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Do Veterans Face Disparities in Higher Education, Health, and Housing?

Veterans are an understudied group that forms an important part of the fabric of American society and that constitutes a significant segment of the population….

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Veterans are an understudied group that forms an important part of the fabric of American society and that constitutes a significant segment of the population. In the first post of this two-part series, we will investigate how the outcomes of veteran men–in educational attainment, health, and housing–differ from those of comparable men who did not serve in the military. Looking only at men, for reasons described below, we find that relative to nonveteran men with a high school degree and a similar distribution of demographic and geographic characteristics, veterans are 7 percentage points less likely to have a college degree and are over 50 percent more likely to experience a disability. Veterans are also somewhat likelier to rent a home than to own and, as renters, pay a lower average rent, suggesting they experience lower quality housing or live in worse neighborhoods.

Service in the military may bring both economic advantages and economic disadvantages. It represents a commitment of time away from classroom education or civilian employment during the very years when many people begin their careers. It also carries with it the threat of injury or severe mental stress. However, military service may also bring advantages, such as opportunities to learn new technical and interpersonal skills, access to health insurance through the Veterans’ Administration, or subsidies to higher education through the G.I. Bill.

The Data Set

We use the 2019 five-year American Community Survey (ACS), the last one before the onset of the COVID-19 pandemic, to compute average outcomes for male veterans and nonveterans aged between 25 and 69. This cut of the data has us looking at the population of veterans who served when enlistment in the armed forces was voluntary, after the end of the draft in 1971. It is a challenge to construct a comparison group since veterans differ from nonveterans among many dimensions. For example, veterans are overwhelmingly likely to be male high school graduates as the military typically requires a high school degree for service. Veterans are older, with enlistment rates drifting down over time. They are also more likely to be native-born and white, and more likely to have been born in the South and the Midwest than in the Northeast and the West.

Therefore, for a more comparable group for veterans, we take the population of nonveteran male high school graduates and weight them to match the age, racial, ethnic, immigrant and geographic distributions of veterans. Following a previous paper, we use as weights the fractions of the male high school graduate population in each age, race, origin, and geography category who are veterans. We will refer to this control group as “comparable nonveterans” for the rest of the series. While our methodology does not remove all sources of differences between veterans and “reweighted” nonveterans (for example, the veterans may differ from nonveterans in other aspects of their background, or in unobservables such as personality or interests, for which there is no data in the ACS), it avoids the most obvious sources of noncomparability between them and allows us to focus on the consequences of being a veteran.

Differing Outcomes in Education, Health, and Housing

Despite having access to the benefits of the G.I. Bill, veterans are less likely than comparable nonveterans to pursue further education after high school. We see in the chart below that while 34 percent of male high school graduates who are not veterans obtain a bachelor’s degree or higher, only 27 percent of veterans do so. Veterans are also less likely to end their education with a bachelor’s degree (17 percent vs. 22 percent) and to go on to obtain an advanced degree (10 percent vs. 12 percent) than nonveterans. These differences may be due to the direct effects of military service (including spending a number of critical years for education in the military), as well as to unobserved differences between veterans and nonveterans that are not captured by their age, ethnic, and geographic background.

Veterans Are Less Likely to Hold a Bachelor’s or Advanced Degree

Percent

Sources: American Community Survey; authors’ calculations.

On the health front, we see in the panel chart below that while the percentage of veterans that is uninsured is substantially lower than nonveterans, veterans are over 50 percent more likely to have a disability, with the odds rising even higher for some specific disabilities. Thanks to being eligible for additional forms of health insurance, only 6 percent of veterans are uninsured, compared with 11 percent of comparable nonveterans (left panel). However, despite this coverage, the health of veterans, at least as measured by the presence of disabilities, is poorer (right panel). Veterans are also half again as likely to be disabled, with 19 percent of veterans having a disability as opposed to 12 percent of comparable nonveterans. Veterans are more than twice as likely to have a hearing disability (7 percent vs. 3 percent) and nearly twice as likely to have a sensory disability (9 percent vs. 5 percent). Given that people serving in the armed forces usually have to pass a medical review, disparities between veterans and nonveterans in their disability rate likely emerge either directly from military service or from differences in what veterans and comparable nonveterans do after the veterans leave the military.

Veterans Are More Likely to Have Health Insurance, Yet Are More Likely to Be Disabled

Percent

Percent

Sources: American Community Survey; authors’ calculations.

This analysis also sheds light on the housing situation of veterans and nonveterans who either own or rent. (We don’t consider homelessness; while veteran homelessness is a critical policy concern, there are potential data gaps since the ACS methodology of finding respondents likely undersamples the homeless). In the panel chart below, we see that the renting status of veterans and nonveterans differs little (left panel), standing in contrast to the educational and health differences identified above. Veterans are somewhat more likely to rent than nonveterans are, but the homeownership rate among veterans is 70 percent, just one percentage point less than that of comparable nonveterans. However, veterans may be consuming housing of lower quality. Veterans who are renters pay about 6 percent less in rent than comparable nonveteran renters, suggesting that they rent housing with fewer amenities or in worse neighborhoods (right panel); the same observation about housing quality may apply to veteran homeowners.

Veterans Are Slightly More Likely to Rent, and Rent Less Expensive Housing

Home Ownership
Percent

Average Rent
U.S. dollars

Sources: American Community Survey; authors’ calculations.

To conclude, we see that, when making the comparison with nonveterans who are demographically similar to veterans, veterans have lower education attainment and a greater prevalence of disabilities than nonveterans. The data also suggest veterans are in somewhat worse housing situations. In the second post of this series, we will investigate differences in earnings and labor market outcomes of veterans and nonveterans, and how these differences may be explained by their disparities in terms of education and health. More broadly, we will continue to track data relevant to economic outcomes by race/ethnicity, gender, income, age, veteran status, and geography in a new monthly data product, Equitable Growth Indicators (EGI). Visit our web feature for charts and brief takeaways on disparities in people’s experience of inflation, earnings, employment, and consumer spending.

Rajashri Chakrabarti is the head of Equitable Growth Studies in the Federal Reserve Bank of New York’s Research and Statistics Group.  

Dan Garcia is a research analyst in the Federal Reserve Bank of New York’s Research and Statistics Group.

Maxim Pinkovskiy is an economic research advisor in Equitable Growth Studies in the Federal Reserve Bank of New York’s Research and Statistics Group.

How to cite this post:
Rajashri Chakrabarti, Dan Garcia, and Maxim Pinkovskiy, “Do Veterans Face Disparities in Higher Education, Health, and Housing?,” Federal Reserve Bank of New York Liberty Street Economics, May 25, 2023, https://libertystreeteconomics.newyorkfed.org/2023/05/do-veterans-face-disparities-in-higher-education-health-and-housing/.


Disclaimer
The views expressed in this post are those of the author(s) and do not necessarily reflect the position of the Federal Reserve Bank of New York or the Federal Reserve System. Any errors or omissions are the responsibility of the author(s).

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February Employment Situation

By Paul Gomme and Peter Rupert The establishment data from the BLS showed a 275,000 increase in payroll employment for February, outpacing the 230,000…

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By Paul Gomme and Peter Rupert

The establishment data from the BLS showed a 275,000 increase in payroll employment for February, outpacing the 230,000 average over the previous 12 months. The payroll data for January and December were revised down by a total of 167,000. The private sector added 223,000 new jobs, the largest gain since May of last year.

Temporary help services employment continues a steep decline after a sharp post-pandemic rise.

Average hours of work increased from 34.2 to 34.3. The increase, along with the 223,000 private employment increase led to a hefty increase in total hours of 5.6% at an annualized rate, also the largest increase since May of last year.

The establishment report, once again, beat “expectations;” the WSJ survey of economists was 198,000. Other than the downward revisions, mentioned above, another bit of negative news was a smallish increase in wage growth, from $34.52 to $34.57.

The household survey shows that the labor force increased 150,000, a drop in employment of 184,000 and an increase in the number of unemployed persons of 334,000. The labor force participation rate held steady at 62.5, the employment to population ratio decreased from 60.2 to 60.1 and the unemployment rate increased from 3.66 to 3.86. Remember that the unemployment rate is the number of unemployed relative to the labor force (the number employed plus the number unemployed). Consequently, the unemployment rate can go up if the number of unemployed rises holding fixed the labor force, or if the labor force shrinks holding the number unemployed unchanged. An increase in the unemployment rate is not necessarily a bad thing: it may reflect a strong labor market drawing “marginally attached” individuals from outside the labor force. Indeed, there was a 96,000 decline in those workers.

Earlier in the week, the BLS announced JOLTS (Job Openings and Labor Turnover Survey) data for January. There isn’t much to report here as the job openings changed little at 8.9 million, the number of hires and total separations were little changed at 5.7 million and 5.3 million, respectively.

As has been the case for the last couple of years, the number of job openings remains higher than the number of unemployed persons.

Also earlier in the week the BLS announced that productivity increased 3.2% in the 4th quarter with output rising 3.5% and hours of work rising 0.3%.

The bottom line is that the labor market continues its surprisingly (to some) strong performance, once again proving stronger than many had expected. This strength makes it difficult to justify any interest rate cuts soon, particularly given the recent inflation spike.

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Mortgage rates fall as labor market normalizes

Jobless claims show an expanding economy. We will only be in a recession once jobless claims exceed 323,000 on a four-week moving average.

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Everyone was waiting to see if this week’s jobs report would send mortgage rates higher, which is what happened last month. Instead, the 10-year yield had a muted response after the headline number beat estimates, but we have negative job revisions from previous months. The Federal Reserve’s fear of wage growth spiraling out of control hasn’t materialized for over two years now and the unemployment rate ticked up to 3.9%. For now, we can say the labor market isn’t tight anymore, but it’s also not breaking.

The key labor data line in this expansion is the weekly jobless claims report. Jobless claims show an expanding economy that has not lost jobs yet. We will only be in a recession once jobless claims exceed 323,000 on a four-week moving average.

From the Fed: In the week ended March 2, initial claims for unemployment insurance benefits were flat, at 217,000. The four-week moving average declined slightly by 750, to 212,250


Below is an explanation of how we got here with the labor market, which all started during COVID-19.

1. I wrote the COVID-19 recovery model on April 7, 2020, and retired it on Dec. 9, 2020. By that time, the upfront recovery phase was done, and I needed to model out when we would get the jobs lost back.

2. Early in the labor market recovery, when we saw weaker job reports, I doubled and tripled down on my assertion that job openings would get to 10 million in this recovery. Job openings rose as high as to 12 million and are currently over 9 million. Even with the massive miss on a job report in May 2021, I didn’t waver.

Currently, the jobs openings, quit percentage and hires data are below pre-COVID-19 levels, which means the labor market isn’t as tight as it once was, and this is why the employment cost index has been slowing data to move along the quits percentage.  

2-US_Job_Quits_Rate-1-2

3. I wrote that we should get back all the jobs lost to COVID-19 by September of 2022. At the time this would be a speedy labor market recovery, and it happened on schedule, too

Total employment data

4. This is the key one for right now: If COVID-19 hadn’t happened, we would have between 157 million and 159 million jobs today, which would have been in line with the job growth rate in February 2020. Today, we are at 157,808,000. This is important because job growth should be cooling down now. We are more in line with where the labor market should be when averaging 140K-165K monthly. So for now, the fact that we aren’t trending between 140K-165K means we still have a bit more recovery kick left before we get down to those levels. 




From BLS: Total nonfarm payroll employment rose by 275,000 in February, and the unemployment rate increased to 3.9 percent, the U.S. Bureau of Labor Statistics reported today. Job gains occurred in health care, in government, in food services and drinking places, in social assistance, and in transportation and warehousing.

Here are the jobs that were created and lost in the previous month:

IMG_5092

In this jobs report, the unemployment rate for education levels looks like this:

  • Less than a high school diploma: 6.1%
  • High school graduate and no college: 4.2%
  • Some college or associate degree: 3.1%
  • Bachelor’s degree or higher: 2.2%
IMG_5093_320f22

Today’s report has continued the trend of the labor data beating my expectations, only because I am looking for the jobs data to slow down to a level of 140K-165K, which hasn’t happened yet. I wouldn’t categorize the labor market as being tight anymore because of the quits ratio and the hires data in the job openings report. This also shows itself in the employment cost index as well. These are key data lines for the Fed and the reason we are going to see three rate cuts this year.

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Inside The Most Ridiculous Jobs Report In History: Record 1.2 Million Immigrant Jobs Added In One Month

Inside The Most Ridiculous Jobs Report In History: Record 1.2 Million Immigrant Jobs Added In One Month

Last month we though that the January…

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Inside The Most Ridiculous Jobs Report In History: Record 1.2 Million Immigrant Jobs Added In One Month

Last month we though that the January jobs report was the "most ridiculous in recent history" but, boy, were we wrong because this morning the Biden department of goalseeked propaganda (aka BLS) published the February jobs report, and holy crap was that something else. Even Goebbels would blush. 

What happened? Let's take a closer look.

On the surface, it was (almost) another blockbuster jobs report, certainly one which nobody expected, or rather just one bank out of 76 expected. Starting at the top, the BLS reported that in February the US unexpectedly added 275K jobs, with just one research analyst (from Dai-Ichi Research) expecting a higher number.

Some context: after last month's record 4-sigma beat, today's print was "only" 3 sigma higher than estimates. Needless to say, two multiple sigma beats in a row used to only happen in the USSR... and now in the US, apparently.

Before we go any further, a quick note on what last month we said was "the most ridiculous jobs report in recent history": it appears the BLS read our comments and decided to stop beclowing itself. It did that by slashing last month's ridiculous print by over a third, and revising what was originally reported as a massive 353K beat to just 229K,  a 124K revision, which was the biggest one-month negative revision in two years!

Of course, that does not mean that this month's jobs print won't be revised lower: it will be, and not just that month but every other month until the November election because that's the only tool left in the Biden admin's box: pretend the economic and jobs are strong, then revise them sharply lower the next month, something we pointed out first last summer and which has not failed to disappoint once.

To be fair, not every aspect of the jobs report was stellar (after all, the BLS had to give it some vague credibility). Take the unemployment rate, after flatlining between 3.4% and 3.8% for two years - and thus denying expectations from Sahm's Rule that a recession may have already started - in February the unemployment rate unexpectedly jumped to 3.9%, the highest since February 2022 (with Black unemployment spiking by 0.3% to 5.6%, an indicator which the Biden admin will quickly slam as widespread economic racism or something).

And then there were average hourly earnings, which after surging 0.6% MoM in January (since revised to 0.5%) and spooking markets that wage growth is so hot, the Fed will have no choice but to delay cuts, in February the number tumbled to just 0.1%, the lowest in two years...

... for one simple reason: last month's average wage surge had nothing to do with actual wages, and everything to do with the BLS estimate of hours worked (which is the denominator in the average wage calculation) which last month tumbled to just 34.1 (we were led to believe) the lowest since the covid pandemic...

... but has since been revised higher while the February print rose even more, to 34.3, hence why the latest average wage data was once again a product not of wages going up, but of how long Americans worked in any weekly period, in this case higher from 34.1 to 34.3, an increase which has a major impact on the average calculation.

While the above data points were examples of some latent weakness in the latest report, perhaps meant to give it a sheen of veracity, it was everything else in the report that was a problem starting with the BLS's latest choice of seasonal adjustments (after last month's wholesale revision), which have gone from merely laughable to full clownshow, as the following comparison between the monthly change in BLS and ADP payrolls shows. The trend is clear: the Biden admin numbers are now clearly rising even as the impartial ADP (which directly logs employment numbers at the company level and is far more accurate), shows an accelerating slowdown.

But it's more than just the Biden admin hanging its "success" on seasonal adjustments: when one digs deeper inside the jobs report, all sorts of ugly things emerge... such as the growing unprecedented divergence between the Establishment (payrolls) survey and much more accurate Household (actual employment) survey. To wit, while in January the BLS claims 275K payrolls were added, the Household survey found that the number of actually employed workers dropped for the third straight month (and 4 in the past 5), this time by 184K (from 161.152K to 160.968K).

This means that while the Payrolls series hits new all time highs every month since December 2020 (when according to the BLS the US had its last month of payrolls losses), the level of Employment has not budged in the past year. Worse, as shown in the chart below, such a gaping divergence has opened between the two series in the past 4 years, that the number of Employed workers would need to soar by 9 million (!) to catch up to what Payrolls claims is the employment situation.

There's more: shifting from a quantitative to a qualitative assessment, reveals just how ugly the composition of "new jobs" has been. Consider this: the BLS reports that in February 2024, the US had 132.9 million full-time jobs and 27.9 million part-time jobs. Well, that's great... until you look back one year and find that in February 2023 the US had 133.2 million full-time jobs, or more than it does one year later! And yes, all the job growth since then has been in part-time jobs, which have increased by 921K since February 2023 (from 27.020 million to 27.941 million).

Here is a summary of the labor composition in the past year: all the new jobs have been part-time jobs!

But wait there's even more, because now that the primary season is over and we enter the heart of election season and political talking points will be thrown around left and right, especially in the context of the immigration crisis created intentionally by the Biden administration which is hoping to import millions of new Democratic voters (maybe the US can hold the presidential election in Honduras or Guatemala, after all it is their citizens that will be illegally casting the key votes in November), what we find is that in February, the number of native-born workers tumbled again, sliding by a massive 560K to just 129.807 million. Add to this the December data, and we get a near-record 2.4 million plunge in native-born workers in just the past 3 months (only the covid crash was worse)!

The offset? A record 1.2 million foreign-born (read immigrants, both legal and illegal but mostly illegal) workers added in February!

Said otherwise, not only has all job creation in the past 6 years has been exclusively for foreign-born workers...

Source: St Louis Fed FRED Native Born and Foreign Born

... but there has been zero job-creation for native born workers since June 2018!

This is a huge issue - especially at a time of an illegal alien flood at the southwest border...

... and is about to become a huge political scandal, because once the inevitable recession finally hits, there will be millions of furious unemployed Americans demanding a more accurate explanation for what happened - i.e., the illegal immigration floodgates that were opened by the Biden admin.

Which is also why Biden's handlers will do everything in their power to insure there is no official recession before November... and why after the election is over, all economic hell will finally break loose. Until then, however, expect the jobs numbers to get even more ridiculous.

Tyler Durden Fri, 03/08/2024 - 13:30

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