Crémieux Profile picture
Oct 27, 2024 12 tweets 4 min read Read on X
What does labor-saving technology do to workers? Does it make them poor? Does it take away their jobs?

Let's review!

First: Most papers do support the idea that technology takes people's jobs.Image
This needs qualified.

Most types of job-relevant technology do take jobs, but innovation is largely excepted, because, well, introducing a new innovation tends to, instead, give employers money they can use to hire people. Image
But if technology takes jobs, why do we still have jobs?

Simple: Because through stimulating production and demand, it also reinstates laborers!

This is supported by the overwhelming majority of studies:Image
This reinstatement effect is largely consistent across types of technology, with innovations still looking a bit odd.

That is the weirdest category of technology besides "other", so roll with it. Image
Now the operative question is, if workers lose their jobs and end up reinstated in other jobs, what happens to their incomes?

Well, technology introduction tends to boost incomes!Image
Across types of tech, this result is pretty consistent: studies agree, technology makes us richer! Image
But, you might ask, whose income is boosted? Because if reinstatement affects far smaller numbers of workers than replacement, some people might still be getting shafted.

Well, the net employment effects of technology are highly ambiguous:Image
If we look across types of technology the picture I mentioned above for innovation-style technology shows up again: many studies suggest it's good for employment. Image
The reason impacts on net employment are so ambiguous is because they really have to be qualified.

For example, in general, when robots cause manufacturing employment to fall, there's a compensatory effect on service-sector employment that's at least as large in magnitude: Image
What makes that impact so interesting is another way it's qualified: It's smaller in industries more at-risk of offshoring.

In other words, industrial robots save American jobs from going overseas.Image
Industrial robots also contribute directly to reshoring. In other words, when Americans buy robots to do their manufacturing, Mexicans lose their jobs.

The welfare impact for domestic workers is positive. Not so for Mexicans, but that's just how things go. Image
Overall, labor-saving technology is clearly good, and the longer we delay adopting it, the poorer we will be relative to the world in which we picked it up immediately.

Want to know more? Check out my latest article: cremieux.xyz/p/workers-for-…

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More from @cremieuxrecueil

Jan 27
The researcher who put together these numbers was investigated and almost charged with a crime for bringing these numbers to light when she hadn't received permission.

Now we have an update that goes through 2020!

First: Where are Sweden's rapists from?

Mostly not Sweden. Image
What countries were those foreign rapists from?

We only got information on the top five origins, constituting roughly half of the foreign-born samples, and thus about a quarter of all the rapists. Image
What about welfare usage? 35.1%.
Alcoholism? 14.9%
Drug addiction? 23.7%
A diagnosed psychiatric disorder besides that? 13%

What about a criminal prior? 52%. That compares to 13.4% of non-rapist criminals. So rapes? Considerably more preventable.
Read 5 tweets
Jan 17
Greater Male Variability rarely makes for an adequate explanation of sex differences in performance.

One exception may be the number of papers published by academics.

If you remove the top 7.5% of men, there's no longer a gap! Image
The disciplines covered here were ones with relatively equal sex ratios: Education, Nursing & Caring Science, Psychology, Public Health, Sociology, and Social Work.

Because these are stats on professors, this means that if there's greater male variability, it's mostly right-tail
Despite this, the very highest-performing women actually outperformed the very highest-performing men on average, albeit slightly.

The percentiles in this image are for the combined group, so these findings coexist for composition reasons. Image
Read 6 tweets
Jan 17
One of the issues with understanding Greater Male Variability on IQ tests is that groups that perform better tend to show greater variance

Therefore, to estimate the 'correct' male-female gap, you need to estimate it when the difference is 0

In the CogAT, that looks like this: Image
In Project Talent, that looks like this: Image
And comparing siblings in the NLSY '79, that looks like this: Image
Read 5 tweets
Jan 14
About a decade ago, a theory emerged:

If men do more of the housework and child care, fertility rates will rise!

Men have been doing increasingly large shares of the housework and child care.

Fertility is lower than ever.Image
In fact, they're doing more in each generation, but fertility has continued to fall. Image
The original claim, that men's household work would buoy fertility, was based on cross-sectional data that was inappropriately given a causal interpretation.

The updated cross-sectional data is as useful, and it affords no assurances about the original idea.

We should move on.
Read 4 tweets
Jan 13
American military veterans have a suicide problem.

Some have theorized the reason is deployment-related trauma.

Leveraging the random assignment of new soldiers to units with different deployment cycles, Bruhn et al. found that was wrong.

Deployment did not increase suicides. Image
Looking only at violent deployments (ones with peer casualties), there aren't noncombat mortality effects either.

What explains veteran suicide rates? Image
The reason seems to be that the proposition is wrong: veterans do not have increased suicide risk.

This may seem surprising, but it's not!

Their suicide rates are elevated over the general population because most of them are young White men. That group has a suicide issue. Image
Read 8 tweets
Jan 12
That aspect is probably not that unrealistic, unfortunately.

Across the OECD, on average, just 55% of 15-to-16-year-olds got this question right, and no country saw 80% get it.

Most people globally *do* struggle even reading simple tables. What else?

Thread.🧵 Image
That table-reading question is "Level 3", which, amazingly, corresponds to an already-high level of ability, by global standards.

This is a simpler Level 1 question, but with this, 92% of the OECD got it, including just 65% of Brazilians and 53% of Peruvians. Image
Level 2!

Just 77% of the OECD got this, with less than half of the Mexican population being up to the task.

In fact, only Asian countries got over 90% on this trivial question. Image
Read 9 tweets

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