Stimulus Misgivings

President Biden said publicly last week:

... There is a consensus among economists left, right, and center that is over -- and including the IMF and in Europe, that overwhelming consensus is, in order to grow the economy a year, two, three, and four down the line, we can’t spend too much.

Put bluntly, this lie is Trump-worthy in scale. 

My view is that there is a consensus amongst politicians that they like having an excuse to spend more money.

Check out this piece from Olivier Blanchard. He's a macroeconomist from MIT who most definitely is not on the right of the political spectrum. It's entitled "In Defense of Concerns Over the $1.9T Relief Plan".

Blanchard does some "back of the envelope" calculations. His high end estimate of the size of the output gap for the U.S. at $900B. He also notes that the current Biden proposal of $1,900B comes on top of December's stimulus package of $900B. If $2,800B is what is needed to fill a $900B output gap, this implies a multiplier of less than a third. Blanchard does not find that credible, and thus concludes that the Biden plan will overstimulate the economy.

The side effect of overstimulation is inflation. Blanchard predicts it will go up if Biden's plan is passed. 

Having said all that, he does understand the politics involved:

There are the political realities: a window of opportunity that may close in the future, the advantage of a hot economy during the midterm election season, the notion that sending Americans anything less than $1,400 dollar checks would be reneging on a promise; and there are other economic issues I have not discussed: what private demand would have been in the absence of the package, the timing of state and local government spending, the room the stimulus leaves for an infrastructure program, the ability of the Fed to control incipient inflation, and so on. All these issues are relevant and need to be discussed.

Even so, he concludes: "In the end, if the full package passes, it may be that everything turns out fine, but this is not my central scenario."

Blanchard is not the only economist on the left that is worried about the Biden proposal. Larry Summers and Jason Furman have also voiced their concerns.

Politicians and COVID-19 Lies

(I am trying to reduce COVID coverage this semester. This is a follow-up).

Over the last year, I documented a lot of cases of politically motivated lying about COVID-19 cases and deaths. This was both in the U.S., and elsewhere.

And, keep in mind, some of this may not be lying at all, but rather an inability of local sources to keep up with new information.

The important one from this past month is the apparent cover-up in the state of New York. 

I am not versed on the background numbers on this, but I did live in New York until I was 24, and I still have close family there. It has always been my impression that their system of state-supported nursing homes is thicker than in other states, and that there seemed to be a policy of more readily triaging the stable out of hospitals into nursing homes. 

This became a problem last spring: nursing home patients would contract COVID-19, they'd be checked into a hospital, they'd get stabilized, and then sent back to the nursing home where they'd infect more people.

Healthcare professionals were aware that this might spread the infection, and asked for a new policy. But, a political decision was made on March 25th to require nursing homes to follow the old policy. No doubt this was to reduce workloads at jammed hospitals. Anyway, a lot more seniors in New York died than in other states, due to this policy.

Here's the thing: the Cuomo administration was asked directly for information on the results of this policy. And they both fibbed about the numbers, and stalled releasing the correct ones for six months. Now there's a report out showing that the policy probably led to around 1,000 excess deaths.

This is a big deal because Governor Cuomo was probably the American politician who created the most positive impression with his ability to handle the crisis. Now that whole thing has been called into question, and as is usual in politics, the cover-up may be worse than the original sin.

Have I Got an Infographic for You!

Part of the problem with uniting Europe is that Europe isn't very united. 

The most obvious manifestation of this is that the Eurozone (where they use the Euro as their currency) does not include all countries in the EU, but also contains countries not in the EU.

It gets worse:

 

What the heck is all the extra stuff? The EU Customs Union are the countries that have no tariffs between them. The EEA is the set that allows free movement of goods and people across borders. The EFTA is a group that has free trade between them (no tariffs or regulatory restrictions on goods crossing borders). The Schengen area is where there are no border crossings where you might have to present a passport.

Texas: The Other Shoe Drops

Part of the problem in power supply and demand everywhere, but which is becoming obvious in Texas, is that both demand and supply are inelastic. This means that small shifts in one or the other lead to huge price increases.

Electrical utilities need to keep the juice flowing, when they can. Blackouts and brownouts are part of that mix. But so is buying any power that's available on the spot market.

And in Texas, customers can choose fixed or variable rates for their electricity. Variable rates are generally lower, until they're not. There are now reports coming out of people getting bills for thousands of dollars in their monthly electricity bills as the power retailers recoup some of the high costs incurred for wholesale power this past week (where reports of prices 360 times normal were reported).

And Even More On Texas

Marginal Revolution put out a bleg for informed commentary about the situation in Texas.

The action is all in the comments. There is some devolution into name calling, but not much.

I learned stuff from:

• peri: Agreed. I lived in four homes in two parts of the southeast for 11 years. The house construction is not good.
• bart johnson: I had not heard of capacity payments. That sounds a little like my GoT suggestion, only more civilized.
• Walter: the first half was good, but I thought the second half finger-pointed a lot.
• Nonlinear Power: notes the incentives in Texas aren't great, but Alberta has similar ones and has no problems, so he blames the weather.
• DiodeWest: notes that ERCOT (the Texas grid) is all about low cost, and not quality
• Andrew Adams: if power is so cheap in Texas, why haven't the savings gone to quality?
• RF_Austin: is not correct. There is a price cap, but it is insanely high and not likely to be binding (except of course in a crazy storm). From what I read about it, it's so high that it looks like the biggest default value they could code in (I think it was $9,000 for something that is usually $25)
• KSC: retail customer loyalty is low in Texas. In most places, you're locked in to your utility.
• PHinton: an excellent point about how you have to be more reliable the bigger your share of the market, and wind isn't where it needs to be on that.

One commenter recommend this post from StreetWiseProfessor, which I liked. The bit about negative prices is new to me with renewables, but the economics of this are well-known, and they are not pretty. 

Derrill Watson, a professor at Tarleton State (whose CV makes me think he might know Swigert and Price) writing at Notes On Liberty, has a pretty good discussion for his principles students.

Daniel Cohan has a tweet storm pinned to the top of his Twitter page. He makes a number of good points. One of the things he notes is that current battery capacity within ERCOT is 0.3% of peak usage. He's also all over the details ERCOT's scenario analysis, and argues they weren't too far off the mark with their worst cases. He is rough on the failure of the gas power generation industry, and the problem created because there's competition for the resource from the gas heating industry. He slams coal (and rightfully so) ... but he does the really bad thing of saying that we need to replace it with something more reliable. Like what, unicorns??

A Little More On Texas

I forgot to link to this post that was on Marginal Revolution this week. May as well quote it in full now:

Myopic Voters and Natural Disaster Policy

by  Alex Tabarrok February 18, 2021 at 7:31 am in

• Current Affairs
• Economics

Do voters effectively hold elected officials accountable for policy decisions? Using data on natural disasters, government spending, and election returns, we show that voters reward the incumbent presidential party for delivering disaster relief spending, but not for investing in disaster preparedness spending. These inconsistencies distort the incentives of public officials, leading the government to underinvest in disaster preparedness, thereby causing substantial public welfare losses. We estimate that $1 spent on preparedness is worth about $15 in terms of the future damage it mitigates. By estimating both the determinants of policy decisions and the consequences of those policies, we provide more complete evidence about citizen competence and government accountability.

From the now classic paper of the same title by Andrew Healy and Neil Malhotra. As Neil said on twitter “It becomes depressing tweeting out this article after every instance of government failure,” but there you go. 

Google Scholar says that paper has gotten almost 700 cites in the 12 years it's been out. That's pretty good.

In this case, winterizing isn't good politics, but cleaning up after the disaster probably will be.

Texas' Power Problems

Texas, Texas, of all places is having energy problems this week.

There is a lot of misinformation out there about what is going on. Here's my advice: do not trust the politicians for accurate information, and don't trust anyone who seems to favor one source of energy over another. Instead, go to the Energy Information Administration, part of the Department of Energy in D.C., which is the best source for data on these things.

My other advice is: think like an economist. Please.

So let's figure this out.

• You never heard of energy problems in Texas before. That makes this an acute rather than a chronic problem. Of course, it is weather related, but you probably knew that already.
  
• It's mostly a problem of electricity. Many households from Texas and through the southeast do not have furnaces. Instead they have heat pumps, which are kind of like a reverse air conditioner. So, no electricity means no heat.
  
• The U.S. infrastructure has 3 electrical grids for the transmission of power within the grid (transfer of power from one grid to another is not done on a large scale). The smallest of these covers most of Texas. It's just as cold in Oklahoma, and Arkansas, but there's no problems there because they are on a different grid. Hmmm ... there's a clue ... decisions were made within the Texas system that are turning out uniquely badly in this acute weather situation.
• Much colder parts of the world do not have trouble with heating. So the problem isn't really with the absolute level of coldness, but with the relative coldness in that particular region.
• Most people don't get a basic feature of energy: we deal with it in steps (or stages). Generation (and pollution) happen in one step. Storage (and accident risk) happen in another. Usage is in a third. For example, if your car uses gas, it does storage then generation then use, while if it is an electric car it does generation (remotely) then storage then use. Some forms of energy are preferable because of features of their generation, while others are preferable because of features of their storage.
• Batteries are a joke. This is how we store electrical power. They are an old technology (predating the internal combustion engine by about a century) that has never worked well. Yes, there have been big improvements in them in recent decades. But think about it: you do not have anything around your house that requires much power (like microwaves and hair dryers) that uses batteries. Cars are not really an exception: they spend much of their stored power to move the battery; moving the lightweight humans is a bonus. This is a longer point, mostly to get you to this: for electricity, storage is not much of an option. So the problem combines insufficient generation and lack of storage.
• This is a weird one. For all its oil wells, Texas doesn't use much oil for heating or power generation. Go figure.
• A lot of fingers are pointed at Texas' huge investment in windmills. It is true that the windmills are not running (and, it's a winter storm, there is no shortage of wind). The thing that most people do not realize is that the windmills rely on a energy from other sources: they're machines just like anything else and they run better when they're warm. If you can't store electricity, you can't keep a windmill warm with a windmill. You could do it with windmills in other warmer locations, but then you run into the problem that Texas is its own smaller grid. The Wall Street Journal pwned this one with data from the EIA: most of the windmills were shut down before the storm hit to keep from damaging them.
• Do note that other sources, particularly gas and coal, were ramped up when the windmills were shut down ... just apparently not enough. 
• Also, keep in mind two essential facts about scale. First, there isn't that much renewable energy production. No matter how much you favor renewables, it is inadvisable to view power generation as anything other than gas, coal, and nuclear. Be realistic about this one (but on the good side, it means that wind isn't really the source of problems). Second, the renewable energy industry is sneaky on this one: almost all renewable energy totals are dominated by hydro. Wind and solar sound cool, but it's really mostly big dams that we don't build much any more.
  
• It's not just wind that is having problems with the cold. There are issues with gas and nuclear too. This is where the economics comes in. There was a tradeoff here: winterization is expensive, and decision-makers in Texas did not put enough money into that. This is related to the relative cold mentioned above: places that are colder choose more winterization. Keep in mind that energy generation is a heavily regulated industry, and that the grid itself is a public entity that's merely kept at arms-length by bureaucrats who don't want you to know that everything comes back to them (sort of like Fannie Mae in 2007).
• It isn't huge, but it isn't nothing either: homes that have furnaces in Texas mostly have gas. So cranking up the furnaces puts strain on the amount of power from gas that can be used for other things.
• In general, there is no shortage of power in Texas, or inadequacy of the grid. Cooling in the summer in Texas requires a lot more energy than heating in the winter. But there's an acute shortage right now. Part of this is the winterization issue, and part of it that if you're busier in the summer, you do all your repairs in the winter, decreasing your flexibility. That again is sound economics. But if this is sound tradeoff, what's unsound?
• It's back to storage! It's not exactly like this, but essentially all the electricity everywhere was generated in a plant somewhere else about a second ago. Wind and solar can't be stored (solar is nice, but it provides power at the wrong time of the day). Natural gas is also largely unstorable. Hydro power can be stored, but Texas is pretty flat and dry and doesn't have much within its grid. Oil can be stored more readily than natural gas, but again there's the issue that all those potentially explosive tanks don't actually hold much relative to usage.

You can probably see where this is going. I think I've been pretty clear in arguing that the problem is not wind power. What it is, instead, is that the people who love wind also hate coal and nuclear power. And without advocating for them too much here, the economics is like this: wind (and other sources) might be preferable for generation because of their lower pollution, but that's only half the tradeoff. And if you have a tradeoff (in anything), and you're only focused on half of it ... you're probably going to come out the loser. Where coal and nuclear are better is with storage. In your life, if you have considered pollution problems but not storage problems, you may have been misled.

OK, so what about nuclear. This is the one that almost all the time is the safest and most reliable. But again, the problem is the tradeoff: when there's a problem it scares the sh*t out of people. And, if you look into the history of nuclear accidents, they're almost always about some human or mechanical part failing when they cranked up or cranked down the power. So this is not going to help anywhere, including Texas, with acute problems. Nuclear is what you ought to use for your baseline of some high percentage of peak usage. Who does this? France.

And that leaves coal power. You do not have to like coal power. You do not have to use it much. But you have to realize that it like having a woodpile and wood burning fireplace in your home. You only have to maintain it for when you need it. And if you're worried about pollution, the way to mitigate that is to run your coal plants at close to 100%. When you don't need them, you shut them down completely (and this is exactly what the power industry does, and has for decades). Coal is also the most storable energy source: no pipelines, no tanks, just big piles of rock that aren't as flammable as other stuff, and that don't flow away when you're not watching them. Coal also needs the least winterization: if you can warm up the conveyor belt you are good to go, and you can do that by dumping coal into the burner from a truck to get the heat going (you can even make the trucks electric if you like).

And in Texas this week, while coal power production ramped up, it didn't ramp up very much. Again, use your economics: it didn't ramp up much because it was already running at capacity. How would you test that? By looking at whether energy production from coal is fairly stable or not. Here's the EIA:

Coal power should. not. be. stable. It is the one that you can turn off if you don't like it, but you should also be able to turn it on when needed. And that's not what's happened at all.

BTW: the chart is a cool one to examine, because it shows both the low power from residuals, but also the ups and downs in demand that are mostly met by gas and hydro ... because solar actually makes the ups and downs worse (solar is procylical, gas and hydro can be countercyclical if they need to be, and so can coal if you let it).

N.B. TF brought up the very good point in class that the heat pumps common in Texas really don't work very well once the outside temperature gets below about 40. For the economics above, this means it is much more likely for residences to put a draw on the natural gas distribution system (to run the furnaces they do have), but this will pull gas out of the electrical power generation system which is the thing that's not performing well.

Update. I forgot to put in a link to the graph. You can't direct link to it. Instead, you go to the EIA's Data Tools, Apps, and Maps page, and then double-click on the tile entitled Hourly Electric Grid Monitor.

Relative Fiscal Stimulus

The Biden administration and Democrats in Congress are closing on passing a new fiscal stimulus package.

As always, an economist should be asking, compared to what? Greg Mankiw posted this chart drawn from Moody's Analytics:

Do note that this is scaled by GDP, so this is showing that the 2 stimulus packages passed so far are already more generous than those in every other large economy except Japan. Reasonable estimates of the size of our third package will blow right past Japan.

And, of course, as the largest economy in the world, the close to largest percentages of the largest economy indicate that our government has already gone bigger than everyone else.

N.B. While the cases and deaths in the U.S. are large, we are the third most populous country in the world. Relatively speaking, our pandemic is objectively not worse than most of the other countries on this list.

You Trade Most with People Who are Physically Closer, and Most Like You

Visual Capitalist posted a chart of the UK's trade relationships with the EU members. A chart like this could be done for just about any country.

 

Also, rather obviously, countries also trade most with whomever is economically biggest: bigger economy tends to mean more trade.

So, not surprisingly, the UK trades the most with Germany: it's big, it's fairly close, and it's culturally similar to the UK.

France and Italy are the next two biggest countries in the EU, and the UK trades less with them because they're smaller. They're also more culturally similar to each other, than they are to the UK, which will tend to decrease trade. Italy is further away than France, so it's lower on the list.

The UK, the Netherlands, and Germany share a more Germanic culture, language, and majority Protestant background. On the other hand, Belgium shares with France and Italy a Romance language and "latin" culture, and majority Catholic background. So, the Netherlands is a bigger trading partner than is Belgium, even though the countries are comparable and Belgium is closer.

The other big trading partner is Ireland. Different culture, different religious background, but a mostly shared language. AND, Ireland is the only country that shares a land border with the UK, and it's also the fairly close over water, so, lots of trade there.

Alternatively, if you look down towards the bottom of the list, you see mostly countries that have a Slavic rather than a Germanic language, most of which are further away, and smaller, with a religious background that is sometimes Catholic and something Eastern Orthodox. The UK doesn't trade much with those countries, but there are exceptions. Cyprus and Malta, are the two smallest countries in the EU. And yet they are not at the bottom of trade with the UK. Why is that so? Probably because both of them spent time as colonies of the UK!

FWIW: a model in which trade depends on distance is called a "gravity model". Paul Krugman (who now writes an opinion column for The New York Times) won a Nobel Prize for its development.

List of GDP Stats

In class I showed a bunch of these. There are more. I'm not concerned about you knowing all this stuff. It's just lists of facts after all. The bigger point is that you should know that these things exist and you can go find them if necessary.

Here's what I showed you in class:

• List of U.S. states ranked by GDP (you should know the big four, and the areas of the country where the poorer states tend to be located).
• List of U.S. metropolitan areas ranked by GDP (you should know the big three, and be able to name a bunch of the top 10 or 15.
• List of U.S. counties ranked by GDP (you should know that this exists, that New York county, New York City, and New York state are not similar at all, and maybe the names of a few prominent counties around the country. For example Harris County was in the news about mail in voting quite a bit back in October, but it would be natural for someone to say "who the heck cares about some county down in Texas", but it would be missing why that county is important. It's also important because of the counties that are very big economically, but really don't have a major city in them, like Orange County, and Fairfax County).
• List of world metropolitan areas by GDP (you should know the big ones, but also the surprises on the list: that Tokyo is huge, that Seoul is one of the biggest, or that Istanbul would be near the top of the list).
  
• List of provinces in China by GDP (you should know the big ones, like Guangdong, Shandong, Jiangsu, because these things are as populous as big western European countries, and some are approaching their level of GDP. You should also know that the U.S. has one city that isn't in a state but is comparable in its own right — the Washington metropolitan area is our 6th biggest and sprawls past the limits of D.C., while China has designated three this way: Shanghai, Beijing, and Chongqing).
• List of NUTS-1 regions in Europe by GDP. The EU is trying to get rid of the old subdivisions within member countries, which were of different sizes and often had more relevance historically than they do today, with a new system called by its acronym NUTS (there's maps here). NUTS-1 are the biggest ones, these are divided into NUTS-2 sub-regions, and those further divided into NUTS-3 sub-sub-divisions. By the time you retire, people may talk about something like Northwest Italy or East Sweden or South Spain as naturally as Americans talk about North and South Carolina. It's also plausible that some of the NUTS preserved historical features. For example, is the NUTS-1 containing Paris really the richest one in Europe, or did the French convince everyone else that their main one should include more territory than others, while the English didn't bother to add stuff on to Greater London? You should know the big ones around the continent: this is where the action is.

When I write that you should "know" this stuff, that does not mean I'm going to check if you have them memorized for an exam. It does mean you should know where to find this information, and be curious about the details. 

For example, you might note that Wuhan is on the list of biggest metropolitan areas, not far below Miami and Madrid and above Sydney: Wuhan was not a household word 13 months ago, but perhaps people would have paid more attention to COVID-19 if they knew how big Wuhan actually was on the world stage. Wuhan was really the first place in the world to ever be locked down (on January 23, 2020); can you imagine our reaction if Miami had been locked down? 

It was also a big thing when COVID-19 had its first sustained outbreak in Europe, in northern Italy in late February (a map towards the bottom of this post shows that it didn't land in a poor area, or slowly spread from the outside, but rather landed in one of the richest areas of Europe, and quickly clobbered it). Perhaps we would have paid more attention if people knew that the Northwest Italy NUTS that was hit initially has a GDP larger than the entire San Francisco Bay area.

Also, everything in this class coverage was about size of GDP. But we're also concerned about GDP per capita, and there's a wealth of lists of that too.

Our Strange Recession

The way we study things in generally experimental sciences is to make multiple observations of the same thing under controlled conditions.

The way we study things in generally non-experimental social sciences is to make multiple observations of things we presume might be the same, and then make sure we have all the other variables that might change that included in our analysis. 

The problem with doing this with recessions is ... they're often very different from the preceding one, and often from the whole set of about 40 recessions that we know of, going back in the U.S. to 1820.

Take the example of the current pandemic/lockdown recession. It's an even 100 years since we had a pandemic during a recessions. And, no country on Earth ever locked down anything before they all pretty much decided to just that late last winter.

Anyway, let's take a look at the labor market to get a sense of how different it is. The two graphs come from the Bureau of Labor Statistics website, which has nice tools for finding and charting data.

First up, here's the unemployment rate. This only goes back to 1948, so it missed the Great Depression, which would be not just off the chart, but probably 2 additional blocks up at 25%.

Even so, we can see how the ongoing recession is different: the peak rate is higher, while always steeper on the LHS this one is even steeper, and while it may not continue this way all the way down, it looks like the descent is faster than in earlier recessions. 

Even stranger is the labor force participation rate:

 

Generally, it's fairly hard to spot recessions in the labor force participation rate. 

Digression: this data is often interpreted incorrectly, and this is as good a time as any to explain. Notice that the hump is roughly symmetrical from about halfway up on the left (around 1980), to around 2015 on the right. Casual observers are inclined to say that the labor force participation rate went up, almost exclusively, because of women entering the workforce. That isn't the case: that was more of a smooth rise up until about 2000 — it does little to explain the hump. Instead the hump is likely from baby boomers being in the labor force during their prime years.

Anyway, it's fair to say from this chart that labor force participation has also behaved unusually in the pandemic/lockdown recession.

Looking at the raw numbers may help.

 

Year and month	Civilian noninsti- tutional population	Civilian labor force						Not in labor force
		Number	Percent of population	Employed		Unemployed
				Number	Percent of population	Number	Percent of labor force
1986	180,587	117,834	65.3	109,597	60.7	8,237	7.0	62,752
1987	182,753	119,865	65.6	112,440	61.5	7,425	6.2	62,888
1988	184,613	121,669	65.9	114,968	62.3	6,701	5.5	62,944
1989	186,393	123,869	66.5	117,342	63.0	6,528	5.3	62,523
1990	189,164	125,840	66.5	118,793	62.8	7,047	5.6	63,324
1991	190,925	126,346	66.2	117,718	61.7	8,628	6.8	64,578
1992	192,805	128,105	66.4	118,492	61.5	9,613	7.5	64,700
1993	194,838	129,200	66.3	120,259	61.7	8,940	6.9	65,638
1994	196,814	131,056	66.6	123,060	62.5	7,996	6.1	65,758
1995	198,584	132,304	66.6	124,900	62.9	7,404	5.6	66,280
1996	200,591	133,943	66.8	126,708	63.2	7,236	5.4	66,647
1997	203,133	136,297	67.1	129,558	63.8	6,739	4.9	66,837
1998	205,220	137,673	67.1	131,463	64.1	6,210	4.5	67,547
1999	207,753	139,368	67.1	133,488	64.3	5,880	4.2	68,385
2000	212,577	142,583	67.1	136,891	64.4	5,692	4.0	69,994
2001	215,092	143,734	66.8	136,933	63.7	6,801	4.7	71,359
2002	217,570	144,863	66.6	136,485	62.7	8,378	5.8	72,707
2003	221,168	146,510	66.2	137,736	62.3	8,774	6.0	74,658
2004	223,357	147,401	66.0	139,252	62.3	8,149	5.5	75,956
2005	226,082	149,320	66.0	141,730	62.7	7,591	5.1	76,762
2006	228,815	151,428	66.2	144,427	63.1	7,001	4.6	77,387
2007	231,867	153,124	66.0	146,047	63.0	7,078	4.6	78,743
2008	233,788	154,287	66.0	145,362	62.2	8,924	5.8	79,501
2009	235,801	154,142	65.4	139,877	59.3	14,265	9.3	81,659
2010	237,830	153,889	64.7	139,064	58.5	14,825	9.6	83,941
2011	239,618	153,617	64.1	139,869	58.4	13,747	8.9	86,001
2012	243,284	154,975	63.7	142,469	58.6	12,506	8.1	88,310
2013	245,679	155,389	63.2	143,929	58.6	11,460	7.4	90,290
2014	247,947	155,922	62.9	146,305	59.0	9,617	6.2	92,025
2015	250,801	157,130	62.7	148,834	59.3	8,296	5.3	93,671
2016	253,538	159,187	62.8	151,436	59.7	7,751	4.9	94,351
2017	255,079	160,320	62.9	153,337	60.1	6,982	4.4	94,759
2018	257,791	162,075	62.9	155,761	60.4	6,314	3.9	95,716
2019	259,175	163,539	63.1	157,538	60.8	6,001	3.7	95,636
2020	260,329	160,742	61.7	147,795	56.8	12,947	8.1	99,587
Monthly data, seasonally adjusted(1)
2020
January	259,502	164,455	63.4	158,659	61.1	5,796	3.5	95,047
February	259,628	164,448	63.3	158,732	61.1	5,717	3.5	95,180
March	259,758	162,721	62.6	155,536	59.9	7,185	4.4	97,037
April	259,896	156,478	60.2	133,370	51.3	23,109	14.8	103,418
May	260,047	158,200	60.8	137,224	52.8	20,975	13.3	101,847
June	260,204	159,797	61.4	142,100	54.6	17,697	11.1	100,407
July	260,373	160,085	61.5	143,777	55.2	16,308	10.2	100,288
August	260,558	160,818	61.7	147,276	56.5	13,542	8.4	99,740
September	260,742	160,078	61.4	147,543	56.6	12,535	7.8	100,664
October	260,925	160,718	61.6	149,669	57.4	11,049	6.9	100,207
November	261,085	160,536	61.5	149,809	57.4	10,728	6.7	100,548
December	261,230	160,567	61.5	149,830	57.4	10,736	6.7	100,663
2021
January	260,851	160,161	61.4	150,031	57.5	10,130	6.3	100,690
Footnotes (1) The population figures are not adjusted for seasonal variation.
NOTE: Revisions to population controls and other changes can affect the comparability of labor force levels over time. In recent years, updated population controls have been introduced annually with the release of January data. Additional information is online at https://www.bls.gov/cps/documentation.htm#pop.

I think it's fair to assume that we were at full employment in January 2019. Using that as a baseline, it's fair to say that unemployment is up by about 4.3 million people.

Given the scale of the numbers, population growth contributes a little to that, but can probably be safely ignored. For example, if population grows by about 0.5%/year (as shown in the leftmost column), each column in the table should go up by about that rate, and for unemployment that might contribute 0.1 (rounded up) to the 4.3 million increase.

For the employed, we are off about 8.6 million. But, from above, only half of those are unemployed. Where did the rest go? They are picked up in the decline in the labor force by 4.3 million. 

Note that for the employed and the labor force that the population increase of 1.3 million will make more of a difference. Doing a rough distribution, I'd say that 1.2 million should have gone into employment (meaning the announced number is down more than it looks), 0.1 into unemployment, and 1.3 into the labor force. So, adjusting a little gets the labor force down by 5.6M, employment down by 9.8M, and unemployment up by 4.2M.

Recall how people can be outside the labor force, but still in the civilian non-institutional population: they do not have a job and they are not looking. Further, if they all were looking, unemployment would be up to about 15.7M or a rate of 9.5%. That should put things in perspective that we are in pretty bad shape: it's comparable to the two highest peaks in the unemployment rate in the top chart.

From my longer perspective, I'll tell you that this is something the Democrats have always worried about in recessions, but which never really showed up in the data very seriously: people not interested in being employed. Now we have that, so it's important not to judge this recession by just its unemployment rate. 

It also means that as far as policy goes, we also shouldn't be excessively focused on the unemployed. Yes, we have a lot of them, and many deserve help from policy. But, since past recessions had far fewer people dropping out of the labor force, it's not clear that existing policies or off-the-shelf proposals are going to be focused on the right people.

Historical Real GDP (for the U.S)

The extended data set shown in the beginning of the Barro text comes from the Maddison Project. Angus Maddison was an economist whose life work was the creation of very long historical GDP series. The project is now part of the Groningen Growth and Development Centre at the University of Groningen in The Netherlands.Their data is free to download.

As of this semester, the data for the U.S. is annual, and has been extended back to 1820. These charts come from a spreadsheet saved to the class's shared Google Drive folder.

I am not certain, but I'm really sure that Barro got his data from the Maddison Project (there really aren't any competitors), and that probably at the time he downloaded it, it only went back to 1869.

U.S. Costs of COVID-19

Here's an infographic from Visual Capitalist:

These are drawn from "The COVID-19 Pandemic and the $16 Trillion Virus," by Cutler and Summers.

Since you're all undergraduates, I do try to clue you in to authors and sources you should pay attention to. 

• Visual Capitalist didn't do the research, just the image. 
• The article was published in the Journal of the American Medical Association, the best or second best journal in the field.  But, it was published in their opinion section, rather than under basic research.
• David Cutler is a professor of economics at Harvard (and a former department chair and college dean). He is one of the top researchers in health economics. Here's Cutler's Google Scholar page (70K cites and an h-index of 107 is crazy), Cutler's biographical page at Harvard, and his Cutler's Wikipedia page. He also served in the Clinton and Obama White Houses. In my view, Cutler might be moving up from the medium to the short list for a future Nobel Prize.
  
• And Lawrence Summers is even bigger. He's a professor of economics and former president of Harvard, He is one of the top researchers in macroeconomics, and was already huge when I was in graduate school 30 years ago. Here's Summer's Google Scholar page (157K cites, and an h-index of 178), and Summers' Wikipedia page. He served in the Clinton White House, topping out at Secretary of the Treasury. He was also Chief Economist at the World Bank. Here's Summers' press biography. And, both his parents were economics professors at the University of Pennsylvania, and ... get this ... each of his parents had a brother who was an economist who won a Nobel Prize. I think Summers is probably a lock on a Nobel Prize in the next decade.

The bottom line is that they will have a huge audience.

The biggest piece of the pie is reduced economic activity. Cutler and Summers draw on the Congressional Budget Office for that number, which is a sum over the next decade. Personally, it seems high, but not outrageous to me.

For regulatory purposes, economists have estimated the value of a human life. Non-economists find this controversial, mostly because we do it at all, but it serves a need. Their figure of $4.4T for premature death uses an estimate of ultimately 625K deaths valued at $7M each (that's a conservative value, I usually use $10M). I find the deaths number plausible, but not the overall total. This is because the $7M figure is for a whole life. While I don't generally agree with the common viewpoint that a COVID-19 diagnosis affects the old, I do think the total number should be cut down by quite a lot ... probably over half.

I am less well-versed in the costs of long-term health impairment. Having said that, I think everyone underestimates this. Since Cutler and Summers can back up their numbers, I'll accept them. The same goes for the mental health costs.

Now let's put this in perspective. It would be incorrect to naively compare this number to GDP. The value above is a stock variable, while GDP is a flow variable. (The authors do this anyway, because it's popular, but I don't encourage my students to do this). A better comparison might be to financial wealth of the United States, which is about $100T. So COVID-19 is going to knock off about a sixth of that. 

That's like a college student with a car worth $12K, and a huge insurance deductible of $2K, getting into a collision: it would hurt, big time.

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BTW: At this time last year, I was ballparking that the costs to China (a smaller and poorer economy) would be in the range of several hundred billion dollars. But, there are researchers in Australia who made the definitive estimates of the costs of SARS-COV-1. And 11 months ago they estimated the costs to the U.S. of COVID-19 would be $1.7T. Cutler and Summer's guesstimate is 10 times as high. Of course, when they published that estimate, the U.S. had a handful of cases in the Seattle area, and it was still a week before Rudy Gobert and the shutdown of the NBA, and everything else after that.

Visualizing Income Support Due to COVID-19

Income support means, roughly, that a government provides some replacement income to people during a time of crisis. In the case of COVID-19 this support is often large, but combines temporary and permanent measures.

All of this is being tracked through this site at Oxford. And all their data is available for free download. Ain't the internet great?

Visual Capitalist has put together an interactive graphic showing countries shaded by their level of support with the passage of time. Click through to play with it. Do press play at the bottom left to show changes through time.