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  1. Last week, the employment news was all about how payrolls increased by 269,000 jobs and blew past expectations. Yet, when we looked at the actual number of employed persons, it turned out that the number of employed people has gone down in recent months. At 158.4 million, total employment is still nearly 400,000 workers below where it was before the Covid Panic of 2020.

    Those who support the everything-is-great narrative have responded to the unimpressive employed-workers numbers by dismissing them as a result of workers retiring and other demographic changes.  These explanations, however, require that we ignore the fact that millions of men age 25-54—that is, men of working age—have removed themselves from the workforce. When so many men—men who would have been in the workforce 20 or 30  years ago—aren't even trying to get a job, this lowers the unemployment rate and makes total jobs numbers look more impressive. 

    In fact, as of September of this year, there appears to be nearly a six-million-man gap between the number of men in the prime-age group—age 25-54—and the number of prime-age men actually in the workforce. Depending on why they're out of the workforce, that is potentially some very bad news for both the economy and for society overall. 

    How Many Men Are Out of the Work Force?

    Prime-age male workforce participation rose year-over-year in November, rising to 88.4 percent above last November's estimate of 88.2 percent. Workforce participation has been climbing out of a hole since the rate hit an all-time low of 86.4 percent during April 2020. 

    men
    Source: Bureau of Labor Statistics (Current Population Survey).

    The larger trend in workforce participation for prime-age men, however, has been one of decline for decades. During the 1950s and into the early 60s, prime-age workforce participation for men was nearly 98 percent. That began to fall throughout the 60s, and by 1980, it was around 94 percent. The trend didn't end there, however, and even during the construction boom of the housing-bubble years, participation never rose above 91.4 percent. The participation rate has never risen above 90 percent since 2009.

    What does this mean in total numbers of prime-age males? If we look at the difference between total prime-age men, and the total number of them in the work force, we find that the gap as of November was about 7,040,000 men.

    men2
    Source: OECD: "Working Age Population, Age 25-54";   Bureau of Labor Statistics (Current Population Survey).

    The workforce measure is of civilianworkers, however, so if we account for approximately one million active-duty males, that leaves us with about 6 million men out of the work force. But what about stay-at-home dads? Many of these dads have at least part-time jobs, and are thus still in the work force. According to Census data, however, the number of stay-at-home dads who are also "out of the workforce" numbers approximately 200,000

    So, if we shrink that gap by the men in the military and by the stay-at-home dads who don't earn wages, we are left with about 5.8 million men who are spending their days doing something other than working for (legal) wages or parenting children.

    So, how are these men surviving without income? According to research by Ariel Binder and John Bound, most of these men are low-income, but receive income from parents, spouses, and girlfriends. Among men not in the work force, this cohabitants' income "accounts for the largest share of income" in the households where these men reside. Many of these men elect not to work because the opportunity cost of not working is relatively low. As Alan Kreuger has noted, the decline in workforce participation has been especially steep among those with lower earning potential such as those with a high school degree or less.  Many men in this category also report poor health and that they take pain medication daily. This also suggests high incidence of opioid addiction among men not in the work force. Few younger men who have left the workforce are eligible for government disability benefits. Among older men, however, disability benefits supplement income from other household members. 

    What If These Men Rejoined the Work Force? 

    Having a few million men leave the workforce drives down the unemployment rate. What would the employment picture look like if all these men were to suddenly join the workforce by looking for work?

    According to the Bureau of Labor Statistics, there is a gap of four million between job openings—10 million—and total unemployed workers—6 million. If all the current job openings were magically filled by current unemployed workers, that would still leave 2 million unemployed workers. Now, let's add back into the work force those 5.8 million males who are aren't in the work force at all. We'd then have a situation in which all job openings were filled and we still would have 7.8 million unemployed workers. The unemployment rate would increase to 4.7 percent, or the highest rate since September 2021. 

    But that's not a very probable scenario. While many of the six million unemployed workers are only in transition, many others are unemployed because their industries are cutting jobs, or because the workers generally lack the proper skills or education. When it comes to the men who have left the work force entirely, the picture is more bleak. As we've seen, a sizable portion of men who have left the work force have likely done so for reasons that make them something other than ideal job candidates. If they were to begin looking for work, the more likely scenario is one in which the currently unemployed 6 million workers would balloon up to over 10 million. This would drive the unemployment rate up over 6 percent while also softening upward pressure on wages. 

    men3
    Source: Bureau of Labor Statistics, Household Employment Survey;  JOLTS Survey; US Census; Bureau of Labor Statistics (Current Population Survey).

    Once layoffs start to accelerate—as many indicators suggest will happen in 2023—the situation will only become worse with the unemployment rate heading up even higher. 

    If one were to go only on the headlines we get from the mainstream business press, though, it does seem like there's nary a potential worker to be found out there anywhere. The truth is less pleasant as millions of prime-age men aren't working, looking for work, or caring for children. That phenomenon is very good for making the official unemployment rate seem low, but it also lowers the economy's overall productivity while reducing savings. Even worse are the sociological effects of millions of men sitting at home living off of government disability checks or the toil of relatives, girlfriends and spouses.

  2. Arguably the most important question facing the Centers for Disease Control and Prevention (CDC) is an explanation for the unexpected excess deaths in the United States during 2021 and 2022. These excess deaths are occurring at a time when covid prevalence in the US is very low. The CDC does not seem to be interested in explaining these deaths, so the public is filling the vacuum with their own theories. One theory is that the excess deaths are due to adverse effects of the covid vaccines. The CDC has mortality data stratified by vaccination status, but it refuses to release the data to the public. This refusal only reinforces theories that covid vaccines are the culprit. The United Kingdom, however, has released mortality data stratified by age group and vaccination status for January 2021 through May 2022, though it is unclear whether it will continue to update these data. There are many ways to present these data.

    It is my opinion that the best way to test the hypothesis that covid vaccines are responsible for excess deaths is to compare unadjusted mortality rates for unvaccinated people to those of a composite of all partially and completely vaccinated people (people with intent to vaccinate completely). The UK data table organizes mortality for each age group using seven vaccination categories: unvaccinated; first vaccine dose less than twenty‑one days before death; first vaccine dose at least twenty‑one days before death; second vaccine dose less than twenty‑one days before death; second vaccine dose at least twenty‑one days before death; third vaccine dose or booster less than twenty‑one days before death; and third vaccine dose or booster at least twenty‑one days before death. Separation of data for each vaccination status introduces a bias in favor of vaccination, known as the immortal time bias.

    For example, someone who dies following the first vaccine dose will not be represented in second or third vaccine dose data. The third vaccine dose data do not represent the general population, but only those people who have survived past the first and second vaccine doses. It is my opinion that this time bias was largely responsible for the mythology that covid is an epidemic of the unvaccinated. This mythology was created when the vaccine became available. Very few people had received the vaccine, and the vast majority of the population was unvaccinated, making true case rates difficult to estimate by counting people rolling into the ICU. This mythology persists among my colleagues and the administration at my institution despite having been thoroughly disproven.

    The mortality rates in the data table are “adjusted” for age. I report unadjusted mortality rates, calculated by dividing the number of deaths by the person‑days and then multiplying by 100,000. The differences between unadjusted mortality and “adjusted” mortality are small and do not change any of the conclusions. But it is my opinion that rather than trying to “adjust” for age, we should analyze each age group separately to see how finely the age should be stratified to eliminate different patterns between age groups. I would have preferred the 18–39 age group to be further divided, but I have to work with the data available.

    Figure 1: UK unadjusted mortality rates, 18–39 age group

    Note: The blue curve represents unvaccinated subjects. The gold curve represents subjects who received any form of covid vaccination (with intent to completely vaccinate), and its values were calculated by summing the deaths and person‑days for each vaccination subgroup.

    Figure 1 shatters the myth that the benefits of covid vaccines outweigh the costs for all age groups. The mortality rate for the 18–39 age group was greater in vaccinated subjects than unvaccinated subjects for several months during the period of study. The average difference in mortality from January 2021 to May 2022 showed a net harm from vaccination. But were the differences significant? It would be inappropriate to perform statistical tests such as a t‑test on these data because the statistical weight of each data point could not be equal: the data points represent aggregates of individual test subjects, and we have no information about the variance within each aggregate value.

    On average, there was an additional death for roughly every twenty thousand vaccinations in the 18–39 age group. Although the best we can conclude from these data is that vaccination is associated with increased mortality in this age group, we cannot assert that vaccination caused the increase in mortality. It is possible that some unknown factor caused the increased mortality and that this factor was more prevalent in vaccinated subjects than unvaccinated subjects. However, this is the best we can do, given that the Food and Drug Administration (FDA) and CDC stopped the controlled trials after about three months. Thanks to government authorities, we will never have a properly controlled trial of the vaccines. The FDA and CDC should accept the blame for this uncertainty and admit that these vaccines are NOT safe and that they have known for over a year that these vaccines are not safe.

    Figure 1 also suggests that any benefits vaccination may grant in terms of reduced deaths from covid decline over time. The trends during the final four months of the data series suggest that either mortality will be equal for the vaccinated and unvaccinated or mortality for the vaccinated will be greater due to adverse events occurring many months after vaccination.

    Figure 2: UK unadjusted mortality rates, 60–69 age group

    Note: The blue curve represents unvaccinated subjects. The gold curve represents subjects who received any form of covid vaccination (with intent to completely vaccinate), and its values were calculated by summing the deaths and person‑days for each vaccination subgroup.

    Figure 2 demonstrates that there was net benefit from vaccination (reduced mortality) in subjects ages 60–69. In this age group, the vaccinated group demonstrated a lower mortality rate each month. Were the benefits significant? Just as with the data for the 18–39 age group, it would be inappropriate to perform statistical tests such as a t-teston these data. The greatest difference between the unvaccinated and vaccinated mortality rates was seen early in the data series, with the two curves converging during the latest months of the data series. It is unclear whether more recent months will continue to demonstrate a benefit from vaccination. Hopefully, the UK will continue to report data to the public.

    The average benefit over the period of the study can be used to estimate how many vaccinations will prevent a death. In my opinion, this number represents a better indicator of clinical significance than odds ratios.

    Table 1: Vaccinations needed to prevent one death, ages 40 and over

    Age group

    Vaccinations to prevent one death

    40–49

    1,832

    50–59

    326

    60–69

    117

    70–79

    34

    80–89

    12

    90 and over

    9

    Source: Numbers were calculated by dividing 100,000 by the average difference between mortality rates for vaccinated and unvaccinated subjects.

    Table 1 illustrates that a recommendation of vaccination for people over ninety would be very reasonable, while such a recommendation for people ages 40–49 would be very questionable, especially since full vaccination seems to be a never-ending proposition. Note that a net benefit of the vaccine does not justify a mandate for vaccination, since death by covid and death by vaccine are not comparable, even though both are deaths. Individuals have different perceptions about these two forms of death.

    My direct observation of patients demonstrates that some people are much more concerned about covid than about the vaccine, while others are much more concerned about the vaccine than about covid. The best that healthcare providers can do is to inform our patients about the risks of both choices and to let patients decide for themselves. Browbeating patients into vaccination is inexcusable, as the vaccines are objectively NOT safe.

    Space does not permit a detailed discussion of the data for the other age groups, but some observations are of note. For instance, the 40–49 age group demonstrated a net harm from vaccination in March and April 2021 as well as in February, April, and May of 2022. Also, the over-ninety age group demonstrated a net harm from vaccination for March, April, and May 2022. The maximal benefit of vaccination was seen in different months for each age group, which likely reflects the progressive rollout of vaccination beginning with the oldest age group. All of the age groups demonstrated a convergence of mortality rates during the final months of the data series compared to earlier months.

    Conclusion

    The risks of the covid vaccines are often comparable to the risks of getting the disease itself. This is especially true for younger people. The principle of informed consent requires healthcare providers to inform patients of the objective risks of vaccination. Older patients are more likely to exhibit net benefit from vaccination. Vaccination should be offered but not recommended to patients under the age of forty.

  3. In 2008, the State of Oregon inadvertently ran a randomized health insurance experiment. They decided they had just enough money in their annual budget to give Medicaid coverage to an additional ten thousand citizens randomly chosen via a lottery. While there was no improvement in health outcomes, hospital admissions increased by 30 percent, outpatient visits by 35 percent, and ER visits by 40 percent. The experiment cost a lot of money—36 percent more—with no tangible benefit.

    Amazingly, there is not a strong relationship between healthcare spending and health outcomes. America spends almost $4 trillion a year on healthcare, around twice what most other developed nations spend per head, and approximately half of it is taxpayer funded. With only 4 percent of the world’s population, the US accounts for half of the pharmaceuticals consumed worldwide. If more healthcare were the answer, the US would be the healthiest country on the planet. Yet while Japan’s and Singapore’s healthcare expenditures per head are only a fraction of those of the US, Japanese and Singaporeans live over five years longer than Americans.

    The US’s excess spending on healthcare mostly goes to overpriced, ineffective, and unnecessary treatments. It is generally assumed that more care is caring more, but the reality echoes the eerily astute insight that Ivan Illich put forth in the initial pages of his 1970 book Deschooling Society, in which he deconstructed the bureaucratic ethos. He noted that bureaucrats

    confuse process and substance. Once these become blurred, a new logic is assumed: the more treatment there is, the better are the results; or escalation leads to success. The pupil is thereby “schooled” to confuse teaching with learning, grade advancement with education, a diploma with competence, and fluency with the ability to say something new. . . . Medical treatment is mistaken for health care, social work for the improvement of community life, police protection for safety, military poise for national security, the rat race for productive work.

    Actually, clean drinking water, nutritious food, workplace safety, sanitary living conditions, employment, and a supportive social network have a bigger effect on health outcomes than access to healthcare does. The Centers for Disease Control and Prevention told us in 1999 that while “the average lifespan of persons in the United States has lengthened by >30 years” since 1900, “25 years of this gain are attributable to advances in public health” rather than to medicine. In 2000, the prestigious journal Pediatrics released a comprehensive study that attributed the 90 percent decline in infectious disease mortality to improvements in sanitary conditions and nutrition rather than medical treatments. Cleaner drinking water was responsible for nearly half of the reduction in total mortality and nearly two-thirds of the reduction in child mortality in the twentieth century.

    Longer lifespans and better health, wherever they are still enjoyed—as life expectancy has been falling since 2014, and chronic disease is more prevalent than ever—are largely due to better nutrition and hygiene, ventilated housing, indoor heating, garbage collection, sanitary sewage systems, and cleaner water and food. In the nineteenth century, people’s housing and working conditions improved dramatically. Most of the basic conveniences we take for granted today, like indoor flushing toilets and clean running water, were not widely available in the first half of the twentieth century. Before the internal combustion engine, city streets were lined with horse dung. People lived several to a room, sharing disease. The average living space per person in America doubled between 1973 and 2014, a very recent change.

    Poor people typically have worse health outcomes than affluent people do, and the healthcare that poor people consume largely comes at the taxpayer’s expense. So, even from the statist “welfarist” perspective, if someone getting into government really wanted to do something to improve health and longevity, he could redirect a percentage of the huge sums squandered on Medicaid toward improving housing quality in the areas where living conditions are worst and health outcomes poorest.

    Go after low-hanging fruit, like eliminating mold in apartments. The program would more than pay for itself with the drop-off in health visits. Go to the places with the worst water quality and improve it. Go where the air is dirty and clean it up, or litigate against the polluters. Publicize the effects of poisonous herbicides like Roundup on the microbiome. Improve the quality of the soil so that people can have access to more nutritious produce. Every dollar spent would likely result in several dollars saved from not having to treat preventable illnesses.

    The fact that this is never proposed either indicates that I am uniquely original in my genius (plausible) and should give up economics to run for office or that our so-called public servants are less interested in improving people’s health than they are in shovelling public money into the hands of their cronies in the medical industry.

  4. On this episode of Radio Rothbard, Tho Bishop and Ryan McMaken discuss the recent report that the Pentagon has failed its fifth straight audit and why no one seems to care. Why has the public lost interest in basic fiscal sanity? How recent is this problem? What might force Americans to care?

    Looking for Christmas gifts? Use promo code ROTHPOD for a 20% discount on select books featured on Radio Rothbard. Or, use code MURRAYCHRISTMAS for a special 10% discount on select new Mises apparel: Mises.org/RR_111_Store

    Recommended Reading

    "As the Pentagon Fails Another Audit, Congress Wants to Spend Even More on 'Defense'" by Ryan McMaken: Mises.org/RR_111_A

    "Can a Deeply Unserious America Fix Its Economy?" by Jeff Deist: Mises.org/RR_111_B

    "Biden's Defense Plan: Limitless Global Meddling" (War, Economy, and State podcast): Mises.org/RR_111_C

    America: From Republic to Empire (video series): Mises.org/RR_111_D

    The Betrayal of the American Right by Murray N. Rothbard: Mises.org/RR_111_E

    Be sure to follow Radio Rothbard at Mises.org/RadioRothbard.

  5. Massachusetts voters approved yet another tax hike for high-income residents, while California voters rejected a similar proposition. The current tax fever does not bode well for economic growth.

    Original Article: "Taxing the Wealthy: A Tale of Two State Propositions"

    This Audio Mises Wire is generously sponsored by Christopher Condon.