(What’s Left of) Our Economy: More Reopening, Not Endless Money, is Now the Best Jobs Strategy

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African Americans, American Rescue Plan, Biden, CCP Virus, coronavirus, COVID 19, Covid relief, education, Employment, Federal Reserve, Hispanics, hotels, Jerome Powell, Jobs, Latinos, leisure and hospitality, lockdowns, recovery, restaurants, shutdown, stay-at-home, stimulus package, unemployment, wages, Wuhan virus, {What's Left of) Our Economy

There’s no doubt that the American jobs market has suffered an out-and-out disaster since it got hit by the CCP Virus and the follow-on lockdowns and other restrictions. There’s also no doubt that many workers and their families are still suffering greatly, and will need government aid to make it to the Other Side, and the Biden administration’s American Rescue Plan legislation that the President will likely sign into law soon will help fill this gap.

Plenty of doubt remains, however, about whether all, or close to all, of the massive funds approved in this measure are actually needed to cure the economy’s remaining employment woes, and one of the main reasons is the nature of the jobs blow that’s been delivered. Because it’s been so heavily concentrated in the country’s leisure and hospitality industries (encompassing eateries and drinking places of all kinds, plus hotels and motels, and entertainment and cultural venues), it’s entirely possible that nowadays, the most effective way to fix the jobs market fastest would be to lift the lockdowns and other mandated curbs that have fallen so hard on sectors that depend on serving in-person customers.

The case for relying on a virus-relief/stimulus package this big, at this stage of the economy’s recovery from its pandemic-induced recession, has been eloquently stated by President Biden and by Federal Reserve Chair Jerome Powell. The former warned just before the legislation passed that the U.S. economy “still has 9.5 million fewer jobs than it had this time last year. And at that rate, it would take two years to get us back on track.”

The latter has stated that he won’t be satisfied that full employment has returned until he sees what one reporter has called “broad-based gains in employment, and not just in the aggregate or at the median.” As a result, the Fed Chair is paying particular attention to (the reporter’s words again) “Black unemployment, wage growth for low-wage workers and labor force participation for those without college degrees, categories that historically have taken longer to recover from downturns than broader metrics.”

But it’s precisely these less fortunate portions of the workforce that would be helped disproportionately – and then some – by focusing on reopening steps that would surely affect the leisure and hospitality industries just as disproportionately.

If you doubt the importance of leisure and hospitality job loss over the last year in terms of overall U.S. jobs loss, here’s what you need to know. Of the 8.068 million positions shed by the country’s private sector between last Februrary (the final month of pre-CCP Virus normality for the American economy), fully 3.451 million have come in the leisure and hospitality industries. That’s nearly 43 percent.

Put differently, during that final normal economic month, leisure and hospitality workers represented just 13.04 percent of all private sector workers. Yet their employment plunge was more than three times as great relatively speaking.

Moreover, leisure and hospitality’s progress in getting back to pre-pandemic square one has been slower than that of the private sector overall. Since the April employment trough, leisure and hospitality has regained 4.955 million of the 8.224 million jobs lost during the worst of the pandemic, or 60.25 percent. For the private sector in toto, 13.267 million of the 21.353 million jobs lost in March and April have come back since – 62.13 percent.

It’s also clear that many of the kinds of workers about which Fed Chair Powell has been most concerned are concentrated in leisure and hospitality. For example, in 2019, (America’s last pre-CCP Virus full year), 13.1 percent of these sectors’ workers were African American versus 12.3 percent for the entire U.S. economy (including government workers at all levels), and 24 percent were Hispanic or Latino versus 17.6 percent for the entire economy.

Leisure and hospitality companies tend to employ Americans with low levels of formal education, too. According to the Labor Department, in 2019, 79.9 percent of the nation’s “first-line supervisors of house-keeping and janitorial workers” 25 years and older lack even an associate’s degree, and 76 percent of their food preparation and service counterparts fall into this category. The shares are even higher for the workers they supervise. Meanwhile, only 51.5 percent of all U.S. workers haven’t taken their education beyond high school.

Not surprisingly, therefore, leisure and hositality jobs pay poorly. In February, 2020, just before the arrivals of the pandemic and the lockdowns, their average hourly wages were only 59.28 percent those of all private sector workers. Last month, this figure had fallen to 57.58 percent. (See Table B-3 here.) 

For most of the pandemic period, the U.S. government at all levels pursued a mitigation strategy that aimed mainly at curbing economic and other forms of human activity across-the-board. Now, even with vaccinations and growing population-wide immunity showing strong signs of bringing the pandemic under control, the Biden administration and the Democratic Congress are just as determined to stimulate the economy that’s still significantly shut down by with an American Rescue Plan that seems just as indiscriminate.

As I’ve been writing (see, e.g., here), it should have been clear since late last spring that the anti-virus fight would have much more effective (and less harmful to the economy and other dimensions of public health) had it targeted protecting especially vulnerable populations. I strongly suspect that, with the fullness of time, it will become just as clear that a stimulus and jobs strategy emphasizing accelerating reopening, and thus aiding sectors and workers hardest hit by the remaining shutdowns, will prove a much more effective employment cure than the indiscriminate spending approach on which Washington has just doubled down.

(What’s Left of) Our Economy: In Case You Still Doubt How Much Manufacturing Matters

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automotive, CCP Virus, coronavirus, COVID 19, electronics, Immigration, infotech, Nikkei Asia, semiconductors, stay-at-home, Taiwan, TSMC, wages, Wuhan virus, {What's Left of) Our Economy

One of the most encouraging recent developments in American public policy lately is the virtual disappearance of the idea that manufacturing boasts no special importance to the American economy. I guess that’ll happen when a pandemic reveals dangerous shortages of key medical equipment (and the long supply chains needed to supply equally key parts, components, materials and the production equipment to make all of these items).

Ditto for the loss by a U.S.-based company (Intel) of the global lead in the knowhow to produce the world’s most powerful semiconductors – which run not only the world’s exploding numbers of electronics devices and networks, but soaring percentages of production machinery, as well as lying at the heart of nearly all present and future defense-related goods.

But I’m far from taking this triumph for granted – no doubt because this victory has been so recent, and because I’ve spent so much of my career making the case for government promotion of manufacturing against a free market-worshipping opposition that not only represented an entrenched conventional wisdom, but that could vastly out-spend and therefore practically drown out us “industrial policy” supporters.

And that’s why I was so pleased to see an article just out from the Japanese publication Nikkei Asia that dramatically illustrated how a robust national manufacturing base can supercharge an entire national economy and its workforce’s well-being.

Nikkei Asia described the effect on Taiwan of the new expansion programs being carried out by its world-class semiconductor manufacturing company TSMC (the firm that, along with South Korea’s Samsung, has taken the global microchip manufacturing technology lead from Intel). TSMC’s planned growth is dramatic, largely because the CCP Virus and its effects have created such surging demand for and consequent shortages of microchips. Blame (or credit) the booming popularity of semiconductor-powered electronic devices critical for increasingly popular stay-at-home work and leisure, and the on-and-off jolts generated by the pandemic for giant semiconductor-using industries like the automotive sector.

Compounding the impact, according to authors Cheng Ting-Fang and Laury Li, is the trend of “other Taiwanese companies…bringing production home from China amid Beijing-US trade tensions.”

And the results? “Business has never been brisker for construction companies in Taiwan….” Consequently, wages are way up for construction workers with both ordinary skill sets and specialized knowledge. But even though labor shortages are evident, Taiwan’s government shows no signs of killing this living standards bonanza by trying to open immigration flood gates.

As explained by a manager in the construction industry itself, “Foreign workers are not the ultimate solution as the government sets limits on their entry and many positions, such as electroplating specialists, require professional knowledge.”

Bottlenecks are already appearing and more are sure to come. But it also seems that Taiwan’s businesses will be solving the problem in the way that brings the greatest, most broadly shared national benefits – with technological and managerial innovation (i.e., by improving productivity) rather than by suppressing wages via artificially pumping up Taiwan’s labor supply.

At the same time, it’s not just workers that are in great demand on Taiwan. As the Nikkei Asia article specifies, “Cranes, trucks, excavators and all manner of heavy vehicles stream in and out of the vast construction site for” TSMC’s new advanced semiconductor factory in the city of Tainan. So the need for these machines is pressing, too – and thus for the workers and machinery needed to turn them out.

Is there a downside? Absolutely. Higher wages (and they’ve advanced throughout the economy) have driven major real estate and housing price increases (though the wage hikes indicate that affordability remains pretty much the same, and therefore bubble fears are unwarranted so far). And Taiwan’s water supplies and other infrastructure systems are under strain.

Overall, though, I’d bet on Taiwan to cope successfully with these and other actual and potential problems – which most other countries would actually love to have. And that’s precisely because, to a practically unrivalled extent, the country knows how much manufacturing matters. 

Full disclosure: I own some TSMC stock.  

 

Im-Politic: For Biden, It’s Americans Last on Migrants and the Virus

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asylum seekers, Biden, CBP, CCP Virus, coronavirus, COVID 19, detention, Donald Trump, El Salvador, Guatemala, Honduras, ICE, Im-Politic, immigrants, Immigration, Immigration and Customs Enforcement, Journal of the American Medical Association, lockdowns, Mexico, migrants, Remain in Mexico, stay-at-home, testing, U.S. Customs and Border Patrol, Worldometers.info, Wuhan virus

Some of you might have heard and been concerned about reports that President Biden’s new policies will result in migrants caught by U.S. border authorities being released into the United States without being tested for the CCP Virus. If you knew how much potential for superspread these policies hold, you’d be even more concerned.

Under President Trump, the problem appeared under control because Washington ended the policy of processing migrants who crossed the southern border illegally and then releasing them into the United States to await future hearings on their requests for permanent residency. Instead, apprehended migrants claiming to be asylum seekers, were returned to Mexico (whatever their nationality) until their cases could be brought up. And last March, these policies were extended to all would-be border crossers due to pandemic concerns.

Yet due at least partly to the Biden administration’s immigration-welcoming statements and actions (including during the campaign), migrant flows northward have surged, and current U.S. detention centers have been filling to overflowing despite American court orders preventing them from holding detainees for more than 72 hours in certain facilities in Texas. Worsening the situation has been Mexico’s new refusal in some instances to accept migrants expelled from U.S. territory. (See here for details.) And the new U.S. President seems determined to facilitate immigration inflows generally.

Therefore, the U.S. Customs and Border Enforcement (CBP) agency publicly acknowledged last week that “some migrants will be processed for removal, provided a Notice to Appear, and released into the U.S. to await a future immigration hearing.” Crucially, this practice is proceeding even though CBP doesn’t test arrivals for the CCP Virus unless symptoms are visible. (See the previously linked article for the statement.) 

Which is where the public health threat comes in. Because data from the virus has seemed to be unusually prevalent among these migrants. To begin with, although figures only go through August, a paper published by the Journal of the American Medical Association (JAMA) found that the monthly rate of cases in detention centers was more than 13 times that for the U.S. population as a whole.

Although the JAMA authors wrote that increased testing at the centers only partly explains these high numbers, it also points out that they may also stem from “challenges faced implementing the Pandemic Response Requirements” – like overcrowding. At the same time, they confirm that because asymptomatic detainee testing has been “limited,” even these case numbers could be underestimates. And since migrants tend to be relatively young, asymptomatic cases are surely more common than among legal U.S. residents generally.

The total number of virus cases found among migrants in the detention centers since February has been small – just over 9,300. But the real measure of the danger comes from the incidence of the CCP Virus in the migrants’ main native countries – which look to be sources of large and ever greater greater supply going forward.

Yes, their overall case rates are much lower than their U.S. counterparts, as these data from the Worldometers.info website show:

cases per million

U.S.:                  83,687

Mexico:            14,920

Guatemala:         9,052

Honduras:         15,573

El Salvador:        8,708

One big reason, however, is that they’ve done so little testing, as these numbers from the same source make clear:

tests per million

U.S.:               984,900

Mexico:            37,781

Guatemala:      45,624

Honduras:        39,569

El Salvador:   110,338

Given the immense virus-related uncertainties revealed by these statistics, any measures that increase the numbers of untested migrants in the United States are simply incomprehensible for any government taking seriously the obligation to protect its own population. And given the tight controls already restricting individual, group, and business activities in the United States, these Biden decisions seem even less defensible.

It’s one thing for the new President to reject an America First framework for public policy. It’s quite another to adopt positions that merit the bizarre and perverse label “Americans Last.”

(What’s Left of) Our Economy: The Latest on the Virus, Lockdowns, and Jobs

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California, CCP Virus, coronavirus, COVID 19, Jobs, Labor Department, lockdowns, New York, public health, states, stay-at-home, Wallethub.com, Wuhan virus, {What's Left of) Our Economy

With the release last week of the Labor Department’s U.S. state-level employment data for December, we have a great new handle on the relationship between the various lockdown and stay-at-home policies mandated throughout the country, and the still horrific toll on job losses during the CCP Virus era.

And as with recent statistics on state-level economic growth (and contraction) rates (see here and here), the numbers seem to point to the economic curbs themselves as the biggest influence on employment levels and changes, as opposed to other factors, like individuals’ virus-induced fear of using various types of in-person services (like travel) and the resulting knock-on effects throughout the entire economy.

One major indication of the mandates’ impact comes, as with the growth figures, from the outsized job losses experienced in New York and California, two states with some of the most severe lockdown regimes imposed over the past year.

In December, 2019, just before the virus began spreading to the United States, New York and California accounted for 18.37 percent of all the nation’s non-farm jobs (the Labor Department’s U.S. jobs universe.) But one year later, their employment losses came to 27.91 percent of the U.S. total.

Additional reasons for blaming the mandates for the employment damage come from comparing the performances the best and worst jobs performers, and the least and most restrictive states. As with the previous post on growth levels, the ranking of mandate strictness comes from the Wallethub.com website. (And sharp-eyed readers will note that the rankings have changed over the last few months, which makes perfect sense since the lockdown regimes’ extent has fluctuated, too.)

First let’s see the Wallethub ranks of the states with the best employment records between December, 2019 and December, 2020. (The lower the rank, the more “open” the state.)

Top 10 job performers (by % change)       Wallethub.com rank

1. Idaho: +0.6                                                          14

1. Utah: +0.6                                                             6

2. Mississippi: -1.4                                                  21

3. Alabama: -1.7                                                      12

3. Georgia: -1.7                                                       18

4. Nebraska: -2.3                                                     17

5. South Carolina: -2.4                                            10

6. Arizona: -2.8                                                       30

6. Arkansas: -2.8                                                       4

6. Indiana: -2.8                                                       20

7. Montana: -2.9                                                     13

7. South Dakota: -2.9                                               2

8. Missouri: -3.1                                                       7

9. Tennessee: -3.2                                                  19

10. Texas: -3.3                                                        28

Right off the bat you’ll see that because of ties, the Top 10 is really a Top 15 – which actually serves our purposes even better. And the big takeaway here is that with one exception (Arizona) and one near-exception (Texas), all of these states rank in the top half on the open/closed scale (26 and lower for the 50 states plus the District of Columbia).

And of these 15 states, four were among the ten most open, and twelve were among the twenty most open.

Does the reverse proposition hold? Have the most closed states generally compiled the worst employment records? Here’s what the numbers say:

Bottom 10 job performers (by % change)     Wallethub.com rank

1. Hawaii: -13.8                                                          43

2. Michigan: -10.9                                                      29

3. New York: -10.4                                                     39

4. Massachusetts: -9.1                                                49

5. Vermont: 9.0                                                           45

6. New Hampshire: -8.8                                             23

7. Rhode Island: -8.7                                                  36

8. Minnesota: -8.3                                                      32

9. California: -8.0                                                       51

9. New Jersey: -8.0                                                     34

10. Delaware: -7.8                                                      33

10. Pennsylvania: -7.8                                                35

10. Oregon: -7.8                                                         37

Because of the “tie effect,” this Bottom 10 set is really a Bottom 13. Four of them fall in the category of ten most restrictive states (ranked between 51 and 41 on the Wallethub scale), and seven more are among the next ten most restrictive states. Moreover, only one state (New Hampshire) has been in the top half of most open states. So the relationship between lockdowns and employment performance looks strong from this perspective as well.

The issue can be examined the other way around, too – by examining the employment performance of the most open and least open states. Here are the results for the ten most open states. (As with the list of ten most closed states below, the Top Ten here really is a Top Ten.) They’re presented in descending order of openness.) 

Ten least restrictive on lockdowns         Job creation rank (out of 37)

Oklahoma:                                                                15

South Dakota:                                                            6

Iowa:                                                                         11

Arkansas:                                                                   5                  

Florida:                                                                    14

Utah:                                                                          1

Missouri:                                                                   7

Wisconsin:                                                               25

Alaska:                                                                    24

South Carolina:                                                         4

Revealingly, fully half of these states were among the ten states with the best employment records, three more were in the next ten. Consequently, eight of the ten ranked in the top half on the openness scale. (Because of the “tie effect,” the top half here starts at number 19 – of 37 differing state rankings).

And although Oklahoma looks like something of an exception here (the most consistently open state being only the 15^th best jobs performer), there’s a pretty simple explanation: Oklahoma’s economy is energy-heavy, and that sector has been absolutely slammed the deep recession experienced during the CCP Virus period.

Florida, which relies so heavily on tourism, has an “excuse” as well. (By the same token, though, it’s no coincidence that the worst employment performer, Hawaii, is tourism-dependent as well, along with fellow job laggards California and, to a lesser extent, New York.)

Finally, the table below shows how the most closed states fared in terms of job loss.  These are presented in descending order of “closed-ness.”

Ten most restrictive on lockdowns          Job creation rank (out of 37)

California:                                                                  31

Virginia:                                                                     12

Masschusetts:                                                             34

District of Columbia:                                                 21

New Mexico:                                                             26

Washington:                                                               18

Vermont:                                                                    33

North Carolina:                                                          10

Hawaii:                                                                      37

Illinois:                                                                      24

Fully four of these ten have been among the five worst employment states during the virus period (including tourism-reliant Hawaii and California). Three more (Illinois, New Mexico, and the District of Columbia) joined them in the bottom half. Of the two exceptions, Virginia’s solid employment record surely stems from its status not only as a state with a strongly growing information technology sector and an army of federal workers (many of whose jobs in turn owe to federal contracting).

One last point should be remembered as well: As extensively documented, the lockdowns and stay-at-home orders have generated their own serious healthcare damage . So the states with the relatively limited mandates surely have curbed both these CCP Virus costs as well as economic damage. Meaning that the already compelling case for anti-virus measures targeting the most vulnerable rather than indiscriminately putting the clamps on businesses and other forms of activity has just grown that much stronger.

Im-Politic: Did “The Science” Give Us the Virus?

Tags

Anthony S. Fauci, bio-weapons, CCP Virus, China, coronavirus, COVID 19, Im-Politics, Joe Biden, lockdowns, National Institutes of Health, New York, Nicholson Baker, pandemics, public health, SARS, stay-at-home, terrorism, Trump, virology, Wuhan virus

That’s a pretty stunning header, I know. But it’s anything but crazy, or even click-baity – at least if you take seriously a long, very serious, and very carefully reported article published January 4 about the CCP Virus’ origins in New York magazine, which hasn’t exactly been an enthusiast for President Trump or science- or China-bashing.

For author Nicholson Baker makes clear not only that for years before the Trump era, America’s top public health officials (who epitomize “The Science” that all the adults in the nation’s room from President-elect Joe Biden on down have anointed as the only valid sources of U.S. and global virus policy advice) pushed measures certain to boost the odds that something like Covid 19 would be created, and somehow escape from, a laboratory someplace in the world – including China.

And notably, one of the main pushers was one Dr. Anthony S. Fauci, Director of the National Institutes of Health’s (NIH) National Institute of Allergy and Infectious Diseases.

It’s important to make clear here what Baker isn’t saying. He isn’t saying that the Chinese manufactured the virus as a bio-weapon. He isn’t saying that Beijing loosed this pandemic on the world on purpose. And he certainly isn’t accusing Fauci and the rest of the public health establishment of acting maliciously.

But what he is saying is awfully damning, and urgently needs to be examined by the incoming Biden administration, the entire U.S. political and policy communities, and of course the public.  For Baker marshalls and summarizes voluminous evidence for the proposition that the most reasonable theory of the virus’ origin is not that in its highly infectious form it developed naturally in some mammal species (like a bat) and then jumped to humans (e.g., at a wet market) – the explanation offered at various times by the Chinese government and by many infectious disease specialists. Instead, the author supports the idea that it was produced by scientists from a naturally occuring mammalian virus, specifically by scientists at one of the three advanced virology facilities in and around the city of Wuhan.

And then, Baker – who is extremely careful to distinguish between facts and suppositions – speculates that “it eventually got out” by hazard. Release via “a lab accident — a dropped flask, a needle prick, a mouse bite, an illegibly labeled bottle,” he emphasizes, “isn’t a conspiracy theory. It’s just a theory.” But he rightly argues that “It merits attention…alongside other reasoned attempts to explain the source of our current catastrophe.”

But where do the roles of the U.S. and global public health establishments come in? During recent decades, as Baker reports, scientists have been conducting “’gain of function’ experiments — aimed to create new, more virulent, or more infectious strains of diseases in an effort to predict and therefore defend against threats that might conceivably arise in nature.” And many of these experiments were funded by the Fauci’s Institute at the NIH. (Similar work was being funded by the Defense Department, whose interest in bio-weapons and fighting them was reawakened by the increase in global terrorism in the 1990s and the prospect that germs like anthrax would be used to advance extremist goals. This threat, of course, materialized right after September 11 with letters containing the germs sent through the mail – in an immense irony – by a U.S. government bio-weapons researcher.)

As implied immediately above, Fauci and his colleagues had the best of intentions. But as Baker documents exhaustively, they ignored numerous warnings from fellow professionals that, in no less than two related ways, they might be creating a problem far worse than that they were trying to solve. First,in their determination to design in the lab super-dangerous bio threats that terrorists hypothetically might some day create and use, they lost sight of how their own experiments could unleash such actual threats in the here-and-now due to the real possibility of leaks (hardly unknown in the world of biological research).

In Baker’s words, “Why, out of a desire to prove that something extremely infectious could happen, would you make it happen? And why would the U.S. government feel compelled to pay for it to happen?” Echoing these worries were numerous scientists, such as Johns Hopkins biomedical engineer Steven Salzberg, who noted several years ago, “We have enough problems simply keeping up with the current flu outbreaks — and now with Ebola — without scientists creating incredibly deadly new viruses that might accidentally escape their labs.”

Second, no evidence has been found yet that any of the coronaviruses that are naturally occuring and that have infected humans (like the SARS “bird flu” – which actually came from mammals – of 2002-03) are remotely as contagious as their lab versions, or are found in animals that often come into contact with humans outside China and its wet markets. In fact, Baker quotes Rutgers University microbiologist Richard Ebright has describing Chinese virologists’ efforts to scour remote locations for animal sources of natural coronaviruses that can be supercharged in a lab as “looking for a gas leak with a lighted match.”

In addition, Fauci arguably magnified these dangers by channeling some of the U.S. government funding for “gain of function” research to the Wuhan virology labs. On the one hand, this decision made sense (as long as gain-of-function was being sought in the first place) because China has been the origin point of so many mammalian coronaviruses, and therefore the home of so many leading virus specialists. On the other hand, safety first hasn’t exactly been a national Chinese watchword.

So the implications for simply “following The Science” seem clear. And they go beyond what should be (but isn’t) the screamingly obvious point that, especially in a field as new and rapidly changing as this branch of virology, there is no “The Science.” Expert opinion almost inevitably will be mixed, and politicians and their journalist mouthpieces flocking to one side while completely ignoring the other is bound to end badly. Matters are bound to end even worse, of course, when the favored faction aggressively tries to stamp out and discredit as “conspiracy thinking” the other’s theories – as Baker shows indisputably was the case with public health authorities and experts (including Fauci) who continue to try absolving the Wuhan labs from any responsibility.

More important, this tale bears out what I and many others have written for months (e.g., here): The pandemic is a crisis with many dimensions – economic and social as well as medical. The public health establishment’s contributions are indispensible. But not only is its expertise limited. Like any other human grouping defined by common characteristics and experiences like fundamental interests and educational backgrounds and occupational environments, this establishment is influenced by its own distinctive unconscious biases and predispositions.

In this case, in Baker’s words, some of the most important are “scientific ambition, and the urge to take exciting risks and make new things.” All of which are perfectly fine and even praiseworthy – in their place.

Further, the medical dimension of the crisis is complex, too, as shown both by all the evidence of major public health costs generated by the lockdown and stay-at-home orders championed so singlemindedly by Fauci and his acolytes, and by the strong disagreements among the virologists and similar researchers laid out in such detail by Baker. So it’s the job of political leaders to take all these considerations into account, not to act as if only one cohort of advisers has a monopoly on wisdom in all relevant areas.

And let’s end on an O’Henry type note. I can’t resist pointing out that President Trump, too, has been one of those U.S. leaders whose administration has robustly funded this gain-of-function research – one of the few instances in which he’s, apparently with no objections, followed The Science.

(What’s Left of) Our Economy: U.S. Manufacturing’s Biggest 2020 Winners & Losers

Tags

aerospace, automotive, Boeing, CCP Virus, computer and electronics products, consumer goods, coronavirus, COVID 19, energy, Federal Reserve, food products, fossil fuels, furniture, housing, industrial production, inflation-adjusted output, lockdowns, machinery, manufacturing, on-line shopping, stay-at-home, travel, wood products, Wuhan virus, {What's Left of) Our Economy

Thanks to last Friday’s release of the Federal Reserve’s report on December U.S. manufacturing production, it’s possible to identify the sector’s biggest winners and losers for inflation-adjusted growth. And their ranks include some notable surprises. (As with all U.S. government economic data, though, there’ll be plenty of revisions over the next few years.)

First, let’s keep in mind that the following categories are pretty broad, including a wide range of products whose performances have varied just as widely. For example, as noted previously (e.g., here), “machinery” contains everything from machine tools to heating and cooling equipment to semiconductor production gear to turbines to construction equipment to farm machinery.

Still, these groupings are specific enough to show how much care is needed when generalizing about the performance of a piece of the economy as big as manufacturing. Moreover, they’re the categories that come early on in the incredibly detailed presentation each month of manufacturing output results deep in the weeds of the Fed’s own website.

With these observations in mind, the five strongest growers (or most modest shrinkers) in manufacturing during 2020 were automotive (vehicles and parts combined) at plus-3.64 percent; food, beverage, and tobacco products (up 0.40 percent), wood products (0.38 percent), computer and electronics products (up 0.14 percent), and non-metallic mineral products (down just 0.52 percent).

The biggest losers? Petroleum and coal products (down 13.34 percent); printing and related activities (off by 10.41 percent); furniture and related products (down 9.86 percent); non-durable miscellaneous manufactures (down 8.57 percent); and aerospace and other non-automotive transportation equipment (an 8.27 percent contraction).

Some of these results were entirely predictable. For example, petroleum and coal products essentially entails the fossil fuels industries, which have been decimated by the overall U.S. and global economic slumps triggered by the CCP Virus, and by the particular hit taken by business and leisure travel. And don’t forget the lingering effects of Boeing’s safety troubles. Moreover, of course those Boeing woes in turn have taken their toll on the aerospace sector.

On the flip side, despite major concern about the strength of America’s food supply chain, it proved impressively resilient. And since Americans didn’t stop eating, real food production expanded – although as the table below shows, its this expansion was much slower than in 2019.

I’m not sure what’s been up with furniture, though, especially considering that the good performance of wood products surely reflects the strength of a domestic housing industry that should have spurred production of furniture. Moreover, so far, the 2020 trade statistics reveal no significant increase in imports.

Non-durable miscellaneous manufactures are something of a puzzle, too. This category includes items like jewelry, silverware, sporting goods, toys, and musical instruments. Since on-line shopping has propped up consumption during the pandemic period, purchases and domestic production of these goods should have remained strong, too – even though many of these sub-sectors have long dominated by imports.

And speaking of imports, a clear sign of their importance is the negligible growth of the domestic computer and electronics industries. It’s clear that the virus and related lockdowns and stay-at-home orders has greatly increased demand for information technology products. But it’s evident that the biggest winners weren’t U.S.-based suppliers. In fact, 2020 growth was way below 2019’s, as the table below shows.

Meanwhile, the solid growth of the automotive sector is pretty remarkable, since the sector literally shut down almost completely in March and April. That looks like awfully strong evidence that much of the economic damage of the pandemic period has stemmed from government restrictions, and not from any inherent weakness in the economy.

In any event, below are the results for all of manufacturing’s main big industry groups, along with the data for the durable goods and non-durable goods super-sectors, and industry overall. For comparison’s sake with the pre-CCP Virus period, I’ve also presented their after-inflation growth for 2019. And a year from now, the final Fed 2021 statistics will permit judging just how complete a retun to normalcy has been achieved.

                                                                              2018-19              2019-20

manufacturing                                                        -1.06                   -2.63

durable goods                                                         -1.70                   -2.97

wood products                                                       +3.58                  +0.38

non-metallic mineral products                               -1.17                   -0.52

primary metals                                                       -2.69                   -7.66

fabricated metals products                                     -1.72                   -5.38

machinery                                                              -2.39                   -3.80

computer & electronics products                          +6.19                  +0.14

electrical equipmt, appliances & components       -1.71                   -1.68

motor vehicles and parts                                        -9.05                  +3.64

aerospace and misc transporation equipment       +0.29                   -8.27

furniture and related product                                +0.34                   -9.86

miscellaneous manufactures                                +0.30                    -3.67

non-durable goods                                                -0.72                    -2.24

food, beverage and tobacco products                  +2.67                   +0.40

textiles and products                                            -2.24                    -5.04

apparel and leather goods                                    -7.50                    -3.64

paper                                                                    -2.37                    -1.91

printing and related activities                              -3.20                  -10.41

petroleum and coal products                               -1.32                  -13.34

chemicals                                                            -2.07                     -1.31

plastics and rubber products                               -3.24                     -0.78

other manufacturing                                           -8.59                      -8.51

(What’s Left of) Our Economy: The CCP Virus Lockdowns’ State-Level US Effects II

Tags

CCP Virus, Commerce Department, coronavirus, COVID 19, lockdowns, shutdowns, states, stay-at-home, Wallethub.com, Wuhan virus, {What's Left of) Our Economy

Yesterday’s RealityChek post presented some facts about the economic performance of America’s states during the CCP Virus era that struck me, anyway, as surprising and important. And it ended with the observation that two big states that have imposed relatively sweeping anti-virus curbs on business and consumer activity – New York and California – accounted for a considerably outsized share of the national economy’s shrinkage during the pandemic through the third quarter of this year (the latest economic statistics available).

Today’s post will use the same data – from a recent Commerce Department report – to show that overall, the states with the most restrictive lockdown etc regimes have generally experienced the biggest economic contractions. That conclusion may sound too obvious to bother thinking about, but it matters because economic distress, as I’ve written repeatedly, produces its own serious public health (both mental and physical costs). Moreover, at least according to most of the public health establishment, even if mass vaccination goes as quickly and smoothly as realistically possible, normality could still be nearly a year off.

As with the previous post, however, some qualifications need to be discussed, and in addition to yesterday’s, two more should be kept in mind. First, despite the connection between CCP Virus-related economic and business curbs on the one hand and slumping economies on the other, there’s a non-trivial number of exceptions, as will be shown below. So it’s distinctly possible that some states have found the kind of balance between still-sometimes (but not always) conflicting economic and public health imperatives that’s worth emulating.

Second, not only have the lockdowns etc been very on-and-off in nature since the pandemic became a pandemic in late winter, but measurements of these lockdowns’ scale unavoidably entail a pretty fair amount of subjectivity.

The source I’m using for this (at this link) looks on-target in general to me. But I have to admit puzzlement at some of the rankings. For example, the source organization, Wallethub.com, places Michigan right in the middle of these rankings – even though Michiganders have been among the most vehement opponents of virus curbs. Have many of the folks directly experiencing this state’s restrictions just been throwing unwarranted tantrums?

Moreover, Maryland, where I live now, has imposed pretty tight restrictions, too, although at least Republican Larry Hogan has been one of those governors who’s given different counties a fair amount of regulatory autonomy since the state (like even many smaller ones) is fairly diverse. But I’m not convinced that overall its curbs have been patchy enough to place it in the lockdowns-light half of states.

Meanwhile, New Mexico is ranked just a little more restrictive than Michigan, though my own look at this state’s policies concluded they’ve been quite lockdown-y.

But nobody’s perfect, so I’m going with Wallethub.com as my lockdown guide, and here’s what I did. First, I looked at the ten states whose economies grew the most (or contracted the least) between the firt and third quarters of this year, and identified where they stand in the Wallethub rankings, and then performed the same exercise with the ten states that suffered the worst contractions. The growth (and contraction) figures represented percentage changes in real gross domestic product, and the Wallethub scale assigns the least restrictive states the lowest numbers. Here are the results:

Top 10 1Q-3Q GDP                                               rank on lockdown scale

Utah: +1.07                                                                            3

Washington: +-0.44                                                             36

Delaware: -0.08                                                                   31

Arizona: -0.52                                                                     45

Iowa: -0.54                                                                            5

Idaho: -0.81                                                                           2

Indiana: -1.01                                                                      15

Georgia: -1.03                                                                     13

Arkansas: -1.27                                                                   10

Alabama: -1.34                                                                   14

The big takeaway? Of these ten states, seven imposed relatively light anti-CCP Virus restrictions

(earning rankings in the lowest half of the fifty states plus the District of Columbia). And four of these states were among the ten least restrictive states. So that looks like solid evidence that the relatively open states were rewarded with the best economic performances, and that this openness as such deserves significant credit. But three states on this list put into effect lockdowns on the tight side and fared relatively well economically, too – Washington, Delaware, and Arizona.

Have they found the policy sweet spot? Or is there something about their economies’ structures that have produced economic resilience? One observation pointing to the importance of structure: both Washington and Arizona boast highly developed tech sectors – Amazon and Microsoft, e.g., headquartering the former, and the latter containing much semiconductor production.

Here are the states with the worst growth performances during the pandemic:

Bottom 10 1Q-3Q GDP                                               rank on lockdown scale

Hawaii: -6.67                                                                              51

Wyoming: -5.24                                                                           7

New York: -4.56                                                                        38

Oklahoma: -3.84                                                                         4

Tenn: -3.33                                                                                18

Alaska: -3.28                                                                             12

Nevada: -3.14                                                                            20

New Jersey: -3.08                                                                     47

Vermont: -3.06                                                                          41

North Dakota: -2.98                                                                   9

And these results seem to cut against those of the previous list – because of these low growers, only four had imposed very restrictive lockdowns (Hawaii, New York, New Jersey, and Vermont). Further, three were among the very least restrictive states (Wyoming, Oklahoma, and North Dakota). And the other three were well in the half of states that have been least restrictive (Tennessee, Alaska, and Nevada).

Nonetheless, economic structure considerations as well as policy measures seem to be influencing these results. Principally, Wyoming, Oklahoma, and North Dakota all depend very heavily on a fossil fuels sector that has been plunged into a deep slump due to the virus’ overall economic effects. And lockdown-light-ish Nevada has suffered from the tourism depression.

Now let’s view the situation from the opposite perspective. Let’s take the states with the ten tightest and ten loosest lockdown regimes, and examine their respective economic performance. First, the ten tightest lockdowners, with the most resrictive at the top:

Most restrictive on lockdowns                                1Q-3Q GDP growth rank

Hawaii                                                                                    50

California                                                                               36

Mass.                                                                                      32

Maine                                                                                     34

New Jersey                                                                             47

Colorado                                                                                 33

Arizona                                                                                    4

Oregon                                                                                   20

Pennsylvania                                                                          37

Vermont                                                                                  41

Here the correlation between policy and performance looks awfully strong. Fully eight of the ten biggest economic loser states are among the states with the tightest lockdowns, and three of these are among the ten most restrictive. Interestingly, Arizona comes across as a standout according to this measure, too.

Economic structure is playing a role here, too – as seen by the presence of tourism-reliant Hawaii and Vermont. In addition, Pennsylvania’s become a big energy state thanks to the Marcellus shale formation, and Colorado has long depended heavily on both energy and tourism.

At the same time, Pennsylvania’s got lots of office workers who’ve been able to do their jobs from home – as does New Jersey (which along with New York was hit early and hard by the virus). And what gives with California – of course tourism-heavy, but in many ways the center of both high tech manufacturing and high tech service provision in the nation, not to mention research and development?

So lockdown decisions seem to have made major contributions to these states’ relatively deep downturns.

A similar conclusion seems justified from this list of the ten states that have permitted their economies to remain most open and imposed the fewest cubrs on behavior – with the least restrictive closest to the top:

Least restrictive on lockdowns                                1Q-3Q GDP rank

South Dakota                                                                     14

Idaho                                                                                   6

Utah                                                                                     1

Oklahoma                                                                         47

Iowa                                                                                    5

Wisconsin                                                                         11

Wyoming                                                                         49

Missouri                                                                           21

North Dakota                                                                   41

Arkansas                                                                            9

Seven of these ten lockdown-lightest states are in the top half of U.S. economic performers, four are in the top ten and one (Wisconsin) is Number 11. Moreover, the three conspicuous exceptions to this pattern – economically woeful Oklahoma, Wyoming, and North Dakota – are all, as previously pointed out, states that have suffered because they’re energy-heavy.

As a result, the way I see it, this table and at least two of the others of the four total presented here, along with yesterday’s state-level data, further strengthen the case that lockdowns per se have exacted major – though far from catastrophic –  economic prices. But by the same token, these results confront the nation with the question of far away the economic tipping point might be. 

(What’s Left of) Our Economy: The CCP Virus Lockdowns’ State-Level US Effects I

Tags

California, CCP Virus, Commerce Department, coronavirus, COVID 19, GDP, gross domestic product, inflation-adjusted growth, lockdowns, New York, real GDP, shutdows, states, stay-at-home, Utah, Washington, Wuhan virus, {What's Left of) Our Economy

One of my coolest holiday gifts came courtesy of Uncle Sam. Not a tax refund or stimulus check, but the Commerce Department’s release last week on “Gross Domestic Product by State, 3^rd Quarter, 2020.”

Seriously.

I always look forward to these data because they enable gauging how developments in the national economy are affecting individual states as well as regions, and vice versa, and this latest report is especially interesting because of all that it says about the economic impact of the highly diverse set of lockdowns and shutdowns and stay-at-home orders and the like that the states have imposed during the CCP Virus era.

This will be the first of two posts on the subject, and I’ll focus on some simple descriptive findings – many of which came as surprises to me. Beforehand, though, it’s important to lay out some warnings against drawing overly tight conclusions between a state’s economic performance and the virus curbs it’s put I effect.

Among the most important:

>The pandemic hit different states at different times, so differences in their growth rates (what these gross domestic product, or GDP, figures are particularly valuable for), in many instances have relatively little to do with their lockdown etc regimes.

>The states have highly diverse demographic profiles (e.g., average age of the population, population density) that can also produce highly diverse economic performances for reasons largely unrelated to economic curbs.

>Different state economies are also dominated by different industries, and as has become obvious, some industries’ health has been decimated by the virus (especially in-person services of all kinds like dining and travel and hospitality, but also energy) while some have held up fairly well (like manufacturing). It’s become just as obvious that many jobs that can be performed at home, and therefore the income and spending they generate have been much less affected by the pandemic than jobs requiring a worker’s presence (e.g., in those in-person service sectors).

>Finally (for now), state economies don’t exist in isolation from each other. Commuters and shoppers often cross state lines when traveling to work or stores, and their businesses often sell their products and offer their services to customers nation-wide – inevitably weakening or strengthening the impact of state-specific curbs.

Still, the new GDP-by-state numbers (which include the District of Columbia) reveal any number of important results since they take the story past the deep second quarter virus- and shutdown-induced downturn suffered by the entire national economy, as well as the strong third quarter rebound.

One big surprise: The entire U.S. economy saw output drop by 2.17 percent in inflation-adjusted terms (the gauge most closely watched) between the first quarter of the year (the last mainly pre-pandemic quarter) and the third. But two states actually managed to grow in inflation-adjusted terms (the gauge most closely watched by students of the economy): Utah (whose economy expanded by 1.04 percent in real terms) and Washington (0.44 percent).

The Washington result was unexpected, at least for me, because its West Coast location placed it closer to the CCP Virus’ origins in China, because the first virus case was recorded there in January (at least as far as is known to date), and because one of its economic crown jewels is aerospace giant Boeing, which has been hit so hard both by recent travel restriction and the safety woes troubling its jetliners.

The worst performing states, in relative (percentage terms) were less surprising. The leader here far and away was Hawaii, whose constant dollar GDP shrank by 6.67 percent) followed by Wyoming (down 5.24 percent by the same measure) and New York (4.56 percent). The Aloha State has of course been victimized by the depression in the travel and tourism industries, Wyoming is energy dependent, and New York collectively caught the CCP Virus early, when so little was known about its virulence and deadliness, and about which Americans were least and most vulnerable.

Oddly, however, the number of states that appear to have been especially hard hit economically between the first and third quarters was pretty limited. Only nine overall experienced price-adjusted contractions of more than three percent. In addition to the three biggest losers above, they were Oklahoma, Tennessee, Alaska, Nevada, New Jersey, and Vermont. And bonus points for you if you see major energy (Oklahoma, Alaska) and tourism (Nevada and Vermont) effects at work here.

Other than that, the economies of eighteen states shrank between two and three percent in constant dollar terms between the first and the third quarters – meaning that, generally, they weren’t far from the national total of 2.17 percent. The rest contracted by less than two percent or (as with Utah and Washington) eaked out some growth.

But this isn’t to say that the economic impact of the virus and related economic curbs haven’t been highly concentrated in at least one respect: A way outsized share of this production destruction has taken place as of the third quarter in just two states: New York and California.  

New York’s the champ here. During the first quarter, its economy represented 7.74 percent of the U.S. total in inflation-adjusted terms. By the third quarter, though, its $67.80 billion contraction represented 16.36 percent of the entire country’s $414.33 billion. In other words, measured by lost output, it punched more than twice above its economic weight.

During this period, California’s real GDP fell by more than New York’s in absolute terms ($74.30 billion). But its economy has long been bigger than New York’s – accounting for 14.81 percent of constant dollar US GDP during the first quarter, or nearly twice New York’s share. So its 17.93 percent shrinkage was smaller relative to the size of its economy than New York’s.

Their combined impact, however, is genuinely astonishing. Accounting for a combined 22.55 percent of the U.S. economy adjusted for inflation in the first quarter, they generated 34.29 percent of the nation’s economic shrinkage – more than a third.

And this is where the lockdown angle comes in: By one gauge of virus-era state economic regimes, (which themselves have almost all been on and off at least to some extent, thereby creating yet another complication) New York’s and California’s were among the strictest. And the next RealityChek post will examine in more detail the relationship these curbs and state economic growth.

Im-Politic: Germany’s Looking Like an Increasingly Tarnished Anti-CCP Virus Gold Standard

Tags

CCP Virus, coronavirus, COVID 19, Germany, Im-Politic, infections, lockdowns, mortality, reopening, shutdowns, stay-at-home, Worldometers.info, Wuhan virus

As the now-well-worn (but still pretty darned good!) wisecrack goes, “I’m old enough to remember when Germany was held up as a model for fighting the CCP Virus.” (See e.g., here and here.) And as this gibe implies, that portrayal of Germany keeps getting exposed as premature.

In fact, by several key grim virus metrics, Germany has caught up with the United States – which of course has just as often been held up as a model for how not to fight the pandemic.

For example, according to the Worldometers.info website, on a per capita basis, Germany’s daily death rate is now greater than the United States’. As of last Friday (I’m skipping the weekend numbers because CCP Virus-related info tends to get reported more slowly on Saturdays and Sundays), Germany’s new reported virus-related fatalities were 30 percent of America’s (838 vs 2,794). Yet Germany’s population (83.91 million) is only 25.28 percent of America’s (331.91 million).

Germany’s performance looks better in terms of seven-day average (7DA) daily figures – which are more accurate because they smooth out the inevitable random daily fluctuations. On December 18, the German figure of 598 was only 23.15 percent of its U.S. counterpart of 2,583.

But major German catch-up has still taken place. And it’s been going on for months. October 16 is when the American 7DA daily fatality total began its latest big move. That day’s figure was 716. So between then and December 18, it rose by 260.75 percent.

October 16 is just before Germany’s current death surge, and that day, the 7DA stood at 21. So through December 18, it’s risen by 2,748.62 percent. That’s more than ten times faster.

The new daily infections numbers tell a similar story. Let’s cut to the chase and examine the 7DAs. By this measure, the United States’ current and worst CCP Virus wave began about October 5, when the daily 7DA stood at 44,691. By December 18, it was up just under 400 percent.

Germany’s current wave (a true second wave) began about the same time, and on October 5, the 7DA for daily new infections stood at 2,292. As of December 18, the figure was 24,460 – a level just over 967 percent above October 5’s, and a rate of increase more than twice as fast as the United States.’

None of this means that Germany’s virus strategy has been a failure, and certainly doesn’t mean that America’s has been a success. In the first place, serious measurement problems continue to plague the infection and mortality data everywhere. (See, e.g., here.)

In the second place, it’s not cricket to compare any geographic regions’ CCP Virus strategies without taking major virus-related differences into account. In this case, it’s crucial to note that temperatures affect the virus’ spread, and that Germany got colder faster, at least between October and November, than the United States.  (For the U.S. data, see here. For the German data, see here.) Germany is also about seven times more densely populated than America, and its relatively crowded conditions alone clearly encourage virus spread. Moreover, it’s not as if Germany has locked down consistently since the CCP Virus’ arrival.

At the same time, the German-American differences in temperatures and temperature changes have hardly been enormous. (Further complicating the weather analysis – the United States’ enormous size also means enormous weather variance from region to region.) And the population density hasn’t changed during this year. So the gaps between these variables can’t possibly begin to explain why Germany’s current surge – albeit from much lower absolute starting levels – has been so much worse than the United States. But they’ve been the statistics used most often to judge virus strategies, so it seems fair to examine exactly what they’ve revealed lately.

Nor does it make sense to blame Germany’s relatively poor performance this fall and winter so far on its various reopenings. Unless you think shutting down an entire national economy for that many months consecutively, with no relief, is a viable approach to a pandemic.

Instead, it’s time to recognize, especially for lockdown and mask-wearing and other mass restrictions enthusiasts, that if – even before the pandemic is one year old – countries with mitigation approaches as far apart as those of Germany and the United States have been so widely labeled can see such completely unexpected infection and mortality results, the establishment conventional wisdom on sweeping behavioral curbs is weaker than advocates insist. And consequently, the best possible tradeoffs between CCP Virus spread and mortality effects on the one hand, and other public health and economic costs on the other, shouldn’t be regarded as set in stone.

Im-Politic: Lockdowns vs Reopening, Apples-to-Apples

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CCP Virus, coronavirus, COVID 19, Democrats, domestic violence, education, Im-Politic, Kristi Noem, lockdowns, mental health, Michelle Lujan Grisholm, New Mexico, Republicans, shutdown, South Dakota, stay-at-home, substance abuse, The New York Times, The Washington Post, Worldometers.info, Wuhan virus

Truth in advertising: The more I look into CCP Virus economic restrictions and regulations on mask-wearing, the more skeptical about their anti-virus power I become. That’s not to say that I believe they have no mitigating effect at all, or even that they have only marginal impacts in absolute terms.

But when it comes to the lockdowns and shutdowns, the evidence keeps telling me that the differences in virus-related outcomes so far between states and countries that have imposed the most and the fewest contain too many inconsistencies (especially during the current second virus wave) to dismiss. And of course the case for them becomes even weaker upon considering the kinds of economic and public health costs they’ve inevitably exacted, and which I’ve been writing about since March.

In terms of mask-wearing, as I’ve explained before, my objections center not on those non-virus costs (because there seem to be none) but on what I’ve called the fetishization of this practice, and the illusions it seems to be breeding.

I’ve been hesitant to weigh in more fully on the debate over lockdowns per se because apples-to-apples comparisons are so difficult to find. Too many entries concentrate tightly on differing restrictions regimes and too few take into account crucial variables like population density and weather and median age of inhabitants After all, all else equal, localities where people are tightly packed together are obviously going to face greater spread challenges in particular than those in which they’re few and far between. Ditto, especially when it comes to the current second wave, for localities where winter begins earlier and settles in more persistently. And it’s by now well-established that the elderly are by far the most vulnerable segment of any population.

Within these United States, however, I think I’ve found two states that have taken radically different anti-virus strategies, and that are pretty similar demographically. And their experiences make a pretty convincing case for the anti-lockdown (and mask) side.

The two states are New Mexico and South Dakota – both largely rural and therefore both thinly populated. Only 17 inhabitants are found per square mile in the former and just ten in the latter. And those in percentage terms, the gap is wide, clearly both are dominated by wide open spaces. (The national average is 87.4 – all these figures come from the 2010 Census.) The median ages of their people as of 2019 is similar, too – 38.6 years for New Mexico and 37.7 years for South Dakota. (The national average was 37.7 that year.)

An initial examination indicates that New Mexico and its Democratic Governor has performed considerably better against the CCP Virus than South Dakota and its Republican Governor – who’s sometimes villified for all but fostering a death cult.

Since the pandemic’s arrival in the United States in sometime near the beginning of this year (or was it late last year?), New Mexico’s cases per million have been just over half those of South Dakota (98,386 as of today, versus 52,435, according to the reliable Worldometers.info website). And its death rate per million has been much lower, too – 837 per million versus 1,256, according to the same source.

But the biggest difference of all? New Mexico has been one of the states that has locked down and restricted most extensively, according to the New York Times‘ compilation of this information. It’s latest batch of restrictions started last month, when Governor Michelle Lujan Grisham ordered non-essential businesses to close, and put into effect a two-week stay-at-home order. There’s been some relaxation since then, but The Times reports that all but one of its counties remains in the most restrictive lockdown phase. Moreover, mask-wearing is mandatory.

In South Dakota, meanwhile, Governor Kristi Noem has never ordered a lockdown or mask mandate.

And given this striking contrast, the differences between the two states’ anti-CCP Virus approaches don’t look nearly so great.

Moreover, they look even less impressive during this second wave period. Even though the pandemic’s human toll in New Mexico has been lower than in South Dakota overall, recently the trends have tracked surprisingly closely.

South Dakota’s current case surge began October 6, when the seven-day average of daily recorded new infections was 409. This figure peaked November 14 (having risen by 256.48 percent during those five weeks), and since then has fallen by 40 percent, to 875 as of yesterday.  (These figures come from the Washington Post ‘s excellent searchable database.) 

New Mexico’s current case surge began three weeks later (November 1), at a seven-day daily average of 767 new infections. It peaked just three weeks later, on November 23, at 2,671 – and its rate of increase was only slightly slower than South Dakota’s. Since then, through yesterday, it’s down a little faster than South Dakota’s (43.69 percent).

Also undercutting the “death cult” charges: South Dakota’s weather began turning colder about two weeks before New Mexico’s, and has stayed colder since. The patterns for both states have been pretty choppy, but you can see the details at this database. (I looked up the info for Pierre, South Dakota, and Albuquerque, New Mexico, specifically.)

Over the next two weeks, the U.S. government will be releasing data that will provide a much clearer, up to date picture of the CCP Virus’ state-level economic toll (through November for employment, through the third quarter for growth) – and an indirect indication of its non-virus health (especially mental health and substance abuse-related) and social costs (e.g., domestic violence, children’s educational achievement). These figures will permit pronouncing a much more comprehensive, convincing judgment as to whether policy cures implemented for the virus have been better or worse than the disease.