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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.

This is a lot of words to write, "I don't understand why aggregate statistics don't apply to the individual".

Subsets of aggregate data can move in different directions from the summary statistics of the whole dataset. Trying to understand why people don't take selected macro statistics as gospel truth about their own lives is, to use a common phrase, extremely out of touch.

And stuff like this:

  1. 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.

Is bordering on outright delusional. There are more Americans than just Democrats and Republicans and you don't get 55% fair/poor personal financial situation from just Republicans (no matter how much I'd love for 55% of Americans to be Republicans, alas).

What's actually going on here is that the chattering classes and the politicians and bureaucrats they support are finding, once again, that they can't actually tell people what to think about their personal lives. It's baldly obvious that this group doesn't actually know what they're talking about any functionally better than most people and that their ability to cite macro statistics is more an attempt to cast a magic spell than a real explanation of ground truth.

Trying to understand why people don't take selected macro statistics as gospel truth about their own lives is, to use a common phrase, extremely out of touch.

It depends on the purpose of the discussion.

Is it to discuss policy? Is it to discuss aggregate public perception? Averages matter.

Is it to vent? They don't.

The question to ask: why are we on this forum?

Because the same power that wants people's minds to be made up by academia doesn't allow this forum to exist elsewhere. That's why.

Statistics are a useful mathematical tool. Statistics made by other people about anything remotely political is almost necessarily nonsense propaganda.

The incentives that econometrics have to lie are so great you might as well ask a Soviet Factory manager how many tons of steel he actually produced.

And yes that means one's lying eyes are back in the competition for an epistemic framework on those issues.

The one time someone tried to prove to me that the official data was too low by citing their own personal receipts, the receipts ended up matching the official data.

It would be great if one of the numerous people here making these claims had evidence that the CPI stats are being gamed instead of having to resorting to "academia and the media is biased => the BEA and BLS stats nerds are biased"

We can look at the various changes to the basket of goods and how it really doesn't measure anything except the cost of living for NEETs (the heavy underemphasis on energy and housing I see as clear deliberate manipulation for instance).

And this is to say nothing of unemployment numbers which have been cooked to hell and back by essentially every government of every State.

the heavy underemphasis on energy and housing I see as clear deliberate manipulation for instance

Let's look at the weights of the CPI-U as of 2022-Dec:

  • 7.5% - Rent of primary residence
  • 25.4% - Owners' equivalent rent of residences
  • 3.6% - Household energy
  • 3.3% - Motor fuel

I've ensured no overlap between the categories.

So, that's 32.9% of the CPI is housing and 6.9% is energy.

You believe these numbers are heavily underemphasized and are a "clear deliberate manipulation".

Please elaborate.

unemployment numbers... have been cooked to hell and back by essentially every government of every State.

Please elaborate.

There's different opinions on what is under/overstated in CPI so you might disagree on specifics, but the tricks you can use to manipulate it are well known at this point.

One is to readjust the methodology to the new habits of consumers, which allows you to pretend adaptations to higher costs of living are normal and lower the measured impact of inflation or to game the new and improved allocation to fit to local price changes and constantly change the methodology. Gas is so much more expensive people drive less? Cost of living is not going up, people just choose to spend more on Netflix and less on driving around.

Another is to use good substitutions and the other mechanisms by which you pick which actual goods to track. You can either substitute for cheaper goods as if they had equal value or fail to report shrinkflation and keep tracking the price of a good that is cheaper under the same name.

As for unemployment, there's as many methods to cheat as there are systems to measure it. In France the traditional way to cheat is to exclude from the numbers people who can't find work after a certain time and vary that amount of time to massage the figure. But we also cook it by excluding people from it if they're on some government benefits and in other situations that you can make a plausible argument for but apply to a lot of people who do work to live in practice.

I'm well aware of those nuances (i.e. Paasche vs Laspeyres indices).

  1. I don't see what that has to do with your claim that housing and energy are "heavily underemphasized".
  2. CPI is mostly a Laspeyres index, which means it is generally biased upwards compared to other indices (i.e. GDP deflator).

Re unemployment, I'm not sure this matters much unless you can show that the definitions have been changed to benefit someone.

More generally, you're basically saying "there exist degrees of freedom in defining these metrics".

Sure.

But the distance between that and allegations of "clear deliberate manipulation" and "cooked to hell and back by essentially every government of every State" is HUGE. You haven't even begun to cross that line.

#MotteAndBailey

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