Political Foundations of Racial Violence: Testa & Williams (2026)

What this is. The paper’s core results, the conceptual framework it tests, the identification strategy, and the estimating equations: enough to know what it found and how, without reading all 62 pages. To replicate or extend, read the original at doi.org/10.1093/qje/qjaf045.

TL;DR

Testa and Williams use a regression discontinuity design on county-level popular-vote shares in presidential elections across the post-Reconstruction South (1880-1900) to show that a narrow Democratic Party loss in a county raised the probability of a Black lynching in the following four years by about 10 percentage points, equivalent to an 80% increase over the control mean. No comparable effect exists for white lynchings, ruling out a general violence response. Southern newspapers aligned with the Democratic Party increased anti-Black crime accusations after Democratic losses, consistent with an elite strategy channel linking racial antagonism to mob violence. Separate subgroup analyses find positive estimates with Democrat-only and white-only elites, and significantly larger effects in counties with above-median Black population shares; differences for the elite subgroups are marginal or statistically insignificant. These patterns are consistent with Blalock (1967)‘s power threat hypothesis. The paper reports a positive, marginally significant mediating effect of Black lynchings on Democratic electoral success in the early twentieth century, echoing Jones, Troesken, and Walsh (2017) on lynching and Black political participation. The findings suggest that racial violence helped consolidate the Solid South and suppress Black political participation, foreshadowing the de jure vote-suppression of Jim Crow.

Core results

Magnitudes and significance are as reported; */**/*** = 10%/5%/1%. Locators point into the source PDF.

#	Result	Locator	Magnitude
R1	Democratic county loss raises Black lynching probability by ~10 pp (80% over control mean); robust across polynomials, bandwidths, and spatial controls	Table II Panel A col 3, p. 755	beta = 0.104** (SE 0.041); control mean = 0.13; optimal bandwidth ~15 pp
R2	No comparable effect on white lynchings (placebo); coefficients small and insignificant across all specifications	Table II Panel A cols 5-8, p. 755	beta = -0.009 (SE 0.013) in col 7; indistinguishable from zero
R3	Effect nearly doubles in previously uncompetitive counties (the election constitutes new information about local political strengths): beta = 18.8 pp	Table II Panel B col 3, p. 756	beta = 0.188*** (SE 0.072); 703 obs
R4	Anti-Black crime accusations rose after Democratic county losses, including in Democratic newspapers	Table V cols 1-5 and 7-8, p. 772	All-paper estimates: beta = 0.126*, 0.139**, 0.168***, 0.136**, and 0.055** (SE 0.024-0.073); Democratic-paper estimates: 0.104** (SE 0.042) and 0.168*** (SE 0.060); control means = 0.19-0.20
R5	Democratic newspapers actively reported county presidential losses (39% increase); Democratic papers show 99% increase vs. near-zero for non-Democratic papers	Table VI cols 1, 3-4, p. 776	beta = 0.043*** (SE 0.016) for any coverage; beta = 0.119*** (SE 0.020) for Democratic papers
R6	Positive estimates appear with Democrat-only and white-only elites; the effect is significantly larger with above-median Black population share	Table VII Panel A cols 1, 3, 5, p. 779	beta = 0.127*** (SE 0.044), 0.110*** (SE 0.042), and 0.177*** (SE 0.065), respectively; subgroup difference p-values = .11, .08, and .00
R7	Black lynchings in 1880-1900 predict Democratic electoral victory in 1904-1912, even conditioning on prior Democratic performance; correlation is suggestive of electoral reversal	Table IX cols 1-2, p. 784	beta = 0.021*** (SE 0.006) on any Democratic win 1904-1912
R8	Causal mediation analysis reports a positive, marginally significant indirect effect through Black lynchings	Table IX col 5, p. 784	Indirect effect = 0.004* (SE 0.002); direct effect = -0.013 (SE 0.018)
R9	The core lynching result survives alternative controls, inference, bandwidths, and polynomial orders	Table III Panels A-C, pp. 760-761	County FE: 0.055*** (SE 0.022); half-bandwidth: 0.160** (SE 0.068); cubic polynomial: 0.127** (SE 0.057); baseline 0.104** under alternate clustering
R10	Backlash is strongest when a loss is informative after prior Democratic strength	Table IV, p. 765	0.160** (SE 0.063) after prior Democratic win vs 0.050 (SE 0.066) after prior loss; joint uncompetitive/prior-win split: 0.392*** (SE 0.130) vs 0.046 (SE 0.042), split p = .00
R11	Losses to populist opposition produce especially large lynching increases	Text p. 767; Online Appendix Table C.4	50.4-54.2 pp, a 319%-360% increase over control mean and four to five times the residual nonpopulist estimates
R12	Placebo thresholds and windows do not reproduce the lynching effect	Figure VI, p. 763; text pp. 762-764	Off-threshold and out-of-period estimates are statistically indistinguishable from zero; effects are significant only in the first two post-election years
R13	Non-Democratic newspapers show no statistically significant positive accusation response	Table V cols 9-10, p. 772	-0.368 (SE 0.230) and -0.312 (SE 0.210), both insignificant; N = 206
R14	Newspaper accusation increases concentrate in Democrat-led and high-Black-population counties	Table VII Panel B, p. 780	Democrat-only elite: 0.245*** (SE 0.056) vs 0.038** (SE 0.016); large Black constituency: 0.229*** (SE 0.049) vs -0.019 (SE 0.055)
R15	The lynching response falls to near zero after state Jim Crow voting laws take effect	Table VIII cols 1-2, p. 782	Pre-law: 0.160*** (SE 0.056); post-law: 0.010 (SE 0.050); split p = .03
R16	Newspaper accusation effects change across Jim Crow periods	Table VIII cols 3-6, p. 782	All papers: 0.265*** (SE 0.044) pre-law vs -0.283*** (SE 0.060) post-law; Democratic papers: 0.291*** (SE 0.048) vs -0.014 (SE 0.074)
R17	Lynchings are associated with later Democratic wins and moderate the prior vote-margin relationship	Table IX cols 3-4, p. 784	Lynching coefficient: 0.051*** (SE 0.013) full sample and 0.047*** (SE 0.011) within bandwidth; interaction: 0.001*** (SE 0.000) and 0.003*** (SE 0.001)
R18	Alternative outcome windows support a short-lived post-election response	Text p. 762; Online Appendix Table C.2 and Figure C.2	Alternative outcomes imply 30.0%-97.8% increases; effects are large and significant only during the first two post-election years
R19	Congressional-district election estimates are small and imprecise	Text p. 768; Online Appendix Table C.5	Approximately 4% increase over control mean, compared with 80% for presidential-election baseline
R20	The close-election design passes density and pretreatment balance checks	Text pp. 750-751; Table I, pp. 752-753	McCrary density test p = .4; pretreatment discontinuities are statistically insignificant across the characteristics in Table I
R21	Non-Democratic papers do not increase county-election reporting after a Democratic loss	Table VI cols 5-6, p. 776	-0.051 (SE 0.095) and 0.007 (SE 0.140), both insignificant
R22	The lynching estimate is positive with a white-only elite and null otherwise; the subgroup difference is marginal	Table VII Panel A, p. 779	0.110*** (SE 0.042) with white-only elite vs -0.092 (SE 0.120) without; split p = .08
R23	The lynching effect is larger where the Black population share is above median	Table VII Panel A, p. 779	0.177*** (SE 0.065) above median vs -0.031 (SE 0.038) below; split p = .00
R24	The placebo white-lynching estimate remains null in previously uncompetitive counties	Table II Panel B col 7, p. 756	0.016 (SE 0.023), statistically insignificant

Overall (paper’s conclusion). The post-Reconstruction Democratic Party used racial violence, amplified through partisan newspapers, as a strategic tool to suppress Black political participation when legal disenfranchisement was unavailable. Close presidential election losses served as focal signals that credibly threatened Democratic hegemony; the ensuing lynching surge helped reverse Democratic electoral fortunes and prefigured the formal vote-suppression mechanisms of Jim Crow. These findings qualify the prevailing economic explanation of lynching, which emphasizes Black-white labor competition, by showing that political factors were primary.

Theory / model

The paper proposes no formal structural model. Its conceptual framework (Section II.B, p. 743) draws on Blalock (1967)‘s power threat hypothesis, which posits that a dominant group increases its use of social control measures against a minority as the minority’s political power grows. In the post-Reconstruction South, lynching of Black people was plausibly an instrument for maintaining white Democratic hegemony after emancipation removed formal slavery and before Jim Crow provided legal disfranchisement tools.

The framework posits two specific mechanisms through which a Democratic electoral loss could galvanize racial violence:

Informational channel (Section II.B, p. 745). Local political actors use recent vote shares to assess the relative strengths of competing groups. When actors lack complete information, even a close Democratic loss can serve as a focal point for coordination among members of the pro-Black opposition (following Anagol and Fujiwara (2016) and Granzier, Pons, and Tricaud (2023)). Anticipating such mobilization, local Democratic elites have an incentive to mount a violent preemptive backlash. This mechanism predicts that effects should be stronger where the loss constitutes more novel information, that is, in counties where Democrats had previously won by comfortable margins.

Elite strategy channel (Section II.B, p. 746 and Section IV.B, p. 768). Democratic newspapers, which dominated the Southern press and reported on county-level presidential results, could operationalize racial hatred by publishing anti-Black crime accusations (rape, murder, robbery). The paper notes that lynch mobs frequently invoked such accusations; its newspaper RD shows accusations rose after close Democratic losses but does not estimate whether newspaper reports caused lynchings. Glaeser (2005) models the supply side of this process: elites supply hatred to mobilize voters, dividing poor-white and Black coalitions. Ottinger and Posch (2024) document a related dynamic in which Southern elites used newspapers to mobilize white voters against populist political threats. The paper interprets this press response as evidence consistent with strategic efforts to suppress Black political participation.

The framework is tested empirically; no equilibrium condition or Euler equation is derived. The two channels generate testable predictions: larger effects in previously uncompetitive counties (informational channel), and increased anti-Black accusations in Democratic-affiliated newspapers after close losses (elite strategy channel). The results are consistent with both predictions, though the newspaper analysis does not by itself establish a causal link from accusations to lynchings.

Method

The primary identification strategy is a sharp regression discontinuity design (RDD) exploiting the county-level popular-vote threshold for a Democratic loss (or win) in presidential elections. The method builds on regression-discontinuity-design for causal identification and panel-regression for the newspaper analysis.

Main RD estimator. Equation (1), p. 748:

$$\text{Any Lynching}_{c(s)\tau} = \beta \cdot \text{Democratic Loss}_{c\tau} + f(\text{Loss Margin}_{c\tau}) + \phi_\tau + \theta_s + \mathbf{X}'_{c\tau} \boldsymbol{\Gamma} + \varepsilon_{c\tau} \tag{1}$$

where $\text{Any Lynching}_{c(s)\tau}$ is a binary indicator for at least one Black (or white) lynching in county $c$ of state $s$ in the four-year window after presidential election $\tau \in \{1880, 1884, 1888, 1892, 1896, 1900\}$. $\text{Democratic Loss}_{c\tau}$ is a binary indicator for whether the Democratic presidential candidate lost the county popular vote. $f(\text{Loss Margin}_{c\tau})$ is a flexible running polynomial (linear in the main specification) in the Democratic vote-share loss margin. $\phi_\tau$ is an election-period fixed effect, $\theta_s$ is a state fixed effect, and $\mathbf{X}_{c\tau}$ is a vector of spatial controls including quadratic polynomials in county longitude and latitude.

The local average treatment effect (LATE) is identified under the assumption that counties where Democrats barely lost are comparable in all pretreatment characteristics to those where they barely won — a condition supported by balance tests (Table I, pp. 752-753) and a McCrary (2008) density test (p-value 0.4; p. 750).

Bandwidth selection. MSE-optimal bandwidths are computed following Calonico, Cattaneo, and Titiunik (2014), restricting estimation to county-elections close to the Loss Margin = 0 threshold. The core Black-lynching result (Table II col 3) uses an optimal bandwidth of approximately 15 percentage points, yielding about 1,481 observations.

Newspaper RD estimator. Equation (2), p. 769:

$$\% \text{Accusations}_{n(c)t(\tau)} = \beta \cdot \text{Democratic Loss}_{c\tau} + f(\text{Loss Margin}_{c\tau}) + \phi_\tau + \Upsilon_{t(\tau)} + \alpha_{\sigma(c)} + \varepsilon_{nt} \tag{2}$$

where $\% \text{Accusations}_{nt}$ is the share of newspaper pages (per 100) in newspaper $n$ in year $t$ (within the four-year period following election $\tau$) that contain anti-Black crime accusation phrases (“negro rape,” “negro murder,” “negro robbery” and variants). $\Upsilon_{t(\tau)}$ is a year-within-election-cycle fixed effect, and $\alpha_{\sigma(c)}$ is a newspaper-city fixed effect.

Causal mediation. Table IX column 5 combines the RD variation with a structural mediation analysis to decompose the effect of Democratic losses on downstream Democratic electoral success (1904-1912) into a direct effect and an indirect effect through the Black lynching channel, following a local average structural equation approach.

Empirical specifications

All specifications focus on the 11 former Confederate states (the “Solid South”) over the 1880-1900 presidential election cycle period, covering elections in November of each election year.

Main RD (R1, R2). Equation (1) with linear running polynomial, election-period and state fixed effects, and spatial covariates. Outcome: indicator for any Black (or white) lynching in the four years after election $\tau$. Estimated at MSE-optimal bandwidth. Standard errors clustered at the county level (counties reclassified if boundaries changed between elections; see p. 751). Reported in Table II Panel A, p. 755.

Uncompetitive-counties subsample (R3). Equation (1) restricted to county-elections where $|\text{Loss Margin}_{c,\tau-1}| > 16.2$ (the median vote margin among sample Democratic losses), so the loss in $\tau$ is relatively novel information. Reported in Table II Panel B, p. 756. Split-sample p-value tests the null of equal coefficients across subsamples.

Robustness suite (Table III, pp. 760-761): alternative clusterings (county, county-decade, state-election-period); specifications omitting covariates, spatial controls, or lat/lon polynomials; county fixed effects; county-pair fixed effects based on geographic proximity; quadratic controls for 1880 Black population shares; bandwidth multipliers of 0.5x and 1.5x; quadratic, cubic, and quartic running polynomials. The reported Black-lynching estimates range from 0.055 to 0.160 and are significant at least at the 10% level.

Newspaper RD (R4, R5, R13, R21). Equation (2) is estimated on the newspaper-year panel from newspapers.com, linked to contemporaneous counties. The Table V accusation-rate samples range from 206 to 3,524 observations across pooled and partisan subsamples; election-period and election-cycle-year effects are included with state, city, or newspaper fixed effects by column. Table VI replaces the rate with an indicator for any county-election reporting and uses 240 to 2,499 observations across pooled and partisan splits, with election-period, election-cycle-year, and city fixed effects. Standard errors are clustered by county except for non-Democratic newspaper columns in Tables V and VI, where they are heteroskedasticity robust. Partisan affiliation follows Gentzkow et al. (2014) and Gentzkow, Shapiro, and Sinkinson (2014). Locators: Tables V-VI, pp. 772 and 776.

Elite composition and power-threat subsamples (R6, R14, R22, R23). Equation (1) is estimated separately by whether a county had a Democrat-only elite, a white-only elite, and an above-median Black population share (Table VII Panel A). Equation (2) is likewise estimated across these splits for newspaper accusation frequency (Panel B). The county specifications include election-period and state fixed effects plus quadratic spatial controls; the newspaper specifications include election-period and election-cycle-year effects plus city fixed effects. Standard errors are clustered by county. The split-sample p-values test differences across the subgroups. Table VII, pp. 779-780.

Jim Crow moderation (R15, R16). Equations (1) and (2) are estimated separately before and after a state enacted a Jim Crow voting law, including poll taxes, literacy tests, multi-box laws, and secret-ballot laws (timing from Jones, Troesken, and Walsh (2012)). County lynching regressions include election-period and state effects and spatial controls; newspaper accusation regressions include election-period, election-cycle-year, and city effects. Standard errors are clustered by county. The lynching effect is significant before Jim Crow (0.160***, SE 0.056) and near zero afterward (0.010, SE 0.050). Table VIII, p. 782.

Downstream electoral analysis (R7, R8). OLS regressions of Democratic presidential victory in 1904, 1908, or 1912 on a binary indicator for any Black lynching in the county during 1880-1900 election periods (Table IX cols 1-2). Causal mediation in col 5 adapts the baseline RD by fixing the Democratic loss margin at zero, then separately estimating the direct and indirect (through lynching) paths to later Democratic victory.

The mediated effect is decomposed into direct and lynching-mediated paths:

$$\text{Total Effect} = \text{Direct Effect} + \text{Indirect Effect}_{\text{Black Lynching}}$$

Table IX column (5) reports direct and indirect effect estimates from the Stata mediate package, with county-level controls and the baseline RD bandwidth; the paper reports county-clustered standard errors (Table IX notes, p. 784).

The downstream electoral regressions in Table IX columns 1-4 can be written as:

$$\text{Democratic Win}_{c,1904-1912} = \alpha + \beta \text{Black Lynching}_{c\tau} + \delta \text{Loss Margin}_{c\tau} + \eta (\text{Black Lynching}_{c\tau} \times \text{Loss Margin}_{c\tau}) + \phi_\tau + \theta_s + \mathbf{X}'_{c\tau}\boldsymbol{\Gamma} + u_{c\tau}$$

Columns (1)-(2) omit the loss-margin terms; columns (3)-(4) include both terms. The outcome indicates a Democratic county win in the 1904, 1908, or 1912 presidential election. Columns (1) and (3) use the full sample, while (2) and (4) restrict observations to the baseline MSE-optimal bandwidth. All include election-period and state fixed effects and quadratic county longitude and latitude controls, with standard errors clustered by county. The table reports 5,914 and 1,481 observations for the full and bandwidth samples, respectively (Table IX, p. 784).

For newspaper reporting, the paper substitutes an indicator for any newspaper-year coverage of county election results for the accusation-rate outcome in Equation (2). It retains election-period, election-cycle-year, and newspaper-city fixed effects; standard errors are clustered by county except in the non-Democratic-paper subsample, where they are heteroskedasticity robust. The newspaper-year sample counts and estimates are in Table VI, p. 776.

Datasets used

Dataset	Role in paper	Wiki page
Historic American Lynching (HAL) Project (Hines and Steelwater 2023)	County-level Black and white lynching indicator outcomes for all states except Texas and Virginia	Project HAL
Seguin and Rigby (2019) lynching data	County-level lynching outcomes for Texas and Virginia to supplement HAL	no page yet
U.S. Decennial Census (1870, 1880, 1900, 1910)	County demographics (population density, Black population share), slaveholder shares, Confederate veteran shares	Census
Clubb, Flanigan, and Zingale (2006) ICPSR presidential and congressional election returns	County-level vote tabulations for presidential elections 1880-1900 and congressional elections; main explanatory variable	no page yet
newspapers.com full-text archive (as of June 10, 2023)	Anti-Black crime accusation rates (% pages) and county election-reporting rates in Southern city newspapers	no page yet
Gentzkow et al. (2014) and Gentzkow, Shapiro, and Sinkinson (2014) newspaper political affiliations	Partisan affiliation coding for Southern newspapers during the sample period	no page yet
Kestenbaum (2023) Political Graveyard	Partisan composition of local officeholders (mayors, postmasters) matched to counties	no page yet
Logan (2020) racial composition data	County racial composition of elected officials	no page yet

Sample: 11 former Confederate states; presidential elections 1880-1900 (6 elections); lynching windows through approximately 1904; newspaper years cover four-year post-election windows through 1904; downstream electoral analysis through 1912.

When to read the full paper

Read the original if you are: studying the political economy of racial violence, ethnic conflict, or elite-fomented social antagonism; working on the causal effects of electoral outcomes on social behavior beyond officeholding; extending the close-elections RD design to new social outcomes; or examining the historical origins of Jim Crow and Black disenfranchisement. The online appendix contains the McCrary density test, robustness tables (B1-E5), causal mediation details, and congressional-election extensions. Replication data are at doi.org/10.7910/DVN/08YUBP.

Attribution and rights

Source: peer-reviewed, The Quarterly Journal of Economics (2026), 733-794. This distillation was extracted by an LLM on 2026-06-28 and is not human-verified or independently reproduced. The paper is paywalled; the verbatim PDF is not hosted here.

Testa, Patrick A., and Jhacova Williams. “Political Foundations of Racial Violence in the Post-Reconstruction South.” The Quarterly Journal of Economics (2026), 733-794. DOI: 10.1093/qje/qjaf045. © The Author(s) 2025. Published by Oxford University Press on behalf of President and Fellows of Harvard College. All rights reserved. Reproduced here as a brief extract for research purposes only.