besttrousers

Professor Peterson,

Thanks for joining us today!

I’m a behavioral economist who works on labor issues, and I’ve been reading some of your work, such as the Self-Authoring Suite, with interest. It’s helping me think about potential interventions to help unemployed people rejoin the labor force. Thanks for putting it out there!

However, I’ve also been very frustrated to hear some of the claims you’ve made about economics, many of which been inaccurate.

It’s important to be precise in your speech, so I’ll give you two examples, before my question (I apologize for the length, but I thought it was important to provide the original quotes, and a brief summary of why they were incorrect):

Example 1

Here’s an excerpt from your recent interview with Cathy Newman:

Newman: Okay. Sure. But I want to put to you that here in the UK, for example, let’s take that as an example. The gender pay gap stands at just over 9%. You’ve got women at the BBC recently saying that the broadcaster is illegally paying them less than men to do the same job. You’ve got only seven women running the top FTSE 100 companies!

Peterson: Yeah.

Newman: So it seems to a lot of women, that they are still being “dominated and excluded”, to quote your words back to you.

Peterson: It does seem that way, but multivariate analysis of the pay gap indicate that it doesn’t exist.

Newman: But that is not true, is it? I mean, that nine percent pay gap! That’s a gap between median hourly earnings between men and women!

Peterson: Yeah, but there’s multiple reasons for that. One of them is gender, but it’s not the only reason. If you’re a social scientist worth your salt, you never do a univariate analysis. Like you say, well women in aggregate are paid less than men. Okay, well then we break it down by age, we break it down by occupation, we break it down by interest, we break it down by personality.

Your claim that “multivariate analysis of the pay gap indicate that it doesn’t exist.” Is incorrect. For an overview of research in this area, you can see Blau and Kahn’s 2017 review of the literature.

I suspect that you are looking at analyses that include occupational controls (based on what you said in the interview, and tweets like this one).

However, using occupational controls in this way is actually leads to a flawed analysis, as women choose what occupation to pursue. If women are being discriminated against in a given field, you would expect them to be less likely to pursue a career in that field. Including occupational controls will therefor lead to a biased estimate. It’s what statisticians call “collider bias”.

(For details, see the discussion of this issue on page 74 of Causal Inference, or the /r/economics FAQ)

Example 2

In one of your lectures, you said the following:

Because women have access to the birth control pill now and can compete in the same domains as men roughly speaking there is a real practical problem here. It's partly an economic problem now because when I was roughly your age, it was still possible for a one-income family to exist. Well you know that wages have been flat except in the upper 1% since 1973. Why? Well, it's easy. What happens when you double the labor force? What happens? You halve the value of the labor. So now we're in a situation where it takes two people to make as much as one did before. So we went from a situation where women's career opportunities were relatively limited to where there they were relatively unlimited and there were two incomes (and so women could work) to a situation where women have to work and they only make half as much as they would have otherwise.

There’s a lot that incorrect here – wages have not been stagnant since 1973 (I suspect you are thinking of household income, which has been more-or-less constant due to compositional changes due to later marriages), doubling the labor force would not halve the value of labor (the economy is not a fixed pie, more workers in the labor force grow the economy).

Most importantly, the premise is wrong. It’s not the case that it used to be possible for households to have one earner, and now it is not. Instead, what happened was we saw dramatic increases in the effectiveness of “household production” (think: laundry machines, clothes that need less frequent repair, microwave dinners). In 1965, the average women spent 32 hours/week on housework, and 10 hours a week on childcare – a full time job!

We aren’t poorer than we used to be, or working more. Instead, we’ve seen people effectively move from one industry (domestic labor) to another (firm labor).

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Question

I know you’ve found it frustrating when your research has been misrepresented in the media, so I’m sure you can understanding the frustrations economists have when reading or listening to you misrepresent economics. These are common mistakes (we catalog them all the time over at /r/badeconomics) but also would be pretty easy to correct by talking to an economist, or reading the relevant literature. It's also important not to make such mistakes. Many of your fans have read these and now incorrectly believe that their wages are lower because of women entering the workforce.

What is the mechanism you have been using to check the accuracy of the claims you make about economics – or other fields you are not an expert in? What can we economists (or other experts) do to help you better understand these fields?

Here's a link to the babysitting story at Slate.

Thanks for the response, though I'll note that you didn't answer my question! I'm sure you're busy with the other questions, but I'd love a response to the specific question if you are able to.

I'm not going to retract my claim that the entry of women into the workforce put downward pressure on male wages. I can't see how that could be otherwise (although it may not be something that applies over the medium to long term, which is at the base of your objection, I think).

It could be otherwise because women entered the workforce effects both the supply and demand for labor. ie, people who now have incomes will spend money. This is why you don't see wages decrease in response to normal population growth.

(You could imagine that there are things like big population shocks that change the labor/capital ratio - indeed, wages in Europe dramatically increased after the Black Death because of this. But slow and anticipated shocks would not have this effect).

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And the paper you cite directly notes that "The adjusted ratios [of female/male earnings rose over 1980-2010] from 71.1 to 82.1 percent in the human capital specification and from 79.4 to 91.6 percent in the full specification." So that indicates that a very large proportion of the gap has nothing to do with gender, per se, which is precisely the point I have been making.

It actually doesn't - which is the point I made about colliders. You can't look at human capital variation in a vacuum, because human capital occurs after gender on the causal chain.

The evidence for discrimination in labor markets is substantial - see here for a good overview of experimental evidence. For example, CVs with female names are much less likely to get interviews. A classic study showed that "blinding" hiring committees for musicians resulted in substantially more female hires.

Discrimination against women has been alleged in hiring practices for many occupations, but it is extremely difficult to demonstrate sex-biased hiring. A change in the way symphony orchestras recruit musicians provides an unusual way to test for sex-biased hiring. To overcome possible biases in hiring, most orchestras revised their audition policies in the 1970s and 1980s. A major change involved the use of blind' auditions with a screen' to conceal the identity of the candidate from the jury. Female musicians in the top five symphony orchestras in the United States were less than 5% of all players in 1970 but are 25% today. We ask whether women were more likely to be advanced and/or hired with the use of blind' auditions. Using data from actual auditions in an individual fixed-effects framework, we find that the screen increases by 50% the probability a woman will be advanced out of certain preliminary rounds. The screen also enhances, by severalfold, the likelihood a female contestant will be the winner in the final round. Using data on orchestra personnel, the switch to blind' auditions can explain between 30% and 55% of the increase in the proportion female among new hires and between 25% and 46% of the increase in the percentage female in the orchestras since 1970.

That said, as you rightly point out, it seems like the effects of discrimination have decreased over time.

Do you know of anyone who has both donated a kidney and had a caesarean? I'm curious what the comparison is.

obfuscation and confusing verbiage.

We asked for less of this.