. Presented at the American Sociological Association Meetings, San Francisco, CA, 2004. This research was partially supported by a grant from the National Science Foundation (SES-0000244). The authors would like to thank Mary Corcoran, Alex Hicks, Greg Hooks, Justin McCrary, Isaac Martin, Mark Mizruchi, Chris Roberts, Yu Xie, and Mayer Zald for their feedback and encouragement. 2 Title: Did the Civil Rights Movement Have a Direct Impact on Public Policy? Evidence from the Passage of State Fair Housing Laws, 1959-1965 Abstract: Sociologists have begun to systematically investigate the outcomes of social movements, but it remains unclear whether social movements directly and independently impact the adoption of public policy. In the case of the U.S. civil rights movement, sociological research has been inconclusive. The main barrier is the focus on national politics and federal policymaking, which yields only a limited number of observations for analysis. This paper exploits variation in the timing of state-level fair housing laws and analyzes a new source of data to assess the effect of the civil rights movement on policy adoption. Utilizing discrete-time, eventhistory methods, we find that NAACP mobilization is directly and positively related to the passage of fair housing laws in northern states, even when controlling for public opinion and other potentially confounding variables. In contrast to Downsian models, our findings suggest that social movements shape policy outcomes by signaling to legislators the policy preferences of specific segments of the electorate. In particular, legislators saw NAACP mobilization as a proxy for the mobilization of the black electorate as well as a signal of the electoral reward for supporting fair housing and the penalty for opposing it. The implications of these findings for future research are discussed. 3 If sociological research on social movements was once primarily focused on explaining the emergence, maintenance, and transformation of social movements (e.g., McAdam, McCarthy, Zald 1988), then the field is now centrally concerned with examining the outcomes of social movements (Giugni 1998; Giugni, McAdam, and Tilly 1999). The search for the causes of social movements has in many ways become a search for the consequences of social movements. Research along these lines has rapidly aborned, and sociologists have now studied the impact of social movements on a strikingly assorted array of outcomes, including elective office (Andrews 1997), policy implementation (Amenta, Carruthers, and Zylan 1992; Andrews 2001), life course and demographic changes (McAdam 1999), and scientific credibility (Epstein 1996)—to cite but a handful of recent examples. One theoretical question that remains unresolved is whether social movements have a direct impact on the adoption of public policy. Here, as with much else in the field of social movements, sociologists continue to mine the history of the civil rights movement for evidence (Morris 1999). The empirical findings have been somewhat contradictory. There is qualitative, historical evidence that the mobilization of the civil rights movement wrought numerous changes in American politics, society, and policy (Garrow 1978; McAdam 1982; Button 1989; Morris 1993; Andrews 1997). But there is also some support for Downsian theories, which assign greater causal priority to public opinion in the policy-making process. One important study of Congressional action on equal employment opportunity (EEO) legislation finds evidence that public opinion was fundamental determinant of policy adoption and that the influence of social movements was largely mediated through public opinion (Burstein 1985). A recent study of EEO policy finds statistical evidence that the civil rights movement and public opinion on policy adoption had historically contingent effects (Santoro 2002). 4 While they have contributed greatly to our understanding, previous studies have all posed their question in a similar manner, asking whether and how social movements shaped national politics and federal policy-making. This way of casting the question imposes two distinct limitations. First, focusing on federal policy restricts the number of observations and thus raises questions about the generalizeabilty and robustness of the empirical results—whether the method of choice is the case study or time-series analysis. Second, attempts to expand the number of observations—by modeling a dependent variable other than the probability or odds of adoption—introduces ambiguity in the interpretation of the empirical results. We depart from previous research by exploiting variation in the timing of state fair housing legislation. From 1959 to 1965, sixteen states outside the South passed fair housing laws, which prohibited racial, religious, and national origin discrimination in various sectors of the private housing market. Obtaining such laws was a major objective of civil rights organizations like the National Association for the Advancement of Colored People (NAACP), which sought to leverage the power of the black ballot in northern states, where blacks held and exercised the franchise. But fair housing laws did not all pass at the same time. This temporal variation in the passage of state fair housing laws permits us to model the probability or odds of passage directly, enabling us to make a stronger and clearer multivariate assessment of whether and how social movements and public opinion influence policy adoption. Applying discrete-time, event-history methods to a state-year data set, we find that the mobilization of the civil rights movement, as measured by the percentage of African Americans in a state belonging to the NAACP, is positively related to the passage of fair housing laws, even when controlling for other factors associated with policy innovation. This includes a measure of public opinion regarding housing integration. We interpret the findings as evidence that the 5 mobilization of groups like the NAACP conveyed information to legislators about the policy preferences of the black electorate (rather than the median voter), as well as the costs and benefits associated with satisfying or disregarding them. Legislators were responsive to NAACP strength because it signaled that the electoral reward of supporting fair housing was substantial and the penalty severe. Omitted variables bias and unobserved heterogeneity pose a potential threat to the empirical results, but they are otherwise robust. The remainder of this article is divided in three sections. The first section motivates the question in the context of the theoretical literature on social movements, party organizations, public opinion, and policy-making. A second section presents the empirical strategy and reports the results of the statistical analysis. The concluding section discusses the broader implications of the findings and suggests new directions for future research. SOCIAL MOVEMENTS, PUBLIC OPINION, AND THE POLITICS OF POLICYMAKING If the “interest of many scholars in social movements stems from their belief that social movements represent an important force for social change” (McAdam, McCarthy, and Zald 1988: 727, quoted in Burstein 1999), sociologists are now beginning to assess their impact systematically. The earliest generation of research on social movements was primarily concerned with explaining their emergence, development, and decline, but recently there has been a surge of new interest in understanding whether and how social movements matter—especially in their impact on politics and policy (Giugni 1998; Giugni, McAdam, and Tilly 1999). There is disagreement over the precise definition of a social movement, but we concur with Burstein (1999: 7-9) that in research on democratic politics, particularly in the context of the modern 6 United States, it is most sensible to think of social movements (e.g., Southern Christian Leadership Conference) as belonging on the same continuum of organizational forms with interest groups (e.g., American Federation of Labor—Congress of Industrial Organizations or National Association of Manufacturers) and political parties (e.g., Democratic or Republican party). While social movements may not enjoy the same legal status in the political process as a political parties, or the same degree of political access as interest groups, all three types of groups can be understood as forms of collective action aimed at achieving identifiable social, political, or economic objectives through their participation in a (more or less) democratic political system. Notwithstanding the new focus on outcomes, sociological research on social movements remains dominated, as ever before, by the U.S. civil rights movement (Morris 1999). Library shelves are crowded with chronicles of the storied campaigns in Greensboro, Birmingham, and Selma; they buckle with the weight of tomes on Martin Luther King, Jr., Bayard Rustin, James Farmer, and Roy Wilkins. Every year, numerous books and dissertations join the scores of others already available. The introductory chapter of a recent volume on the impact of social movements begins tellingly with a vignette of the March on Washington in 1963 (Giugni 1999). What is evident from the constant flow scholarly output is nothing so much as the belief that the civil rights movement was a matter of great consequence. This view has the support of careful research. The broader impact of the civil rights movement is most evident in the South. In a comparative analysis of local communities in Florida, Button (1989) finds that the movement left indelible, if complex, legacies. It transformed the racial character of electoral politics from total exclusion to black participation and control. It opened up access to city employment in fire and police protection as well as 7 municipal services. Progress in the private sector came more slowly, but it, too, exhibited noticeable change. Examining numerous counties across Mississippi, Andrews (1997, 2004) finds statistical evidence that the civil rights movement not only facilitated the election of black candidates to political office, but also had discernible effects on the disbursement of federal expenditures to anti-poverty programs (Andrews 2001, 2004). If the civil rights movement wrought wide-ranging changes throughout southern society, historical monographs suggest that the movement was a major force in the highest corridors of federal policy-making as well. Such research finds that the civil rights movement had a direct impact on policy, not only shaping the implementation of policies already in place but also sparking the adoption of entirely new policies. Based on a historical analysis of the Birmingham campaign in 1963, Morris (1993: 633) concludes that the “unprecedented levels of mobilization, organization, and collective action” led by the Southern Christian Leadership Conference generated hundreds of additional demonstrations and protests throughout the South, ultimately convincing Kennedy himself that the time for ad hoc, stopgap solutions had passed—that only the passage of omnibus legislation could redress the systemic inequality that had given rise to the region-wide crisis. Though the president obviously never lived to see what would come of his change of heart, what ultimately resulted was the Civil Rights Act of 1964. Garrow (1978: 178, quoted in Burstein 1985: 70) makes a similar argument about the passage of the Voting Rights Act of 1965. Combing through primary sources, he finds that the march on Selma led a reluctant Congress to pass strong legislation for the first time, even as public opinion also changed in response to the march. The importance of the civil rights movements seems obvious and appealing, and it is especially tempting to accept the claim that it was responsible for major developments in public 8 policy. But at least one important perspective on policy-making, which has gone in sociology under the label “democratic theory” (Burstein 1998), assigns causal priority in the policy-making process to public opinion. This perspective is driven by a powerful and simple insight: “Public sentiment shifts. Political actors sense this shift. And they alter their policy behavior at the margin” (Stimson, MacKuen, and Erikson 1995: 543, quoted in Burstein 1998: 30). In such a model, social movements, interest groups, and political parties influence policy only indirectly— by changing public opinion about a particular issue or changing the salience of a particular issue in the hierarchy of public opinion (Burstein 1999: 12-17). The intuition behind “democratic theory” is recognizable to anyone familiar with the economic theory of democracy associated with Anthony Downs (1957). Put simply, Downsian models predict that policy will reflect the policy preferences of the median voter. Under the assumption that 1) voters are motivated solely by ideological commitments, 2) parties (and the legislators affiliated with them) are motivated solely by winning elections, and 3) ideology can be arranged on a one-dimensional scale, Downs formally demonstrated that elections serve reward or punish parties and their associated legislators based on their responsiveness to mass opinion; namely, the policy preferences of the median voter.1 Hence the policy behavior of 1 If the ideological midpoint between the two parties is located to the left of state opinion, then voters elect more Republicans to the legislature, shifting the ideological makeup of the legislature rightward toward state opinion. If the movement in legislative ideology is “sluggish” (i.e., does not move completely toward state opinion), then state opinion pulls policy still further rightward. On the other hand, if the ideological midpoint between the two parties is located to the right of state opinion, then voters elect more Democrats to the legislature, shifting the ideological makeup of the legislature leftward toward state opinion. If the movement in legislative ideology 9 parties and their legislators closely track mass opinion. To the extent that political parties or social movements play any role whatsoever, it is mainly a secondary one (Erikson, Wright, and McIver 1993). The responsiveness of public policy to public opinion is a topic of ongoing research, and scholarly consensus remains tantalizingly elusive (Manza, Cook, and Page 2002). Nonetheless, all but the most ardent skeptics concede the existence of a general connection (Erikson, Wright, and McIver 1993; Brace et al 2002). As Burstein (2003: 34) writes, “policy is affected by opinion most of the time.” This general connection, however, has led some students of social movements to argue for a presumptive skepticism of previous studies that that do not control for public opinion. In this view, such studies could be yielding biased estimates of the effect of social movements on public policy (Burstein 1998: 42; Burstein and Linton 2002: 398-9). For instance, if public opinion and social movements are both positively correlated with policy outcomes, but public opinion is unobserved, then there is a clear case of omitted variables bias, and estimates of the effect of social movements could be too large. This problem has given rise to warnings that the findings of previous research on social movements “should be treated with caution” (Burstein 1998: 44) and that “researchers should not take organizations’ direct influence on policy outcomes for granted” (Burstein and Linton 2002: 400). is “sluggish,” then state opinion pulls policy still further leftward. In either instance, state opinion drives policy through the mechanism of competitive partisan elections (Erikson, Wright, and McIver 1993). The assumptions made by the Downsian model are necessary to make the problem analytically tractable, but critics have raised questions about whether the assumptions are inaccurate or unrealistic. 10 What support is there for Downsian models in sociological research on the civil rights movement, public opinion, and policy adoption? The strongest support comes from a resourceful and important study in which Burstein (1985) marshals a range of evidence to analyze the impact of public opinion and social movements on equal employment opportunity (EEO) legislation. Through the analysis of a time-series data set, Burstein finds evidence of a positive, bivariate relationship between public opinion and Congressional sponsorship of EEO proposals (Burstein 1985: 50-1). Moreover, he finds limited multivariate evidence that public opinion is more strongly and consistently related to Congressional sponsorship than any other single variable, including EEO-related demonstrations, general demonstrations, and anti-rights demonstrations (Burstein 1985: 83, 85). “Most of the other variables,” he writes, “have no influence on congressional support at all once attitudes are taken into account” (Burstein 1985: 85). Burstein also presents descriptive statistics showing a clear association between public opinion and Congressional votes on the Civil Rights Act of 1964 and the Equal Employment Opportunity Act of 1972 (Burstein 1985: 53-5). Members of Congress were more likely to vote in support of EEO legislation if public opinion in their region favored EEO. Burstein’s conclusion is unambiguous. “The major reason Congress acted was, of course, public opinion. Congress passed EEO legislation in 1964 and amended it in 1972 primarily because it was convinced that the public wanted it to” (Burstein 1985: 180). The relevance of civil rights activism is not entirely dismissed, but Burstein maintains that protests and demonstrations entered into the policy-making process largely as a signal of public opinion; namely, by heightening Congressional awareness of the “increasingly pro-EEO trend in public opinion” and by elevating the salience of civil rights as a matter of public concern (Burstein 1985: 181). 11 A recent study casts doubt on Burstein’s conclusions. Analyzing a longer and richer timeseries (1933-1972) than the one assembled by Burstein, Santoro (2002) finds multivariate evidence that the impact of the civil rights movement and public opinion on the adoption of EEO policy varied historically.2 Santoro’s analysis indicates that the mobilization of social movements, as measured by the number of black protests reported in the New York Times, independently contributed to the adoption of EEO policy in the period, 1940-1964. Public opinion, as measured by the percentage of respondents in national polls supporting the principle of equal employment opportunity for blacks and women, did not. After 1964, however, social movements faded in their significance, and public opinion became the only important predictor of adoption (Santoro 2002: 194). Santoro interprets his empirical results, quite reasonably, as 2 Santoro’s dependent variable is an EEO policy scale constructed from information about three types of policies: EEO bills that cleared the House or the Senate, Congressional EEO statutes, and executive orders pertaining to EEO. The scale ranges from a 0 for the years in which no policies were adopted to a 20 for the year 1972, when Congress passed the Equal Employment Opportunity Enforcement Act. The scale is a “summative measure” that contains information about six potential dimensions of EEO policy (enforcement powers, acts outlawed, public coverage, private coverage, information gathering, quantification) passed in a given year (Santoro 2002: 203). To construct the variable, Santoro identified whether a particular dimension (e.g., enforcement powers) was present in a given policy. When a particular dimension was present, he scored one point for the number of government branches involved in the adoption of the policy. The resulting sum was then converted into a Z-score. This procedure was followed for all six dimensions, and the Z-scores for each dimension were summed. Santoro added a constant to each year so that the lower value on the scale would be a zero. 12 evidence of a “dramatic events-conventional politics” model of policy-making. In the first stage of policy-making, social movements take on greater causal importance than public opinion because they are successful in staging “dramatic events” that place their favored policies at the center of the public agenda. Once these policies are enacted, however, social movements wither away—victims of their own success—and public opinion and other aspects of “conventional politics” come to shape policy development (Santoro 2002: 197). With empirical research thus far yielding mixed evidence, more research on the civil rights movement, public opinion, and policy adoption is clearly needed. What is not clear is whether another study of national politics and federal policy-making will yield much added value. Focusing on the national case sharply limits the number of observations available for analysis and raises a number of straightforward methodological concerns. Historical monographs provide a “thick description” of the various ways that the civil rights movement shaped the dynamics of policy-making. But they obviously offer a very limited basis for generalization. Time-series analysis is a major step forward, but the data are inescapably sparse, which raises concerns about the robustness of the results. For instance, since Burstein cannot directly model the passage of EEO legislation, which only passed twice at the national level, he chooses to analyze Congressional sponsorship of EEO legislation during the same period, using a twoyear Congress as the unit of analysis (Burstein 1985). This is a clever solution because it increases the number of observations, but it is only a partial solution. The data remain extremely sparse. In fact, most of the regression-based results (Burstein 1985: 51, 65, 83, 85, 87) are estimated on the basis of sixteen observations (N=16). Conventional tests of statistical significance can be problematic in such small samples, and outlying observations are bound to be highly influential and could be driving the effect of public opinion. Moreover, it can be difficult 13 to carry out multivariate analysis and hence difficult to rule out alternative explanations of the observed relationships. As he acknowledges himself, “With only sixteen congresses to work with and a relatively large number of independent variables, many of which are highly correlated with each other, there are severe limitations on multivariate analysis” (Burstein 1985: 219).3 Burstein’s use of Congressional sponsorship as a dependent variable also introduces measurement problems.4 To be sure, doing so is necessary to make the statistical analysis tractable, and the variable is generally informative about the level of support for EEO legislation 3 For instance, one plausible hypothesis not tested by Burstein is that sponsorship is a function of black electoral strength; sponsorship increases as the size or participation of the northern black electorate grows. Perhaps the effect of public opinion would diminish such a variable were included. But with only sixteen observations it would be almost meaningless to test a “black electorate” hypothesis against the “public opinion” hypothesis while controlling for other variables associated with Congressional sponsorship. To his credit, Burstein is careful not to overreach in his interpretation of the empirical results, regularly stressing how the findings are “consistent” with democratic theory. The problem is that the results are consistent with other plausible theories, and the sparseness of the data makes it difficult to adjudicate the different possibilities at the most elementary multivariate level. 4 As noted above, Burstein does analyze the relationship between public opinion and legislative passage, but he presents only descriptive data here. Moreover, inspection of Table 3.3 and Table 3.4 (Burstein 1985: 53-5) shows that the variation is largely driven by the South. This is problematic because it is not clear whether sectional differences in public opinion identify political ideology, or something else entirely—for instance, notions of black inferiority or fears of black competition in the labor market. 14 in Congress. But it is less informative about the effect of social movements or public opinion on the probability or odds of legislative passage—whether they exceed the threshold necessary for passage. The necessary threshold, of course, varies by issue. In some instances, all that is required is a simple majority, while in other instances it is necessary to form a veto-proof majority. In the case of civil rights legislation in the postwar U.S. Congress, what was necessary for passage was clear to nearly all political observers at the time. Could a northern DemocratRepublican coalition provide enough votes to wrest a bill away from the Rules Committee in the House, and could the same coalition provide enough votes to invoke cloture in the Senate? Knowing that public opinion is positively correlated with Congressional sponsorship of EEO proposals is useful, but it is less informative about whether and how it is related to the actual passage of EEO legislation.5 In fact, there is reason to wonder whether the use of Congressional sponsorship overestimates the effect of public opinion. A legislator who personally opposes fair housing but who represents a district where the median voter supports fair housing has a strong incentive to sponsor a fair housing bill without working to see that the legislation passes. This would lead to inflated estimates of legislative support for a fair housing bill. These problems are far less pronounced in Santoro’s study (2002). By constructing a scale that essentially measures the number and comprehensiveness of policies enacted in a given year, he expands the number of data points from sixteen to thirty-one (1933-1964), twenty-four 5 Judging from Figure 3.1 (Burstein 1985: 46), it is not hard to imagine that one could estimate a similar association between public opinion and Congressional sponsorship using only the observations for the years prior to 1964—before the passage of any EEO legislation. If the estimates are substantially the same whether or not EEO legislation has passed, how informative can they be about passage? 15 (1940-1964), and thirty-two (1940-1972), depending on the model estimated. It is still possible to raise questions about sample size, but a larger concern is that the scale makes it difficult to precisely identify the substantive effect of the independent variables. This is because the scale aggregates information on different types of policies. Aggregation is clearly necessary because there are not enough policies of each type to model their adoption directly, and the coefficients are obviously interpretable as the effect of a one-unit increase in the independent variable on the scale of policy adoption. But there is still some remaining ambiguity; it not clear whether changes on the scale reflect the adoption of a statute, bill, or executive order.6 We address the limits of previous research by shifting our focus away from federal policy-making and exploiting variation in the timing of state fair housing laws, which passed in sixteen northern states during the late-1950s and early 1960s. This variation, along with the number of events, makes it possible to model the probability of passage directly, obviating the need to develop any proxies. The results will also be readily interpretable, since it will be possible to estimate the effect of particular variables on the odds or probability that a state will pass fair housing legislation. State fair housing laws were civil rights laws that prohibited racial, religious, and national origin discrimination in various sectors of the private housing market (Lockard 1968). These laws naturally varied in the scope of their coverage and the robustness of their enforcement provisions. Some laws covered all types of housing, while other laws made selective exceptions for owner-occupied units. Some laws covered both the rental and sales market, while others 6 The scale also requires the assumption that the different types of policies (executive orders versus Congressional legislation) share the same determinants. This assumption is obviously necessary, but it seems open to question. 16 covered only the rental market. All of the laws, however, sought to regulate housing discrimination in the private housing market, categorically distinguishing them from a previous generation of laws that focused exclusively on public housing (Lockard 1968: 117-9). Despite this similarity, fair housing laws did not all pass at the same time. Table 1 lists the dates of their passage. In 1959, Massachusetts, Connecticut, Oregon, and Colorado became the first states to enact fair housing legislation. Two years later, another four states—New York, New Jersey, Minnesota, and Pennsylvania—would join them. By 1965, sixteen states had managed to pass fair housing laws. Why the striking variation in the timing of passage? The mobilization of the civil rights movement is one plausible answer. Over the course of the postwar period, fair housing became a major political objective of civil rights groups like the NAACP. Although such groups grew relatively weak in the immediate aftermath of Second World War, they gained considerable strength in the mid-1950s (Lockard 1968:29). By 1955, they had begun to participate actively in legislative and electoral politics of most northern states, especially on questions of fair housing. Jack E. Wood, one-time housing secretary of the NAACP, recalled in an interview that northern blacks started to seriously engage the legislative process in 1955 during the battle over the Metcalf-Baker law, which prohibited discrimination in publicly assisted housing in New York State (Lockard 1968: 30). Mobilization only grew in subsequent years, and by 1959 four states had successfully passed fair housing legislation. Civil right rights organizations like the NAACP influenced legislation in multiple ways. These included the methods of “conventional politics” (Santoro 2002), such as mobilizing delegations of voters to lobby individual legislators, or organizing them to attend legislative hearings or key votes. Channing Tobias, head of the NAACP, could not have articulated the modus operendi of his association any more clearly. In a keynote speech to the NAACP in 1957, 17 Tobias noted that the mission of the association was to eradicate “compulsory racial segregation” through “orderly democratic processes,” including “filing of court suits, the development of voting power, sponsorship of civil rights legislation, the dissemination of information and appeals to the conscience of the American people” (New York Times, July 14, 1957). “Conventional politics” proved particularly effective in northern states, where blacks wielded the franchise, unlike their counterparts in the South. In fact, African Americans often held the balance of power in states like New York, where Democrats and Republicans were highly competitive. The electoral significance of the black ballot was not lost on politicians like Republican governor Nelson A. Rockefeller, whose victory over sitting Democratic governor W. Averell Harriman in 1958 was aided substantially by the support of Jewish, black, and Puerto Rican voters. In 1960, Rockefeller’s failure to deliver a fair housing law—over and against the obstructionist tactics of upstate Republicans like Senator Walter J. Mahoney—raised concern among astute observers that he would lose their votes in his 1962 re-election bid (New York Times, April 2, 1960; New York Times, January 8, 1961). In 1961, New York passed a fair housing law, with Rockefeller presiding over the process. Civil rights organizations in the North also worked outside of normal channels to varying degrees—staging direct-action protests, threatening to stage such protests, or generally playing up fears of social unrest. In 1963, when Republican governor James A. Rhodes refused to publicly support a fair housing law then pending in the Ohio legislature, civil rights activists held a sit-in at the state capitol (Lockard 1968). Two members of the Congress of Racial Equality (CORE) chained themselves to seats in the House gallery (New York Times, June 14, 1963), while other activists obstructed access to the governor’s office. A leader of the Ohio Committee for Civil Rights, Theodore H. Berry, formally disavowed responsibility for organizing the 18 protest, but he did not fail to caution legislators that more disturbances could be expected if the legislature remained inactive. “Such direct action movements,” he warned, “will multiply in Ohio as the inevitable result of the vacuum created by the lack of executive and legislation response” (Ohio Committee for Civil Rights, News Bulletin, June 10, 1963, quoted in Lockard 1968: 34). The mobilization of the civil rights movement in Ohio did not yield immediate results, as the bill would expire, but the state would soon pass a fair housing law in 1965. Whatever the particular channel by which the civil rights movement aimed to influence policy, it is clear that all of them (lobbying, direct action, or threats of direct action) worked through the same general mechanism—that is, by conveying information about the political costs and benefits of pleasing or ignoring a specific segment of the electorate, not the median voter. NAACP mobilization signaled to legislators the potential benefits of catering to the preferences of black voters (winning the black vote) as well as the costs of disregarding them (losing the black vote). When and where the NAACP was strong, legislators were likely to support fair housing, since the electoral benefits of supporting fair housing were high and the political costs of opposing fair housing were high as well. When and where the NAACP was weak, legislators were not likely to support fair housing, since the electoral benefits of supporting fair housing were low and the political costs of opposing fair housing were also low. This intuition is the basis of our hypothesis that the mobilization of the civil rights movement is positively and independently associated with the passage of state fair housing legislation. 19 EMPIRICAL ANALYSIS Models We analyze the passage of state fair housing laws using discrete-time, event-history methods (Allison 1982; Peterson 1991; Yamaguchi 1991). This problem poses a special methodological challenge because fair housing laws were not the only type of civil rights legislation passed by northern state legislatures during the postwar period. Historically, northern states passed two other types of legislation—fair employment practice (FEP) laws and public accommodation laws. In fact, inspection of Appendix A reveals that the passage of a fair housing law in a given state typically came only after FEP and public accommodation laws. The passage of fair housing law can thus be seen as the completion of a policy sequence within a state that is typically initiated by the passage of a FEP law. This strong pattern of sequencing requires a modeling strategy that explicitly controls for the factors leading to the prior adoption of other types of civil rights legislation.7 Since the passage of a fair housing law can be conceptualized as a Markoff-type process in which the passage of fair housing legislation is partially a function of the earlier passage of other civil rights legislation, we estimate a model of the functional form: log(Pit/(1-Pit)) = αt + β1Xi + β2Zit + β3Mit + ∈it in which Pit is the probability that state i passes a fair employment law in year t provided that it has not yet done so, α is an intercept for time t, Xi is a time-constant vector of covariates for state i, β1 is a vector of associated effects, Zit is a vector of time-varying covariates for state i that varies according to year t, β2 is a vector of associated effects, Mit is a time-varying vector of covariates indicating the passage of other civil rights legislation by state i in year t, β3 is a vector of associated effects, and ∈it is an error term. Hence, β1 and β2 may be interpreted as vectors of 7 Thanks to Yu Xie for pointing this out to me. 20 the effects associated with covariates Xi and Zit, respectively, net of the forces that led to the passage of other types of civil rights legislation. Data This model requires a data set with a variety of annual information on the social, political, economic, and institutional characteristics of thirty-seven “northern” states during the period 1941-1968.8 We constructed a data set from cross-sectional data on the states that we collected from a wide range of published and unpublished sources, including government reports, private publications, and archival records. Whenever possible, we sought annual data, but in the instances where they were not available, we collected as much data as possible and then generated annual data through linear interpolation. Appendix B provides more detailed information about coding and data sources. The data set is organized in the standard unit-time format required by discrete-time, event-history models—in this case, state-year observations. The first year for which observations on the states are recorded is 1941. We continue to record observations on all thirty-seven states for each subsequent year in which their legislatures met in regular or special session, as reported by Book of the States (Council of State Governments, various years). Once a state passes fair 8 I exclude thirteen states altogether, eleven states from the South as well as Alaska and Hawaii. I follow V.O. Key (1949) in defining the South as the set of states once belonging to the former Confederacy. This includes Alabama, Arkansas, Florida, Georgia, Mississippi, North Carolina, Louisiana, South Carolina, Tennessee, Texas, Virginia. The exclusion of Alaska and Hawaii is consistent with a widespread convention established in studies of state economic performance (e.g., Brace 1993). 21 housing legislation, however, we no longer observe it in subsequent years. The year 1968 is the last year for which we observe a state that has not yet passed fair housing legislation. This procedure translates into a data set or “risk set” comprised of 723 state-year observations. Our rationale for periodizing the risk set from 1941 to 1968 is straightforward. In 1941, states initially became at risk for passing FEP legislation as a result of Roosevelt’s wartime FEPC. Its establishment touched off numerous state initiatives that culminated in the emergence of fullfledged legislative campaigns. Beginning in 1944, such campaigns were mounted in almost legislative session in almost every state. Since the passage a FEP law initiates the process by which a state acquires the full complement of civil rights laws, we begin collecting data when states first become at risk for the passage of FEP laws. We end the data set in 1968, when Congressional passage of the Fair Housing Act significantly reduced the likelihood that states would adopt fair housing legislation. Variables and Controls Our dependent variable is the passage of a state fair housing law. This time-varying, indicator variable is set to 1 if a state adopted an enforceable FEP law in a given year, and set to 0 if it did not (Lockard 1968). Our independent variable is the percentage of African American residents belonging to the NAACP in a given state-year. The measure is time-varying, and it is constructed by dividing the number of NAACP members in a state-year by the number of African Americans in a stateyear and then multiplying the resulting number by 100 (U.S. Bureau of the Census, 1975; 22 NAACP, various years).9 If the coefficient were positive and statistically significant after introducing the control variables, it would constitute evidence supporting the hypothesis. We control for the passage of prior civil rights laws in two different ways. First, we operationalize the effect of prior legislation as a time-varying measure of how many pieces of civil rights legislation had been passed in state i by year t. This measure varies from 0 to 2. Second, we use a time-varying dummy variable set to 1 if a state i had passed a public accommodations law by year t, and 0 if it had not. We construct a time-constant control for public opinion by averaging the percentage of white respondents in a state giving a racially liberal answer to two different questions on Gallup Poll surveys administered in 1958 and 1963. Table 2 presents the wording of both questions along with the associated frequency distributions. Question 1 asks whether a respondent would move if “colored people came to live next door.” In both survey years, more than half of whites exhibited racially liberal beliefs, stating that they would not move. Question 2 is more strongly worded, asking whether the respondent would move if “colored people came to live in great numbers in your neighborhood.” Roughly twenty percent of white respondents in both survey years would remain in their neighborhoods under such circumstances. It is noteworthy that the distribution of answers for each question is fairly stable across time. Our measure of public opinion is the average percentage of respondents in every state answering “No” to these four questions about open housing. If the coefficient for the measure is positive and significant, then 9 The results reported in Table 4 are substantially the same if NAACP membership is entered separately with percentage black, and if the linear time counter is excluded to conserve degrees of freedom. 23 public opinion could greatly diminish the effect of civil rights mobilization, providing evidence contradicting the hypothesis.10 The literature on the determinants of public policy in the states is vast (Besley and Case 2003; Burstein 1998), but we control for other variables consistently associated with policy innovation generally and civil rights legislation specifically. Theories of economic modernization predict that the level of income, industrialization, and urbanization in a state is associated policy innovation (Dye 1969; Walker 1969; Gray 1973). We control for these factors with time-varying measures of per capita income, per capita value added manufacturing, and percentage urban resident, respectively (U.S. Bureau of the Census, various years). Some theories of electoral politics predict that policy innovation occurs in states where the electoral strength of parties is comparable (Walker 1969; Skocpol et al 1993; Holbrook and Van Dunk 1993; Barrileaux, Holbrook, and Langer 2002). Under these circumstances, legislators and candidates for office make broader appeals than they otherwise would. We construct a timevarying control for electoral competition by averaging the percentage margin of victory for the sitting governor, the seat advantage of the majority party in the upper house expressed as a percentage of the total number of seats in the house, the seat advantage of the majority party in the lower house expressed as a percentage of the total number of seats in the house (Council of State Governments, various years; Congressional Quarterly 1994). We subtract the average from 10 We tried different ways of averaging “No” responses, but the pooled average for all four questions draws on the most information and yields the most consistently performing measure. 24 100, yielding a number whose coefficient is positive if electoral competition raises the probability of passage. Other theories of electoral politics find that party control of government is highly relevant to policy innovation. For instance, “institutional politics” (Amenta and Halfman 2000) theories predict that the impact of party organizations is mediated by the institutional structure of political authority. In the specific case of civil rights, Chen (2004) finds that state FEP legislation was less likely to pass if Republicans controlled a veto point in the legislative process, even when considering the underlying preferences of the electorate. The same effect is plausibly working in the politics of fair housing legislation, since there are numerous indications that realtors and property owners worked with conservative Republicans to block such laws (Fine 2000; New York Times, January 29, 1959). We control for Republican control through a time-varying dummy set to 1 if Republicans hold a majority in either house or if the sitting governor is Republican; it is set to 0 if otherwise (Council of State Governments, various years). Power-resources theories predict that the adoption of new policies is positively related to the political and electoral strength of groups who stand to benefit from them (Esping-Anderson 1985). We control for power resources by including measures of percentage black, percentage Jewish, percentage Catholic, and unionization (U.S. Census Bureau 1975; American Jewish Committee, various years; Official Catholic Directory, various years; Troy 1985). All of these groups stood to benefit from the protection afforded by fair housing laws. At the same time, however, “racial” threat theories make the opposition prediction about the effect of these groups—that policy innovation varies inversely with the strength of beneficiary groups because non-beneficiaries are threatened by them (Blumer 1958; Olzak 1992; Behrens, Manza, and Uggen 2003). We control for threat theories with the inclusion of the same controls for power- 25 resources theories. However, we do not have any a priori expectations about the directionality of the effect. Diffusion theories predict that policy innovation is a function of events in adjacent states (Berry and Berry 1990; Zylan and Soule 2000). A number of different mechanisms are associated with diffusion effects. We control for diffusion very straightforwardly by including a time-varying measure of the number of adjacent states with fair housing laws. Results We follow a two-step estimation strategy to test the hypothesis. First, we estimate a separate bivariate regression between the passage of fair housing laws and every single covariate. This will provide a sense of whether there is prima facie evidence supporting the hypothesis. Then we determine whether the bivariate results are spurious by estimating a series of multivariate regressions, beginning with the fullest possible specification and successively trimming the model of covariates that are co-linear or statistically insignificant. Generally speaking, removing theoretically relevant covariates from a model is not preferable because it introduces known specification error into the regression equation (Western 1996: 169; Western and Jackman 1994: 414) and can potentially “distort the significance levels of conventional statistical tests” (Freedman 1983: 152). But it is necessary in this instance because there are only a modest number of events, which can result in small event-to-variable (EPV) ratios. When the EPV ratio is too small in the logistic regression framework, coefficient estimates can be inconsistent and significance tests can be problematic (Peduzzi et all 1996). In light of these considerations, we carry out several types of robustness checks to make sure the results are not statistical artifacts. 26 Table 3 presents logit coefficients and standard errors from thirty-eight separate eventhistory models predicting the passage of fair housing legislation. These models are meant to identify the bivariate relationship between a given covariate and the passage of fair housing laws, but they include a linear time counter as well as a control for the previous passage of civil rights laws within the state. One result is particularly striking. The coefficient for civil rights mobilization is positive and significantly related to the passage of fair housing legislation across all specifications. This is consistent with the hypothesis. But the coefficient for public opinion is positive and comes close to significance in some specifications as well, and it therefore remains possible that the effect of civil rights mobilization is spurious. Of the control variables, industrialization is the most consistently significant, along with electoral competition and the number of adjacent states passing FH laws. Table 4 presents logit coefficients and standard errors several multivariate specifications of the event-history analysis. Each model includes a linear time counter along with a control for the previous passage of civil rights legislation. The fullest possible specification of the model overfits the data. For example, Model 1 appears to provide evidence supporting the hypothesis, but it is severely oversaturated, with 110 failures completely determined. We trim the model by removing variables that exhibit multicollinearity. Inspection of a correlation matrix (Appendix C) reveals that many of the socioeconomic variables—income, industrialization, urbanization, percent black, percent Jewish, percent Catholic, and unionization—are highly correlated with one another as well as the prior passage of other types of civil rights laws.11 We remove these 11 Additional evidence of multicollinearity can be seen in Table 2. Income, urbanization, percentage Jewish, and percentage Catholic (which are highly multicollinear as well as highly correlated with the previous passage of civil rights legislation) are significant in specifications 27 variables, except for industrialization, which is retained because it is correlated with the other socioeconomic variables and because it remains highly significant across all of the specifications reported earlier. We also retain the control for the prior passage of other civil rights laws. Since all of the retained controls are correlated with the removed variables, it is plausible to think of them as partially identifying the effect of the removed variables. The results of the trimmed model are reported as Model 2, which supports the hypothesis. The model fits the data extremely well, exhibiting a proportional reduction-in-error of .48. The coefficient for civil rights mobilization is positive and significant, even when controlling for public opinion, whose coefficient is positive and significant as well. The controls are significant and signed in the expected direction. Another specification of the model supports the hypothesis as well. Model 3 is a specification that is identical to Model 2 except that it includes a control for the passage of public accommodations legislation in place of the control that measures the number of civil rights laws within the state. The results of Model 3 are highly comparable to those of Model 2. The coefficients for civil rights mobilization and public opinion remain significant, and the controls all show similar results to other multivariate specification. It is worth noting that the coefficient for civil rights mobilization is highly similar in size and significance across the bivariate and multivariate models. For instance, it ranges from .273 to .275 in specifications that control for the number of civil rights laws in a state, and it ranges from .204 to .241 in specifications that control for the passage of a public accommodations law. The foregoing models provide evidence that the civil rights movement had a positive effect on the passage of state fair housing legislation, even when controlling for public opinion, including only a linear time counter. But when a control for the previous passage of civil rights legislation is added, their effect diminishes in magnitude and significance. 28 but to what extent does leaving out public opinion overestimate the effect of social movements? Table 5 presents the odds ratios associated with standard-deviation increases in civil rights mobilization and public opinion.12 Column A reports the standardized odds ratios for Model 2 and Model 3 as specified in Table 4. Column B reports the standardized odds ratios for the same models with public opinion excluded from the specification. A comparison of Column A and Column B shows that the odds ratio for civil rights mobilization for each model is higher in specifications excluding public opinion. For instance, when public opinion is excluded from Model 2, increasing civil rights mobilization by one standard-deviation makes it 2.93 times more likely that a state will pass fair housing legislation. However, when public opinion is included in Model 2, then a one standard-deviation increase in civil rights mobilization makes it only 2.59 times more likely that fair housing legislation will pass. This supports the argument (Burstein and Linton 1998) that models of policy-making that exclude public opinion may overestimate the impact of interest organizations. But it should be born in mind that the effect of interest organizations—here the civil rights movement—falls only slightly. In fact, it remains large and statistically significant across specifications. While the effect of public opinion is equally large and significant, it does not cancel out the effect of the civil rights movement. The results thus far seem highly robust across model specifications, but how robust are they to outlying observations? A jackknife diagnostic reveals that the results for civil rights mobilization and public opinion in Model 2 and Model 3 from Table 4 are fairly robust to the exclusion of observations from random years or states, and the controls exhibit minor only 12 The odds ratio associated with a standard-deviation change in a given covariate is given by the formula e β s, where β is the logit coefficient and s is the standard deviation of the covariate of interest. 29 sensitivity.13 As a further robustness check, we also estimated each specification in a linear probability framework and obtained highly comparable results for the main effects.14 Next, we ran a Cox semi-parametric proportional hazards models of each specification using the exact partial likelihood estimation option in Stata 8.0, and the results were similar. Lastly, we estimated each model using only observations from 1955 to 1968, and we found that the main results were substantially the same. Unobserved heterogeneity and omitted variables bias is a potential concern, since fixedeffects models in a logistic regression framework is not possible with so few events. Hence it is not possible to rule out the existence of some unmeasured variable that is correlated both with civil rights mobilization and the passage of fair housing legislation. If such a variable did exist, then estimates of the impact of civil rights mobilization could potentially be biased. 13 For the specifications reported as Model 2 and Model 3 in Table 4, Republican control is the most sensitive result. A handful of results appear sensitive to the exclusion of 1959, 1961, and 1965. The coefficients grow slightly smaller and become insignificant. But it should be born in mind that four to five events (passages) occurred in each of these years. Excluding these years shrinks the number of events under analysis by as much as third, making it arguably too stringent of a test. It is more informative that all of the results (except for Republican control) show good robustness to the exclusion of observations from random states. We therefore feel justifying in describing the results as robust. 14 For exploratory purposes, we also estimated several fixed-effects models within a linear probability framework, and we obtained comparable results under certain model specifications. Multicollinearity is highly evident, however, and we therefore consider the results inconclusive. 30 But the results appear to be robust in a number of different ways. The coefficient for civil rights mobilization is consistently significant across a range of specifications, even when including a significant control for public opinion. It is not driven by observations from outlying states, and it stands up to estimation using different functional forms. DISCUSSION AND CONCLUSION This article exploits temporal variation in the passage of state fair housing legislation in the North to assess whether the civil rights movement had a direct, independent effect on policy adoption. Applying discrete-time, event-history methods to a state-year data set, it finds that the mobilization of the civil rights movement, as measured by the percentage of African Americans belonging to the NAACP in a given state-year, raises the likelihood of passage, even when controlling for public opinion and other variables associated with policy innovation. Although we cannot conclusively rule out omitted variables bias or unobserved heterogeneity, we consider the finding otherwise robust evidence that the mobilization of NAACP conveyed information to legislators about the policy preferences of the black electorate and the magnitude of the political rewards for fulfilling them and the penalties for ignoring them. Contrary to Downsian theories that stress the critical role of the median voter, our findings suggest that social movements can influence the policy-making process by signaling to policy-makers the political costs and benefits of their policy behavior vis-à-vis a particular segment of the electorate. While other research establishing the impact of social movements on policy outcomes may not explicitly consider public opinion, we would submit, based on our analysis, that it is premature to adopt a stance of presumptive doubt toward their findings. 31 Of course, one study of a single policy during a limited period of time in one country can only go so far toward assessing the relationship between social movements, public opinion, and the policy-making process. We hope that future research will explore the validity of our claims with new evidence collected from policy struggles involving different types of social movements and ranging across the federal system and separation of powers. 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Public Opinion on Housing Integration in 1958 and 1963: Gallup Poll 1. If colored people came to live next door, would you move? Gallup Poll 1958 (N=1,457) Yes: 21% Might: 23% No: 56% Gallup Poll 1963 (N=3,543) Yes: 21% Might: 24% No: 55% 2. Would you move if colored people came to live in great numbers in your neighborhood? Gallup Poll 1958 (N=1,457) Yes: 50% Might: 30% No: 21% Gallup Poll 1963 (N=3,546) Yes: 49% Might: 28% No: 23% Source: Gallup Organization 1958; Gallup Organization 1963. Notes: Percentages computed from results reported in actual codebooks; questions posed only to white respondents; sample sizes are for white respondents only; percentages may not sum to 100 due to rounding error. 40 Logit Coefficients and Standard Errors from Selected Bivariate Event-History Models of State Fair Housing Laws Time + Number Variable Model Time Only of Prior CR Time + PA Laws Laws Civil Rights Mobilization 1 .103** .273*** .204*** (.052) (.078) (.071) Public Opinion 2 .032 .050* .047* (.049) (.029) (.028) Income 3 .001* .001 .001 (.001) (.001) (.001) Industrialization 4 .024*** .018** .018** (.007) (.008) (.008) Urbanization 5 .053** .021 .018 (.023) (.026) (.026) Electoral Competition 6 .057** .054** .057** (.025) (.027) (.027) Republican Control 7 -.210 -.240 -.284 (.574) (.595) (.603) Percentage Black 8 -.034 -.085 -.087 (.059) (.071) (.071) Percentage Jewish 9 .108* .001 -.012 (.067) (.079) (.080) Percentage Catholic 10 .046*** .021 .018 (.017) (.019) (.018) Unionization 11 .041 .035 .043 (.026) (.028) (.029) Adjacent States with FH 12 .917*** .975*** .952*** Law (.356) (.379) (.374) TABLE 3. Number of Prior Civil ---Rights Laws within State Passage of Public Accommodation Law Notes: Standard errors in parentheses. N=723. *p≤.10 **p≤.05 ***p≤.01 (two-tailed test) 1.253*** ---2.693*** (.055) 41 Logit Coefficients and Standard Errors from Selected Multivariate EventHistory Models of State Fair Housing Laws 1 2 3 Civil Rights Mobilization 0.565*** 0.275*** 0.241*** (0.195) (0.087) (0.090) Public Opinion 0.156** 0.110*** 0.107*** (0.068) (0.041) (0.042) Income -0.001 ------(0.002) Industrialization 0.049** 0.030*** 0.03*** (0.021) (0.010) (0.010) Urbanization 0.152* ------(0.089) Electoral Competition 0.061 0.084** 0.102*** (0.043) (0.036) (0.038) Republican Control -1.663* -1.488* -1.784** (0.966) (0.782) (0.808) Percentage Black -0.148 ------(0.257) Percentage Jewish -0.092 ------(0.179) Percentage Catholic 0.00 ------(0.059) Unionization 0.123* ------(0.067) Adjacent States with FH Law 1.418*** 0.904** 0.860** (0.526) (0.428) (0.412) Number of Prior CR Laws 1.625* 1.44** ---(0.871) (0.590) Passage of PA Law within State ------2.378*** (0.862) TABLE 4. Time Constant X2 (df) Pseudo-R2 0.049 (0.111) -37.789*** (10.452) 83.22 (14) .57 Notes: Standard errors in parentheses. N=723. *p≤.10 **p≤.05 ***p≤.01 (two-tailed test) 0.031 (0.082) -21.539*** (4.696) 70.29 (8) .48 0.027 (0.079) -21.929*** (4.836) 72.79 (8) .50 42 TABLE 5. Standardized Odds Ratios for Civil Rights Mobilization and Public Opinion from Selected Event-History Models of State Fair Housing Legislation Model 2 (a) Model 3 (b) (a) (b) Civil Rights Mobilization 2.59 2.93 2.30 2.49 Public Opinion 2.69 --- 2.62 --- Note: Column A gives the standardized odds ratios for civil rights mobilization and public opinion for the corresponding models in Table 4. Column B gives the standardized odds ratios for the same models but with public opinion excluded. 43 APPENDIX A. Year The passage of state civil rights laws with administrative enforcement, 19451966 Fair Employment 1945 NY, NJ 1946 MA 1947 CT 1948 1949 NM, OR, RI, WA 1950 1951 1952 1953 1954 1955 MI, MN, PA 1956 1957 WI, CO 1958 1959 CA, OH 1960 DE 1961 IL, KS, MO 1962 1963 AL, IN, HI 1964 1965 AZ, MD, NV, UT, NH, NB 1966 KY Source: Lockard 1968: 24 Public Accommodations Fair Housing CT, NJ NY, RI MA, OR WA, CO MA, CT, CO, OR OH, PA NJ, MN, NY, PA AL, IN, KS, MI AL, CA, MI AZ, MN, MO, NH KY IN, RI, NH, OH, WI 44 APPENDIX B. Variable Pass Income Industrialization Urbanization Republican Control Electoral competition Public Opinion Black Jewish Catholic NAACP Unionization Prior Laws Adjacency Variable Descriptions and Sources Description Dummy set to 1 if a fair housing law passes during the year, 0 otherwise; time-varying Per capita income in 1964 dollars; time-varying, interpolated from Census, 1940-1970 Source Lockard 1968 U.S. Bureau of the Census, various years Value added manufacturing per capita in 1964 cents; U.S. Bureau of the time-varying; interpolated from Census, 1940Census, various 1970 years Percentage of urban residents in a state; time-varying; U.S. Bureau of the interpolated from Census, 1940-1970 Census, various years Dummy set to 1 if Republicans hold a majority in Council of State either house or the governorship; 0 otherwise; Governments; time-varying Congressional Quarterly, various years Percentage margin of victory for the sitting governor, Council of State Governments, seat margin of the majority party in the House various years expressed as a percentage, and seat margin of the majority party in the Senate expressed as a percentage; averaged and subtracted from 100; time-varying Gallup 1958; Percentage of respondents supporting racial Gallup 1963 integration on four questions in two Gallup Polls, 1958 and 1963; time-constant; see text Percentage of black residents in a state; time-varying; U.S. Bureau of the interpolated from Census data, 1940-1970 Census, 1975 Percentage of Jewish residents in a state; timeAmerican Jewish varying Committee, various years Percentage of Catholic residents in a state; timeOfficial Catholic varying, interpolated from data points in 1941, Directory, 1951, 1961, 1966 various years Percentage of black residents in a state belonging to NAACP, various the NAACP years Percentage non-agricultural workforce belong to a Troy 1984 union in 1960; time-varying; interpolated Number of civil rights laws having passed in a state; Lockard 1968 time-varying Percentage of adjacent states having passed fair Lockard 1968 housing laws; time-varying 45 APPENDIX C. Correlations and Descriptive Statistics for Independent Variables Used in the Analysis 1 2 3 4 5 6 7 8 9 10 11 12 1.00 ----------------------- 1. Civil Rights Mobilization 2. Public Opinion -0.02 1.00 --------3. Income 0.12 -0.23 1.00 ------4.Industrialization -0.01 -0.26 0.55 1.00 ----5. Urbanization 0.00 -0.20 0.65 0.61 1.00 --6. Electoral 0.07 -0.20 0.37 0.28 0.41 1.00 Competition 7. Republican 0.06 0.00 0.11 0.12 0.12 0.19 Control 8. Percent Black -0.22 -0.37 0.41 0.45 0.33 0.08 9. Percent Jewish -0.11 -0.05 0.33 0.38 0.57 0.20 10. Percent -0.02 0.01 0.19 0.40 0.51 0.13 Catholic 11. Unionization -0.01 -0.13 0.27 0.40 0.36 0.29 12. Number of -0.07 -0.12 0.47 0.45 0.52 0.22 Prior CR Laws 13. Public -0.05 -0.07 0.40 0.39 0.41 0.15 Accommodations Law In-State 14. FH Laws in 0.05 -0.05 0.46 0.20 0.18 0.14 Adjacent States Mean 3.76 42.96 2114 74.04 59.18 70.49 Standard 3.46 9.00 469 42.23 16.73 17.70 Deviation Note: All monetary figures expressed in 1964 dollars. 13 --- 14 --- ----------- ----------- ----------- ----------- ----------- ----------- ----------- ----------- 1.00 --- --- --- --- --- --- --- -0.26 1.00 0.13 0.32 0.23 -0.14 --1.00 0.38 ----1.00 ------- ------- ------- ------- 0.08 -0.05 0.21 0.18 0.19 0.35 -0.08 0.41 1.00 0.15 --1.00 ----- ----- -0.04 0.16 0.30 0.32 0.08 0.88 1.00 --- -0.10 0.10 -0.03 0.10 -0.06 0.27 0.26 1.00 .79 .41 4.13 4.19 1.86 21.15 27.21 2.74 12.28 9.94 .40 .71 .14 .35 .35 .66 46 BIOGRAPHY PAGE Anthony S. Chen is Assistant Professor of Sociology and Public Policy at the University of Michigan. Under the supervision of Jerome Karabel and Margaret Weir, he recently obtained his Ph.D. in sociology at the University of California, Berkeley, where he was a Soros Fellow. Currently, he is completing a book manuscript that uses case studies, comparative methods, and regression-based analysis to reconsider the historical origins of affirmative action policies in employment. Based on his dissertation, the manuscript is provisionally entitled “’Freedom from Discrimination’: Politics, Jobs, and Civil Rights from Fair Employment to Affirmative Action, 1941-1972.” Robin Phinney is a Ph.D. student in the Gerald R. Ford School of Public Policy and the Department of Political Science at the University of Michigan. She holds a B.A. in Political Science and Communication Studies from the University of California, Los Angeles, and is currently researching the politics of homeless policy at the local, state, and federal level.
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