Why People Are Not Going Back To Work

    There seems to be a lot of talk in the public media about why there seems to be a labor shortage. Or, instead, why jobs in specific industries seem challenging to fill. All too often, I hear the phrase repeated that suggests federal efforts to stimulate the economy have resulted in a moral hazard [my words, not anyone else’s]. More specifically, I hear something like, “why are those people so lazy?” Yeah, it is usually about those people.

    First, one must place our economy in a historical context: Since the 1970s, we have effectively become a plutocracy. Over time the economy has explicitly been sculpted to benefit the wealthy. The economy has been designed to reward equity over labor. The net result of this transformation has been a transfer of something on the order of $47T from the lower 90% of the U.S. economy to the upper 10% from 1975 through 2018 (Price & Edwards, 2020). This has resulted in downward pressure on wages, particularly on the lower half of the economic spectrum. With the onset of the COVID pandemic, those on the lower end of this spectrum were placed at the most significant risk of contracting the disease. There was a well-documented racial bias to those data (Parker et al., 2020).

    Let us consider what the economy was during 2020: Individual median income in real dollars was $35,805 (Real Median Personal Income in the United States, 2020). What “median” means is 50% of individuals in this country earned less than this amount. These same data show the median income for child care workers was $25,460. This same source reports the median household income for 2020 was $67,521 (Real Median Household Income in the United States, 2020). What I find particularly interesting is the household income is less than twice that of the individual income. This suggests the following relationship for a two-income household:

P + S = $65,521

Where P  is the primary source of income and S is the secondary source. This relationship further suggests:

P + a*P = $65,521 where S = a*P

Solving for a:

a = 88.6%

So the secondary source of income in this hypothetical two-income household is:

S = $31,716

    The median yearly income for child care workers is $25,460 (Real Median Personal Income in the United States, 2020)[i]. Therefore, if you consider a median two-income household with several children, in the limit, one could argue the secondary source of income is effectively a net $6,256 per year.

    I discovered from these data that when these yearly figures are converted to a median hourly wage, the number of yearly working hours used is 2080. This number is what one gets when multiplying 40 hours per week by 52 weeks per year. In my world, we call this a full-time equivalent or FTE. In general terms, people working that many hours per year is seldom heard of because of holidays, sickness, vacations, etc. Nevertheless, this number is a helpful number of hours to use in order to find a common baseline for comparison purposes. However, the implication is the source of the secondary income in our hypothetical example is working for a net $3.01 per hour, in the limit.

    Let us ask the question again: Why are those people not going back to work? These data strongly suggest the answer:

why bother?

 

References

Parker, K., Horowitz, J., & Brown, A. (2020, April 21). About half of lower-income Americans report household job or wage loss due to COVID-19. Pew Research Center. Retrieved September 26, 2020, from https://www.pewsocialtrends.org/2020/04/21/about-half-of-lower-income-americans-report-household-job-or-wage-loss-due-to-covid-19/

Price, C. C., & Edwards, K. A. (2020, September). Trends in income from 1975 to 2018. RAND Corporation Objective Analysis. Effective Soltuions. Retrieved November 8, 2021, from https://www.rand.org/pubs/working_papers/WRA516-1.html

Real median household income in the United States [Data set]. (2020). Federal Reserve Bank of St. Louis. https://fred.stlouisfed.org/series/MEHOINUSA672N

Real median personal income in the United States [Data set]. (2020). Federal Reserve Bank of St. Louis. https://fred.stlouisfed.org/series/MEPAINUSA672N

 

 

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[i] This citation was corrected from the original.

Confirmation Bias

 

After the 2020 general election, during the midst of the turmoil associated with the vote count and validation, I had a conversation with an individual associated with the construction company that built my home[1]. This individual was born and raised in North Carolina. Based on previous conversations, it is clear this individual is politically conservative. This particular conversation was one the individual initiated as he was trying to get his head around the November 2020 election outcome. Specifically, this individual could not understand how one particular candidate could get over 70 million votes and lose the election[2] (Lindsay, 2020). I tried to explain the general increase in the population eligible to vote. I also explained the increase in the percentage of eligible voters who voted (that percentage was 67% (Lindsay, 2020), the highest in 120 years, although that figure was not available to me at the time)). In response, the individual asked me, “do you believe in the ‘deep state’” (G. Turner, personal communication, December 10, 2020).

Honestly, the question caught me off guard. My response was that I did not. I should have asked for a definition of terms. I presumed that the individual was referring to the so-called conspiracy theory (I am not using that term to convey the scientific connotation). My presumption was that he meant the conspiracy theory that holds there is a cabal of individuals working behind the scenes to control the government for their own benefit. It is my understanding that this is a relatively widely held belief. At least in 2018, 74% of the individual polled believed that such a cabal either definitely, or probably, existed (Morin, 2018). I find that number to be breathtakingly high. How is it that such a significant number of our fellow citizens believe that there is some sort of shadow government operating behind the scenes clandestinely to manipulate our government? What would be the point of such a shadow government? What problem does it solve to believe in this cabal? What kind of model must one have that it would require the existence of such a cabal to explain the world around us[3]? I use this term to distinguish between this so-called cabal and the corps of dedicated civil servants who work hard every day to perform their duties as best they can.

We all build a model (a theory, in the scientific context) that explains how we see the world operating around us. This model is the narrative arch we construct to help us make sense of how and why people behave the way they do. This model will have a heavy cultural bias, as it reflects the society in which we live and our upbringing. Once we have either constructed such a model or adopted one, the challenge is: How does one correct this model given new information? This dilemma is the problem of confirmation bias (Confirmation Bias, 2021). This very human trait causes everyone to look for evidence that reinforces the model we have adopted and tend not to look for evidence that is contradictory.

There are several components to confirmation bias (Confirmation Bias, 2021). The cumulative effect of this cluster of biases is to cause groups of adherents to separate. This separation creates the idea of the “group” and the “other.” Once the concept of “other” has been created, it is possible to see this out-group as “less than” the in-group members. Much of what is wrong with our society can be explained in these terms. In our time, this separation of groups and the resulting potential for conflict is exacerbated by the dominance of social media (Orlowski & Rhodes, 2020). Perhaps it was not one of the intentions; however, the algorithms used by platforms such as FaceBook, Twitter, and YouTube [plus subsiteraries] steer members to those areas of discussion that reflect choices made. Since we all pay more attention to things that confirm our respective models, these algorithms tend to steer us further and further apart. The argument could be made that much of the polarization we are experiencing today in American life can be laid at the feet of social media (Orlowski & Rhodes, 2020).

The SOE[4] Conjecture

I would submit that the following two figures represent the entire explanation for all that is going on with our society today.

Figure 1 Productivity vs. real wages since 1973 (Gould, 2020, Figure A)

 

Figure 2 Rate of earnings growth (Gould, 2020, Figure B)

As these figures suggest, since the so-called Reagan Revolution, the U.S. economy has become effectively plutocratic. The U.S. government has become the facilitator of this economic shift, particularly since the Citizens United decision by the Supreme Court, which removed most constraints on the influence of donated money on our political system (Citizens United V. FEC, 2021). While both political parties have been at fault here, modern conservative thought has been at the forefront of this transformation. This pronounced shift from economic equity has been so dramatic a recent study from the Rand Corporation shows that $50 trillion has been moved from the bottom 90% of the American population to the top 1% during this period[5] (Hanauer & Rolf, 2020).

 

The results of this significant shift in wealth have shown themselves in many, often destructive, ways. One of the most astonishing has been the emergence of the so-called opioid crisis (Opioid Epidemic in the United States, 2021). This crisis has cost the lives of a significant number of people, biased toward economically depressed areas that are generally conservative politically and are a subset of the so-called deaths of despair (Diseases of Despair, 2021). Much of the responsibility for the opioid crisis, in particular, has been laid at the feet of the family that owned Purdue Pharma (Opioid Epidemic in the United States, 2021). This company has been driven into bankruptcy because of the family's egregious actions to foment addiction to opiate-based drugs. There are many other examples of the destructive impact of this shift towards plutocracy. The obvious racial bias of the effects of the COVID-19 pandemic has been well articulated recently in a white paper proposal addressed to Walden University concerning the establishment of an Institute for Racial and Economic Equity Research (E. Jordan & J. Glenn, personal communication, January 18, 2021).

Earlier, I asked what problems conspiracy theories were trying to solve. I would suggest these theories, such as that of the so-called deep state, attempt to resolve the cognitive dissonance (Cognitive Dissonance, 2021) that results from supporting political ideals that are destroying society's fabric the believer thinks is being protected. The damage that has been done to our society since the 1970s is real, it is deep, and it is systemic. This latest experiment that has been forced on us with the Trump ascendancy is a direct result of attempts to deal with the impacts' of the cognitive dissonance as implied by the figures presented earlier. I would submit this results from having a world model that does not have a mechanism that allows for correction to incorporate new information: That is the conjecture.

Conclusion

Each of us develops a world model to help explain what we see and how people behave. This model

must be capable of correction to incorporate new information. The so-called theory we develop represents the narrative arch that articulates that model must be capable of incorporating new information but reduces the old model for those cases developed initially. This approach represents the power of the scientific method (Scientific Method, 2020); it allows us to step outside our own confirmation bias. In this way, we may accumulate wisdom.

References

Citizens United v. FEC. (2021, January 7). Wikipedia, the free encyclopedia. Retrieved January 17, 2021, from https://en.wikipedia.org/wiki/Citizens_United_v._FEC

Cognitive dissonance. (2021, January 16). Wikipedia, the free encyclopedia. Retrieved January 18, 2021, from https://en.wikipedia.org/wiki/Cognitive_dissonance

Confirmation bias. (2021, January 2). Wikipedia, the free encyclopedia. Retrieved January 2, 2021, from https://en.wikipedia.org/wiki/Confirmation_bias

Diseases of despair. (2021, January 9). Wikipedia, the free encyclopedia. Retrieved January 16, 2021, from https://en.wikipedia.org/wiki/Diseases_of_despair#:~:text=The%20number%20of%20deaths%20of,150%2C000%20per%20year%20in%202017.

Gould, E. (2020, February 20). State of working America wages 2019. Economic Policy Institute. Retrieved September 29, 2020, from https://www.epi.org/publication/swa-wages-2019/

Hanauer, N., & Rolf, D. M. (2020, September 14). The top 1% of Americans have taken $50 trillion from the bottom 90% - and that's made the U.S. less secure. Time.com. Retrieved September 14, 2020, from https://time.com/5888024/50-trillion-income-inequality-america/

Lindsay, J. M. (2020, December 15). The 2020 election by the numbers. The Water's Edge. Retrieved January 3, 2021, from https://www.cfr.org/blog/2020-election-numbers

Morin, R. (2018, March 19). Poll: Majority believe 'deep state' manipulates U.S. polices. POLITICO. Retrieved January 3, 2021, from https://www.politico.com/story/2018/03/19/poll-deep-state-470282

Opioid epidemic in the United States. (2021, January 13). Wikipedia, the free encyclopedia. Retrieved January 17, 2021, from https://en.wikipedia.org/wiki/Opioid_epidemic_in_the_United_States

Orlowski, J. (Director), & Rhodes, L. (Producer). (2020). The social dilemma [Film]. Netflix. www.netflix.com

Scientific method. (2020, December 29). Wikipedia, the free encyclopedia. Retrieved January 27, 2021, from https://en.wikipedia.org/wiki/Scientific_method

 

 

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[1] This particular blog is not as academic as is typical for here. This blog post is based primarly on my observations, my opinions, and uses some commonly available material designed for popular consumption.

[2] According to Lindsay (2020), the final count was 81.4 million for Biden and 74.2 million for Trump.

[3] Actually, I do have an hypothesis (in the scientific sense) as to the point of this belief. More about this later.

[4] Spooky Ol’ Edgar

[5] Yeah, I know it is a secondary source; get over it.

 COVID19 Racial Bias

Since the late 1970s, real wages and productivity have decoupled (Gould, 2020, Figure A). In real terms, there has been little growth in hourly compensation since this decoupling occurred. The net effect of this divergence has been a significant transfer of wealth from the lowest paid 90% of Americans to the top 1%. Referring to a recently released working paper from the Rand Corporation, the amount of this transfer has been calculated to be on the order of $50 trillion (Hanauer & Rolf, 2020). This wealth transfer has been engineered by the way our economy has been sculpted, by the political and legal systems what we, as citizens have allowed to operate.

Figure 1: Productivity vs. real wages since 1973 (Gould, 2020, Figure A)

As can be seen in Figure 1, productivity gains have increased more or less monotonically during the entire period. Those productivity gains represent increased wealth to some portion of our population. In must be noted, the modest gains in hourly compensation that have occurred during this period have been unevenly spread across the economic spectrum of the U.S.  As can be seen in Figure2, most of the increase in earnings have been accrued by the wealthiest 0.1%. By comparison, 90% of the rest of wage earners in the U.S. have gained next to nothing during the nearly 50 years covered by these data.

Figure 2: Rate of earnings growth (Gould, 2020, Figure B)

These troubling trends in wealth distribution are even more disturbing when viewed through the lens of race. As is shown in 2019 hourly wages data, people of color generally, and African Americans in particular, are paid at rates below their white counterparts at all education levels. This is particularly egregious at the level of advanced college degrees where African Americans are paid at a rate 17.6% below their white counterparts, on average (Gould, 2020). The historic antecedents of the wealth gap between African Americans and white are well understood (Baptist, 2014; Baradaean, 2017; Beckert & Rockman, 2016; Rothstein, 2017; Wilkerson, 2010). But this does not explain the wage-gap observed in the data during the second decade of the twenty-first century, noting the difference between compensation and wealth. It is against this background of nontrivial economic disparity that we will consider the uneven impacts of the COVID19 pandemic.

Figure 3: Hourly wages by race and education (Gould, 2020, Figure P)

As a nation, we were ill prepared, culturally, organizationally, and institutionally for the pandemic that emerged in late 2019. At the time of the pandemic emergence, the U.S. was engaged in a long-standing debate concerning the nature of our health care system and how that should be funded. That debate remains to be completely resolved. What was in place at the time of the pandemic was a combination of publicly subsidized health insurance [aka as the Affordable Care Act (ACA – commonly referred to as ObamaCare)] or health insurance coverage funded by employers. Having health care insurance provided by an employer assumes one is employed. What was clear from the beginning of the COVID19 pandemic is that the downward pressure on real wages that has been going on since the 1970s would have devastating for those who did not have paid sick leave or could work from home. What was also clear is there is an obvious racial bias to who is bearing the brunt of the pandemic, economically as well as from the disease itself. As can be seen in Figure 4, a significant majority of the financial burdens of this pandemic have fallen on people of color (Parker et al., 2020, p. 7). What is also clear is that people of color are more dependent on government COVID response efforts. As can be seen in Figure 5, there is a distinct racial bias to how people are spending government pandemic aid, when it is received (Parker et al., 2020, p. 12).

These data clearly indicate that the inequities inherent in our economy and our social fabric have a distinct racial bias. These data show those inequities have forced some of our citizens to be “on the front lines” of how our country is responding to this pandemic simply because they could not afford to stay home, away from potential exposure. These inequities have been in place for many decades, but with this pandemic, they are more deadly.

Figure 4: Economic Impact of Pandemic (Parker et al., 2020, p. 7)

Figure 5: Stimulus Expectations (Parker et al., 2020, p. 12)

As the nature of the pandemic became better understood, it became clear that the only way to avoid contracting the disease was to avoid contact with others. Those who could, stayed home. But who were those who could not afford to stay home? Given the nature of the wealth transfer upon which our economy is based (Hanauer & Rolf, 2020) it fell to those who did not have the luxury of being able to continue to pay for essentials were being forced into a work place. These so-called front-line workers were of two distinct categories (a) health care providers, and (b) those who provide essential goods and services that require contact with others. There is a distinct racial bias to both categories (Gould & Wilson, 2020).

Figure 6: Percentage of Black Front-Line Workers (Gould & Wilson, 2020, Figure B)

There were many businesses that required person-to-person contact that were not considered essential. These businesses were dramatically impacted by the need to restrict that contact. One might ask, how many businesses are owned by African Americans and in what industries are those businesses?

Figure 7: Percent of Business That are Black Owned (Gould & Wilson, 2020, Figure Q)

There is also a distinct racial bias to the cash reserves available to families who are shut off from their source of income because of the pandemic. This bias can be expected considering the historic wealth gap in this society discussed earlier. The need for these cash reserves is essential if the so-called bread winner(s) are no longer able to work because a particular workplace is shut down.

Figure 8: Available Cash Reserves by Race and Education (Gould & Wilson, 2020, Figure K)

Who are dying from this pandemic? What seems apparent is that one is more likely to die of this disease if one is exposed to the underlying pathogen. There are other factors of course, but the essential element of exposure is required above all else. As has been shown, there is a disproportionate number of African Americans who are dying because they are more likely than their white counter parts to be forced into economic circumstances that risk exposure. There are other reasons for increased likelihood of dying, including pre-morbidity factors (Gould & Wilson, 2020). These factors are also tied directly to the historic social and economic circumstances discussed earlier.

Figure 9: Black American Deaths Out of Proportion to Population (Gould & Wilson, 2020, Figure D)

References

Baptist, E. E. (2014). The half has never been told: Slavery and the making of American capitalism. Basic Books.

Baradaean, M. (2017). The color of money: Black banks and the racial wealth gap. The Belknap Press.

Beckert, S., & Rockman, S. (Eds.). (2016). Slavery’s capitalism: A new history of American economic development. University of Pennsylvania Press.

Gould, E. (2020, February 20). State of working America wages 2019. Economic Policy Institute. Retrieved September 29, 2020, from https://www.epi.org/publication/swa-wages-2019/

Gould, E., & Wilson, V. (2020, June 1). Black workers face two of the most lethal preexisting conditions for coronavirus - racism and economic inequality. Economic Policy Institute. Retrieved September 28, 2020, from https://files.epi.org/pdf/193246.pdf

Hanauer, N., & Rolf, D. M. (2020, September 14). The top 1% of Americans have taken $50 trillion from the bottom 90% - and that's made the U.S. less secuire. Time.com. Retrieved September 14, 2020, from https://time.com/5888024/50-trillion-income-inequality-america/

Parker, K., Horowitz, J., & Brown, A. (2020, April 21). About half of lower-income Americans report household job or wage loss due to COVID-19. Pew Research Center. Retrieved September 26, 2020, from https://www.pewsocialtrends.org/2020/04/21/about-half-of-lower-income-americans-report-household-job-or-wage-loss-due-to-covid-19/

Rothstein, R. (2017). The color of law: A forgotten history of how our government segregated America. Liveright Publishing.

Wilkerson, I. (2010). The warmth of other suns: The epic story of American's great migration. Random House.

 

This blog was never intended to be a "stream of conciseness". My goal has always been to achieve understanding in an academically rigorous way. Over the past year some significant changes have occurred in my life. This changes have forced me to alter the trajectory of what life remains for me. Those changes will be an adventure to be sure.

Having said that, my intellectual curiosity has been rekindled and I have the tools to better approach the kinds of understanding this blog was intended for in the first place. The first major project I intended to tackle is an understanding of how and why it appears that African-Americans' rate of participation in the 2016 was lower than it could have been expected. I am in the process of developing my understanding of this question. There is a book I am reading that will likely provide most of that understanding. I have sent a blanket request to the publisher for permission to use many of the figures in that book as I develop my understanding.

This may take awhile.