[X.com] by @BowTiedYukon

Wife asked our 13 year old to carry something upstairs for her

He said his legs were sore from his football game

She asked ā€œWhy are your legs sore? When you ran the ball you got tackled for a loss, you didnā€™t run anywhere. You went backwardsā€

Tough in this house

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[X.com] by @MattZeitlin

oh my god the way they teased out a causal effect lmaoooooo

"we exploit idiosyncratic variation in the extent of gender balance in fathersā€™ workplaces. Fathers who encounter more women in their relevant ageā€“occupationā€“group at work are more likely to divorce."

Quoted Tweet:

Journal of Public Economics @JPubEcon

Just published in @JPubEcon: "How does parental divorce affect childrenā€™s long-term outcomes?" By @WFrimmel (@jku_econ), @HallaMartin (@WU_econ), @EbmerWinter (@IHS_Vienna) https://t.co/gpesU9mXMn https://t.co/PRi6Jzdp0q

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View original tweet Sun Sep 29 18:35:47 +0000 2024

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[X.com] by @RogueWPA

The gender wage gap is mostly occupational sorting, hence feminists invented comparable worth. Alas, comparable worth requires the state to have godlike omniscience about human capital and compensating differentials. Result: a microcosm of the socialist calculation problem.

Quoted Tweet:

Rob Wiblin @robertwiblin

Jesus this is beyond idiotic: https://t.co/81PJ1i2Y6a https://t.co/MAM2cVzCfk

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View original tweet Thu Sep 12 10:47:51 +0000 2024

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[X.com] by @DrCamiloOrtiz

These data are really damning. Hard to think of another plausible explanation other than actual physical immaturity is being medicated.

Quoted Tweet:

Steve Stewart-Williams @SteveStuWill

"The graph below shows a worrying trend: The youngest kids in class are more likely to be treated for ADHD. This suggests that immaturity is sometimes being mistaken for mental illness, and that some kids are being unnecessarily medicated." https://t.co/zyk4QahinC https://t.co/BcMbsx8ZFU

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View original tweet Wed Sep 11 16:00:01 +0000 2024

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[X.com] by @david_perell

Michael Mauboussin is a researcher at Morgan Stanley, was Chairman of the Santa Fe Institute, and writes about finance and investing.

He's a master at turning complex ideas into strikingly simple writing.

Here are 12 lessons on writing taken from our conversation:

  1. The great gift of writing is it reveals how much you donā€™t know. Youā€™re forced to rethink your arguments and go back to first principles.

  2. Have something to say. Having a great style counts for nothing unless you have something worth sharing with the world.

  3. The main lesson from Michael: Writing is about understanding. You write to broaden your understanding, and in turn, help others do the same. You write to get your arms around an issue.

  4. How written communication is harder than verbal: in a conversation, you get feedback from the other personā€™s face. You can switch tracks midway if they look confused. In writing, you need to predict what might be confusing and deal with it beforehand.

  5. How to develop a style: Find language that resonates with you. Read newspapers, tweets, new bestsellers and old books. Pay attention to words that pop out, or phrases that echo in your memory long after you're done reading them.

  6. It's time to write when there's a gap between how much you know and how much you want to know. Find your knowledge-curiosity gaps, and youā€™ll have more essay topics than you can handle.

  7. Charlie Munger said to be a good thinker, you have to jump disciplinary boundaries. One way to do this is to read widely. If you donā€™t, your work will be swamped with cliches.

  8. Examine the intellectual history of words. Error and mistake, for example, are not synonyms. Luck and fortune do not mean the same things. Your word usage will dramatically improve once you know their historical background.

  9. If Michael is learning a lot without teaching much, he feels out of balance. If heā€™s teaching a lot without learning new things, he feels out of whack again. The takeaway of the previous point: learn a lotā€¦ then share it with others. Write about it. Teach it. Sync the input and the output.

  10. A great quote from mathematician Carl Gauss: ā€œNot notations, but notions.ā€ Math is full of complex notations but what matters more are the notions, the ideas, behind them. Writing is no different. Figure out the important underlying idea you want to share, and make it straightforward and accessible.

  11. Great teachers are great learners. Theyā€™re not just trying to pass on their body of knowledgeā€¦theyā€™re constantly looking to expand it.

  12. If innovative thinking relies on combining building blocks in novel ways, then reading is the primary source of the blocks.

I've shared the full conversation with @mjmauboussin here.

If you'd rather listen on YouTube, Spotify, or Apple, check out the replies in the following tweets.

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[X.com] by @cremieuxrecueil

Everyone knows that alcoholism is bad. Drink too much, you'll fry your brain, or so the wisdom goes.

But it's also common knowledge that a little bit of alcohol is good for you. I mean, just take the conventional epidemiological result:

Clearly people who used to drink and people who never drink do worse than the people who drink a bit. And when people start drinking even more than a bit, they look a little better. Beyond that, they start to look a bit worse, but at no point are they worse than the non-drinkers.

Right?

The problem with the conventional analysis is that selection is at play. The people who don't drink at all and the ex-drinkers are selected into not drinking in weird ways. For example, an ex-drinker might be someone who was a heavy drinker in the past; a never-drinker might be a socially odd person. Who knows! But the potential that they're not normal is very much there.

It would be unethical to run human experiments to figure out what alcohol does, so, how can we know what alcohol does to health?

With a clever little method called Mendelian Randomization, or MR. MR is basically an answer to the question What if I used genes as instrumental variables?

Using Chinese data and genes that affect alcohol metabolism, that's exactly what Millwood et al. did! Since the alcohol metabolism genotypes they used should be otherwise independent of risk, everything should be good to go for using these as predictors of alcohol's effects.

But just to be sure: one of the ways we know these genotypes don't have independent effects is that there were no effects in women, who, for cultural reasons, are pretty close to being non-drinkers. Just take a look at the male-female difference in drinking!

So putting this wonderful genetic predictor to use, we can finally see what alcohol actually does.

Well, the effect of the unconfounded difference in alcohol consumption is that, when it comes to heart health, alcohol doesn't seem to do much, rather than being a bit protective.

But the heart isn't everything. There's certainly more!

Alcohol did increase risk for ischemic stroke, intracerebral hemorrhage, and total strokes.

Not only that, but in another study using a similar method, alcohol increased hypertension, blood pressure, waist circumference, waist-to-hip ratio, fasting blood glucose, and triglycerides. But, consistent with these results, in that paper it didn't seem to have a significant effect on cardiovascular disease or coronary heart disease, and it both increased HDL and decreased LDL.

In aggregate, alcohol is likely to be bad for your health at any level, but selection into disuse means the downsides have been hidden in traditional analyses. And even if alcohol doesn't negatively impact heart health on its own, the fact that it's not protective and it increases other risks means it's risky on net.

Sources:

https://t.co/zbTkmHJ07X

https://t.co/heonK84oC4

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[X.com] by @cremieuxrecueil

Emily Oster had this insight back in 2020.

She exploited the fact that a NEJM piece published in 1993 showed vitamin E had major health benefits and another article published in 2004 showed that vitamin E's benefits were overstated and it might actually be harmful.

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Quoted Tweet:

CrƩmieux @cremieuxrecueil

SIDS and breastfeeding are great examples of knowledge dispersal influencing correlations. In the past, these phenomena were less related to class/edu, but as it became "common knowledge" that certain things prevent SIDS or that breastfeeding is good, class correlations grew. https://t.co/PR1nWoO3W3

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View original tweet Fri May 05 18:44:24 +0000 2023

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[X.com] by @patio11

Some people really benefit from hearing advice that everyone knows, for the same reason we keep schools open despite every subject in them having been taught before.

In that spirit, here's some quick Things Many People Find Too Obvious To Have Told You Already.

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