Author: Jeremy Horpedahl

Has Mexico’s “Canasta Básica” Policy Made Food More Affordable?

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A recent article in The Guardian profiles economist Isabella Weber. She doesn’t seem to like other economists very much, supposedly because we “obsess over ideological purity and are inflexible when searching for solutions.” Weber wants economists to come up with solutions that work even if… I guess, even if they don’t work well in theory? Maybe they will work well in practice?

Anyway, so far as I can tell, the article only gets into details on two concrete solutions to affordability. I’m sure she has more in her book, but let’s see what these are. The first for governments to create “publicly owned entities that can buy and sell grain into its market,” presumably to smooth out fluctuations in grain prices. The second is “the Mexican government’s canasta básica policy, through which retailers voluntarily cap the total price of a basket of two-dozen essential goods.”

Let’s look at the second one, since I think for developed countries like the US, fluctuating grain prices aren’t the primary source of affordability concerns. But perhaps American consumers would like a basket of grocery essentials to be cheaper.

Has this policy in Mexico worked? It was first implemented in 2022, and food inflation has certainly fallen in Mexico since then. But it has also fallen everywhere else in the world — 2022 was peak inflation not just in the US, but in most countries — so we can’t judge the success of the program based on that alone.

Instead, we can look at internationally comparable data on food spending, which comes from the USDA’s Economic Research Service. Our World in Data has a nice chart based on this data, and even though it is now two years out of date (I will provide 2025 data below), the 2023 data makes a case against the success of the “price controls” in Mexico (I put “price controls” in quotes because it is not a true price control, but an attempt to control prices via incentives):

Figure 1

It will probably not surprise you that the US spends much less on food as a percent of total spending than Mexico, given that we are a high-income country. But it is still worth pointing out just how low food spending is in the US. However, this chart still paints Mexico in a very poor light: for countries with about the same income level in the Americas (as measured by consumer expenditures), Mexicans spend much more on food than Argentina, Chile, or Panama.

If we use the 2025 USDA data, and focus on the 10 countries with consumption expenditure closest to Mexico (between about $8,000 and $12,000 of consumption), we see that Mexico is very much on the high end: only Argentina was clearly higher:

Table 1

Finally, we can compare Mexico against itself in this data, looking at food spending going back to 2017:

Figure 2

Food spending actually peaked in 2020, though be cautious of any data from 2020 as the pandemic made data collection difficult. After declining in 2021 and then into 2022 (the policy seems to have been put in place in mid-2022), there haven’t been any further declines. And food spending is still well above pre-pandemic levels (unlike the US, where the 2025 figure of 6.4% is the same as 2017-18).

Ultimately, we would want a more sophisticated analysis than my simple tables and charts here. But it doesn’t appear that Mexico’s 2022 policy really made food much more affordable, either relative to peer countries with similar income levels, or relative to Mexico’s own recent history. And that’s even before we get into any unintended consequences of the “price controls.” Of course, the policy may have made that basic basket of two-dozen items more affordable than it otherwise might be — for that we would need to compare individual item prices to peer countries — but it hasn’t obviously made food overall more affordable in Mexico.

Wealth of Generations in 2025

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Two weeks ago I provided an update on estimates of wealth for recent generations in the US. But just this week, the Federal Reserve gave us the once-every-three-years complete update to this data, which allows us to calculate medians rather than average, and to more precisely separate age groups.

I will have a lot more to say about this data, both on this blog and a book I am working on, but for now here is the chart you have all been waiting for:

“The Grim Old Days” in Charts

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I’ve just started reading Chelsea Follett’s new book The Grim Old Days, which shows just how bad things were in the past. It’s a great book, and I encourage everyone to buy it. If you want a sample of what’s in the book, check out her series of blog posts on “contemporary accounts of daily life in the past” or read her blog post summarizing some of the topics in the book.

As an economist when I think about the past, in my head I see charts. Lots of charts, full of data! Follett’s book is mostly narrative history, and it is not filled with charts and data. That’s OK, I still am very much enjoying the book. But what charts would I select to show how grim the old days were, if I wanted to take that approach to the topic?

Here are four good ones from Our World in Data.

Child mortality in the past was horrible, with only about half of children surviving to adulthood (goes along with Chapters 2 and 3 of her book):

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Wealth of Generations: Update Through the First Half of 2026

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It’s been a while since I updated my generational wealth chart, and we now have estimates through the 2nd quarter of 2026, so here’s the latest chart:

Figure 1

Wealth for younger Americans continues to grow substantially, but let me make two caveats:

  1. Yes, I know median data is better. I’m writing a book that uses median wealth data! But the latest median wealth data from the Fed’s SCF is currently only available through 2022, so it’s not super relevant to current conversations. We should have the 2025 data soon.
  2. Because of the way the data in my chart is produced in the Fed’s DFA, it groups everyone under age 45 together. That’s a mighty big group, and it because it encompasses both Millennials and a lot of Gen Z, it makes it hard to directly compare to earlier generations.

So, until we have 2025 median wealth data, and until the Fed’s DFA starts breaking out Millennials and Gen Z, here is my current best compromise chart:

Figure 2

In Figure 2, I have used the Fed DFA data for age groups, which are still pretty large groups, but you can consistently compare them over time. The average wealth level of both the 18-39 group and the 40-54 group have seen substantial gains. In fact, the gains for younger cohorts have been even better than middle-aged Americans, though both saw substantial gains.

And this chart shouldn’t be affected by the lack of household formation among some younger Americans: I am using the full population as the denominator, so if anything, this will understate growth rates. Even so, the growth rate from the depths of Financial Crisis in 2010 have been substantial: 228 percent growth from 2010 to 2026 for ages 18-39. The growth rate for ages 40-54 was less dramatic, though they also didn’t experience as large of a slump from 2007-2010.

While we can always hope and work towards growth rates being better, average wealth for Americans of working age is currently at record highs, having fully recovered from both the Financial Crisis and the inflation slump of 2022.

Are You Better Off Than You Were 22 Months Ago? Midterm Elections and Real Wage Growth

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The phrase “are you better off than you were 4 years ago?” seemed to have been a winning campaign slogan for Ronald Reagan in 1980. But when I looked at the data, it didn’t really hold up, if we are looking at real income growth to determine “better off.” Real family income growth was actually positive under Carter, but he lost reelection. Then four years later, Reagan won reelection, despite having negative real income growth. This is a pattern we see often in recent presidential reelection years. Interestingly, it does not appear to be 4-year income growth that matters, but 1-year income growth might.

Is there any similar data we can look at for midterm elections? It is well known that Presidents almost always lose seats in a midterm election. But might they lose fewer seats if the economy is performing well? The following scatter plot shows all midterm elections since 1970. On the horizontal axis is the percent change in real wages (AHETPI series, deflated by the PCEPI) from the January a President takes office until November of the midterm election year. The vertical axis shows the net change in Congressional seats for the party of the President, including both the Senate and House (I weight Senate seats at 4.35x House seats, which is somewhat arbitrary).

Figure 1

What can we learn from this scatter plot? I would say there is a weak correlation between the variables: better real wage growth means losing few seats. The sample size is small, so I am reluctant to plot a trendline, but it would be positive. The only two midterm elections since 1970 where the President’s party actually gained Congressional seats had very high wage growth: Bush in 2002 (3.3%) and Clinton in 1996 (a very robust 5.3%). Very negative wage growth shows up just once, for the Nixon/Ford midterm in 1974, and here the Congressional losses were pretty massive.

Now you might object that other factors matter. And surely they do. The Republicans probably would have lost a lot of seats in 1974 anyway, due to Nixon’s resignation. But I’m sure the higher rates of inflation and resulting negative real wage growth didn’t help. And Bush probably got a significant post-9/11 hero bounce in 2002, though the real wage growth might have helped too.

However, Clinton and Obama had the worst midterm losses in this era, in 1992 and 2010, much worse than Nixon/Ford in 1974, and despite positive but weak real wage growth. Does this mean the correlation is useless?

Here’s one way to save it: compare Presidents against themselves. While Clinton and Obama had poor showings in their first midterm elections, their second midterms were much better — and had much better wage growth! Ditto for Nixon, though in reverse: his first midterm was pretty good, and so was real wage growth. Reagan had similarly bland real wage growth rates in both midterms, and had similarly mediocre Congressional losses. Bush did worse in his second midterm — again, you could blame a reverse-9/11 effect, with voters now weary of the global War on Terror, but wage growth was also worse.

What does this all mean for Trump? While we don’t have the full wage growth picture yet, through 18 months it has been pretty mediocre: 0.3%, and falling in recent months due to inflation exceeding wage gains for most of 2026. On social media and among pundits, a lot of people are trying to make comparisons to Biden. “But gas prices were even higher under Biden!”

If Figure 1 is at all useful, it is probably most useful to compare Trump to himself, in his first midterm. Wage growth through November 2018 was about 2.1%: not bad, not great. And he suffered middling Congressional losses. Because wage growth will almost certainly be much worse this time around, we can expect Trump to perform much worse than in his first, 2018 midterm. If Democrats pick up 20 seats in the House and 5 seats in the Senate (current prediction markets suggest about this many), this will put Trump pretty close to the Reagan 1986 point in Figure 1. That feels about right, given recent history, though it wouldn’t be surprising if the Republicans lost even more seats, since that would be a Congressional shift not much different from Trump’s first midterm.

Family Income Continues to Grow in 2025 Data

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Yesterday the Census Bureau released their annual treasure trove of data from the Current Population Survey, Annual Social and Economic Supplement. Loads of new data are now available for 2025 on income, poverty, and health insurance coverage. This new data allows me to update one of my favorite charts, showing the distribution of family income in the U.S. since 1967. Census releases this data by grouping families into nine different income groups, which I have collapsed into three groups, each being as close to one-third of the total as I can get using the publicly available data.

Figure 1

See also a similar chart from Mark Perry which uses household income (rather than family income) over the same time period.

Figure 1 shows that, adjusted for inflation, the proportion of families with income over $150,000 has grown almost seven-fold since 1967. There has been a roughly constant one-third of the population between $75,000 and $150,000, and the ranks of those under $75,000 has been cut in half since 1967. Again, these dollar figures all adjusted for inflation, using the preferred deflator of the Census Bureau.

What’s even more astonishing is when we look at the number of families at various thresholds, rather than just the share, as seen in Figure 2.

Figure 2

In 1967 there were fewer than 3 million families with incomes over $150,000 (in 2025 inflation-adjusted dollars). By 2025, that had grown to over 31 million families. If we look at the highest income threshold in this Census data — over $200,000 — the number of families has grown from just 1 million in 1967 to over 20 million in 2025. And there are fewer lower-income families too: the number of families under $75,000 shrunk, not just as a proportion of the total as seen in Figure 1, but even in absolute terms by almost 3 million families from 1967 to 2025.

Of course, some of these families do have more earners than in 1967, though we shouldn’t overstate that too much. Using other data from Census, we can see that the share of families with multiple earners hasn’t increased much since 1967, and especially hasn’t since the mid-1990s.

Table 1

As seen in Table 1, as far back as 1967 the majority of families in the U.S. had multiple earners. Now it’s true these were not all married couples with both spouses working full-time, and hours of work in the household have risen over time — but not much since the 1990s. This data is somewhat skewed by the aging of the population, as evidenced by the rising number of families with no earners. But even if we drop those families with no earners, multiple-income families haven’t grown much: from 58% of the total in 1967 to 63% in 2025.

Women Have Always Worked, Often in the Formal Labor Force

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In a February 2025 blog post, I created a chart showing male and female work patterns both inside and outside the home, going back to 1900. The data was for the United States, and the general trends were more female work in the paid labor force, more male work in the household (rather than paid labor force), but overall total hours of work being roughly constant from 1900 to 2023 (on average, of course).

Despite women always working, 1900 did look a lot different: adult working-age women in the US spent about 50 hours per week working in their own household, and a little under 10 hours per week in the formal paid labor force. Men were almost a mirror image of this (though working a few hours less per week in total).

So the gradual change over the 20th century was a huge shift in gender roles, and by 2023 women on average spent about the same number of hours in household and paid work. But the US is something of an anomaly here. Female labor force participation was higher — in some cases much higher — in other developed countries around 1900. Using data collected by Claudia Olivetti, here are female labor force participation rates for working age women (generally ages 15-64) around 1890-1900 (I average across years if there are multiple estimates):

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Median Family Income for Married Couples With Children Is Probably Higher Than You Think

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In 2024, median income for married couples with children at home was $143,400 in the US. That’s an almost 80 percent real (inflation-adjusted) increase since 1974, the first year Census reports comparable data. Is there some selection bias in who chooses to get married and have kids? Yes. Has there been an increase in dual-income families? Yes, but probably much less than you think (the median family of this type already had two earners by the late 1970s).

With those caveats, this is still pretty impressive:

Nicholas Polson Has Written Over 200 Academic Papers in 2026 (so far)

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UPDATE: I stupidly didn’t realize my co-blogger Mike wrote about this too. My bad! I skimmed last week’s posts, but it didn’t click in my head. Be sure to read his thoughts.

ALSO: lots of the papers by Polson seem to have vanished from SSRN since I wrote this blog post… yesterday. Everything after August 14th has been taken down. That brings his count of papers in 2026 down to a mere 168 papers. Still essentially several lifetimes of output from a typical academic.

CODA: As Andrew Gelman documented in real time, all of the papers appear to have been removed from SSRN for now. No explanation as of yet, but you can still see many of the papers listed (for now) on Polson’s Google Scholar page.

For most academics, writing papers that may be eventually published in peer-reviewed journals is an important part of what we do. For some academics, it is the main thing they do (others have more emphasis on teaching courses at their university). Most academics always have a few projects they are working on, with perhaps a goal of finishing 2 or 3 a year, and thus having a regular pipeline of a few publications every few years. But some academics are much more prolific.

Take Daron Acemoglu for example. He has long been considered extremely prolific. So far in 2026, according to his Google Scholar page, he has had 15 papers that have either been published this year or come out as new working papers (that’s the bulk of them). In the past year (2025 and 2026), he has had publications in the Quarterly Journal of Economics, the American Economic Review, and the Journal of Economic Literature, among others (the AER paper was his Nobel lecture). For lower tier academics, that’s almost a lifetime of publications in 12 months or so. Acemoglu is extremely productive.

But I just discovered an economist that is, apparently, even more productive than Acemoglu, at least as measured by working papers. Nicholas Polson has, by my count using his SSRN page, already written 258 working papers in 2026 alone. He’s already written (or at least published to SSRN), six papers today, August 26, 2026. In the month of August 2026, he has written and posted to SSRN a total of 104 papers — and counting, since the month isn’t quite over.

These aren’t just short notes. Most of the papers are of normal academic length: 32 pages, 27 pages, 58 pages. The papers are both theoretical — involving complex math in some cases — or empirical, with regressions. Read any single paper, and it feels like just a normal academic paper, the kind of thing that an academic might work on for a few months. He even has a frequent co-author, which is common for economics papers (and helps to be more productive), a systems engineering professor named Vadim Sokolov, who is a co-author on a little over 100 of the papers this year.

What is going on here? Obviously the research productivity of Polson and his co-author Sokolov is aided by AI. Who isn’t using AI to increase their writing and research productivity these days? But I don’t think I have seen any academic, at least not in economics, that has really pushed it to the limit.

Presumably, many of these papers will get submitted to academic journals. I can imagine the editors of journals have a very hard job these days, as the number of papers submitted has likely increased significantly, while the time that referees have available has not increased much (of course, AI is likely making referees more productive too, though many journals ask you not to upload the paper into an AI program as a referee, since it is unpublished work when you are reviewing it).

I really don’t know where academic publishing goes from here. AI has made us all more productive in terms of output, but are we better at answering important questions in our science than pre-AI? Probably, though it is hard to know. Journals and the peer review process has traditionally been the filter to sort real contributions from gibberish. I don’t know how the peer review process continues in its current form given the massive increase in output (much of it good!) that we are seeing from academics. Dr. Polson is just a leading example of a growing challenge for academia.

Welcome Back to School: Potential College Students are Now Declining

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If you have spent any time around higher education lately, you have probably heard of the “demographic cliff” or “enrollment cliff” for years now. Well, it’s finally here. In terms of total number of births, the US peaked in 2007 at a little over 4.3 million births. That’s the highest year ever, even higher than the peak of the Baby Boom (not in terms of fertility rates, of course, I’m just talking about absolute number of births).

Babies born in 2007 turned 18 in 2025. But after 2007, births started to fall. In 2025, there were just about 3.6 million births, a decline of about 700,000 babies since 2007, or a 16 percent decline. The number of 18-year-olds won’t be exactly the same as the number of births in a given year: it’s actually usually a bit higher, as net immigration is much larger than the small number of children that die before they reach 18. For example, the 1982 birth cohort had 3.68 million babies, but 18 years later in the year 2000 there were 4.08 million potential college students.

Historically there have been about 10 percent more 18-year-olds than the birth cohort, but lately (2021-2025) it has only been about 5 percent higher than the birth numbers.

There are, of course, all kinds of social, economic, and political implications of falling births. I just want to mention one that is specific to the industry that I work in: potentially falling college enrollment. And because this enrollment will not be uniform across states and universities, this will cause serious budget issues for many colleges in the coming years.

Some folks in higher ed have lately been asking when the demographic cliff will hit. It’s here: