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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.
To address the concrete point, real median pay is basically flat from its pre-pandemic value. The number you cited in your post was nominal.
Unemployment is also basically flat from pre-Covid (ditto for employment).
So, if people are subconsciously replacing the survey questions with "am I economically better off compared to pre-Covid?", then we should see about as many people answer "yes" as "no".
Don’t take this an attack, Knot, but do you now feel that you were often wrong when you defended the low inflation predictions of mainstream economists(and the bond market) ?
Wrong in the sense that the official data turned out to be false? No. The one time someone gave me concrete anecdotal data - it closely matched the official data. So, I haven't been given any evidence the official data was wrong/falsified.
Wrong in the sense that high inflation ended up persisting higher than I (or the market/Fed) expected? Yes.
Wrong in the sense that I think my approach to the question was worse than the competition. Not really. I don't think "who got that one random prediction right" is a good way to check who will do the best at predicting in general. I will say, my view has become a little more nuanced, but it's fundamentally the same.
I will also note that few on this site (any?) actually gave a concrete predictions on which to judge them, so I'm not even sure any of them did do better. Predicting "inflation will be higher than expected" has a 50% chance of being right by default and even higher if you allow yourself degrees of freedom of what "expected" means.
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Well that suggests real wages increased ratably.
Imagine a situation where wage increases lagged price increases but stabilized. During the interim, people would’ve need to dip into savings / borrow.
So even if from a flow perspective today everyone is the same from a stock perspective they are worse off.
And we do seem to see that (lower savings, more borrowing) suggesting people’s economic position is more fragile.
Maybe. OTOH, we also had those stimulus checks. Who knows how it all shook out.
Well, we know credit card debt has increased by 20% from pre pandemic levels.
We know savings have decreased from pre pandemic.
So yeah basically the average person has less net assets.
Sure, but was that due to inflation? Or was it due to ~0% interest rates making borrowing more attractive? Or temporary pandemic-induced unemployment making borrowing more necessary? etc.
Does it matter? The claim is the economy is doing great so why do people say otherwise. Well this explains the otherwise.
Makes sense.
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