Self-Identified Sexual Orientation and the
Lesbian Earnings Differential
Michael E. Martell
Franklin and Marshall College
mmartell@fandm.edu
Mary Eschelbach Hansen
American University
mhansen@american.edu
December 15, 2014
Abstract
Two decades of research on differences in labor market outcomes by
sexual orientation has concluded that lesbian workers earn more than
heterosexual women. This research, however, is largely based upon
data that do not ask respondents about their own sexual orientation.
We are the first to use nationally representative data that includes selfidentified sexual orientation. We find evidence of a sizable wage penalty
for self-identified lesbians in 2008 and 2010. We show that using common behavioral proxies for sexual orientation overstates of the earnings
of lesbians in some years, but understates it in other years. Using the
different methods of identification leads to different conclusions about
the way the recession affected lesbians: It took much longer for the
wages of self-identified lesbians to recover.
Virtually all existing estimates of wage differentials by sexual orientation in
the U.S. depend on surveys that do not ask respondents about their own sexual
orientation. Researchers must classify respondents as gay, lesbian, or bisexual
using gender information together with reports of cohabitation status or sexual
behavior. That is, same-sex sexual orientation is implied if both members of
a co-habiting couple are of the same gender or if a respondent reports having
sexual relations with a partner of the same sex. Neither method is ideal. Using
the cohabitation status method fails to identify homosexual respondents who
are not currently living with a partner, while using the sexual behavior method
1
omits some sexually inactive homosexuals and includes respondents who would
not self-identify as heterosexual.
Nearly two dozen studies have used these methods of researcher identification to document an earnings penalty for gay men in the United States. About
half of these studies also document an earnings premium for lesbian women,
but half find no significant difference among women by sexual orientation.
There is some recent evidence of a declining lesbian premium (Cushing-Daniels
and Yeung 2009). To our knowledge, the only study that finds a statistically
significant earnings penalty for lesbian women in the U.S. is Carpenter (2005),
which is also the only study to date that uses self-reported sexual orientation.
Carpenter’s data are limited to California. In this paper, we use self-reported
sexual orientation and earnings data from the three most recent General Social
Surveys. We find that the method of classification matters for understanding
the evolution of wage differentials for lesbian, gay, and bisexual workers. We
observe a penalty for both self-identified and researcher-identified lesbians in
2008, confirming Carpenter’s findings. Further, we find that trends in wage
differentials between the self-identified and researcher-identified groups vary
in a meaningful way: Self-identified lesbians still had a substantial earnings
penalty in 2010, but researcher-identified lesbians did not.
We consider two reasons why the measured earnings penalty might differ
by method of identification. First, we consider differences in the composition
of the self-identified and researcher-identified groups. Second, we consider
differences in returns to human capital and family characteristics, as well as
differences by region and occupation. The data show that the recent economic
downturn affected both researcher-identified and self-identified lesbians negatively but it took longer for self-identified lesbians to recover. The observed
wage differentials in the 2008 correspond to the time leading up to the offi-
2
cial begining of the recession. While the lead up to the recession negatively
affected both self-identified and researcher-identified lesbians, the labor market outcomes for self-identified lesbians remained poor for a longer time than
outcomes for the group that includes women who have homosexual behaviors
but self-identify as heterosexual.
The Lesbian Wage Puzzle
Badgett (1995) was the first to note the asymmetry in wage differentials for
male and female homosexuals. She documented a wage penalty for behaviorally gay men, and found a positive but statistically insignificant wage premium for lesbians. The asymmetry in the results for gay men and lesbians
is difficult to reconcile with standard economic theory (for example, Becker
1957), so Badgett’s findings prompted a number of follow-up studies. In table
1 we summarize the results for lesbians in studies of the U.S.1
– Table 1 about here –
The follow up studies confirmed the asymmetry in wage differentials for
gay men and lesbians and documented large and significant earnings premia
for lesbians. Klawitter and Flatt (1998) were the first to find a significant
earnings premium for lesbians in their study of the impact of Employment
Nondiscrimination Acts (ENDAs) on the wages of gay men and lesbians. Many
studies subsequently documented a lesbian premium (Clain and Leppel 2001;
Berg and Lien 2002; Black, Markar, Sanders, and Taylor 2003; Blandford
2003; Comolli 2005), leading to a general consensus that lesbians appear to
be at an economic advantage relative to heterosexual women.2 This work
1
Most studies have been of the U.S, but studies have also found a lesbian premium in Sweden and the U.K. (Ahmed and Hammarstedt 2010; Ahmed, Andersson, and Hammarstedt
2011; Ahmed, Andersson, and Hammarstedt 2013; Arabsheibani, Marin, and Wadsworth
2004). In Greece however, there is evidence of a lesbian penalty (Drydakis 2014).
2
More recent research has begun to investigate the source of the lesbian earnings pre-
3
also consistently documented the significant earnings penalty for gay men,3
even though the authors used different data sources and different definitions
to identify homosexuals.
The two main data sources in the literature are the General Social Surveys
(GSS) and the U.S. Census. The Census does not ask questions about sexual behavior, but, as noted above, researchers identify same-sex cohabitants
as homosexual. Omitting single homosexuals may introduce bias if single respondents are systematically different from cohabiting respondents. Further,
the selection process into partnership varies between homosexual and heterosexuals (Carpenter and Gates 2008). All of the studies using the Census find
a statistically significant annual earnings premium for lesbians relative to heterosexual women, but the range of estimates of the premium is quite wide.
To illustrate: Baumle and Poston (2011) find a premium of four to nine percent, while Antecol, Jong and Steinberger (2008) find a premium of about 30
percent.
Since 1988, the GSS has asked respondents about their sexual behaviors
and sexual histories. Researchers using the GSS have available several measures of sexual behavior with which to identify homosexuals, which we discuss
in more detail below. None of these measures is a perfect proxy for sexual
orientation. Using sexual behavior to identify homosexual respondents omits
sexually abstinent respondents. More importantly, it wrongly classifies some
heterosexual respondents as homosexual and some homosexual respondents as
mium. A portion of the measured premium is attributable to the higher levels of human
capital that lesbians have relative to heterosexual women (Antecol, Jong, and Steinberger
2008). Further, the lesbian premium is larger among lesbians who have never been married
(to a man), which suggests that the lesbian premium may be related to decreased household
specialization for lesbians (Daneshvary, Waddoups, and Wimmer 2009). However, the lesbian premium remains intact after accounting for differentials in the presence of and return
to children in lesbian households (Jepsen 2007). We discuss this literature in greater detail
below.
3
An exception is Clarke and Sevak (2013), who find evidence of a premium for gay men
in recent years.
4
heterosexual. Misclassification is more likely among women than men because
heterosexual women are more likely than heterosexual men to have sex with
a member of the same sex (Laumann et al., 1994, Peplau, 2003). In 2008,
the GSS began asking respondents to identify their own sexual orientation.
The addition of information on self-identified sexual orientation represents a
substantial improvement in our ability to study lesbians in the GSS.
The GSS, unfortunately, has other weaknesses. It reports individual income
only within ranges. Most studies that use the GSS transform income ranges
into other measures or supplement income ranges with additional data from
other sources, as described below. Researchers using the GSS from the 1990s
have generally found a statistically significant lesbian income premium, with
estimates of the premium in the comparatively narrow range of 30 to 38 percent
(Berg and Lien 2002; Black, Markar, Sanders, and Taylor 2003; Blandford
2003).
Perhaps the greatest weakness of the GSS is that each year’s sample is
small. For this reason, researchers who use the surveys across a long span
of time have been more likely to obtain statistically significant results than
those who use only one or two years of the data. An exception is CushingDaniels and Yeung (2009), who use the longest run of GSS: 1988 through
2006. After correcting for selection into full-time work, they find no statistically significant differences in earnings by sexual orientation for either men or
women. Moreover, they find the familiar lesbian premium for married lesbians
only, and they find a (statistically insignificant) penalty for unmarried lesbians.
Cushing-Daniels and Yeung interpret this as evidence of a diminishing of the
premium over time, though Carpenter (2005) suggests that similar evidence
from the 1998-2000 GSS might be associated with changes in the propensity
of lesbians to work full time.
5
Carpenter (2005) is, to our knowledge, the only paper to date that utilizes
a survey conducted in the U.S. in which respondents are asked to identify their
own sexual orientation.4 The data are from the California Health Interview
Survey of 2001 and reveal no statistical difference in hourly wages for gay men
or lesbian women. However, in nearly all the specifications the coefficient on
sexual orientation is negative and in some specifications there is a statistically
significant wage penalty for bisexual women. While data for California are
unlikely to be representative of the entire U.S., it is possible that the difference
between Carpenter (2005) and the typical study is explained by differences
between self-identified and researcher-identified lesbians.
The Importance of Classification
The classification of workers as heterosexual or homosexual is important to
the estimation of wage differentials for two reasons. First, economic theories
that aim to explain the differences in the labor market experiences of lesbian,
gay, and bisexual (LGB) workers highlight the role of identity and disclosure
of an LGB orientation on individual economic outcomes. Second, errors in
classification may represent important omitted variable bias.
Consider the argument that a wage differential for homosexuals may be the
result of differences in patterns of household specialization (Black, Sanders,
and Taylor 2007). The logic is that a lesbian might invest in more human
capital than her heterosexual counterpart because she does not expect to have
a male partner who will specialize in market work. Conversely, a gay man
might invest less in his human capital than his heterosexual counterpart.5
4
Plug and Berkhout (2008) have self-identified sexual orientation of young men the
Netherlands. They find a penalty that they attribute to occupational selection. Carpenter
(2008) has self-identified data for Canada and find a lesbian premium.
5
Of course, this has not been observed empirically as nearly every study documents that
6
This theory of specialization is motivated by identity: We would not expect
women who sleep with women but identify as heterosexual to have different
human capital investments than the representative heterosexual woman.
The disclosure of sexual orientation is also key in theories of discrimination
against LGB workers. The application of standard theories of discrimination
to the LGB case requires employers, co-workers, or customers to observe the
sexual orientation of an LGB worker in order to discriminate against him or
her. Of course, LGB workers are able to conceal their sexual orientation, although the desire to disclose sexual orientation and live openly may motivate
LGB workers to choose tolerant workplaces and accept compensating differentials (Martell 2013a).
Finally, classification might matter if heterosexual women who sleep with
women are systematically different from other women in unobservable characteristics. For example, suppose women who identify as heterosexual and
sleep with women – an unconventional if not uncommon sexual practice – are
unconventional in other ways. If these women exhibit unconventional personal
behaviors in the workplace, their being identified as lesbian by researchers will
bias wage estimates of lesbians. Alternatively, some lesbians who self-identify
may exhibit traditionally masculine traits, such as assertive or risk-taking behaviors, while other lesbians may have workplace behaviors that conform more
to gender norms. In all of these examples, it is possible that an unobserved
personality characteristic – not sexual orientation – is the true cause of any
observed wage differential.
Classifying workers as heterosexual or homosexual based on their selfidentification is also important for analyzing the impact of public policies
such as ENDAs on LGB workers. Important differences between researchergay men and lesbians both have more education than their heterosexual counterparts.
7
identified and self-identified lesbians limit the ability of researchers to accurately measure the effectiveness of public policy directed towards self-identified
LGB workers. Self-identification is also important to measuring changes over
time in the labor market outcomes of LGB workers. If increased tolerance of
homosexuality is accompanied by increases in the likelihood that those engaging in same-sex sexual relations will self-identify, observed changes in wages
or employment outcomes for researcher-identified LGB workers may represent
changes in the composition of that group rather than changes in the actual
experiences of self-identified LGB workers.
This paper is the first to explore the extent to which estimated wage differentials vary across methods for measuring sexual orientation. We show
that using different methods leads to meaningfully different estimates of wage
differentials for lesbians.
Empirical Approach
We follow the existing literature on estimating wage differentials for lesbians,
but we also allow the wage differential to vary over time. We predict log hourly
wages,
ŵi = α + β1 Li + β2 Yit + β3 (Li ∗ Yit ) + βXi + i
(1)
where Li is a dummy variable taking a value of one if a female respondent
self-identifies as a lesbian or bisexual. Yit is a year fixed effect, and Li ∗ Yit is
an interaction term between “lesbian” and “year” that allows us to capture
differences in the wage differential over time. Xj is a vector of control variables
that includes measures of human capital (years of education and potential experience, its square, and interaction between lesbian and potential experience)
and demographics and family characteristics (race, marital status, number of
8
children, region of residence and residence in a metro area). Some specifications below also include interaction terms between lesbian sexual orientation
and characteristics such as potential experience and number of children.
Note that our dependent variable is the hourly wage. Hourly wage is not
recorded in the GSS, but we use the two-step procedure outlined elsewhere to
estimate it (Martell 2013a; Martell 2013b). We first estimate dollar amounts
for annual earnings within the categories reported in the GSS following Badgett’s (1995) approach, which is also the most common approach.6 For each
year of the GSS, we use that year’s Current Population Survey to compute the
median annual earnings within each earnings range for all women who work.
Medians are reported in 2010 dollars. This procedure allows the estimate of
earnings to vary across time within the fixed ranges used by the GSS. However,
for each point in time, variation is still limited, which increases the probability
of type two error (failing to detect wage differentials when they exist).
To compute hourly wage, we divide annual earnings by annual hours of
work. Annual hours is the number of hours the respondent worked last week,
as reported in the GSS, times 50 work-weeks. This hours information was
not available in many of the earlier versions of the GSS that also had sexual
behavior information. In our main specifications we restrict the estimation
sample to those reporting in the GSS that they work full-time. Full-time
workers reported a mean of 43 hours per week with a standard deviation of
10 hours. We also provide specifications with log(annual earnings) as the
dependent variable for comparability with earlier studies.
– Table 2 about here –
6
There have been several approaches to estimating earnings with the GSS. A straightforward approach is to use the midpoint of the income categories reported in the GSS. A
second approach that utilizes the categorical income information is to estimate the probability of being in one category relative to the others using maximum likelihood (Berg and Lien
2002). Findings using the GSS data from the 1990s were consistent regardless of measure
of income.
9
As noted above, because homosexual and bisexual orientation are relatively
rare, the number of lesbians in the GSS is small. Table 2 shows the number of
self-identified lesbians and bisexual women in the sample, along with descriptive statistics of the independent variables. The data include 38 self-identified
lesbian or bisexual women who work full-time, which is just over three percent of the population. This estimate is consistent with existing counts in the
demographic literature (Berg and Lien 2006). Combining lesbians and bisexuals in the data aligns our specifications with those in the existing literature
and creates a larger sample size for estimation. Self-identified lesbians are less
likely to be married, have fewer children, and are more likely to be white than
heterosexual women. We would normally expect these characteristics to be
associated with higher earnings for women. However, self-identified lesbians
have lower average hourly wages than heterosexual women. Annual earnings
of the two groups are not different.
Table 3 shows the estimated wage differentials for self-identified lesbians.
Specifications (1)-(3) show differentials in the hourly wage; specifications (4)(6) show differentials in annual earnings. The first two specifications in each
group of three include full-time workers only; specifications (3) and (6) include
both full-time and part-time workers. All specifications include controls for
census region, and specifications (2)-(3) and (5)-(6) add controls for occupation. All specifications also include an interaction between sexual orientation
and experience, which was suggested by Badgett (1995) and included in nearly
all studies. The interpretation of this coefficient is discussed at length below.
– Table 3 about here –
We find a large but statistically insignificant wage penalty for self-identified
lesbians who worked full-time in 2008. The wage penalty in 2008 is statisti-
10
cally significant when part-time workers are included.7 We find a larger and
statistically significant wage penalty in 2010 that is robust to the inclusion of
occupational controls. The wage penalty in 2010 is approximately 50 percent
of the mean wage, or $6.50 an hour.8 We estimate a wage penalty of just six
percent in 2012, but it is not statistically significant. We find a significant
difference in annual earnings only in 2008 and only when part-time workers
are included.9
Finding a lesbian wage penalty during a period when non-discrimination
laws have come to protect many lesbians and gay men, and when public opinion polls suggest that acceptance of same-sex marriage and child-rearing are
rising, presents a new puzzle for researchers. By 2008, the beginning of the period that our data span, nearly half of all states had implemented laws making
employment discrimination based on sexual orientation illegal (Martell 2013b).
While the passage of these laws had many causes, public support of protection from discrimination for gay and lesbian workers was an important factor
(Haider-Markel and Meier 1996; Klawitter 2011). Indeed, an increase in tolerance in states with non-discrimination laws (Martell 2013b) has been accompanied by increasing levels of tolerance of homosexuality across the country
(Smith 2011). To investigate this puzzle, we consider whether:
1. The penalty is the result of the use of self-identified sexual orientation
rather than researcher assignment to the lesbian group. Is there a measurable penalty for researcher-identified lesbians? Are the lesbians who
self-identify different in important ways from the people to whom re7
We also note that self-identified lesbians are more likely to be unemployed each survey
year. The largest difference was in 2008 when 11 percent of self-identified lesbian respondents
were unemployed in 2008 while only three percent of heterosexual women surveyed were
unemployed.
8
Marginal effects are calculated as eβ1 − 1.
9
Lesbians may be compensating for a lower hourly wage by working more (Klawitter
2011).
11
searchers assign homosexual orientation?
2. The penalty is a result of mis-specification of the model. Are there
important differences in returns to characteristics between lesbians and
heterosexuals, or changes in those returns over time, that eliminates the
penalty?
The Role of Researcher Assignment
We begin our investigation of the role of researcher assignment of sexual orientation by estimating wage differentials for researcher-identified lesbians for
comparison with the results in table 3. We consider two ways to identify
respondents as lesbian. We use the most common definition from the literature, which is to identify a respondent as lesbian if she had any same-sex sex
partners in the last five years. We also include a less-common definition: a
respondent is identified as lesbian if half of her sex partners since the age of
eighteen have been female. Previous research has also identified respondents
as lesbian if they have had at least one same-sex sex partner in the previous
year or at least once since the age of eighteen. We focus on the “last five years”
and “half of sex partners” definitions because they are most closely correlated
with self-identified sexual orientation in our data.
Table 4 shows that there were statistically significant and large wage and
earnings penalties for researcher-identified lesbians in 2008, regardless of definition or specification. On average, the penalty for researcher-identified lesbians
in 2008 is one-third larger than the largest statistically significant penalty
measured for self-identified lesbians. In 2010, however, researcher-identified
lesbians experienced a significant wage premium after controlling for occupation in specification (3). In 2012 we observe wage and earnings premia in five of
the six specifications. These results do not mirror the results for self-identified
12
lesbians in table 3, for whom there was a wage penalty for full-time workers in
all years, with the largest, statistically significant, and robust penalty found
in 2010. Identity and disclosure matter.
–Table 4 about here –
To investigate further the role of identity and disclosure, we consider women
who both self-identify as lesbians and are identified by researchers using the
“past five years” definition of sexual behavior. These results are shown in
the first and second columns of table 5. For the intersection of the sets of
self-identified and researcher-identified lesbians, we find a wage penalty for
lesbians in 2008, but it is statistically significant only when we include parttime workers in specification (2). We document a larger penalty for the union
of the sets, as shown in the third and fourth columns of table 5. We also find a
wage premium in 2012 for the union of researcher-identified and self-identified
lesbians. The results for the union of the sets appear to be dominated by
outcomes for researcher-identified lesbians, while the results for the intersection
of the sets (2) are similar, but not identical, to the results for self-identified
lesbians. Again we see that identity and disclosure matter in the estimation
of the wage differential.
–Table 5 about here –
A comparison of the descriptive statistics in tables 2 and 6 reveals that,
on average, self-identified lesbians are similar to women who are classified as
lesbian based upon their sexual behaviors. Self-identified lesbians are (unsurprisingly) less likely to be married. They have fewer children and have more
education. None of these differences is statistically significant.
– Table 6 about here –
However, a large proportion of respondents are misclassified: 20 percent of
self-identified lesbians would not be classified as lesbians on the basis of their
13
reported sexual behavior, and more than 30 percent of researcher-identified
lesbians do not self-identify. This misclassification is not surprising. Selfidentified sexual orientation, sexual desire and sexual behavior are distinct, and
each is the product of a complex social process (Laumann, Gagnon, Michael,
and Michaels 1994; Carpenter 2008).
Consider first the women who engage in same-sex sexual behavior but who
not self-identify as lesbian or bisexual. Figure 1 compares the number and
characteristics of these women. Researcher-identified lesbians who do not also
self-identify have less education, less potential experience (are younger) and
have more children than respondents who self-identify but are not researcheridentified. Despite the small numbers, these differences are large enough to be
statistically significant at the 10 percent level. These differing characteristics
may play a role in explaining why we document different wage penalties for
self-identified and researcher-identified lesbians. Note also that this type of
misclassification is much less prominent for men in the GSS (Martell 2013a).
Now consider differences between the women who self-identify as lesbian
but who are not identified by researchers as lesbian. The age, education, and
child-bearing patterns for this group are not different from the intersection of
the sets when the “last five years” definition is used, but when the “half of partners” definition is used, these women are older, more education and have fewer
children than the group that both self-identifies and is researcher-identified.
There is an additional – and important – difference between women who selfidentify but are not researcher-identified. All researcher-identified lesbians are
sexually active, and sexually active women have higher earnings than sexually
abstinent women (Black, Markar, Sanders, and Taylor 2003). Not all selfidentified lesbians are sexually active. If respondents abstain from sex, they
do not receive this premium. Misclassification therefore introduces an impor-
14
tant bias, and we cannot rule out the possibility that mis-classification plays
a role in explaining the differences between our findings and earlier findings
using the GSS.
The Role of Returns to Characteristics
Though it would be desirable to use a full decomposition to investigate the
role of returns to characteristics, there are too few observations of lesbians to
obtain useful estimates. We instead check the robustness of the lesbian wage
penalty to a series of expanded specifications that include the interaction of
sexual orientation with human capital and the interaction of sexual orientation
with both family characteristics and year of observation.
We begin by considering whether lesbians earn the same returns to their
human capital, as measured by years of education and potential experience, as
heterosexual women. The expectation that lesbians have higher returns to experience than heterosexual women reaches back to Badgett (1995). She argued
that the typical proxy for potential experience (age minus five years) is more
accurate for lesbian women because they are less likely to bear children, and
therefore they are less likely to have interruptions in their careers. Excluding
the lesbian*experience interaction would therefore overestimate the earnings
of lesbians relative to heterosexual women. Jepsen (2007), Davenshary et al.
(2008), Klawitter (2011) and others make similar arguments. Klawitter (2011)
argues that labor market attachment explains much of the lesbian premium
she documents. In Jepsen (2007), the lesbian*experience interaction term is
smaller than previous estimates using earlier data, and including it considerably reduces the lesbian premium. In contrast, in our pooled GSS data,
the penalty remains when sexual orientation and experience are interacted, as
shown in tables 3 and 4. In table 7 we expand the specification to allow for
15
an interaction between lesbian sexual orientation and years of education. We
do not find a statistical difference.
–Table 7 about here –
Note that allowing the returns to education to vary between heterosexual
and lesbian women causes the statistical significance of the lesbian penalty in
2008 to fall below conventional levels for researcher-identified of lesbians, but
causes the estimated penalty to increase and become statistically significant
for both 2008 and 2010 for self-identified lesbians.
As we discuss more below, the small number of observations of lesbians
in many occupational groups limits our ability to pursue such an exercise.
However, the small sample does not detract from our primary point: Our
understanding of the history of employment outcomes for lesbians is quite
sensitive to the way lesbian workers are identified.
Table 8 shows that the divergence in patterns of changes in the wage differential by method of identification remains when we allow the “returns” to
family characteristics to differ both across groups of women (specifications (1)
and (3)) and over time (specifications (2) and (4)). We find no evidence of a
difference in the returns to marriage or children between lesbian and heterosexual women in any year (only base year shown). These results are consistent
with Jepsen (2007), who studies a period before the recent changes in laws regarding marriage equality and increases in the social acceptance of gay families
discussed above.10
– Table 8 about here –
We do, however, find a statistically significant marriage premium of about
10
Of course, marriage is a problematic variable for lesbians because they are still legally
denied access to marriage in many states. We are unable to observe in GSS data whether
lesbians who are cohabiting in marriage-like relationships identify as married. Further,
demographic research has found that a large portion of lesbians do not formally register
what would constitute a legally recognized relationship (Carpenter and Gates 2008).
16
seven percent for all women, while our estimate of the child penalty is not
statistically significant. While evidence on the impact of marriage on women’s
wages is mixed (Loughran and Zissimopoulos 2009), our estimate of the marriage premium for women is somewhat larger than the premium recently estimated by Killewald and Gough (2013).
Our failure to capture a motherhood penalty is not entirely consistent with
recent work that finds it to be approximately five percent (Budig and Hodges
2010). However, we note that the impact of motherhood on wages is heterogeneous: Lower-earning women experience a larger penalty than higher-earning
women, and there is evidence of a motherhood premium among highly educated women (Amuedo-Dorantes and Kimmel 2005). The difference between
our results and most may therefore be an artifact of either the co-incidence
of the sample frame with the recession and recovery, of our inability to use a
fully interacted model, or of including only full-time workers in our regressions.
In particular, including only full-time workers is likely to under-estimate the
motherhood penalty because mothers who expect large wage penalties are less
likely to work full-time (Budig and England 2001).
Changes in the wage differential across regions have the potential to drive
patterns in the lesbian wage premium. Legal recognition of same-sex marriage,
increased legal opportunities for lesbian and gay men to adopt children, and
protection from discrimination (ENDAs) have increased fairly quickly, but not
evenly across the U.S., as shown in Figure 2. In particular, the legal equality
movement has proceeded more quickly in the West, Northeast and northern
Midwest than it has in other regions. In table 9 we allow the lesbian wage
differential to vary with region and across years. The interactions eliminate
the statistical significance of the penalty for both self-identified and researcheridentified lesbians (specifications (1) and (2)) and increase the point estimates
17
of the premium for researcher-identified lesbians in 2012. Again, including the
interactions does not eliminate the divergence in patterns over time between
lesbians identified by the two different methods.
– Table 9 and Figure 2 about here –
Finally, we investigate the impact of occupational choices and the distribution of wages across occupations by allowing the returns to occupations to vary
with sexual orientation and across years. We group respondents into broad
occupational categories.11 As tables 2 and 6 show, there are small numbers of
lesbians in some occupations. Many year-occupation cells are empty. Therefore, these results should be interpreted cautiously. Specification (2) of table
10 shows that the penalty for self-identified lesbians in 2010 is robust to allowing the returns to occupation to vary by sexual orientation. When we allow
the returns to occupation to vary by sexual orientation and year, we find a
penalty in 2008 but a premium for self-identified lesbians 2010 and 2012 (specification 2). This is the only specification in which results for self-identified
lesbians converge to the results for researcher-identified lesbians.
–Table 10 about here –
The biggest difference in occupations between heterosexual and lesbian
women (regardless of method of identification) is the over-representation of
lesbians among managers and supervisors. Of course, this difference may simply be a side effect of the higher returns to experience. Then again, it could be
an artifact of an unobserved difference in personality characteristics or workplace behaviors.
11
Occupations include: Managers & Supervisors, Professional, Teaching/Social Work,
Allied Health, Support, Sales, Personal Service, Agricultural, Construction & Technology,
and Laborer. These categories are based on the 2010 Standard Occupational Classification
codes of the U.S. Census.
18
The Role of Employment Status
While a full accounting of the causes of differing patterns over time in the
experiences of self-identified and researcher-identified lesbians is beyond the
scope of the current paper, we show in table 11 that the difference in patterns in
wages is related to differences in employment status across years. We estimate
by multinomial logit:
ŷi = β1 Li + β2 Yit + β3 (Li ∗ Yit ) + βXi + i
(2)
where yi equals 0 if respondents are not working, 1 if working part-time
and 2 if working full-time. All variables are defined as in previous sections,
and we add a proxy for non-labor income in Xi .12 Table 11 presents marginal
effects calculated at the mean for each outcome of the dependent variable.
Researcher-identified lesbians experienced the same relatively good employment outcomes as heterosexual women during the recession (see, for example,
Hartmann 2010). There were no significant differences between researcheridentified lesbians and heterosexuals in the propensity to work full or part-time
in any year. In contrast, self-identified lesbians were approximately 27 percent
less likely to work full-time and 16 percent more likely to work part-time in
2008 than heterosexual women.
–Table 11 about here–
The differences in the work status regressions are consistent with the timing
of the differences in wage differentials because the wage/income measure in the
GSS is retrospective – it refers to income for past year – while work status
question refers to the past week. If self-identified lesbians worked less in 2008
and 2009, their lower incomes and hourly wages are captured in the 2010
12
Non-labor income is proxied as total income minus respondent’s income, which is the
same proxy utilized in (Martell 2014).
19
survey. These underemployed workers may have been more likely to change
jobs in 2008 and 2009, and were also likely to have been among those most
burdened by the recession (Biddle and Hammermesh 2013; Elsby, Shin, and
Solon 2013).
The signs and significance of the marginal effects of control variables (presence of children, education and marriage) are consistent with the existing literature. This pattern is robust to including interactions for marriage and
children, but interacting lesbian and education removes the significance of the
marginal effect of the recession on work status for all classification techniques
(not shown).13
There are not enough observations of lesbians in the GSS to to solve the
puzzle of the emerging lesbian wage puzzle completely. We have shown that
the lesbian wage penalty is robust to a variety of empirical specifications and
likely related to varying employment patterns between heterosexual and lesbian women. However, the GSS does not have enough observations to fully
investigate the occupational attainment of lesbians or the source of the disproportionate impact of the recession on lesbians. It is clear, however, that
the size and persistence of the lesbian wage differential depends upon whether
a lesbian claims the label herself or whether it is assigned to her by the researcher.
Conclusion
This paper makes two contributions to the literature on the earnings differentials between lesbians and heterosexual women. First, while the bulk of
13
When we include the lesbian*occupation interaction self-idenified and researcheridentified lesbians are both more likely to be unemployed and less likely to work full time
in 2008. The convergence of estimates only occurs with the occupation interactions, which
mirrors the results for wage differentials.
20
the existing literature finds a lesbian premium, we find evidence of a lesbian
wage penalty of roughly 50 percent for self-identified lesbians in 2010, and
an even larger penalty for researcher-identified lesbians in 2008. We know
little about the experience of gays and lesbians in economic downturns, but
finding of a lesbian penalty in any recent year using any method of identification is surprising given changes in public opinion and the expansion of
non-discrimination laws. The GSS data suggest that self-identified lesbians
were hit harder by the recession than other groups, but the results are not
conclusive. As more data become available, future research should investigate
the mechanism through which the disadvantage manifested during the recession. In particular, it should investigate selection into occupations and into
parenthood for lesbians.
More fundamentally, we show that the method of identifying lesbians is
important for the measurement of wage differentials. The shortcomings of
behavioral definitions of lesbians and of the use cohabitation based data are
well known. The existing literature acknowledges that cohabitation based
data excludes single lesbians and that selection into marriage like relationships
varies by sexual orientation (Carpenter and Gates 2008). However, to our
knowledge, we are the first to demonstrate that mis-classification matters to
our understanding of the history of labor market outcomes for homosexuals.
21
22
GSS 1989-1991
GSS & 1992 NHSLS*
GSS 1989-1996
GSS 1989-1996
GSS 1991-1996
GSS 1994-2002
GSS 1988-2006
1990 U.S. Census
1990 U.S. Census
2000 U.S. Census (state of MA only)
2000 U.S. Census
2000 U.S. Census
2000 Census
2000 Census
2000 Census
2000 Census
2000 Census
2004 CPS
BRFSS 1996-2000**
CHIS 2001*** and GSS
Badget (1995)
Badgett (2001)
Blandford (2003)
Black et al. (2003)
Berg and Lien (2002)
Comolli (2005)
Cushing-Daniels and Yeung (2009)
Klawitter and Flatt (1998)
Clain and Leppel (2001)
Albelda et al. (2005)
Gates (2009)
Antecol et al. (2007)
Daneshevary, Waddoups, and Wimmer (2008)
Daneshevary, Waddoups and Wimmer (2009)
Klawitter (2011)
Baumle and Poston (2011)
Jepsen (2007)
Elmslie and Tebaldi (2007)
Carpenter (2004)
Carpenter (2005)
Sexual Behavior
Sexual Behavior
Sexual Behavior
Sexual Behavior
Sexual Behavior
Sexual Behavior
Sexual Behavior
Cohabitation Status
Cohabitation Status
Cohabitation Status
Cohabitation Status
Cohabitation Status
Cohabitation Status
Cohabitation Status
Cohabitation Status
Cohabitation Status
Cohabitation Status
Cohabitation Status
Self-reported
Self-reported and Sexual Behavior
Method of ID
Insignificant premium
Insignificant premium
Premium
Premium
Premium
Premium
Insignificant penalty
Premium, but household penalty
Premium
Premium
Premium
Premium
Premium, gap higher with less education
Wages of never-married lesbians highest
Premium
Premium
Premium
Insignificant premium
Household income penalty
Insignificant penalty
Findings for Lesbians
Notes: * National Health and Nutrition Survey, **Behavioral Risk Factor Surveillance Survey, ***California Health Interview Survey.
Data
Study
Table 1: Studies of lesbian wage and income differentials in the U.S. by data source.
Table 2: Descriptive statistics for self-identified lesbians.
Self-Identified
Lesbian
Mean St. Dev.
2.58
1.11
10.26
1.03
Log(Wages)
Log(Earnings)
Heterosexual
Mean St. Dev.
2.62
0.81
10.27
0.82
Years of Educ.
Potential Exp.
Married
Num. Children
White
Metro
14.97
20.16
0.18
0.82
0.84
0.21
2.69
10.42
0.39
0.93
0.37
0.41
14.26
24.02
0.45
1.64
0.75
0.15
2.89
12.87
0.50
1.43
0.43
0.36
Occupation
Man & Sup
Professional
Teach/Soc Wok
Allied Health
Support
Sales
Pers Svc
Ag
Constr & Tech
Laborer
Total
N
13
5
2
6
5
1
4
0
1
1
38
Percent
0.34
0.13
0.05
0.16
0.13
0.03
0.11
0.00
0.03
0.03
1.00
N
221
107
120
117
204
78
123
5
9
76
1,060
Percent
0.21
0.10
0.11
0.11
0.19
0.07
0.12
0.00
0.01
0.07
1.00
Region
New England
Mid Atlantic
E. No. Central
W. No. Central
So. Atlantic
E. So. Central
W. So. Central
Mountain
Pacific
Total
N
2
5
5
2
10
1
4
7
2
38
Percent
0.05
0.13
0.13
0.05
0.26
0.03
0.11
0.18
0.05
1.00
N
49
147
165
81
235
68
104
80
131
1,060
Percent
0.05
0.14
0.16
0.08
0.22
0.06
0.10
0.08
0.12
1.00
Note: Full-time workers only.
23
24
(2)
SID
Log(W )
−0.349
(0.350)
−0.505∗
(0.300)
−0.040
(0.284)
0.048∗∗∗
(0.007)
0.023∗∗
(0.011)
−0.026
(0.050)
−0.013
(0.049)
Y es
Y es
1093
0.399
(3)
SID
Log(W )
−0.607∗
(0.333)
0.027
(0.309)
0.392
(0.331)
0.038∗∗∗
(0.006)
0.018∗
(0.010)
−0.021
(0.048)
0.024
(0.048)
Y es
Y es
1438
0.317
(4)
SID
Log(E)
−0.325
(0.297)
−0.343
(0.257)
0.059
(0.222)
0.058∗∗∗
(0.007)
0.021∗∗
(0.009)
−0.041
(0.051)
−0.044
(0.050)
Y es
No
1098
0.370
(5)
SID
Log(E)
−0.339
(0.305)
−0.344
(0.263)
0.110
(0.242)
0.054∗∗∗
(0.007)
0.018∗
(0.009)
−0.001
(0.048)
0.011
(0.047)
Y es
Y es
1098
0.442
(6)
SID
Log(E)
−0.543∗∗
(0.265)
0.006
(0.256)
0.327
(0.262)
0.062∗∗∗
(0.005)
0.017∗∗
(0.008)
−0.035
(0.049)
−0.036
(0.048)
Y es
Y es
1754
0.360
Note: Specification follows Badgett (1995). Full-time workers only in Columns 1, 2, 4, and 5. Full-time and part-time workers in
columns 3 and 6. All specifications include a squared term in experience and controls for years of education, race, marital status and
residence in a large metro area. Robust standard errors in parantheses. * Significant at 10 % ** Significant at 5 % *** Significant at
1 %.
Regions
Occupations
Observations
R2
Year = 2012
Year = 2010
Lesbian*Exp
Experience
Lesbian*2012
Lesbian*2010
Lesbian
(1)
SID
Log(W )
−0.296
(0.332)
−0.529∗
(0.287)
−0.062
(0.260)
0.051∗∗∗
(0.008)
0.024∗∗
(0.011)
−0.060
(0.052)
−0.065
(0.050)
Y es
No
1093
0.344
Table 3: Penalty for self-identified lesbians in pooled GSS sample.
25
(2)
RID 5Y
Log(W )
−0.804∗∗∗
(0.288)
0.514∗
(0.292)
0.913∗∗∗
(0.268)
0.038∗∗∗
(0.006)
0.013
(0.009)
−0.045
(0.048)
0.002
(0.048)
Y es
Y es
1438
0.321
(3)
RID 5Y
Log(E)
−0.715∗∗
(0.292)
0.293
(0.266)
0.610∗∗∗
(0.237)
0.053∗∗∗
(0.007)
0.017∗∗
(0.008)
−0.029
(0.047)
−0.009
(0.047)
Y es
Y es
1098
0.443
(4)
RID Half
Log(W )
−0.760∗∗
(0.313)
0.038
(0.347)
0.389∗
(0.224)
0.047∗∗∗
(0.007)
0.023
(0.014)
−0.048
(0.050)
−0.018
(0.049)
Y es
Y es
1093
0.395
(5)
RID Half
Log(W )
−0.772∗∗
(0.322)
0.332
(0.363)
0.716∗
(0.380)
0.039∗∗∗
(0.006)
0.017
(0.012)
−0.028
(0.049)
0.028
(0.048)
Y es
Y es
1438
0.316
(6)
RID Half
Log(E)
−0.469
(0.323)
−0.084
(0.384)
0.136
(0.270)
0.054∗∗∗
(0.007)
0.017
(0.015)
−0.014
(0.047)
0.013
(0.047)
Y es
Y es
1098
0.439
Note: Specification follows Badgett (1995). Full-time workers only in columns 1, 3, 4 and 6. Full-time and part-time workers in
columns 2 and 4. All specifications include a squared term in experience and controls for years of education, race, marital status and
residence in a large metro area. Robust standard errors in parantheses. * Significant at 10 % ** Significant at 5 % *** Significant at
1 %.
Regions
Occupations
Observations
R2
Year = 2012
Year = 2010
Lesbian*Exp
Experience
Lesbian*2012
Lesbian*2010
Lesbian
(1)
RID 5Y
Log(W )
−0.720∗∗
(0.334)
0.147
(0.300)
0.606∗∗
(0.268)
0.046∗∗∗
(0.007)
0.019∗∗
(0.009)
−0.054
(0.049)
−0.037
(0.049)
Y es
Y es
1093
0.399
Table 4: Penalty for researcher-identified lesbians in pooled GSS sample.
Table 5: Penalty for intersection and union of self-identified and researcheridentified groups.
Lesbian
Lesbian*2010
Lesbian*2012
Experience
Lesbian*Exp
Year = 2010
Year = 2012
Regions
Occupations
Observations
R2
(1)
Both
Log(W )
−0.543
(0.385)
−0.301
(0.312)
0.229
(0.314)
0.047∗∗∗
(0.007)
0.024∗∗
(0.011)
−0.034
(0.050)
−0.018
(0.049)
Y es
Y es
1093
0.398
(2)
Both
Log(W )
−0.761∗∗
(0.353)
0.216
(0.343)
0.819∗∗
(0.340)
0.038∗∗∗
(0.006)
0.018
(0.011)
−0.027
(0.048)
0.017
(0.048)
Y es
Y es
1438
0.318
(3)
Either
Log(W )
−0.570∗
(0.321)
−0.048
(0.293)
0.384
(0.258)
0.047∗∗∗
(0.007)
0.019∗∗
(0.009)
−0.046
(0.049)
−0.032
(0.049)
Y es
Y es
1093
0.398
(4)
Either
Log(W )
−0.677∗∗
(0.280)
0.330
(0.271)
0.599∗∗∗
(0.267)
0.038∗∗∗
(0.006)
0.014
(0.008)
−0.039
(0.048)
0.010
(0.049)
Y es
Y es
1438
0.318
Note: Specification follows Badgett (1995). First specification in each pair includes full-time workers only; second specification includes full-time and parttime workers. All specifications include a squared term in experience and controls
for years of education, race, marital status and residence in a large metro area.
Robust standard errors in parantheses. * Significant at 10 % ** Significant at 5
% *** Significant at 1 %.
26
27
N
15
4
4
8
4
3
6
0
1
2
47
N
Occupation
Man & Sup
Professional
Teach/Soc Wok
Allied Health
Support
Sales
Pers Svc
Ag
Constr & Tech
Laborer
Total
Region
New England
Mid Atlantic
E. No. Central
W. No. Central
So. Atlantic
E. So. Central
W. So. Central
Mountain
Pacific
Total
1
5
5
1
14
2
6
6
7
47
14.28
19.26
0.21
0.98
0.87
0.15
Years of Educ.
Potential Exp.
Married
Num. Children
White
Metro
Log(Wages)
Log(Earnings)
Percent
0.02
0.11
0.11
0.02
0.30
0.04
0.13
0.13
0.15
1.00
Percent
0.32
0.09
0.09
0.17
0.09
0.06
0.13
0.00
0.02
0.04
1.00
2.47
11.15
0.41
1.11
0.34
0.36
Lesbian
Mean St. Dev.
2.46
1.03
10.13
1.00
Percent
0.05
0.14
0.16
0.08
0.22
0.06
0.10
0.08
0.12
1.00
Percent
0.21
0.10
0.11
0.11
0.20
0.07
0.12
0.00
0.01
0.07
1.00
2.90
12.84
0.50
1.43
0.44
0.36
0
3
4
0
6
1
1
2
3
20
N
6
2
3
1
2
2
1
0
0
3
20
N
14.90
20.25
0.10
0.90
0.80
0.20
Percent
0.00
0.15
0.20
0.00
0.30
0.05
0.05
0.10
0.15
1.00
Percent
0.30
0.10
0.15
0.05
0.10
0.10
0.05
0.00
0.00
0.15
1.00
2.92
11.35
0.31
0.97
0.41
0.41
N
51
149
166
83
239
68
107
85
130
1,078
N
228
110
119
122
207
77
126
5
10
74
1,078
14.27
23.95
0.45
1.63
0.75
0.15
Percent
0.05
0.14
0.15
0.08
0.22
0.06
0.10
0.08
0.12
1.00
Percent
0.21
0.10
0.11
0.11
0.19
0.07
0.12
0.00
0.01
0.07
1.00
2.88
12.83
0.50
1.43
0.43
0.36
Heterosexual
Mean St. Dev.
2.63
0.81
10.28
0.82
Researcher-Identified (5Y)
Lesbian
Mean St. Dev.
2.48
1.18
10.19
1.17
Note: Full-time workers only.
N
50
147
165
82
231
67
102
81
126
1,051
N
219
108
118
115
205
76
121
5
9
75
1,051
14.28
24.09
0.45
1.64
0.75
0.15
Heterosexual
Mean St. Dev.
2.63
0.81
10.28
0.82
Researcher-Identified (5Y)
Table 6: Descriptive statistics for researcher-identified lesbians.
Table 7: Changes in the lesbian wage differential from 2008-2012, allowing
returns to experience and education to interact with sexual orientation.
(1)
SID
Lesbian
Lesbian*2010
Lesbian*2012
Experience
Lesbian*Exp
Years Education
Lesbian*Educ
Regions
Occupations
Observations
R2
−1.040∗
(0.621)
−0.539∗
(0.294)
−0.054
(0.272)
0.048∗∗∗
(0.007)
0.019∗
(0.011)
0.109∗∗∗
(0.010)
0.052
(0.040)
Y es
Y es
1093
0.400
(2)
RID 5Y
−0.707
(0.615)
0.148
(0.314)
0.605∗∗
(0.267)
0.046∗∗∗
(0.007)
0.020∗∗
(0.010)
0.110∗∗∗
(0.010)
−0.001
(0.047)
Y es
Y es
1093
0.399
Note: Full-time workers only. All specifications include a squared term in experience and controls for years of education, race, and residence in a large metro
area. Robust standard errors in parantheses. * Significant at 10 % ** Significant
at 5 % *** Significant at 1 %.
28
Table 8: Changes in the lesbian wage differential from 2008-2012, allowing
returns to family characteristics to interact with sexual orientation.
Lesbian
Lesbian*2010
Lesbian*2012
Children
Lesbian*Children
Married
Lesbian*Married
Regions
Occupations
Observations
R2
(1)
SID
(2)
SID
−0.330
(0.366)
−0.477∗
(0.283)
−0.151
(0.306)
−0.017
(0.016)
−0.184
(0.152)
0.073∗
(0.041)
0.364
(0.406)
Y es
Y es
1093
0.401
−0.223
(0.472)
−0.526
(0.624)
−0.511
(0.555)
−0.017
(0.016)
−0.361
(0.372)
0.073∗
(0.041)
0.635
(0.510)
Y es
Y es
1093
0.404
(3)
RID 5Y
(4)
RID 5Y
−0.790∗∗
(0.369)
0.170
(0.316)
0.609∗∗
(0.266)
−0.020
(0.016)
0.048
(0.101)
0.073∗
(0.042)
0.244
(0.319)
Y es
Y es
1093
0.400
−0.983∗∗
(0.469)
0.363
(0.501)
0.717
(0.444)
−0.020
(0.016)
0.158
(0.209)
0.072∗
(0.042)
0.311
(0.689)
Y es
Y es
1093
0.402
Note: Full-time workers only. All specifications include a squared term in experience and controls for years of education, race, and residence in a large metro
area. Robust standard errors in parantheses. * Significant at 10 % ** Significant
at 5 % *** Significant at 1 %.
29
Table 9: Changes in the lesbian wage differential from 2008-2012, allowing
returns to region to interact with sexual orientation.
Lesbian
Lesbian*2010
Lesbian*2012
Regions
Lesbian* Region
Lesbian*Reg*Year
Occupations
Observations
R2
(1)
SID
(2)
SID
−0.187
(0.280)
−0.083
(0.263)
0.092
(0.296)
Y es
Y es
No
Y es
1093
0.404
−0.041
(0.191)
−1.009
(0.729)
−0.393
(0.281)
Y es
Y es
Y es
Y es
1093
0.407
(3)
RID 5Y
(4)
RID 5Y
0.010
(0.167)
0.348
(0.289)
0.555∗∗∗
(0.258)
Y es
Y es
No
Y es
1093
0.405
−0.019
(0.173)
0.945∗∗∗
(0.273)
1.590∗∗∗
(0.500)
Y es
Y es
Y es
Y es
1093
0.408
Note: Full-time workers only. All specifications include a squared term in experience and controls for years of education, race, and residence in a large metro
area. Robust standard errors in parantheses. * Significant at 10 % ** Significant
at 5 % *** Significant at 1 %.
30
Table 10: Changes in the lesbian wage differential from 2008-2012, allowing
returns to occupation to interact with sexual orientation.
(1)
SID
Lesbian
Lesbian*2010
Lesbian*2012
Regions
Occupations
Occ*Lesbian
Occ*Lesbian*Year
Observations
R2
−0.267
(0.364)
−0.486∗
(0.317)
−0.028
(0.288)
Y es
Y es
Y es
No
1093
0.404
(2)
SID
−0.795∗∗∗
(0.279)
0.290∗
(0.180)
0.567∗∗∗
(0.159)
Y es
Y es
Y es
Y es
1093
0.409
(3)
RID 5Y
(4)
RID 5Y
−0.716∗∗∗
(0.282)
0.043
(0.258)
0.527∗∗
(0.287)
Y es
Y es
Y es
Y es
1093
0.404
−0.502∗∗∗
(0.211)
0.283∗∗
(0.146)
0.441∗∗∗
(0.125)
Y es
Y es
Y es
No
1093
0.415
Note: Full-time workers only. All specifications include a squared term in experience and controls for years of education, race, and residence in a large metro
area. Robust standard errors in parantheses. * Significant at 10 % ** Significant
at 5 % *** Significant at 1 %.
31
32
0.112
(0.108)
0.019
(0.112)
0.703
(27.771)
−0.004
(0.004)
−0.010∗∗∗
(0.002)
−0.029
(0.024)
−0.022
(0.025)
1742
0.158∗
(0.094)
−0.096
(0.096)
−1.960
(91.930)
−0.002
(0.004)
−0.013∗∗∗
(0.002)
0.015
(0.022)
0.005
(0.022)
1742
(2)
SID
Part-Time
−0.269∗∗
(0.133)
0.077
(0.132)
1.257
(64.159)
0.006
(0.005)
0.023∗∗∗
(0.003)
0.014
(0.027)
0.017
(0.028)
1742
(3)
SID
Full-Time
0.116
(0.102)
0.010
(0.119)
0.736
(26.443)
−0.010∗
(0.006)
−0.009∗∗∗
(0.002)
−0.027
(0.024)
−0.024
(0.025)
1742
(4)
RID 5Y
Unemployed
0.002
(0.089)
0.044
(0.094)
−1.885
(88.123)
0.003
(0.004)
−0.013∗∗∗
(0.002)
0.008
(0.022)
0.002
(0.022)
1742
(5)
RID 5Y
Part-Time
−0.118
(0.121)
−0.054
(0.131)
1.149
(61.680)
0.007
(0.005)
0.023∗∗∗
(0.003)
0.019
(0.027)
0.021
(0.028)
1742
(6)
RID 5Y
Full-Time
Note: Table shows estimated marginal effects from a multinomial regression. All specifications include a squared term in
experience and controls for years of education, race, residence in a large metro area and non-labor income. Standard errors
in parantheses. * Significant at 10 % ** Significant at 5 % *** Significant at 1 %.
Observations
Year = 2012
Year = 2010
Experience
Lesbian*Exp
Lesbian*2012
Lesbian*2010
Lesbian
(1)
SID
Unemployed
Table 11: Work status of self-Identified and researche-identified lesbians.
When RID defined as homosexual behavior in last 5 years
n=16, 2.4 years younger,
0.4 more children, less
likely married, 3 years
less ed
n=31
n=7
SID not RID
RID not SID
Both RID & SID
When RID defined as half of adult partners of same sex
n=25, 0.9 years older, 0.6
fewer children, 0.9 years
more ed
n=13
n=7
RID not SID
Both RID & SID
SID not RID
Figure 1: Comparing groups of self-identified and researcher-identified lesbians. Differences noted are statistically significant at the 10 percent level.
33
Figure 2: Summary of state laws on non-discrimination in employment, housing, and insurance, as well as marriage legality/recognition and adoption.
Source: Movement Advancement Project (2014).
34
References
Ahmed, A. M., L. Andersson, and M. Hammarstedt (2011). Inter- and
intra-household earnings differentials among homosexual and heterosexual couples. British Journal of Industrial Relations 49 (2), 248–278.
Ahmed, A. M., L. Andersson, and M. Hammarstedt (2013). Sexual orientation and full-time monthly earnings, by public and private sector:
Evidence from Swedish register data. Review of Economics of the Household 11 (1), 83–108.
Ahmed, A. M. and M. Hammarstedt (2010). Sexual orientation and earnings: a register data-based approach to identify homosexuals. Journal of
Population Economics 23 (3), 835–849.
Albelda, R., M. Ash, and M. Badgett (2005). Now that we do: Same-sex couples and marriage in Massachusetts. Massachusetts Benchmarks 7 (2),
16–24.
Amuedo-Dorantes, C. and J. Kimmel (2005). The motherhood wage gap
for women in the United States: The importance of college and fertility
delay. Review of Economics of the Household 3 (1), 17–48.
Antecol, H., A. Jong, and M. Steinberger (2008). The sexual orientation
wage gap: The role of occupational sorting, human capital and discrimination. Industrial and Labor Relations Review 61 (4), 518–543.
Arabsheibani, G., A. Marin, and J. Wadsworth (2004). In the pink:
Homosexual-heterosexual wage differentials in the U.K. International
Journal of Manpower 25 (3), 343–354.
Badgett, M. (1995). The wage effects of sexual orientation discrimination.
Industrial and Labor Relations Review 54 (3), 726–739.
Badgett, M. (2001). Money, Myths and Change: The Economic Lives of
Lesbians and Gay Men. Chicago: University of Chicago Press.
Baumle, A. K. and D. L. Poston (2011). The economic cost of homosexuality:
Multilevel analyses. Social Forces 89 (3), 1005–1031.
Becker, G. (1957). The Economics of Discrimination. Chicago: University
of Chicago Press.
Berg, N. and D. Lien (2002). Measuring the effect of sexual orientation on
income: Evidence of discrimination? Contemporary Economic Policy 4,
394–414.
Berg, N. and D. Lien (2006). Same-sex sexual behavior: U.S. frequency
estimates from survey data with simultaneous misreporting and nonresponse. Applied Economics 38 (7), 757–769.
Biddle, J. E. and D. S. Hammermesh (2013). Wage discrimination over the
business cycle. IZA Journal of Labor Policy 2 (7).
35
Black, D., H. Markar, S. Sanders, and L. Taylor (2003). The earnings effeccts
of sexual orientation. Industrial and Labor Relations Review 56 (3), 53–
70.
Black, D., S. Sanders, and L. Taylor (2007). The economics of lesbian and
gay families. Journal of Economic Perspectives 21 (2), 53–70.
Blandford, J. (2003). The nexus of sexual orientation and gender in the
determination of earnings. Industrial and Labor Relations Review 56 (4),
622–642.
Budig, M. J. and P. England (2001). The wage penalty for motherhood.
American Sociological Review 66 (2), 204–225.
Budig, M. J. and M. J. Hodges (2010). Differences in disadvantage: Variation in the motherhood penalty across white women’s earnings distribution. American Sociological Review 75 (5), 1–24.
Carpenter, C. S. (2004). New evidence on gay and lesbian household incomes. Contemporary Economic Policy 22 (1), 78–94.
Carpenter, C. S. (2005). Self-reported sexual orientation and earnings: Evidence from California. Industrial and Labor Relations Review 58 (2),
258–273.
Carpenter, C. S. (2008). Sexual orientation, work, and income in Canada.
Canadian Journal of Economics 41 (4), 1239–1261.
Carpenter, C. S. and G. Gates (2008). Gay and lesbian partnership: Evidence from California. Demography 45 (3), 573–590.
Clain, S. H. and K. Leppel (2001). An investigation into sexual orientation discrimination as an explanation for wage differences. Applied Economics 33, 37–47.
Clarke, G. and P. Sevak (2013). The disappearing gay income penalty. Economics Letters 121, 542–545.
Comolli, R. (2005). The Economics of Sexual Orientation and Racial Perception. Ph. D. thesis, Yale University.
Cushing-Daniels, B. and T.-Y. Yeung (2009). Wage penalties and sexual
orientation: An update using the General Social Survey. Contemporary
Economic Policy 27 (2), 164–175.
Daneshvary, N., C. Waddoups, and B. S. Wimmer (2008). Educational attainment and the lesbian wage premium. Journal of Labor Research 29,
365–379.
Daneshvary, N., C. Waddoups, and B. S. Wimmer (2009). Previous marriage
and the lesbian wage premium. Industrial Relations 48 (3), 432–453.
Drydakis, N. (2014). Sexual orientation discrimination in the Cypriot
labour market. distastes or uncertainty? International Journal of Manpower 35 (5), 720–744.
36
Elsby, M. W., D. Shin, and G. Solon (2013). Wage adjustment in the great
recession. NBER Working Paper (19478).
Gates, G. J. (2009). The impact of sexual orientation anti-discrimination
policies on the wages of lesbians and gay men. California Center for
Population Research Working Papers Series.
Haider-Markel, D. P. and K. J. Meier (1996). The politics of gay and lesbian rights: Expanding the scope of the conflict. The Journal of Politics 58 (2), 332–349.
Hartmann, H. I., A. English, and J. Hayes (2010). Women and men’s
employment and unemployment in the Great Recession. Institute for
Women’s Policy Research.
Jepsen, L. K. (2007). Comparing the earnings of cohabiting lesbians, cohabiting heterosexual women, and married women: Evidence from the 2000
Census. Industrial Relations 46 (4), 699–727.
Killewald, A. and M. Gough (2013). Does specialization explain marriage
penalties and premiums? American Sociological Review 78 (3), 477–502.
Klawitter, M. (2011). Multilevel analysis of the effects of antidiscrimination
policies on earnings by sexual orientation. Journal of Policy Analysis
and Management 30 (2), 334–358.
Klawitter, M. and V. Flatt (1998). The effects of state and local antidiscrimination policies on earnings for gays and lesbians. Journal of Policy Analysis and Management 4, 658–686.
Laumann, E. O., J. H. Gagnon, R. T. Michael, and S. Michaels (1994). The
Social Organization of Sexuality: Sexual Practices in the United States.
The University of Chicago Press.
Loughran, D. S. and J. M. Zissimopoulos (2009). Why wait? The effect of
marriage and childbearing on the wages of men and women. Journal of
Human Resources 44 (2), 326–349.
Martell, M. E. (2013a). Differences do not matter: exploring the wage gap
for same-sex behaving men. Eastern Economic Journal 39 (1), 45–71.
Martell, M. E. (2013b). Do ENDAs end discrimination for behaviorally gay
men? Journal of Labor Research 34 (2), 147–169.
Martell, M. E. (2014). How ENDAs extend the workweek: Legal protection
and the labor supply of behaviorally gay men. Contemporary Economic
Policy 32 (3), 560–577.
Movement Advancement Project (2014). Snapshot: LGBT legal equality by
state. Date Accessed: November 10, 2014.
Peplau, L. A. (2003). Human sexuality: How do men and women differ?
Current Directions in Psychological Science 12 (2), 37–40.
37
Plug, E. and P. Berkhout (2008). Sexual orientation, disclosure and earnings.
IZA Discussion Paper (3290).
Smith, T. (2011). Public attitudes toward homosexuality. National Opinion
Reserach Council Technical Report.
Tebaldi, E. and B. Elmslie (2007). Sexual orientation and labor market
discrimination. Journal of Labor Research 28 (3), 436–453.
38