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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.
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:
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.
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.
Out of curiosity, how much stock do you put in the polls of economists that IGM Chicago puts out? Presumably such polls dilute out individual cranks and their idiosyncrasies all come out in the wash, but it would still be of limited use if there's systematic biases and blind spots.
Low to no usefulness.
To be a useful survey question of economists, a question needs to:
Given those limitations not all the survey questions are useful.
Many of them have a huge scope like asking "would regulation of x industry be [good]". That becomes basically a vibes questions about how you feel about regulation in general. Even the staunchest libertarian leaning economist can acknowledge regulation is sometimes helpful. And even the staunchest statist pro-regulator out there can acknowledge that some regulations are harmful. So the question really becomes 'what quality of regulation do you think is likely'.
If the economists don't clearly come down on one side of the question, then you are back to a foundational problem of "how do you know which experts to trust if the experts disagree with each other?" This seems useful for someone that wants to organize a panel discussion between economists that disagree with each other, but less useful if you are just a pleb trying to figure out what the experts say on a topic.
Sometimes there are questions about price movements, or supply and demand movements. You can predict what economists will say by understanding a basic econ 101 textbook. You'll typically see fewer "uncertain" answers for these questions. It is maybe useful to have a professional economist interpret a current political problem and translate the econ 101 rules for everyone. But I do believe that people can do this for themselves. And typically when they fail to make this translation it is because they willfully don't want it to be true, and no amount of expert consensus will get through to them.
https://www.kentclarkcenter.org/surveys/women-and-the-labor-market/
I'll go through this survey on their website to demonstrate.
Question A: (rephrased basic econ question) If you take someone out of the labor force for a few years will they be paid more or less than someone that continued to work during that time? Obviously they will be paid less. Ok, what would be the effect of them not leaving the labor force at all. They would be paid the same.
Question B: (not limited in scope, agreement slightly unclear) It is comparing two treatment effects and asking which one is bigger. This can be very misleading: Treatment A might be huge, while treatment B might only be large. Or Treatment A is small, while treatment B is non-existent. In both cases the economist would answer the same. In this specific question you can go to the comments and find that while they think Treatment A is bigger, many seem to think Treatment B matters too.
Question C: (Agreements slightly unclear, This may be a useful one) I do think the economists didn't read the question very closely, or else there is an interpretation of "substantially" that I don't understand. This type of regulation would only address one of the things that cause a difference in pay for mothers vs not-mothers. And quite a few economists said in the previous example, that educational and occupational choices still matter. What this question is implying through the answer and the other survey responses: There is a gender pay gap. This gender pay gap has at least two major causes (educational and occupational choices vs parenthood and social norms around men's and women’s roles in childrearing). A partial solution for only one of the more major causes will substantially cause the gender pay gap to close. Removing the word "substantially" from the question would remove my objection, but it would also render the question much closer to a basic econ question.
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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.
That just means V is up. During COVID the Fed flooded the market with liquidity but my guess is a lot of that was semi trapped in interest on excess reserves.
By the same token during COVID you would have expected far more inflation based off of base money growth.
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I preferred Micro. If I had any specialty it would have been public choice.
Macro is dark wizardy
If you like public choice, then you like would’ve enjoyed law and economics.
They had some overlap for sure. The law and econ stuff sometimes got too close to straight philosophy for my taste. Public choice was ultimately grounded in making predictions about politicians and political outcomes.
Perhaps but L&E ended up rather accurately “backing into” common law rules that evolved over time. It definetly made me think “this framework is prettt strong”
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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.
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I'll add nutrition "experts" to the pile as one of the groups that I started losing trust in. I still can't believe I fell for the idea that sodium is "bad for you" above the recommended 2300mg/day recommendation. Preventing muscle cramps by cranking up my sodium intake and following up on the empirical evidence for low-sodium diets was one of my first indications that the public health professionals are either ignorant or lying.
Nutrition is protoscience, barely better than psychology.
at least psychology has IQ going for it, which is useful.
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Really? So what can I know about the food I eat?
Specific about given food - fine. How to avoid scurvy and similar - fine.
That we should avoid extremely processed food, overeating, sugary drinks and similar traps - many clear cases that should be avoided are known.
But science based guide for optimal diet? Hahaha. No.
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Eat more calories to gain weight and less to lose weight is pretty solid.
That's physics, not nutrition, to be fair.
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Quite a lot actually. We know that lack of Vitamin C will cause scurvy, lack of Vitamin D will cause rickets, and lack of Iodine will cause goiter. The last two were extremely common prior to the 20th century.
Unfortunately, nutrition science didn't build on these successes but started to make conclusions which weren't supported by evidence.
The other problem is that the job got a lot harder. We have basically invented entire new classes of food since then, and more importantly there's been a lot of population mixing. Given that the optimal diet for one group (not even race, much narrower genetic groups than that) can be completely opposite that of another, it's a damn hard nut to crack now.
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I can't say I disagree, as an aspiring psychiatrist who currently has to occasionally write diet charts.
Well, at least the drugs work, regardless of the theoretical grounding of more hand-wavey stuff like therapy.
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