• Why Is Everyone So Upset Over Ukraine?

    The latest from the brain of Donald Trump:

    This doesn’t surprise me. I don’t think Trump really gets the distinction that dirt on Joe Biden is a personal benefit, not a national benefit of the kind you get during, say, a trade negotiation. To him, his reelection campaign is just another part of his presidency. So why is everyone getting so upset?

    That’s Trump for you. The bigger problem is that I suspect an awful lot of the public doesn’t immediately get the distinction either, and we’ve done a poor job of hammering it home.

  • Why Are So Many Black Men in Prison?

    One of our new writing fellows, Camille Squires, published a piece on Monday telling us that the “Kamala was a cop” meme didn’t originate with Bernie-bro-ish white guys. Rather, it originated on Black Twitter among African Americans who were keenly familiar with Kamala Harris’s mixed record as California’s attorney general. Harris billed herself as California’s “top cop,” and in this era of mass incarceration that just didn’t sit well. It’s a good piece, and I only wish it had been longer since I would have been interested in a deeper dive into exactly what Black Twitter thought of Harris.

    Squires’s piece also reminded me that, after years of not getting around to it, I finally read Michelle Alexander’s groundbreaking book, The New Jim Crow, a few weeks ago. For those of you who haven’t read it, here’s a nickel summary:

    Alexander argues that America has a long history of controlling the black population by whatever means it can get away with. First it was slavery. Later, when that was outlawed, we turned to Jim Crow because it was the best we could do. Then, following the civil rights era, we turned to mass incarceration. It wasn’t as effective as either slavery or Jim Crow, but again, it was the best we could do.

    The core of Alexander’s case is the obvious one: we imprison a lot of people, and among those people we imprison a far bigger share of African Americans than we do of white people. The excuse for this is the war on drugs, which led to the arrest and incarceration of vast numbers of black men. Crucially, Alexander says, we arrest black men for drug offenses that we barely touch white men for. We make up lots of reasons for this, but they mostly turn out to be spurious. Basically, even though black and white men are involved in the drug trade about equally, we mostly imprison only black men for violating our drug laws.

    One of the things that struck me as I was reading The New Jim Crow was that it sounded familiar. Not just in its themes, but almost literally. And then it hit me: it sounded very much like some of the things that Angela Davis and her colleagues wrote about incarceration in the early 70s. After rummaging around a bit, I finally found what I was thinking of: an essay by Bettina Aptheker called “The Social Functions of the Prisons in the United States,” part of Davis’s 1971 essay collection If They Come In the Morning. I reread it, and it was eerily similar to Alexander’s book.

    But it was written 50 years ago. How could it be so similar if Alexander was focused on two recent phenomena: the era of massive prison construction and the war on drugs? And that in turn prompted me to think about timing: Alexander’s argument could only be persuasive if the data on black imprisonment fits the timing of the war on drugs. So I started to root around. This chart is the result:

    This data is surprisingly hard to come by, and I had to cobble it together from a wide variety of sources. Luckily, in 1991 the Bureau of Justice Statistics published a short study called “Race of Prisoners Admitted to State and Federal Institutions, 1926-86.” I say “luckily” because this is not a statistic that can simply be pulled from a database somewhere. A researcher has to dig into the data, clean it up, and finally come up with a reliable and consistent table of data that covers a long time period. I also say “luckily” because this appears to be the only study ever done on this exact subject and it forms the backbone of my chart.

    That’s the dark blue line. The orange line is simple prison population by race, and this is a little easier. Early data comes from census reports and later data from annual Justice Department bulletins. As you can see, it follows the blue line pretty closely and provides a good check that the 1991 study is fairly reliable.

    So what does this show us? Surprisingly (to me, anyway), what it shows is that there wasn’t a huge surge in the rate of black imprisonment during the drug wars of the 70s and 80s. Rather, the share of black men being arrested and imprisoned has gone up slowly but steadily since at least 1926. Between 1970 and 1990, the total number of people in prison skyrockets, but the share of prison admissions that’s black continues the same slow ascent it’s displayed all along.

    I’m not sure what to make of this. Alexander’s argument about the war on drugs might still be correct. Contrary to what most people think, our nation’s prisons aren’t mostly filled up with drug offenders. It’s mostly filled up with robbers and murderers and carjackers and other folks who have committed violent crimes. So even if the drug offenders who are arrested and imprisoned are very heavily black, it might not affect the overall black imprisonment rate a lot.

    I’m not sure, and I’m not going to draw any conclusions here. Maybe I’m missing something in the data. Or maybe it doesn’t matter. Maybe the black share of prisoners didn’t change much during the prison-building boom of the 70s and 80s, but the simple act of imprisoning more people was all we needed to make sure we got lots of black men off the streets and under the control of the criminal justice system. If a few white men were collateral damage, so be it.

    Either way, though, it seems like the story changes. The war on drugs, in particular, doesn’t seem like it had a noticeable effect on black imprisonment rates, and Alexander tosses around numbers so blithely in her book that it’s impossible to construct a consistent statistical argument from them.

    The New Jim Crow was published in 2012, and it’s entirely likely that it’s been discussed to death since then. Maybe my objections here are nothing new and have been addressed before. But if they have, I haven’t noticed it. I’m curious if anyone has anything to say about this.

    POSTSCRIPT: It’s worth noting that the imprisonment rate of black men began to fall a couple of decades ago and has continued to fall ever since. It’s still far higher than the white imprisonment rate, but there’s at least some progress being made.

    I’d also like to point out, as usual, that even if you think the prison-building spree of the 70s and 80s was misguided, it wasn’t completely irrational. Violent crime really did start to skyrocket in the mid-60s, and it really did scare people—including black people in urban cores who were the most numerous victims. As we now know, the crime increase was largely caused by lead poisoning, but nobody knew it at the time. They just knew that their streets were unsafe and they wanted something done about it.

  • No Surprise: Health Insurance Saves Lives

    It’s really hard to evaluate the effect of health coverage on health. Sure, you can compare groups with and without coverage, but they’re almost certain to be so different (in income, race, employment, age, etc) that it’s impossible to tease out the effect of health coverage itself. Ideally, you’d like to perform a randomly controlled trial where you take a single group and then randomly split it in half. One half gets coverage and the other doesn’t. Since the two groups are the same, it’s fairly straightforward to measure health differences and then calculate how they’re related to coverage.

    Unfortunately, an RCT is all but impossible in this arena. How do you randomly deny health coverage to half a group, after all? It’s basically only been done once, when Oregon conducted a lottery to decide who would qualify for Medicaid coverage from a group of people on a waiting list. The Oregon study was interesting, but the sample size was smallish and the results have been hard to quantify.

    But now a team of researchers has conducted a different kind of RCT. In 2015 the IRS sent out a letter to people who paid a penalty for not having health insurance and provided them with information about the cost and availability of getting coverage via either Medicaid or one of the Obamacare exchanges. Millions of letters were sent out, but 14 percent of the group was randomly selected to not receive the letter. Here’s how that affected coverage in the following year:

    The difference in takeup rates is about one percentage point. This may seem small, but when the test group is very large that’s plenty to deliver reliable results. Here’s what happened:

    The control group, which had lower rates of coverage, also had higher mortality rates. The difference is small, about 0.05 percentage points, which is not surprising since the death rate for middle-aged people is pretty small to begin with (in fact, the mortality part of the study was limited to individuals aged 45-64, since younger age groups have virtually zero mortality). But again, given the large size of the test group, it’s quite possible to draw conclusions from this difference:

    We found positive effects of the intervention on subsequent coverage enrollment decisions, particularly for taxpayers who were uninsured in the year prior to the intervention. We also found that the intervention reduced mortality among middle-aged adults in the subsequent two years, which we attribute to the additional coverage the intervention induced. Our findings thus provide strong empirical support, and the first experimental evidence, for the hypothesis that health insurance coverage reduces mortality.

    I’ve argued for a long time that focusing too much on mortality is misguided. Not only are mortality differences small among the non-elderly to begin with, which makes it hard to study even under the best circumstances, but mortality is a tiny part of what health care is about. By far, the greatest effect of health care for most of us is simply to make us feel better. We get antidepressants. We get flu shots. We get CPAP machines. We get artificial knees and hips. We get asthma inhalers. Most of these things have either no effect on mortality or only a tiny effect. Nonetheless, we’re collectively willing to pay a lot of money for this care, and we lead far better lives because of it.

    That said, it’s common sense that health coverage should also have some effect on mortality, and arguments to the contrary have always seemed a little silly to me. How could it not? That makes it nice to see experimental evidence confirming this.

    As always, this is just a single study and it might turn out that there are flaws in its design. Still, it’s the first to make use of a truly large test group, one that’s big enough to pick up tiny differences. And those differences, it turns out, are real.

  • On the Eve of Election, BoJo Hides In a Fridge

    Andrew Parsons/i-Images via ZUMA

    One of Piers Morgan’s producers tried to set up an impromptu interview with Boris Johnson this morning:

    When Swain presses the prime minister, stating he was live on the show, Johnson replied “I’ll be with you in a second” and walked off, before Piers exclaims “he’s gone into the fridge”. Johnson walks inside a fridge stacked with milk bottles with his aides. One person can be heard saying: “It’s a bunker.”

    Conservative sources subsequently insisted that Johnson was “categorically not hiding” in the fridge, from which Johnson emerged carrying a crate of milk bottles

    You know you’re having a bad day when your minders have to deny that you were hiding in a fridge. The election is tomorrow.

  • Latest International Test Shows American Performance Is . . . About the Same as Always

    The results of the latest PISA test are out, and since a picture is worth a thousand words, here’s a picture:

    The PISA test is administered by the OECD every three years to 15-year-olds, and roughly speaking American kids have been doing about the same on it for a couple of decades. However, what’s unique about PISA is that it’s an international test, which means we get to compare ourselves to other countries and then wail about how poorly we’re doing. Here are our scores on the reading test compared to a small subset of our peer countries:

    Not too bad! Canada is the outlier here, but we’re at the top end of the cluster of other countries. Now here’s math:

    Not so good! Japan is the unsurprising winner, and the US is bringing up the rear as it usually does. PISA’s approach to math is a little unusual, so every three years there’s a tedious discussion about whether this is the reason American kids don’t do very well even though they do fine on other math tests. Personally I don’t know. But we sure seem to fill up Silicon Valley and Wall Street with quants and coders every year.

    As always when I venture into OECD territory, I conclude that the whole test is a sham and the real test is whether or not you can figure out how to use the OECD’s data tools. I’ll give myself a B- this time around. However, you can also browse around the results on the Department of Education’s site, which includes comprehensive league tables that compare the US to the entire set of other countries that participate in PISA. Good luck!

  • Lunchtime Photo

    On Sunday evening Marian and I went down to the “Nights of 1000 Lights” at Sherman Gardens in Corona Del Mar. It was all quite lovely, of course, and among other things they had a Christmas tree where you could write down your Christmas wish on a red card and then tie it to a branch. Most of them looked like this:

    Uh huh. As usual, it took a child to show us the true spirit of this magical season:

    December 8, 2019 — Corona Del Mar, California