《社会保障概论》课程教学资源（课后阅读资料）APSR_Volume112. Issue 4.Nov 2018_Protecting_the_Right_to_Discriminate_The_Second_Great_Migration_and_Racial_Threat_in_the_American_We

American Political Science Review (2018)112.4,1104-1110 doi:10.1017/S0003055418000448 American Political Science Association 2018 Letter Protecting the Right to Discriminate:The Second Great Migration and Racial Threat in the American West TYLER T.RENY University of California,Los Angeles BENJAMIN J.NEWMAN University of California,Riverside aking advantage of a unique event in American history,the Second Great Migration,we explore whether the rapid entry of African Americans into nearly exclusively White contexts triggered "racial threat"in White voting behavior in the state of California.Utilizing historical administrative data,we find that increasing proximity to previously White areas experiencing drastic Black population growth between 1940 to 1960 is associated with significant increases in aggregate White voter support for a highly racially-charged ballot measure,Proposition 14,which legally protected racial discrimination in housing.Importantly,we find that this result holds when restricting the analysis to all-White areas with high rates of residential tenure and low rates of White population growth.These latter findings indicate that this relationship materializes in contexts where a larger share of White voters were present during the treatment and exercised residential-choice before the treatment commenced,which is suggestive of a causal effect substantial body of research in American poli- ing direction taken in recent research is the identifica- tics explores the impact of "racial threat"(Key tion of events where large changes in minority pop- 1949)on White Americans'political attitudes ulations occurred and characteristics of the event fa- and behavior.As summarized in prior scholarship cilitate causal inference,typically by mitigating con- (Enos 2016:Oliver 2010:Cho and Baer 2011:see On- cerns about selection bias.Examples include the in- line Appendix A for an expanded review),this litera- flux of African American evacuees from New Orleans ture is beset with conflicting findings,with one of the into neighboring cities following Hurricane Katrina primary contributing factors being the problem of se- (Hopkins 2012)and the exodus of African Ameri- lection bias.Indeed,this research typically analyzes the can residents from Whites'neighborhoods following impact of the size of geographically proximate racial the demolition of public housing in Chicago (Enos minority populations on Whites using observational 2016). data,limiting causal inference due to concerns over In this letter,we identify a previously overlooked the non-random nature of minority settlement patterns event in American history that provides useful fea- and residential selection among Whites (Clark 1992) tures for gaining insight on the effect of racial con- Prior scholarship has attempted to assuage these con- text on White voter behavior.Following the First cerns by controlling for self-reported neighborhood Great Migration(1910-1930)of African Americans out racial preferences(Oliver and Wong 2003),performing of the American South to Northeastern cities (Gre- endogeneity tests (Rocha and Espino 2009),demon- gory 2005),a second and larger exodus of African strating that racial orientations are not predictive of Americans out of the South(1941-1970)resulted in a respondents'racial context(Branton and Jones 2005). massive and unprecedented migration to the Amer- and using instrumental variables (Acharya,Blackwell. ican West-most notably to the state of California and Sen 2016).Additionally,scholarship has attempted (Wilkerson 2011).Dubbed the Second Great Migra- to bypass this issue altogether by using survey and tion (SGM).this event provides a useful test of racial field experiments(Glaser 2003;Enos 2014).A promis- threat,as African Americans previously constituted an almost non-existent share of the California popu- Tyler T.Reny is a PhD Candidate,Department of Political Science, lation.Residential choice among Anglo-Californians University of California,Los Angeles(ttreny@ucla.edu). prior to the SGM occurred largely in the absence Benjamin J.Newman is an Associate Professor,School of Public of Black residents,distinguishing this event from the Policy and Department of Political Science,University of California. vast majority of existing studies of racial threat where Riverside (bnewman@ucr.edu). the Whites under study had long-standing contact We thank Bryan Wilcox-Archuleta,Matt A.Barreto,APSR's with African Americans and residential decisions were anonymous reviewers,and participants,panelists,and discussants at the 2018 Western Political Science Association Conference,the Mid- made with regard to racial demographics (Freund west Political Science Association conference,and the UCLA Racia 2007). and Ethnic Politics Research Lab for helpful feedback and discus- We leverage this historical event to evaluate the im- sion.We thank Steven Melendez for his assistance with data prepara- pact of proximity to areas undergoing rapid demo- tion and processing.Finally,we are grateful for the research support from the UCLA Luskin Center for History and Policy.Replication graphic change on White voting for Proposition 14, files can be found on the American Political Science Review Data- a California ballot proposition in the 1964 election verse:https://doi.org/10.7910/DVN/UAOZRO that sought to exempt the real estate industry and 士 Received:September 26,2017;revised:April 3,2018;accepted:June homeowners from anti-discrimination laws (HoSang 29,2018.First published online:September 5,2018. 2010).Applying theories of racial threat,we expect 1104

American Political Science Review (2018) 112, 4, 1104–1110 doi:10.1017/S0003055418000448 © American Political Science Association 2018 Letter Protecting the Right to Discriminate: The Second Great Migration and Racial Threat in the American West TYLER T. RENY University of California, Los Angeles BENJAMIN J. NEWMAN University of California, Riverside Taking advantage of a unique event in American history, the Second Great Migration, we explore whether the rapid entry of African Americans into nearly exclusively White contexts triggered “racial threat”in White voting behavior in the state of California.Utilizing historical administrative data, we find that increasing proximity to previously White areas experiencing drastic Black population growth between 1940 to 1960 is associated with significant increases in aggregate White voter support for a highly racially-charged ballot measure, Proposition 14, which legally protected racial discrimination in housing. Importantly, we find that this result holds when restricting the analysis to all-White areas with high rates of residential tenure and low rates of White population growth. These latter findings indicate that this relationship materializes in contexts where a larger share of White voters were present during the treatment and exercised residential-choice before the treatment commenced, which is suggestive of a causal effect. Asubstantial body of research in American poli￾tics explores the impact of “racial threat” (Key 1949) on White Americans’ political attitudes and behavior. As summarized in prior scholarship (Enos 2016; Oliver 2010; Cho and Baer 2011; see On￾line Appendix A for an expanded review), this litera￾ture is beset with conflicting findings, with one of the primary contributing factors being the problem of se￾lection bias. Indeed, this research typically analyzes the impact of the size of geographically proximate racial minority populations on Whites using observational data, limiting causal inference due to concerns over the non-random nature of minority settlement patterns and residential selection among Whites (Clark 1992). Prior scholarship has attempted to assuage these con￾cerns by controlling for self-reported neighborhood racial preferences (Oliver and Wong 2003), performing endogeneity tests (Rocha and Espino 2009), demon￾strating that racial orientations are not predictive of respondents’ racial context (Branton and Jones 2005), and using instrumental variables (Acharya, Blackwell, and Sen 2016). Additionally, scholarship has attempted to bypass this issue altogether by using survey and field experiments (Glaser 2003; Enos 2014). A promis￾Tyler T. Reny is a PhD Candidate, Department of Political Science, University of California, Los Angeles (ttreny@ucla.edu). Benjamin J. Newman is an Associate Professor, School of Public Policy and Department of Political Science, University of California, Riverside (bnewman@ucr.edu). We thank Bryan Wilcox-Archuleta, Matt A. Barreto, APSR’s anonymous reviewers, and participants, panelists, and discussants at the 2018 Western Political Science Association Conference, the Mid￾west Political Science Association conference, and the UCLA Racial and Ethnic Politics Research Lab for helpful feedback and discus￾sion.We thank Steven Melendez for his assistance with data prepara￾tion and processing. Finally, we are grateful for the research support from the UCLA Luskin Center for History and Policy. Replication files can be found on the American Political Science Review Data￾verse: https://doi.org/10.7910/DVN/UAQZRO. Received: September 26, 2017; revised: April 3, 2018; accepted: June 29, 2018. First published online: September 5, 2018. ing direction taken in recent research is the identifica￾tion of events where large changes in minority pop￾ulations occurred and characteristics of the event fa￾cilitate causal inference, typically by mitigating con￾cerns about selection bias. Examples include the in￾flux of African American evacuees from New Orleans into neighboring cities following Hurricane Katrina (Hopkins 2012) and the exodus of African Ameri￾can residents from Whites’ neighborhoods following the demolition of public housing in Chicago (Enos 2016). In this letter, we identify a previously overlooked event in American history that provides useful fea￾tures for gaining insight on the effect of racial con￾text on White voter behavior. Following the First Great Migration (1910-1930) of African Americans out of the American South to Northeastern cities (Gre￾gory 2005), a second and larger exodus of African Americans out of the South (1941-1970) resulted in a massive and unprecedented migration to the Amer￾ican West—most notably to the state of California (Wilkerson 2011). Dubbed the Second Great Migra￾tion (SGM), this event provides a useful test of racial threat, as African Americans previously constituted an almost non-existent share of the California popu￾lation. Residential choice among Anglo-Californians prior to the SGM occurred largely in the absence of Black residents, distinguishing this event from the vast majority of existing studies of racial threat where the Whites under study had long-standing contact with African Americans and residential decisions were made with regard to racial demographics (Freund 2007). We leverage this historical event to evaluate the im￾pact of proximity to areas undergoing rapid demo￾graphic change on White voting for Proposition 14, a California ballot proposition in the 1964 election that sought to exempt the real estate industry and homeowners from anti-discrimination laws (HoSang 2010). Applying theories of racial threat, we expect 1104 Downloaded from https://www.cambridge.org/core. Shanghai JiaoTong University, on 26 Oct 2018 at 03:56:49, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0003055418000448

Protecting the Right to Discriminate proximity to rapidly diversifying cities to be associ- In sum.1940 to 1965 represents a pronounced pe- ated with stronger support among White voters for riod of racial change and conflict in the American West, Proposition 14.Because many Anglo-Californians in and key features of the SGM afford a unique opportu- the early 1960s made housing decisions before this de- nity to assess the causal effect of racial threat on White mographic shock took place,we have increased confi- voting behavior.First,the residential decisions of the dence that the SGM provides a rare test of racial threat study group(Whites)were largely made in the absence that ameliorates concern over selection bias. of the treatment group (African Americans).The in- terpretation of findings from prior observational stud- ies of racial threat are often marred by concerns over THE SECOND GREAT MIGRATION AND selection bias;however,in the case of the SGM.res- PROPOSITION 14 idential decisions by Whites were made largely with- out consideration of the Black composition of their Throughout the early twentieth century,the African own or neighboring communities.Second,the migra- American population in California was small and tion of African Americans into California was rapid concentrated in a handful of census tracts designated and concentrated in a few cities,increasing our confi- specifically for non-Whites.The 1940 decennial census, dence that the 1964 vote preceded much of the White conducted immediately before the start of the SGM flight that occurred between mid-1960 to 1980 follow- indicates that African Americans comprised less than ing the Watts Riots,the overturning of Proposition 2%of the state population and less than 3%of the 14 by the Supreme Court,and school desegregation population in urban counties that would come to (Schneider 2008).In short,we treat the rapid increase house the largest Black populations.Holding aside the in California's Black population as a racially threaten- Black population,the non-Black minority population ing "shock"to White society and a potentially impor- in California in 1940 was only 2.7%,leaving the state tant source of White support for Proposition 14. nearly 96%White 4号 The SGM drastically changed this,and represents one of the largest demographic shocks to White soci- EMPIRICAL STRATEGY AND DATA 'asn ety in contemporary American history.By 1960,Cal- ifornia's Black population grew by over 600%to ap- As the SGM involved the drastic growth of Black proximately 885,000.In a number of cities,the Black populations in key areas throughout the state of Cal- population exploded:Berkeley,Emeryville,Richmond ifornia,our empirical strategy centers upon analyz- and Vallejo all saw their Black populations expand by ing the effect of spatial proximity to Black growth ten percentage points or more.In Compton,the Black cities on White support for Proposition 14.Theories of population grew from zero to nearly 40 percent by 1960 racial threat are rooted in Key's (1949)proposition that Figure 1 displays the cities with the highest Black pop- White political behavior in the American south was ulation growth.This population growth strained hous- partly a consequence of the presence of African Amer- ing in the few Black neighborhoods throughout the icans in their communities.More recent work,however, state,increasing demand for housing in neighboring argues that it is the in-migration and growth of an out- communities (HoSang 2010).As the Black commu- group that serves as a motivating shock to White po- 575.1018 nity grew,political elites and homeowners sought to litical behavior (Green,Strolovitch,and Wong,1998; protect White communities from what they saw as a Hopkins 2009;Newman 2013).Following this work, threat to home values and neighborhood identity(Lip- and that by Enos(2016),we conceptualize racial threat sitz 1996).Together,these actors maintained racial ex as the motivating effect on White political behavior of clusion through a variety of official and unofficial poli- drastic changes in a spatially proximate Black popu- cies,leading to some of the most entrenched segrega- lation.Given that theories of racial threat argue that tion in the nation (HoSang 2010). the psychological salience of a group is a function of its The election of state legislator William Rumford(D) size and spatial proximity(Enos 2016),we conceptual- in 1949 and Governor Pat Brown (D)in 1958 aided ize our "treatment"as the proximity of White voters to in the passage of several anti-discrimination measures, epicenters of Black population growth. precipitating the White backlash that culminated in We constructed a dataset from historical administra- Proposition 14.Real estate interests,politicians,and tive data from the U.S.Census Bureau and the Office of evangelical church leaders coordinated to collect sig- the Secretary of State.The data is provided at the Cen- eys natures for a proposition to amend the state consti- sus place (i.e.,city)level,the finest level of aggregation tution,protecting what White residents believed was we could acquire from historical sources.In total,our their right to discriminate.The measure,Proposition full dataset includes voting results for 392 cities in Cal- 14,passed 65 to 35 percent with overwhelming sup- ifornia.Because we are primarily interested in White port from White Californians who,according to the voting behavior,we subset the data for our analyses to CA Field Poll surveys,supported the measure by 3 cities that were 90%or greater White(n=340)in 1960. to 1 (HoSang 2010).Less than one year after the Our dependent variable is city-level vote for Proposi- passage of Proposition 14,the Watts Riot broke out tion 14 (mean 65.7%,sd =10.6%)as reported by in Los Angeles,which was one of the most destruc- the 1964 California Secretary of State Supplement to tive urban race riots in American history (Queally the Statement of the Vote.Our key independent vari- 2015). able is city proximity to its nearest Black growth city.To 1105

Protecting the Right to Discriminate proximity to rapidly diversifying cities to be associ￾ated with stronger support among White voters for Proposition 14. Because many Anglo-Californians in the early 1960s made housing decisions before this de￾mographic shock took place, we have increased confi￾dence that the SGM provides a rare test of racial threat that ameliorates concern over selection bias. THE SECOND GREAT MIGRATION AND PROPOSITION 14 Throughout the early twentieth century, the African American population in California was small and concentrated in a handful of census tracts designated specifically for non-Whites. The 1940 decennial census, conducted immediately before the start of the SGM, indicates that African Americans comprised less than 2% of the state population and less than 3% of the population in urban counties that would come to house the largest Black populations. Holding aside the Black population, the non-Black minority population in California in 1940 was only 2.7%, leaving the state nearly 96% White. The SGM drastically changed this, and represents one of the largest demographic shocks to White soci￾ety in contemporary American history. By 1960, Cal￾ifornia’s Black population grew by over 600% to ap￾proximately 885,000. In a number of cities, the Black population exploded: Berkeley, Emeryville, Richmond, and Vallejo all saw their Black populations expand by ten percentage points or more. In Compton, the Black population grew from zero to nearly 40 percent by 1960. Figure 1 displays the cities with the highest Black pop￾ulation growth. This population growth strained hous￾ing in the few Black neighborhoods throughout the state, increasing demand for housing in neighboring communities (HoSang 2010). As the Black commu￾nity grew, political elites and homeowners sought to protect White communities from what they saw as a threat to home values and neighborhood identity (Lip￾sitz 1996). Together, these actors maintained racial ex￾clusion through a variety of official and unofficial poli￾cies, leading to some of the most entrenched segrega￾tion in the nation (HoSang 2010). The election of state legislator William Rumford (D) in 1949 and Governor Pat Brown (D) in 1958 aided in the passage of several anti-discrimination measures, precipitating the White backlash that culminated in Proposition 14. Real estate interests, politicians, and evangelical church leaders coordinated to collect sig￾natures for a proposition to amend the state consti￾tution, protecting what White residents believed was their right to discriminate. The measure, Proposition 14, passed 65 to 35 percent with overwhelming sup￾port from White Californians who, according to the CA Field Poll surveys, supported the measure by 3 to 1 (HoSang 2010). Less than one year after the passage of Proposition 14, the Watts Riot broke out in Los Angeles, which was one of the most destruc￾tive urban race riots in American history (Queally 2015). In sum, 1940 to 1965 represents a pronounced pe￾riod of racial change and conflict in the American West, and key features of the SGM afford a unique opportu￾nity to assess the causal effect of racial threat on White voting behavior. First, the residential decisions of the study group (Whites) were largely made in the absence of the treatment group (African Americans). The in￾terpretation of findings from prior observational stud￾ies of racial threat are often marred by concerns over selection bias; however, in the case of the SGM, res￾idential decisions by Whites were made largely with￾out consideration of the Black composition of their own or neighboring communities. Second, the migra￾tion of African Americans into California was rapid and concentrated in a few cities, increasing our confi￾dence that the 1964 vote preceded much of the White flight that occurred between mid-1960 to 1980 follow￾ing the Watts Riots, the overturning of Proposition 14 by the Supreme Court, and school desegregation (Schneider 2008). In short, we treat the rapid increase in California’s Black population as a racially threaten￾ing “shock” to White society and a potentially impor￾tant source of White support for Proposition 14. EMPIRICAL STRATEGY AND DATA As the SGM involved the drastic growth of Black populations in key areas throughout the state of Cal￾ifornia, our empirical strategy centers upon analyz￾ing the effect of spatial proximity to Black growth cities on White support for Proposition 14. Theories of racial threat are rooted in Key’s (1949) proposition that White political behavior in the American south was partly a consequence of the presence of African Amer￾icans in their communities.More recent work, however, argues that it is the in-migration and growth of an out￾group that serves as a motivating shock to White po￾litical behavior (Green, Strolovitch, and Wong, 1998; Hopkins 2009; Newman 2013). Following this work, and that by Enos (2016), we conceptualize racial threat as the motivating effect on White political behavior of drastic changes in a spatially proximate Black popu￾lation. Given that theories of racial threat argue that the psychological salience of a group is a function of its size and spatial proximity (Enos 2016), we conceptual￾ize our “treatment” as the proximity of White voters to epicenters of Black population growth. We constructed a dataset from historical administra￾tive data from the U.S. Census Bureau and the Office of the Secretary of State. The data is provided at the Cen￾sus place (i.e., city) level, the finest level of aggregation we could acquire from historical sources. In total, our full dataset includes voting results for 392 cities in Cal￾ifornia. Because we are primarily interested in White voting behavior, we subset the data for our analyses to cities that were 90% or greater White (n = 340) in 1960. Our dependent variable is city-level vote for Proposi￾tion 14 (mean = 65.7%, sd = 10.6%) as reported by the 1964 California Secretary of State Supplement to the Statement of the Vote. Our key independent vari￾able is city proximity to its nearest Black growth city.To 1105 Downloaded from https://www.cambridge.org/core. Shanghai JiaoTong University, on 26 Oct 2018 at 03:56:49, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0003055418000448

蒙 Tyler T.Reny FIGURE 1.Map of Rapidly Growing Black Cities 1940-1960 and 口 Benjamin Pasadena J.Newman Pittsburg Elsinore Black Pop Growth 1940-1960 0%-5% 6%-10% 11%-20% >20% Note:City-level African American population growth 1940-1960 in Southern (panel A)and Northern (panel B)California.98h percentile growth cities include Compton,Emeryville,Richmond. Vallejo,and Berkeley and additional 95th percentile growth cities of Pasadena,Elsinore,Menlo Park,Pittsburg.A map of the central valley,including 95th percentile growth cities of Bakersfield. Fowler,and Madera.is presented in Figure M.1

Tyler T. Reny and Benjamin J. Newman FIGURE 1. Map of Rapidly Growing Black Cities 1940–1960 Compton Pasadena Elsinore Black Pop Growth 1940−1960 0%−5% 6%−10% 11%−20% >20% Richmond Vallejo Pittsburg Emeryville Berkeley Menlo Park Note: City-level African American population growth 1940–1960 in Southern (panel A) and Northern (panel B) California. 98th percentile growth cities include Compton, Emeryville, Richmond, Vallejo, and Berkeley and additional 95th percentile growth cities of Pasadena, Elsinore, Menlo Park, Pittsburg. A map of the central valley, including 95th percentile growth cities of Bakersfield, Fowler, and Madera, is presented in Figure M.1. 1106 Downloaded from https://www.cambridge.org/core. Shanghai JiaoTong University, on 26 Oct 2018 at 03:56:49, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0003055418000448

Protecting the Right to Discriminate TABLE 1.The Effect of Proximity to Black Growth Areas on Support for Proposition 14 Prop14,1964 0008140000/L0LL (1) (2) (3) (4) Proximity 5.94** 5.88* 36.06* (0.80) (1.46) (12.33) Proximity Squared 35.14 (14.94) Proximity Cubed 10.22* (4.90) Log Proximity 10.85* (2.57) Median Income -0.72 -1.07 -0.83 (0.90) (1.06) (0.93) Unemployment -6.53 -10.31 -5.62 (31.61) (34.28) (31.23) Homeownership -7.14 -4.89 -7.00 (6.97 (7.12) (6.93) Partisan Composition(%D) 1.49 -3.79 0.33 (5.86) (6.95) (5.90) Population Density 0.01 0.01 0.01 (0.01) (0.01) (0.01) Constant 70.69* 81.06 89.64** 83.21* (0.84) (7.81) (10.45) 4号 (8.21) v 337 181 181 181 0.12 0.08 0.12 0.09 Adjusted R2 0.12 0.05 0.08 0.06 Residual Std.Error 9.50(df=335) 9.74(df=174) 9.59(df=172) 9.68(df=174) F Statistic 46.34*(df=1;335)2.63*(df=6;174) 2.98(df=8;172)3.02*(df=6;174) Note:OLS coefficients with heteroskedastic robust standard errors in parentheses.90%and greater White cities.Columns 1 and 2 assume linear relationship between proximity and city-level Proposition 14 vote.Columns 3 and 4 allow for non-linearity. *p<0.1;*p<0.05:*p<0.01(two-tailed). calculate this measure,we used city-level demographic partisanship as a confounder.Measures of population estimates from the 1940 and 1960 U.S.Census files to density control for variation in geographic and popula- calculate percentage point change in the Black popu- tion size of each city.As poorer and more racially con- lation (mean 1.17%,s.d.=3.97%).Figure 1 displays servative Whites might be more likely to live adjacent 575.1018 the level of Black growth in cities throughout Southern to high Black growth cities,we include controls for me- and Northern California.We identified Black growth dian income,home ownership,and unemployment (de- cities as those in the 98th percentile of Black population scriptive statistics are included in Online Appendix C). growth,capturing cities that experienced Black pop- ulation growth between 10 and 40 percentage points over the twenty-year span,constructed a matrix of Eu- RESULTS clidean distances between the centroids of all Cali- We begin by estimating the bivariate relationship be- fornia cities,and defined proximity as the distance in tween proximity and city-level vote for Proposition 14 miles from the nearest Black growth city (mean =-69.8. for cities with 90%or greater White population,the sd =64).For ease of interpretation,we divide this vari- results of which are presented in column 1 of Table 1. able by 100 and multiplied by-1,so that a unit increase The results indicate that proximity to cities with rapidly indicates a 100-mile increase in proximity.By using a growing Black populations is associated with higher continuous treatment indicator on non-nested data,we levels of White support for Proposition 14.The benefit bypass the concern in the racial threat literature over of this analysis is that it maximizes statistical power,as the sensitivity of results using multilevel data to the the analyses including control variables have a reduced choice of administrative boundary (Tam Cho and Baer sample size due to the limited coverage of smaller cities 2011;Voss 1996;for more discussion see Online Ap- in the 1960 decennial census.As the relationship in pendix B). column 1 could be driven by confounders,column 2 We gathered a number of additional control vari- presents the results from a model including city-level ables at the census tract level and merged them with our dataset via a weighted spatial join.We obtained 1964 voter registration figures for cities from the Berke- ley School of Law Center for Research and control for 1 The U.S.Census did not collect certain contextual variables for cities with fewer than 1,000 residents,an issue we address in Online city-level percent Democrat (of registered)to rule out Appendix E. 1107

Protecting the Right to Discriminate TABLE 1. The Effect of Proximity to Black Growth Areas on Support for Proposition 14 Prop 14, 1964 (1) (2) (3) (4) Proximity 5.94∗∗∗ 5.88∗∗∗ 36.06∗∗∗ (0.80) (1.46) (12.33) Proximity Squared 35.14∗∗ (14.94) Proximity Cubed 10.22∗∗ (4.90) Log Proximity 10.85∗∗∗ (2.57) Median Income − 0.72 − 1.07 − 0.83 (0.90) (1.06) (0.93) Unemployment − 6.53 − 10.31 − 5.62 (31.61) (34.28) (31.23) Homeownership − 7.14 − 4.89 − 7.00 (6.97) (7.12) (6.93) Partisan Composition (%D) 1.49 − 3.79 0.33 (5.86) (6.95) (5.90) Population Density 0.01 0.01 0.01 (0.01) (0.01) (0.01) Constant 70.69∗∗∗ 81.06∗∗∗ 89.64∗∗∗ 83.21∗∗∗ (0.84) (7.81) (10.45) (8.21) N 337 181 181 181 R2 0.12 0.08 0.12 0.09 Adjusted R2 0.12 0.05 0.08 0.06 Residual Std. Error 9.50 (df = 335) 9.74 (df = 174) 9.59 (df = 172) 9.68 (df = 174) F Statistic 46.34∗∗∗ (df = 1; 335) 2.63∗∗ (df = 6; 174) 2.98∗∗∗ (df = 8; 172) 3.02∗∗∗ (df = 6; 174) Note: OLS coefficients with heteroskedastic robust standard errors in parentheses. 90% and greater White cities. Columns 1 and 2 assume linear relationship between proximity and city-level Proposition 14 vote. Columns 3 and 4 allow for non-linearity. ∗p < 0.1; ∗∗p < 0.05; ∗∗∗p < 0.01 (two-tailed). calculate this measure, we used city-level demographic estimates from the 1940 and 1960 U.S. Census files to calculate percentage point change in the Black popu￾lation (mean = 1.17%, s.d. = 3.97%). Figure 1 displays the level of Black growth in cities throughout Southern and Northern California. We identified Black growth cities as those in the 98th percentile of Black population growth, capturing cities that experienced Black pop￾ulation growth between 10 and 40 percentage points over the twenty-year span, constructed a matrix of Eu￾clidean distances between the centroids of all Cali￾fornia cities, and defined proximity as the distance in miles from the nearest Black growth city (mean = -69.8, sd = 64). For ease of interpretation, we divide this vari￾able by 100 and multiplied by -1, so that a unit increase indicates a 100-mile increase in proximity. By using a continuous treatment indicator on non-nested data, we bypass the concern in the racial threat literature over the sensitivity of results using multilevel data to the choice of administrative boundary (Tam Cho and Baer 2011; Voss 1996; for more discussion see Online Ap￾pendix B). We gathered a number of additional control vari￾ables at the census tract level and merged them with our dataset via a weighted spatial join. We obtained 1964 voter registration figures for cities from the Berke￾ley School of Law Center for Research and control for city-level percent Democrat (of registered) to rule out partisanship as a confounder. Measures of population density control for variation in geographic and popula￾tion size of each city. As poorer and more racially con￾servative Whites might be more likely to live adjacent to high Black growth cities, we include controls for me￾dian income, home ownership, and unemployment (de￾scriptive statistics are included in Online Appendix C). RESULTS We begin by estimating the bivariate relationship be￾tween proximity and city-level vote for Proposition 14 for cities with 90% or greater White population, the results of which are presented in column 1 of Table 1. The results indicate that proximity to cities with rapidly growing Black populations is associated with higher levels of White support for Proposition 14. The benefit of this analysis is that it maximizes statistical power, as the analyses including control variables have a reduced sample size due to the limited coverage of smaller cities in the 1960 decennial census.1 As the relationship in column 1 could be driven by confounders, column 2 presents the results from a model including city-level 1 The U.S. Census did not collect certain contextual variables for cities with fewer than 1,000 residents, an issue we address in Online Appendix E. 1107 Downloaded from https://www.cambridge.org/core. Shanghai JiaoTong University, on 26 Oct 2018 at 03:56:49, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0003055418000448

Tyler T.Reny and Benjamin J.Newman FIGURE 2.Effect of Proximity to Black Growth Areas on Support for Proposition 14 80 80 80 70 60 60 60 0 50 4级 50 LO 50 L 體 -200-150-100 -50 0 -200-150 -100 -50 -200-150-100 -50 0 Prox Growing Black Cities Prox Growing Black Cities Prox Growing Black Cities (miles) (miles) (miles) Note:Lines indicate predicted city-level Proposition 14 vote and 95%confidence interval moving from 200(2 s.d.below mean)to zero miles from Black growth cities for models 2,3,and 4 from Table 1.All other variables are set to their means. 4号元 control variables.As shown in column 2.the relation- when including county-level fixed effects(Table D.2). ship between proximity to nearest Black growth city Given our interest in the behavior of White voters,we and support for Proposition 14 holds.To assess the ro- demonstrate that our results hold when further restrict- bustness of these results when accounting for possi- ing the analysis to cities that were 95%or greater White ble nonlinearity in the relationship between proximity in 1960(Table E.1),and when employing an ecologi- and city-level voting for Proposition 14,we estimate a cal inference model to estimate support for Proposi- model including a squared and cubed proximity term tion 14 among White voters (Table F.1).Alternatively, (column 3)and logged proximity (column 4).While our results hold when lifting the percent White sam- these results indicate a non-linear relationship between ple restrictions (Table E.1).Additionally.our results these two variables,it is difficult to compare the aver- hold when using different thresholds to define a "treat- age impact of proximity across models.To do so we es- ment"city (Table G.1)and when measuring proximity timate predicted values and first-differences. to Black growth cities using driving distances and times We plot predicted city-level Proposition 14 vote in (Table G.2).To account for possible post-treatment Figure 2 for models 2(panel 1),3 (panel 2),and 4 bias,we demonstrate that our results hold when re- (panel 3)from Table 1.In panel 1,holding all other placing our 1960 control variables with pre-treatment variables at their means,we find that a city located (i.e.,before the SGM)variables derived from the 1940 adjacent to a Black growth city is estimated to sup- Census (Table H.1).While column 1 of Table 1 demon port Proposition 14 at 72.4%(95%CI:[70.5%,74.3%]), strates that our results hold when analyzing all predom- whereas estimated support in a city 200 miles away inantly White California cities,to further ensure that (mean-2s.d)is60.6%(95%CI:[56.1%,65.1%]), our results are not driven by the mid-to-large cities cov- a difference of 11.8 percentage points (95%CI:[6%, ered by the 1940 and 1960 Censuses,we demonstrate 172%).Looking at panel 2,we find that the effect of that the effect of proximity holds when analyzing the proximity seems to be most pronounced in the first 75 n 187 smaller-sized cities not covered by these cen- miles.The effect of moving from a city 75 miles away suses (Table E.1).Next,as placebo tests,we demon- to one adjacent to a Black growth city is 11.5 percent- strate that the positive effect of proximity to Black age points (95%CI:[5.4%,18.1%]).The difference growth cities is restricted to Proposition 14 and not ob- across the full range of proximities is only a slightly served when analyzing race-neutral propositions (Ta- larger12.7%(95%CI:[4.3%,20.6%]).In panel3,us- ble I.1).Lastly,we uncover complementary results to ing logged proximity,we find an almost identical first those presented in Table 1 when analyzing individual- difference of 12.6%(95%CI:[6.4%,18.9%]).Because level survey data estimating White support for Propo- the effect of proximity is similar in all models,for ease sition 14 as a function of Black population growth in of interpretation we will use the linear specification for respondents'counties of residence(Table J.1). the remaining models in the article. While the SGM and the 1964 election offer a case where selection bias is substantially reduced,such con- ROBUSTNESS CHECKS cern is not entirely removed.Black residents did not settle at random in California cities.Further,while We demonstrate in the Online Appendix that our re- "White flight"from California cities was most pro- sults hold when using beta regression (Table D.1)and nounced between mid-1960 to 1980(Schneider 2008).it 1108

Tyler T. Reny and Benjamin J. Newman FIGURE 2. Effect of Proximity to Black Growth Areas on Support for Proposition 14 50 60 70 80 −200 −150 −100 −50 0 Prox Growing Black Cities (miles) Predicted Vote Prop 14 (%) 50 60 70 80 −200 −150 −100 −50 0 Prox Growing Black Cities (miles) 50 60 70 80 −200−150 −100 −50 0 Prox Growing Black Cities (miles) Note: Lines indicate predicted city-level Proposition 14 vote and 95% confidence interval moving from 200 (2 s.d. below mean) to zero miles from Black growth cities for models 2, 3, and 4 from Table 1. All other variables are set to their means. control variables. As shown in column 2, the relation￾ship between proximity to nearest Black growth city and support for Proposition 14 holds. To assess the ro￾bustness of these results when accounting for possi￾ble nonlinearity in the relationship between proximity and city-level voting for Proposition 14, we estimate a model including a squared and cubed proximity term (column 3) and logged proximity (column 4). While these results indicate a non-linear relationship between these two variables, it is difficult to compare the aver￾age impact of proximity across models. To do so we es￾timate predicted values and first-differences. We plot predicted city-level Proposition 14 vote in Figure 2 for models 2 (panel 1), 3 (panel 2), and 4 (panel 3) from Table 1. In panel 1, holding all other variables at their means, we find that a city located adjacent to a Black growth city is estimated to sup￾port Proposition 14 at 72.4% (95% CI: [70.5%, 74.3%]), whereas estimated support in a city 200 miles away (mean – 2 s.d.) is 60.6% (95% CI: [56.1%, 65.1%]), a difference of 11.8 percentage points (95% CI: [6%, 17.2%]). Looking at panel 2, we find that the effect of proximity seems to be most pronounced in the first 75 miles. The effect of moving from a city 75 miles away to one adjacent to a Black growth city is 11.5 percent￾age points (95% CI: [5.4%, 18.1%]). The difference across the full range of proximities is only a slightly larger 12.7% (95% CI: [4.3%, 20.6%]). In panel 3, us￾ing logged proximity, we find an almost identical first difference of 12.6% (95% CI: [6.4%, 18.9%]). Because the effect of proximity is similar in all models, for ease of interpretation we will use the linear specification for the remaining models in the article. ROBUSTNESS CHECKS We demonstrate in the Online Appendix that our re￾sults hold when using beta regression (Table D.1) and when including county-level fixed effects (Table D.2). Given our interest in the behavior of White voters, we demonstrate that our results hold when further restrict￾ing the analysis to cities that were 95% or greater White in 1960 (Table E.1), and when employing an ecologi￾cal inference model to estimate support for Proposi￾tion 14 among White voters (Table F.1). Alternatively, our results hold when lifting the percent White sam￾ple restrictions (Table E.1). Additionally, our results hold when using different thresholds to define a “treat￾ment” city (Table G.1) and when measuring proximity to Black growth cities using driving distances and times (Table G.2). To account for possible post-treatment bias, we demonstrate that our results hold when re￾placing our 1960 control variables with pre-treatment (i.e., before the SGM) variables derived from the 1940 Census (Table H.1).While column 1 of Table 1 demon￾strates that our results hold when analyzing all predom￾inantly White California cities, to further ensure that our results are not driven by the mid-to-large cities cov￾ered by the 1940 and 1960 Censuses, we demonstrate that the effect of proximity holds when analyzing the n = 187 smaller-sized cities not covered by these cen￾suses (Table E.1). Next, as placebo tests, we demon￾strate that the positive effect of proximity to Black growth cities is restricted to Proposition 14 and not ob￾served when analyzing race-neutral propositions (Ta￾ble I.1). Lastly, we uncover complementary results to those presented in Table 1 when analyzing individual￾level survey data estimating White support for Propo￾sition 14 as a function of Black population growth in respondents’ counties of residence (Table J.1). While the SGM and the 1964 election offer a case where selection bias is substantially reduced, such con￾cern is not entirely removed. Black residents did not settle at random in California cities. Further, while “White flight” from California cities was most pro￾nounced between mid-1960 to 1980 (Schneider 2008),it 1108 Downloaded from https://www.cambridge.org/core. Shanghai JiaoTong University, on 26 Oct 2018 at 03:56:49, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0003055418000448

Protecting the Right to Discriminate FIGURE 3.Reanalysis by Residential Tenure,White Growth,and Housing Markets 0008140000/L0LL Acquired Before 1940-Below Median Acquired Before 1940-Above Median White Growth-Below Median White Growth-Above Median Jolop//.sdu Control-Contracting Housing Control-Inflating Home Values 0.0 2.5 5.0 7.5 10.0 Proximity Coefficient Note:OLS regression coefficients and heteroskedastic robust standard errors of proximity to Black growth cities.90%or greater White cities.The first panel splits the sample at median percent of city residents who moved into their residence prior to 1940,the second splits the sample at median White growth(1940-1960),and the final controls for proximity to cities with the largest drop in housing availability or increase in home values.Full model results available in Appendix Table K.1. is possible that substantial residential sorting occurred cities is stronger in White cities with below median between 1940 to 1964.One method for addressing this White growth (range:[-172,-0.003],mean =-2.2). 4号 possibility is to re-analyze our model among targeted It is also possible that "redlining"(Rothstein 2017) subsamples of the data. forced African Americans to settle in neighborhoods First,we explore whether our results hold when deemed less desirable,which may have contained looking at White cities with higher levels of White resi- poorer and more racially conservative Whites.Such dential tenure.The 1960 decennial census includes data possibility could explain the relationship we observe on when individuals moved into their residence.Us- between proximity to Black growth cities and White ing this data,we can restrict our analysis to White support for Proposition 14.This possibility is not sug- cities where a higher rate of residents reported hav- gested by the data,as proximity to Black growth cities ing moved in before 1940(i.e.,before the start of the is not strongly correlated with pretreatment indicators SGM).The first row of results in Figure 3(full results of 1940 socioeconomic standing.such as median home 是 available in Table K.1)demonstrates that the effect of values (r =0.10),homeownership rates (r =0.15),or proximity to Black growth cities holds(p<0.01)when unemployment rates (r =0.01).Another concern is looking at above-median tenure cities.This result is that our results are due to housing competition.It is critical,as it indicates that when conducting a test re- possible that proximity to Black growth cities is cap- 575.1018 ducing White residential selection bias,the estimated turing the effect of proximity to areas experiencing in- effect of proximity remains positive and statistically creased competition for housing.The bottom panel of significant. Figure 3 display the coefficient for proximity to Black Second,we can assess whether our results hold growth cities when adding a control variable for prox- when looking at majority-White cities with lower lev- imity to cities with the most drastic(95th percentile) els of White population growth between 1940-1960. contraction in available housing units(i.e.,vacant units Racially conservative Whites residing in cities experi- for sale or rent)between 1940-1960,or the most dras- encing Black in-migration may have fled to adjacent tic increases in home values between 1940-1960.We all-White cities,taking their racially threatened atti- find the effect of proximity holds in both models (p< tudes with them.Such a process could have induced the 0.001),indicating that proximity to Black growth cities findings we observe,suggesting they are less due to the remains positive and significant when holding constant activation of racial threat among Whites residing in proximity to areas manifesting symptoms of housing proximity to Black growth cities and due instead to competition. the migration of racially threatened Whites to neigh- boring cities.While we find suggestive evidence that White populations contracted the most in cities within CONCLUSION five miles of Black growth cities,we find no evidence that White population growth disproportionately oc- Exploiting a large demographic shift during the SGM, curred within neighboring cities five or more miles we sidestep some of the concerns of existing observa- away from Black growth cities(see Figure L.1).More- tional research on racial threat and find evidence that over,the results presented in Figure 3 belie this con White residential proximity to growing Black popula- cern:rather than being endemic or more pronounced tions in California was positively associated with voting in White cities experiencing high White population for Proposition 14 in the 1964 election.As such,our growth,we find the effect of proximity to Black growth study makes a novel and compelling contribution to 1109

Protecting the Right to Discriminate FIGURE 3. Reanalysis by Residential Tenure, White Growth, and Housing Markets 0.0 2.5 5.0 7.5 10.0 Acquired Before 1940 − Above Median Acquired Before 1940 − Below Median White Growth − Above Median White Growth − Below Median Control − Inflating Home Values Control − Contracting Housing Proximity Coefficient Note: OLS regression coefficients and heteroskedastic robust standard errors of proximity to Black growth cities. 90% or greater White cities. The first panel splits the sample at median percent of city residents who moved into their residence prior to 1940, the second splits the sample at median White growth (1940-1960), and the final controls for proximity to cities with the largest drop in housing availability or increase in home values. Full model results available in Appendix Table K.1. is possible that substantial residential sorting occurred between 1940 to 1964. One method for addressing this possibility is to re-analyze our model among targeted subsamples of the data. First, we explore whether our results hold when looking at White cities with higher levels of White resi￾dential tenure. The 1960 decennial census includes data on when individuals moved into their residence. Us￾ing this data, we can restrict our analysis to White cities where a higher rate of residents reported hav￾ing moved in before 1940 (i.e., before the start of the SGM). The first row of results in Figure 3 (full results available in Table K.1) demonstrates that the effect of proximity to Black growth cities holds (p < 0.01) when looking at above-median tenure cities. This result is critical, as it indicates that when conducting a test re￾ducing White residential selection bias, the estimated effect of proximity remains positive and statistically significant. Second, we can assess whether our results hold when looking at majority-White cities with lower lev￾els of White population growth between 1940–1960. Racially conservative Whites residing in cities experi￾encing Black in-migration may have fled to adjacent all-White cities, taking their racially threatened atti￾tudes with them. Such a process could have induced the findings we observe, suggesting they are less due to the activation of racial threat among Whites residing in proximity to Black growth cities and due instead to the migration of racially threatened Whites to neigh￾boring cities. While we find suggestive evidence that White populations contracted the most in cities within five miles of Black growth cities, we find no evidence that White population growth disproportionately oc￾curred within neighboring cities five or more miles away from Black growth cities (see Figure L.1). More￾over, the results presented in Figure 3 belie this con￾cern: rather than being endemic or more pronounced in White cities experiencing high White population growth, we find the effect of proximity to Black growth cities is stronger in White cities with below median White growth (range: [−17.2, −0.003], mean = −2.2). It is also possible that “redlining” (Rothstein 2017) forced African Americans to settle in neighborhoods deemed less desirable, which may have contained poorer and more racially conservative Whites. Such possibility could explain the relationship we observe between proximity to Black growth cities and White support for Proposition 14. This possibility is not sug￾gested by the data, as proximity to Black growth cities is not strongly correlated with pretreatment indicators of 1940 socioeconomic standing, such as median home values (r = 0.10), homeownership rates (r = 0.15), or unemployment rates (r = 0.01). Another concern is that our results are due to housing competition. It is possible that proximity to Black growth cities is cap￾turing the effect of proximity to areas experiencing in￾creased competition for housing. The bottom panel of Figure 3 display the coefficient for proximity to Black growth cities when adding a control variable for prox￾imity to cities with the most drastic (95th percentile) contraction in available housing units (i.e., vacant units for sale or rent) between 1940–1960, or the most dras￾tic increases in home values between 1940–1960. We find the effect of proximity holds in both models (p < 0.001), indicating that proximity to Black growth cities remains positive and significant when holding constant proximity to areas manifesting symptoms of housing competition. CONCLUSION Exploiting a large demographic shift during the SGM, we sidestep some of the concerns of existing observa￾tional research on racial threat and find evidence that White residential proximity to growing Black popula￾tions in California was positively associated with voting for Proposition 14 in the 1964 election. As such, our study makes a novel and compelling contribution to 1109 Downloaded from https://www.cambridge.org/core. Shanghai JiaoTong University, on 26 Oct 2018 at 03:56:49, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0003055418000448

Tyler T.Reny and Benjamin J.Newman the existing scholarship on the role of racial threat in Gregory,James.2005.The Southern Diaspora:How the Great Mi- shaping White political behavior.Remarkably,demo- grations of Black and White Southerners Transformed America. graphic change remains a politicized and salient issue Chapel Hill,NC:University of North Carolina Press. fifty years after the referendum we study.As the na- Hopkins,Daniel J.2009."The Diversity Discount:When Increasing Ethnic and Racial Diversity Precents Tax Increases."The Journal tion continues to diversify,understanding the impact of of Politics 71(1):160-77 these demographic shifts on the attitudes and behav- Hopkins,Daniel J.2012."Flooded Communities."Political Research iors of native-born residents is increasingly crucial to Ouarterly 65 (2):443-59. understanding national political trends writ large. HoSang,Daniel.2010.Racial Propositions:Ballot Initiatives and the Making of Postwar California.Berkeley,CA:University of Cali- fornia Press. Key,V.O.1949.Southern Politics:In State and Nation.New York: SUPPLEMENTARY MATERIAL Vintage Books. Lipsitz,George.1996.The Possessive Investment in Whiteness:How To view supplementary material for this article,please White People Profit from Identity Politics.Philadelphia,PA:Temple visit https:doi.org/10.1017/S0003055418000448 University Press. Replication materials can be found on Dataverse at: Newman,Benjamin J.2013."Acculturating Contexts and Anglo Op- https://doi.org/10.7910/DVN/UAQZRO. position to Immigration in the United States."American Journal of Political Science 57 (2):374-90. Oliver,J.Eric.2010.The Paradoxes of Integration:Race,Neighbor- hood,and Civic Life in Multiethnic America.Chicago:University REFERENCES of Chicago Press. Oliver,J.Eric,and Janelle Wong.2003."Intergroup Prejudice in Mul- Acharya,Avidit,Matthew Blackwell,and Maya Sen.2016."The Polit- tiethnic Settings."American Journal of Political Science 47 (4): ical Legacy of American Slavery."Journal of Politics 78(3):621-41 567. Branton,Regina P.,and Bradford S.Jones.2005."Reexamining Queally,James.2015."Watts Riots:Traffic stop was the spark that Racial Attitudes:The Conditional Relationship between Diversity ignited days of destruction in L.A."Los Angeles Times.http: and Socioeconomic Environment."American Journal of Politica //www.latimes.com/local/lanow/la-me-In-watts-riots-explainer- Science49(2):359-72. 20150715-htmlstory.html Clark,William A.V.1992."Residential Preferences and Residential Rocha,Rene,and Rodolfo Espino.2009."Racial Threat,Residen- Choices in a Multiethnic Context."Demography 29 (3):451-66. tial Segregation,and the Policy Attitudes of Anglos."Political Re. Enos,Ryan.D.2014."Causal Effect of Intergroup Contact on Exclu- search Quarterly 62 (2):415-26. sionary Attitudes."Proceedings of the National Academy of Sci- Rothstein,Richard.2017.The Color of Law:A Forgotten History ences111(10):3699-704. of How Our Government Segregated America.London:Liverlight Enos,Ryan D.2016."What the Demolition of Public Housing Publishing. Teaches Us about the Impact of Racial Threat on Political Behav Schneider,Jack.2008."Escape from Los Angeles:White Flight from ior."American Journal of Political Science 60 (1):123-42. Los Angeles and Its Schools,1960-1980."Journal of Urban History Freund,David M.P.2007.Colored Property:State Policy and White 34(6:995-1012 Racial Politics in Suburban America.Chicago:University Of Tam Cho,Wendy K.,and Neil Baer.2011."Environmental Determi- Chicago Press nants of Racial Attitudes Redux:The Critical Decision Related Glaser,James M.2003."Social Context and Inter-Group Political At- to Operationalizing Context."American Politics Research 39 (2) titudes:Experiments in Group Conflict Theory."British Journal of 414-36. Political Science 33(4):607-20 Voss,D.Stephen.1996."Beyond Racial Threat:Failure of an Old Hy- Green,Donald,Dara Z.Strolovitch,and Janelle Wong.1998. pothesis in the New South."Journal of Politics 58 (4):1156-70. "Defended Neighborhoods,Integration,and Racially Motivated Wilkerson,Isabel.2011.The Warmth of Other Suns:The Epic Story Crime."American Journal of Sociology 104(2):372-403. of America's Great Migration.New York:Vintage Books 1110

Tyler T. Reny and Benjamin J. Newman the existing scholarship on the role of racial threat in shaping White political behavior. Remarkably, demo￾graphic change remains a politicized and salient issue fifty years after the referendum we study. As the na￾tion continues to diversify, understanding the impact of these demographic shifts on the attitudes and behav￾iors of native-born residents is increasingly crucial to understanding national political trends writ large. SUPPLEMENTARY MATERIAL To view supplementary material for this article, please visit https://doi.org/10.1017/S0003055418000448 Replication materials can be found on Dataverse at: https://doi.org/10.7910/DVN/UAQZRO. REFERENCES Acharya,Avidit,Matthew Blackwell, and Maya Sen. 2016. “The Polit￾ical Legacy of American Slavery.” Journal of Politics 78 (3): 621–41. Branton, Regina P., and Bradford S. Jones. 2005. “Reexamining Racial Attitudes: The Conditional Relationship between Diversity and Socioeconomic Environment.” American Journal of Political Science 49 (2): 359–72. Clark, William A. V. 1992. “Residential Preferences and Residential Choices in a Multiethnic Context.” Demography 29 (3): 451–66. Enos, Ryan. D. 2014. “Causal Effect of Intergroup Contact on Exclu￾sionary Attitudes.” Proceedings of the National Academy of Sci￾ences 111 (10): 3699–704. Enos, Ryan D. 2016. “What the Demolition of Public Housing Teaches Us about the Impact of Racial Threat on Political Behav￾ior.” American Journal of Political Science 60 (1): 123–42. Freund, David M. P. 2007. Colored Property: State Policy and White Racial Politics in Suburban America. Chicago: University Of Chicago Press. Glaser, James M. 2003. “Social Context and Inter-Group Political At￾titudes: Experiments in Group Conflict Theory.” British Journal of Political Science 33 (4): 607–20. Green, Donald, Dara Z. Strolovitch, and Janelle Wong. 1998. “Defended Neighborhoods, Integration, and Racially Motivated Crime.” American Journal of Sociology 104 (2): 372–403. Gregory, James. 2005. The Southern Diaspora: How the Great Mi￾grations of Black and White Southerners Transformed America. Chapel Hill, NC: University of North Carolina Press. Hopkins, Daniel J. 2009. “The Diversity Discount: When Increasing Ethnic and Racial Diversity Precents Tax Increases.” The Journal of Politics 71(1): 160–77. Hopkins, Daniel J. 2012. “Flooded Communities.” Political Research Quarterly 65 (2): 443–59. HoSang, Daniel. 2010. Racial Propositions: Ballot Initiatives and the Making of Postwar California. Berkeley, CA: University of Cali￾fornia Press. Key, V. O. 1949. Southern Politics: In State and Nation. New York: Vintage Books. Lipsitz, George. 1996. The Possessive Investment in Whiteness: How White People Profit from Identity Politics.Philadelphia,PA:Temple University Press. Newman, Benjamin J. 2013. “Acculturating Contexts and Anglo Op￾position to Immigration in the United States.” American Journal of Political Science 57 (2): 374–90. Oliver, J. Eric. 2010. The Paradoxes of Integration: Race, Neighbor￾hood, and Civic Life in Multiethnic America. Chicago: University of Chicago Press. Oliver, J. Eric, and Janelle Wong. 2003. “Intergroup Prejudice in Mul￾tiethnic Settings.” American Journal of Political Science 47 (4): 567. Queally, James. 2015. “Watts Riots: Traffic stop was the spark that ignited days of destruction in L.A.” Los Angeles Times. http: //www.latimes.com/local/lanow/la-me-ln-watts-riots-explainer- 20150715-htmlstory.html Rocha, Rene, and Rodolfo Espino. 2009. “Racial Threat, Residen￾tial Segregation, and the Policy Attitudes of Anglos.” Political Re￾search Quarterly 62 (2): 415–26. Rothstein, Richard. 2017. The Color of Law: A Forgotten History of How Our Government Segregated America. London: Liverlight Publishing. Schneider, Jack. 2008. “Escape from Los Angeles: White Flight from Los Angeles and Its Schools, 1960–1980.” Journal of Urban History 34 (6): 995–1012. Tam Cho, Wendy K., and Neil Baer. 2011. “Environmental Determi￾nants of Racial Attitudes Redux: The Critical Decision Related to Operationalizing Context.” American Politics Research 39 (2): 414–36. Voss, D. Stephen. 1996. “Beyond Racial Threat: Failure of an Old Hy￾pothesis in the New South.” Journal of Politics 58 (4): 1156–70. Wilkerson, Isabel. 2011. The Warmth of Other Suns: The Epic Story of America’s Great Migration. New York: Vintage Books. 1110 Downloaded from https://www.cambridge.org/core. Shanghai JiaoTong University, on 26 Oct 2018 at 03:56:49, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0003055418000448