Illinois Veterans Employment and Earnings Profiles i

Illinois Veterans Employment and Earnings Profiles: The Impact of Local

Labor Markets

February 28, 2019

JooHee Han, PhD Post-doctoral Research Associate

Labor Education Program Project for Middle Class Renewal

University of Illinois at Urbana-Champaign

PROJECT FOR MIDDLE CLASS RENEWAL

Illinois Veterans Employment and Earnings Profiles ii

ABOUT THE PROJECT FOR MIDDLE CLASS RENEWAL

The Project for Middle Class Renewal’s mission is to investigate the working conditions of workers in today’s economy and elevate public discourse on issues affecting workers with research, analysis and

education in order to develop and propose public policies that will reduce poverty, provide forms of representation to all workers, prevent gender, race, and LGBTQ+ discrimination, create more stable forms

of employment, and promote middle-class paying jobs. Each year, the Project will be dedicated to a number of critical research studies and education forums on contemporary public policies and practices impacting labor and workplace issues. The report that follows, along with all other PMCR reports, may

be found at go.illinois.edu/pmcr

Illinois Veterans Employment and Earnings Profiles iii

EXECUTIVE SUMMARY

Currently around 631,029 veterans (men and women) of all eras and 90,000 post-9/11 veterans reside in Illinois. Prior studies at the national level suggest that post-9/11 veterans are at higher risk of unemployment and face earnings penalties or premiums in different occupations and sectors once they get a job.

As the local labor market contexts may produce different circumstances for veterans in Illinois, the report, “Illinois Veterans Employment and Earnings Profiles: The Impact of Local Labor Markets,” from the Project for Middle Class Renewal at the School of Labor and Employment Relations, University of Illinois, Urbana-Champaign creates an earnings profile of Illinois veterans. The analysis focuses primarily on post-9/11 veterans.

The study’s major findings are:

• Post-9/11 veterans in Illinois, on average, are not at higher risks of unemployment when accounting for demographic differences.

• Employed post-9/11 male veterans of almost all educational attainments are more likely to work fulltime than their nonveteran peers.

• Post-9/11 veterans with a bachelor’s degree or an advanced degree struggle in finding employment more than nonveteran peers with the same educational attainment.

• There is an average annual income penalty of $11,812 among post-9/11 male veterans with an advanced degree.

• Post-9/11 male veterans with some college education on average earn $2,128 more per year than nonveterans.

• Only in Transportation and Material Moving Occupations do post-9/11 male veterans earn higher hourly wages than comparable nonveterans in Illinois.

• Only in the Utilities industry do post-9/11 male veterans earn more than nonveterans (by $6.29 per hour).

• Occupations that produce better or worse wages for veterans in Illinois are not necessarily the same in other states.

• Post-9/11 male veterans in Illinois appear to have experienced wage penalties in many mostly high paying jobs occupations.

Recommendations:

1. Employment policies should target veterans with college educations. 2. Veteran policies should examine the causes of wage penalties in high wage occupations and address

how to improve veterans’ earnings. 3. Policies should pay attention to service members with higher education. 4. Policies should take the local labor market context into account. 5. To close the gap between military job skills and the skills required for the civilian labor market,

policymakers need to develop better crosswalks between the two by incorporating state-specific employment/earnings profiles.

Illinois Veterans Employment and Earnings Profiles 1

TABLE OF CONTENTS Executive Summary iii

1. Introduction 2

2. Prior Research 2.1. Employment and Unemployment 2.2. Earnings

3 3 4

3. Data and Method 5

4. Analyses 4.1. Employment and Unemployment 4.2. Earnings (Post-9/11 Male Veterans)

6 6

10

V. Conclusion and Policy Suggestions 14

References 16

Illinois Veterans Employment and Earnings Profiles 2 1. INTRODUCTION

Veterans’ socio-economic conditions have been a major concern of the public, scholars, and policy makers. Veterans constitute about 8% of the adult U.S. population and the high unemployment rate of post-9/11 young veterans (30% unemployment rate for veterans age 18-24 in 2011) has drawn extensive public attention (Bureau of Labor Statistics 2012).

A series of policies for veterans have been developed and implemented to address and reduce the obstacles to service members’ successful transitions to civilian life and particularly to the civilian labor market. Along with the GI Bill, which allows educational funding to veterans or their family members, many policies and government organizations for veterans focus on helping veterans find employment.1 Despite the variety of policies, many veterans feel that finding well-paying jobs and meaningful careers remain the most critical obstacles in their civilian transition process (Prudential 2012).

These programs and polices for ex-service members mostly run at the national level although local offices also exist. For example, Transition GPS, a mandatory five-day workshop covering job-search assistance and related services, is offered in military bases. But these services are often far from the town service members are returning to. This geographic limitation makes it harder to tailor the program based on the local labor markets.

At the same time, studies on the effects of veteran status on civilian labor market outcomes rarely focus on geographic variations. Most studies use

1 A few examples include the Veteran Retraining Assistance Program (VRAP) for veterans ineligible for the GI Bill, Local Veteran Employment Representatives (LVER) that assists veterans’ job search, and the Veterans Workforce Investment Program (VWIP), Veterans Opportunity to Work (VOW) to Hire Heroes Act of 2011, and Work Opportunity Tax Credit (WOTC) for employers who hire veterans (Collins et al. 2012; U.S. Department of Veteran Affairs 2018). In addition, the military initiated Training Assistant Program (TAP), replaced later with Transition Goals Plans Success (Transition GPS), mandatory for almost all existing service members. 2 https://www.umass.edu/employmentequity/diversity-analytics

national level data from the monthly Current Population Survey (CPS) (e.g. Collins et al. 2012; Kleykamp 2013), from the annual American Community Survey (ACS) (e.g. Heaton and Krull 2012; Schulker 2017), or both (e.g. Loughran 2014). Although these data sources have available geographic information, studies rarely examine locational variations.

However, a rich literature exists on how local labor markets operate in different local contexts including laws, policies, institutions, and the demographic compositions of race and gender (e.g. Cohen and Huffman 2003; Sutton, Bosky and Muller 2016). For this reason, recent policies and programs increasingly stress the association of local contexts to labor market outcomes expecting that localized policy interventions will produce more effective outcomes than global policy interventions. For example, the Opportunity Atlas project maps which neighborhoods intergenerational social mobility is strong and weak based on the children’s family socio-economic status and other demographics, like race (Chetty et al. 2018). The Center for Employment Equity at the University of Massachusetts calculates race/gender demographic compositions in large private sector firms in each industry/occupational group, and by states and cities in order to identify where minorities fare better and worse in accessing good jobs.2

It is important to understand the labor market profiles of veterans in Illinois and the obstacles they encounter in the state labor market. The analysis requires looking beyond national level analysis. However, only in rare cases have veterans’ labor market profiles been examined at

Illinois Veterans Employment and Earnings Profiles 3 the local level (e.g. Castro, Kintzle, and Hassan, 2014; Farmer et al. 2017).

In this study, by the Project for Middle Class Renewal at the University of Illinois Urbana-Champaign, I examine the labor market profiles of veterans in Illinois and compare the results with national level results from earlier studies. More specifically, the report will answer the following research questions: (1) Do veterans in Illinois have more difficulty in finding a job than nonveterans? (2) Which veterans struggle most with unemployment? (3) What occupations employ veterans in Illinois? (4) What occupations and industries do veterans earn more or less than comparable nonveterans?

In brief, the report finds that the occupations that produce varying wage levels for veterans in Illinois are not necessarily the same as in other states. Policies that are meant to improve employment outcomes from Illinois veterans must be sensitive to local labor market conditions. To close the gap between military job skills and the skills required for the civilian labor market, policymakers need to develop targeted pathways between the two.

The U.S. Department of Veterans Affairs (VA) estimates that Illinois’ veteran populations is the 10th largest in the nation (U.S. Department of Veterans Affairs 2016).3 Recently, the Army announced a plan to expand their recruitment targeting 22 cities including Chicago, San Francisco, and Seattle (New York Times 2018). This suggests that more veterans will come back to Illinois in a few years if such recruitment in Chicago is successful. Thus, more precisely understanding the labor market status of veterans in Illinois will provide lawmakers with better grounds for localized and tailored labor market policies.

3 California, Texas, Florida, Pennsylvania, New York, Ohio, North Carolina, Virginia, and Georgia are the other 9 states with largest veteran population.

2. PRIOR RESEARCH

2.1. Employment and Unemployment

The high unemployment rates among the young post-9/11 era veterans in the early 2010s fueled concerns over the economic well-being of veterans. However, relatively little research has been conducted on the economic reintegration into civilian life of ex-service members (Kleykamp 2013). Official labor statistics from the Bureau of Labor Statistics (BLS) show that post-9/11 veterans struggle more with finding employment than nonveterans. According to the BLS (2012), the 2011 unemployment rate among post-9/11 veterans was 9.9%, while it was 7.9% among nonveterans. The difference in unemployment rates between the two groups was highest among 18 to 24 years old with 30.2% and 16.1% for post-9/11 veterans and nonveterans respectively. According to the most recent available data the difference declined in 2017 (Bureau of Labor Statistics 2018). While the unemployment rates of veterans and nonveterans by states are published periodically by the BLS no further disaggregated information by demographics like age, race, education is provided for each state.

These observed differences in unemployment rates between veterans and nonveterans are not necessarily the effect of veteran status. The demographics of service members (e.g., age, education, gender, race, and marital status) may differ from nonveterans because military service itself is the outcome of both self-selection and screening from the military (Kleykamp 2013). Studies using multivariate analyses controlling for these characteristics show mixed results on the effect of veteran status on unemployment. Analyzing the 2010 American Community Survey data, Heaton and Krull (2012) find that the

Illinois Veterans Employment and Earnings Profiles 4 unemployment rates among post-9/11 veterans are similar to the civilians once adjusting for demographics. On the other hand, Kleykamp (2013), using the merged outgoing rotation group (MORG) series of the Current Population Survey from 2005 to 2011, finds that post-9/11veterans have 50% to 65% higher odds of unemployment than nonveterans, controlling for major demographics and education. Studies may find mixed results because they rely on different datasets (ACS vs. CPS) covering different years (2010 vs. 2005-2011) and apply different statistical methodologies (adjusted matching vs. logistic regression).

Why unemployment rates are higher for veterans than nonveterans is likely caused by multiple factors. Heaton et al. (2018) argue that it is because the job search dynamics and strategies are different for the two groups. Comparing recipients of the Unemployment Compensation for Ex–Service Members (UCX) and those of the equivalent civilian Unemployment Insurance (UI) program, the authors find that UCX recipients wait a longer time until they apply for unemployment benefits than UI recipients do. In other words, ex-service members often stay unemployed longer than civilian UI recipients without getting unemployment benefits. Loughran (2014) attributes the higher unemployment rates of veterans to their more recent separation from their previous job (i.e., military service) compared to nonveterans separated from their civilian jobs.

These studies refute the commonly referred explanations for unemployment, like veterans’ poorer health conditions, self-selection, employer discrimination against veterans, and skills mismatch between ex-service members’ military skills and civilian jobs. Nonetheless, Heaton et al.’s (2018) finding that veterans are more willing to accept lower wages and more likely to be enrolled in vocational or job training than nonveterans suggests that a skill mismatch and/or employer discrimination may be a source of high unemployment rates among veterans. In an audit of veterans’ entry-level job applications, Kleykamp (2009) found that black veterans with

administrative military occupations had a higher callback rate for a job interview relative to black nonveterans. However, callback rates are not different among whites and Hispanics regardless of military occupations and among black non-administrative veterans from combat units. This suggests that, at least for black ex-service men and women, the kinds of civilian-transferable skills they posses influences the probability of employment.

The risk of unemployment among veterans varies by educational level. In 2017, unemployment rates of post-9/11 veterans were 5.9%, 5.1%, and 2.5% for high school graduates, some college or associate degree, and bachelor’s degree and higher respectively (Bureau of Labor Statistics 2018). This shows that veterans with higher educational attainment have lower unemployment rates than less-educated veterans. However, Kleykamp (2013) shows that the differences in unemployment risks by educational attainment for veterans are not statistically significant when controlled for demographics.

2.2. Earnings

Two different theories lead to contradictory hypotheses regarding veterans’ status in the civilian labor market. One approach predicts that veterans will receive a premium in the civilian labor market. De Tray (1982), for example, conceptualized that military service signals to potential employers that veterans are more productive than nonveterans. They argue that veterans are highly motivated as to self-select into the military and that passing military screening is evidence of both physical and mental ability. On the other hand, another approach posits that veterans will face a penalty. Civilians hold certain stereotypes about combat-exposed veterans, including that they struggle with physical and psychological problems like disabilities or PTSD (McLean and Kleykamp 2014). In addition, some employers may expect that military service is the

Illinois Veterans Employment and Earnings Profiles 5 outcome of negative selection if the military is considered as an employer of last resort.

While studies show mixed results of the effects of military service on labor market outcomes for prior-9/11 era veterans, recent studies on post-9/11 veterans mostly find that military service positively influences veterans’ earnings, at least for minorities (Brown and Routon 2016; Kleykamp 2013; Routon 2014). Kleykamp (2013), for example, shows that veterans, on average, earn about a 5% to 10% higher hourly wage.

However, not all post-9/11 veterans enjoy the same level of earnings premium. Veterans’ earnings premium is lower for those veterans with some college education and with a bachelor’s degree relative to veterans with a high school diploma or with less than a high school diploma. This results in a veteran-nonveteran hourly wage difference as small as 1 cent for college graduates (Kleykamp 2013). These results suggest that less educated veterans benefit most from military service.4 Similarly, among veterans who served in the 21th century, Brown and Routon (2016) find that veteran wage premiums are limited to those at the lower wage distributions (below median wage) whereas veterans at the upper wage distributions face wage penalties. In sum, considering that earnings are closely associated with educational attainment, these findings suggest that less-educated and less-skilled veterans benefit more from military service while more educated and skilled veterans either face a wage penalty or no premium from military service.

Occupation and industry also influence whether veterans have a wage premium or a penalty. Schulker (2017) finds that veterans earn more 4 Veterans with less than a high school diploma are found to earn $2.61 more in hourly wages than nonveterans but the difference is not statistically significant. 5 ACS is an annual survey of approximately 3,500,000 households while CPS is a monthly survey of approximately 60,000 households.

than comparable nonveterans in the civilian occupations and industries that overlap with the military occupations they held. This suggests that veterans can garner premiums in the occupations/industries into which veterans can transfer their skills achieved from military service. Likewise, many veteran employment policies address which civilian occupations best match veterans’ military skills. For example, RAND developed “crosswalks” between the Military Occupational Specialty (MOS) code and civilian occupations to enhance veterans’ understanding of skills that employers want and employers’ understanding of skills that veterans posses (Wenger et al. 2017).

The following section explains the data and methodology used for the analysis. The report then explores the employment and earnings profiles of veterans in Illinois, followed by a comparison to national level analyses. Finally, a brief conclusion offers policy suggestions for improving the employment effects of veterans’ programs.

3. DATA AND METHOD

In order to capture labor market profiles of veterans in Illinois, data from the American Community Survey (ACS) is examined. Additionally, the U.S. Bureau of Labor Statistics periodically publishes reports on the status of veterans using the estimates from the Current Population Survey (CPS). However, when studying the veteran population ACS data has multiple advantages over CPS data. The ACS sample size is larger than CPS.5 Including a larger number of veterans in the sample is critical because the veteran population is about 8% of total population. But importantly, post-9/11 era veterans are only about 1.7% of the U.S.

Illinois Veterans Employment and Earnings Profiles 6 population. Therefore, to be able to break down the veteran population by state, occupation, industry, gender, and educational level requires a much larger sample size.

In this study, a 5-year cumulative dataset compiled by the ACS administration from the annual surveys between 2013 and 2017 is used to produce more accurate estimations from a larger sample size. In addition, because this report captures the recent status of veterans in Illinois rather than the trends over time, the 5-year estimates are less sensitive to yearly fluctuations. All the analyses are adjusted by sampling weights. The analysis was limited to the surveys from Illinois.

Employment status, labor force participation rates, employment population ratios, and unemployment rates are calculated for nonveterans and veterans of all eras (by post-9/11 and pre-9/11) by sex. I then provide the results of logistic regressions in the form of odds ratios controlling for demographics and by educational level for men and women.

For the occupational distributions and the earnings by occupation/industry, the veteran sample is limited to post-9/11 era male veterans employed in paid work. Prior research indicates that earnings and unemployment rates of pre-9/11 veterans become similar to nonveterans as they spend more time in the civilian labor market (Loughran 2014). In addition, a majority (80%) of the post-9/11 veterans in Illinois are men. For the analysis of the effect of veteran status on annual income and hourly wage, results from Ordinary Least Square (OLS) regressions are provided by educational level, controlling for demographics. Then, for each occupational and industry group, the coefficients of veteran status from OLS regression are provided with predicted hourly wages for post-9/11 veterans and nonveterans.

4. ANALYSES

4.1. Employment and Unemployment

The Illinois employment status of the civilian noninstitutional population, 18 years old and over, by veteran status, period of service, and sex is summarized in Table 1. Illinois veterans of all-eras constitute 6.7% of the state’s total population; slightly less than 8.3% at the national level (U.S. Bureau of Labor Statistics 2018). Men comprise 93.1% of all veterans and 80% of the post-9/11 veterans, slightly less than the national level (i.e., 82.6%). The post-9/11 veteran proportion of total population is 1.0%, smaller than the national proportion of 1.7%.

While the nonveteran labor force participation rate is 67.5%, the total veterans’ labor participation rate is much smaller at 43.9%. Such a small labor force participation rate is primarily because veterans are mostly from old wars and have likely retired. At 7.3% the veterans’ unemployment rate is slightly smaller than that of nonveterans (8.2%). However, when the sample is limited to post-9/11 veterans, their unemployment rate (9.8%) is higher than nonveterans (8.2%) by 1.6 percent point. Conversely, labor force participation rates of post-9/11 veterans (69.2%) are higher than nonveterans (67.5%). There’re also gender differences. Male post-9/11 veterans’ labor force participation rate (71.3%) is significantly higher than female veterans (59.1%). However, unemployment rates for male and female post-9/11 veterans are similar at 9.9% and 9.5% respectively. In sum, among post-9/11 veterans, more men actively seek employment than women, but men and women successfully find a job at similar rates.

However, the observed differences in unemployment rates and labor force participation rates between post-9/11 veterans and nonveterans do not account for demographic differences. Once controlling for education, race compositions, and age, it appears that post-9/11 veterans are not unemployed at a higher rate than nonveterans.

Illinois Veterans Employment and Earnings Profiles 7

Veteran status and period of service Total Men Women TOTAL VETERANS

Civilian noninstitutional population 631,029 587,241 43,788 Percent of total population 6.7 6.2 0.5 Civilian labor force 276,933 252,403 24,530 Participation rate 43.9 43.0 56.0 Employed 256,589 234,088 22,501 Employment-population ratio 40.7 39.9 51.4 Unemployed 20,344 18,315 2,029 Unemployment rate 7.3 7.3 8.3

Post-9/11 Veterans Civilian noninstitutional population 89,998 74,811 15,187 Percent of total population 1.0 0.8 0.2 Civilian labor force 62,296 53,319 8,977 Participation rate 69.2 71.3 59.1 Employed 56,177 48,057 8,120 Employment-population ratio 62.4 64.2 53.5 Unemployed 6,119 5,262 857 Unemployment rate 9.8 9.9 9.5

Pre-9/11 Veterans Civilian noninstitutional population 541,031 512,430 28,601 Percent of total population 5.7 5.4 0.3 Civilian labor force 214,637 199,084 15,553 Participation rate 39.7 38.9 54.4 Employed 200,412 186,031 14,381 Employment-population ratio 37.0 36.3 50.3 Unemployed 14,225 13,053 1,172 Unemployment rate 6.6 6.6 7.5

NONVETERANS Civilian noninstitutional population 8,806,886 3,954,866 4,852,020 Percent of total population 93.3 41.9 51.4 Civilian labor force 5,941,995 2,985,359 2,956,636 Participation rate 67.5 75.5 60.9 Employed 5,456,345 2,730,235 2,726,110 Employment-population ratio 62.0 69.0 56.2 Unemployed 485,650 255,124 230,526 Unemployment rate 8.2 8.5 7.8

Table 1. Illinois Employment Status of the Civilian Non-institutional Population 18 Years Old and Over by Veteran Status, Period of Service, and Sex, 2013-2017 (averages)

Illinois Veterans Employment and Earnings Profiles 8 Figure 1 depicts veteran’s odds ratios 6 (compared to nonveterans) of unemployment from logistic regressions controlling for demographics. While male veterans of all eras have 15% higher odds of unemployment than male nonveterans, the statistically different odds ratios of unemployment are found only among pre-9/11 male veterans.

Nonetheless, the risk of unemployment may not be distributed uniformly across veterans with different educational attainment. One way of examining it is to break down the sample into subsamples by educational attainment and run a logistic regression separately. Figure 2 summarizes male and female post-9/11 veterans’ odds ratios of unemployment relative to nonveterans by educational attainment. It shows that male and female veterans with a bachelor’s degree and male veterans with an advanced degree have 92%, 147%, and 112% higher odds of unemployment respectively than nonveteran

6 “Odds ratio” represents the odds that an outcome (i.e., unemployment) will occur between two groups (i.e., veterans and nonveterans) given that other conditions are the same.

counterparts. In other words, veterans with higher education are likely to have difficulties in finding a job while no meaningful difference was found among veterans with less than a college degree except female veterans with a General Educational Development (GED) certificate.

Also, once veterans get a job they are more likely to work full-time than comparable nonveterans. Figure 3 summarizes post-9/11 veterans’ odds ratios of working fulltime, defined as usually working 35 hours or more per week, by sex and educational attainment. It shows that male veterans are more likely to work fulltime than nonveteran counterparts controlling for age and race in all educational levels except veterans with a GED. The odds ratios for veterans with a bachelor’s degree is not statistically significant, which suggests that both veterans and nonveterans with a bachelor’s degree are likely to work fulltime.

1.15*1.11

1.16**1.18

0.98

1.34

0.80

0.90

1.00

1.10

1.20

1.30

1.40

Veterans-All Era Post-9/11 Veterans Pre-9/11 Veterans

Men Women

Figure 1: Post-9/11 Illinois Veterans' Odds

*** p<.001, ** p<.01, * p<.05, ‡ p<.10

Illinois Veterans Employment and Earnings Profiles 9

For veterans with some high school but no diploma (the proportion of this group is quite small because about 90% of recruits since 1990s have a high school diploma), their odds of working fulltime are 310% higher than nonveteran high school dropouts. On the other hand, female veterans’ odd ratios of fulltime employment are smaller than nonveterans in all

educational level except for veterans with less than a high school diploma.

Table 2 summarizes the percent distribution of employed male veterans and nonveterans in Illinois and across states by occupation, veteran status, and period of service. In Illinois, relative to nonveterans, a higher proportion of veterans work in Management , Bus iness , and Financial

0.49

0.98

1.17 1.01 1.01

0.70

1.92** 2.12*

1.37

0.05*

1.03

1.00

2.47*

0.74

-

0.50

1.00

1.50

2.00

2.50

Men Women

Figure 3: Post-9/11 Illinois Veterans' Odds Ratios of Unemployment to Nonveterans by Educational Attainment and Sex

*** p<.001, ** p<.01, * p<.05, ‡ p<.10

1.0

4.1**

2.2***

0.7

2.9***

1.5*

1.4

2.0*

0.7

2.7

0.4

0.2

0.3

0.3

0.3

0.7

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5

Middle School or less

Some HS, no diploma

HS diploma

GED or alt credential

Some college, no degr

Associate's degree

Bachelor's Degree

Advanced Degree WomenMen

Figure 2: Post-9/11 Illinois Veterans' Odds Ratios of Fulltime Employment Status to Nonveterans by Educational Attainment and Sex

*** p<.001, ** p<.01, * p<.05, ‡ p<.10

Illinois Veterans Employment and Earnings Profiles 10

Operations occupations (16.8% vs. 14.7%); Professional and related occupations (19.8% vs. 18.0%); Office and Administrative Support occupations (9.1% vs.7.7%); and Installation, Maintenance, and Repair occupations (9.2% vs. 5.2%). On the other hand, a smaller proportion of veterans work in Service occupations (12.7% vs. 13.9%); Sales and related occupations (5.4% vs. 10.2%); and in Transportation and Material Moving occupations (10.7% vs. 12.0%).

Relative to the national average, a higher proportion of Illinois veterans work in Office and Administrative Support occupations (9.1% vs. 7.4%), Production occupations (9.0% vs. 6.1%), and Transportation and Material Moving occupations (10.7% vs. 8.8%). Fewer state veterans are employed in Service occupations (12.7% vs. 15.7%), and Sales and related occupations (5.4% vs. 7.4%).

4.2. Earnings (Post-9/11 Male Veterans)

Veterans in Illinois experience annual earnings penalties across all educational levels except those without a high school diploma and with some college credits but without a degree. However, the penalties and premiums are not statistically significant except for veterans with an advanced degree and with some college education. Table 3 summarizes veteran status’ effects on annual income and hourly wage controlling for age, race, industry and occupation. Veterans with some college education on average earn $2,128 more per year than their nonveteran counterparts, while veterans with an advanced degree earn $11,812 less than comparable nonveterans per year.

However, Illinois veterans are more likely to work fulltime and work more hours than nonveterans as shown above. Thus, it is necessary to examine hourly wages as well. Hourly wage is calculated

Occupation Non-veterans Post-9/11 Veterans Pre-9/11 Veterans

Illinois National* Illinois National* Illinois Total employed 2,893,625 71,907,000 56,230 2,698,000 93,006 As a percent of total employed Total employed 100.0 100.0 100.0 100.0 100.0 Management, business, and financial operations occupations 14.7 17.4 16.8 17.3 15.3

Professional and related occupations 18.0 18.9 19.8 20.0 16.2 Service occupations 13.9 14.0 12.7 15.7 11.1 Sales and related occupations 10.2 9.9 5.4 7.4 8.3 Office and administrative support occupations 7.7 6.0 9.1 7.4 7.6

Farming, fishing, and forestry occupations 0.6 1.1 0.2 0.4 0.6

Construction and extraction occupations 8.1 9.9 7.1 6.6 7.3

Installation, maintenance, and repair occupations 5.2 7.7 9.2 10.2 7.1

Production occupations 9.6 7.5 9.0 6.1 9.0 Transportation and material moving occupations 12.0 9.4 10.7 8.8 17.4

Table 2: Percent Distribution of Employed Male Veterans and Nonveterans by Occupation, Veteran Status, and Period of Service, 2013-2017

* 2017 national annual averages (Bureau of Labor Statistics 2018, Table 4)

Illinois Veterans Employment and Earnings Profiles 11

by dividing annual income by usual hours worked per week and weeks worked last year. It appears that veterans with a high school diploma face a wage penalty, earning $2.1 less per hour than comparable nonveterans. Considering that about 90% of military recruits since 1990s have a high school diploma, it implies that the majority of veterans in Illinois may experience a wage penalty.

The wage penalties and premiums are likely unevenly distributed across occupations and industries. Skill transferability can influence employees’ performance resulting in veterans’ earnings penalties or premiums by occupations. Table 4 summarizes post-9/11 male veterans’ status in each occupation controlling for age, educational attainment, race, industry, and the predicted hourly wages of both non-veterans and post-9/11 veterans.

Twenty-five occupational groups are listed in order from the largest wage penalties to the largest premiums for veterans.7 It shows that veterans in Arts, Design, Entertainment, Sports, and Media Occupations face the largest wage penalty of 7 Detailed occupations are grouped into 25 broader occupational groups based on the IPUMS ACS occupational codes (https://usa.ipums.org/usa/volii/c2ssoccup.shtml) 8 The difference is statistically significant at p<.05 and robust even when additionally controlling for industry. 9 The difference stays robust when controlling for industry. 10 These are not statistically significant or only marginally significant at p<.10, with additional controls for industry.

$4.73 per hour relative to comparable nonveterans.8 In these occupations, veterans on average earn $22.4 per hour while nonveterans earn $27.1. Similar penalties ($4.67) are found among veterans working in Management, Business, Science, and Arts Occupations.9 On average, in these occupations veterans earn $36.7 per hour while nonveterans earn $41.4 per hour. In Business Operations Specialists, Computer and Mathematical Occupations, and Sales and Related Occupations robust veteran wage penalties are observed. Veterans working in Military Specific Occupations, Extraction, Legal Occupations, Farming, Fishing, and Forestry Occupations, Healthcare Practitioners and Technical Occupations, Construction and Extraction Occupations, and Food Preparation and Serving Occupations appear to suffer varying amounts of wage penalties.10

On the other hand, veterans earn more in Transportation and Material Moving Occupations, Production Occupations, Protective Service Occupations, and Education, Training, and Library Occupations. The premiums range from $1.91 to $4.06 per hour. However, the

Educational attainment Annual Income S.E. Hourly Wage S.E. Middle School or less -4,235 5,106 -2.1 2.4 Some HS, no diploma 5,942 4,944 1.9 2.1

HS diploma -2,726 1,989 -2.1** 0.8 GED or alt credential -2,393 4,093 0.3 1.7

Some college, no degree 2,128‡ 1,173 0.4 0.6 Associate's degree -1,756 1,974 -1.0 0.9 Bachelor's Degree -3,669 3,011 -0.8 1.4 Advanced Degree -11,812* 4,639 -1.9 1.4

Table 3: Coefficients of Post-9/11 Illinois Veterans from OLS Regressions on Annual Income and Hourly Wage (in 2016 $) by Educational Attainment for Men.

*** p<.001, ** p<.01, * p<.05, ‡ p<.10

Illinois Veterans Employment and Earnings Profiles 12

difference is statistically significant only in Transportation and Material Moving Occupations.

It is noteworthy that veteran penalties are found mostly in relatively high-paying occupations while premiums are mostly in relatively low-paying occupations.11 While the occupations where veterans have wage premiums do not

11 Hourly wages for veterans in occupations where veteran wage penalties are observed are as follows: Management, Business, Science, and Arts Occupations ($36.7), Business Operations Specialists ($32.7), Computer and Mathematical Occupations ($35.1), and in Sales and Related Occupations ($24.2). Hourly wages for veterans in occupations where veteran wage premiums are observed are as follows: Transportation, and Material Moving Occupations ($20.5), Production Occupations ($22.2), and in Protective Service Occupations ($22.6).

necessarily require college education those where veterans have wage penalties often require a college degree or higher. This suggests that veterans with higher educational attainment are more likely to face wage penalties. It is consistent with the finding in Table 3 above, which shows that veterans with associate degrees, bachelor’s degrees, and advanced degrees face earnings

Occupations Veteran Status Effect Predicted Mean Hourly Wage ($)

Coefficient

S.E. Ind. Cont-rolled

Non-veterans

Post-9/11 veterans

Arts, Design, Entertainment, Sports, and Media Occupations -4.73* 2.38 * 27.1 22.4 Management, Business, Science, and Arts Occupations -4.67** 1.37 * 41.4 36.7 Military Specific Occupations -4.30 4.40 21.2 16.9 Business Operations Specialists -3.78* 1.79 ‡ 36.4 32.7 Extraction Workers -3.55‡ 2.12 22.5 19.0 Legal Occupations -3.51 4.78 56.5 53.0 Computer and Mathematical Occupations -3.40* 1.47 * 38.5 35.1 Sales and Related Occupations -2.98* 1.19 * 27.1 24.2 Farming, Fishing, and Forestry Occupations -2.38 2.65 15.1 12.8 Healthcare Practitioners and Technical Occupations -2.37 2.06 45.6 43.2 Construction and Extraction Occupations -0.79 1.47 26.4 25.6 Food Preparation and Serving Occupations -0.02 1.17 12.3 12.2 Healthcare Support Occupations 0.17 2.99 16.7 16.9 Building and Grounds Cleaning and Maintenance Occupations 1.25 1.62 15.5 16.8

Installation, Maintenance, and Repair Workers 1.34 1.05 23.1 24.5 Office and Administrative Support Occupations 1.58 1.16 19.3 20.9 Life, Physical, and Social Science Occupations 1.79 2.06 31.8 33.6 Transportation and Material Moving Occupations 1.91* 0.86 ‡ 18.6 20.5 Personal Care and Service Occupations 1.93 3.11 14.8 16.7 Production Occupations 2.18‡ 1.28 20.0 22.2 Financial Specialists 3.12 4.45 39.7 42.8 Community and Social Services Occupations 3.31 4.12 22.2 25.5 Protective Service Occupations 3.53‡ 1.94 19.1 22.6 Education, Training, and Library Occupations 4.06‡ 2.09 28.5 32.6 Architecture and Engineering Occupations 4.89 4.47 36.7 41.6

Table 4: Coefficients of Post-9/11 Illinois Veterans from OLS Regressions on Hourly Wage (in 2016 $) by 25 Occupational Groups and Predicted Mean Hourly Wages for Nonveterans and Post-9/11 Veterans.

*** p<.001, ** p<.01, * p<.05, ‡ p<.10

Illinois Veterans Employment and Earnings Profiles 13 penalties in terms of annual income and hourly wage.12

Table 4 identifies in which occupations penalties and premiums are found. At the national level, post-9/11 veterans enjoy annual income premiums compared to nonveterans in the following occupations: Building/grounds and maintenance, Education/training/library, Health support Life/physical/social science, Office

12 Penalties in annual income are statistically significant only for veterans with advanced degrees.

administration/support, Production, Protective service, and Transportation occupations (Schulker 2018). Among these occupations, however, only in Transportation and Material Moving Occupations do post-9/11 veterans earn higher hourly wages than comparable nonveterans in Illinois.

On the other hand, post-9/11 male Illinois veterans earn lower hourly wages than

NAICS Veteran Status Effect Predicted Mean Hourly Wage ($)

Coefficient S.E Occ. Cont-rolled

Non veterans

Post-9/11 veterans

11. Agriculture, Forestry, Fishing and Hunting (not covered in economic census) -6.82** 2.01 *** 19.0 12.2 21. Mining, Quarrying, and Oil and Gas Extraction -0.40 1.86 26.4 26.0 22. Utilities 6.29* 2.61 ** 35.8 42.1 23. Construction -0.86 1.38 27.1 26.3 31. Manufacturing-Foods, Textiles 3.06 3.86 23.5 26.5 32. Manufacturing-Wood, Chemical, Nonmetallic -3.04* 1.54 * 28.3 25.3 33. Manufacturing- Metallic, Equipment -1.57 1.21 28.2 26.7 42. Wholesale Trade -6.65** 2.05 ** 28.7 22.1 44. Retail Trade-Motor vehicle, appliances, clothing -1.37 1.06 19.8 18.4 45. Retail Trade-Sporting goods, general merchandise 0.28 2.19 18.4 18.7 48. Transportation and Warehousing-Transportation of all kinds 1.87 1.32 24.0 25.9 49. Transportation and Warehousing-Postal, Warehousing -1.49 1.20 21.2 19.8 51. Information -2.97 3.19 31.9 28.9 52. Finance and Insurance -5.09 3.41 ‡ 42.1 37.0 53. Real Estate and Rental and Leasing -1.99 3.37 29.4 27.4 54. Professional, Scientific, and Technical Services 1.28 2.82 41.3 42.6 55. Management of Companies and Enterprises -4.06 11.93 45.5 41.4 56. Administrative and Support and Waste Management and Remediation Services -1.43 1.30 19.5 18.0 61. Educational Services 1.13 1.50 26.4 27.5 62. Health Care and Social Assistance -1.07 1.48 * 31.7 30.7 71. Arts, Entertainment, and Recreation -0.13 1.97 18.2 18.1 72. Accommodation and Food Services 1.10 1.43 13.9 15.0 81. Other Services (except Public Administration) -0.30 1.25 20.6 20.3 92. Public Administration (not covered in economic census) -2.46* 1.01 29.4 27.0

Table 5: Coefficients of Post-9/11 Illinois Veterans from OLS Regressions on Hourly Wage (in 2016 $) by NAICS and Predicted Mean Hourly Wages for Nonveterans and Post-9/11 Veterans.

*** p<.001, ** p<.01, * p<.05, ‡ p<.10

Illinois Veterans Employment and Earnings Profiles 14 nonveterans in a number of areas, including Arts, Design, Entertainment, Sports, and Media Occupations, Management, Business, Science, and Arts Occupations, Business Operations Specialists, Extraction Workers, Computer and Mathematical Occupations, and in Sales and Related Occupations. Interestingly, at the national level, post-9/11 veterans face annual income penalties in legal, personal care/service, and sales occupations. The differences suggest that post- 9/11 veterans may face varying earnings premiums and penalties in different occupations by local labor markets.

We can also identify the industries that veterans earn higher or lower wages than comparable nonveterans. Table 5 summarizes post-9/11 veteran effects on hourly wages in each industry (2-digit NAICS: North American Industry Classification System) controlling for age, educational attainment, race, occupation and the predicted hourly wages of non-veterans. Only in the Utilities industry do veterans earn more than nonveterans (by $6.29 per hour). While in Manufacturing (Foods, Textiles) and Transportation and Warehousing (Transportation of all kinds) industries, veterans on average have higher wages than nonveterans, the differences are not statistically significant. On the other hand, in Agriculture, Forestry, Fishing and Hunting (not covered in economic census), Manufacturing-Wood, Chemical, Nonmetallic Wholesale Trade industries, veterans earn less than nonveterans even when controlling for occupation.

5. CONCLUSION AND POLICY SUGGESTIONS

Currently around 631,029 veterans reside in Illinois. Approximately 90,000 of them are post-9/11 veterans who are at higher risks of unemployment than nonveterans. However, post-9/11 veterans in Illinois, on average, are not at higher risks of unemployment when accounting for demographic differences. Nonetheless, it appears that post-9/11 veterans with a bachelor’s degree or an advanced degree struggle in finding

employment more than nonveteran peers with the same educational attainment.

Although employed post-9/11 male veterans of almost all educational attainments are more likely to work fulltime than nonveterans, the differences in unemployment risk by educational attainment suggest that future employment policies should target veterans with college educations. The average annual income penalty of $11,812 among veterans with an advanced degree also shows that this group is disadvantaged even after finding a job in the civilian labor market. As current policies for veterans’ transition to civilian life mostly focus on service members with a high school diploma - the majority of recruits - the findings suggest that these policies should also pay attention to service members with higher education.

Post-9/11 male veterans in Illinois appear to have experienced wage penalties in many occupations. Veterans working in Arts, Design, Entertainment, Sports, and Media Occupations, Management, Business, Science, and Arts Occupations, Business Operations Specialists, Computer and Mathematical Occupations, and Sales and Related Occupations fare worse than nonveterans. These occupations are mostly high paying jobs. Thus future veteran policies should examine the causes of wage penalties in these occupations and address how to improve veterans’ earnings.

A major finding of this study is that the occupations that produce better or worse wages for veterans in Illinois are not necessarily the same as in other states. Therefore, it is important to take the local labor market context into account when developing policies. To close the gap between military job skills and the skills required for the civilian labor market, policymakers need to develop better crosswalks between the two. Wenger et al. (2017), for example, developed a crosswalk between the U.S. Army MOS (Military Occupational Specialty) code and civilian occupations using distance metrics based on surveys on six domains including knowledge, skills, abilities, work activities, work contexts, and work styles. While the process incorporates

Illinois Veterans Employment and Earnings Profiles 15 earnings into the metric, a more contextualized plan would tailor such crosswalks based on veteran earnings premiums and penalties in the local labor markets.

This study primarily focuses on post-9/11 male veterans in Illinois. Nonetheless, as an increasing number of women are serving in the military (about 15% of current recruits) the number of female veterans will increase in the future. Thus, a better understanding of female veterans’ earnings and employment profiles will help develop gender specific policies. In addition, it would be advisable to examine how marital status, number of children at home, citizenship, and other unobserved characteristics, like motivation may influence the labor market outcomes of veterans.

Illinois Veterans Employment and Earnings Profiles 16

References

Brown, Christian and P. Wesley Routon. (2016). “Military Service and the Civilian Labor Force: Time- and Income-Based Evidence.” Armed Forces & Society, 42(3):562-584.

Bureau of Labor Statistics. (2012). “Employment Situation of Veterans – 2011.” US Department of Labor, Washington, DC.

Bureau of Labor Statistics. (2018). “Employment Situation of Veterans – 2017.” US Department of Labor, Washington, DC.

Castro, Carl Andrew, Sara Kintzle, and Anthony Hassan. (2014). “The State of the American Veteran: The Los Angeles County Veterans Study.” USC School of Social Work Center for Innovation and Research on Veteran and Military Families.

Chetty, Raj, John N. Friedman, Nathaniel Hendren, Maggie R. Jones, and Sonya R. Porter. (2018). “The Opportunity Atlas: Mapping the Childhood Roots of Social Mobility.” NBER Working Paper No. 25147.

Cohen, Philip N. and Matt L. Huffman. (2003). “Occupational Segregation and the Devaluation of Women's Work across U.S. Labor Markets." Social Forces, 81(3):881-908.

Collins, Benjamin, David H. Bradley, Cassandria Dortch, Lawrence Kapp, Christine Scott. 2012. “Employment for Veterans: Trends and Programs.” Congressional Research Service.

Farmer, Carrie M., Terri Tanielian, Shira H. Fischer, Erin L. Duffy, Stephanie Dellva, Emily Butcher, Kristine Brown, Emily Hoch. (2017). “Supporting Those Who Served in Massachusetts: Needs, Well-Being, and Available Resources for Veterans.” RAND Corporation Research Brief.

Heaton, Paul and Heather Krull. (2012). “Unemployment Among Post-9/11 Veterans and Military Spouses After the Economic Downturn” RAND Occasional Paper.

Heaton, Paul, Diana Catherine Lavery, David Powell, and Jeffrey B. Wenger. (2018). “Comparing Ex-Servicemember and Civilian Use of Unemployment Insurance.” RAND Corporation.

Keeling, Mary, Sara Kintzle and Carl A. Castro. (2018). “Exploring U.S. Veterans’ post-service employment experiences.” Military Psychology 30(1):63-69, DOI: 10.1080/08995605.2017.1420976

Kleykamp, Meredith. (2009). “A Great Place to Start? The Effect of Prior Military Service on Hiring.” Armed Forces & Society, 35(2):266-285

Kleykamp, Meredith. (2013). “Unemployment, earnings and enrollment among post 9/11 veterans.” Social Science Research, 42:836–851.

Loughran, David S. (2014). “Why Is Veteran Unemployment So High?” RAND National Defense Research Institute.

MacLean, Alair and Meredith Kleykamp. (2014). “Coming Home: Attitudes toward U.S. Veterans Returning from Iraq.” Social Problems 61(1):131–154.

Illinois Veterans Employment and Earnings Profiles 17 New York Times. (2018). “The Army, in Need of Recruits, Turns Focus to Liberal-Leaning Cities.”

Retrieved 1/2/2018 from https://www.nytimes.com/2019/01/02/us/army-recruiting-tech-industry-seattle.html

Prudential. (2012). “Veterans’ employment Challenges: Perceptions and experiences of transitioning from military to civilian life.”

Routon, Wesley. (2014). “The effect of 21st century military service on civilian labor and educational outcomes.” Journal of Labor Research, 35:5–38.

Schulker, David. (2017). “The Recent Occupation and Industry Employment Patterns of American Veterans.” Armed Forces & Society, 43(4):695-710.

Sutton, April, Amanda Bosky and Chandra Muller. (2016). “Manufacturing Gender Inequality in the New Economy: High School Training for Work in Blue-Collar Communities.” American Sociological Review 81(4):720–748.

U.S. Department of Veterans Affairs. (2016). “Veteran Population Projections 2017-2037.” Retrieved 1/2/2018 from https://www.va.gov/vetdata/docs/Demographics/New_Vetpop_Model/Vetpop_Infographic_Final31.pdf

Wenger, Jeffrey B., Ellen M. Pint, Tepring Piquado, Michael G. Shanley, Trinidad Beleche, Melissa A. Bradley, Jonathan Welch, Laura Werber, Cate Yoon, Eric J. Duckworth, and Nicole H. Curtis. (2017). “Helping Soldiers Leverage Army Knowledge, Skills, and Abilities in Civilian Jobs.” RAND Corporation.