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: anthony.s.chen@umich.edu

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.

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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 policy-

making, 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, event-

history 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.

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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).

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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

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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 POLICY-

MAKING

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

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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

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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.

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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).

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A recent study casts doubt on Burstein’s conclusions. Analyzing a longer and richer time-

series (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.

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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 two-

year 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

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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.

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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 Democrat-

Republican 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?

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(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.

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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,

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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.

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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.

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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 full-

fledged 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 state-

year 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 time-

varying 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 event-

history 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 fixed-

effects 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. We also hope that future

research will do more to delineate conditions under which—and the precise range of mechanisms

whereby—social movements influence policy adoption. When and why policy is responsive to

the mass public and/or social movements are among two of the most fundamental questions

facing liberal democracies, and sociologists have much work to do before the answers to these

questions are well understood.

32

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38

TABLE 1. Passage of State Fair Housing Laws by Year, 1959-1966 Year States 1959 Massachusetts, Connecticut, Colorado, Oregon 1960 1961 New Jersey, Minnesota, New York, Pennsylvania 1962 1963 Alaska, California, Michigan 1964 1965 Indiana, Rhode Island, New Hampshire, Ohio, Wisconsin Source: Lockard 1968: 24

39

TABLE 2. 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) Gallup Poll 1963 (N=3,543)

Yes: 21% Yes: 21% Might: 23% Might: 24% No: 56% No: 55%

2. Would you move if colored people came to live in great numbers in your neighborhood? Gallup Poll 1958 (N=1,457) Gallup Poll 1963 (N=3,546)

Yes: 50% Yes: 49% Might: 30% Might: 28% No: 21% 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

TABLE 3. Logit Coefficients and Standard Errors from Selected Bivariate Event-History Models of State Fair Housing Laws

Variable

Model

Time Only

Time + Number of Prior CR

Laws

Time + PA

Laws Civil Rights Mobilization 1 .103**

(.052) .273***

(.078) .204***

(.071) Public Opinion 2 .032

(.049) .050*

(.029) .047*

(.028) Income 3 .001*

(.001) .001

(.001) .001

(.001) Industrialization 4 .024***

(.007) .018**

(.008) .018**

(.008) Urbanization 5 .053**

(.023) .021

(.026) .018

(.026) Electoral Competition 6 .057**

(.025) .054**

(.027) .057**

(.027) Republican Control 7 -.210

(.574) -.240 (.595)

-.284 (.603)

Percentage Black 8 -.034 (.059)

-.085 (.071)

-.087 (.071)

Percentage Jewish 9 .108* (.067)

.001 (.079)

-.012 (.080)

Percentage Catholic 10 .046*** (.017)

.021 (.019)

.018 (.018)

Unionization 11 .041 (.026)

.035 (.028)

.043 (.029)

Adjacent States with FH Law

12 .917*** (.356)

.975*** (.379)

.952*** (.374)

Number of Prior Civil Rights Laws within State

---- 1.253*** ----

Passage of Public Accommodation Law

2.693*** (.055)

Notes: Standard errors in parentheses. N=723. *p≤.10 **p≤.05 ***p≤.01 (two-tailed test)

41

TABLE 4. Logit Coefficients and Standard Errors from Selected Multivariate Event-History 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) Time 0.049 0.031 0.027 (0.111) (0.082) (0.079) Constant -37.789*** -21.539*** -21.929*** (10.452) (4.696) (4.836) X2 (df) 83.22 (14) 70.29 (8) 72.79 (8) Pseudo-R2 .57 .48 .50

Notes: Standard errors in parentheses. N=723. *p≤.10 **p≤.05 ***p≤.01 (two-tailed test)

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TABLE 5. Standardized Odds Ratios for Civil Rights Mobilization and Public Opinion from Selected Event-History Models of State Fair Housing Legislation

Model 2 Model 3

(a) (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.

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APPENDIX A. The passage of state civil rights laws with administrative enforcement, 1945-1966

Year

Fair Employment

Public Accommodations

Fair Housing

1945 NY, NJ 1946 MA 1947 CT 1948 1949 NM, OR, RI, WA CT, NJ 1950 1951 1952 NY, RI 1953 MA, OR 1954 1955 MI, MN, PA 1956 1957 WI, CO WA, CO 1958 1959 CA, OH MA, CT, CO, OR 1960 DE 1961 IL, KS, MO OH, PA NJ, MN, NY, PA 1962 1963 AL, IN, HI AL, IN, KS, MI AL, CA, MI 1964 1965 AZ, MD, NV, UT, NH, NB AZ, MN, MO, NH IN, RI, NH, OH, WI 1966 KY KY Source: Lockard 1968: 24

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APPENDIX B. Variable Descriptions and Sources Variable Description Source Pass Dummy set to 1 if a fair housing law passes during

the year, 0 otherwise; time-varying Lockard 1968

Income Per capita income in 1964 dollars; time-varying, interpolated from Census, 1940-1970

U.S. Bureau of the Census, various years

Industrialization Value added manufacturing per capita in 1964 cents; time-varying; interpolated from Census, 1940-1970

U.S. Bureau of the Census, various years

Urbanization Percentage of urban residents in a state; time-varying; interpolated from Census, 1940-1970

U.S. Bureau of the Census, various years

Republican Control

Dummy set to 1 if Republicans hold a majority in either house or the governorship; 0 otherwise; time-varying

Council of State Governments; Congressional Quarterly, various years

Electoral competition

Percentage margin of victory for the sitting governor, seat margin of the majority party in the House 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

Council of State Governments, various years

Public Opinion Percentage of respondents supporting racial integration on four questions in two Gallup Polls, 1958 and 1963; time-constant; see text

Gallup 1958; Gallup 1963

Black Percentage of black residents in a state; time-varying; interpolated from Census data, 1940-1970

U.S. Bureau of the Census, 1975

Jewish Percentage of Jewish residents in a state; time-varying

American Jewish Committee, various years

Catholic Percentage of Catholic residents in a state; time-varying, interpolated from data points in 1941, 1951, 1961, 1966

Official Catholic Directory, various years

NAACP Percentage of black residents in a state belonging to the NAACP

NAACP, various years

Unionization Percentage non-agricultural workforce belong to a union in 1960; time-varying; interpolated

Troy 1984

Prior Laws Number of civil rights laws having passed in a state; time-varying

Lockard 1968

Adjacency Percentage of adjacent states having passed fair housing laws; time-varying

Lockard 1968

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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 13 14

1. Civil Rights Mobilization

1.00 --- --- --- --- --- --- --- --- --- --- --- --- ---

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 Competition

0.07 -0.20 0.37 0.28 0.41 1.00 --- --- --- --- --- --- --- ---

7. Republican Control

0.06 0.00 0.11 0.12 0.12 0.19 1.00 --- --- --- --- --- --- ---

8. Percent Black -0.22 -0.37 0.41 0.45 0.33 0.08 -0.26 1.00 --- --- --- --- --- --- 9. Percent Jewish -0.11 -0.05 0.33 0.38 0.57 0.20 0.13 0.32 1.00 --- --- --- --- --- 10. Percent Catholic

-0.02 0.01 0.19 0.40 0.51 0.13 0.23 -0.14 0.38 1.00 --- --- --- ---

11. Unionization -0.01 -0.13 0.27 0.40 0.36 0.29 0.08 0.21 0.19 -0.08 1.00 --- --- --- 12. Number of Prior CR Laws

-0.07 -0.12 0.47 0.45 0.52 0.22 -0.05 0.18 0.35 0.41 0.15 1.00 --- ---

13. Public Accommodations Law In-State

-0.05 -0.07 0.40 0.39 0.41 0.15 -0.04 0.16 0.30 0.32 0.08 0.88 1.00 ---

14. FH Laws in Adjacent States

0.05 -0.05 0.46 0.20 0.18 0.14 -0.10 0.10 -0.03 0.10 -0.06 0.27 0.26 1.00

Mean 3.76 42.96 2114 74.04 59.18 70.49 .79 4.13 1.86 21.15 27.21 .40 .14 .35Standard Deviation

3.46 9.00 469 42.23 16.73 17.70 .41 4.19 2.74 12.28 9.94 .71 .35 .66

Note: All monetary figures expressed in 1964 dollars.

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.