I’ve taught college classes since 2010, but I never graded attendance directly until this year. I thought that students are adults who can make their own choices about where to spend their time, and if they could do well on my tests and assignments without spending much time in class, more power to them.
But I got tired of seeing students miss a lot of class, then fail by getting poor grades on the tests and assignments, or scramble for the last few weeks to avoid failing. Explaining the importance of attendance didn’t seem to help, so I finally turned to the economist’s solution- incentives. This Spring I tried grading attendance in one class, and this successful experiment plus the growth of AI mean I plan to grade attendance in all classes from now on.
The Benefits:
Get to know student’s names faster
Students feel rewarded for showing up
Students show up more, bringing more energy to the room
Students show up more, so they learn more and do better on other assignments
Physically showing up is one thing I can be sure the AI isn’t doing for them, it will be a while before humanoid robots are that good
The Costs That Turned Out Not to Be Big Deals
I thought students would dislike me policing their whereabouts and give me lower course evaluations (which is part of why I waited for tenure to try this). But my Spring evals were at least as high as usual, with none mentioning the attendance policy. When I asked students in a different class about this, most said they wished I would grade attendance if it meant less weight on exams.
I thought tracking attendance would be burdensome, but it turns out my main course software (Canvas) already has an attendance-tracking tool built in that lets you just click on names in a seating chart each day and enters grades automatically. It is certainly less burdensome than grading most assignments.
I still had some students disappear for a while due to personal issues; sometimes even the strongest grade incentives aren’t enough to get people to class. But overall I can’t believe I waited this long. I’m currently putting attendance as 10-15% of the course grade, but I dream about someday running a discussion-based class like a Liberty Fund seminar, doing a 100% attendance/participation grade, and not having to grade anything.
Yesterday I showed that BLS jobs reports from the CES aren’t getting worse over time, if we judge them by how much they are later revised. In fact, they are much better than decades past, with the last 20 years or so standing out as much better than the past.
Today I want to address a related but separate topic: are the initial jobs reports good at telling us when a downturn in the labor market is beginning? This is actually the strongest argument for releasing this survey data in a timely manner, even though the data often goes through significant revisions later. The report typically comes out the first Friday of a new month, so it is very current data. Given that the likely new BLS Commissioner has signaled he prefers the more accurate quarterly release, even though it is 7-9 months after the fact, it is useful to ask if these initial reports have any value in telling us when labor market declines (and recessions) are beginning.
That’s right: you are getting two posts from me this week, on essentially the same topic. Because it’s very important right now.
The short answer: the report is very good for the purpose of identifying downturns, especially the start of the downturns. Let’s walk through the past few recessions.
You’ve probably heard a lot about BLS data recently (or at least more than usual) with Trump firing the BLS Commissioner after a bad monthly revision to the nonfarm payroll jobs figures. But this didn’t come out of the blue, as there was plenty of criticism of the jobs numbers during the Biden term as well, mostly coming from the political right.
The two main criticisms leveled at the BLS, in my reading of it are:
The BLS is getting worse at estimating jobs numbers over time, leading to larger revisions
The revisions are done in a way that is favorable to Democrats
I think both of those claims can be analyzed with the following chart, which also shows those claims to be incorrect:
These are notable posts from 2025, roughly presented in descending order, starting with the post that got the most views.
Is there a competitive threat to the NBA? Mike Makowsky wrote, “… let’s put it this way. Why *wouldn’t* the Saudi Arabian PIF invest $5 billion in creating a rival basketball league?”
2. Perspective: This Stock Correction Fear, Too, Will Pass In March, Scott Buchanan presented “an optimistic take on the current stock market pullback.” Indeed, the market came back, despite the tariff doomerism of 2025 Spring.
7. Was the US at Our Richest in the 1890s? If you don’t believe Jeremy, consider one of the American Girl Doll historical books I was just reading to my kid. In our book, a little girl sends a letter to Samantha (the 1904 doll) reporting that bothof her parents just died from the flu.
8. The Wild Market of July 8th, 2025 James Bailey on the topic that we are all trying to keep up with this year: “Yesterday the S&P 500 shot up 9% on the news that most of Trump’s new tariffs were paused.”
9. No Tech Workers or No Tech Jobs? I (Joy) wish I had more time to write about the market for tech jobs this year. There is some indication that hiring is slowing. Some people still call it a correction from the Covid tech over-hiring spree. Other people take this as a sign that AI reduces the need for human programmers and otherwise “high-skill” humans, while some refute that claim.
10. Other “I, Pencils” It was fun for several dozen of us economists when everyone else in the world suddenly re-discovered the value of international exchange.
11. The Best Investments of the 1970s James considers “what were the best investments of the 1970’s?” Interesting to consider the performance of gold in retrospect considering stagflation.
15. Salty SALT in the OBBB Zachary explains. “Economically, the SALT makes it cheaper for individuals to live in high-tax jurisdictions. That’s distortionary.”
Reflections: We’ve been doing this for 5 years now, as of August 2025. From the analytics I can see, our posts have been the answer to a stranger’s Google query hundreds of thousands of times. Having been the beneficiary of so many other posts from strangers online, I’m happy about that.
Reminder: You can subscribe to our WordPress site to get posts sent to your email. The widget for putting your email in should be on the right side of your screen on a computer, or you can find it by scrolling to the bottom of the home page on a mobile device. WordPress will let you customize your preferences so that you get emails batched once a week if you prefer that to Every Day.
Based on my crude analytics from WordPress, “traffic” to our site from LLMs is low but increasing. It appears that readers occasionally click over from chatgpt.com or perplexity.ai What we can’t see is if and when our writing is re-molded as part of an LLM answer without attribution. In one sense, writing online is more important than ever, to feed the beast and help get good quality answers to LLM users. On the other hand, old systems in place like upvotes and view counts that used to motivate people to write for free might crumble in the new world.
From me in 2024: “AI companies have money. Could we be headed toward a world where OpenAI has some paid writers on staff? Replenishing the commons is relatively cheap if done strategically, in relation to the money being raised for AI companies.”
If anyone knows Mark Zuckerberg, please tell him that I’ll write for a fraction of what he’s paying these new engineers. What if he gave out a writing fellowship on the understanding the person never publishes (else the other bots would scrape it) and just exclusively lets Llama train off of original work?
In our case, anyway, we enjoy writing and learn from the process, so we are looking forward to being here every day.
In the Road to Serfdom, Friedrich Hayek uses some basic quantitative logic to make an important point about employment and political economy.
Hayek starts by assuming that government jobs are stable relative to those in the private sector. This might seem obvious, but let’s just start by checking the premises. Below are the percent change in total compensation and total employment for government employees and for the private sector. From year to year, private employment and total compensation is more volatile. So, Hayek’s initial premise is correct.
From there, he proceeds to say that if any part of income or employment is guaranteed or stabilized by the government, then the result must be that the risk and volatility is borne elsewhere in the economy. He reasons that if there is a decline in total spending, then stable government pay and employment implies that the private sector must have a deeper recession than the overall economy. Looking at the above graphs, both government employment and the total compensation are much less volatile.
But can’t governments intervene in macroeconomic stabilization policies effectively? Yes! They can and do stabilize the economy, especially with monetary policy. But Hayek is referring to individual stabilizations. For any individual to be guaranteed an income, all others must necessarily experience greater income volatility. How’s that?
Consider two individuals. Person #1 has an average income of $100. In any given year, his income might be $10 – or 10% – higher or lower than average. For the moment, person #2 is not employed and has income volatility of zero. If the government provides a job with a constant pay rate to person #2, then they still have zero income volatility. But instead of earning a consistent $0, person #2 earns a consistent $50. Nice.
Of course, person #2 gets his pay from somewhere. By one means or another, it comes from person #1. Let’s be generous and assume the tax on person #1 has no resulting behavioral effect. His new average income is $50, being $10 higher or lower in any given year. But now, that $10 deviation is over a base of $50 rather than $100. Person #1’s income varies by 20% relative to his new average!
Reasoning through this, we can consider that a person has a stable portion of their income and a volatile portion. If someone takes a part of your stable portion and leaves you with all of your volatile portion, then your remaining income is now more volatile on average. I think that this point is interesting enough all by itself.
IRL, many of our taxes are not lump sum. Rather, progressive taxation causes a negative incentive for production & earnings. The downside is that we produce less. The upside is that the government takes a higher proportion of our volatile income than of our stable income (because income changes are always on the margin and those marginal dollars are taxed at a higher rate). So, the government shares the income volatility of the private sector. By continuing to pay government employees a stable salary, the government is effectively absorbing some of that year-to-year income volatility on behalf of its employees.* The government is, in a sense, providing income insurance to a subgroup.
What does this have to do with The Road to Serfdom? Hayek argues that, as the government employs an increasing proportion of the population, the remaining private sector experiences increasing income and employment volatility. Such volatility increases private risk exposure so much that people begin to fawn over and increasingly compete for the stability found in government work. He gets anthropological and argues that the economic attraction to government jobs will introduce greater competition for those jobs and subsequently greater esteem and respect for those who are able to get them. This process makes the government jobs even more attractive.
My own two cents is that there is nothing internally unstable about this process. Total real income would fall compared to the alternative. However, such a state of affairs might be externally unstable as other governments/economies compete with the increasingly socialist one.
*An important analogue is that firms behave in a similar way. An individual may receive a relatively constant salary so long as they are employed. But the result must be that the firm bears more of the net-profit volatility. So, as more people want stable private sector jobs, the profit volatility of firms would increase and result in greater [seemingly windfall] profits and losses.
The Affordable Care Act was supposed to make it easier for American workers to switch jobs by making it easier to get health insurance from sources other than their current employer. Mostly it didn’t work out that way. But a new paper finds that one piece of the ACA actually made people less likely to switch jobs.
The ACA Dependent Coverage Mandate required family health insurance plans to cover young adults though age 26, when prior to the 2010 passage of the ACA many had to leave the family plan at age 18 or 19. I thought these newly covered young adults would be more likely to switch jobs or start businesses, but there turned out to be absolutely no effect on job switching, and no overall increase in businesses (though it did seem to increase the number of disabled young adults starting businesses, and other parts of the ACA increased business formation among older adults).
But while the Dependent Coverage mandate seems not to have reduced job lock for young adults, it increased job lock among their parents. That is the finding of a new paper in the Journal of Public Economics by Hannah Bae, Katherine Mackel, and Maggie Shi. Using a large dataset with exact months of age and coverage, MarketScan, allows them to estimate precise effects:
We find that dependents just to the right of the December 1985/January 1986 cutoff—those eligible for longer coverage—are more likely to enroll and remain covered for longer once the mandate is in effect. Dependent enrollment increases by 1.8 percentage points at the cutoff, an increase of 9.2 % over the enrollment rate for dependents born in December 1985. In addition, the enrollment duration increases by 9.7 days (14.6 %). Turning to their parents, we find that parental job retention likelihood increases by 1.0 percentage point (1.8 %) and job duration increases by 5.8 days (1.6 %) to the right of the cutoff. When scaled by the estimated share of dependents on end of year plans, our findings imply that 12 additional months of dependent coverage correspond to a 7.7 % increase in job retention likelihood and a 7.0 % increase in retention duration.
I believe in this parental job lock effect partly because of their data and econometric analysis, and partly through introspection. I plan to work for years after I have the money to retire myself in order to keep benefits for my kids, though personally I’m more interested in tuition remission than health insurance.
On top of working longer though, benefits like these enable employers to pay parents lower money wages. A 2022 Labour Economics paper from Seonghoon Kim and Kanghyock Koh found that the Dependent Coverage Mandate “reduced parents’ annual wages by about $2600 without significant reductions in the probability of employment and working hours.” But at least their kids are better off for it.
I had planned to write about the Trump-BLS fight today. But considering that two of my co-bloggers have already written about this (Mike on Monday and Scott on Tuesday) and that I have written about supposedly “fake” jobs numbers before several times (see January 2024 and August 2024), I will hold off on that topic until all of the dust settles. But this is a very important topic, and I believe Trump is clearly in the wrong (as is Kevin Hassett, see my tweets from this week), so please do continue to follow this topic and sane voices on it (see a Tweet from Ernie Tedeschi and from me for a long-run perspective on data accuracy).
But now, on to something a little more light-hearted: is everyone traveling to Europe these days?
Judging by my Facebook feed, it seems that Yes, lots of people are traveling to Europe. But this could be a result of selection bias in at least two ways: the people I am friends with on Facebook, and what people choose to post about on Facebook.
So what does the hard data say? We actually have pretty good long-run data on this question. In short: yes, lots more Americans are traveling to Europe (and overseas generally). Though don’t worry: not everyone went to Europe this summer, despite what social media might have you believe.
For starters, here’s a chart showing three decades of US overseas travel:
Thousands of keyboards were likely drenched four days ago as coffee spewed from thousands of nostrils upon reading the headlines that President Trump fired the head of the Bureau of Labor Statistics because he (the prez) didn’t like the July 2025 job numbers that were reported. Apparently, the job stats were not as great as we had been led to expect for the new regime of tariffs and deportations. (Someone should inform the politicians that businessmen need predictability for making any expansionary plans). So, shoot the messenger, that will fix it.
The First Ire was apparently kindled especially by the truly massive downward revisions to the May (-125,000) and June (-133,000) job figures, which reduced the combined employment gain for those months by 258,000. That made for three anemic employment months in a row, which is a different picture that had been earlier portrayed. For those unfamiliar with past BLS reports, that could seem like manipulation or gross incompetence. For instance, whitehouse.gov published an article titled, “BLS Has Lengthy History of Inaccuracies, Incompetence”, excoriating the “Biden-appointed”, now-fired Erika McEntarfer who “consistently published overly optimistic jobs numbers — only for those numbers to be quietly revised later.”
But massive overestimations of jobs creation, followed a month or two or three later by massive downward revisions are pretty standard procedure for the BLS in recent years. Fellow blogger Jeremy Horpedahl has noted prior occurrences of this, e.g. here and here. There is no reason to suspect nefarious motives, though. The understaffed and overworked folks at BLS seem to be doing the best they can. It is just a fact that some key data simply is not available as early as other data. There are also rational adjustments, e.g. seasonal trends, that must first be estimated, and only later get revised.
Bloomberg explains some of the fine points of the recent revisions:
The downward revision to the prior two months was largely a result of seasonal adjustment for state and local government education, BLS said in earlier comments to Bloomberg. Those sectors substantially boosted June employment only to be largely revised away a month later.
But economists say the revisions also point to a more concerning, underlying issue of low response rates.
BLS surveys firms in the payrolls survey over the course of three months, gaining a more complete picture as more businesses respond. But a smaller share of firms are responding to the first poll. Initial collection rates have repeatedly slid below 60% in recent months — down from the roughly 70% or more that was the norm before the pandemic.
In addition to the rolling revisions to payrolls that BLS does, there’s also a larger annual revision that comes out each February to benchmark the figures to a more accurate, but less timely data source. BLS puts out a preliminary estimate of what that revision will be a few months in advance, and last year [2024], that projection was the largest since 2009.
Perhaps it would be wise for the BLS to hang a big “preliminary” label on any of the earlier results they publish, to minimize the howls when the big revisions hit later. Or perhaps some improvements could be made in pre-adjusting the adjustments, since revisions there do seem to swing things around outrageously. I expect forthcoming BLS reports to be the subject of derision from all sides. We all know which parties will scoff if the job report looks great or if it looks not great. Presumably the interim head of the Bureau, William Wiatrowski, is busy polishing his resume.
And POTUS should be careful what he wishes for – “great” job growth numbers would, ironically, strengthen the case for the Fed to delay the interest rate cuts he so desires.
In my recent post that included Federal Reserve political independence, I dared to use the word ‘trust’, and commenters let me know that they were not pleased about it. In strict economic terms, there is no such thing as trust. Either that, or it’s the same thing as expectations or maybe low-information expectations. Since it wasn’t the main thrust of my post, I didn’t lay-out the informed reasoning behind my confidence in President Trump’s inability to cause Argentina or Turkey or even 1970’s US levels of political influence on the Fed.
In short, I’m not worried about it because the operational structure of the Fed and the means by which individuals join the Fed are determined by congress and are pretty robust. Below is a diagram that I made. I know that it’s a lot, but I’ll explain below.
Last week I wrote about the GDP predictions from Kalshi and the GDPNow Model. They were both showing 2.4% for Q2 of 2025 last week. They both changed slightly by yesterday, up to 2.8% and 2.9%. The final result (technically, the “advanced” result, but the final one for purposes of this comparison) was 2.97%. The Atlanta Fed GDPNow model continues to be a top performer, and you can’t do much better than averaging these two estimates. And you can pretty consistently do better than the median result from the WSJ/Dow Jones survey of economists.
Economist Writing Every Day 