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Culture War Roundup for the week of October 30, 2023

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On the use of anecdotes and “lived experiences” to contradict statistical data.

Say for the sake of argument that you’re arguing with a left-leaning individual (let’s call him “Ezra”) on the issue of police bias. You both agree the police has a least a little bit of bias when it deals with blacks, but you disagree on the root cause. Ezra contends this is due to structural racism, i.e. that laws are created in such a way such that blacks will always bear the brunt of their enforcement. He further contends that local police departments are often willing to hire white men with questionable backgrounds in terms of making racist remarks. This inherent racism exacerbates issues of uneven enforcement, and in the worst cases can lead to racist white police officers killing unarmed black men. While you agree that black men are arrested at disproportionate rates, you claim the reason for this is more simple. Black men get arrested for more crimes because… black men commit more crimes. You cite FBI crime statistics to back this up. In response, Ezra says that the FBI data you cited is nonsense that doesn’t match up with reality, but rather is cooked up by racist data officials putting their thumbs on the scales to justify the terrible actions of the criminal justice system on a nationwide basis. After all, Ezra knows quite a few black people himself, and none of them have committed any crimes! And while none of them have been arrested, a few of them have told him stories of run-ins with the police where they were practically treated as “guilty before proven innocent”. In short, Ezra’s lived experiences (along with those of people he knows) contradicts your data while buttressing his own arguments.

Do you think Ezra’s lived experiences are a valid rebuttal here?


Yesterday I made a post on the partisan differences in economic outlook. The three main points were that 1) the US economy is doing fairly well, 2) Republicans think the economy is doing absolutely terribly, much worse than Democrats think, and 3) that most of this perception difference is because Biden, a Democrat, currently occupies the White House. I initially thought I was going to get highly technical arguments quibbling over the exact measurement of data. Economic data is highly complex, and as such, reasonable people will always be able to disagree about precisely how to measure things like unemployment, GDP, inflation, etc. It’s not particularly hard to cherrypick a few reasonable-sound alternatives that would tilt measurements one way or the other. For instance, how much of housing costs should be calculated in the inflation of consumption prices? Rent can be seen as pretty much pure consumption, but homes that are purchased also have an investment aspect to them. As such, the current inflation calculations use “owners’ equivalent rent” to account for this. Most economists think this is overall the better way to calculate inflation on this particular measure, but again, reasonable people could disagree, and getting a few of them on record saying “the current measurements are faulty” is an easy way to throw doubt on data. While I did get a few of these types of comments (example 1 , example 2), they weren’t the majority of the responses by a long shot.

Instead I got plenty of arguments about “lived experiences” which people claimed as disproving the data I cited. These weren’t quite to the level of “Chicken costs $5 more at my local supermarket, therefore all economists are liars with fraudulent data”… but it wasn’t that far off.

Don’t believe me? Here’s 9 examples:

To be clear, a few of these above examples don’t say that their anecdotes prove economists are lying, and are instead using their personal experiences to say how economic conditions feel worse, although they were typically at least ambiguous on whether they trusted their own experiences over economic data at the national level. On the other hand, there were some who were quite unequivocal that economic data is fabricated in whole or in part since the things economists say don’t match with how the economy seems in their personal lives.


Going back to the example of bias in policing that I mentioned earlier, I’d say that the vast majority of people on this forum would say that you can’t really use “lived experiences” to contradict data. Anecdotes aren’t worthless, as they can give you insight into peoples’ perceptions, or how the consequences of data can be uneven and apply more to some locations than others. But at the end of the day, you can’t just handwave things like FBI crime statistics just because you know some people that contradict the data. As such, it feels like a rather blatant double standard to reject “lived experiences” when it comes to things like racism, only to turn around and accept them when it comes to the economy.

The cop-out argument from here is to point at the people preparing the data and say that they’re the ones at fault. The argument would go something like this: “My outgroup (the “elites”, the “leftists”, the “professional managerial class”, the “cathedral”, or whatever) are preparing most of the data. Data that disagrees with my worldview (like the current economic outlook) is wrong and cooked up by my outgroup to fraudulently lie to my face about reality. On the other hand, data that does agree with my worldview (like FBI crime statistics) is extra legitimate because my outgroup is probably still cooking the data, so the fact that it says what it does at all is crazy. If anything, the “real” data would probably be even more stark!”

This type of argument sounds a lot like the controversy around “unskewing” poll results. Back in 2012, Dean Chambers gathered a fairly substantial following on the Right by claiming polls showing Obama ahead were wrong due to liberal media bias. He posted “corrected” polls that almost monotonically showed Romney ahead. He would eventually get his comeuppance on election day when Obama won handily. A similar scenario played out in 2016 when many of the more left-leaning media establishment accused Nate Silver of “unskewing” poll results in favor of Trump. Reporters don’t typically have the statistical training to understand the intricacies of concepts like “correlated errors”, so all they saw was an election nerd trying to make headlines by scaring Democrats into thinking the election was closer than it really was. They too were eventually forced to eat their words when Trump won.

While issues of polling bias can be resolved by elections, the same can’t be said of bias in our examples of racism and the economy, at least not as cleanly. If someone wants to believe their anecdotes that disproportionate black arrests are entirely due to structural racism, they can just go on believing that for as long as they want. There’s no equivalent to an election-loss shock to force them to come to terms. The same is true of economic outlooks. Obviously this is shoddy thinking.

The better alternative is to use other economic data to make a point. If you think unemployment numbers don’t show the true extent of the problem, for instance, you can cite things like the prime age working ratio if you think people are discouraged from looking for work. Having tedious debates on the precise definitions of economic indicators is infinitely better than retreating to philosophical solipsism by claiming economic data is broadly illegitimate. Economic rates of change tend to be exponential year over year, so if large scale fraud is really happening then it’s hard to hide for very long. There would almost always be other data you can point to in order to make a case, even if it’s something as simple as using night light data to estimate economic output. Refusing to do even something like this is akin to sealing yourself in an unfalsifiable echo chamber where you have carte blanche to disregard anything that disagrees with your worldview.

I blame Fauci.

Its hard to come out of Covid without some sense that "the science lies to us". I generally like to trust experts, but now it constantly feels like a slight level of uncertainty has crept into all my interactions with experts. The idea of an entire group of academics capture by a single interest group and willing to lie to our faces ... no longer seems very far fetched. At most you'll get a couple of the experts that defect and say all of their colleagues are wrong.

What it often requires me to do is to go look at the data the experts have, rather than what they say about their own data. At which point I get frustrated about even having experts in the first place. I usually have to rely on other smart people that I actually trust to go and check the data.

Things where I am suspicious about what the experts say:

  1. Lockdowns
  2. Covid vaccines in the young
  3. Death rates of covid
  4. What the "intelligence community" says about political things
  5. Runaway global warming
  6. Economists on the topic of currency

Since Fauci isn't really being punished for any lies, I can assume most experts picked up on the hint: say what we want you to say and you'll be protected.

I still tend to have a lot of trust for economists, but that is maybe because I have found economists I actually trust, and I don't read the economists that would ruin my trust.

I can believe that we are in a great economic period right now. Nothing in my life suggests anything is great or terrible economically, so its not hard to think that either scenario is possible. There are multiple measures of employment, and I really wish news orgs would just report the full table of employment measures, U1-U7 (if I remember correctly). I feel like any one of them is potentially misleading individually, but altogether they give a great picture.

I have a very hard time trusting economists related to currency. The topic has always seemed like black magic to me. There is a joke among the academics I work with that monetary economists are always a bit on the weird side. I personally feel that its because monetary economics is a bit like studying cthulu. Simply witnessing it and understanding it drives you a little crazy. Also if there is any place where apparatus of government control has an incentive to get economists to lie, then that place is gonna be monetary economics. You simply cannot have modern sized governments without currency manipulation and money printing. I don't think they tend to lie too often about inflation numbers, or I at least believe that the numbers they give are consistently measured. Its more of a big giant lie that I worry about, rather than tiny lies to benefit one specific administration.

I still tend to have a lot of trust for economists, but that is maybe because I have found economists I actually trust, and I don't read the economists that would ruin my trust.

They were the first class of experts to lose my trust, after 2008. Hmm, actually, maybe the second after Iraq and the GWOT. Of course I never believed the "gender" and "psychology" experts in the first place, so there is that too.

I studied economics between 2009-2013. It was a contentious time for economics. I don't trust an expert just because they have a PhD in economics, but I think some basics of the field have held up really well. And I think the field in general has robust data gathering and adversarial checking of data.

Micro or macro? If macro, can you explain what it means that M1 and M2 money supply has been FALLING? Most of the pundits seem to be saying "nothing to see here", whereas the stopped clocks are saying it's a harbinger of recession.

Good god, it's been a while since I've cracked open my econ degree.

TLDR, M1 and M2 are basically how much free-flow, readily available cash is in the hands of the public(as opposed to Banks, the federal deposit, and other entities.)

Or, put another way, how much money do civilians and John Q Public have available at quick notice.

If it's been falling, well... that means they have less cash on-hand. Why that is could be due to... well, a long list of reasons.

Also, that redefinition of m1 annoys me to a horrendous degree for some odd reason.

The M1 redefinition makes estimating models annoying too, although M3 is a good enough measure nowadays given how liquid even savings accounts and GICs are.