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bhupy

A lot of anecdotes and conjecture here, so it’s worth analyzing the median trends across generations:

https://www.bloomberg.com/opinion/articles/2020-09-23/median...

https://twitter.com/ernietedeschi/status/1308748407633309696

https://twitter.com/ernietedeschi/status/1308813020425007105

(yes, these are all adjusted for inflation)

Real median per capita income is the highest its ever been regardless of which inflation index you use -> https://twitter.com/Noahpinion/status/1307793622369103872

Not only that, we’re on average working fewer hours — so not only has income growth been higher in recent years, it’s been of higher quality -> https://twitter.com/Noahpinion/status/1308790402082766849

Anecdotes are important because they allow people to voice their concerns, but it’s important that we don’t miss the forest for the trees.

View on HN

The median might have done well, but we know for a fact that inequality has risen dramatically in the past 40 years, mostly as an effect of big tax cuts to the wealthy. I'd be interested in seeing an analysis dividing the population in bottom 50, top 10 and middle 40, post-tax.

This is the most similar thing I could quickly find

http://piketty.pse.ens.fr/files/ideologie/pdf/G11.7.pdf

and it seems to show that low-income salaries have largely stagnated for the last 50 years. I don't think it's debatable that places like the Greater Boston area have seen increases in rent that have gone faster than inflation. Combine the two phenomena and you'll see how many people are priced out of large attractive cities.

Thomas Sowell makes an interesting point that very few people stay in the same categories of rich or poor in their lifetimes. Young people make up the majority of the poor, but after working and gaining experience the vast majority move out of that category.

I am pretty sure I am an example of that. Graduated in the dot com bust in 2001 and was unemployed for a year and a half. Apparently my partner and I are now in the top 10% of household earnings for our country. (Household earnings being another very misleading statistic - as people become paid better they move out of shared houses, making things look worse when they are actually getting better).

I dont think that describes accurately the economy. Socioeconomic mobility is declining too, people who were born to rich families become rich and those where were born in poor families become poor.

It is not all young people who will earn a lot of money later.

It’s actually been quantified -> https://journals.plos.org/plosone/article?id=10.1371/journal...

Based on the empirical tax analysis, 12% of the population found themselves in the top 1% of the income distribution for at least one year. 39% of Americans spent a year in the top 5% of the income distribution, 56% found themselves in the top 10%, and a whopping 73% spent a year in the top 20% of the income distribution.

Interesting. Is that from windfalls like inheritances or big insurance payouts?

> inheritances

No, because this study analyzes historical tax filings, and inheritances are not counted as taxable income.

> big insurance payouts

On average, probably not, because big insurance payouts are (by definition) actuarial anomalies. They're tail-risk events.

I don't see how so many people can be in the top 5% unless selling your house counts as income and you are counting the econonic activity when someone sells the family home to downsize in their senior years. At any rate without an illustration of how the claims about income works in practice I don't know what to make of this article. Most people aren't going to spend a year as high level executives.

> Most people aren't going to spend a year as high level executives.

I think you might be over-estimating what it takes to be in the top 5%

Here are the numbers -> https://dqydj.com/income-percentile-calculator/

If you earn $170,000, you're in the top 5%. That's absolutely attainable within 5 years of graduating into a high-skill job.

That's also attainable within one's lifetime if they end up doing any sort of management or decision-making (as opposed to just manual labor all their lives).

It's my understanding that 170,000 per year is more than most managers will ever make in most parts of the country. However I can maybe see 170,000 making sense if it's based on household income and a household may have two manager class employees making 90,000 a year.

That said i'm still having a hard time believing the claim that a large number of households will have top 5% earnings. I'd love to see a blog post or something along those lines contexualizing that journal article.

Sure thing! I typically like to only link to primary source so as to avoid accusations of bias.

Here are some articles that summarize the primary source:

https://web.archive.org/web/20160327182251/https://taxfounda...

https://www.aei.org/carpe-diem/evidence-shows-significant-in...

Thanks. That first link makes more modest claims than the second one. They also appear to use different methodology (surveys vs tax returns). I appreciate the different links.

aren't household earnings calculated using the tax definition of household? if I live with three other engineers as roommates, that's not a $400k household; it's four $100k "households", despite the fact that we share the same roof.

> mostly as an effect of big tax cuts to the wealthy

Maybe partially so, particularly capital gains taxes. But I'd wager globalization likely had a much more pronounced impact on American inequality by pushing labor out to Asia

Low income salaries actually experienced a higher increase than higher income salaries between 2014-2019 (basically pre-COVID) -> https://www.cbsnews.com/news/low-wage-workers-are-getting-bi...

And while Piketty's work is popular, he isn't gospel. The IMF was unable to reproduce Piketty's findings in empirical data -> https://www.imf.org/external/pubs/ft/wp/2016/wp16160.pdf, and then Auten & Splinter further refuted the findings by taking into account taxes & transfers -> http://davidsplinter.com/AutenSplinter-Tax_Data_and_Inequali...

Taking some vague numbers from that article, a low-income salary might be $20,000, which gets an increase of 5%, so $1000. Meanwhile a high-income salary of say $100,000 gets an increase of 2.5%, so $2500. Which one is the bigger increase?

Measuring these things in percentages hides the fact that the underlying numbers are immensely different. Perhaps if we reported numbers differently, we would say that the pay increase for the high-paid worker was 2.5x the pay increase for the low-paid worker.

In terms of what it'll do for you, an extra $1000 at $20,000 p.a. is definitely a bigger increase than $2500 when you're making six figures.

Alright, let's actually follow up on two of your links for once.

Regarding "The IMF was unable to reproduce":

"Piketty's response[54] noted, however, that Góes used measures of income inequality rather than wealth inequality, and inappropriately took the interest rate on sovereign debt as his index of the rate of return on capital, which makes his results not commensurate with those of Piketty's study."

Regarding "Auten & Splinter further refuted":

"There’s plenty of other literature, mentioned in the Auten-Splinter paper, the Economist articles and elsewhere, that challenges the methods used by Piketty and his collaborators. Such challenges are mainly possible because tax data draw an incomplete and often difficult-to-interpret picture of the income distribution. Tax systems are complex, different governments choose not to tax different kinds of income, and of course people, rich and poor, cheat on their tax returns. Measuring wealth inequality rises to a whole new level of difficulty: Since so few countries have wealth taxes these days, only guesstimates of the wealth distribution are possible.

So on Tuesday, Piketty, Saez, Zucman and a long list of other signatories issued a sweeping response to critics of the popular inequality narrative, pointing out that all the data-based arguments can be settled by making solid data available."

Unsurprisingly, these two doesn't seem to very convincing "refutations".

I'm not convinced you actually read through either of those sources, especially considering that none of your quotes actually ever appear in them.

First, and foremost, Piketty's findings are based on theoretical models, not empirical observations. The two fatal flaws Piketty makes are 1) he models a zero-sum world where wealth is fixed, and 2) doesn't take into account taxes & transfers.

From the IMF research:

Using a sample of 19 advanced economies spanning over 30 years, I find no empirical evidence that dynamics move in the way Piketty suggests. Results are robust to several alternative estimates of r-g.

I find no empirical evidence that the dynamics move in the way Piketty suggests. In fact, for at least 75% of the countries examined, inequality responds negatively to r − g shocks, which is in line with previous single-equation estimates by Acemoglu and Robinson (2015). The results also suggest that changes in the savings rate, which Piketty takes as relatively stable over time, are likely to offset most of the impact of r − g shocks on the capital share of the national income. Thus, it provides empirical evidence to the model developed by Krusell and A. Smith (2015), who say Piketty relies on flawed theory of savings. The conclusions are robust to alternative estimates of r − g and to the exclusion or inclusion of tax rates in the calculation of the real return on capital.

From Auten & Splinter

Our estimates also differ for the bottom half of the distribution. PSZ estimated that the bottom 50 percent share of pre-tax and after-tax shares decreased by about 7.5 and 6.2 percentage points since 1979. In contrast, we estimate that pre-tax and after-tax income shares decreased by 5.6 and 2.2 percentage points over this period. Our estimates suggest that taxes and transfers offset most of the recent changes in both bottom and top income shares. In contrast with the PSZ estimate that average real pre-tax incomes of the bottom 50 percent remained virtually unchanged, we estimate that they increased by nearly one-third.

For pre-tax/after-transfer income (which includes Social Security benefits) and after-tax income, we estimate a real increase for the bottom half of the distribution of nearly two-thirds

> I'm not convinced you actually read through either of those sources, especially considering that none of your quotes actually ever appear in them.

Of course I didn't? That would require me to spend several hours to go through those reports, hence I refer to other who have.

Why don't you answer the replies to each report instead - of people that have actually had the time to go through them and reply?

I see, you suggest that there exists refutations to the refutations I've cited. Great! Why haven't you linked them?

Uhm? It's a google away

> Low income salaries actually experienced a higher increase than higher income salaries

In percentage points. If someone gets a pay rise from $1/hr to $2/hr, they will experience a dizzying 100% wage growth, more than any CEO could ever hope for.

This is simply a mathematical property if small numbers, it doesn't contain any meaningful information on economic development or policy.

That's correct, but also not particularly relevant, as there's no society on the planet where low income salaries experience a higher absolute increase than higher income salaries.

The fundamental point is: there's a narrative that lower income salaries 1) don't increase at all, and 2) increase at a slower rate than higher income salaries, and both are false.

It's also important to remember that the increase in salaries at the lower income levels, do NOT necessarily represent a single earner's pay history. Those numbers show us the snapshot-in-time income numbers for everyone currently at that salary level, but does not account for people actually moving income levels as they progress in their career. The data isn't "here's the life of Joe over the last 5 years", it's "here's the life of people without college degrees that are X years old with Y years of experience with X & Y held constant over 5 years".

If low-end wages double and home prices double, the ratio remains the same but the poor person is still falling behind due to fixed expenses. You'd need disposable income to double for the effect to be neutral (probably a bit more because even poor people deserve a bit of indulgence now and then). As it is, poor people are more sensitive to housing inflation. Even if wages and home prices move up in lockstep (which they haven't) they'll take more years to save up enough for a down payment. That's why so many remain permanent renters, denied the equity and tax advantages of home ownership and putting them at even further disadvantage.

So yes, the point about inequality damn well is relevant. Anyone who wants to pretend they know about statistics should know that distributions matter as much as averages and medians.

What I’m suggesting is irrelevant is pointing out that percentage increases are lower in absolute terms, because that’s universally true everywhere.

If low-end wages double, you have to look at how low-end home prices did, not median home prices. Housing is a positional good.

> If wages and home prices move up in lockstep (which they haven’t)

These numbers are all inflation adjusted, and inflation calculation includes all of those costs:

https://twitter.com/jmhorp/status/1308799186301747200

https://www.bls.gov/cpi/tables/relative-importance/2019.txt

Even if housing costs have gone up more than overall inflation, other things have fallen, and OVERALL inflation rate is the best rough measure of "cost of living". Focusing just on home prices or healthcare is incomplete way of understanding purchasing power / cost of living. When we say that the median income has increased adjusted for inflation, it means that the real salary has increased even accounting for the increased prices of all of the stuff that needs to be bought.

And finally, re-iterating the point: these numbers don’t represent a single earner’s pay history. It doesn’t really make sense to compare a single individual’s fixed expense in the context of these distributions, because they represent different individuals at different snapshots in time. While the shape of the distribution may be (moderately) fixed, the composition of it changes dramatically.

Something big happened in 1971 that affected the core of the economy: we unhitched the US Dollar from gold.

https://wtfhappenedin1971.com/

I get what you're saying, but I think that the inflation does not adequately represent: 1) housing (usually one's biggest expense) 2) college (nowadays the biggest debt problem)

I think the highest stress is among young people who DID get a college degree, and who DO live in the highest-rent cities in the country, and their situation is not captured by the data you cite.

BUT, I'm not saying your data isn't relevant. Just that housing and college are pretty big things to leave out, but IIUC they are not part of the standard inflation measure.

> their situation is not captured by the data you cite

Exactly. They're people too. Their circumstances matter. Also, let's not forget that not everyone even in a high-demand area is also high-income. Somebody has to do the "lesser" jobs, and for them housing is even more of a problem. Arbitrarily excluding certain metro areas because "you're a techie and can live anywhere" is just counter to reality, and just seems like a way to skew the numbers.

I think it's extremely important not to discount the circumstances of individuals. Like you said, they're people too.

But the value in this data is in helping us understand what the root causes are, and what the solutions should be.

> Arbitrarily excluding certain metro areas because "you're a techie and can live anywhere" is just counter to reality, and just seems like a way to skew the numbers.

The goal behind "arbitrarily" analyzing the data per-metro is not to skew the numbers, but to help us understand that the root cause is largely local, rather than a global systemic one. Everyone knows that housing is way more expensive than a median income can afford in San Francisco, but that's a San Francisco problem, not an America problem. It's also one that's generally well understood: they're not building enough housing due to exogenic limits.

I completely agree that we should understand the root cause, but I completely disagree that excluding certain cities helps us do that. Rather, it obfuscates. If you want to illuminate, you should aggregate by population density, then slice and dice by age, income quintile (not just median), parental income quintile, etc.

> that's a San Francisco problem

What's your excuse for the hundreds of places that aren't San Francisco but still have ridiculous ratios between income and housing prices? Your own sources identify some. The absolute last thing this site needs is more SF-centric tunnel vision.

> What's your excuse for the hundreds of places that aren't San Francisco but still have ridiculous ratios between income and housing prices?

There aren't "hundreds" of places. Here's a list of metropolitan statistical areas (MSAs) by population -> https://en.wikipedia.org/wiki/List_of_metropolitan_statistic...

In the top 10, only 3 have experienced a dramatic increase in income-to-home-price multiple -> https://www.jchs.harvard.edu/home-price-income-ratios

Of those that have experienced a dramatic increase, the root causes are common: restrictive land use policy that prevents us from building more housing. One may call that "tunnel vision", but others may call that "systematically isolating root causes".

> In the top 10, only 3

Yet again why the arbitrary limitation? Your own source shows about a dozen areas going from the 5-8 band to the over-8 band since 1990. More than two dozen going from the 4-5 band or lower to the 5-8 band. When each multiple represents most of $100K. When the entire graph should ideally remain about the same color overall but is clearly getting worse. Buy hey, let's look only at the top 10 out of 392 and ignore the fifth of the population that's not in an MSA. That's totally the way to "systematically isolate root causes" ... so long as the root causes are the ones we find convenient. Otherwise not.

It's not arbitrary, I'm just sampling the most populous because that's typically where the increases have allegedly been the most dramatic. The intention behind choosing only the top 10 is to be as minimally charitable to my own point as possible.

In the top 20 most populous MSAs, only 7 experienced a substantial multiplier increase.

In the top 50, it's even less.

The further down the list you go, the less likely there has been a dramatic increase in home-price-to-income ratio.

There's a whole collection of "Fine, American cities" (https://twitter.com/jmhorp/status/1221828340656431105) where multipliers have either not increased, or decreased.

> The absolute last thing this site needs is more SF-centric tunnel vision.

Indeed. Canadian here -- you Americans have it good! In Canada, there aren't so many metros to choose from. Moving away from the city you grew up in generally means moving much, much farther away, and adapting to a very different climate. For any given profession, the number of places with good opportunities is also a much more limited selection.

> BUT, I'm not saying your data isn't relevant. Just that housing and college are pretty big things to leave out, but IIUC they are not part of the standard inflation measure.

They are not left out:

https://twitter.com/jmhorp/status/1308799186301747200

https://www.bls.gov/cpi/tables/relative-importance/2019.txt

There's also not one single standard inflation measure, there are a number of different ones with different weights. The real median income is up regardless of which measure you choose to use.

Rent/housing, education and insurance of all varieties and transportions wipe out all these gains in actual income.

You get some of it back in the form of food costs and energy costs which are relatvely low.

On paper you're absolutely right. On paper even the poorer amongst should be better off than they would have been in 1990.

These income gains are inflation adjusted, and about half the entire weight of most inflation indexes is just housing, education, and health care costs:

https://twitter.com/jmhorp/status/1308799186301747200

https://www.bls.gov/cpi/tables/relative-importance/2019.txt

Even if housing costs have gone up more than overall inflation, other things have fallen, and OVERALL inflation rate is the best rough measure of "cost of living".

There's some disagreement around whether we should use CPI-U, CPI-W, or PCE — CPI-W underweights housing, for eg — but importantly, the median income has increased since 1981 regardless of the choice of index. The median total compensation has increased since WW2 regardless of the choice of index.

There's a gig economy and there's a talent economy. If you're in the talent economy where employers come looking for you all is good with the world.

If you're in the gig economy where you are fighting a dozen other people for the same split shift gig on minimum wage then the world is terrible.

What we need is to turn the gig economy into a talent economy. Jobs should wait, not people.

Really what you want is for gig / delivery style jobs to be unionized, or for it to not be legal or easy for sole operators to work with a bicycle and a backpack. I think we want limits the ability of companies like uber to employ people as contractors. If you force them to have a staff and to manage their staff, then their workers talent is important.

But at that price point, I'll probably make the trip to get my own pizza / take out.

The gig economy isn't really gig's it more about the externalization of laziness. And companies breaking the social contract IMHO. They are creating such serious problems long term for the work forces that lose effective labor to these crap jobs.

I'm Australia, I live a far distance from and India restaurant I like. I'll still do the drive to pickup my food. If I use some gig delivery app then I'm pretty sure I'm asking for someone to do work for me that's probably unpaid in some extent. I know almost to 100% that they don't have superannuation and anything near the benefits that I had when I worked in crappy jobs when I was younger.

This also irks me from a employment participation standpoint. In the tech world, people bemoad "the best minds of my generation working out how to make people click adds" etc. But no ones talking about what happens to a few generations of people that are forced into pay cheque to pay cheque living and the down stream social welfare and or retirement cost of these shit jobs.

We're letting a lot of companies make money off the future well being of their workforce who happen to also be our citizens.

Long post. Sorry if it's ranty.

>Really what you want is for gig / delivery style jobs to be unionized, or for it to not be legal or easy for sole operators to work with a bicycle and a backpack

So basically do what some states have done for plumbers, electricians or other trades with a licensing body and professional cartel?

Bars to entry and a strong incentive to keep the status quo once you're in will certainly jack up prices and pay and businesses who have to follow the law will have to get their gig services from the cartel members but everyone else will just consume less of the services. Considering that these gig economy services are mostly consumer facing I think you'd just see demand fall off a cliff if prices were raised by regulation. The survivors would have high wages but unless some other employment option is available labor force participation will suffer.

I think if it was as easy as cranking the regulation knob to 11 someone would have already done it.

I know and agree regulation won't fix it, it just move the problem around. It's a tough problem.

You're forgetting about the vast majority of jobs: the mundane economy. If you're in the mundane economy, you compete with a dozen other people for full-time jobs that pay somewhat above minimum wage, and no employer in the right mind would actively look for you in particular. You obsess about your CV and worry if anyone will hire you for anything if you lose the job you currently have.

A tech worker is in the talent economy. The receptionist at their company's office is in the mundane economy.

I'd argue most tech workers are in the mundane economy as well. If it were not the case, leet code and open offices would not be a thing.

I am really flabbergasted how people with low income don't look very hard for good deals, or pay for things that they shouldnt be paying for at that stage of their life.

I saw an article saying there is no place in America people can afford to live on (I forget amount). Someone shared it on social media, and I did the calculation and I knew many places that were affordable by those standards, even in a large city.

They retorted there isn't a place in America that you can find a place under 800$. I'm like .... did you look very hard? When I was in philadelphia from 2007-2009, I shared a 3 bedroom apartment with 3-4 other people for ~200$. When I wanted my own 'place', from 2009-2013 I rented a micro apartment in down town Philadelphia for 400$/month.

I'm sure prices are higher now, but there are affordable places to live, but you have to be willing to give up something: commute time, amenities, size, privacy, etc.

With income, other industries have room to complain, but not tech. my 28k TC starting salary isnt even what people are getting signing bonuses these days.

While I doubt that you have a reliable source for your assumption that poor people don’t seek out deals or limit unnecessary purchases, I’ll note that being poor literally reduces your capacity to make good decisions - https://www.reuters.com/article/us-poverty-brain/study-finds....

I don't know. If we're going down the route of what counts as "inflation-adjusted": Does housing, studying, medicare count there or only [or overwhelmingly] consumer goods? If it's the latter - which I would expect - than the stats are cherry-picked and the money ain't worth as much as it used to be.

There are a number of different indexes we use to adjust for inflation, and different people agree on which index is the best.

That being said, per the linked source, the inflation-adjusted income has increased no matter which index you use to calculate the inflation.

well, yes. My point was more or less that I haven't seen an adequate inflation index whenever I read about this topic (which is quite often). So just saying "no matter which index you use" isn't worth much if every usual index is going for the wrong measurements. Nonetheless, there are articles which focus on the real inflation and it doesn't look good: https://www.theatlantic.com/ideas/archive/2020/02/great-affo...

Choice Quote: "The price tags for tuition and fees at colleges and universities have risen twice as fast as wages, if not more, in recent years. Rental costs are outpacing wage gains by a percentage point or more a year. Health-care costs have grown twice as fast as workers’ wages. And child-care costs have exploded."

That's all correct, but ~60% of the weight in PCE and CPI-U are given to housing, healthcare, and education costs:

https://twitter.com/jmhorp/status/1308799186301747200

https://www.bls.gov/cpi/tables/relative-importance/2019.txt

Even if housing costs have gone up more than overall inflation, other things have fallen, and OVERALL inflation rate is the best rough measure of "cost of living".

Keep in mind that this still means that we ought to solve the rising house price problem (by liberalizing zoning restrictions) and reducing healthcare prices (either by having the State subsidize all of it or better price transparency). Doing so just improves the inflation-adjusted wage even more than it's already improved.

thanks for the discussion and your sources. I guess your numbers add up. Nonetheless, I don't think using inflation is enough as measuring stick. Upward mobility/inequality is not really captured in it. Also, it appears public service in the US has suffered a lot in the last years. So my full picture of the US is not as bright as yours although your sources and arguments are fine in itself.

If you’re interested, I provided some empirical data around upward mobility during one’s life elsewhere. I’ll just copy-paste here for convenience:

“Based on the empirical tax analysis, 12% of the population found themselves in the top 1% of the income distribution for at least one year. 39% of Americans spent a year in the top 5% of the income distribution, 56% found themselves in the top 10%, and a whopping 73% spent a year in the top 20% of the income distribution.

https://journals.plos.org/plosone/article?id=10.1371/journal...

I’m not sure whether this oft-cited research demonstrates much regarding upward mobility, per se, but it does provide some compelling insight into the volatility of income throughout one’s life. Typically, when speaking of upward mobility, some degree of stability is assumed to follow an upward income movement, but this study doesn’t preclude the possibility of someone going from, say, the 20th income percentile to the 80th for a year, then subsequently falling back to the 20th income percentile for the remainder of their life. That’s not a fault of the study, to be sure, but it does limit the scope of its application with regard to the topic of upward mobility.

You’re absolutely correct that, while one may spend time in the a higher percentile, they may then fall back to a lower percentile for the remainder of their life.

Nevertheless, it’s an important analysis because if the majority of people really do spend a few years in affluence, it suggests the uncomfortable reality that there is a higher degree of personal responsibility involved than we may be letting on.

> it suggests the uncomfortable reality that there is a higher degree of personal responsibility involved than we may be letting on.

How did you reach this conclusion? I don't see any link between data demonstrating that most people spend at least one year in relative affluence and even the general concept of "personal responsibility," let alone some sort of specific causal relationship between the two.

Because if the majority of people spend some time in the top quintile (54% spend at least 3 years in the top 20%), it means that the majority of people experience the same (or similar) set of opportunities available to the top quintile income earners. Either they are able to capitalize on those opportunities and stay in the top quintile, or they are unable to do so and fall down to a lower quintile.

Also, nobody is concluding that it’s 100% personal responsibility. Rather, the implication is that personal responsibility might play a greater role in outcomes than some of us are willing to accept.

> Because if the majority of people spend some time in the top quintile (54% spend at least 3 years in the top 20%), it means that the majority of people experience the same (or similar) set of opportunities available to the top quintile income earners.

This is an assumption that you're making, not a logical conclusion which naturally flows from the data. All we know is that 54% of people have been in households with annual income landing in the top quintile three times. The article says nothing about opportunity - would you consider a household where two adults each work two full-time jobs, all four jobs paying $30,000, to have similar levels of "opportunity" to a new CS grad making the same $120,000 total working at FANG?

With regard to social mobility, I found the article's most compelling data to be that representing the percentage of individuals who spent 10 or more years in one of the provided income categories, as that seems more conducive to measuring sustained improvement in economic outcomes. Those numbers are as follows: Top 20%: 31.4%, Top 10%: 14.2%, Top 5%: 6.6%, & Top 1%: 1.1%. These seem to illustrate a far stabler income distribution than that suggested by the 1-5 year figures. I'd be interested in seeing comparable figures for 15 and 20 years, as well, but they aren't readily available.

>Rather, the implication is that personal responsibility might play a greater role in outcomes than some of us are willing to accept.

In all candor, while I could certainly be misreading you, it sounds to me as if you're so "willing to accept [personal responsibility playing] a greater role in outcomes" that you're practically evangelizing for the notion.

This is tangential to the discussion at hand, but, if you feel that the role of personal responsibility is under-emphasized in the United States, my assumption would be that you must spend a lot of time in relatively homogeneous, counternormative circles. American culture has long been characterized by what many other cultures might consider a glaring over-reliance on the ideal of personal responsibility as a means of attaining prosperity (perhaps that cultural inclination is unsurprising, given the unprecedented growth historically experienced by Americans). Personal responsibility is a bipartisan value for most Americans, though what it actually means often remains elusive in practice.

In Deaths of Despair [0] the authors explain how the economy in the US basically bifurcated. Nearly all gains go to those with post-secondary education. The large population of Americans without a college degree is not experiencing the boom that the rest of us have experienced since the bottom of the 2008 recession.

This doesn't change the facts you shared. The median is clearly rising. But it can also help explain the reality we all see on the ground, where those who are near the bottom of the income distribution are more frustrated than ever and see the system as rigged against them.

0: https://press.princeton.edu/books/hardcover/9780691190785/de...

I think it’s exactly correct that a post-secondary education is a reliable guarantee for an upper-middle-class way of life (depending on the degree, of course).

That being said, it isn’t clear that those that go without a post-secondary education are necessarily less able to afford one today than they were in 1991.

1. The net tuition (not the sticker price, which only the rich really pay) is moderately higher, adjusted for inflation -> https://twitter.com/CPopeHC/status/1301975027147997189

2. And while private tuition has always been expensive, the majority of Americans attend public universities (myself included) -> https://www.statista.com/statistics/183995/us-college-enroll...

3. And while there has been a modest increase in the inflation-adjusted price, the ROI of college degrees has increased more than the price. The net result is that the median number of years to recoup the cost of a bachelors degree, adjusted for inflation, has gone down since the 1980’s, from about 22 years to about 10 years -> https://libertystreeteconomics.newyorkfed.org/2014/09/the-va...

If I remember my r/badeconomics crash course, the issue is that jobs are being replaced, and being replaced with jobs like burger flipping instead of manufacturing which would allow you to skill up.

> The net tuition (not the sticker price, which only the rich really pay)

What exactly does "net tuition" exclude? Financial aid comes in many forms - grants, loans (multiple kinds), work study. Excluding some of these might be fair. Excluding others would be chicanery.

> the majority of Americans attend public universities (myself included

Also, the majority of students attend big universities. Want to guess how tuition has increased at Texas A&M or Ohio State vs. a legion of tiny schools that barely achieve accreditation? How many of the sources you found on Twitter are improperly taking an average across schools instead of across students?

> What exactly does "net tuition" exclude? Financial aid comes in many forms - grants, loans (multiple kinds), work study. Excluding some of these might be fair. Excluding others would be chicanery.

The source explains it better than I can:

The amount that students and their families have to pay for enrollment, “net price,” is generally much less than the published price (“sticker price”), for two primary reasons. First, students often receive grant aid from federal and state government programs. The Pell grant program allocates up to $6,345 per year to students enrolled fulltime in postsecondary education. Students from the poorest families receive that full amount, and the award size declines as family income and wealth increase.

Second, private colleges and universities sometimes give discounts to students based on their perceived ability to pay. This practice has the benefit of allowing students to enroll who otherwise would not be able to afford to do so. But it can also be viewed more pessimistically as price discrimination, which is generally perceived as a predatory behavior when exercised by for-profit companies. Essentially, colleges charge students the highest price that they would individually be willing to pay, up to the sticker price, in order to maximize revenue.

> Want to guess how tuition has increased at Texas A&M or Ohio State vs. a legion of tiny schools that barely achieve accreditation?

The source includes that information as well:

> students at public four-year colleges have seen their net costs go up significantly because of increases in tuition that were not offset to the same extent by aid and scholarships. The average annual net cost at a four-year public college has grown by almost 81% beyond inflation over the past decade, to $3,870.

On its own, that looks really bad, but once you account for the change in ROI, the net outcome looks a little different. The upfront cost is higher today, but the long run benefit is even higher.

> The source explains it better than I can

That doesn't completely answer the question. It addresses discounts and grants, but there's more to it than that.

> On its own, that looks really bad

Yes, it does, and that's still no accounting for differences in size. Even state schools vary widely. Eastern Michigan University is not University of Michigan by a long shot.

> once you account for the change in ROI

That matters little to someone trying to figure out how they're going to afford a house while they're still paying off student loans. It mostly kicks in much later, and money later is not the same as money earlier. If you really want to consider that increased ROI, you also have to consider how it's offset by lost opportunities for saving and compounding interest because people are buried when they first get out of school.

Also, if college is no less affordable, why are they so buried? Graduating with more student-loan debt than income was practically unthinkable when I went to school. It's commonplace now. Why? This whole empathy-lacking "it's no harder than it used to be" argument just doesn't pass the smell test.

> That doesn't completely answer the question. It addresses discounts and grants, but there's more to it than that.

Discounts are huge. "Discounts" is just another way of saying that the university charges different prices based on how rich you are, and the sticker price is basically a fiction. It's essentially total price discrimination, except we only learn the true prices after we reveal our income level. It's certainly a problem worth solving.

> Yes, it does, and that's still no accounting for differences in size. Even state schools vary widely. Eastern Michigan University is not University of Michigan by a long shot.

You'd be surprised, the difference isn't as wide as you think it is. The Wall Street Journal put together a tool to let you compare the median debt + earnings per college and degree -> https://www.wsj.com/articles/which-college-graduates-make-th...

Eastern Michigan University + Engineering

Median debt: $12,643

Median earnings: $48,900

University of Michigan + Mechanical Engineering

Median debt: $17,525

Median earnings: $74,200

In both instances, earnings exceed debt. Also keep in mind, those numbers are total debt, not tuition. You can play around with the tool and select different universities and different majors. It's behind a paywall, but if you don't have access, I can pull the numbers for whichever university you'd like to compare.

> That matters little to someone trying to figure out how they're going to afford a house while they're still paying off student loans.

No, the implication is that the salary for college graduates is almost always above the median wage. The calculus is whether the wage increase is higher or lower than the monthly cost to pay off the degree. If it's lower, then the degree is not worth it.

> Also, if college is no less affordable, why are they so buried? Graduating with more student-loan debt than income was practically unthinkable when I went to school. It's commonplace now. Why?

Because it's one thing to say that student loan debt is commonplace, and another thing entirely to suggest that unpayable student-loan debt is commonplace. Consider that almost 100% of homeowners have mortgages (and hence are in debt), but most of them pay them off, and end up with an asset at the end of it. College degrees are (for the most part) exactly like that. The median student loan debt is $17,000 (https://www.forbes.com/sites/zackfriedman/2020/02/03/student...) — but paying that off is like paying off a car loan for a Toyota Corolla, only college degrees aren't a depreciating asset (depending on the major).

> This whole empathy-lacking "it's no harder than it used to be" argument just doesn't pass the smell test.

I wouldn't ascribe intent, but data like this is important to understand what the reality is for the majority of people. While there absolutely exists adverse situations where someone is riddled with hundreds of thousands of dollars in student debt with no employable skill to help pay that off, it doesn't represent the majority of college graduates. The news also has a bias for reporting on the most exceptional cases, you never really hear about the successes. Importantly, this doesn't mean that we shouldn't help those that are struggling. It just means that we don't need to upend the entire system to do so.

I was comparing UM to EMU in terms of size, not cost, but this is still illustrative. Treating the two schools as equal understates cost, as the per student average is higher.

Also, did you "forget" about people without degrees again? They live in the same places, they're also affected by the high cost living, but the ROI of a college degree doesn't help them at all. It's a red herring. As with so much in this discussion, it obscures reality instead of illuminating it.

> Treating the two schools equal understates cost, as the per student average is higher.

Maybe I didn’t make myself clear: the data pulled from the WSJ tool is per student. It’s what the middle individual (per university) expects to owe vs earn. The size of the university doesn’t matter in the context of that data.

> Also, did you “forget” about people with degrees again?

No I didn’t, but people without college degrees earn the median wage and do not have to worry about paying off student loans, which was the earlier contention.

People with college degrees earn above the median wage, at which point the median numbers here don’t really apply to them.

You have to pick your grievance: either you earn the median wage OR you have to worry about paying student loans, but not both. The (wage - expenses) amount is, on average, positive in either case.

The ROI number represents the true value of college, because it not only incorporates the price, it incorporates the net expected returns. Not including the latter obscures more than it illuminates. Simply comparing the price now vs the price in year X is not apples-to-apples, because you were essentially buying a different thing in the 1980’s that was worth less than the unique thing you’re buying today. They just happen to both be named “college degree”.

> The size of the university doesn’t matter

You're missing the point again. This isn't about the original data. It's about how you combine data from multiple schools to calculate an overall average. If that process doesn't include enrollment, you get the wrong answer.

>> Also, did you “forget” about people with degrees again?

>No I didn’t,

> [four paragraphs about degrees, ignoring non-degreed people again]

I'm not allowed to make the comment that deserves.

I’m not sure I’m missing anything.

To recap this conversation, I cited net tuition data that calculates per student tuition, and pegs public 4 year in-state tuition average at ~$11,000 per student.

You responded by suggesting that university sizes vary, and therefore that data is incomplete (though you still haven’t explained exactly how). You then cited EMU vs UM.

I pulled up the actual per-student data at EMU vs UM, and showed that the data across both 1) corroborates the net tuition calculation, and 2) don’t wildly vary from each other. Again, these are per student calculations. The spot-check samples agree with the aggregate calculation.

> [four paragraphs about degrees, ignoring non-degreed people again]

I didn’t ignore non-degreed people. When analyzing people that don’t have degrees, we have to try to understand what the root cause is: whether it’s because they don’t want to attend, because they couldn’t get admission, or because they couldn’t afford it. I’m simply making the argument that reason #3 is no more likely today than it was 40 years ago. I gave you maybe 4 paragraphs arguing why that is the case (degree confers higher salary that more than pays for the up-front cost + everyone has access to student loans + median loan amount is roughly == price of an entry level car)

In the context of a conversation about the costs of college, I’m also pointing out that (by definition), non-degreed people don’t have to worry about those costs. Non-degreed people are also overwhelmingly the people that earn the median wage, and if you’ve paid attention this entire thread, the numbers for median wage earners are positive — even if not as positive as their degree-holding counterparts.

The median is only useful in certain kinds of distributions and many people argue that income distribution isn't one of those.

Do you have a citation for that? The median is generally the most reliable metric to use specifically for income, since it isn’t impacted by outliers.

The median is often used for income, that doesn't make it "reliable."

It’s “reliable” insofar as it tells us how the “average” person is doing, and by definition the lower bound for the top half of the population.

Not reliable at all if you have a bimodal or multimodal distribution.

That’s not true. As long as you’re taking into account the median purchasing power, it doesn’t matter what the shape of the distribution is.

Real median income has increased regardless of the choice of inflation index.

How so its a much much better measure than the arithmetic mean ?

I generally agree with you. I suppose the argument--depending upon what the overall distribution looks like exactly--is that you can have a sizable minority clustered somewhere below what would have been considered a reasonable middle-class lifestyle while the median still looks reasonable.

Also CPI doesn't really account for housing prices in many of the metros where the best jobs are or higher education prices.

By definition, the “cluster” below the median is exactly half, regardless of the shape of the distribution.

> Also CPI doesn’t really account for housing prices

Per my source, the median income is the highest it’s been since 1981, and the total compensation the highest it’s been since WW2 regardless of the inflation index you use.

Also, the median number of years to recoup the cost of a bachelors degree, adjusted for inflation, has gone down since the 1980’s, from about 22 years to about 10 years -> https://libertystreeteconomics.newyorkfed.org/2014/09/the-va...

> By definition, the “cluster” below the median is exactly half, regardless of the shape of the distribution.

Right, but that doesn't measure how for away from the median the upper and lower clusters are.

> Also, the median number of years to recoup the cost of a bachelors degree, adjusted for inflation, has gone down since the 1980’s, from about 22 years to about 10 years

That would be consistent with a hypothesis that real wages have increased for higher earners and decreased for lower earners, right?

> Right, but that doesn’t measure how far away from the median the upper and lower clusters are.

Well, it doesn’t particularly matter how far from the upper the median clusters are if their absolute standard of living has improved — and we measure that by accounting for inflation. Regardless of which inflation metric you use (some include housing prices, some don’t), median income has risen.

As for the lower cluster, the most reliable metric to use there is the poverty rate...which has also substantially fallen -> https://twitter.com/Noahpinion/status/1308790816937095169?s=...

You can also look at the historic income trends divided up by quintile -> https://www.census.gov/data/tables/time-series/demo/income-p... (Table H1, All Races, it's an Excel spreadsheet). Inflation adjusted income for the bottom two quintiles have also increased substantially.

> That would be consistent with a hypothesis that real wages have increased for higher earners and decreased for lower earners, right?

No, it would be consistent with a hypothesis that real wages have increased faster for higher earners than for lower earners, but demonstrates no evidence that it has decreased for lower earners.

The empirical results show that real wages increased across all income levels, and between 2014-2019, it actually increased faster for lower earners -> https://www.cbsnews.com/news/low-wage-workers-are-getting-bi...

And that cluster can be anywhere below the median that is the problem. It could even be at zero.

That's a separate argument, because at that point we're no longer talking about the standard of living of the "average American".

That being said, across all quintiles (the bottom 2 quintiles include the clusters below the median), real income has also grown substantially -> https://www.census.gov/data/tables/time-series/demo/income-p... (click Income Limits for Each Fifth and Top 5 Percent, it's an Excel spreadsheet)

I'm not sure what use it is to consider the "average american". I'm concerned about the cohort of people who are barely scraping by, you seem to paint a picture that these peoples lives have improved because their "real income" has grown substantially. Ok so they were barely making rent at 15k/year, and their real wages increase by 5k/year since 2010. Has their rent remained stable over the last then years? Perhaps these quotable numbers aren't all that useful except to further marginalize?

Correct, which is why we adjust for inflation, and there are a ton of different inflation indexes one can use. Per the links in the source comment, regardless of which index you use, we have seen an increase in income.

> Has their rent remained stable over the last then years?

From the data, outside of expensive coastal metros, yes. If you don't have a college education, you're more likely to enjoy a higher standard of living in Little Rock, Arkansas or Minneapolis, MN than in San Francisco or Manhattan.

> Perhaps these quotable numbers aren't all that useful except to further marginalize?

No, these quotable numbers tell us that we're generally trending in the right direction. Therefore, any solution we employ to help those that are the poorest among us (which is important) doesn't necessarily need to upend the entire system.

> From the data, outside of expensive coastal metros, yes. If you don't have a college education, you're more likely to enjoy a higher standard of living in Little Rock, Arkansas or Minneapolis, MN than in San Francisco or Manhattan.

Are we comparing a person in one location to another? I thought we were talking about improvements year over year.

> Are we comparing a person in one location to another? I thought we were talking about improvements year over year.

We're doing both. And in both metrics, the bottom are the best off today than ever before. Unfortunately, the bottom were really poor in the 20th century, so being better than that (while good), doesn't mean our work as a society is complete. But that's a welfare problem, not a "what is the system like for the average American" problem.

It's also worth noting that, in America, the bottom 3 quintiles are extremely underrepresented in the highest COL metros. That's just not where they're concentrated. Given the purchasing power disparity between US states, the variance in the US-level data is probably too wide to be useful, and you kind of have to compare from State-to-State -> https://www.advisorperspectives.com/dshort/updates/2019/12/1.... Once you account for that, the root causes also become easier to identify — predominately local land use policy.

The problem with using the median for income is that it does not tell anything about inequality. If the top 1% get their income doubled (or the bottom 30% their income halved, or both at the same time) with all else being equal, the median does not change. You really need a high percentile as well. Low percentiles are not that interesting, because the distribution is much more compressed there.

In essence, a median that keep climbing nicely is no indication that the situation is not becoming catastrophic. Granted, using the average is arguably worse.

If the top 1% get their income doubled, and the median doesn't change (even after accounting for inflation / purchasing power), then it's debatable if we even have a problem.

If the bottom 30% income halved, you're correct that we have a problem, but that hasn't actually happened.

You can view the inflation-adjusted income data split up by quintile here -> https://www.census.gov/data/tables/time-series/demo/income-p... (Table H-1, All Races, it's an Excel spreadsheet). Even among the bottom quintile, inflation-adjusted income has increased.

> If the top 1% get their income doubled, and the median doesn't change (even after accounting for inflation / purchasing power), then it's debatable if we even have a problem.

I think we do, as these people have disproportionate economical and political power, which results in unbalanced economic policies that favour one specific socio-economic class and breeds discontent. I don’t have links handy, as I am on the phone, but there are works showing a correlation between political instability and economic inequality.

By definition, the top 1% are a minority of voters, so their influence is only as strong as the votes that they themselves are able to cast, or that they are able to convince others to cast. Their impact on elections is overstated -> https://fivethirtyeight.com/features/money-and-elections-a-c...

I don’t mean any disrespect, but history ancient and recent has shown that this is not true. On several occasions an upper class minority has been able to convince parts of lower classes to behave against their best interests. A very relevant example is the capture of the GOP and the enduring support they get from poor, rural whites even though their policies systematically favour wealthy elites. Witness how republican senators turned a minority of the votes from this limited support base into a weapon to completely remake the judiciary.

What is spent during campaigns is just the tip of the iceberg, and is a tiny drop in the daily deluge of propaganda. Look at the media landscape in the US. Private interests such as the Murdochs, Robert Herring, and whoever controls the Sinclair Broadcast group drive the narrative and the constant brain washing. I mean, they keep convincing a significant part of the population that accessible health care is bad. You seem to assume that people are rational and not easily influenced. They are not, and they are.

> On several occasions an upper class minority has been able to convince parts of lower classes to behave against their best interests.

No, on several occasions, an upper class minority has been able to convince parts of lower classes to behave against what you think their best interests should be.

> I mean, they keep convincing a significant part of the population that accessible health care is bad.

Look, I understand that a lot of people on this forum think that there's one and only one way to achieve accessible healthcare, but the reality is that there are SO many different ways to get affordable / high quality care. Singapore, Switzerland, the UK, Denmark, Germany, and the Netherlands all have wildly different healthcare systems, but all produce fairly good outcomes (especially Singapore).

I'm happy to talk more about all of them: I write software for claims processing systems for a living and can tell you all about how healthcare pricing works.

What you're witnessing is that there's broad agreement around what the problem is, but violent disagreement on what the solution ought to be.

You really want to be comparing distribution curves rather than looking at any single average.

Well, we're looking at the median here, which tells us what the lot of the "average American is".

If you want to compare distribution curves, you can look at the income growth separated by quintile.

That can be found here -> https://www.census.gov/data/tables/time-series/demo/income-p...

Click on "Income Limits for each Fifth and Top 5 percent", All Races. It's an Excel spreadsheet.

The real income of the bottom 2 quintiles have also dramatically increased.

Say you calculate the median income for all spectators at a football game at $40,000. Suddenly Bill Gates walks in and the median skyrockets creating a false reality of what all others actually make. Median can often over-simply and create erroneous information.

Maybe you're thinking of the mean? BG shouldn't shift the median much in the situation you described unless the income distribution is really weird.

You are confusing median and mean.

this is correct. conventional statistical functions rely on a whole host of assumptions about the shape and type of data. Typically that its a bell-curve distribution & ratio style data. The more you move away from that parametric style of data, the more conventional statistical functions simply have no meaning.

To use an example. I worked at a shop where we had a freemium model. About, let's say, 50% of our customers paid $0.00. About 2% paid over, say, 10K. Between those two points we had a reasonably clean exponential curve, clustering at key product price points. (I've goosed the numbers for confidentiality purposes, but this is close enough for discussion). In this scenario, what was the average ROI per account? Well, truth is, that's not a useful answer, as it was roughly $0.01.

I wound up building a small set of non-parametric data tools to assess the customer base. It was a fun journey, but a critical lesson is: the kind of data you have and its shape determine the statistical functions that have meaning, and, they didn't teach that kind of data analysis in your basic calc-based stats class in college. :)

Nobody cares because they can’t afford a house to live in, and family health insurance costs as much as rent.

By definition the median income cannot win a bidding war for housing when there’s only enough supply available for the top 5%.

As of 2019, around 65% of americans own their own homes. That's down somewhat from the peak of 69% in 2004. So, far more than the "top 5%".

That 65% includes people who bought housing while it was still possible to do so without being in the top 5% of earners

That's essentially only true in SF, NYC, Seattle, and maybe DC — and that can largely be attributed to local land use restrictions more than anything else.

Here's a list of the salary required to afford the median home -> https://www.hsh.com/finance/mortgage/salary-home-buying-25-c...

This thread breaks down the ratio of home-price-to-median-income per MSA -> https://twitter.com/jmhorp/status/1221828310000271361

There's an entire zone of "Fine, American Cities", all affordable to both Boomers and Millennials. There are dozens of metro areas you can move to, buy a home (if you like), and start saving your income.

It's important to note that these charts apply to the nation, not individual cities. The rent has increased 5x since 1990 in Boston - wages are up 2.7x:

* Boston Rent: https://fred.stlouisfed.org/series/CUURA103SEHA

* Boston Wages: https://fred.stlouisfed.org/series/MHIMA25025A052NCEN

The same is true for almost every major (growing) city beside Houston & Dallas.

Combined that with the fact that income taxes are higher at these "higher wages" and that student debt payments are up 4x just since 2007 - who knows how much since the 1990s - and you can start to see why things aren't so rosy for young professionals.

* Student debt: https://fred.stlouisfed.org/series/SLOAS

If you look hard enough, you can find any chart to support almost any opinion. The point of the "anecdata" was to get people to look at a certain side of things. Particularly for people living in HCOL cities that aren't "highly skilled".

Not true in every metro, there's a tool you can play with to show you the wage-to-house-price multiple: https://twitter.com/jmhorp/status/1221828310000271361

Major metros where the multiplier has largely stayed the same:

Columbus 1984: 2.47x

2017: 2.97x

Omaha

1984: 2.3x

2017: 2.77x

Little Rock

1984: 2.85x

2017: 2.75x

Kansas City

1984: 2.64x

2017: 3.01x

Pittsburgh

1984: 2.16x

2017: 2.42x

Minneapolis

1984: 2.64x

2017: 3.34x

Houston

1984: 2.66x

2017: 3.68x

Chicago:

1984: 2.45x

2017: 3.49x

Also, inflation adjustments take into account the increase in prices of all goods & services, including housing -> https://www.bls.gov/cpi/tables/relative-importance/2019.txt. So even if housing costs have gone up more than overall inflation, other things have fallen, and OVERALL inflation rate is the best rough measure of "cost of living". There's disagreement over which indexes are better (based on how they weight different expenses); CPI-U vs CPI-W give different importance to different goods & services. Importantly, the inflation-adjusted incomes have gone up regardless of which index you choose to use.

Does this count people who are unemployed? Or is it only the median of people who are employed?

https://www.businessinsider.com/how-coronavirus-recession-is...

These numbers account for those that are unemployed, but also these numbers are all pre-COVID.

I agree that it's important to compare anecdotes to available data, but we should be careful not to assume that the available data is itself "the forest." In other words, the map is not the territory.

While it's certainly possible that the sort of anecdotes commonly found in threads like this (regarding the challenges facing today's youth) are unfounded, I think it's more likely that they reflect qualitative changes not represented by the data (or, alternatively, changes which simply aren't represented by the particular data typically used in conjunction with analysis of these topics).

Data showing that the median person earns more working fewer hours today than their parents did at the same age, for example, can't reflect (hypothetical, let's say) circumstances such as:

* An increasingly competitive job market: Unemployment figures don't account for increasing education and experience requirements job-seekers face, nor do hours worked reflect time spent on career preparation in an era where high school students study for the SATs, college students are taught that "networking" is an essential skill, and college grads are more likely to have had multiple internships than their parents are to have had one between them.

* Increasing career instability: Not only are single-employer careers long gone, but, for many, so are single-career lifetimes. Additionally, the increasingly bimodal distribution of incomes means that, while the median income may have increased, the consequences of falling out of a "good" career track can seem greater than they used to be. [1] For reference, 44% of Americans work in 'low-wage jobs' with a median income of ~ $18,000. [2]

* Increases in the cost of living that counteract income gains: Rent, housing prices, (more-important-than-ever) higher education, healthcare & childcare have all increased significantly over recent decades, which likely makes it difficult for many to feel as wealthy as one would suspect.

Considering circumstances like these helps me understand how many may feel much worse than real median income might suggest and makes it seem less strange that young people appear to be poorer than their parents were at the same age - living with their parents longer into adulthood, buying fewer homes, getting married later, having fewer children, etc...

I would also speculate that, in terms of perception alone, the rise of social media and increasing economic inequality (with specific regard to the research suggesting that individual well-being is more closely linked to low inequality than absolute levels of economic welfare) could negatively impact the average American's perception of their quality of life.

1 - https://www.pewsocialtrends.org/2020/01/09/trends-in-income-...

2. - https://www.brookings.edu/blog/the-avenue/2019/11/21/low-wag...

Lies, damn lies, and statistics. The first 3 links are for household income. They are comparing 2 income GenX/Millenial households with 1 income Boomer households.

Here is generational wealth: https://www.washingtonpost.com/business/2019/12/03/precariou...

Yes, household income is typically used because you only pay rent once per household, not twice. You typically only have one set of expensive appliances, furniture, etc per household, not 2.

Also, household size has historically fallen -> https://twitter.com/Mark_J_Perry/status/1307408040686235650

You can also just ignore dual-income households and look at the data for single-income households, it's essentially the same (if not better) -> https://twitter.com/ernietedeschi/status/1308775197311467520

Some quotes are really timeless and applicable to many contexts, in this case the first part (pulling out the knife a bit) could be about the progressive center-right and the latter part (denying that it exists all together) is more of the status-quo apologists like the above post. Heavily cherry-picked statistics (like "household" here) even though on the ground facts is so obviously different (house prices, student debt, health care costs, child care costs etc).

"If you stick a knife in my back 9 inches and pull it out 6 inches, that's not progress. If you pull it all the way out, that's not progress. Progress is healing the wound that the blow made. They haven't pulled the knife out; they won't even admit that it's there."

-Malcolm X

We typically use "household" numbers because you only pay rent once per household, not twice. You typically have only one set of expensive appliances per household, not 2 (or N), etc etc.

That being said, this is a common (worthy) criticism, and there are 2 data points one can respond with:

1. Household size has actually fallen -> https://twitter.com/Mark_J_Perry/status/1307408040686235650

2. You can compute the "individualized" growth by accounting for dual incomes, and the outcome is still largely the same -> https://twitter.com/Mark_J_Perry/status/1307408040686235650

3. You can also just ignore dual-income households and observe what the reality looks like for single-income households alone, again similar outcome -> https://twitter.com/Mark_J_Perry/status/1307408040686235650

Your war of attrition style of argumentation isn't that impressive. The amount of time I would need to spend to counter your links is like 10x of the time you spend producing it - which is pretty obvious given how prolific you've been in this thread.

You're right, dispassionately citing relevant metrics and sources to make a set of points is far less impressive than complaining about being out-argued. We should all aspire to whatever we call that style of argumentation!

Out-argued? Don't flatter yourself. You're only spamming links in the hope that no one will bother looking them up. It's the same MO that your fellow status-quo apologist raynier and refurb do, in every. Single. Thread. Suggesting. Inequality. Look it up, I'm not exaggerating.

Got it, so you’re not only incapable of actually engaging with arguments that are clearly cited with verifiable links, you also appear to have an axe to grind attacking other people totally unrelated to the discussion at hand. This is gold standard argumentation, I clearly have so much to learn from you!

I asked you to google a quote which take a minute to find at most. In this topic you consistently require folks to spend much more time to even come close to interpreting your links.

Axe to grind? Yes. I do notice patterns that I don't really fancy, reactionary ones in particular. Aristocrats defending monarchy get little sympathy from me.

The vast majority of my links are literally pictures of charts and 280 character tweets.

In general, when you make a claim, the burden is on you to prove it, and you should hence provide links to your citations. Imploring others to Google around to corroborate your own arguments (especially when — in your case — the arguments are incoherent) imposes that burden on the recipient. It’s far higher a burden than reading links that have already been supplied, especially when those links are tweets and charts.

On only one occasion in this discussion, my links included research papers — but that was in response to claims about Piketty, a researcher. I generally expect people that bring him up to be able to parse research papers — a skill that you typically learn as an undergraduate.

Both articles can be found within seconds by selecting the text, right-clicking and clicking "Search Google".

The tweets you are linking are summarizing cherry-picked data that itself would require much more effort to figure out.

Both quotes I pasted show significant problems with those "refutations". The first is simply using the wrong data and the latter seem to just be complaining that there's too little data to make an accurate estimate (and the obvious solution is to lobby for states to provide this, which status-quo apologists seem very unwilling to do).

Why am I not convinced?

Because the data doesn’t fit your world view, so you’re fine just ignoring the data?

The comment you responded to above poses a valid question - what should we do if empirical data seems to contradict our own lived experience?

"The data" is not homogeneous or infallible, nor can it fully describe all phenomena it's applied to. At best, data can provide us with a rough approximation of the landscape it attempts to describe. In this particular case, I think that landscape is smaller than the territory established by the OP's linked blog post (which seems to transcend the easily-measurable world of simple economic indicators).

Would you consider it prudent to dismiss one's lived experience offhand, at the mere site of a few quickly-pasted links to tweets containing simple, decontextualized data points? What, then, if another commenter subsequently provides contradictory data? Scrolling through a typical HN thread would turn into a nauseating ride on some sort of intellectual see-saw.

If the commenter you responded to is "not convinced" by some tweeted factoids claiming that Americans are working less and making more than ever, does that imply that they're ideologically motivated?

I don't think so, no more than I think your reply to them implies that your own motivation is ideological. Without additional context, those "facts" don't significantly imperil any specific worldview.

Lived experience, while important, should be treated like anecdotes.

While anecdotes are valuable, the plural of anecdote != data.

Should we help people whose lived experience is worse than ours? Absolutely.

Does the mere existence of people whose lived experience contradicts that of the aggregate majority suggest that we ought to upend our systems? No, and that's the point.

In general, when we see (overwhelming) empirical outcomes that don't confirm our priors, we ought to shift our priors. We do this in the context of climate change, there's no reason we shouldn't also do this in the context of the economy and labor markets.

For sure. I think the question is what does the empirical evidence say in this case. And, for complex issues where drawing conclusions from data is nontrivial, using judgement.

Lived experience is certainly anecdotal, and I agree that anecdotes don’t simply transform into data when aggregated. That’s not the point I was trying to make.

You ask, “Does the mere existence of people whose lived experience contradicts that of the aggregate majority suggest that we ought to upend our systems?” First of all, I’ve said nothing regarding “upending our systems.” More importantly — just as anecdotes != data, neither can data replace the role of lived experience. If many people feel like they’re struggling today, that doesn’t contradict data saying that they should be making more money in less time - to me, it suggests that there may be more to the “equation” of positive lived experience than income.

In other words, while I don’t think that it’s feasible to precisely compare the “difficulty” of living across different eras, it’s certainly possible that people can be making more money than ever before and also struggling en masse. The whole of life can’t be explained by simple economic data. Scratch that - the whole of economic life can’t even by explained by economic data... I expanded on this concept in a reply to another comment of yours, but you may not have seen it.

Well, I draw informed, qualitative conclusions which take quantitative data into account.

I think everyone who read my comment understood what I left unsaid, even if they didn't agree with it. And, as the saying goes, there are lies, damned lies, and statistics.

Just because an argument is logical and has facts doesn't mean it's correct. There are multiple ways to shape, work with, or interpret data.

But, speaking of data, is the guy who's tweets you referenced - Ernie Tedeschi, a reliable source? Better or worse than, say, Alan Greenspan? What are his general biases? Same with the Bloomberg article. That article itself said "A rising but uneven tide - the late '10s weren't equally beneficial to all Americans."

Plus, let's use Occam's razor. Which way does it cut?

- Rent prices in major cities / economic hubs for non-tech workers.

- Cost of healthcare in the US

- Cost of higher education in the US

- Cost of home ownership by major cities in the US.

- Job security and availability of well-paying work for non-tech workers?

- Is the economy benefitting those who need it most?

- How equitably have the fruits of economic growth been distributed?

> There are multiple ways to shape, work with, or interpret data.

This is correct, but no matter how you look at it, the data tells largely the same story.

Maybe you think that the median paints an insufficient picture or you want to consider all quintiles including the bottom 2 -> https://www2.census.gov/programs-surveys/cps/tables/time-ser... — there's been a real increase across all 5 quintiles, adjusted for inflation.

Maybe you think that this doesn't account for housing/healthcare/education. But no matter which inflation index you use (each put different weights to housing, medical costs, education, etc), the adjusted median personal income is up. (And YES, this all accounts for all those things -> https://twitter.com/jmhorp/status/1308799186301747200)

Maybe you think this is attributable to dual-income households. But when you ignore those and focus on single-income households, it's still up, and higher than boomer counterparts -> https://twitter.com/ernietedeschi/status/1308775197311467520

Maybe you think this is attributable to working more hours instead of actual wage increases. But hours worked is actually decreasing -> https://fred.stlouisfed.org/series/AVHWPEUSA065NRUG

Maybe this is all well and good, but the lower wages have stagnated, and that's what we should be talking about...except that has also not been true in the 2010's -> https://www.cbsnews.com/news/low-wage-workers-are-getting-bi...

After a certain point, it's worth reflecting on whether you're imposing new constraints / explanations on the data for the sake of intellectual curiosity, or just because you really don't want to revisit prior conclusions.

> But, speaking of data, is the guy who's tweets you referenced - Ernie Tedeschi, a reliable source? What are his general biases?

He's a policy economist https://www.linkedin.com/in/ernie-tedeschi-74ba48b/ who's worked for the US Treasury, who's focus is labor markets. His biases are no different from Piketty, Saez, or Zucman, who also have biases. What's more important is what to make of the data they cite.

I appreciate your response. To be honest it's a bit of chart/graph overload for me. If you've got the moment I'd appreciate and find helpful your take on this -

https://www.pewresearch.org/fact-tank/2018/08/07/for-most-us...

Is the article talking about something different? Would you say they're incorrect? Is their data old? Etc.

To me it seems they're arguing real wages haven't increased that much in the last 40 years.

Also I just want to point out, that the very end of your article about wages increasing for low-wage workers, says:

"That's not to say that low-paid workers have it easy. According to the Tax Policy Center, the bottom 20% of households are earning typical annual income of about $13,300. By comparison, the top 20% of U.S. households earn about $221,000 annually, or nearly 17 times more than the lowest quintile."

My interpretation is, who cares if there's a 50% wage increase from $10/hr to $15/hr if neither of those is a decent living wage to begin with, and the folks at the top of the pyramid are just making staggering amounts of money? The top 20% averages $220K, the top 1% ... much much more.

Which is a bit off-topic, but, at the end of the day economics itself is about people, otherwise there'd be no point! : )

> Is the article talking about something different? Would you say they're incorrect? Is their data old? Etc.

It's probably a combination of a couple things.

1) the article's editorializing of the data doesn't match up with the actual raw data -> https://fred.stlouisfed.org/series/MEPAINUSA672N. This raw FRED data is basically as close to the "primary source" as you can get with this sort of thing.

2) the article looks at total benefits costs and compares them with total wages and salaries, which should set off a couple alarm bells: in the US total compensation is what we need to look at. Basically, they're double counting healthcare costs by ignoring the fact that employers pay the majority of premium costs (https://www.kff.org/report-section/ehbs-2019-section-6-worke...), while also counting the full cost of those benefits against the after-wage dollar amounts. In other words, we've all been receiving huge phantom raises, and we just don't know it because it doesn't show up in our bank accounts.

3) They don't take into account taxes and transfers, which median earners broadly enjoy. To give you a sense, here's what the median disposable income looks like after taxes & transfers, by country: https://en.wikipedia.org/wiki/Disposable_household_and_per_c...

> My interpretation is, who cares if there's a 50% wage increase from $10/hr to $15/hr if neither of those is a decent living wage to begin with, and the folks at the top of the pyramid are just making staggering amounts of money?

Because that 50% wage increase from $10/hr to $15/hr tells us very little about a single earner's pay history — it presupposes that a single person stays at that level for the entirety of their life (which we know not to be true). Those numbers show us the snapshot-in-time income numbers for everyone currently at that salary level, but does not account for people actually moving income levels as they progress in their career. The data isn't "here's the life of Joe over the last 5 years", it's "here's the life of people without college degrees that are X years old with Y years of experience with X & Y held constant over 5 years". I suppose "the lowest quintile wage has modestly increased over time" has a different ring to it than "the entry level starting salary has modestly increased over time".

Also, this is a bit more debatable, but one can also argue if it really matters if the people at the top are making staggering amounts of money, if people in the middle tier (again, not a static group) are also doing better, despite being of (predominately) lower skill — especially since that staggering increase at the top doesn't happen in a vacuum, it's because our system rewards those who play an outsized role in providing goods & services that increase our collective standards of living.

Thank you! Much appreciated, and interesting.

> The data isn't "here's the life of Joe over the last 5 years", it's "here's the life of people without college degrees that are X years old with Y years of experience with X & Y held constant over 5 years"

That's an excellent point. I think that, for various reasons, I've been generalizing more in our discussion and you have been making much more specific and limited claims. One reason I've been generalizing is that I don't know a lot about this stuff : ).

I guess my natural next question is, why do young people (to generalize) feel screwed over by our current economy?

No problem! You've been a lot of fun to talk with, so thanks for that.

> I guess my natural next question is, why do young people (to generalize) feel screwed over by our current economy?

If I were to guess, it's probably because young people have experienced now not 1, but 2 major crises in their lifetime (2008, 2020).

Young people also have congregated to some of the most expensive metros in the US, and those localities have done a terrible job building enough housing to keep up with demand.

I think the collective angst is justified, but needs to be contextualized so that we don't prescribe the wrong solutions.

+1 : )

> Real median per capita income is the highest its ever been regardless of which inflation index you use

Median is very misleading because of rise in income inequality. More than 50% of gains in median income last 20 years have gone to the top 25% https://www.pewsocialtrends.org/2020/01/09/trends-in-income-...

And working less hours is also skewed by the rise of millions of gig jobs that don't have set hours.

The top 25% of the population is doing great by any measure. But when you discard the top 25%, the rest doesn't look so good. Income inequality in US is higher than almost every other industrialized nation. As high as it was in the 30's when massive social unrest gave rise to unions and worker protections.

When you factor in student loan debt and minimum wage being degraded by inflation and gig jobs, the bottom 50% are poorer than ever. As of this year, student loans have eclipsed credit card and auto loans as the second largest form of consumer debt behind mortgages

> Median is very misleading because of rise in income inequality. More than 50% of gains in median income last 20 years have gone to the top 25%

how can this possibly make sense? by definition, the earnings of the top quartile cannot affect the median.

I'm an idiot, was confused with mean

Median is immune to outliers, so it's generally what you want to look at even in spite of inequality.

That being said, you can even look at the per-quintile levels -> https://www.census.gov/data/tables/time-series/demo/income-p...

See table H-1, All Races (it's an Excel spreadsheet). Across all quintiles, including the bottom 2, inflation-adjusted income has increased.

> When you factor in student loan debt

The median number of years to recoup the cost of a bachelors degree, adjusted for inflation, has gone down since the 1980’s, from about 22 years to about 10 years -> https://libertystreeteconomics.newyorkfed.org/2014/09/the-va...

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