Category: Uncategorized

Look, if homeopathic remedies make you feel better, take them. If the Paleo diet helps you eat fewer TV dinners, that’s great—even if the Paleo diet is probably premised more on The Flintstones than it is on any actual evidence about human evolutionary history. If non-organic crumbs bother you, avoid them. And there’s much to praise in Whole Foods’ commitment to sustainability and healthful foods.

Still: a significant portion of what Whole Foods sells is based on simple pseudoscience. And sometimes that can spill over into outright anti-science (think What Doctors Don’t Tell You, or Whole Foods’ overblown GMO campaign, which could merit its own article). If scientific accuracy in the public sphere is your jam, is there really that much of a difference between Creation Museum founder Ken Ham, who seems to have made a career marketing pseudoscience about the origins of the world, and John Mackey, a founder and CEO of Whole Foods Market, who seems to have made a career, in part, out of marketing pseudoscience about health?

From a must-read Daily Beast article titled “Whole Foods: America’s Temple of Pseudo-Science,” which contrasts the left’s embrace of pseudo-science in the form of dubious claims about foods (from homeopathic “remedies” to GMOs). I really wish I had been the one to write this, and bonus points for referencing the Whole Foods store that was the one grocery store within walking distance from our house when we lived in North Carolina.

Besides the left’s own love affair with pseudo-science in the form of bogus health claims, I never understood why the same left — usually so quick to decry the Tea Party, the Koch Brothers, and rag on “libertardians” — loves Whole Foods so much, given its CEO’s professed love of Ayn Rand and Austrian economists and his comparing Obamacare to fascism, no less.

Since around 1965, we have been living in the era of the self-expressive marriage. Americans now look to marriage increasingly for self-discovery, self-esteem and personal growth. Fueled by the countercultural currents of the 1960s, they have come to view marriage less as an essential institution and more as an elective means of achieving personal fulfillment. …

As a psychologist, I could not help noticing that this history of marriage echoes the classic “hierarchy of needs” outlined in the 1940s by the psychologist Abraham Maslow. According to Maslow, human needs fit into a five-level hierarchy: The lowest need is that of physiological well-being — including the need to eat and drink — followed by the need for safety, then for belonging and love, then for esteem and finally for self-actualization. …

My colleagues and I contend that an analogous process has occurred in our expectations about marriage.

From a New York Times op-ed on marriage by Eli J. Finkel, a psychologist at Northwestern University.

I guess what this means is that, much like development policy, the institution of marriage has stopped working because the average married American expects way too much for his or her partner. Or: much like there is such a thing as development bloat, there is also such a thing as marriage bloat?

Our own marriage is far from perfect, but when we read Finkel’s op-ed on Sunday morning, my wife and I both admitted that we hadn’t married each other for “self-expression,” for which we can each turn to our own individual interests, hobbies, and friends. In fact, when we find self-expression in each other, it really comes more as a positive externality than anything else. Given that, it might be that managing one’s expectations that one’s partner will always and forever be all that and a bag of chips the best prescription for a long and healthy marriage.

A recent letter to the editor of the New York Times, in response to an article titled “How Single Motherhood Hurts Kids“:

As the product of a single-mother family, I take issue with the broad generalizations in your article. To those single mothers who work diligently to provide good homes for their children, the headline itself is an affront. The assumption is that single motherhood hurts children and this is how that happens.

In fact, this article is really about single, low-income, multipartner mothers, many of whom are teenagers. That is only a segment of the broad range of mothers who are single.

Setting aside the claim that single motherhood hurts kids, which I am in no way qualified to assess, I wanted to make an important point for consumers of social science results with this post. My point consists of two related sub-points, viz.

1. The vast majority of findings in the quantitative social sciences are true on average.
2. By definition, there is a whole distribution around that average, which means that the effect might be negative for some, zero for others, and positive for still others.

In other words, if I tell you that having a college degree increases your annual income by $30,000 on average, it is likely that the along the distribution of the average treatment effect of going to college on annual income, there are some people for whom the effect is negative — they went to college, but they ended up with a worse job than they would’ve had otherwise gotten had they accumulated four years of experience instead — and there are some people for whom the effect is more on the order of $100,000 per year.

Does the author of the letter to the editor quoted above make the mistake of assuming that average effects are uniformly distributed? Not really, because he recognizes that if you condition on certain things (high-income, adult single-mothers who have few partners), the result is likely to disappear.

And it’s not just the general, non-quantitative lay readers of the New York Times who make the mistake of assuming a uniform distribution of treatment effects. Every once in a while, I will get a comment in a referee report that goes something like “You find that an increase in food prices increases the number of food riots, but there are cases where food gets so expensive that people eat too little and, as a consequence, they are too weak to riot” (this is a fictitious example, by the way). To which your response should be: “Well, yeah.”

The whole point of running regressions, in most cases, is to know what happens on average. To be sure, there is a certain movement toward characterizing heterogeneous treatment effects in applied microeconomics, but doing so is difficult, because causally identifying average effects is difficult enough as is, and causally identifying heterogeneous effects is even more difficult.