J78 | Macro Paper Warehouse

Vanguard: Black Veterans and Civil Rights After World War I

Mon, 01 Jan 0001 00:00:00 +0000

This paper provides the first causal evidence on how military service shaped Black civil rights activism in the aftermath of World War I. The research question is whether random induction into the segregated National Army caused Black men to join the nascent NAACP and become prominent community leaders during the New Negro era. The authors leverage the WWI draft lottery — in which each registrant’s unique serial number was drawn from a bowl to determine induction order — as an instrument for military service, a source of exogenous variation not previously exploited in the literature.

To support this analysis, Ang and Chinoy construct an unusually rich dataset by digitizing nearly one million Black draft registration cards from the first registration (June 17, 1917), linking them through the 1930 full-count census to 233,517 NAACP member observations across 227 branches from 1912 to 1940, and supplementing with Veterans Administration records, Army Transport Service passenger lists, and biographical dictionaries of prominent African Americans. The instrument — serial number percentile within draft board and race (SNP%) — is validated against all observed pre-draft registrant characteristics and yields a first-stage F-statistic of 1,051 in the preferred specification.

The main finding is that Black men randomly induced to serve in the military were nearly three times more likely to join the NAACP than observably similar registrants from the same draft board (TSLS coefficient 0.0219, se = 0.0049, against a sample mean NAACP participation rate of 0.8%). The authors estimate that the draft induced more than 10,000 Black men to join the NAACP in total. Military service also raised the probability of appearing in biographical dictionaries of historically prominent African Americans by a factor of roughly 1.6 (TSLS coefficient 0.0027, se = 0.0012, sample mean 0.17%). These results are robust to alternative instruments, flexible polynomial specifications of SNP%, state-year fixed effects, and alternative veteran-status measures from VAMI and ATS records. They are also not explained by differential residential mobility: adding controls for interstate and North-South migration leaves the main coefficient essentially unchanged (0.0217-0.0218).

In contrast, TSLS estimates for all socioeconomic outcomes — literacy, home ownership, employment, census-predicted income, actual 1940 income, and educational attainment — are small and insignificant, ruling out human capital acquisition as a mechanism. Club involvement measured in the census is likewise unaffected, indicating that NAACP membership reflects specifically civil rights activism rather than generically greater social participation.

The mechanism the paper identifies is experienced discrimination. Effects on NAACP participation increase monotonically with the racial gap in induction rates across draft boards (significant at p = 0.01). Effects are large and significant for men assigned to camps that restricted Black soldiers’ access to military training (coefficient 0.0351, se = 0.0104) and to officer promotion (coefficient 0.0360, se = 0.0111), and are large for men in both restriction types simultaneously (coefficient 0.0367, se = 0.0114). In contrast, men attending less discriminatory camps show small and insignificant effects. Among the two all-Black combat divisions, NAACP participation is highest for veterans of the 92nd Division — subjected to constant racial abuse under U.S. command — and lower for the 93rd Division, which served under more hospitable French command. Previously unstudied veteran surveys from Virginia and Connecticut corroborate this narrative: respondents from camps with training and promotion restrictions were more than twice as likely to mention racial injustice, and mentions of injustice were more predictive of postwar civic engagement than any other survey theme.

The scope of the paper is Black male registrants in the first WWI draft registration (men aged 21-30 as of June 17, 1917), linked to a sample of approximately 300,000 in the 1930 census. Effects are attenuated for men from counties with greater racial hostility — proxied by Confederate state status, Confederate monument density, and county lynching rates — consistent with the interpretation that activism was more feasible in less repressive environments.

Q: What is the core identification strategy and why was it not feasible to use it before this paper? A: The paper uses each Black registrant’s serial number percentile within his draft board and racial group (SNP%) as an instrument for WWI military service. Unlike the WWII and Vietnam drafts, which used birthday-based lotteries, the WWI lottery assigned induction order by drawing unique serial numbers from a bowl, making serial number rank the source of quasi-random variation. This source had never been exploited in the literature, partly because the serial numbers had to be hand-captured from digitized draft card images.

Q: How strong is the first stage, and was the lottery truly random? A: The first-stage F-statistic is 1,051, and a ten-percentile decrease in SNP% is associated with a 34.5 percentage point increase in the probability of serving. Bivariate serial numbers show some non-random patterns — nine of 13 pre-draft characteristics correlate with raw SN% — likely because some Southern boards inflated numbers for white registrants. Conditioning on board fixed effects and using SNP% within board-race cells eliminates these correlations; Panel B of Appendix Table A1 shows the largest standardized coefficient falls to 0.006.

Q: What is the magnitude of the effect on NAACP membership and how does the causal estimate compare to a naive OLS? A: The TSLS coefficient is 0.0219 (se = 0.0049) against a sample mean of 0.8%, implying roughly a threefold increase in NAACP membership. The OLS estimate of 0.0116 understates the causal effect, consistent with the marginal man induced by the lottery being observationally weaker than infra-marginal volunteers.

Q: Does the effect reflect simply that veterans moved to Northern cities where NAACP branches were more accessible? A: No. Adding indicators for interstate migration and North-South migration leaves the TSLS coefficient essentially unchanged at 0.0218 and 0.0217, respectively. The Great Migration channel is thus not the operative mechanism.

Q: Did military service improve Black veterans’ economic outcomes? A: TSLS estimates for literacy, home ownership, employment, census-predicted income, actual 1940 income, and educational attainment are all small and statistically insignificant. This contrasts sharply with evidence on Black veterans of WWII and Korea (Greenberg et al., 2022) and is consistent with the documented absence of meaningful postwar benefits or training for Black WWI soldiers.

Q: If it was not human capital or migration, what mechanism does the paper establish? A: The primary mechanism is exposure to institutional discrimination during military service. Three distinct empirical patterns converge: (1) effects increase monotonically with draft board racial disparities in induction rates; (2) effects are large and significant for men at camps that denied training and promotion, and near zero for men at less discriminatory camps; (3) veteran survey mentions of racial injustice are more common among men from discriminatory camps and are more predictive of postwar NAACP membership than any other survey theme.

Q: How do the two all-Black combat divisions differ in their postwar NAACP participation, and what does this reveal? A: Veterans of the 92nd Division, who fought under U.S. command amid constant racial abuse, show the highest NAACP participation rates. Veterans of the 93rd Division, who fought under French command and were received with relative hospitality, show lower (though not statistically significantly lower) participation. Since both divisions received similar formal training and neither group shows socioeconomic gains, the differential reflects discrimination exposure rather than skill acquisition.

Q: What is the quantitative scale of the effect for the most discriminatory camps? A: For men assigned to camps with restrictions on both training and promotion, the TSLS coefficient on NAACP membership is 0.0367 (se = 0.0114) — more than 1.5 times the average estimate of 0.0219. Men at camps without restrictions show coefficients that are small and statistically insignificant.

Q: How does county-level racial hostility moderate the effect? A: The effects of military service on NAACP membership are larger — more positive — for men from counties with fewer Confederate monuments, lower lynching rates, and non-Confederate state status. This is interpreted as evidence that activism in response to discriminatory military experiences was more feasible in less racially hostile local environments, rather than as evidence that discrimination exposure was lower.

Q: What is the paper’s aggregate policy implication regarding the scale of the draft’s effect on the civil rights movement? A: The authors estimate that the WWI draft induced more than 10,000 Black men to join the NAACP. Veterans accounted for nearly 15% of all male NAACP members, against roughly 8% of Black male adults in the population, and were significantly more likely to appear in biographical dictionaries of prominent African Americans. The draft thus constituted a sizable and measurable contribution to the organizational vanguard of the early civil rights movement.

Q: How does the paper contribute to the economics of discrimination beyond documenting discriminatory behavior by majority actors? A: Most economics research on discrimination studies the conduct of white decision-makers (e.g., racial bias in hiring, lending, or bail). This paper examines how experiences of discrimination reshape the political behavior and aspirations of the minority group itself. The results show that institutional betrayal — systematic exclusion, degradation, and denial of training — generated deep discontent that translated into aggressive political mobilization, a dynamic the authors trace through subsequent episodes including the WWII Double V campaign and responses to police killings.

Serial number percentile within draft board and race (SNP%): The instrument constructed by the authors. Each WWI registrant received a serial number from 1 to the size of his draft board; those numbers were drawn in random order to determine induction priority. SNP% measures where a registrant fell in that draw relative to others in his board and racial group, and serves as the source of quasi-random variation in veteran status.

New Negro era: The period of invigorated Black political and cultural assertiveness following WWI, characterized by renewed racial pride, economic independence, and progressive politics. The movement spanned the Harlem Renaissance, the Universal Negro Improvement Association, the American Negro Press, and the Brotherhood of Sleeping Car Porters, and represented a rejection of the “conservatism, parochialism, and political accommodationism” of older Black leaders.

Draft board racial gap: The authors’ measure of draft board discrimination, defined as the difference in induction rates between Black and white registrants within a given draft board. The interquartile range spans roughly 0 to 20 percentage points, with a notable fraction of boards exhibiting gaps exceeding 30 percentage points.

Camp discrimination: The denial of military training and officer promotion opportunities to Black soldiers, documented in War Department reports by military intelligence officers tasked with monitoring the treatment of Black soldiers. The paper classifies each camp as restricted or unrestricted on each dimension and uses this classification to estimate heterogeneous treatment effects.

Institutional betrayal: The paper’s characterization of the U.S. government’s treatment of Black WWI soldiers — drafting them at higher rates than whites, denying them training and promotion, and assigning them to menial labor — as generating a profound sense of injustice that motivated postwar political activism rather than loyalty or accommodation.

NAACP membership as civil rights activism proxy: The paper uses dues-paying membership in local NAACP branches as its primary quantitative measure of civil rights participation. Membership involved active financial cost (annual fees of $1 to $10 at a time when median Black family income was below $500), exposure to harassment and violence in the South, and participation in local protest and legal advocacy, distinguishing it from passive civic engagement.

Why Is Workplace Sexual Harassment Underreported? The Value of Outside Options amid the Threat of Retaliation

Mon, 01 Jan 0001 00:00:00 +0000

Layer 1 — Summary

Research question and argument

Dahl and Knepper address the long-standing puzzle of why workplace sexual harassment is chronically underreported despite high estimated prevalence. Survey evidence indicates that no fewer than 1 in 28 U.S. workers report annual victimization, yet only 1 in 11,000 workers files a formal charge with the Equal Employment Opportunity Commission (EEOC). Even following the #MeToo movement, formal charges rose only about 10%, leaving an enormous gap unexplained.

The paper’s central hypothesis is that employers coerce victims into silence through the credible threat of retaliatory firing. The key mechanism: because reporting constitutes a “protected activity” triggering employer notification, workers who fear losing their jobs will suppress claims. This threat is most binding when a worker’s outside options are weak — when it is hard to find a new job or when unemployment insurance (UI) benefits are thin. The paper tests this hypothesis by asking whether external shocks that reduce the value of outside options increase the threshold of harassment severity above which workers are willing to report.

Measurement strategy

Measuring underreporting directly is impossible by definition. The authors’ key methodological insight is to use the selectivity of filed charges as an indirect proxy. Under mild assumptions, if workers become more selective about which incidents they report, the average quality of filed charges must rise. The authors measure quality using the EEOC’s own merit determination: a charge is deemed meritorious if the employer settles, the claimant withdraws upon receipt of benefits, or the EEOC finds reasonable cause after investigation. The merit rate thus serves as an observable proxy for the (unobservable) degree of underreporting.

Baseline descriptive evidence supports the mechanism’s relevance: across 2000–2015, sexual harassment charges were nearly 50% more likely to be meritorious than non-harassment charges (27.0% vs. 18.6%), and more than twice as likely to involve employer retaliation (63.4% vs. 30.7%). The proportion of EEOC sexual harassment cases involving retaliation rose from 52% in 2000 to 72% in 2015, a period over which the annual volume of filed charges fell by 37%.

Analysis 1 — Labor market conditions (2000–2015)

The first empirical design exploits monthly variation in state-industry unemployment rates over 2000–2015 using EEOC microdata on individual charges. The regression controls for industry, state, and time fixed effects, isolating within-state-industry variation in unemployment. The identifying assumption is that a worker’s willingness to file depends only on her outside options and the severity of harassment she experiences, conditional on fixed effects.

The results indicate that each one percentage point increase in a state-industry’s monthly unemployment rate is associated with a 0.5–0.7% increase in the probability that a filed charge is deemed meritorious by the EEOC. This is consistent with the hypothesis that workers become more reluctant to report as outside labor market options weaken.

Heterogeneity analysis using linked EEO-1 establishment data strengthens the interpretation. The effect is amplified in industries that employ a larger fraction of men and in establishments where male managers account for a higher share of supervisory roles. Oﬀending establishments in the sample have, on average, 2.8 percentage points more male employees and 5 percentage points more male managers than non-offending establishments. The selectivity-unemployment gradient is larger in these male-dominated environments, consistent with a role for gendered power disparities in enabling employer retaliation.

Analysis 2 — North Carolina UI reform (quasi-experiment)

The second design exploits North Carolina’s 2013 UI reform as a plausibly exogenous reduction in the value of outside options. In response to the near-insolvency of its UI trust fund following the Great Recession, North Carolina simultaneously reduced maximum weekly benefits by approximately 35% (from $535 to $350 per week) and cut maximum benefit duration from 26 to 20 weeks. Together, these changes reduced the maximum total regular UI benefit available to North Carolinians by approximately 50%, from roughly $14,000 to $7,000. These reforms also violated the Congressional non-reduction rule, making individuals ineligible for an additional 47 weeks of federal Emergency Unemployment Compensation benefits, further amplifying the effective cut. North Carolina was the only state to simultaneously reduce both the level and duration of benefits.

The authors implement a difference-in-differences design comparing North Carolina to other Southern states that did not change their UI programs, controlling for state and month-year fixed effects. Pre-reform parallel trends are documented via event study. Administrative UI recipiency data show that the short-term UI recipiency rate in North Carolina fell from 33% to 10% — a 59% decline relative to control states — within roughly two years of the reform.

The main finding is that the selectivity of sexual harassment charges filed in North Carolina increased by approximately 7 percentage points following the reform, representing more than a 30% increase relative to control states. This is consistent with the hypothesis that reduced UI generosity raises the cost of a retaliatory firing, causing workers to suppress all but the most severe harassment incidents.

The authors note that North Carolina also reduced corporate and personal income taxes shortly after the UI reform. Because tax cuts should increase both labor demand and labor supply (insofar as substitution effects dominate income effects), this would tend to reduce the reporting threshold, leading them to interpret the 30%+ estimate as a lower bound on the causal effect of the UI reform on selectivity.

Formal model

The paper presents a threshold model of reporting behavior adapted from Boone and Van Ours (2006). Workers choose a reporting threshold: the minimum harassment severity above which they will file a charge. The threshold rises when the value of outside options falls, either because the probability of finding a new job declines (recession) or because unemployment benefits shrink. The model predicts that the merit rate of filed charges will rise as outside options weaken. The model explicitly does not predict the volume of charges, because firm behavior — which may adjust endogenously to higher reporting thresholds — is not modeled.

Scope conditions

All findings concern formal EEOC charges filed in the United States between 2000 and 2015 (analysis 1) and through the post-2013 reform period (analysis 2). The EEOC definition of illegal harassment requires severity sufficient to create a “hostile or offensive work environment” or an adverse employment action. The paper’s merit measure captures harassment that exceeded this legal threshold; non-meritorious charges may still involve some level of misconduct. The sample for establishment-level heterogeneity analyses covers private firms with 100 or more employees (EEO-1 filers), approximately 40% of U.S. employees. The mechanism specifically concerns retaliation-driven suppression of formal reporting; effects on informal or anonymous reporting cannot be assessed.

In depth

Q1. Q: What is the core mechanism the paper proposes to explain underreporting?

A: Employers threaten workers with retaliatory firing for engaging in protected activity (filing an EEOC charge). Because the EEOC notifies the named employer within 10 days of receiving a charge, worker anonymity is rarely preserved. When a worker’s outside options are weak — because unemployment is high or UI benefits are thin — the expected cost of a retaliatory firing is higher, raising the severity threshold above which a victim is willing to report. Workers therefore “tough it out” rather than risk their current job.

Q2. Q: How does the paper measure something that is, by definition, not reported?

A: By using the quality of filed charges as a proxy for the degree of underreporting. Under the threshold model, if workers only report when harassment exceeds a higher bar, the average quality of what does get filed must rise. The EEOC’s own merit determination (settlement, withdrawal with benefits, or reasonable-cause ruling) provides an objective, externally-assessed quality measure. An increase in the merit rate signals that the population of filed charges has become more selected — that is, that the unreported fraction has grown.

Q3. Q: What does the 0.5–0.7% figure mean, and what is its interpretation?

A: Each one percentage point increase in a state-industry’s monthly unemployment rate is associated with a 0.5–0.7 percentage point increase in the probability that a filed sexual harassment charge receives a merit designation from the EEOC. This is interpreted as evidence that workers become more selective — filing only more severe cases — as outside options weaken, consistent with higher underreporting at lower harassment thresholds.

Q4. Q: Why did the number of EEOC sexual harassment charges fall by 37% between 2000 and 2015, even as retaliation rates rose?

A: The paper offers the interpretation that firms have become more effective at credibly threatening retaliation to suppress reporting. The 37% volume decline does not imply harassment has diminished; it may reflect a rising fraction of victims staying silent. The authors note the model does not make a prediction about volume because firm behavior is not modeled — volume depends on both worker reporting thresholds and employer conduct.

Q5. Q: Why is North Carolina’s UI reform particularly well-suited as a natural experiment?

A: Four features make it attractive. First, the reform was motivated by trust fund insolvency rather than local labor market conditions, making it more plausibly exogenous to harassment reporting trends. Second, it was implemented during a period of historically high unemployment, when the social safety net was unusually relevant to workers considering risky actions. Third, the cuts affected both the intensive margin (benefit level, down ~35%) and the extensive margin (duration, from 26 to 20 weeks; added eligibility restrictions), with total maximum benefits cut by approximately 50%. Extensive-margin cuts are likely particularly salient for workers worried about a retaliatory firing. Fourth, the cuts to regular UI were permanent and primary, rather than affecting supplemental federal programs.

Q6. Q: What role does industry and establishment gender composition play?

A: The underreporting effect — proxied by the merit-unemployment gradient — is amplified in industries with a larger fraction of male coworkers and in establishments with a higher fraction of male managers. Establishments named in sexual harassment charges have, on average, 2.8 percentage points more male employees and 5 percentage points more male managers than non-respondent establishments. The male-manager underreporting gradient is further amplified by higher unemployment, suggesting gendered power disparities interact with labor market conditions to suppress reporting.

Q7. Q: Does the paper make predictions about the volume of charges, not just their quality?

A: No. The threshold model explicitly does not model firm behavior and makes no prediction about charge volume. Whether volume rises or falls following a labor demand shock is theoretically ambiguous: firms may respond to higher reporting thresholds by escalating harassment (increasing both incidence and severity), or may not respond at all. The identifying assumption requires only that a worker’s willingness to file depends on her outside options and the severity of harassment she experiences — not on firm behavior.

Q8. Q: What is the “value of a statistical harassment” (VSH) figure, and how does it relate to the paper’s motivation?

A: Hersch (2018) estimates the VSH for serious cases at approximately $7.6 million, roughly comparable to the value of a statistical life (VSL). Dahl and Knepper cite this figure to underscore the magnitude of the underreporting problem: with an estimated 5 million workers victimized annually, the social costs of suppressed reporting are substantial. The comparison to VSL motivates why closing the reporting gap matters for welfare, not just legal compliance.

Q9. Q: What is the ex-ante moral hazard interpretation of the UI results?

A: Most UI research focuses on ex-post effects — how benefit generosity affects job search behavior for workers who have already lost their jobs. Dahl and Knepper document an ex-ante moral hazard effect: UI generosity affects the behavior of currently employed workers by changing the expected cost of actions (reporting harassment) that might trigger job loss. Lower UI generosity raises the effective cost of a retaliatory firing, discouraging reporting. This is analogous to, but in the opposite direction from, Lusher et al. (2020), who find that UI expansions reduced productivity among currently employed workers.

Q10. Q: What does the parallel-trends evidence show for the NC difference-in-differences?

A: The paper presents an event study documenting parallel pre-reform trends in the merit rate between North Carolina and control states. The control group is other Southern states that did not change their UI programs during the sample period, excluding AR, FL, GA, and SC (which made changes) and the West South Central division (which exhibited differential pre-trends). The UI recipiency rate tracks closely between NC and control states prior to July 2013, then diverges sharply thereafter, dropping from 33% to 10% in North Carolina within two years — a 59% decline relative to controls.

Key Concepts

Merit determination (EEOC): The EEOC assigns a merit designation to a sexual harassment charge if the named employer settles with the employee, the claimant withdraws the charge upon receipt of benefits, or the EEOC itself determines after investigation that there is “reasonable cause” to believe harassment occurred. As used in this paper, merit designations capture cases where harassment exceeded the legal threshold of a “hostile or offensive work environment” or produced an adverse employment decision — not all cases involving some level of misconduct.

Selectivity of charges: The fraction of filed EEOC sexual harassment charges that receive a merit designation. In the paper’s framework, higher selectivity (a higher merit rate) signals that workers are filing only more severe cases — i.e., that underreporting of less severe cases has increased. Selectivity is used as an observable proxy for the (unobservable) degree of underreporting.

Reporting threshold (ᾱ): In the paper’s threshold model, the minimum level of harassment severity above which a worker will file an EEOC charge. The threshold is determined by the equality between the expected gains from reporting (probability of success times compensation plus elimination of harassment) and the expected costs (probability of retaliation times the gap between current wage and unemployment value). The threshold rises when outside options weaken — either through lower job-finding probabilities or reduced UI benefits.

Outside options: In this paper, the expected value to a worker of becoming unemployed: a weighted average of the wage at a new job (weighted by job-finding probability) and unemployment benefits (weighted by the probability of not finding a job). Outside options determine the cost a worker bears if retaliatory firing follows an EEOC charge. The paper’s two empirical analyses correspond to two separate shocks to outside options: aggregate labor demand (unemployment rate) and institutional safety net generosity (UI benefits).

Retaliation: Defined by the EEOC as punishment for engaging in a protected activity, such as filing a charge. Retaliation arose in 63.4% of all EEOC sexual harassment charges filed between 2000 and 2015 — more than double the rate for non-harassment charges — and rose from 52% of harassment cases in 2000 to 72% in 2015. In the paper’s model, the probability of a retaliatory firing is denoted θ, and is treated as fixed (not a function of harassment severity for tractability).

Ex-ante moral hazard (UI): The effect of UI benefit generosity on the behavior of currently employed workers, rather than on those already unemployed. In this paper’s context, higher UI generosity reduces the cost of a potential retaliatory firing for currently employed workers, making them more willing to report harassment. The North Carolina UI reform provides evidence of this ex-ante channel: when benefits were cut, the selectivity of harassment charges rose, consistent with workers becoming less willing to risk their jobs.

EEO-1 data: A mandatory annual survey of private establishments in the United States with 100 or more employees, covering approximately 40% of all U.S. employees. Collected by the EEOC, these data report the gender, race, and occupational distribution of workers within each establishment. In this paper, the EEO-1 files are linked to EEOC charge microdata to analyze how the gender composition of co-workers and managers moderates both the incidence of reported harassment and the degree of underreporting.

Summary based on IZA Discussion Paper 14740. AI-assisted, human review pending.