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The economics of race and eugenic sterilization in North Carolina:
1958–1968
Gregory N. Price
a,
*, William A. Darity Jr.
b,1
a
Department of Economics, Morehouse College, 830 Westview Dr. SW, Atlanta, GA 30314, United States
b
Sanford School of Public Policy, Duke University, 302 Towerview Rd, Durham NC 27709, United States
1. Introduction
To the extent that the discipline of economics provides
analytical and empirical insights into improving the
material well-being of society, historically it has been a
source of policy prescriptions that would promote optimal
population quantity and quality. For example, both Malthus’
(1798) famous essay on population and Ricardo’s (1817)
consideration on how real wages decline with population
growth point toward a conception of an optimum size of
population relative to the global natural resources endow-
ment. The echos oftheir perspective are present in biologist
Paul Ehrlich’s (1968) strictures about an optimum popula-
tion size for the United States and for the world as a whole.
Disturbingly, Ehrlich’s estimates of the optimum are
considerably lower than the current American or global
population. Correspondingly Gregory Clark’s (2007) more
recent exposition on the role of genetically selected
populations’ alleged contributions to the economic success
and rise of Western Europe points toward notions of a
biological and genetic optimum composition of population.
Optimum qualityand quantity of population is decidedly
the terrain of the eugenicists. Indeed, during the first half of
the twentieth century the American eugenics movement
promoted and implemented policies of eugenic sterilization
aimed at reducing the population shares of the biologically
unfit—those individuals with ‘‘dysgenic’’ traits—who pre-
sumably would undermine prospects for national economic
well-being (Leonard, 2005).
2
Economics and Human Biology 8 (2010) 261–272
ARTICLE INFO
JEL classification:
B16
I18
J15
J18
Keywords:
Race
Biogenetic fitness
Eugenic sterilization
ABSTRACT
Theoretical justifications for state-sanctioned sterilization of individuals provided by
Irving Fisher rationalized its racialization on grounds that certain non-white racial groups,
particularly blacks due to their dysgenic biological and behavioral traits, retarded
economic growth and should be bred out of existence. Fisher’s rationale suggests that
national or state level eugenic policies that sterilized the so-called biological and
genetically unfit could have been racist in both design and effect by disproportionately
targeting black Americans. We empirically explore this with data on eugenic sterilizations
in the State of North Carolina between 1958 and 1968. Count data parameter estimates
from a cross-county population allocation mode l of sterilization reveal that the probability
of non-institutional and total sterilizations increased with a county’s black population
share—an effect not found for any other racial group in the population. Our results suggest
that in North Carolina, eugenic sterilization policies were racially biased and genocidal.
ß2010 Elsevier B.V. All rights reserved.
* Corresponding author. Tel.: +1 404 653 7870.
E-mail addresses: gprice@morehouse.edu (G.N. Price),
william.darity@duke.edu (W.A. Darity Jr.).
1
Tel.: +1 919 613 7336.
2
As Leonard (2005) characterize it, the eugenics movement, in the
United States and elsewhere, aimed at improving human heredity by the
social control of breeding based on the assumption that differences in
human intelligence, character and temperament were by and large rooted
in biogenetic differences.
Contents lists available at ScienceDirect
Economics and Human Biology
journal homepage: http://www.elsevier.com/locate/ehb
1570-677X/$ – see front matter ß2010 Elsevier B.V. All rights reserved.
doi:10.1016/j.ehb.2010.01.002
Author's personal copy
While the criteria for determining who was unfit was
not necessarily racial, economic theorizing at the dawn of
the 20th century clearly suggested that biogenetically, the
‘‘Negro’’ lacked the requisite capacities required for
contributing to the growth and prosperity of American
society. A central proponent of this type of racialized
economic theorizing was the pioneer of modern theories of
capital markets—the economist Irving Fisher. Fisher, who
in 1923 founded the American Eugenics Society and was its
first President (Dimand, 2005), advocated the formation of
eugenics boards in every state to implement a program of
‘‘breeding out the unfit and breeding in the fit’’ (Cot, 2005;
Fisher, 1921).
Since the economic theory of the period treated black
Americans as potential candidates for eugenic control, this
paper considers the extent to which they were actual and
disproportionate targets of state-sanctioned eugenic ster-
ilizations.
3
Given that these eugenic practices found their motiva-
tion in economic theory, its presence would constitute an
‘‘economic breeding-out’’ of targeted individuals. We
explore this phenomenon empirically by using historical
cross-county eugenic sterilization data from the State of
North Carolina. We specify and estimate the parameters of
a population allocation model of sterilization to determine
whether the probability of forced sterilizations increased
with the share of a county’s various racial groups. If the
probability varies with particular racial-group shares, such
a correlation would suggest the possibility that, at least in
North Carolina, eugenic policies were racist in design and
effect; particular racial groups were targeted for reduc-
tions in their population share.
Our inquiry contributes to the emerging subfield of S
tratification Economics (Darity, 2005), as we examine a
process involving the political economy of the provision of
public tax-supported goods/services—in this case state-
supported sterilization—that generates inequalities
between ascriptively distinguished groups similar to
analyses conducted in Alesina et al. (2001),Loubert
(2005) and Price (2008). As we consider how race
conditioned a stigma of biological and genetic inferiority,
our results provide additional empirical evidence regard-
ing the historical consequences of racial stigma (Price et al.,
2008; Loury, 2002). Our examination of how race may have
conditioned state-sanctioned forced sterilizations adds to
the literature on how American eugenics policies were
influenced by demographics (Ramsden, 2008), including
individual characteristics such as gender (Schoen, 2001;
Sanger, 2007) and race (Peart and Levy, 2004; Darity, 1994;
Leonard, 2003; Cot, 2005; Dimand, 2005).
The remainder of the paper is organized as follows. In
Section 2, we provide an overview of the history of
economic thought as it relates to eugenics. The overview
will provide the context for understanding how eugenic
sterilization policies were conceived and implemented in
the United States. The data, specifically from North
Carolina, as well as the history of its tax-supported
sterilization program is provided in Section 3. In Section
4, we present our methodology and results. The North
Carolina sterilization data are in the form of counts at the
county level; therefore, we estimate the parameters of
count data specifications of the number of sterilizations,
which, in turn, yields estimates of how the probability of
forced sterilizations changed with respect to variations in a
county’s various racial population shares. The last section
provides conclusions.
2. Irving Fisher, economic theory, race, and eugenics
policy
In the history of economic thought, the contributions of
Irving Fisher stand-out as being of singular importance to
justifications for state-sanctioned eugenic sterilization
policies. Fisher characterized his theory of interest (Fisher,
1907, 1930) as a theory of ‘‘impatience and opportunity’’.
He theorized that interest rates emerge from the balancing
by individuals of preferences for consumption today
versus consumption tomorrow.
4
This straightforward principle, which still informs
much of modern economic theory (Thaler, 1997), was
the source of additional meta-theorizing by Fisher as to
what constituted the foundations of impatience and
opportunity—or time preference.
5
Since Fisher viewed
the interest rate as an important determinant of an
economy’s investment and growth rate, knowing the
foundations of time preference could inform strategies
(e.g. policy interventions) that would be favorable to
improving a society’s living standards.
While Fisher based the broad determinants of interest
on economic and personal factors, his early refinements of
the theory were such that an important determinant of the
personal factors were determined by personal heritable
factors that conditioned the behavior of individuals. The
genetic extension of Fisher’s theory are apparent in his
lectures on the distribution of income to Yale under-
graduates between 1901 and 1910 (Aldrich, 1975). In these
lectures, Fisher posited that income is proportional to
innate ability, implying that the distribution of income
reflects the distribution of ability.
6
This necessarily follows
if a low rate of time preference produces higher future
income. If some individuals are innately predisposed
toward low rates of time preference, then their superior
position in the income distribution—relative to those
3
Cot (2005) in her examination and analysis of Irving Fisher’s
consideration of what racial-groups merit eugenic attention notes that
in 1913, Fisher advocated for the imposing of birth-control measures on
the so-called ‘‘colored races’’ in the United States.
4
As Dimand (2005) notes, Irving Fisher did not originate the theory of
‘‘impatience and opportunity’’. He merely extended and refined the
principle articulated by the classical economists Eugene von Bohm-
Bawerk, Nassau William Senior, and Fisher’s approximate contemporary
John Rae.
5
Thaler (1997), makes a case that Fisher was also a pioneer of
behavioral economics, as Fisher often appealed to departures from
rationality as a method for describing how individuals actually act when
making choices.
6
As discussed and cited by Aldrich (1975), Irving Fisher’s lectures to
Yale undergraduates between 1901 and 1910, are archived as: Irving
Fisher Papers, Yale University Sterling Memorial Library New Haven,
Connecticut.
G.N. Price, W.A. Darity Jr./ Economics and Human Biology 8 (2010) 261–272
262
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innately predisposed toward high rates of time prefer-
ence—can be rationalized.
Fisher posited early that race conditioned the genetic
distribution of endowments. In The Rate of Interest (Fisher,
1907), Theory of Interest (Fisher, 1930), and Elementary
Principles of Economics (Fisher, 1912), Fisher singled out the
Chinese, Indians, Russian peasants, and American Negroes
as being innately predisposed toward impatience and lack
of foresight. Those innate traits were viewed as ‘‘dys-
genic’’—in the sense that their prevalence in the population
increases the number of individuals who are unable to
optimize across the present and future in a way that
maximizes the wealth and income of society. As a matter of
eugenic policy Irving Fisher suggested that they should be
bred out (Fisher, 1921, p. 223):
If the birth-control exercised by individual parents
could itself be controlled by a eugenic committee it
could become the surest means of improving the
human race. Society could breed-out the unfit and
breed in the fit.
These were the sentiments, informed by economic
theory, of Irving Fisher, economist turned social reformer
and policy advocate, as first president of the American
Eugenics Society in 1922.
A key policy instrument advocated by the American
Eugenics society to breed-out the unfit was birth control.
Birth control as a policy instrument is consistent with
economic theories that significantly attribute an indivi-
dual’s marginal productivity to their genetic endowment.
The modern view of this Fisher-inspired approach to
economics is succinctly summarized by Miller (1997, p.
391), who argues that given that the distribution of
attributes and abilities is conditioned on individual genetic
endowments:
It follows that efforts to maximize a nation’s standard of
living should try to improve its citizens’ genetic quality,
especially with regard to intelligence and other
economically important traits. Improving the genetic
quality of citizens calls for having those carrying the
genes for desirable traits (as evidenced by their
possession of the traits themselves) producing more
than their proportionate share of that nation’s children.
Miller (1997) proceeds to provide a rationale for the
economics of birth control on the grounds that by targeting
the birth rates of the poor—who, in his analysis, necessarily
are poor as a result of having a genetic predisposition
toward impatience and lack of foresight—the average
standard of living will be higher.
7
While there is no evidence that Fisher explicitly
singled-out blacks as exclusive targets for being bred-
out through birth control, there is evidence that he did so
indirectly. Margaret Sanger, the founder of the American
Birth Control League was a life-long member of the
American Eugenics Society, and Irving Fisher, himself,
endorsed her plans for the First National Birth Control
Conference in 1921 (Gordon, 2007), that established the
Sanger-led American Birth Control League—which later
became the Planned Parenthood Federation of America. In
1938, Sanger initiated the ‘‘Negro Project’’, aimed at
educating black Americans about birth-control practices.
The ‘‘Negro Project’’ soon became, under the leadership of
the Birth Control Federation of America (BCFA), a program
aimed at controlling the reproduction of low income blacks
(Schoen, 2005).
8
The leadership of the BFCA held the view
that particularly in the South, blacks reproduced exces-
sively relative to whites, resulting in blacks contributing
disproportionately to the population of the unintelligent
and unfit.
It is the birth-control policy sentiments of the Negro
Project that are suggestive of Irving Fisher’s indirect
influence on how eugenic policies may have targeted
black Americans. For Fisher, birth control as a policy
instrument potentially had the most direct bearing on
eugenically engineering birth rates across demographic
categories (Fisher, 1921). Given that, at least in the 1920s,
the birth rate of whites exceeded that of non-whites, Fisher
(1921) suggested that birth control policies should be
targeted at the ‘‘colored races’’, presumably to maintain
the relative superior ‘‘germ plasm’’’ of whites who
ostensibly possessed the requisite genetic traits consistent
with optimum national well-being. In this context, by
supporting Margaret Sanger’s birth-control organization
and endorsing its propaganda, Fisher (1921) provided the
scientific credibility for a birth-control program aimed at
black Americans.
Fisher’s scientific paradigm of biological and genetic
determinism in economic behavior, and his enthusiastic
support of a social reform movement based on eugenics
could have induced path dependency in eugenic birth-
control programs directed at black Americans. In general,
a policy is path dependent if initial moves in one
direction elicit further moves in that same direction
and the trajectory of change up to a certain point
constrains the trajectory after that point (Kay, 2005).
9
We
exploit this insight in our empirical strategy to determine
7
Miller’s basic idea is that in the absence of birth control the ‘‘dysgenic’’
poor will increase in number relative to the affluent, which, in turn,
ostensibly reduces the number of high ability and high-earning
individuals in the population.
8
A project of the BCFA Extension Department, the Negro Project was
supervised by a special committee that included Margaret Sanger. It was
guided by a national Negro Advisory Council made up of representatives
of 25 major black organizations and universities, and included many
prominent black leaders. The Negro Project assembled clinical data to
influence the adoption of clinics and contraceptive techniques primarily
in the American south with demonstration projects in Nashville,
Tennessee and Berkeley County, South Carolina.
9
Collier and Collier (1991) also provide a useful framework for
considering how policy choices are subject to path dependence. They
indicate that initial conditions can define and delimit policy choices. As
such, policy agents make choices contingent on initial objectives, setting a
specific trajectory of policy actions that are difficult to reverse.
Paul David (1985) provided the influential impetus for the notion of
path dependency in the context of an optimizing choice made at a point in
time persisting across time because of the legacy of the choice. Kay (2005)
provides a useful critique of appeal to the idea of path dependency in
policy choices.
G.N. Price, W.A. Darity Jr. / Economics and Human Biology 8 (2010) 261–272
263
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whether black Americans were selective targets of
eugenic sterilization programs in North Carolina. Given
the credibility that Irving Fisher’s economic theories
provided to notions of dysgenic traits compromising a
nation’s economic welfare, and his advocacy and support
for race-specific birth-control programs, it is plausible
that early supporters of race-specific programs such as
Margaret Sanger’s American Birth Control League and the
Negro Project, pursued birth-control policy objectives
that disproportionately targeted black Americans.
Furthermore, given this initial policy objective, those
policies may have remained on a historical trajectory
carrying its own momentum.
3. North Carolina sterilization data
We examine the effects of race on eugenic sterilization
with historical data from the State of North Carolina. The
history of state-sanctioned eugenic sterilization in North
Carolina began in 1929, when the General Assembly
authorized the governing body or executive head of any
penal or charitable public institution to sterilize any
patient or inmate when it was determined to be in the
individual’s and/or the public’s best interest.
10
At the
local level, county boards of commissioners were
authorized to order the sterilization at public expense
any individual—whether convicted criminal or civilian—
determined to be mentally defective or feeble-minded
upon receiving a petition from the individual’s next of kin
or legal guardian.
In 1933 the General Assembly formally established
the Eugenics Board of North Carolina to review petitions
for the sterilization of individuals. In 1937, the General
Assembly authorized any state hospital to charge
appropriate local jurisdictions for sterilization expenses,
and North Carolina introduced the nation’s first state-
supported birth-control program (Schoen, 2001). Rela-
tive to sterilization laws in other states, the North
Carolina law was unique in that it allowed local welfare
officials to submit sterilization petitions for their clients.
As such, the scope of North Carolina’s eugenic steriliza-
tion law extended directly to recipients of public
welfare.
Under the Executive Organization Act of 1971, the
Eugenics Board was transferred to the North Carolina
Department of Human Resources. The secretary of the
Department of Human Resources—appointed by the
Governor of North Carolina—exercised managerial and
executive oversight over sterilization petitions and pro-
ceedings of the Eugenics Board. In 1973, the Eugenics
Board was reorganized and became the North Carolina
Eugenics Commission. In 1974, the North Carolina General
Assembly transferred responsibility for sterilization pro-
ceedings to the state judicial system. Finally, in 1977 the
state formally abolished the North Carolina Eugenics
Commission.
As one of 30 states to pass eugenic sterilization laws at
the turn of the 20th century, between 1929 and abolition of
its Eugenics Commission in 1977, the Stateof North Carolina
authorized over 8000 eugenic sterilizations (Schoen, 2001).
The overwhelming majority of the sterilizations apparently
were motivated by the prerogatives of eugenic science, as
Schoen (2001) found evidence that only 468 of the
sterilizations were voluntary. Eugenic sterilizations also
appear to have been subject to racial bias. Aggregate data
reported in the last publicly available report of the North
Carolina Eugenics Commission (Casebolt, 1968) indicates
that of 7141 sterilizations performed between 1929 and
1968, approximately 39 percent were on black Americans, a
level higher than their average population share—approxi-
mately 23 percent—in the state over the time period.
We use data from the 1958 to 1968 Biennial Reports of
the North Carolina Eugenics Board which report the
number of sterilizations performed at the county level.
11
While North Carolina is one of the few, if not the only state
to make its sterilization records available, our effort is
constrained to the 1958–1968 county-level data for two
reasons. First, while individual sterilization records exist,
current litigation and difficulty of access preclude research
and compilation of data from these sources.
12
Second,
while aggregate data prior to 1958 are available, they are
not reported in annual sequence for all counties.
Table 1 reports a statistical summary—the mean,
median and standard deviation—of all the covariates we
use in our analysis. The first three variables represent
sterilization data for all 100 North Carolina counties
between 1958 and 1968. We disaggregate and report by
type of sterilization: total sterilizations, total institutional
sterilizations, and total non-institutional sterilizations.
13
10
Our historical account of state-sanctioned sterilizations in North
Carolina is based on the reports provided by Brown (1935) and Schoen
(2001) and on the archival history provided in Guide to Research Materials
in the Guide to Research Materials in the North Carolina State Archives:
State Agency and Records. Second Edition (1995).
11
See Brown (1966, 1964), and Winston (1960, 1962).
12
Conversations we had with officials of the State of North Carolina
Furthermore, archives revealed that those records of individuals
sterilized are available, they are not user-friendly nor easy to compile
coherently. Pending litigation, from individuals alleging they were
sterilized wrongfully, also is a barrier to accessing individual sterilization
records.
13
Institutional sterilizations were those administered to individuals
confined to state penal, medical, psychiatric, or convalescent institutions.
Non-institutional sterilizations were those administered to individuals
not confined to state penal, medical, psychiatric, or convalescent
institutions.
Petitions for the sterilization of non-institutionalized individuals
were submitted to the Eugenics Board by the county directors of public
welfare. Petitions for the sterilization of institutionalized individuals
were submitted by the superintendents of the institutions. Sterilizations
consisted of vasectomy (clamping of vas deferens) and castration (the
removal of one or both testicles) for males; and salpingectomy (the
removal of one or both fallopian tubes) and ovariectomy (the removal of
one or both ovaries) for women.
Of the 7141 performed sterilizations authorized by the Eugenics
Board of North Carolina between 1929 and 1968, 1019 were vasectomies,
65 were castrations, 6000 were salpingectomies, and 57 were ovar-
iectomies (Craig, 1968). With respect to gender distribution, approxi-
mately 84 percent of the sterilizations were performed on females, with
black females accounting for approximately 41 percent of total female
sterilizations. Approximately 39 percent of all sterilizations were
performed on blacks, with black males accounting for about 28 percent
of total male sterilizations.
G.N. Price, W.A. Darity Jr./ Economics and Human Biology 8 (2010) 261–272
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Table 1
Covariate summary. State of North Carolina county-level sterilizations and racial-group population shares: July 1958–June 1968
Variable Mean Median Standard deviation
Total sterilizations: July 1958–June 1968 21.63 15 30.24
Total institutional sterilizations: July 1958–June 1968 3.58 2.5 3.99
Total non-institutional sterilizations: July 1958–June 1968 18.05 12.5 27.42
County share of state white population in 1960 .01 .0062 .0108
County share of state black population in 1960 .01 .0078 .0108
County share of state Native American population in 1960 .01 .0002 .0691
County share of state Chinese population in 1960 .01 0.00 .0279
County share of state Filipino population in 1960 .01 0.00 .0368
County share of state Japanese population in 1960 .01 .0008 .0461
County share of state other race population in 1960 .01 .0014 .0220
White share of county population in 1960 .7265 .7370 .1836
Black share of county population in 1960 .2545 .2458 .1807
Native American share of county population in 1960 .0085 .0002 .0368
Chinese share of county population in 1960 .00004 0.00 .00009
Filipino share of county population in 1960 .00006 0.00 .0002
Japanese share of county population in 1960 .0001 .00004 .0005
Other race share of county population in 1960 .0001 .00004 .0003
County population per square mile in 1960 94.29 63 92.40
Percent of county individuals below poverty in 1969 .253 .258 .092
County per capita income in 1969 2141.42 2093.5 419.29
Number of individuals in county served in state psychiatric hospitals in 1980 179.97 105.5 9203.84
Number of individuals in county served in state mental retardation centers in 1980 33.38 24 33.71
Notes: racial-group population shares are based on race and sex group county-level census data for 1960 from the University of Virginia Library Historical
Census Browser at http://fisher.lib.virginia.edu/collections/stats/histcensus/php/county.php. Population per square mile, percent of county individuals
below poverty, and per capita income (in 1996 dollars), number of individuals served in state psychiatric hospital, and number of individuals in county
served in state mental retardation centers, are based on census data from the North Carolina Department of Management & Budget at http://
data.osbm.state.nc.us/pls/linc.
Table 2
Fixed Effect Negative Binomial parameter estimates: county and state racial-group population share model (unobserved sterilization costs conditioned on
population density)
Specification (1) (2) (3) (4) (5) (6)
County population
share model
State population
share model
Population share regressors
White share of county
population in 1960
2.29 (1.55) .821 (1.30) 1.50 (1.24)
Black share of county
population in 1960
2.42 (1.55) 2.82 (1.29)
b
2.99 (1.24)
b
Native American share of
county population in 1960
2.23 (2.08) 1.11 (1.92) 1.59 (1.76)
Asian share of county
population in 1960
66.14 (157.43) 216.46 (167.51) 181.86 (144.99)
Filipino share of county
population in 1960
165.65 (531.36) 341.25 (419.20) 229.58 (383.39)
Other race share of county
population in 1960
275.76 (372.60) 60.08 (357.21) 79.96 (322.44)
County share of state white
population in 1960
3.88 (9.35) 42.31 (14.89)
b
35.22 (13.89)
b
County share of state black
population in 1960
5.81 (8.41) 22.48 (9.89)
b
16.24 (8.90)
c
County share of state Native
American population in 1960
.204 (.627) .281 (.766) .141 (.661)
County share of state Asian
population in 1960
3.72 (2.97) 2.53 (3.04) 1.55 (2.72)
County share of state Filipino
population in 1960
5.35 (3.95) 2.96 (3.67) 1.91 (3.39)
County share of state other
race population in 1960
7.90 (4.99) 1.74 (6.17) 3.70 (5.49)
Diagnostics
N100 100 100 100 100 100
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Institutional sterilizations were the dominant type for the
time period under consideration, constituting approxi-
mately 83 percent of total sterilizations. With respect to
institutional sterilizations, there were 15 counties where
there were none, but this was the case for only four
counties for non-institutional sterilizations. Across both
types of sterilizations, only one county—Clay—reported no
sterilizations at all. Including both institutional and non-
institutional sterilizations, over the 1958–1968 time
period, a total of 2163 sterilizations authorized by the
Eugenics Board were performed in North Carolina.
4. Theory, econometric methodology, and results
To motivate our empirical strategy, we take seriously the
economic motivations provided by Irving Fisher for state-
sanctioned eugenic sterilization policies. We posit that the
North Carolina Eugenics Commission tailored and imple-
mented what it viewed as optimal sterilization policies. In
particular we assume that for racial group ithat constitutes
some fraction 0 Q
i
1 of the population in a political
jurisdiction, there exists a sterilization target S
i
,thatis
consistent with an ideal population share Q
0
i
. This ideal
population share represents a proportion of the racial group
that is free of dysgenictraits that would otherwise retardthe
overall economic well-being of the political jurisdiction.
Formally, we assume that an optimal eugenic sterilization
policy is a solution to:
argmax
ðS
i
jQ
i
¼Q
0
i
Þfor i¼1;2;...N
racial groups. A solution yields a reduced form aggregate
sterilizationfunction S¼PS
i
ðQ
i
Þwhich is a functionof the
respective racial-group population shares.
Given prior eugenicist beliefs about ideal population
shares of particular racial groups, any belief that dysgenic
traits are disproportionately located in a particular group,
and/or not existent at all in a particular racial group, corner
solutions for racial groups are feasible. Indeed, if it is
believed that specific racial groups do not harbor any
dysgenic individuals, their existing population share will
not be subject to eugenic sterilization or S
i
¼S
i
¼0if
Q
i
¼Q
0
i
, where S
i
is the optimal number of eugenic
sterilizations for racial group i.
Our estimation strategy proceeds from a recognition
that our dependent variable is fundamentally integer-
valued and constitutes count data. Therefore, we assume
that the number of eugenic sterilizations for a county are
realizations from either a Poisson, or, if there is hetero-
geneity, a Negative Binomial count distribution. We
specify and estimate the parameters of relevant Poisson
and Negative Binomial regression specifications, where the
estimated parameters measure the effects of exogenous
variables on l—the expected number of sterilizations.
14
Since we are examining the extent to which North
Carolina eugenic sterilization policies were biased toward
particular racial groups, we specify las a function of a
county’s racial-group population allocation—both within
the county, and within the state. It is in this context that
our specifications take seriously the classic eugenic
assumptions that posit that dysgenic traits are conditioned
on or correlated with racial groups in a population.
Because sterilization was presumably a policy pre-
scription to breed out biologically dysgenic individuals,
our parameter estimates will indicate the extent to which
sterilization probabilities were conditioned on particular
racial groups. If, for example, sterilization probabilities
differ across racial groups, an implication is that eugenic
sterilization was biased and/or a certain trait that triggered
sterilization—perhaps latent—was higher among particu-
lar groups of individuals in the population. Under an
unbiased sterilization policy all racial groups would—
conditional on unobservable traits, would face the same
sterilization probabilities.
Table 2 (Continued)
Specification (1) (2) (3) (4) (5) (6)
County population
share model
State population
share model
Pseudo-R
2
.272 .156 .161 .272 .148 .154
x
2
k1
:(H
o
:
b
1
¼
b
k
¼0) 5.68 23.53
a
20.95
a
7.06 13.68
b
12.64
b
Standard errors in parentheses.
a
Significant at the .01 level.
b
Significant at the .05 level.
c
Significant at the .10 level.
Notes: racial-group population shares are based on race and sex group county-level census data for 1960 from the University of Virginia Library Historical
Census Browser at http://fisher.lib.virginia.edu/collections/stats/histcensus/php/county.php. The parameter estimates condition the unobserved
sterilization costs on county population per square mile measured as county population per square mile in 1960 reported in census data from the
North Carolina Department of Management & Budget at http://data.osbm.state.nc.us/pls/linc.
14
If a random variable S
i
conditional on
u
i
is a Poisson random variable
then Prob ðS
i
¼s
i
j
u
i
Þ¼ðe
l
i
l
s
i
i
Þ=s
i
!, for s
i
¼0;1;2...n.
A Poisson regression model is formulated by specifying for some
integer-valued measure of sterilizations S
i
for county i, the mean level
l
i
,
as a function of a vector of exogenous variables (
u
):
ln
l
i
¼
b
0
u
where
b
is a coefficient vector, and
u
is a vector of exogenous variables that
determine the expected value of the number of sterilizations S
i
for the ith
county. The log-likelihood function Lð
b
Þhas a gradient and Hessian given by:
@
Lð
b
Þ
@b
¼X½
u
0
ðS
i
e
b
0
u
Þ ¼ 0
@
2
Lð
b
Þ
@b@b
0
¼X½ðS
0
i
S
i
Þe
b
0
u
<0
Equating the gradient to zero solves for
b
, and the negativity of the
Hessian ensures a global maximum of the log-likelihood estimator of the
coefficients in
b
.
As a Poisson specification assumes there is no unobserved heterogeneity,
the mean and variance of
l
are identical. Given the possibility of unobserved
heterogeneity, the Poisson model can be modified as a Negative Binomial
(Cameron and Trivedi, 1998) where the specification of
l
is:
ln
l
i
¼
b
0
u
þ
e
i
where
e
i
reflects unobserved heterogeneity causing the mean and variance of
l
to differ.
G.N. Price, W.A. Darity Jr./ Economics and Human Biology 8 (2010) 261–272
266
Author's personal copy
We consider parameter estimates of a model with three
measures of sterilization (institutional, non-institutional,
and total) as the dependent variable, and for two distinct set
of exogenous population regressors—county racial-group
shares and state racial-group shares within a county. The
two types of measures of racial-group shares will enable us
to evaluate the context in which eugenically targeting racial
groups might have been manifest. In particular, if the goal of
eugenic sterilization policy in North Carolina was to
optimize the population share of racial groups in a political
jurisdiction, it could have been based on an ideal state racial
population share and/or ideal local racial population share.
We use the racial-group categorizations reported in the
data, and modify it by combining Japanese and Chinese into
one category of Asians, as each group constituted a small
fraction of the state’s total population, and at least from a
phenotypical perspective, may not have been easily
distinguishable from one another if, indeed, eugenic policy
officials desired to target them.
15
Since we do not observe the costs associated with any
sterilization optimization problem eugenics officials may
have been trying to solve, parameter estimates that omit
these unobservable costs could be biased. As such, Tables 2
and 3 report Fixed Effect Negative Binomial parameter
estimates for our sterilization specifications with both
county and state racial-group population shares as
regressors.
16
For each population share specification, the
dependent variable is in sequence, institutional, non-
institutional, and total sterilizations. While institutional
sterilizations are dominated by non-institutional steriliza-
tions, we report across three disaggregated specifications
of the dependent variable as we believe it is plausible that
for individuals confined to state institutions—where
institutional sterilizations took place—eugenic policy
officials had superior opportunities to engage in biased
implementation of sterilization policies, as they had better
opportunity to observe and monitor institutionalized
individuals. Moreover, non-institutional and institutional
sterilizations can be viewed as two different policy
regimes, as the process for institutionalizing individuals
into say state psychiatric facilities was distinct from that of
only recommending eugenic sterilization. As such, differ-
ent probability estimates for non-institutional versus
institutional sterilizations could inform biases that exist
in the processes that determined the two types of
sterilization probabilities.
The parameter estimates in Tables 2 and 3 condition the
unobserved sterilization costs on population density and the
number of poor individuals in a county, respectively.
17
Population density is a mechanism which can catalyze
economic growth ((Boucekkine et al., 2007; Galor and Weil,
2000)). Unobserved sterilization costs across North Carolina
counties plausibly were correlated with population density.
Where population density is high (low), sterilization costs
are lower(higher). Thiscaptures the ideathat the transaction
and information costs of sterilization decline with increases
in population density. For example, greater population
density could increase the presence of hospitals and
surgeons, thereby lowering the cos ts of sterilizat ion. Because
there is evidence that sterilization in North Carolina targeted
the poor to minimize welfare expenditures (Schoen, 2001;
Railey, 2002), the unobserved costs of sterilization could
have been correlated with the number ofpoor individuals in
a county who were either receiving or were eligible for public
assistance. Two diagnostic measures are also reported. The
explanatory adequacy of each regression is assessed with a
Wald chi-square distributed test for the null hypothesis that
the exogenous explanatory variables have parameters that
are jointly insignificant. For all specifications, pseudo-R
2
(McFadden, 1974) is reported as a goodness-of-fit measure.
With the exception of the case where the dependent
variable is total non-institutional sterilizations, the null
hypothesis that the county racial population shares jointly
have no effect is rejected for all the specifications in
Table 2.
18
In the case where the dependent variable is non-
institutional and total sterilizations, the expected number of
sterilization increases significantly with respect to a
county’s black population share and in the case of whites,
decreases significantly. This suggests that for a given county,
sterilization probabilities were disproportionately sensitive
to the size of a county’s black populations share. For Asians
and other races,the estimated coefficients,when significant,
are negative, suggesting that sterilization probabilities were
lower with respect to these racial-group population shares.
The parameter estimates reported in Table 3, which
condition the unobserved sterilization costs on the number
of poor individuals in a county, are similar to the those in
Table 2.
19
The exception being that in the state racial-
15
Combining the Chinese and Japanese population shares was
suggested by an anonymous referee.
16
We report Negative Binomial parameter estimates as simple Poisson
specifications were always rejected based on a test for the mean-variance
equality restriction—an implication of sterilizations having a Poisson
distribution. These estimates are available upon request from the authors.
All our parameter estimates condition exposure to sterilization on a
county’s total population as the reduced form sterilization function is
assumed to be optimized on ideal total racial population shares. Our fixed
effect estimator is that of Hausman et al. (1984) which estimates the
parameters of the Negative Binomial regression with the following
restrictions:
EðSÞ¼exp ðDþ
b
XÞ
VarðSÞ¼ð1þe
D
ÞEðSÞ
where eis a natural logarithm, Xis a vector of exogenous variables, and Dis a
vector of county dummies correlated but fixed with some unobserved effect.
17
In particular, we panel the data not by time, but by population density
and poverty population z-scores. For an example of this type of panel
structure and fixed effect parameter estimation see Geronimus and
Korenman (1992).
18
We use county population per square mile in 1960 as the variable
measuring the unobserved fixed effect. It is implemented by forming
county groups based on standardized z-scores with endpoints of 3 and
þ3. Within county groups, unobserved costs are correlated, but fixed
across all county groups. County population per square mile in 1960 data
were obtained from the University of Virginia Library Historical Census
Browser at http://fisher.lib.virginia.edu/collections/stats/histcensus/php/
county.php.
19
The parameter estimates condition the unobserved sterilization costs
on standardized values (e.g. standard normal variates between 3 and 3)
of the percent of a county’s population that was poor in 1969. This was
measured as the percent of county individuals at or below poverty in
1919 reported in census data from the North Carolina Department of
Management & Budget at http://data.osbm.state.nc.us/pls.linc.
G.N. Price, W.A. Darity Jr. / Economics and Human Biology 8 (2010) 261–272
267
Author's personal copy
group share specifications (columns 3–6), none of the
coefficients are jointly significant. This suggests that if
indeed eugenic officials were using sterilization as a
mechanism to limit poverty, blacks were still sterilization
policy targets with respect to minimizing their share of the
population as a share of total county population, but not as
a share of the state population.
Collectively, the parameter estimates in Tables 2 and 3
are consistent with the interpretation that if state and
county eugenics policy officials had distinct conceptions
about ideal racial population ratios and /or which racial
groups should be objects of the sterilization policy, both
state and county officials behaved as if the population
share of blacks should be targeted for reduction. The
probability of sterilizations increased significantly with
the black population share both at the county level and
when measured relative to the county’s state share of
blacks in the entire state.
For total sterilizations, the fact that among all racial
groups, the black population ratio is the only share that is
positive and significant in Tables 2 and 3 suggests that
North Carolina’s eugenic sterilization policy not only was
biased but genocidal, insofar as positive and significant
sterilization probabilities conditioned on a county’s black
population has the effect of reducing the size of the black
population.
20
That the results in Tables 2 and 3 differ only
in how unobserved sterilization costs are specified—the
sign and significance of the black population parameters
are similar for the specifications where there is joint
significance of all parameters. This suggests that the racial
Table 3
Fixed Effect Negative Binomial parameter estimates: county and state racial-group population share model (unobserved sterilization costs conditioned on
poverty population)
Specification (1) (2) (3) (4) (5) (6)
County population
share model
State population
share model
Population share regressors
White share of county
population in 1960
2.37 (1.56) .839 (1.31) 1.58 (1.25)
Black share of county
population in 1960
2.02 (1.57) 2.63 (1.30)
b
2.70 (1.25)
b
Native American share of
county population in 1960
1.54 (2.23) .896 (2.01) 1.22 (1.86)
Asian share of county
population in 1960
111.15 (145.11) 227.78 (158.33) 195.60 (135.77)
Filipino share of county
population in 1960
68.37 (479.43) 351.09 (427.09) 249.98 (384.51)
Other race share of county
population in 1960
117.11 (363.40) 85.52 (345.40) 35.90 (307.48)
County share of state white
population in 1960
10.15 (12.48) 7.29 (13.09) 3.39 (11.04)
County share of state black
population in 1960
5.36 (10.81) 18.61 (9.86)
c
12.47 (8.69)
County share of state Native
American population in 1960
.102 (.677) .667 (.869) .588 (.756)
County share of state Asian
population in 1960
.783 (2.74) .132 (3.05) .931 (2.67)
County share of state Filipino
population in 1960
1.06 (3.68) .445 (3.97) 1.30 (3.49)
County share of state other
race population in 1960
4.47 (5.31) 5.04 (6.24) 6.32 (5.46)
Diagnostics
N100 100 100 100 100 100
Pseudo-R
2
.263 .153 .158 .259 .143 .151
x
2
k1
:(H
o
:
b
1
¼
b
k
¼0) 4.18 13.01
b
10.48
c
4.39 6.36 6.36
Standard errors in parentheses.
a
Significant at the .01 level.
b
Significant at the .05 level.
c
Significant at the .10 level.
Notes: racial-group population shares are based on race and sex group county-level census data for 1960 from the University of Virginia Library Historical
Census Browser at http://fisher.lib.virginia.edu/collections/stats/histcensus/php/county.php. The parameter estimates condition the unobserved
sterilization benefits on standardized values (e.g. standardized normal variates between 3 and 3) of the percent of a county’s population that was
poor in 1969. measured as the percent of county individuals at or below Poverty in 1969 reported in census data from the North Carolina Department of
Management & Budget at http://data.osbm.state.nc.us/pls/linc.
20
The United Nations Convention of the prevention and punishment of
the crime of genocide, ratified in January of 1951 defines genocide as any
of the following acts committed with intent to destroy, in whole or in part,
a national, ethnic, racial or religious group: (1) killing members of the
group, (2) causing serious bodily or mental harm to members of the
group, (3) deliberately inflicting on the group conditions of life calculated
to bring about its physical destruction in whole or in part, (4) imposing
measures intended to prevent births within the group, and (5) forcibly
transferring children of the group to another group.
G.N. Price, W.A. Darity Jr./ Economics and Human Biology 8 (2010) 261–272
268
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Table 4
Negative Binomial parameter estimates augmented with controls: county and state racial-group population share model
Specification (1) (2) (3) (4) (5) (6)
County population
share model
State population
share model
Population share regressors
Constant 1.96 (2.26) .833 (2.57) .687 (2.10) 1.22 (1.75 .177 (2.51) .268 (2.02)
White share of county population in 1960 1.18 (1.52) .341 (1.37) .474 (1.14)
Black share of county population in 1960 1.44 (1.55) 3.25 (1.38)
b
2.86 (1.15)
b
Native American share of county
population in 1960
3.85 (2.27)
c
3.30 (2.68) 3.19 (2.17)
Asian share of county population in 1960 195.38 (172.79) 156.19 (225.91) 162.19 (183.25)
Filipino share of county population in 1960 302.85 (498.40) 164.16 (556.32) 184.75 (444.24)
Other race share of county population in 1960 530.27 (386.33) 604.62 (408.51) 611.85 (343.53)
County share of state white population in 1960 44.89 (18.49)
b
17.83 (28.69) 21.86 (23.65)
County share of state black population in 1960 19.02 (14.85) 57.14 (23.32)
b
47.39 (18.78)
b
County share of state Native American
population in 1960
1.85 (.755)
b
.157 (1.39) .492 (1.12)
County share of state Asian population in 1960 3.25 (2.84) 6.15 (4.83) 5.19 (3.91)
County share of state Filipino population in 1960 6.31 (3.69)
c
8.62 (6.67) 7.60 (5.28)
County share of state other
race population in 1960
8.55 (6.17) 4.66 (8.12) 5.41 (6.55)
Controls
Number of individuals in county
served in state psychiatric
hospitals in 1980
.0009 (.0004)
b
.000004 (.0007) .0002 (.0005) .001 (.0004)
b
.0002 (.0008) .0001 (.0006)
Number of individuals in county
served in state mental retardation
centers in 1980
.003 (.004) .011 (.006)
c
.009 (.005)
c
.012 (.007)
c
.003 (.009) .004 (.008)
County population per square mile in 1960 .002 (.005) .002 (.002) .002 (.002) .001 (.009) .002 (.002) .002 (.002)
Percent of county individuals at
or below poverty in 1969
.608 (2.55) 1.12 (3.30) .601 (2.66) 1.72 (2.50) 2.81 (3.57) 2.79 (2.86)
County per capita income in 1969 .0006 (.0006) .0002 (.0008) .0003 (.0006) .0006 (.0006) .0005 (.0008) .0005 (.0007)
Diagnostics
N100 100 100 100 100 100
Pseudo-R
2
.152 .086 .102 .171 .072 .089
x
2
k1
:(H
o
:
b
1
¼
b
k
=0) 72.65
a
66.97
a
83.69
a
81.85
a
56.33
a
73.09
a
x
2
1
: 12.23
a
601.72
a
536.0
a
3.09
b
605.89
a
515.46
a
Standard errors in parentheses.
a
Significant at the .01 level.
b
Significant at the .05 level.
c
Significant at the .10 level.
Notes: racial-group population shares are based on race and sex group county-level census data for 1960 from the University of Virginia Library Historical Census Browser at http://fisher.lib.virginia.edu/collections/
stats/histcensus/php/county.php. Number of individuals in county served in state psychiatric hospitals, Number of individuals in county served in state mental retardation centers, county population per square
mile in 1960, percent of county individuals at or below poverty in 1969, and per capita income in 1969 (in 1996 dollars) are based on census data from the North Carolina Department of Management & Budget at
http://data.osbm.state.nc.us/pls/linc.
G.N. Price, W.A. Darity Jr. / Economics and Human Biology 8 (2010) 261–272
269
Author's personal copy
bias of sterilization policy in North Carolina was predicated
upon racial population share ideals—at least in terms of
county population shares.
The parameter estimates in Tables 2 and 3 are
consistent with genocide in several ways. First, while
blacks were not the only victims of eugenic sterilization,
during the period 1958–1968 they accounted for a
disproportionate number of state ordered sterilizations
relative to their share of the North Carolina population.
Indeed, while non-black racial groups accounted for the
majority of sterilizations over the time interval under
consideration, their population shares do not significantly
explain their likelihood of sterilization. While this effect
could reflect the fact that relative to blacks, non-black
racial groups were more evenly dispersed spatially across
the state, that sterilization probabilities are only sensitive
to the black population share in both county and state
share population specifications suggest that the spatial
distribution of racial-groups shares is not confounding the
parameter estimates.
For non-black racial groups, our parameter estimates
suggest that eugenic sterilizations were authorized and
administered for reasons unrelated to their population
shares, whereas, for blacks eugenic sterilizations were
authorized and administered with the aim of controlling
their population share.
Of course, it is possible that in North Carolina
sterilization policy officials were also optimizing steriliza-
tions directly on other desired and presumably heritable
economic and/or health outcomes, and not necessarily on
racial population shares as our specifications and para-
meter estimates in Tables 2 and 3 imply. Consequently, our
fixed effect parameter estimates could suffer from omitted
variable bias, caused by unobservables not accounted for in
our fixed effect estimates. To evaluate our parameter
estimates for robustness with respect to these potential
omitted variables, we add additional controls directly into
to our population-group allocation model of eugenic
sterilization.
The parameter estimates in Table 4 consider whether
the objectives of eugenic sterilization policy officials
included minimizing the incidence of poverty and max-
imizing the incidence of wealth—both according to classic
eugenics theory presumably driven by heritable biogenetic
traits. We capture this by adding to the specification for
each county the percent of individuals who were at or
below poverty in 1969 and county per capita income in
1969. To control for the costs of sterilization, we also
include population per square mile in 1960 to render the
specification comparable to the population exposure
specifications in Tables 2 and 3. We also account for the
possibility that sterilization policies in North Carolina were
motivated by reducing the population share of individuals
determined biologically unfit due to some heritable
deficient mental health characteristic—the so-called ‘‘fee-
ble-minded’’. We capture this by adding as controls two
proxy variables from a later time period, since no measures
capturing the mental health characteristics of a county’s
population were available in close time proximity to the
1958–1968 time period under consideration. Our proxy
variables measuring the mental health characteristics of a
county’s population are: (1) the number of individuals in a
county served in a state psychiatric hospital in 1980 and
(2) the number of individuals in a county served in state
mental retardation centers in 1980.
21
Relative to the parameter estimates in Tables 2 and 3,
there are some differences for the parameter estimates
with augmented controls in Table 4. For institutional
sterilizations, the probability increases with respect to the
Native American population share for the county share
specification, and with respect to increases in the white,
Native American, and Filipino population in the state share
specification. Because these specifications control for the
individual mental health characteristics of a county and
because institutional sterilizations were a small fraction of
total sterilizations, this suggests that perhaps whites,
Native Americans, and Filipinos constituted a large fraction
of institutional sterilizations as a result of being deemed
mentally deficient. This implication is reinforced by the
fact that the populations shares of these racial groups is
insignificant when the regress and is non-institutional and
total sterilizations—only the black population share is
significant.
That the sign and significance of a county’s black
population share remains the same for institutional and
total sterilizations—a pattern that is approximately iden-
tical to the parameter estimates reported in Tables 2 and 3
where there are no controls—suggests that our results are
fairly robust with respect to omitted variables that capture
other possible policy objectives of eugenic sterilization
officials in North Carolina. Thus, even if eugenic steriliza-
tion policy officials in North Carolina had other stated
policy objectives unrelated to racial-group population
shares in a county or state, our results suggest that actual
total sterilization outcomes were conditioned primarily
upon a county’s black population share.
5. Conclusion
Were eugenic sterilization policies racist in intent,
design and effect? Eugenic sterilization policies were
motivated historically by appeals to social Darwinism and
economic theory which posited that certain racial and
social groups were ‘‘‘biologically unfit’’ and ‘‘dysgenic’’. It
was argued that their behavior constrained economic well-
being for the total population.
22
For eugenicists, economic well-being could be opti-
mized if the biologically unfit dysgenic racial groups were
sterilized—economically bred-out. This policy sentiment
21
It is possible that our 1980 proxies for the number of individuals in a
county with so-called mental defects are poor measures of their
contemporaneous measures. If true, one could make a case for not using
them at all—omitting them. However, Wickens (1972) demonstrates that
the parameter bias from omitting poor proxies is greater than the
parameter bias with including them.
22
The historical motivations of eugenics apparently have not dis-
appeared in contemporary times. In 2008, a Louisiana state legislator
introduced a bill that would pay poor women $1000 to have their
fallopian tubes tied to minimize the growth of a population in Louisiana
that would be dependent upon federal and state-supported income
assistance (Waller, 2008). As far as we know, this bill did not pass and
become a law.
G.N. Price, W.A. Darity Jr./ Economics and Human Biology 8 (2010) 261–272
270
Author's personal copy
was inspired by Irving Fisher, an enthusiastic supporter
and champion of eugenics at the turn of the 20th century.
While Fisher later moderated his views on the so-called
biologically unfit and dysgenic characteristics of blacks,
others continued to maintain such views. Fisher’s early
support of eugenics policy organizations could have
induced a policy path dependency that resulted in black
Americans being disproportionate targets of eugenic
sterilization.
23
Using data from North Carolina on official eugenic
sterilizations conducted between 1958 and 1968, we have
considered the extent to which sterilization probabilities
were conditioned on the share of blacks in the population.
This is one way in which an optimal eugenics policy could
manifest itself given its presumption of a positive
correlation between biological unfitness, dysgenic traits
and racial-group population shares. Our results, based on
count data parameter estimates show that in North
Carolina, the incidence of sterilization was conditioned
on race, as the probability of institutional and total
sterilization rose with the black population share. This
effect also was unique and appears to be robust as total
sterilization probabilities were not sensitive to the
population shares for any other racial group. Nor were
our results altered by inclusion of control variables
measuring eugenic sterilization policy objectives unre-
lated to racial-group population shares such as individual
mental health and poverty status. While other racial
groups were sterilized under North Carolina’s eugenics
programs, our results suggest that since sterilization
probabilities were not sensitive to their populations
shares, these other racial groups were sterilized for reasons
other than controlling their population share. Such a
eugenics policy prescription apparently was reserved for
North Carolina’s black population.
Like Price et al. (2008), our findings have implications
about the need for and efficacy of policy interventions
designed to achieve equal treatment for groups subjected
to discriminatory treatment and stigmatization. Racial
stigma and its attendant presumption of inferiority—
biogenetic or otherwise—has consequences for the histor-
ical trajectory of black–white disparities in social and
economic outcomes. In this context, traditional public
policy interventions based on ensuring equal treatment of
blacks can have limited efficacy, as historically based racial
stigma constrains whites to view blacks as being less than
equal. The eugenics movement clearly viewed blacks and
whites as biologically and genetically unequal, and not
worthy of equal treatment.
Our results show that in North Carolina, eugenics policy
did not treat blacks and whites equally. The stigma of a
belief in black biogenetic inferiority shaped a vulgar social
outcome in North Carolina—racially disparate state-sanc-
tioned eugenic sterilization.
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23
There were several other influential economists associated with the
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