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    [OC] Was eine Stunde durchschnittlicher US-Arbeit im Jahr 1985 im Vergleich zu 2025 einbrachte, verteilt auf sechs Alltagsgegenstände

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    1. Low_Ability4450 on

      Methodology :

      A year of public college tuition now costs the wage-time of nearly 40 mid-range TVs. In 1985, it was just 3.3 TVs.

      Methodology highlights:

      – Wage benchmark: BLS production & nonsupervisory hourly earnings, FRED series AHETPI ($8.73/hr in 1985 → $31.34/hr in 2025)

      – Homes: FRED median existing-home prices

      – Tuition: NCES + College Board

      – Rent: Census + BLS CPI rent series

      – Big Mac: The Economist Big Mac Index

      – Gas: BLS regular gasoline

      – TVs: retail survey / major retailer comparisons

      Points that can be noted :

      – TV quality improved massively over the period

      – 2025 rent uses latest available ACS data (2024)

      – Big Mac uses 1986 because that’s when the index begins

      Full dataset + CSV + verifier code:

      [https://eco3min.fr/en/us-purchasing-power-1985-vs-2025/](https://eco3min.fr/en/us-purchasing-power-1985-vs-2025/)

      Tools: Python (pandas, matplotlib). Reproducible verifier code published with the dataset (42 checks, all pass).

      Happy to answer questions.

    4. whatacharacter on

      What’s the mid range family TV for 1985? It certainly wasn’t a 50 inch.

    8. Zezu on

      I wouldn’t compare anything with TVs as a unit. I like the method but TVs have gone down wildly in adjusted value over the years.

    10. Bucket_of_Spaghetti on

      The color scheme is confusing and takes too long to digest. Your legend has Red as 2025 but then it randomly becomes green when it’s lower. I would make 2025 a separate color entirely and then only use red/green for your % on the right. You’re mixing legends right now and it makes it hard to quickly understand.

    11. melanogaster on

      why did your order the data like this? why not have it go from most negative to most positive in terms of change? and your legend doesn’t actually represent the colors on the plot.

    12. FarisPride on

      Sure McDonald’s made this data

      Now, let’s do 1985 vs 2025 big Mac size

    13. senseiman on

      I’m guessing the cost of gas in 2026 doesn’t hold up so well in comparison as it did in 2025…

    15. Freedom_33 on

      When I look at this, I get that part of the point is to drive how home prices have increased, and from this chart compared to median earnings.

      One quibble that I think confuses things: by looking at sales price of a home, you are mixing consumption items (Big Macs, TV) with an item that is a mix of consumption and asset (home price sale).

      Someone is buying that home, but someone else is selling it, so in some sense you would have to add that back into their income. So I think showing median home price compared to income isn’t a good measure.

      It does show it’s better to be a home seller than a buyer, but I think wages, consumption, and assets are getting mixed together in a confusing way that doesn’t get right picture across.

      Nice chart and nice data and presentation

    16. CloudEnvoy on

      This post is a great example how data can be manipulative and how much is discretion based.

      How do you choose the exact home? or the exact TV?

      how about the quality of ingredients in a big mac? today its all additives, engineered meat, seed oils, preservatives etc. who cares if it costs the same?

      depending on the exact choices, you can make a million different sets of figures

      this is completely useless

    17. hoopaholik91 on

      The problem I always see with these housing numbers is that they use sales price, not mortgage payment.

      A $200k mortgage in 1985 when they had 12% interest rates is the same monthly payment as a $320k today with our 6.7% interest rates.

      That’s not a perfect comparison either because other costs like insurance and taxes **are** based on sales price, but I think your graph is still an overestimation.

    18. shwaynebrady on

      While I agree housing prices are very high at the moment. Median Housing prices are not the correct metric.

      It needs to be compared on a relative basis, like cost of sq footage. This also doesn’t account for interest rates and loan terms. As we have all witnessed in the COVID era, interest rates fluctuating from 2% to 8% drastically alters not only buying power but also the gross cost of homes.

      Interestingly enough, on average 4 people used to live in a 900sg ft home in 1960 now 2 people live in a 2500 sq ft home in 2026.

      https://www.reddit.com/r/charts/s/MCYb0ldtuK

      Cheap barebones starter homes are like econobox sedans/coupes, yes they stopped building them… because no one wanted to buy them.

    20. kneevase on

      Nearly 30 years ago, the Federal Reserve Board published a more comprehensive (but still very accessible) document which portrayed a similar effect: [https://www.minneapolisfed.org/~/media/files/research/prescott/quant_macro/arpt97.pdf](https://www.minneapolisfed.org/~/media/files/research/prescott/quant_macro/arpt97.pdf)

      It would be nice if the fed would hire a summer student to update the document to include 30 more years of data, but the conclusion is almost certainly the same, which is that most goods and services have experienced large declines in their real price over time, which has made consumers considerably better off. We don’t really notice this over shorter time frames like 5 years, but when you look over 40 or 100 years it’s quite striking.

    21. EmperorPalpitoad on

      Can anyone explain to me how TVs got so cheap?

      I remember in the 2000s where only the rich would buy a giant flat screen TV but the middle class would encourage you to save your money to buy a „budget quality“ CRT TV instead.

    22. avatoin on

      If the log scale is so you can put Big Macs and homes on the same graph, it might be better to normalize the data. Have the reference year be set to 0 and the comparison year show the percent change of hours worked. This way it clear shows how big macs costs about the same but homes are way more expensive, relative to hours worked.

    24. samuraiofsound on

      I think I’ve seen a presentation from a MacDonald’s corporate employee that specifically talked about how the price of the big mac does this intentionally, it is a corporate design choice they’ve made. 

    25. Platos-ghosts on

      It’s a disgrace that society allowed the cost of a Public College education to increase by 150%.

      Local public colleges should be affordable for anyone that works a part-time job, that dream died 40+ years ago. I’m not talking room/board, but tuition/fees for your local college should be easily covered with just a PT job. Private colleges can do what they want, they are a business and not a public good in the same way.

    26. SashikoIsMyVibe on

      This needs some sort of referential extra axis of average incomes and these prices in relation of percentage increase of income.

      Edit: Not a criticism but more a externalized curiosity.

    30. honicthesedgehog on

      I think it’s a neat visualization, but there are a couple issues when you look closer…

      * The callout using a „TVs per year of public college“ metric is not great. You’re basically comparing `381/10 > 151/46`, with both increasing numerator and decreasing denominator making the difference look bigger. Plus, it’s kind of a nonsense comparison anyway, as these aren’t things that anyone really compares directly.
      * The percentages on the right-hand side are incongruous, if not outright conflicting, with the visualization. The distance for -24% and +37% don’t seem meaningfully different (though +22% does look slightly smaller than +37%), but more importantly, -79% looks to be about twice as big as +153%.
      * As mentioned elsewhere, the labeling+color coding scheme is confusing. I’ve definitely seen visualizations that do something similar (maybe from the NYTimes?), I would take some inspiration from them. I’d also drop the tick marks on the X-axis, they just feel like visual noise.

      Overall, I think my biggest issue is that it feels like trying to emphasize both the change over time AND the relative change between categories, using both actual(ish) and percentage change, means that neither comes across especially clearly. Based on visual cues, it feels like the difference for median home price comes across as…mildly trivial, compared to others? Yeah, 37% isn’t nothing, but compared to a 153% increase or even a 79% drop, is it really that bad? Then you notice that you’re talking a net difference of 3,600 hours…

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