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Patterns in the Introduction and Passage of Restrictive Voting Bills are Best Explained by Race

White racial resentment — and not just party and competitiveness alone — goes a long way toward explaining where restrictive voting laws were introduced and passed in 2021.

Published: August 3, 2022

Over the past 18 months, there has been an unpre­ced­en­ted wave of anti-voter legis­la­tion intro­duced and passed across the coun­try. In 2021, at least one bill with a provi­sion restrict­ing access to voting was intro­duced in the legis­lature of every state except Vermont. By early May of this year, nearly 400 restrict­ive bills had been intro­duced in legis­latures nation­wide.

Legis­lat­ors and research­ers have given differ­ent explan­a­tions for this wave. The mostly Repub­lican lawmakers support­ing these bills often argue that the new provi­sions are neces­sary to protect elec­tion integ­rity, despite the absence of wide­spread fraud in Amer­ican elec­tions. Comment­at­ors argue that Repub­lican legis­lat­ors are push­ing to change elec­tion laws to guar­an­tee polit­ical advant­ages for their party. Some past research supports this argu­ment, demon­strat­ing that certain restrict­ive voting policies are most likely to be adop­ted in elect­or­ally compet­it­ive states controlled by Repub­lic­ans. Other schol­ar­ship shows that states pass restrict­ive voting laws when Amer­ic­ans of color have strong and grow­ing polit­ical power.

The Bren­nan Center has developed a unique data set for test­ing these explan­a­tions. Specific­ally, we tracked every restrict­ive voting provi­sion intro­duced in every state legis­lature in 2021 (as we do every year) and used Legis­can data to identify the spon­sors of these bills. We then exam­ine which district-level char­ac­ter­ist­ics are most correl­ated with whether a lawmaker sponsored a restrict­ive voting bill.

We tested several factors, includ­ing the partisan and racial makeup of legis­lat­ive districts and states as well as the racial opin­ions of constitu­ents. Our research shows that racial factors were power­ful predict­ors of spon­sor­ship. This is consist­ent with the theory that “racial back­lash” — a theory describ­ing how white Amer­ic­ans respond to a perceived erosion of power and status by under­min­ing the polit­ical oppor­tun­it­ies of minor­it­ies — is driv­ing this surge of restrict­ive legis­la­tion. To be sure, the data also confirm that partis­an­ship is a power­ful predictor of spon­sor­ship. But even after account­ing for racially polar­ized voting in the United States, we show that racial demo­graph­ics are a power­ful factor inde­pend­ent of party in determ­in­ing where restrict­ive voting laws are intro­duced and passed.

To eval­u­ate the impact that race has on spon­sor­ship, we use two meas­ure­ments. First, we look simply to the racial makeup of the districts repres­en­ted by the bill spon­sors and their home states. Second, we use responses to a survey called the 2020 Cooper­at­ive Elec­tion Study (CES). We lever­age responses to two ques­tions that have been used for years to meas­ure what polit­ical scient­ists call “racial resent­ment.” foot­note1_wx6wxb2 1 Respond­ents are asked how much they agree with the follow­ing state­ments on a scale of 1 to 5: “Irish, Itali­ans, Jewish and many other minor­it­ies over­came preju­dice and worked their way up. Blacks should do the same without any special favors” and “Gener­a­tions of slavery and discrim­in­a­tion have created condi­tions that make it diffi­cult for blacks to work their way out of the lower class.” We reverse code agree­ment with the second state­ment. It’s import­ant to note that this meas­ure does not and cannot identify whether, as the Bren­nan Center’s Ted John­son explains, there’s “a racist bone in your body.”

Instead, it meas­ures how white Amer­ic­ans think about the role of race in polit­ics, and it is gener­ally a good proxy — in the aggreg­ate — for how racially conser­vat­ive Amer­ic­ans are. These scores cannot be used to neatly rank each and every legis­lat­ive district accord­ing to how “racist” it is. Rather, we argue that districts with higher racial resent­ment scores on the survey are gener­ally more likely to feel threatened by Amer­ica’s grow­ing racial diversity. The fact that higher scores are asso­ci­ated with higher rates of spon­sor­ship even after account­ing for partis­an­ship under­scores the explan­at­ory power of these ques­tions. foot­note2_8soe4nf 2 Some research­ers disagree about what precisely these ques­tions capture, given how correl­ated they can be with other conser­vat­ive beliefs like indi­vidu­al­ism, limited govern­ment, and self-reli­ance (see, for instance, this paper). Never­the­less, most polit­ical scient­ists agree that the racial resent­ment score captures import­ant inform­a­tion about Amer­ic­ans’ racial views, and it remains cent­ral to schol­ar­ship on race and polit­ics in the United States.

Our key find­ings at the legis­lat­ive district level include:

  • Repres­ent­at­ives from the whitest districts in the most racially diverse states were the most likely to spon­sor anti-voter bills.
  • Districts with higher racial resent­ment were more likely to be repres­en­ted by lawmakers who sponsored restrict­ive bills.

At the state level, we find:

  • It is the inter­ac­tion between race and partis­an­ship that matters. States with unified Repub­lican control are not uniformly likely to intro­duce or pass restrict­ive provi­sions. In fact, predom­in­antly white states are unlikely to intro­duce or pass restrict­ive provi­sions, regard­less of which party controls the legis­lature. But racially diverse states controlled by Repub­lic­ans are far more likely to intro­duce and pass restrict­ive provi­sions.

End Notes

Legislative District–Level Results: Racial Composition and Sponsorship

We start by explor­ing the rela­tion­ship between race and restrict­ive voting legis­la­tion within states. We iden­ti­fied the legis­lat­ive spon­sor for each restrict­ive provi­sion intro­duced in 2021 using data from Legis­can. We estab­lish a few hypo­theses based on what past research on racial back­lash and legis­lat­ive activ­ity tells us. First, we think that whiter legis­lat­ive districts are more likely to be repres­en­ted by lawmakers who spon­sor restrict­ive legis­la­tion. But that’s not all: we also expect the rela­tion­ship between a district’s white­ness and the like­li­hood that its repres­ent­at­ive sponsored one of these restrict­ive bills will be stronger in more racially diverse states.

In the figure below, we graph the rela­tion­ship between district white­ness and the like­li­hood that a lawmaker sponsored restrict­ive voting laws in whiter states. On the left-hand side, we plot the rela­tion­ship in lower cham­bers; the right-hand side shows the rela­tion­ship in upper cham­bers. foot­note1_76hz973 1 Nebraska’s unicam­eral legis­lature is included in the upper cham­ber models. Here, we aren’t yet account­ing for the fact that race and diversity are correl­ated with partis­an­ship and compet­it­ive­ness; these are just the simple rela­tion­ships between race and legis­lat­ive spon­sor­ship. The bands around the lines repres­ent confid­ence inter­vals, which meas­ure uncer­tainty about the strength of the rela­tion­ships. For more discus­sion of our meth­od­o­logy and results, please see the Tech­nical Appendix at the bottom of this page.

We can see from this figure that there is a relat­ively weak rela­tion­ship between white­ness and spon­sor­ship in a state that’s about 80 percent white. On the left side of each plot — where we’re look­ing at less-white districts — the like­li­hood of being repres­en­ted by a lawmaker who sponsored a restrict­ive bill is low. As we move to the right and look at whiter districts, that prob­ab­il­ity increases slightly. Thus, even in racially homo­gen­ous states, whiter districts are a little more likely to be repres­en­ted by lawmakers who spon­sor restrict­ive voting bills. 

Chart of district demographics and restrictive bill sponsorship

But we expec­ted this rela­tion­ship to be stronger in states with more racial diversity. In the next figure, we add in what the rela­tion­ship between district demo­graph­ics and spon­sor­ship looks like in much more diverse states — defined here as states that are just 50 percent white. The rela­tion­ship between race and spon­sor­ship in the 80 percent white states stays the same as in the previ­ous figure. The rela­tion­ship in less-white states is plot­ted in lighter blue. In this figure, the light-blue line has a much steeper slope, indic­at­ing that there is a far larger differ­ence between less-white and whiter districts in these states — just as we hypo­thes­ized.

Chart of district demographics and restrictive bill sponsorship

Of course, race, partis­an­ship, and elect­oral compet­it­ive­ness all move together in Amer­ican polit­ics. How do we know that these rela­tion­ships aren’t just reflect­ive of the fact that whiter districts are more Repub­lican and that Repub­lic­ans spon­sor these bills at higher rates? Or that racially diverse states are more likely to be compet­it­ive and that these bills might be intro­duced at higher rates in compet­it­ive states?

To disen­tangle these rela­tion­ships, we use a stand­ard stat­ist­ical tool called regres­sion analysis. Regres­sion analysis lets us test whether the rela­tion­ship between race and spon­sor­ship matters even after we account for the inde­pend­ent rela­tion­ships partis­an­ship and compet­it­ive­ness have with spon­sor­ship. If everything in the previ­ous figures were explained by partis­an­ship and compet­it­ive­ness, there would­n’t be any vari­ation left to explain after account­ing for those vari­ables. And if there were no rela­tion­ship between race and spon­sor­ship, the lines would be flat (or the uncer­tainty bands would be very wide). If we only have a story of partis­an­ship on our hands, account­ing for that should mean that whiter districts are no more likely to be repres­en­ted by lawmakers spon­sor­ing restrict­ive bills than less-white districts.

In the next figure, we graph­ic­ally show these rela­tion­ships after account­ing for other vari­ables. foot­note2_cro8nli 2 Through­out, predicted prob­ab­il­it­ies plots hold other covari­ates at their means. We do not see flat lines; instead, these rela­tion­ships look remark­ably similar to what they looked like before. While the lines move around a little bit, the same pattern remains: the whitest districts in the least-white states were the most likely to be repres­en­ted by a lawmaker look­ing to restrict voting, and the rela­tion­ship between race and spon­sor­ship was much stronger in these racially diverse states. This means the inter­play between district- and state-level racial char­ac­ter­ist­ics system­at­ic­ally influ­ences the like­li­hood that a district is repres­en­ted by one of these lawmakers, above and beyond the rela­tion­ship between party, compet­it­ive­ness, and spon­sor­ship.

Chart of district demographics and restrictive bill sponsorship

End Notes

Legislative District–Level Results: Racial Resentment and Sponsorship

In the previ­ous section, we showed that whiter legis­lat­ive districts were consid­er­ably more likely to be repres­en­ted by lawmakers who sponsored restrict­ive legis­la­tion and that this was espe­cially true in racially diverse states. Using regres­sion analysis, we were able to show that the rela­tion­ship between race and spon­sor­ship remains in racially diverse states even after account­ing for other factors like partis­an­ship and compet­i­tion.

As we mentioned above, recent social science research indic­ates that whiter areas that are surroun­ded by racially diverse areas are prone to the polit­ics of white back­lash or racial threat. The patterns we observed above are consist­ent with that narrat­ive. To test how reli­able that find­ing is, we now think about racial back­lash in a completely differ­ent way. Rather than rely only on demo­graphic data from the census, in this section, we’ll look at how white respond­ents to a national survey answered ques­tions about the role of race in Amer­ican life. As we explained previ­ously, we’ll lever­age the widely used racial resent­ment score from the 2020 wave of the Cooper­at­ive Elec­tion Study.

We start, as above, by just graph­ing the rela­tion­ship between districts’ racial resent­ment scores and the like­li­hood that they were repres­en­ted by lawmakers who sponsored at least one bill with a restrict­ive voting provi­sion in it. On the left-hand side of the plot below, we show the rela­tion­ship in the lower cham­bers; the right-hand side shows the rela­tion­ship in the upper cham­bers.

We see that, on aver­age, districts with higher racial resent­ment scores were far more likely to be repres­en­ted by a legis­lator who sponsored one of these bills. The rela­tion­ship reaches conven­tional levels of stat­ist­ical signi­fic­ance in both the upper and lower cham­bers. And these slopes are steep, indic­at­ing a very strong rela­tion­ship: the districts with the highest resent­ment scores were many times more likely to be repres­en­ted by one of these lawmakers. 

Chart of racial resentment and restrictive bill sponsorship

This same survey, however, shows that race and partis­an­ship are linked with racial resent­ment — white respond­ents in the CES who identify as hard-right have much higher racial resent­ment scores. Once again, we find simple rela­tion­ships between two char­ac­ter­ist­ics are incap­able of saying much on their own. Could it be that white voters score higher on the racial resent­ment score and are repres­en­ted by these lawmakers at higher rates, despite no inde­pend­ent rela­tion­ship between resent­ment and spon­sor­ship?

To disen­tangle these rela­tion­ships, we again turn to regres­sion analysis. As before, if there were no rela­tion­ship between resent­ment scores and spon­sor­ship above and beyond what racial demo­graph­ics and partisan affil­i­ation can explain, we’d expect a flat line (or very wide uncer­tainty bands) after account­ing for those other char­ac­ter­ist­ics. A flat line would mean that districts with high resent­ment scores were repres­en­ted by lawmakers who sponsored restrict­ive bills at the same rate as districts with lower scores, after account­ing for the other relev­ant char­ac­ter­ist­ics of the district.

Chart of racial resentment and restrictive bill sponsorship

And yet, again, we do not see a flat line. The lines are less steep, and our band of uncer­tainty is wider, mean­ing that some — but by no means all — of the rela­tion­ship between resent­ment and spon­sor­ship is explained by those other factors like partis­an­ship. But the slope of the line remains relat­ively steep: even after account­ing for those other factors, the districts with the highest resent­ment scores were at least 50 percent more likely to be repres­en­ted by a legis­lator push­ing a restrict­ive bill. And, in stat­ist­ical speak, the uncer­tainty bands are narrow enough to remain “signi­fic­ant” in both cham­bers (p < 0.05).

Taken as a whole, these two tests of racial back­lash — one look­ing at demo­graphic inform­a­tion from the census and one look­ing at survey responses — provide strong evid­ence that race and racial back­lash influ­enced the spon­sor­ship of restrict­ive voting bills in 2021, and this influ­ence cannot be explained by partisan factors alone.

State-Level Results

The results so far are clear: repres­ent­at­ives from whiter districts in racially diverse states were the most likely to spon­sor restrict­ive legis­la­tion in 2021, and this was true for members of the upper and lower cham­bers. These lawmakers also repres­ent districts with high racial resent­ment scores.

Now we ask whether there are patterns in the states where these provi­sions were intro­duced and passed and whether these rela­tion­ships are influ­enced by race and unified Repub­lican control. foot­note1_z0ijkh3 1 Although Nebraska’s unicam­eral legis­lature is form­ally nonpar­tisan, we include it here as a Repub­lican-unified state. The results are consist­ent with the analysis presen­ted above, and our results are stat­ist­ic­ally signi­fic­ant even when we use differ­ent regres­sion tech­niques. Restrict­ive voting rights legis­la­tion is shaped by both race and by partis­an­ship.

In the figure below, we present the results of a stat­ist­ical model called “robust regres­sion” (this differs from tradi­tional regres­sion models by giving less weight to outliers — like Texas, for instance, where lawmakers intro­duced hundreds of restrict­ive provi­sions last year). foot­note2_92lr0t2 2 It’s worth noting that all our results hold even if we simply exclude Texas. Let’s start by look­ing at the rela­tion­ship between race and the number of provi­sions intro­duced and passed in states where Repub­lic­ans didn’t have unified control.

Chart of state demographics, partisan control, and restrictive legislation

These lines are flat. In other words: if a state didn’t have unified Repub­lican control, there wasn’t any rela­tion­ship between race and legis­lat­ive activ­ity. In fact, these states really didn’t intro­duce or pass very many provi­sions at all.

Now let’s add in the states with unified Repub­lican control:

Chart of state demographics, partisan control, and restrictive legislation

In contrast with the states without unified Repub­lican control, there’s a strong rela­tion­ship between racial char­ac­ter­ist­ics and restrict­ive activ­ity in states where Repub­lic­ans hold all the levers of power. Namely, lawmakers in less-white states where Repub­lic­ans call all the shots intro­duced and passed far more restrict­ive provi­sions.

But once again, we’re left with the ques­tion of complex rela­tion­ships. Are less-white Repub­lican states more compet­it­ive? Could that compet­it­ive­ness be driv­ing these rela­tion­ships? In the next two figures, we revisit these rela­tion­ships, but as with the legis­lat­ive district analyses, we stat­ist­ic­ally account for these other factors.

Chart of state demographics, partisan control, and restrictive legislation

Even after we control for other char­ac­ter­ist­ics, the rela­tion­ship between race and restrict­ive legis­la­tion persists in the states with total Repub­lican control. How can this be? It turns out that even uncom­pet­it­ive Repub­lican states saw signi­fic­ant legis­lat­ive activ­ity, espe­cially when it came to the intro­duc­tion of these bills. While the four whitest uncom­pet­it­ive Repub­lican states (Wyom­ing, North Dakota, Montana, and West Virginia) collect­ively intro­duced 28 restrict­ive provi­sions in 2021, the four least-white uncom­pet­it­ive Repub­lican states (Missis­sippi, Alaska, South Caro­lina, and Oklahoma) intro­duced 63 restrict­ive provi­sions — more than twice as many. Thus, race seems to be a driv­ing factor for voting rights back­lash in Repub­lican-domin­ated states even when those states aren’t elect­or­ally compet­it­ive.

End Notes

Conclusion

In recent years, voting rights and access to demo­cracy have become highly partisan issues, with the Repub­lican Party being largely respons­ible for the wave of legis­la­tion restrict­ing access to voting intro­duced and passed in state legis­latures across the coun­try. It is also true that race and partis­an­ship are deeply inter­twined. There is strong partisan sort­ing by race, with the over­whelm­ing major­ity of Amer­ic­ans of color identi­fy­ing as Demo­crats. We there­fore might expect that any rela­tion­ship between the spon­sor­ship of restrict­ive voting legis­la­tion and the racial compos­i­tion of the constitu­en­cies repres­en­ted by the bills’ spon­sors could be explained by the clear partisan divide on the issue.

Our analysis makes clear that this is not the case. The recent trend of restrict­ive voting laws lies at the inter­sec­tion of race and partis­an­ship. We are not seeing these bills intro­duced and passed every­where that Repub­lic­ans have control. Rather, they are most preval­ent in states where they have control and where there are signi­fic­ant non-white popu­la­tions. Simil­arly, it is not just that Repub­lican-lean­ing legis­lat­ive districts are repres­en­ted by lawmakers who spon­sor these bills. The spon­sor­ship of these bills is concen­trated in the whitest parts of the most diverse states. Further, consist­ent with estab­lished schol­arly theor­ies of racial threat, we find evid­ence that race and racial resent­ment matter above and beyond the influ­ence of partis­an­ship.

Technical Appendix

Meth­od­o­logy

To explore the drivers of new restrict­ive voting legis­la­tion, we lever­age the data from the Bren­nan Center Voting Laws Roundup Project, which iden­ti­fies bills intro­duced around the coun­try with provi­sions touch­ing on voting access, eligib­il­ity, and other issues cent­ral to state voting regimes. We use the provi­sions from each voting bill as it was origin­ally intro­duced (if it died) or as it was even­tu­ally passed. In other words, if a bill is intro­duced and is later amended to include addi­tional restrict­ive provi­sions, but the bill does not pass, these amend­ments are not reflec­ted in our analyses.

Other Data Sources

In addi­tion to the data on the voting law provi­sions, we use inform­a­tion from other sources to system­at­ic­ally exam­ine the causes of this wave of legis­la­tion. We incor­por­ate inform­a­tion about how hard it was to vote in each state before the 2021 legis­lat­ive session from the Cost of Voting Index, and we use data from LegiS­can to identify the spon­sor(s) of each bill. We incor­por­ate data about the racial compos­i­tion and other sociodemo­graphic indic­at­ors of states and legis­lat­ive districts from the Amer­ican Community Survey 2020 5-Year Estim­ates (the latest data avail­able). We control for partis­an­ship by look­ing at state- and legis­lat­ive district–­level support for Trump in the 2020 pres­id­en­tial elec­tion using data from the MIT Elec­tion Data and Science Lab and Voting and Elec­tion Science Team, respect­ively. foot­note1_ch1lndp 1 We calcu­late Trump’s vote share for each legis­lat­ive district by assign­ing each precinct to the district in which its geograph­ical centroid is located. While this method will not perfectly calcu­late Trump vote share in some cham­bers where precincts cross district lines, we have no reason to believe this poses analyt­ical prob­lems. In Kentucky and West Virginia, where precinct-level results are not avail­able, we assign each census block the pres­id­en­tial results of the county in which it falls. District-level results are then calcu­lated as the popu­la­tion-weighted mean of Trump’s vote share of each block in the district. Our results do not change if instead we omit Kentucky and West Virginia. States are considered compet­it­ive in 2020 if Trump won between 45 percent and 55 percent of the vote share.

Racial resent­ment scores are taken from the 2020 Cooper­at­ive Elec­tion Study (CES). We retain the responses of white voters, and each respond­ent’s resent­ment score is calcu­lated as their mean agree­ment with the follow­ing ques­tions: “Irish, Itali­ans, Jewish and many other minor­it­ies over­came preju­dice and worked their way up. Blacks should do the same without any special favors” and “Gener­a­tions of slavery and discrim­in­a­tion have created condi­tions that make it diffi­cult for blacks to work their way out of the lower class” (reverse coded). Respond­ents to the CES are coded to their home ZIP code. Calcu­lat­ing districts’ racial resent­ment scores follows the same approach as Trump vote share in Kentucky and West Virginia: we start by assign­ing each census block the aver­age racial resent­ment score of the ZIP code in which its centroid falls. District-level scores are the popu­la­tion-weighted mean of each block in the district. Two-thirds of ZIP codes fall entirely within a single upper-cham­ber district, and more than half are wholly within a single lower-cham­ber district.

Finally, to account for addi­tional partisan explan­a­tions, we identify which states were under unified Repub­lican control in 2021 using data from the National Confer­ence of State Legis­lat­ors. Obser­va­tions miss­ing ACS data or precinct-level pres­id­en­tial results are omit­ted; the rela­tion­ships are not differ­ent when they are included in the models not using these controls.

Regres­sion Tables

In Table 1, we show the results of the regres­sions run at the legis­lat­ive district level. Although partis­an­ship doesplay an import­ant role in the spon­sor­ship of restrict­ive provi­sions above and beyond the local and state racial compos­i­tion, race remains a cent­ral force in the spon­sor­ship of these restrict­ive provi­sions. In fact, the R2s on the models includ­ing only racial demo­graph­ics are consid­er­ably higher than models includ­ing only partisan meas­ures in the upper and lower cham­bers alike. Import­antly, as the table and figures above make clear, these rela­tion­ships are not mean­ing­fully changed by the inclu­sion of other covari­ates.

Table 1

In Table 2, we present the state-level regres­sion table. As discussed above, we use a robust regres­sion (using `rlm()` from the MASS library in R) due to concerns about poten­tial outliers.

Table 2

State-level models using OLS are presen­ted in the follow­ing table.

Table 3

End Notes