In my previous post, I linked to a Tyler Cowen post that quoted Betsey Stevenson:

The problem is that old jobs are long gone for the vast majority of those who remain unemployed.

In a narrow technical sense that may be true. But according to Yahoo, this is also true:

More signs of labor shortages emerged, with employers scrambling to find qualified workers to fill positions and meet surging demand during the post-pandemic recovery. The Bureau of Labor Statistics reported that job openings soared to a record more than 9 million in April. And a separate new sentiment survey showed a record 48% of small businesses reported that they had unfilled job openings last month.

Meanwhile, the BLS says workers are suddenly quitting their jobs at record rates.

And yet unemployment is still 5.8%, far higher than in 2019. This is a really weird labor market.

PS. I wonder if the quit rate is linked to recent reports of some companies offering considerably higher wages? Workers may be shifting from one job to another. If so, the wage increases may spread.

PPS. Today, I’m even more skeptical of UBI than I was last year.

PPPS. I recently spoke with a college student who within the past 5 weeks received $3800 in stimulus checks. Summer job? Not this year.

Roughly 49% of the US population has not received at least the first dose of a Covid vaccine. Total employment is down 7.6 million from early 2020. Should we conclude:

1. The 160 million unvaccinated Americans have searched and searched and just can’t find any location willing to offer them a vaccine. (Or that perhaps it’s too expensive for them to afford.)

2. The unemployed have searched and searched and just can’t seem to find any employers who are looking for workers. (But not teens, they are having no problem finding jobs.)

Speaking for myself, I’m inclined to doubt both hypotheses. I suspect that there are other factors that explain the surprisingly large number of unvaccinated and unemployed.

Perhaps some people don’t want to be vaccinated. Perhaps some people don’t want to be employed.

PS. Tyler Cowen quotes Betsey Stevenson making this claim:

The problem is that old jobs are long gone for the vast majority of those who remain unemployed.

Perhaps the old jobs are permanently gone. Or maybe it’s the old workers that are temporarily gone.

Here’s The Economist, discussing the woes of the Labour Party:

In their recent book “Brexit Land” two academics at the University of Manchester, Maria Sobolewska and Robert Ford, argue that today’s political divide is cultural rather than economic. The university-educated classes define themselves by their cosmopolitan values—their enthusiasm for immigration and fierce hostility to racial and gender-based prejudice. Voters from the old working-class define themselves by their fealty to “traditional values” of flag, family and fireside. And a large new Labour block—immigrants and the children of immigrants—usually sides with the first group despite being more culturally conservative. Originating in long-term changes such as the expansion of the universities and the rise of a multicultural society, the division has been supercharged by Brexit.

Another article in the same issue points out that Labour’s problems are compounded by the fact that the “electoral geography” favors the Tories:

Culture matters too. Mr Johnson has offended the sensibilities of the liberal professionals whom Mr Cameron wooed. A hard Brexit, tougher migration rules that restrict the supply of European au pairs and restaurant staff, and cuts to foreign aid all run against the grain of these areas.

But gains in these areas alone would not provide Labour with a viable path to power. The party needs to gain 128 seats at the next election to get a majority. The graduate vote is concentrated in urban areas, giving it big margins in cities but not elsewhere. Analysis by Onward, a think-tank close to the Conservatives, suggests that changes in electoral geography mean the Tories could gain another 50 seats at the next election, while simultaneously losing 37 mostly in their southern heartlands. 

And the Tories aren’t satisfied with their advantage in electoral geography, they also want to make it harder to vote:

American-style voter ID laws are coming to Britain

They will have almost no effect on fraud, because there is hardly any

Seven local authorities asked voters for various forms of identification in May 2019, after warning that they would be doing so. On average, 0.4% of would-be voters who were asked for id failed to show it, were turned away, and did not return to the polling station.

But many more might conclude that voting has become too much of a hassle, and not bother. “Not everyone gets as excited about elections as we do,” says Jess Garland of the Electoral Reform Society, which opposes the change. Any effect is likely to be uneven. A poll for the government found that 10% of non-white people would be less likely to vote in person if they were required to show photo id, compared with 5% of whites.

Remember, this is not the USA.

Another issue of The Economist looks at Mexico’s new president, a man of “the left” (as if these terms still have any meaning):

Mr López Obrador has attracted far less global attention than other populist leaders. But look closer and he appears astonishingly similar to them (see table). In his eyes, Mexicans fall into two groups: the people, whose authentic will he represents, and the elite, who are to blame for all Mexico’s ills. He sees himself as on a historic mission to sweep away the rotten habits of the past and establish a republic of virtue.

Inside the same issue, The Economist shows that in 1970, right-of-center parties received support from people with higher levels of education and higher incomes:

Today, right wing parties receive support from people with lower levels of education and higher incomes:

Show me a non-college educated business owner and I’ll show you a Republican. Show me a PhD making under $50k and I’ll show you a Democrat.

There are two types of people who accuse me of TDS. Those who say that Obrador, Bolsonaro, Modi, and Orban are obviously evil, but Trump’s not like that. And those who claim that Trump is similar to the other populists, but they are not in fact evil. I see both types in my comment section. Both are wrong.

While I’m only 275 pages into Ed Nelson’s big 2 volume set entitled “Milton Friedman & Economic Debate in the United States”, I can already say that it’s one of my favorite books on macroeconomics.

One issue that has frequently puzzled me is how to interpret causality in the Phillips Curve relationship. I have always interpreted Friedman’s natural rate model as one where causality went from inflation to output. More specifically, if inflation is higher than expected, then unemployment will be lower than the natural rate, and vice versa (perhaps due to sticky nominal wages.)

Keynesians usually seem to interpret causality in the opposite direction, low unemployment causes high inflation, and vice versa. And today, that seems to be the most widely accepted interpretation. Nelson (p. 273) quotes Friedman offering an interpretation that is consistent with my view:

There was, however, a crucial difference between Fisher’s analysis and Phillips’s, between the truth of 1926 and the error of 1958, which had to do with the direction of causation. Fisher took the rate of change of prices to be the independent variable that set the process going.

But Nelson also cites other statements by Friedman that are consistent with the Keynesian interpretation. He then suggests:

Friedman was also clear that both inflation and unemployment were endogenous variables. That being the case, neither a story based on causation from unemployment to inflation nor a story based on causation from inflation to unemployment can be accepted as a comprehensive description of the Phillips Curve relationship.

You probably know what I’m going to say. What’s really going on is that both inflation and unemployment are affected by NGDP shocks. When NGDP rises faster than expected, it increases inflation and reduces unemployment. When NGDP rises slower than expected, inflation tends to fall and unemployment rises. But what does Nelson say? How does he reconcile various statements by Friedman that seem inconsistent?

The answer offered here is that Friedman’s perspective was that, although inflation and output were jointly determined, the former variable could in large measure be usefully regarded as the driver of the relationship because inflation is a nominal variable and hence ultimately policy determined. Fluctuations in output (in relation to potential) would not occur if the private sector’s expectations of nominal variables corresponded continuously to the actual paths.

I really like this explanation. In Chapter 1 of my book coming out in July, I discuss the tricky issue of causality in macroeconomics. In the end, I conclude that statements about causal relationships should be judged on their usefulness. Thus it’s useful to say that monetary policy caused the Great Recession if another plausible setting of monetary policy instruments would have prevented the Great Recession, but not otherwise.

While Friedman is my favorite macroeconomist, I don’t believe that he got everything right. Like most people of his generation, he focused a lot of attention on inflation. And yet in many cases, his analysis makes more sense if you substitute NGDP growth for inflation. Thus his claim that a slowdown in inflation almost always results in higher unemployment would be more accurate if applied to a slowdown in NGDP growth. After all, inflation can slow due to a positive supply shock.

I’ve recently discovered another Ed Nelson paper on whether it makes sense to think in terms of “nominal shocks”, and will have more to say on this issue in a future post.

PS. Friedman’s quote is referring to a 1926 paper by Fisher that first developed the so-called “Phillips Curve”. It was rediscovered by Phillips in 1958, who gave it a Keynesian interpretation. Both Friedman and I prefer Fisher’s interpretation.

Back in 2014, there was a vigorous debate over gain-of-function (GoF) research. Prestigious journals published articles showing that this research is extremely dangerous, and probably should not be allowed:

First, from the calculations in two in-depth pandemic risk analyses (7–9), there is a substantial probability that a pandemic with over a 100-million fatalities could be seeded from an undetected lab-acquired infection (LAI), if a single infected lab worker spreads infection as he moves about in the community. From the Klotz (2014) analysis, there is about a 1–30% probability, depending on assumptions, that, once infected, the lab worker will seed a pandemic. This large probability spread arises from varying the average number of people infected by an infected person between 1.4 and 3.0 (R₀, in standard epidemiology notation), varying the details of commutes to and from work on public transportation, and whether infected acquaintances are quarantined before spreading infection. The Merler (2013) study, based on a computer-generated population grid of size and varying density of the Netherlands, supports our concern over a lab escape not being detected until it is too late: “there is a non-negligible probability (5–15%), strongly dependent on reproduction number and probability of developing clinical symptoms, that the escape event is not detected at all.”

These concerns were not completely ignored. The US stopped funding gain-of-function research in 2014. However, the moratorium was lifted in 2017.

Former NYT reporter Donald McNeil says there have already been serious lab leaks:

Despite constantly rising biosafety levels, viruses we already know to be lethal, from smallpox to SARS, have repeatedly broken loose by accident.

Most leaks infect or kill just a few people before they are stopped by isolation and/or vaccination. But not all: scientists now believe that the H1N1 seasonal flu that killed thousands every year from 1977 to 2009 was influenza research gone feral. The strain first appeared in eastern Russia in 1977 and its genes were initially identical to a 1950 strain; that could have happened only if it had been in a freezer for 27 years. It also initially behaved as if it had been deliberately attenuated, or weakened. So scientists suspect it was a Russian effort to make a vaccine against a possible return of the 1918 flu. And then, they theorize, the vaccine virus, insufficiently weakened, began spreading.

Even worse, these sorts of lab accidents are fairly common. This is from a 2015 comment on a research paper:

The 1977 H1N1 virus caused a global epidemic, and as Rozo and Gronvall themselves concluded, it originated in a microbiology laboratory and its release was unintentional. Which laboratory is responsible matters little in the GoF debate.

Rozo and Gronvall also stated that, “in 1977, influenza research was performed without modern biosafety regulations and protective equipment, making the lab accident hypothesis much less relevant to the modern GoF debate.” However, the current record of containment of high-consequence pathogens is hardly reassuring.

My review of 11 relevant events (2) found that escapes of high-consequence pathogens causing community infections typically occur from state-of-the-art laboratories, including six outbreaks of severe acute respiratory syndrome and one of foot-and-mouth disease since 2003. [Emphasis added]

Tyler Cowen argues that proof of the Chinese lab leak theory would be a big blow to the prestige of the Chinese government. (Not for me, I already had an extremely low opinion of the CCP.) I think Tyler is right, but Thomas Frank argues that the biggest effect would be to discredit the global scientific establishment:

The last global disaster, the financial crisis of 2008, smashed people’s trust in the institutions of capitalism, in the myths of free trade and the New Economy, and eventually in the elites who ran both American political parties. . . .

Now here we are in the waning days of Disastrous Global Crisis #2. Covid is of course worse by many orders of magnitude than the mortgage meltdown — it has killed millions and ruined lives and disrupted the world economy far more extensively. Should it turn out that scientists and experts and NGOs, etc. are villains rather than heroes of this story, we may very well see the expert-worshiping values of modern liberalism go up in a fireball of public anger.

It isn’t just that we were doing the same sort of dangerous research as the Chinese, we were actually funding the Wuhan lab. But it gets worse. Another former NYT science reporter (these guys get cancelled pretty often) suggests that the global community of virologists have been less than completely honest with the public. Here’s Nicholas Wade:

By this criterion, the signatories of the Lancet letter were behaving as poor scientists: They were assuring the public of facts they could not know for sure were true.

It later turned out that the Lancet letter had been organized and drafted by Peter Daszak, president of the EcoHealth Alliance of New York. Daszak’s organization funded coronavirus research at the Wuhan Institute of Virology. If the SARS2 virus had indeed escaped from research he funded, Daszak would be potentially culpable. This acute conflict of interest was not declared to the Lancet’s readers. To the contrary, the letter concluded, “We declare no competing interests.”

Virologists like Daszak had much at stake in the assigning of blame for the pandemic. For 20 years, mostly beneath the public’s attention, they had been playing a dangerous game. In their laboratories they routinely created viruses more dangerous than those that exist in nature. They argued that they could do so safely, and that by getting ahead of nature they could predict and prevent natural “spillovers,” the cross-over of viruses from an animal host to people. If SARS2 had indeed escaped from such a laboratory experiment, a savage blowback could be expected, and the storm of public indignation would affect virologists everywhere, not just in China. “It would shatter the scientific edifice top to bottom,” an MIT Technology Review editor, Antonio Regalado, said in March 2020.

In 2008, I became disillusioned with the field of macroeconomics. In my view, macroeconomists caused the Great Recession by not emphasizing that at each an every point in time the Fed needed to set monetary policy at a position expected to lead to on target growth in aggregate demand. When economists inside and outside central banks failed to correctly diagnose the problem in 2008, policy became highly contractionary and the global economy collapsed.

The scientific establishment needs to avoid doing research that could lead to the death of 100 million people. It’s that simple. And this is true regardless of whether of not Covid came from a Wuhan lab.

The scandal is not the fact that Covid came from a lab (which we don’t know yet, but seems doubtful), the real scandal (if there is one) is that Covid could have come from a lab. That in itself would be totally unacceptable. Some people would probably be reassured by this:

Shi breathed a sigh of relief when the results came back: none of the sequences matched those of the viruses her team had sampled from bat caves. “That really took a load off my mind,” she says. “I had not slept a wink for days.”

Her lack of sleep makes me even more nervous. Is this research really that dangerous?

On the other hand, most evidence still points toward a natural origin for the Covid-19 virus. If Covid-19 is eventually found in nature, it will be a huge black eye for the US and a huge PR coup for China.

PS. Our regulators are probably far too risk averse when it comes to nuclear power, and nowhere near risk averse enough when it comes to virus research.