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What Will History Say


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What Will History Say


Ken Melvin

When the new US History books come out in 2040, what will they have to say about 2020? What will they say about:  Globalization?  The Trump Presidency?  Global Warming?  The 2020 Pandemic?  China’s Rise?  America’s Decline?  Capitalism and Free markets?  Mitch McConnell?

to run where the brave dare not go.

Globalization: From a US perspective, globalization began in the 1970s with the first large-scale offshoring of semi-conductor, clothing, shoe, electronic, … manufacturing, and the large-scale importation of automobiles, and accelerated during the 1980s. Capitalists and 401Ks were the most significant forces driving globalization. As a result of globalization, the DJI soared to new heights.

By 2020, most all of our critical medicines were being manufactured in China and India; hampering our ability to respond to the Covid-19 Pandemic, causing tens of thousands of Americans to die unnecessarily. The US was no longer self-sufficient, hadn’t been for more than twenty years.

Significant unintended consequences of Globalization include:   Millions of well-paying jobs were sent overseas.  A Globalization related Opioid Epidemic that began in the 1990s. The American landscape was littered with dead and dying communities.   By 2020, 40% of US Workers were living from paycheck to paycheck; working at jobs that did not pay a living wage.   America suffered a soaring homeless population. Due to offshored critical manufacturing, the nation was unable to respond to a worldwide pandemic.

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Meanwhile potable water becomes more of a problem for Americans

From The Guardian:

In 2010, the UN declared clean water to be a human right. Yet a decade later, millions of Americans lack basic indoor plumbing, more than 100 million are exposed to toxic chemicals in their drinking water, and water bills have risen by an average of 80% across 12 US cities, in a cascading crisis of water affordability.

The Guardian is tackling the subject of the US water crisis with a landmark series, in partnership with Consumer Reports and others – and we’re asking for our readers’ help to test the water quality in your area. As Bernie Sanders and the Michigan congresswoman Brenda Lawrence argue, it is time clean water ceased to be a source of government profit, and became a basic right:

Unbelievably, when it comes to water infrastructure, America’s challenges resemble those of a developing country. The American Society of Civil Engineers gives our drinking water infrastructure a ‘D’ grade and our wastewater infrastructure a ‘D+’.

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New and continued jobless claims level off, as spreading secondary impacts and job recalls balance

New and continued jobless claims level off, as spreading secondary impacts and job recalls balance

Weekly initial and continuing jobless claims give us the most up-to-date snapshot of the continuing economic impacts of the coronavirus on employment. Three full months after the initial shock, the overall damage remains huge, with recalls to work roughly balanced with spreading new secondary impacts.

First, here are initial jobless claims both seasonally adjusted (blue) and non- seasonally adjusted (red). The non-seasonally adjusted number is of added importance since seasonal adjustments should not have more than a trivial effect on the huge real numbers:

There were 1.433 million new claims, which after the seasonal adjustment became 1.508 million. This is “only” 58,000 less than last week’s number – the smallest weekly decline since the worst reading in April but nevertheless is the lowest so far since the virus struck.


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May inflation steadies: meanwhile, an artificial all time high in “real” wages

May inflation steadies: meanwhile, an artificial all time high in “real” wages

 by New Deal democrat

In May, overall consumer prices declined by -0.1% (blue in the graph below), while consumer prices excluding energy (gas) rose +0.1% (red):

Note that in 2015 when gas prices collapsed, prices otherwise continued to increase, showing the underlying strength of the economy. But in March and April of this year, even prices outside of gas declined, showing underlying weakness. This is a typical recessionary scenario. May’s increase in prices ex-energy may be a good sign.


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May jobs report: a welcome positive shock

May jobs report: a welcome positive shock

–  by New Deal democrat


  • 2,509,000 million jobs added. This makes up about 12% of the 22.1 million job losses in March and April.
  • U3 unemployment rate improved 1.4% to 13.3%, compared with the January low of 3.5%.
  • U6 underemployment rate improved 1.6% to 21.2%, compared with the January low of 6.9%.
  • March and April were both revised further downward, by -492,000 and 150,000 respectively, for a net of -642,000 more jobs lost compared with previous reports.

Leading employment indicators of a slowdown or recession


I am still highlighting these because of their leading nature for the economy overall.  These were uniformly very positive:

  • the average manufacturing workweek rose 0.8 hours from 38.1 to 38.9 hours. This is one of the 10 components of the LEI and will be a positive.
  • Manufacturing jobs rose by 225,000. Manufacturing has still lost 1.145 million  jobs in the past 3 months, or close to 10% of the total.
  • construction jobs rose by 464,000. Even so, in the past 3 months -596,000 construction jobs have been lost, or about 8% of the total.
  • Residential construction jobs, which are even more leading, rose by 65,600. Even so, in the past 3 months there have still been -58,800 lost jobs, or about 7% of the total.
  • temporary jobs rose by 41,300. Since February, there have still been -852,800 jobs lost, or over 1/4 of all temporary help jobs.
  • the number of people unemployed for 5 weeks or less declined to 3.875 million, compared with April’s total of 14.283 million. This is similar to the “less awful” readings of the weekly initial jobless claims.
  • Professional and business employment rose by 127,000, which is still 2.156 million, or about 10% below its February peak.

Wages of non-managerial workers

  • Average Hourly Earnings for Production and Nonsupervisory Personnel: declined $0.14 from $25.14 to $25.00, which is still a gain of over 3% in 2 months. This reflects that job losses were primarily among lower wage earners.

Aggregate hours and wages:

  • the index of aggregate hours worked for non-managerial workers rose by 4.9%. In the past 3 months combined this has nevertheless fallen by about 10%.
  •  the index of aggregate payrolls for non-managerial workers rose by 4.4%. In the past 3 months combined this has nevertheless fallen by about 11%.

Other significant data:

  • Full time jobs were responsible for 2.2 million of the gains.
  • Part time jobs were responsible for 1.6 million of the gains.
  • The number of job holders who were part time for economic reasons declined  by 254,000 million to 10.633 million. This is still an increase since February of   6.315 million.


This report was a positive shock. Rehiring in May outweighed the continuing and spreading layoffs. At first blush it appears this was primarily among the retail and leisure and hospitality sectors which were more than decimated in March and April.

A few sectors have recovered more than half of the jobs that were lost, but most have only regained 10% or 20% of their losses. Further, because average hourly wages have maintained over 80% of the increase in April – because lower wage jobs were primarily lost – this strongly suggests that the job recalls were relatively speaking tilted towards higher paying jobs as well.

Most importantly, aggregate payrolls are still down more than 10% from their recent peak. Unless a miracle happens and a huge majority of the job losses are reversed in the next 45 days, when the enhanced unemployment insurance passed by Congress runs out in July, there is going to be a major knock-on shock to the economy.

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Coronavirus, the economy, and the election: the jury is still out on all three

Coronavirus, the economy, and the election: the jury is still out on all three

There is some housing data out today; I’ll probably have a post up about it tomorrow at Seeking Alpha, and I’ll link to it here.

Meanwhile, the jury is still out on the effects of the “reopening” of many States on coronavirus infections.

Here’s a graph of the 7 day average of tests, new infections, hospitalizations, and deaths, divided between the Boston, NYC, Philadelphia metro areas and Michigan on the one hand and everywhere else:

Testing has continued to increase dramatically, while cases “everywhere else” have plateaued or possibly begun to slightly rise again. This still shows hospitalizations and deaths declining.


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A Compromise on Liability

A Compromise on Liability

So Mitch McConnell and the senate Republicans want blanket employer liability protection as the price of another round of economic support.  They have this leverage because Democrats kept postponing their agenda until they were the only ones with a list of things they wanted to spend money on.

(This illustrates classic bargaining theory to a T.  Bargaining power depends on how much you think you will lose if the agreement is delayed [Rubinstein] or fails completely.  Democrats feared economic damage to the public if bailout bills weren’t approved immediately.  Once the financial markets were backstopped Republicans considered the rest to be low stakes.  Hence the strong tilt to McConnell et al.)

So here is a possible Democratic counter:

OK, you want liability protection.  Let’s give it to any employer, large or small, that sets up a health and safety committee to oversee protections on the job, elected by the whole workforce, one person one vote.  If protections are consensual, liability is waived.  Otherwise proceed at your own risk.

This would be good policy, and it has the political advantage of placing liability within a larger, readily communicable frame about participation and consent.

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Woke Is Reactionary: The Small Business Lending Edition

Woke Is Reactionary: The Small Business Lending Edition

We live in a drastically unequal society.  Everywhere you look you will find injustice, constraint and exploitation.  Being a member of a racial or other minority increases the odds you will end up on the short end, so what should we do about it?  There’s a progressive solution, to change the system so injustice, constraint and exploitation are minimized.  And then there’s the woke solution, to demand benefits targeted to minorities (and women) that will more evenly distribute the injustice, constraint and exploitation that remains.

You can support the woke solution, but please don’t confuse it with progressive social change.

For a current example, look at this recent op-ed in the New York Times by Pamela Shifman and Salamishah Tillet, “How We Spend Tells Us Whose Lives Matter”.  They point out, “only 12 percent of the black and Latino [small business] owners in a survey who applied for aid reported receiving what they had asked for.”  I don’t know how that compares to white/Anglo owners, and no link is provided to the source they relied on.  But let’s assume with them this means minority SB owners have been disadvantaged in the expanded lending program to counter the effects of the coronavirus.  Knowing this country, I wouldn’t be surprised if this were true.

Two reasons are given for the disparity.  First, minority-owned businesses are less likely to have an existing loan relationship with a bank, and private banks are being used to funnel loans authorized by Congress.  Second, these businesses have slimmer reserves and are less able to survive the process of application, review and disbursement.  Again, let’s assume this analysis is correct.

The progressive solution would be to either impose greater obligations on the private banking system or bypass it altogether in administering the program.  If commercial banks are to be deputized to distribute public funds they should be required to do so not just for their existing clients but their share of the applicant pool, and streamlined procedures should be in place to get the money out the door as quickly as possible.  Or perhaps it would have been possible to forego using commercial banks altogether (or in part) and to quickly ramp up a dedicated lending facility operating in conjunction with the Fed or a specialized government agency.  (How much easier all of this would have been if we had a nationwide public banking system already in place.)

And then there’s the woke solution: “providing dedicated funding opportunities for minority and women-owned businesses, and within that funding pool, for women of color-owned businesses.”  So the inadequacies and unfairness of the lending arrangement are OK as long as they don’t disproportionately fall on these groups.  I suppose white business owners locked out of the deal can console themselves with their privilege.

Again, the woke program is a choice some may make; it’s goal is to take the racism and sexism out of exploitation.  Just don’t confuse social justice with a more equally distributed injustice.

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New coronavirus cases vs. testing in “reopened” States

New coronavirus cases vs. testing in “reopened” States

Are new coronavirus infections increasing in States that “reopened” on or about May 1? The jury is still out. The number of infections is up in 4 of the 5 biggest States that have done so, but so are the number of tests. The likelihood that most or all of the increase is an artificial of an increase in testing depends on the date on which you start your comparison.

I haven’t been able to find graphs that nicely show both tests and positives together, so let me just show you 2 separate graphs of the 7 day average in number of new cases diagnosed vs. the 7 day average in testing for Texas, which is the state with the biggest number of new cases.

First, here are new coronavirus infections, which are up 42% from April 30:

Figure 1

But here are new tests performed, which are up 120%:

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The Amateur Epidemiologist II

I am interested in critiquing my understanding of the simplest SIR epidemiological model and also praising a critique of an effort to extend the model and guide policy developed by some very smart economic theorists.

First the useful point is that this post by Noah Smith is brilliant. As is typical, Smith argues that the useful implications economic models depend on strong assumptions so economic theory isn’t very useful. He praises simple empirical work instead.

I will discuss Smith contra Acemoglu, Chernozhukov, Werning and Whinston and Smith pro Sergio Correia, Stephan Luck and Emil Verner after the jump, but really Smith is better at presenting Smith than I am.

It made me wonder. In the simplest model herd immunity stops an epidemic when 1-1/R0 of people have been infected. R0 as I recently learned and everyone now knows is the number of people who would catch a pathogen from one infected person if no one had any resistence. Over time people develop resistence so Rt < R0. If 1-1/R0 of people are resistent, then Rt =1. A bit later Rt<1 so each infected person will lead to a geometrical decreasing series of expected infections so total infections would be 1-1/R0 plus a (small) constant over the number infected at that critical time t. The SIR has susceptible, infected and resistent. The idea is that if one has not been exposed one is vulnerable. If one becomes infected, one carries and sheds the pathogen for a while and then one recovers. After one recovers one is immune and won't get it again. The key assumption in the model is that for every infected people R0 people are exposed (and infected if not immune) and that those people are chosen at random out of the entire population. It is necessary to assume that spread is equally likely from Mr A to Ms B if they share a house or live on opposite sides of the country. This is a silly assumption and the model is the old model used to teach kids and not, I'm sure, current research. It is also the model always used to guide public policy decisions (see me contra benchmark models ) In population biology and evolutionary biology the silly assumption is called "pan mictic" in economics it is called "random matching". The assumption is made very often because doing without it can get one stuck in really hard math. I would like to put a few minutes of effort into trying to figure out if the random matching assumption affects the level of infection needed for herd immunity (of course everyone knows it matters a lot). Below I will always assume R0 =3. Model 2 the population is actually divided into N equal subpopulations and there is no spread from one to the other. The disease starts with one case in one sub population. It will spread until a few more than two thirds of that population has been infected. Spread will stop when 1/(3N) of the whole population is infected. the relaxation of random matching assumption reduceces the incidence needed for herd ommunity by the factor N. This works for any N. Model 3 very like model 2. Half of people have innate immunity to the virus. People transmit the virus to on average 6 other people (on average 3 have innate immunity). the virus will spread until 5 of 6 are immune. that means (5/6)-(1/2) = 1/3 must acquire immunity (by getting infected). So 1/3 not 2/3. OK can we be sure that the number who will get onfected is less than 2/3 ? Consider Model 4. people live one to a square of an invisible chess board (which is a really big square) they transmit the pathogen to those with whoù they share an edge. R0 = 3 (I get it from 1 neighbor and early in the epidemic give it to my other 3 not yet infected neighbors). How many people get infected ? All of them Katy. The currently infected are always in the border zone between the resistent and the vulnerable. So R0 = 3 implies herd immunity will stop the spread at some level which ranges from 1/(3N) for N as big as I like, to 100%. R0=3 and a priori reasoning without arbitrary assumptions which we know are false and make for convenience tells us nothing at all. Without some assumption about mixing, matching, and population structure, the core SIR assumptions have no implications. Maybe economists and epidemiologists have more in common than we thought.

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