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Notes -
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:
WhiningCoil says inflation numbers are “literally impossible to square with the lived experience” of housing costs going up, or the prices of staple foods doubling.
haroldbkny says inflation has been unprecedented in all his “life experience”, and he hasn’t seen the wages of anyone he knows growing to match it.
Walterodim says it’s “incredibly obvious” that people have “personally experienced much sharper increases in prices” than officials claim, and that officials must be “cooking the books”.
JTarrou says his personal standard of living went down, and that he’s paying “a third higher to double on most normal expenses (energy, groceries, etc.), and as such my national metrics smell of “statistical bullshit”and that “economic metrics are bullshit statistical lies”.
JTarrou further claims that economics is staffed by people who “all drank the same koolaid”, and that while anecdote is small data, it’s the only data he’s sure “isn’t horseshit”
HlynkaCG says he “has receipts” and linked to a 2 year old post where his local price of cheap meat went from $5/lb to $6.75 (a 35% increase) whereas the national meat price index at the time had only gone up by 9.5% over that period.
SlowBoy says recent economic events have been like “receiving Biden’s twelve inches”, and that the data are all gamed by lying government officials.
No_one implies people are waking up to statistical lies by linking to a Tweet of someone who went to their local grocery story where the cost of meat has jumped from $10 to $16.
freemcflurry says he makes more money than he used to, but “things just feel shitty”; the prices of chicken breast as his local grocery store doubled from $2/lb to $4/lb, and there are now masses of homeless people in his city walking around “like zombies with festering sores all over their skin.”
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.
If we're talking about national level statistics, it's perfectly possible that the lived experience and the statistics are both picking up on true things. It could be true both that the San Francisco police only arrest black men in the absolute most blatant cases of violent crime, and that Chicago police are racists, sending otherwise reasonable black men to prison for possession of a bit of cocaine. (I have neither anecdata nor data on either of these specific possibilities, but the Chicago police do have a reputation of practicing the soft bigotry of letting underclass black people murder each other.) In which case, it would be good if San Francisco police were harsher and Chicago police were more careful. In the national statistics, this might look like a wash, but on the local level it isn't. San Francisco can't really atone for Chicago's racism.
Meanwhile, in the economy, it could, for instance, both be true that food makes up a relatively small part of people's overall expenses, and that it's the main expense they are able to control in the short term, so it fluctuating is more painful than durable goods fluctuating, since it's usually easier to put off buying new durable goods. Maybe it feels worse to not be able to buy beef than to not be able to buy (whatever it is that didn't inflate as much, I'm spending so much on food I haven't really considered buying it, whatever it is...)
Additionally, part of it for me is the expense breakdown and where the cuts have to be made. There are several unavoidable expenses, and a very small field of adjustable expenses. As such, all tightening of the belt has to be done out of a very small portion of the overall budget.
Heating, and gas cannot be adjusted. I already use them as little as possible, and any further reduction would be stupid and harmful. Any increase in heating or gas costs then, has to be cut out of something else. Hard goods (furniture, dishware, clothing, appliances etc) likewise cannot be adjusted, as I pay nothing for them (hooray Facebook Marketplace!)
Food and other consumables can be adjusted, but only by dropping in quality noticably. Because this is my only flex point, it is where almost all of the change in standard of living occurs. Say my overall spending power drops by 10%. That's not a lot, but this category makes up only 20% of my spending, and is the only area where change can occur, so I have to take a very large hit to the quality of consumables just to break even. This hurts a lot. Eating cheaper makes me feel worse, noticably, both physically and emotionally.
I think many experience a similar effect. If only 10% of your budget is discretionary spending and your real purchasing power drops by 10%, you now have no discretionary spending money at all. That is a massive hit to quality of life. Straight from "well I work a lot but I get fun outings and the occasional vacation," all the way to "I literally just work to live to continue working."
This is my experience as well.
In our case, we switched to both working, and are sending our children (toddler and pre-k) to childcare, because the state pays for 90% of the childcare cost. This is fine, I think the kids like it well enough, but it pads out the GDP without necessarily improving living standards in comparison to having more households with stay at home mothers in them. This is the kind of detail that makes me suspicious of some of the economic figures.
There are positives to the current situation, but it also feels more fragile -- when someone is sick, it's a bigger problem, including calling out from work (and we aren't supposed to call out morning of, so we have to decide the day before), and a general lack of flexibility with the children. This is part of what's going on with being unable to suspend kids or even have them home sick -- there's nobody around to look after them. There are kids I teach who are clearly stressed out, lashing out, disrupting things for the others, and shouldn't be in a large school 7 hrs a day, but there isn't an alternative, there's nobody else they're able to be with, everyone is following very strict rules watching one another's children and elderly, without any slack.
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