Economic Recovery from the Pandemic

How well have countries recovered from the declines in the pandemic? It’s actually a bit difficult to answer that question, because it depends on how you measure it. Even if we agree that GDP is the best measure, how do we measure recovery? One possibility is to simply ask whether the country has exceeded its pre-pandemic GDP level. Exactly which quarter to use as the baseline is debatable, but here is a chart that Joseph Politano made for G7 countries using the 3rd quarter of 2019 as the baseline.

But we know that absent the pandemic, most countries would have continued growing (absent a recession for some other reason), so just getting back to pre-pandemic levels isn’t necessarily a full recovery. But how much growth should we have expected? It’s a hard question, but here’s a chart along those lines from the Washington Post, using the CBO’s measure of “potential GDP” as what growth might have looked like.

Using either of these approaches, it appears that the US has recovered pretty well, although it would be nice to have a comparison across countries using the same approach as the Washington Post chart does. While there is no consistent measure similar to CBO’s potential GDP figure for all countries, a simple approach is to project growth forward using the average pre-pandemic growth rate. I have done so for a number of countries, using the average growth rate from 2017-2019. In the following charts, the blue line is actual GDP levels, and the orange line is projecting the 2017-2019 growth rate forward. Sorry that I can’t easily fit all these into one chart, so here come the charts!

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Counting Jobs

Last week I wrote about the challenges of counting deaths. But surely in economics, we can count better, especially when it comes to something concrete like the number of people working. Right?

Maybe not. If you follow the economic data regularly, you’ll know that once per month, the Bureau of Labor Statistics releases data on the employment situation of the nation’s economy. And if you are familiar with this report, you will probably know that it is based on two separate surveys, one of businesses and one of households. And furthermore, it gives us two separate measures of employment, the number of people working for pay.

Joseph Politano has been tracking the employment situation reports, and he writes that the two measures of employment have “completely diverged since March of [2022], with the establishment survey showing payroll growth of nearly 2.7 million and the household survey showing employment growth of 12,000.” The surveys are tracking the labor market differently, so it’s not surprising that they won’t be exactly the same (they rarely are), but this sort of discrepancy is huge. Even accounting for most of the differences between the surveys, there is still a gap of about 2 million jobs.

Today, the BLS released yet another measure of employment, this one comes from the Business Employment Dynamics series. The BED is not released as quickly as the data in the employment situation report — the BED data released today is for the 2nd quarter of last year. But that’s because this data is much more comprehensive, and it’s actually the same data underlying the employment measure from businesses in the monthly employment report (it comes from unemployment insurance records, which covers most of the workforce).

What did the BED find for the 2nd quarter of 2022? A net loss of 287,000 jobs. The BED is only looking at private-sector jobs, and it is also seasonally adjusted to smooth out normal quarterly fluctuations. If we look back at the monthly data on employment, what did it look like in the 2nd quarter of 2022? Using the seasonally adjusted, private-sector jobs number to match the BED, it showed a gain of 1,045,000 jobs. In other words, we have a discrepancy of 1.3 million jobs in a single quarter. This is huge.

Perhaps some of this could be attributed to different seasonal adjustment factors, but even using the unadjusted data there is still a gap: 3,089,000 jobs added in the monthly payroll survey (private sector only), but only a net gain of 2,432,000 private-sector jobs in the BED data. That discrepancy is smaller, but it is still a difference of over 600,000 jobs. Note here that there was job growth in the second quarter in the BED measure, just not enough job growth that on a seasonally adjusted basis that it showed net growth. Another way to think of this: there is almost always growth in the 2nd quarter, but we expected it to be a bit stronger than this data shows.

If you aren’t confused enough yet, BLS produces yet another measure of employment, called the Quarterly Census of Employment and Wages. Really this is the broadest measure of jobs and is using the same underlying data as the BED and monthly nonfarm jobs in the business survey. But like the BED, it is also released with a significant lag. What does it show? A gain of 2,338,000 jobs in the 2nd quarter of last year (this includes public sector employment too). That number isn’t seasonally adjusted and compares with the CES (monthly nonfarm employment) number of 2,702,000, a discrepancy of 364,000 jobs (note: the CES will later be revised and benchmarked with the QCEW data).

What can we learn from all these different estimates of jobs? And which is right? The short answer to the second question is: they are all right, but measuring different things. The big takeaway is that there was indeed job growth in the 2nd quarter of 2022 (even the household survey shows job growth), but based on more complete data the monthly business survey probably overstated job growth, and it may have actually been pretty weak job growth compared to what we would normally expect in that quarter in the private sector (but of course, we aren’t in normal times).

On Counting and Overcounting Deaths

How many people died in the US from heart diseases in 2019? The answer is harder than it might seem to pin down. Using a broad definition, such as “major cardiovascular diseases,” and including any deaths where this was listed on the death certificate, the number for 2019 is an astonishing 1.56 million deaths, according to the CDC. That number is astonishing because there were 2.85 million deaths in total in the US, so over half of deaths involved the heart or circulatory system, at least in some way that was important enough for a doctor to list it on the death certificate.

However, if you Google “heart disease deaths US 2019,” you get only 659,041 deaths. The source? Once again, the CDC! So, what’s going on here? To get to the smaller number, the CDC narrows the definition in two ways. First, instead of all “major cardiovascular diseases,” they limit it to diseases that are specifically about the heart. For example, cerebrovascular deaths (deaths involving blood flow in the brain) are not including in the lower CDC total. This first limitation gets us down to 1.28 million.

But the bigger reduction is when they limit the count to the underlying cause of death, “the disease or injury that initiated the train of morbid events leading directly to death, or the circumstances of the accident or violence which produced the fatal injury,” as opposed to other contributing causes. That’s how we cut the total in half from 1.28 million to 659,041 deaths.

We could further limit this to “Atherosclerotic heart disease,” a subset of heart disease deaths, but the largest single cause of deaths in the coding system that the CDC uses. There were 163,502 deaths of this kind in 2019, if you use the underlying cause of death only. But if we expand it to any listing of this disease on the death certificate, it doubles to 321,812 deaths. And now three categories of death are slightly larger in this “multiple cause of death” query, including a catch-all “Cardiac arrest, unspecified” category with 352,010 deaths in 2019.

So, what’s the right number? What’s the point of all this discussion? Here’s my question to you: did you ever hear of a debate about whether we were “overcounting” heart disease deaths in 2019? I don’t think I’ve ever heard of it. Probably there were occasional debates among the experts in this area, but never among the general public.

COVID-19 is different. The allegation of “overcounting” COVID deaths began almost right away in 2020, with prominent people claiming that the numbers being reported are basically useless because, for example, a fatal motorcycle death was briefly included in COVID death totals in Florida (people are still using this example!).

A more serious critique of COVID death counting was in a recent op-ed in the Washington Post. The argument here is serious and sober, and not trying to push a particular viewpoint as far as I can tell (contrast this with people pushing the motorcycle death story). Yet still the op-ed is almost totally lacking in data, especially on COVID deaths (there is some data on COVID hospitalizations).

But most of the data she is asking for in the op-ed is readily available. While we don’t have death totals for all individuals that tested positive for COVID-19 at some point, we do have the following data available on a weekly basis. First, we have the “surveillance data” on deaths that was released by states and aggregated by the CDC. These were “the numbers” that you probably saw constantly discussed, sometimes daily, in the media during the height of the pandemic waves. The second and third sources of COVID death data are similar to the heart disease data I discussed above, from the CDC WONDER database, separated by whether COVID was the underlying cause or whether it was one among several contributing causes (whether it was underlying or not).

Those three measures of COVID deaths are displayed in this chart:

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The Decline of Working Hours, in the Long Run and Recently

If you look at the long-run trends in labor markets, one of the most obvious changes is the decline in working hours. The chart from Our World in Data shows the long-run trend for some countries going back to 1870.

Hours of work declined in the US by 43% since 1870. In some countries like Germany, they fell a lot more (59%). But the decline was substantial across the board. One thing to notice in the chart above is that for the very recent years, the US is somewhat of an outlier in two ways. First, there hasn’t been much further decline after about the mid-20th century. Second, average hours of work in the US are quite a bit higher than many of developed countries (though similar to Australia).

But the labor market in the US (and in other countries) is in a very unusual spot at the present moment after the pandemic. So what has happened really recently. Many economists are looking into this question of hours and other questions about the labor market, and a new working paper titled “Where Are the Workers? From Great Resignation to Quiet Quitting” presents a lot of fascinating data about the current state of work in the US. The paper is short (just 14 pages) and readable for non-experts, so I encourage you to read it all yourself.

Here is one table and one chart from the paper that I will highlight, which shows that hours of work have been falling, but in a very specific set of workers: those who work lots of hours, and those with high incomes. For workers at the high end of hours worked, the 90th percentile, they have dropped from 50 hours to 45 hours of work per week just from 2019 to 2022. But workers at the median? Unchanged at 40 hours per week. (The data comes from the CPS.)

The figure below is only for male workers, and it shows a similar decline in hours worked for those at the high end of the earnings distribution. For those at the bottom, hours of work at mostly unchanged.

Air Travel Prices Have Not “Soared” Since 1980 — They’ve Been Cut in Half

Winter holiday travel is notoriously frustrating. This year was especially bad if you were flying on Southwest. But that frustration about delayed and cancelled flights seems to have caused a big increase in pundits criticizing the airline industry generally. Here’s one claim I’ve seen a few times lately, that airline prices have “soared” as airlines consolidated.

Reich’s claim that there are 4 airlines today is strange — yes, there are the “Big Four” (AA, United, Delta, and Southwest), but today there are 14 mainline carriers in the US. There have been many mergers, but there has also been growth in the industry (Allegiant, Frontier, JetBlue, and Spirit are all large, low-cost airlines founded since 1980).

But is he right that prices have increased since 1980? Using data from the Department of Transportation (older data archived here), we can look at average fare data going back to 1979 (the data includes any baggage or change fees). In the chart below, I compare that average fare data (for round-trip, domestic flights) to median wages. The chart shows the number of hours you would have to work at the median wage to purchase the average ticket.

The dip at the end is due to weird pandemic effects in 2020 and 2021, so we can ignore that for the moment (early analysis of the same data for 2022 indicates prices are roughly back to pre-pandemic levels, consistent with the CPI data for airfare).

The main thing we see in the chart is that between 1980 and 2019, the wage-adjusted cost of airfare was cut in half. Almost all of that effect happened between 1980 and 2000, after which it’s become flat. That might be a reason to worry, but it’s certainly not “soaring.”

Of course, my chart doesn’t show the counterfactual. Perhaps without several major mergers in the past 20 years, price would be even lower. Perhaps. But research which tries to establish a counterfactual isn’t promising for that theory. Here’s a paper on the Delta/Northwest merger, suggesting prices rose perhaps 2% on connecting routes (and not at all on non-stop routes). Here’s another paper on the USAir/Piedmont merger, which shows prices being 5-6% higher.

There are probably other papers on other mergers that I’m not aware of. And maybe all of these small effects from particular mergers add up to a large effect in the aggregate. But, as my chart indicates, even if the consolidation has led to some price increases, they weren’t enough to overcome the trend of wages rising faster than airline prices.

One last note: the average flight today is longer than in 1979. I couldn’t find perfectly comparable data for the entire time period, but between 1979 and 2013, the average length of a domestic flight increased by 20%. So, if I measured the cost per mile flown, the decline would be even more dramatic.

Tough Year for Investing (with one little-known, totally safe exception)

There’s still a few more days left in the year, but at this point it is safe to say, unfortunately, that it was a very bad year for investing. This Google chart shows most of the bad news. Note: nothing in this post is investment advice about the future, just a summary of the past.

The S&P 500, the typical benchmark for US equities, was down 20%. Bonds, usually a safe haven, were down over 14% as measured by the Vanguard Total Bond fund (more on bonds later).

Gold, the traditional hedge against bad times, was flat. I guess that’s not so bad. But gold is also traditionally considered a hedge against inflation, and inflation will probably end up being somewhere in the range of 5-7% this year (depending on your preferred index). So in real terms, even gold was down. And the supposed new hedge against fiat currency? Bitcoin is down 65% (crypto has other potential redeeming features, but inflation hedging was supposed to be one of them).

Did anything do well? Oil was basically flat too, starting and ending the year in the $75-80 range. Of course, oil companies did very well this year — Exxon is up over 70%, since prices were elevated for much of the year. But picking individual stocks is always fraught with danger. For example, you might think electric car companies would have done well in the past year, given the high gas prices for much of the year, yet Tesla was down over 70% (I won’t speculate here about why, but it may have other idiosyncratic explanations).

There is one boring, sleeper investment that would have earned you a decent return. Not a massive return, but one that will likely be slightly higher than the rate of price inflation (once we have complete inflation data). And the investment is totally safe, and by April you would have known exactly your rate of return for the full year: 8.5%.

That investment? Series I Savings Bonds, issued by the US Treasury. Series I Bonds pay a fixed rate of return for 6 months, which you know at the time you buy it. The interest rate rests every 6 months based on the rate of CPI inflation. If you invested in these bonds in January 2022, you would have earned 3.56% for 6 months, and then you would have earned 4.81% for the second half of 2022. And this was all known as early as April 2022 (though not officially confirmed by the Treasury until May).

While a lot of people were talking about the possibility of high inflation at the beginning of 2022, I don’t recall many people advising anyone to buy these bonds. It’s not a super well known investment, and not super exciting. Plus each investor is capped at $10,000 per year in most cases, so you couldn’t have moved all your money into I Bonds. Another restriction is that you lose some of the interest if you pull the money out before 5 years.

Still, this was one bright spot in an otherwise terrible year for most broad investment types.

The Wealth of Generations: Latest Update

I’ve covered the topic of generational wealth before, and here’s the latest data on how each generation was doing at roughly the same age. The data is updated through the 3rd quarter of 2022.

The main takeaways:

  • Millennials are roughly equal in wealth per capita to Baby Boomers and Gen X at the same age.
  • Gen X is currently much wealthier than Boomers were at the same age: about $100,000 per capita or 18% greater
  • Wealth has declined significantly in 2022, but the hasn’t affected Millennials very much since they have very little wealth in the stock market (real estate is by far their largest wealth category)

Inflation-Adjusted Wages Have Been Rising Since June 2022

Back in May 2022, I wrote about the very bad picture for inflation-adjusted wages in the US. While they were still slightly above pre-pandemic levels, wages had been falling consistently since the beginning of 2021.

But since then, we’ve got some better news. The chart below shows the data (note: I’m using wages for private production and non-supervisory workers here, rather than for all private workers in the May post).

While the overall inflation picture still looks bad, with 7.1% annual inflation in the latest report, we also see that in the past 5 months wage growth has exceeded CPI growth. It’s also been true compared with the PCE price index for the past 4 available months (November PCE data won’t be available until next Friday). Inflation has cooled slightly in the past few months, while wages have continued to grow.

This all means that real (inflation-adjusted) average wages in the US have been rising consistently since June 2022. Finally, some good news!

Message To My Students: Don’t Use AI to Cheat (at least not yet)

If you have spent any time on social media in the past week, you’ve probably noticed a lot of people using the new AI program called ChatGPT. Joy blogged about it recently too. It’s a fun thing to play with and often gives you very good (or at least interesting) responses to questions you ask. And it’s blown up on social media, probably because it’s free, responds instantly, and is easy to screenshot.

But as with all things AI, there are numerous concerns that come up, both theoretical and immediately real. One immediately real concern among academics is the possibility of cheating by students on homework, short writing assignments, or take-home exams. I don’t want to diminish these concerns, but I think for now they are overblown. Let me demonstrate by example.

This semester I am teaching an undergraduate course in Economic History. Two of the big topics we cover are the Industrial Revolution and the Great Depression. Specifically, we spend a lot of time discussing the various theories of the causes of these two events. On the exams, students are asked to, more or less, summarize these potential causes and discuss them.

How does ChatGPT do?

On the Industrial Revolution:

And on the Great Depression:

Now, it’s not that these answers are flat out wrong. The answers certainly list theories that have been discussed by at various times, including in the academic literature. But these answers just wouldn’t be very good for my class, primarily because they miss almost all of the theories that we have discussed in class as being likely causes. Moreover, the answers also list theories that we have discussed in class as probably not being correct.

These kinds of errors are especially true of the answer about the Great Depression, which reads like it was taken straight from a high school history textbook, ignoring almost everything economists have said about the topic. The answer for the Industrial Revolution doesn’t make this mistake as much as it misses most of the theories discussed by Koyama and Rubin, which was the main book we used to work through the literature. If a student gave an answer like the AI, it suggests to me that they didn’t even look at the chapter titles in K&R, which provide a roadmap of the main theories.

So, my message to students: don’t try to use this to answer questions in class, at least not right now. The program will certainly improve in the future, and perhaps it will eventually get very good at answering these kinds of academic questions.

But I also have a message to fellow academics: make sure that you are writing questions that aren’t easily answered by an AI. This can be hard to do, especially if you haven’t thought about it deeply, but ultimately thinking in this way should help you to write better exam and homework questions. This approach seems far superior to the one that the AI suggests.

Fight for $15? $25? $40?

Remember the “Fight for $15”? It’s a 10-year-old movement to raise the federal minimum wage to $15 per hour. While there hasn’t been any increase in the federal minimum wage since the movement began in 2012, plenty of states and localities have done so.

I won’t rehash the entire debate on the minimum wage here, but I will point you to this post from Joy on large minimum wage changes, and here are several other posts on this blog on the same topic. But lately I have seen an increasing call for even larger minimum wage increases, well beyond $15.

A prominent recent call for a higher wage comes from the SEIU, the second largest labor union in the nation. They are calling for a $25 minimum wage in Chicago, where the legal minimum wage just recently crossed $15 last year. Again, without getting into the detailed debates about the economics of the minimum wage, we can recognize that this would be a massively high minimum wage, given that median hourly wage for the Chicago MSA was $22.74 in May 2021. It’s certainly a bit higher in 2022, and the city of Chicago is probably a bit higher than the entire MSA. Still, we are talking about a minimum wage that would cover roughly half the workforce. Well, at least half the current workforce. The negative employment effects would potentially be large.

Here I will dabble a little bit in the minimum wage literature. One of the most famous recent papers that suggests increasing the minimum wage doesn’t have large negative employment effects is a 2019 paper by Cengiz, et al. This paper only looks at legal minimum wages that go up to 59% of the median market wage, which is the highest wages have been pushed up so far. By contrast, that $25 minimum wage in Chicago would be somewhere around 100% (!) of the local median market wage. That’s huge, and goes far beyond what even the most sympathetic-to-the-minimum-wage research has looked at.

But here’s the most recent minimum wage call that really takes the cake: over $40 per hour in Hawaii. That comes from, in a way, a Tweet from Hal Singer:

Now in fairness, he doesn’t exactly call for a $40 minimum wage in Hawaii, but he does say we should use the minimum wage as a tool to address homelessness, and then points to a study showing that you would need to earn $40/hour in Hawaii to afford a two-bedroom apartment. That’s pretty close. The median wage in Hawaii? About $23 in May 2021. In fact, the 75th percentile wage in Hawaii was $36.50 in 2021! So, depending on exactly how much wage growth there has been in Hawaii since May 2021, we are likely talking about a $40 minimum wage covering 75% of the workforce! That would likely have some “bite,” as economists say.