I have seen it many times. It comes from this Washington Post article, but it seems to go viral on Twitter about every 6 months or so.
The implication of the chart seems to confirm what many young people feel in their bones: Boomers had it much easier, and it’s getting harder and harder for later generations to catch up and build wealth. For many the graph… explains a lot, as one recent viral Tweet put it (in the weird world of social media, 5 short words and a recycled chart are all it takes for 20,000 retweets).
But wait. A few questions probably come to mind. For example, when Boomers were young they comprised a much larger share of the population. The original article makes an attempt to adjust for this, by calculating a few ratios towards the end of the article. However, there’s a much more straightforward way to adjust for this, which also nicely fits into a chart: put wealth in per capita terms!
If we do that, here’s the chart we get (also, of course, adjusted for inflation).
Data is for 1989-2021 from the Federal Reserve’s Distributional Financial Accounts, but only the first quarter is available right now for 2021. For 1989, it is the average of the third and fourth quarters. Population data comes from Census single-year of age estimates for various years. 2020 and 2021 population estimated using growth rate from 2010-2019.Continue reading →
How well do masks work at preventing disease transmission? This is a question that many of us have been asking throughout the pandemic. I have been trying to read as much about mask effectiveness as I can (for example, here’s a Tweet of mine from way back in June 2020). I think the bottom line is that, if you want really good RCTs of mask use during the COVID pandemic, there is surprisingly little evidence in any direction. But there are lots of studies, less well done but still OK, suggesting that masks do provide some protection.
I don’t want to wade into all of that research here, because Bryan Caplan has been doing that lately himself. His reading of the literature is that masks aren’t a silver bullet, but he suspects “that masks reduce contagion by 10-15%.” Still he thinks that the costs of masks (inconvenience, discomfort, and dehumanization) are large enough that they don’t pass a cost-benefit test. But this seems like a very strange conclusion given that he suspects masks reduce contagion by 10-15%! So let’s be explicit about the cost-benefit analysis.
[I am assuming that reducing contagion by 10-15% means 10-15% fewer cases and deaths. I see this as a bare minimum, since contagious disease can follow exponential growth trends, so 10-15% less contagion could mean that cases/deaths are reduced by more than 10-15%, but I’m making a simplifying assumption and the hard case.]
Quantifying the costs of the pandemic deaths is tricky, and it’s something that Bryan and I have debated before. Perhaps this is just a rehash of that debate (Bryan is highly skeptical of the VSL estimates), but I think it’s worthwhile to plug in some numbers.
It’s time to head back to school! Which means it’s time for college students to once again ask the question: How am I going to pay for this?
It’s common knowledge that college is expensive and getting more expensive every year. A Google search for “skyrocketing tuition” produces almost 60,000 results. But whenever a fact is so commonly accepted, it’s worth asking if it’s really true.
Here’s one way to think about: are college tuition and fees increasing faster than the overall rate of inflation? For much of recent history, the answer has been most definitely “yes.” I start the series here in 2006, because there were some methodological changes to the index just before 2006. Cumulatively, college tuition and fees (as measured in the CPI) have increased by 78%, while prices overall have only increased by about 38%.
But for the very recent history, since 2017, the answer is “no.” College tuition and fees have often been increasing at slower rates than overall prices in the CPI, and the difference is especially dramatic in 2021. Since 2017, overall prices have increased by about 12.4%, but college tuition and fees has only increased by 7.8%.
However, even this data overstates how much tuition and fees have gone up for undergraduates in the US!
The latest inflation data for the US has been released, and the headline CPI-U annual increase of 5.4% is once again raising worries that high inflation could be a permanent part of the landscape for the near future.
My personal opinion is that the picture is much too muddled now, between temporary supply issues and low bases for 2020 prices, to say much about the medium-term picture. I think we’ll have a better picture by the end of the year. Still, it’s worth drilling down into the data, as we have done in the past on this blog, to understand some things about economics, prices, and how price changes are impacting real people.
Certainly the prices of some goods are rising at alarming rates. Many of these are related to automobiles and transportation generally, but some categories of food have rose a lot in the past year too (though groceries overall are only up 2.6%).
But I want to talk about two categories of consumption: beer and hot dogs.
Actually, my co-blogger Zachary has already written about beer. And using the producer price index, he found that canned beer is actually cheaper than it was a year ago. If you like canned beer, rejoice! And for all beer at home, the CPI shows only a 1.8% increase since last year, after a similar small 1.6% increase last July (not much of a base effect… a clue for later!).
But not all Americans consumer alcohol. So let’s talk about that most American food product: the hot dog.
To try and encourage vaccination during the on-going COVID pandemic, there have been many public and private incentives offered. For example, free doughnuts. Or offering $200 to state employees in Arkansas (taxable income, of course!).
But when the governor of Ohio announced on May 12, 2021 that they would be offering a $1 million lottery prize, with 5 winners, it took the incentive game to a new level (college scholarships were also a prize for 5 winners under 18).
So do the lotteries “work”? Do they get more people vaccinated? And even if they do “work,” does it pass a cost benefit test? Many expressed concern that, even if more people get vaccinated, that this is a lot of money to spend in uncertain budget times.
What do they find? First, vaccine lotteries do work! They estimate that vaccination rates increased by 1.5% in Ohio because of the lottery. This amount is above and beyond the increase that would have been expected without the lottery (by comparing Ohio to other states that didn’t use a lottery — this is what the synthetic control method does).
Lately there has been lots of both good and bad news about the pandemic and its impact on the economy. But here’s once piece of good news you might have missed: the recession which began in February 2020 ended in April. And not April 2021… it ended in April 2020. At least, that’s according to the NBER Business Cycle Dating Committee, which made the announcement last week.
The 2020 recession of just 2 months is by far the shortest on record. NBER maintains a list of recessions with monthly dates going back to 1854 (there are annual business cycles dates before that, including important modern revisions of the original estimates, but the monthly series starts in 1854). In that timeframe, there have been 7 recessions in the 6-8 month range, but nothing this short. Still, it was mostly definitely a recession, as unemployment briefly spiked to levels not seen since the Great Depression. But only for 2 months. Keep in mind that the first part of the Great Depression last 43 months.
Unemployment Rate, 1948-present
But how can this be? Is the recession really over? There are still about 6-7 million fewer people working than before the pandemic began. Lots of businesses are still hurting. The unemployment rate is still 2 full percentage points above pre-pandemic levels. How in the world can we say the recession ended 15 months ago?
To answer that question, it helps to know what NBER and most macroeconomists mean by a “recession” — essentially, it is used interchangeably with “contraction.” It means the economy, by a broad array of measures (NBER uses about 10 measures), is shrinking — or we might say, going in the wrong direction. The only other option, at least in the NBER chronology, is an expansion — when the economy is going in the right direction.
Does an economic expansion mean that everything is fine the economy?
We have known for a long time (basically since the start of the pandemic) that COVID primarily affects the elderly. Infection fatality rates are hard to calculate (since not all infections are reported), but most of the data suggest that the elderly are much more likely to die from COVID than other age groups.
For some, this has become one of the most important aspects of the pandemic. For example, Don Boudreaux emphasizes the age distribution of deaths many times in a recent episode of Econtalk, and he uses this point to argue that we addressed the pandemic incorrectly (to say the least). Boudreaux specifies that COVID is only deadly for those 70 and older. And while I won’t rehash the argument here, please also see my exchange with Bryan Caplan, where he argues that elderly lives are worth a lot less than younger lives (I disagree).
At first blush, the data seems to bear that out. The CDC reports that almost 80% of COVID-involved deaths were among those aged 65 and older (I will use the CDC’s definition of COVID-involved deaths throughout this post). In other words, of the currently reported almost 600,000 COVID deaths in the US, about 475,000 were 65 and older. Throw in the 50-64 age group, and you’ve now got 570,000 of the deaths (95% of the total).
But is this the right way to think about it? Remember, the elderly always account for a large share of deaths, around 75% in recent years. So it shouldn’t surprise us that most deaths from just about any disease are concentrated among the elderly.
You have probably seen the latest inflation data. The headline number is 5.4% increase in prices in the past year as measured by the CPI-U. That’s a lot! Even the Core CPI (removing volatile food and energy) is up 4.5%.
If you follow the data closely, you may also have heard that a big chunk of that increase comes from prices related to automobiles: new cars, used cars, rental cars, car parts. All way up!
If you are in the market to buy a car, or if you really need a rental, it’s a bad time for prices. (Conversely, if you have an extra car sitting around, it’s a great time to sell!)
But what if you aren’t in the market for a car? What does the inflation data look like? The White House CEA tweeted out this chart to deconstruct the factors in the recent CPI release.
Key sentence from the abstract: “In the San Francisco, Los Angeles, and Seattle metropolitan areas, the price of land everywhere within those three markets having been bid up by amounts that at least equal typical household income.”
Economists, libertarians, and more recently “neoliberals” have long complained about land-use restrictions as a primary factor contributing to unaffordable housing. This paper provides some pretty solid data, at least for some housing markets.
Here’s a key chart from the paper, Figure 5. Notice that there is a lot of heterogeneity across cities. In San Francisco, land use restrictions add roughly four times the median household income to the price of housing. But in places like Columbus, Dallas, and Minneapolis, there is essentially no zoning tax. That’s not because these cities have no land use restrictions! It’s just that they aren’t currently binding.
The paper also notes that “zoning taxes are especially burdensome in large coastal markets.”
This is similar to what I showed in a very non-scientific map that I created (in about 5 minutes) for a Twitter thread that I wrote in January 2020 on housing prices. In that map and thread I pointed out that there are still lots of fine US cities where you can purchase homes for roughly 3 times median income (a commonly used rule of thumb for affordability).
Cities where you can buy the median house for about 3 times median income.
Will these cities continue to be affordable in the future? As demand increases, and supply-side restrictions remain in place, we would predict the same thing will happen to Columbus as happened to San Francisco. But probably not for decades.
So if you seek housing affordability, move to the Zone of Affordability! But let’s also work on reforming the rest of the country to make everywhere affordable.
On Sunday the world lost a great teacher, economist, and all-around fantastic person in Steve Horwitz. If you don’t know about Steve, I recommend reading the tributes from Pete Boettke and Art Carden.
Pete and Art speak to Steve’s overall legacy and greatness. But I will tell you about a very specific piece of advice that Steve gave me about teaching undergrads.
Steve called it “the graduate student disease.” By this he meant the tendency of newly minted PhD economists to teach undergraduate courses as if they were mini versions of graduate courses. Steve insisted this was the wrong approach.
