Report | Jobs and Unemployment

The public-sector jobs crisis: Women and African Americans hit hardest by job losses in state and local governments

Briefing Paper #339

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Press release

The Great Recession created tremendous hardship for millions of Americans. One aspect of this recession and its aftermath has been particularly damaging for women and African Americans: the decision by many state and local governments to respond to diminished revenues and budget shortfalls by cutting public-sector jobs. Because women and African Americans have historically been overrepresented in public-sector employment, they have been disproportionately affected by state and local government budget cuts. Since the official end of the recession in June 2009, the private sector has slowly recovered some of the jobs it lost during the downturn, while the public sector has continued shedding jobs at a rapid rate. Indeed, in 2011 state and local governments experienced their worst job decline on record. Without a change of course in state and local governments’ budget decisions, women and African Americans stand to suffer disproportionately from continued cuts in the public sector.

This briefing paper begins by providing background on the public sector’s commitment to equal opportunity and affirmative action in employment, and then explores the degree to which women and African Americans are overrepresented in state and local government jobs. It next turns to a discussion of how state and local public-sector workers have significantly higher levels of education than their private-sector peers, yet are consistently underpaid relative to similar private-sector workers. Then, it compares racial- and gender-based wage disparities in the state and local public sectors and the private sector. The briefing paper next explains the disproportionate impact of state and local public-sector job cuts on women and African Americans, and concludes by contrasting the private sector’s slow jobs recovery with continued employment declines in the public sector.

Key findings include:

  • Historically, the state and local public sectors have provided more equitable opportunities for women and people of color. As a result, women and African Americans constitute a disproportionately large share of the state and local public-sector workforce.
  • Overall, the wage gap across genders is similar in the state and local public sectors and in the private sector. However, it is smaller for highly educated women employed in state and local government.
  • State and local public-sector workers of color face smaller wage disparities across racial lines, and at some levels of education actually enjoy a wage premium over similarly educated white workers.
  • The disproportionate share of women and African Americans working in state and local government has translated into higher rates of job loss for both groups in these sectors. Between 2007 (before the recession) and 2011, state and local governments shed about 765,000 jobs. Women and African Americans comprised about 70 percent and 20 percent, respectively, of those losses. Conversely, Hispanic employment in state and local public-sector jobs increased during this period (although most of that increase likely occurred in the lowest-paid jobs).
  • Job losses in the state and local public sectors stand in contrast to the jobs recovery in the private sector. From February 2010 (the month the labor market “bottomed out”) to January 2012, the United States experienced a net increase in total nonfarm employment of more than 3.2 million jobs, while state and local government employment fell by 438,000. Over this period, every major sector of the economy experienced net growth in jobs except the public sector.

The public sector’s commitment to equal opportunity and affirmative action

In the 1960s and 1970s, the federal government, through a combination of executive orders and legislation, prohibited discrimination on the basis of sex and race in employment and the payment of wages.1 Studies of the hiring practices and wages of the state and local public sectors have shown the effectiveness of anti-discrimination policies, especially in contrast to the private sector. Since the creation of equal opportunity and affirmative action programs, women and African Americans have seen greater employment opportunities in the economy as a whole, but particularly in the public sector (Crosby 2004). Though discrimination in the public sector likely still exists,2 government remains a model of how to achieve greater equality in employment and workplace diversity.

While some would argue that the United States’ labor market today is largely free of prejudice and discrimination, a substantial and growing body of research suggests that gender- and race-based prejudices continue to afflict the U.S. workforce.3 These prejudices often take the form of wage disparities. Today, women earn only 77 cents for every dollar paid to their male counterparts, and the situation is worse for African American and Hispanic women, who earn only 62 cents and 54 cents, respectively, for every dollar paid to their non-Hispanic white male counterparts (National Women’s Law Center 2012).4 Furthermore, the Equal Employment Opportunity Commission continues to win settlements against employers in race discrimination cases based on compensation disparities.5

Research buttresses this evidence of wage discrimination with findings of significant race- and gender-based discrimination in hiring. For example, Harvard University researchers found that résumés with “white-sounding” names such as “Emily” are 50 percent more likely to elicit interviews than equivalent résumés with “black-sounding” names such as “Lakisha” (Bertrand and Mullainathan 2004). In addition, a multi-year, national study on race and sex discrimination in large and midsized private businesses found that intentional discrimination exists in every region of the country and in each of nine occupational categories, and it “is so pervasive that affirmative action programs continue to be necessary” (Blumrosen and Blumrosen 2002). Even as recently as this year, the U.S. Department of Labor Office of Federal Contract Compliance Programs found that FedEx engaged in discrimination against 21,000 applicants in 15 states (U.S. Department of Labor 2012). In short, although the American ideal may be to judge individuals by the content of their character, we have not yet guaranteed equal opportunity in all cases.

Today, every job in state and local government is subject to federal regulations concerning equal opportunity (Dale 2005), and many state and local governments require affirmative action plans beyond federal equal opportunity requirements. When compared with the private sector, the state and local public sectors have gone to greater lengths to enact affirmative action policies. However, many of the affirmative action programs implemented by state and local governments have met opposition from state legislatures and governors proposing to ban such laws.6

In the private sector, affirmative action laws and regulations are comparatively few. Federal law requires only two types of private-sector employers to implement affirmative action plans: those that have federal contracts or subcontracts in excess of $50,000 and that also have at least 50 employees, and those with 15 or more employees that have faced a judicial finding of discrimination.

Tallying the number of public- and private-sector jobs subject to monitoring requirements and set-aside programs, about one in four American workers hold jobs covered by mandatory federal affirmative action programs (U.S. Department of Labor 2002).

Despite the persistence of discrimination in state and local government, affirmative action and equal opportunity policies have transformed the public sector, relative to the private sector, into increasingly hospitable employers of women and African Americans. Fifty years of efforts to redress past discrimination have proven their effectiveness in greater numbers of women and African Americans entering state and local government. As a result, public-sector jobs at the state and local levels remain critical to their livelihoods.

The importance of the state and local public sectors to women and African Americans

Figure A

Female share of employment, by sector, 1989–2011

Total employment State & Local Public sector Difference with total employment Private sector Private sector difference
1989 47.1% 56.2% 9.2% 45.7% 36.6%
1990 47.0% 56.5% 9.4% 45.7% 36.2%
1991 47.3% 56.8% 9.5% 46.0% 36.5%
1992 47.6% 57.1% 9.4% 46.3% 36.8%
1993 47.7% 57.3% 9.6% 46.3% 36.7%
1994 47.6% 57.1% 9.5% 46.2% 36.7%
1995 47.6% 57.3% 9.7% 46.1% 36.4%
1996 47.8% 57.8% 10.1% 46.3% 36.2%
1997 47.8% 58.1% 10.3% 46.3% 35.9%
1998 47.8% 58.0% 10.2% 46.3% 36.1%
1999 48.0% 58.6% 10.7% 46.4% 35.8%
2000 47.9% 59.6% 11.8% 46.2% 34.4%
2001 48.0% 59.5% 11.6% 46.3% 34.7%
2002 48.1% 59.2% 11.1% 46.4% 35.3%
2003 48.3% 59.7% 11.4% 46.6% 35.2%
2004 48.1% 59.3% 11.2% 46.4% 35.2%
2005 48.0% 59.8% 11.8% 46.3% 34.5%
2006 47.9% 59.7% 11.8% 46.2% 34.4%
2007 48.0% 59.9% 11.9% 46.3% 34.3%
2008 48.3% 60.0% 11.7% 46.6% 34.9%
2009 49.0% 59.9% 11.0% 47.3% 36.3%
2010 48.8% 59.5% 10.7% 47.2% 36.5%
2011 48.3% 59.5% 11.1% 46.7% 35.6%

Source: Authors’ analysis of Current Population Survey Outgoing Rotation Group microdata

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For decades, women and African Americans have been employed in the state and local public sectors at rates that are higher than their shares of private-sector and overall employment. As shown in Figure A, in 2011 women comprised 48.3 percent of overall employment, yet accounted for 59.5 percent of employment in state and local government, significantly higher than their 46.7 percent share of private-sector employment. As the figure illustrates, women’s share of state and local government jobs has increased by 3.3 percentage points since 1989.

Figure B

African American share of employment, by sector, 1989–2011

Total employment State and local public sector State and local Private sector Private sector
1989 10.9% 14.1% 3.1% 10.1% -0.9%
1990 10.9% 14.0% 3.1% 10.1% -0.8%
1991 10.9% 14.1% 3.1% 10.1% -0.8%
1992 10.9% 14.5% 3.5% 10.1% -0.9%
1993 11.0% 14.5% 3.5% 10.1% -0.9%
1994 11.2% 14.5% 3.4% 10.3% -0.9%
1995 11.3% 14.8% 3.5% 10.4% -0.9%
1996 11.3% 14.7% 3.4% 10.5% -0.8%
1997 11.4% 15.1% 3.7% 10.6% -0.8%
1998 11.6% 14.5% 2.9% 10.9% -0.7%
1999 11.7% 14.4% 2.7% 11.0% -0.7%
2000 11.4% 14.0% 2.6% 10.8% -0.6%
2001 11.3% 13.9% 2.6% 10.6% -0.7%
2002 11.1% 14.0% 2.9% 10.4% -0.7%
2003 11.0% 14.1% 3.0% 10.3% -0.7%
2004 11.0% 13.5% 2.5% 10.4% -0.7%
2005 11.1% 13.6% 2.5% 10.5% -0.6%
2006 11.2% 13.8% 2.7% 10.5% -0.6%
2007 11.3% 13.2% 2.0% 10.7% -0.6%
2008 11.2% 13.6% 2.4% 10.6% -0.6%
2009 11.0% 13.0% 2.0% 10.4% -0.6%
2010 11.0% 12.9% 1.9% 10.4% -0.6%
2011 10.9% 12.8% 1.9% 10.3% -0.5%

Source: Authors’ analysis of Current Population Survey Outgoing Rotation Group microdata

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In comparison, Figure B illustrates that in 2011, African Americans accounted for 10.9 percent of overall employment, yet held 12.8 percent of state and local public-sector jobs and 10.3 percent of private-sector jobs. As the figure shows, African Americans, like women, have traditionally been underrepresented in the private sector and overrepresented in the state and local public sectors. However, African Americans’ representation in state and local government jobs has declined 2.3 percentage points since 1997.

Figure C

Hispanic share of employment, by sector, 1989–2011

Total employment State & Local State & Local Private Sector Private Sector
1989 7.6% 5.5% -2.1% 8.1% 0.4%
1990 8.7% 6.1% -2.6% 9.3% 0.6%
1991 8.8% 6.4% -2.4% 9.4% 0.6%
1992 8.9% 6.3% -2.6% 9.5% 0.6%
1993 9.0% 6.5% -2.6% 9.6% 0.5%
1994 9.3% 6.6% -2.7% 9.8% 0.5%
1995 9.5% 7.2% -2.3% 9.9% 0.5%
1996 9.6% 7.4% -2.3% 10.1% 0.5%
1997 10.4% 7.4% -3.0% 11.0% 0.6%
1998 10.6% 7.6% -3.0% 11.2% 0.6%
1999 10.8% 7.6% -3.2% 11.4% 0.6%
2000 12.1% 8.1% -4.0% 12.9% 0.8%
2001 12.4% 8.5% -3.9% 13.2% 0.8%
2002 12.7% 8.8% -3.9% 13.5% 0.8%
2003 13.1% 8.5% -4.6% 14.0% 0.9%
2004 13.4% 8.8% -4.5% 14.3% 0.9%
2005 13.7% 8.8% -4.8% 14.6% 0.9%
2006 14.1% 9.1% -5.0% 15.1% 1.0%
2007 14.5% 9.6% -4.9% 15.4% 1.0%
2008 14.4% 9.7% -4.7% 15.3% 0.9%
2009 14.5% 10.0% -4.5% 15.4% 0.9%
2010 14.7% 10.6% -4.2% 15.6% 0.9%
2011 15.0% 10.6% -4.3% 15.8% 0.9%

Source: Authors’ analysis of Current Population Survey Outgoing Rotation Group microdata

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In contrast to the patterns among women and African Americans, Hispanics remain underrepresented in the state and local public sectors and overrepresented in the private sector. As illustrated in Figure C, in 2011 Hispanics made up 15 percent of overall employment, yet accounted for 10.6 percent of state and local government employment, far lower than their 15.8 percent share of private-sector employment. The figure shows how the Hispanic share of employment in state and local government and in the private sector has steadily kept pace with Hispanics’ growth in overall employment since 1989.

A better-educated workforce, lower overall pay

Figure D

Employment shares by sex and race, state and local public sectors versus private sector, 2011

State and local public sectors Private sector
Male Female Male Female
White 29.1% 41.9% 35.3% 31.7%
African American 4.6% 8.2% 4.8% 5.5%
Hispanic 4.5% 6.2% 9.6% 6.3%
Other race 2.4% 3.3% 3.6% 3.2%

Note: Shares may not sum properly due to rounding.

Source: Authors’ analysis of Current Population Survey Outgoing Rotation Group microdata

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When making any wage comparisons across the public and private sectors, it is important to recognize that workers in the state and local public sectors have, on average, a different demographic profile than workers in the private sector. As previously noted, state and local government workers are more often female, and a greater share is African American. Figure D further illustrates these patterns by graphing the share of employment for state and local public-sector employees and private-sector employees by gender and race.

Figure E

Education levels of state and local public-sector versus private-sector employees, by sex, 2011

Source: Authors’ analysis of Current Population Survey Outgoing Rotation Group microdata

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State and local public-sector employees also tend to have significantly higher levels of education than private-sector workers. Figure E compares the education levels of state and local public-sector workers with those of private-sector workers, separated by sex. As the figure shows, 46.2 percent of men in state and local government jobs have at least a bachelor’s degree, compared with 29.1 percent in the private sector. For women, the difference is even larger: 54.1 percent in the state and local public sectors have at least a bachelor’s degree, compared with 30.1 percent in the private sector.

Figure F

Education levels of state and local public-sector versus private-sector employees, by race, 2011

Source: Authors’ analysis of Current Population Survey Outgoing Rotation Group microdata

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Figure F makes a similar comparison of education levels in the state and local public sectors versus the private sector, this time separated by race. State and local government workers show significantly higher levels of education across all racial groups, with particularly striking differences for African Americans and Hispanics. For African Americans, the share with at least a bachelor’s degree, at 42.1 percent, is more than double that of the private sector (20.1 percent). Among Hispanic state and local government workers, 34 percent have at least a bachelor’s degree—nearly three times the 11.7 percent share in the private sector.

Despite these significantly higher levels of education—and contrary to assertions by some governors in recent state-level debates—the most rigorous studies have consistently shown that state and local government employees earn less both in wages and total compensation than comparable private-sector workers (Keefe 2010). Using data from the Annual Social and Economic Supplement of the Current Population Survey and standard regression models for wage analyses, we compared the wage income of private-sector employees with that of state and local government workers. After controlling for education, experience, sex, race, ethnicity, marital status, full-time/part-time status, number of hours worked, citizenship status, Census region, metropolitan status (whether residing within or outside the boundaries of a major metropolitan area), and employer size, we find that state and local government employees make, on average, 11.7 percent less in wages than similar private-sector employees.7 (These same controls are used in all subsequent wage comparisons in this briefing paper.) Other studies looking at total compensation including employer-provided benefits find a narrower gap but that public-sector workers are still under-compensated in comparison to private-sector workers (Keefe 2010, 2011).

Table 1

State and local public-sector wage penalty, overall and by sex and race

Wage penalty
Average annual wage income penalty for state and local public-sector employees versus private-sector employees -11.7%***
Comparison with private-sector employees of the same sex
Men in state and local public sectors -11.1%***
Women in state and local public sectors -12.2%
Comparison with private-sector employees of the same race
Whites in state and local public sectors -14.5%***
African Americans in state and local public sectors -1.7%***
Hispanics in state and local public sectors -3.7%***

Notes: Controls for all models include education, experience, gender, race, marital status, organizational size, metropolitan status, citizenship, Census region, full-time status, and total work hours. Full regression results are included in the appendix tables. See the “Table and figure notes” section of the briefing paper for more detail.

*Probability estimate 0 is >.1. (Interactive models show significance of the interaction term.)

**Probability estimate 0 is >.05.

***Probability estimate 0 is >.01.

Values describe percentage difference in annual income from wages compared with that of similar private-sector workers, using the equation dlog(y)/dx =100% x (eβ-1).

We use interactive models to calculate specific effects by sex and race. The values displayed are calculated using the equation dlog(y)/dx =100% x (eβ-1), where β equals the sum of the coefficients on the sex/race indicator term and the sex/race-state and local sector interaction term.

In the model interacting the state and local sector indicator variable with the female indicator variable, the state and local indicator is highly significant (p<.0001), while the interactive term is not statistically significant (p=.2). This suggests that the wage penalty of working in the state and local public sectors versus the private sector is the same for both men and women. Full regression results are included in the appendix tables.

Source: Authors’ analysis of Current Population Survey Annual Social and Economic Supplement microdata, pooled years 2006 and 2007

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As also shown in Table 1, a gap between state and local public-sector workers and similar private-sector employees appears for both genders and for whites, African Americans, and Hispanics. In a regression that allowed for the effect of state and local government employment on wages to differ between men and women,8 there was no statistically significant difference between the sexes: Both earned about 11–12 percent less than private-sector workers of the same gender.

An examination of how the state and local public-sector wage penalty applies to individuals of different races reveals that whites in state and local government jobs earn 14.5 percent less than whites in the private sector. The results indicate smaller wage gaps for African American and Hispanic workers, with these groups earning 1.7 percent and 3.7 percent less, respectively, than private-sector employees of the same race. It should be noted that these smaller wage gaps do not stem from people of color in state and local government jobs earning more than their white colleagues; overall, they earn less. Rather, the large racial wage gap for African Americans and Hispanics that exists in the private sector offsets much of the state and local public-sector wage penalty (a finding that will be discussed in greater depth in the following section).

A smaller wage disparity for many state and local government workers

Having established that a wage penalty exists for state and local public-sector employees when compared with private-sector workers regardless of race or gender, we now examine how race- and gender-based wage disparities in state and local government compare with those in the private sector. For women with at least a bachelor’s degree—who, as mentioned earlier, account for 54.1 percent of women in the state and local public sectors—the wage gap with similarly educated males is smaller in state and local government than in the private sector. Likewise, the wage disparities between whites and African Americans, and between whites and Hispanics, are significantly smaller in the state and local public sectors. This, combined with the model hiring practices previously described, may help explain why the public sector continues to attract disproportionate shares of women and African Americans.

Table 2 shows the male-female wage gap in state and local government and in the private sector. Among state and local public-sector workers, women on average earn 20.9 percent less in wages than their male counterparts. This is statistically no different from the average male-female wage gap of 20.4 percent in the private sector.9 However, as previously noted, state and local government employees tend to have significantly higher levels of education than private-sector workers, particularly among women. The data show that the state and local public sectors do a better job of equalizing pay across genders for workers with higher levels of education. Women with a bachelor’s degree in state and local government jobs earn 16.9 percent less in wages than their male counterparts, compared with a male-female wage gap of 18.9 percent for similarly educated private-sector workers. The benefit of working in state and local government jobs is more striking for women with advanced degrees. While they still earn 12.4 percent less than similarly educated men in state and local public-sector jobs, this is far smaller than the private-sector wage gap of 21 percent.

Table 2

Male-female wage gap in the private sector versus the state and local public sectors

Private sector State and local public sectors
Average female wage income compared with male wage income -20.4%*** -20.9%***
Female wage income compared with wage income of similarly educated males
Less than a high school education -25.7%*** -23.7%
High school -23.0%*** -27.2%***
Some college -16.5%*** -27.3%
Bachelor’s degree -18.9%*** -16.9%***
Advanced degree -21.0* -12.4%***

Notes: Controls for all models include education, experience, gender, race, marital status, organizational size, metropolitan status, citizenship, Census region, full-time status, and total work hours. Full regression results are included in the appendix tables. See the “Table and figure notes” section of the briefing paper for more detail.

*Probability estimate 0 is >.1. (Interactive models show significance of the interaction term.)

**Probability estimate 0 is >.05.

***Probability estimate 0 is >.01.

Values describe percentage difference in annual income from wages compared with that of similar male workers in the same sector, using the equation dlog(y)/dx =100% x (eβ-1).

We use interactive models to calculate specific effects by education. The values displayed are calculated using the equation dlog(y)/dx =100% x (eβ-1), where β equals the sum of the coefficients on the education indicator term and the education-state and local sector interaction term.

In the interactive models, the probability estimates denote the statistical significance of the interaction terms. Thus for models with statistically insignificant interaction terms, such as the "less than a high school education" interaction in the state and local public sectors, this indicates that the male-female wage gap at this education level is not statistically different from the wage gap at the "high school" education level. Full regression results are included in the appendix tables.

Source: Authors’ analysis of Current Population Survey Annual Social and Economic Supplement microdata, pooled years 2006 and 2007

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State and local government jobs also strongly reduce the wage gap between different racial groups. Table 3 shows differences in wages for African Americans and Hispanics compared with white workers in the private sector and in the state and local public sectors. As the table shows, the difference between the sectors is dramatic. In the private sector, African Americans earn an average of 12.9 percent less than white workers. Yet among state and local public employees, the wage disparity between African Americans and whites is only 2.2 percent. Likewise, Hispanic workers in the private sector earn, on average, 11.1 percent less than white workers. In the state and local public sectors, this disparity is only 2.9 percent.

Table 3

Racial wage gaps in the private sector versus the state and local public sectors

Private sector State and local public sectors
Average African American wage income compared with white wage income -12.9%*** -2.2%**
Average Hispanic wage income compared with white wage income -11.1%*** -2.9%**

Notes: Controls for all models include education, experience, gender, race, marital status, organizational size, metropolitan status, citizenship, Census region, full-time status, and total work hours. Full regression results are included in the appendix tables. See the “Table and figure notes” section of the briefing paper for more detail.

*Probability estimate 0 is >.1.

**Probability estimate 0 is >.05.

***Probability estimate 0 is >.01.

Values describe percentage difference in annual income from wages compared with similar white workers in the same sector, using the equation dlog(y)/dx =100% x (eβ-1).

Source: Authors’ analysis of Current Population Survey Annual Social and Economic Supplement microdata, pooled years 2006 and 2007

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For African Americans and Hispanics, public-sector jobs demonstrate a lower racial wage gap at some education levels, while demonstrating a wage premium at others. Table 4 shows how the wages of African Americans and Hispanics with different levels of education compare with wages of white workers with equivalent education levels. In the private sector, African Americans at every education level earn wages significantly lower than those of white workers. The smallest wage gap in the private sector is for African Americans with some college, who earn 11 percent less than similarly educated whites. The largest difference is for African Americans with advanced degrees, who earn an average of nearly 20 percent less than whites with advanced degrees. In contrast, in state and local government jobs, African Americans at some education levels receive higher wages than similarly educated whites. For example, African Americans with less than a high school degree, a bachelor’s degree, or an advanced degree earn 8.3 percent, 0.4 percent, and 1.7 percent more, respectively, than whites with the same levels of education. Still, the majority of African Americans in state and local public-sector jobs have either a high school degree or some college. For these two groups, wages are 5.7 percent and 5.2 percent lower, respectively, than those of similarly educated whites.

Table 4

African American and Hispanic wage income compared with wage income of similarly educated white workers, in the private sector versus the state and local public sectors

Race/education level Private sector State and local public sectors
African Americans with less than high school -12.6% +8.3%**
African Americans with a high school diploma -13.1%*** -5.7%***
African Americans with some college -11.0%* -5.2%
African Americans with a bachelor’s degree -13.3% +0.4%**
African Americans with an advanced degree -19.5%*** +1.7%**
Hispanics with less than high school -7.4%** +6.7%*
Hispanics with a high school diploma -10.2%*** -4.0%
Hispanics with some college -9.3% -6.2%
Hispanics with a bachelor’s degree -19.3%*** -0.6%
Hispanics with an advanced degree -19.6%*** -2.0%

Notes: Controls for all models include education, experience, gender, race, marital status, organizational size, metropolitan status, citizenship, Census region, full-time status, and total work hours. Full regression results are included in the appendix tables. See the “Table and figure notes” section of the briefing paper for more detail.

*Probability estimate 0 is >.1. (Interactive models show significance of the interaction term.)

**Probability estimate 0 is >.05.

***Probability estimate 0 is >.01.

Values describe percentage difference in annual income from wages compared with white workers in the same sector, using the equation dlog(y)/dx =100% x (eβ-1). In these interactive models, the described effects reflect the sum of the coefficient on each race indicator variable and the respective race-education interaction variables. The probability estimates denote the statistical significance of the interaction terms. Thus for models with statistically insignificant interaction terms, such as the "African Americans with less than high school" interaction in the private sector, this can be interpreted to mean that either the white-African American wage gap at this education level is not statistically different from the wage gap at the "African Americans with a high school diploma" education level, or that the wage penalty of not having a high school degree is not different for African Americans and whites.

Source: Authors’ analysis of Current Population Survey Annual Social and Economic Supplement microdata, pooled years 2006 and 2007

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Hispanic workers also benefit from more equitable wages in the state and local public sectors. The private-sector wage gap between Hispanics and whites ranges from a low of 7.4 percent for workers with less than a high school degree to a high of 19.6 percent for workers with an advanced degree. In contrast, in state and local government jobs, Hispanic employees with less than a high school education earn 6.7 percent more than similar white employees, and Hispanic workers with advanced degrees earn only 2 percent less than similarly educated whites.

Public-sector job loss: Disproportionately harmful to African Americans and women

The high concentration of women and African Americans working in the public sector, and the greater wage equity many experience there, make cuts to state and local government especially painful for both groups. The Great Recession caused the largest drop in state revenues ever recorded and left many states facing dramatic budget shortfalls (McNichol et al. 2012). Because most state constitutions do not allow deficit spending, this has led to steep reductions in state and local budgets, which has translated into significant job loss among state and local public-sector employees.

Reductions in state and local government workforces are a significant drag on the economy as a whole (Leonhardt 2011)—and are particularly damaging for women. As previously discussed, in 2011 women comprised 48.3 percent of overall employment, but about three-fifths (59.5 percent) of state and local public-sector workers. The disproportionate representation of women in state and local government has resulted in women suffering the vast majority of public-sector job losses. Of the net change in total state and local government employment between 2007 (before the recession) and 2011—a decline of roughly 765,000 jobs—about 70.5 percent of the jobs lost were held by women (Current Population Survey Outgoing Rotation Group 2007–2011). Today approximately 540,000 fewer women are employed in state and local government jobs than in 2007, compared with about 225,000 fewer men (Current Population Survey Outgoing Rotation Group 2007–2011). These numbers represent declines of 5.1 percent and 3.2 percent, respectively (see Figure G).

Figure G

Percentage change in state and local public-sector employment, by sex and race, 2007–2011

Source: Authors’ analysis of Current Population Survey Outgoing Rotation Group microdata

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African Americans have also suffered disproportionately from state and local budget cuts. As noted previously, in 2011 African Americans comprised more than one-tenth (10.9 percent) of overall employment and 12.8 percent of state and local public-sector employment. However, they accounted for almost one-fifth (19.8 percent) of the overall decline in state and local government employment between 2007 and 2011 among racial groups that lost jobs (Current Population Survey Outgoing Rotation Group 2007–2011). This loss of 177,000 jobs (Current Population Survey Outgoing Rotation Group 2007–2011) represents a decrease in African Americans’ state and local government employment of 7.6 percent. As shown in Figure G, this is the largest percentage change for all racial groups.

Examining the proportion of people from the state and local public sectors who are currently unemployed provides another perspective on public-sector job cuts. In 2011 nearly 450,000 women reported that they were unemployed and that their most recent job was from the state or local public sectors (see Figure H). At 62 percent of the total number of people unemployed from the state or local public sectors, this is lower than women’s share of the net change in state and local government jobs (as noted previously, about 70.5 percent)—suggesting that some of the women who lost state and local public-sector jobs since the recession began have either found private-sector work or have exited the labor force (i.e., retired or stopped looking for a job). Nevertheless, it is still larger than the overall female share of state and local government employees.

Figure H

Number of unemployed workers from state and local public sectors, 1989–2011*

* This figure shows the number of unemployed who reported their most recent job was in the state or local public sectors.

Source: Authors’ analysis of Current Population Survey Outgoing Rotation Group microdata

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The situation for African Americans is the reverse. In 2011, African Americans comprised 26.9 percent of those reporting that they were unemployed and had most recently worked in state or local government jobs (Current Population Survey Outgoing Rotation Group 2011). This is much higher than their share (19.8 percent) of the overall decline in state and local public-sector employment among racial groups that lost jobs from 2007 to 2011. This finding suggests that, unlike other groups who either took jobs in the private sector or exited the labor force since the beginning of the recession, African Americans have faced greater difficulty in finding other work and/or remained more strongly attached to the labor market, leading to their higher share of those still unemployed.

Although women and African Americans have experienced significant declines in state and local public-sector employment, Hispanic employment in these sectors has actually increased since 2007. Total Hispanic employment in state and local government jobs grew by about 107,000 people from 2007 to 2011, an increase of 6.3 percent (Current Population Survey Outgoing Rotation Group 2007–2011). As noted previously, in 2011 Hispanics made up 10.6 percent of all state and local public employees—up from 9.6 percent in 2007. This increase in Hispanic workers in state and local government jobs is a positive step toward achieving greater racial and ethnic diversity in employment; however, it accompanies less positive wage trends. Since the start of the recession, the real median wage of Hispanic employees in state and local public-sector jobs has declined by 5.2 percent, compared with a decline of 1.9 percent for African Americans, 0.7 percent for whites, and 2.2 percent for all other races (Current Population Survey Outgoing Rotation Group 2007–2011). This suggests that although more Hispanic workers are entering into state and local public-sector jobs, they are largely taking lower-paying positions.

The private sector’s slow improvement and the public sector’s continued decline

Table 5

Employment by sector since the end of the recession (in thousands)

June 2009 Feb. 2010 Jan. 2012 Net change, June 2009 to Jan. 2012 Net change, Feb. 2010 to Jan. 2012
TOTAL NONFARM EMPLOYMENT  130,503  129,244  132,470  1,967  3,226
Manufacturing 11,725 11,462 11,860 135 398
Construction 6,007 5,529 5,567 -440 38
Trade, transportation, and utilities 24,892 24,537 25,238 346 701
Financial activities 7,749 7,660 7,695 -54 35
Professional and business services 16,445 16,542 17,669 1,224 1,127
Education and health care 19,179 19,393 20,116 937 723
Leisure and hospitality 13,084 12,924 13,510 426 586
Government (all levels) 22,570 22,471 21,986 -584 -485
State and local government 19,743 19,602 19,164 -579 -438

Source: Bureau of Labor Statistics Current Establishment Survey

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Since the recession’s official end in June 2009, job growth in the United States has been distinctly one-sided: The private sector has experienced employment growth in the majority of industries, while the public sector has continued to shed jobs. Table 5 details changes in employment by sector from June 2009 to January 2012. Over this period, the United States saw a net increase in nonfarm employment of roughly two million jobs, with every non-government sector adding jobs except construction and financial services. Over the same period, however, state and local government employment shrunk by nearly 580,000 jobs. It is even more telling to look at the period after February 2010, the month the labor market “bottomed out.” From February 2010 to January 2012, the United States experienced a net increase in total nonfarm employment of more than 3.2 million jobs, while state and local government employment fell by 438,000. Over this period, every major sector of the economy experienced net growth in jobs except the public sector.

Conclusion

For the past five decades, the public sector has led the way in providing opportunity and reducing discrimination in the workforce. This has led to the disproportionate representation of women and African Americans in state and local government jobs. Unfortunately, this overrepresentation has meant that, as state and local governments address revenue shortfalls by slashing budgets and cutting public services, women and African Americans have suffered disproportionately from the resulting job losses since 2007.

The continued cuts to state and local governments also threaten to undermine progress that the public sector has made toward greater wage equality. The economy is losing jobs in a sector (state and local government) that often has smaller pay gaps than the private sector. Especially for people of color and women with high levels of education, this is a step in the wrong direction.

With the private sector finally showing signs of sustained job growth, continued cuts to state and local governments only hamper a faster recovery. Absent further federal assistance and an altered approach to raising state and local revenues, the state and local public sectors will likely continue to shed jobs. An expanded federal recovery program—such as greater fiscal relief to states, funding for infrastructure and school modernization projects, continued support of social insurance programs, and direct job creation programs in hard-hit communities—would go a long way toward accelerating the recovery and assisting women and African Americans who have suffered disproportionately from state and local public-sector job cuts.

Endnotes

1. The establishment and strengthening of civil rights laws protecting women and people of color in employment occurred through the Equal Pay Act of 1963, Federal Executive Order 11246, and Titles VI and VII (as amended by the Equal Employment Opportunity Act of 1972) of the Civil Rights Act of 1964 (U.S. Equal Employment Opportunity Commission).

2.  Police departments have historically lagged far behind other government agencies in hiring women (Crosby 2004), yet have hired African American men in proportion to their labor force participation rate (Austin 2011). In contrast, fire departments have imposed barriers to hiring and promoting African American men, who remain underrepresented since they are employed at only 67 percent of their proportionate representation level (Austin 2011).

3.  It is beyond the scope of this paper to provide a full review of this literature. A good starting point would be Riach and Rich 2002. In addition to field experiments, there are also implicit bias studies (see Grant-Thomas 2011 for an introduction), interviews of employers (Moss and Tilly 2001), and the fact that multivariate regression-based analyses fail to fully explain wage differentials (General Accounting Office 2003).

4.  National Women’s Law Center calculations from U.S. Census Bureau, Current Population Survey, 2011 Annual Social and Economic Supplement, Table PINC-05: Work Experience in 2010 – People 15 Years Old and Over by Total Money Earnings in 2010, Age, Race, Hispanic Origin, and Sex, available at http://www.census.gov/hhes/www/cpstables/032011/perinc/toc.htm (last visited Sept. 27, 2011). Annual racial wage gaps were calculated by subtracting the annual total earnings of African American and Hispanic women from that of non-Hispanic white men.

5.  In EEOC, et al. v. KOKH, No. 5:07-cv-01043-D (W.D. Okla. March 4, 2011), a television station settled a race and sex discrimination case filed by the EEOC for $45,000 and additional consideration. In EEOC v. Williams Country Sausage Co., Civil Action No. 1:10-cv-01263 (W.D. Tenn. filed Sept. 30, 2010), a pork company settled a race discrimination case filed by the EEOC for $60,000 and other relief.

6.  Opponents of state affirmative action efforts have sought to ban those policies through state ballot initiative. For example, in 1996, voters approved California’s Proposition 209, which amended the state constitution to overturn affirmative action policy in state public employment, public education, and public contracting. Court cases on affirmative action, including Fisher v. University of Texas (to be heard by the U.S. Supreme Court this year), have focused largely on state public university admissions policies.

7.  EPI analysis of Annual Social and Economic Supplement of the Current Population Survey, pooled years 2006 and 2007. We use these years because they are the most recent normal business cycle, thereby eliminating any biases in the data resulting from the effects of the subsequent recession.

8.  Allowing for the effect of state and local government employment on wages to vary by gender provides for the possibility that only men or only women receive lower wages in the state and local public sectors when compared with their private-sector counterparts. The results demonstrate that this is not the case.

9.  In the regression model in which a state and local public-sector indicator variable interacts with the female indicator variable (model two in Table A1), the female state and local interaction term is not statistically different from zero. This indicates that the male-female wage gap is, on average, no different across the two sectors.

Table and figure notes

References

Austin, Algernon. 2011. Whiter Jobs, Higher Wages: Occupational Segregation and the Lower Wages of Black Men. Economic Policy Institute Briefing Paper No. 288.

Bertrand, Marianne, and Senhil Mullainathan. 2004. “Are Emily and Greg More Employable Than Lakisha and Jamal? A Field Experiment on Labor Market Discrimination.” The American Economic Review, vol. 94, no. 4, pp. 991–1013.

Blumrosen, Alfred W., and Ruth G. Blumrosen. 2002. The Reality of Intentional Job Discrimination in Metropolitan America—1999. Rutgers State University of New Jersey.

Crosby, Faye J. 2004. Affirmative Action Is Dead; Long Live Affirmative Action. Yale University Press.

Current Establishment Survey. 2009–2012. Survey conducted by the Bureau of Labor Statistics. U.S. Census Bureau.

Current Population Survey Annual Social and Economic Supplement microdata. Various years. Survey conducted by the Bureau of the Census for the Bureau of Labor Statistics [machine-readable microdata file]. U.S. Census Bureau. http://www.bls.census.gov/cps_ftp.html#cpsmarch

Current Population Survey Outgoing Rotation Group microdata. Various years. Survey conducted by the Bureau of the Census for the Bureau of Labor Statistics [machine-readable microdata file]. U.S. Census Bureau. http://www.bls.census.gov/cps_ftp.html#cpsbasic

Dale, Charles V. 2005. Congressional Research Service Report for Congress: Federal Affirmative Action Law: A Brief History. Congressional Research Service, Library of Congress.

Equal Employment Opportunity Act of 1972, Pub. L. 92-261. 86 Stat. 103. 24 Mar. 1972. Print.

General Accounting Office. 2003. Women’s Earnings: Work Patterns Partially Explain Difference between Women’s and Men’s Earnings. General Accounting Office.

Grant-Thomas, Andrew. September/October 2011. “Implicit Bias, Racial Inequality, and Our Multivariate World.” Poverty & Race. Poverty & Race Research Action Council.

Keefe, Jeffrey. 2010. Debunking the Myth of the Overcompensated Public Employee: The Evidence. Economic Policy Institute Briefing Paper No. 276.

Keefe, Jeffrey. 2011. Research series on public- versus private-sector compensation in the states, published by the Economic Policy Institute and accessible through through EPI’s “Public-sector workers earn less” Web commentary. http://www.epi.org/publication/public_sector_workers_earn_less/

Leonhardt, David. 2011. “The Cost of Austerity.” The New York Times’ Economix blog, July 8. http://economix.blogs.nytimes.com/2011/07/08/the-cost-of-austerity/

McNichol, Elizabeth, Philip Oliff, and Nicholas Johnson. 2012. “States Continue to Feel Recession’s Impact.” Center on Budget and Policy Priorities, updated February 27, 2012. http://www.cbpp.org/cms/index.cfm?fa=view&id=711

Moss, Philip, and Chris Tilly. 2001. Stories Employers Tell: Race, Skill, and Hiring in America. Russell Sage Foundation.

National Women’s Law Center. 2012. Closing the Wage Gap is Especially Important for Women of Color in Difficult Times. http://www.nwlc.org/sites/default/files/pdfs/womenofcolorfactsheet.pdf.

Riach, P.A., and J. Rich. 2002. “Field Experiments of Discrimination in the Marketplace.” The Economic Journal, vol. 112, no. 483, pp. F480–F518.

U.S. Department of Labor, Office of Federal Contract Compliance Programs. 2002. “Facts on Executive Order 11246—Affirmative Action.” Accessed March 30, 2012, at http://www.dol.gov/ofccp/regs/compliance/aa.htm.

U.S. Department of Labor, Office of Federal Contract Compliance Programs. 2012. “Shipping Giant FedEx to Pay $3 Million to Settle Charges of Hiring Discrimination Brought by U.S. Department of Labor.” Accessed March 30, 2012, at http://www.dol.gov/opa/media/press/ofccp/OFCCP20120507.htm.

U.S. Equal Employment Opportunity Commission. n.d. “Laws Enforced by EEOC.” Accessed March 2, 2012, at http://www.eeoc.gov/laws/statutes/index.cfm.

Appendix tables

Table A1

OLS results of wage equations comparing private sector versus state and local public sectors

Dependent variable: Log of income from wages

Predictor (1) (2) (3) (4)
State and local -0.1245*** -0.1173*** -0.1568*** -0.1475***
Female -0.2863*** -0.2851*** -0.2847*** -0.2832***
Female * State and local -0.0129 -0.0169*
African American -0.1649*** -0.1650*** -0.1774*** -0.1777***
Hispanic -0.1228*** -0.1226*** -0.1301*** -0.1299***
Other race -0.1407*** -0.1407*** -0.1405*** -0.1405***
African American * State and local 0.1395*** 0.1404***
Hispanic * State and local 0.1193*** 0.1196***
Other race * State and local -0.0036 -0.0037
N  121,943  121,943  121,943  121,943
Adjusted R2 0.428 0.428 0.429 0.429

Notes: Reference categories are white, male, high school education. Other controls for all models include age, marriage status, full-time status, total work hours, Census region, citizenship, metropolitan location status, and firm size.

*Probability estimate 0 is >.1.

**Probability estimate 0 is >.05.

***Probability estimate 0 is >.01.

Source: Authors’ analysis of Current Population Survey Annual Social and Economic Supplement microdata, pooled years 2006 and 2007

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Table A2

OLS results of wage equations comparing private sector versus state and local public sectors

Dependent variable: Log of income from wages

Private sector State and local public sectors
Predictor (1) (2) (3) (4) (5) (6) (7) (1) (2) (3) (4) (5) (6) (7)
Female -0.2279*** -0.2616*** -0.2458*** -0.2861*** -0.2274*** -0.2866*** -0.278*** -0.2344*** -0.3173*** -0.2430*** -0.3355*** -0.2348*** -0.3338*** -0.3625***
African American -0.1376*** -0.1372*** -0.1878*** -0.1905*** -0.1409*** -0.1881*** -0.1702*** -0.0226** -0.0206* -0.0622*** -0.0762*** -0.0592*** -0.1064*** -0.1450***
Hispanic -0.1178*** -0.1188*** -0.1212*** -0.134*** -0.1075*** -0.1239*** -0.1239*** -0.0298** -0.0286** -0.0077 -0.0245 -0.0406 -0.0387 -0.0977**
Other race -0.0735*** -0.0725*** -0.1001*** -0.0997*** -0.1240*** -0.1502*** -0.1407*** -0.0583*** -0.0562*** -0.0841*** -0.0796*** -0.0723* -0.0916** -0.1326**
Less than high school -0.1907*** -0.1814*** -0.1918*** -0.1779*** -0.2072*** -0.1966*** -0.2053*** -0.2253*** -0.2568*** -0.2262*** -0.2573*** -0.2851*** -0.3137*** -0.3891***
Some college 0.1522*** 0.1140*** 0.1521*** 0.1130*** 0.1451*** 0.1084*** 0.1139*** 0.1705*** 0.1709*** 0.1708*** 0.1704*** 0.1723*** 0.1705*** 0.1506***
Bachelor’s degree 0.4808*** 0.4575*** 0.4808*** 0.4547*** 0.4854*** 0.4610*** 0.4678*** 0.4059*** 0.3288*** 0.4059*** 0.3266*** 0.3865*** 0.3102*** 0.3013***
Advanced degree 0.7412*** 0.7296*** 0.7413*** 0.7267*** 0.7368*** 0.7208*** 0.7234*** 0.5821*** 0.4715*** 0.5826*** 0.4675*** 0.5718*** 0.4602*** 0.4346***
Female * education level
Less than high school -0.0352*** -0.0463*** -0.0433*** -0.0176 0.0462 0.0457 0.0322 0.2051***
Some college 0.0817*** 0.0837*** 0.0835*** 0.0714*** -0.0012 -0.0001 0.0004 0.0358
Bachelor’s degree 0.0525*** 0.0586*** 0.0585*** 0.0429*** 0.1327*** 0.1368*** 0.1353*** 0.1523***
Advanced degree 0.0257* 0.0324** 0.0368** 0.0305* 0.1854*** 0.1929*** 0.1897*** 0.2330***
Female * race
African American 0.0990*** 0.1056*** 0.1050*** 0.0676*** 0.0643*** 0.0903*** 0.0884*** 0.1536***
Hispanic 0.0067 0.0349*** 0.0377*** 0.0378** -0.0373 -0.0073 -0.0060 0.0979*
Other race 0.0601*** 0.0613*** 0.0634*** 0.0407 0.0460 0.0409 0.0318 0.0995
African American * education level
Less than high school 0.0067 0.0175 0.0132* 0.1390** 0.1484** 0.3926***
Some college 0.0243* 0.0087 -0.0221 0.0063 0.0077 0.0160
Bachelor’s
degree
-0.0022 -0.0105 -0.0469* 0.0637** 0.0512* 0.1083**
Advanced degree -0.0756*** -0.0802*** -0.1245** 0.0761** 0.0602* 0.1320**
Hispanic * education level
Less than high school 0.0308** 0.0288* 0.0466** 0.1051* 0.1081* 0.2532***
Some college 0.0094 0.0098 0.0025 -0.0238 -0.0145 0.1166**
Bachelor’s degree -0.1068*** -0.107*** -0.1348*** 0.0344 0.0352 0.0119
Advanced degree -0.1107*** -0.1088*** -0.0872** 0.0208 0.0202 0.1313*
Other race * education level
Less than high school -0.0046 0.0040 -0.0072 0.0878 0.1011 0.1412
Some college 0.0512* 0.0468** 0.0332 -0.0115 -0.0118 0.0488
Bachelor’s degree 0.0645*** 0.0595*** 0.0434 0.0803 0.0770 0.0754
Advanced degree 0.1460*** 0.1479*** 0.1401*** -0.0399 -0.0254 0.0597
Female * African American * education level
Less than high school 0.0010 -0.5019***
Some college 0.0606** -0.0155
Bachelor’s degree 0.0735** -0.0928
Advanced degree 0.0878 -0.1143
Female * Hispanic * education level
Less than high school -0.0568* -0.2971**
Some college 0.0151 -0.2211***
Bachelor’s degree 0.0616* 0.0268
Advanced degree -0.0526 -0.1835**
Female * other race * education level
Less than high school 0.0207 -0.1161
Some college 0.0311 -0.1057
Bachelor’s degree 0.0365 -0.0007
Advanced degree 0.0177 -0.1525
N  104,643  104,643  104,643  104,643  104,643  104,643  104,643  17,300  17,300  17,300  17,300  17,300  17,300  17,300
Adjusted R2 0.433 0.434 0.433 0.434 0.434 0.435 0.435 0.380 0.384 0.381 0.385 0.381 0.385 0.386

Notes: Reference categories are white, male, high school education. Other controls for all models include age, marriage status, full-time status, total work hours, Census region, citizenship, metropolitan location status, and firm size.

*Probability estimate 0 is >.1.

**Probability estimate 0 is >.05.

***Probability estimate 0 is >.01.

Source: Authors’ analysis of Current Population Survey Annual Social and Economic Supplement microdata, pooled years 2006 and 2007

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