• fidodo@lemmy.world
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    10 months ago

    When it really hit me was when I found out how much my girlfriend’s parents paid for their house a few miles from the beach in San Diego on blue collar salaries. It was 1/5th the cost adjusted for inflation that it is now. If houses were still that price I could easily afford 2 on my salary, but instead I can’t afford 1

      • Aceticon@lemmy.world
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        10 months ago

        I don’t get it how this post is behing downvoted: understating Offical Inflation mathematically yields bigger Official GDP numbers due to how the Offical Inflation is used to deflate Nominal GDP to produce the supposedly inflation-free Real GDP which is the official one.

        It doesn’t take much to find politicians boasting about growing GDP, so there is huge political pressure to make that number high in ways which aren’t obvious (and tweaking the basket of good and services used to calculate inflation is quite a subtle way to do it). It’s not by chance that some countries (for example the UK) some years ago - basically since the house price bubble in there started going - even started using and Inflation Index that doesn’t include house prices (I’m not quite sure if that’s the case in the US).

        It also fits the observeable effects: a salary in the 2020s that can barelly pay for a small appartment and food, which using the inflation indexes is inflation adjusted to produce a supposedly equivalent salary in the 60s, yields something that back then paid for a house, a car and all the expenses of family of 5, something that can only be explained by the inflation adjustment being wrong (if it was right, it would roughly buy the same now and back then) hence the inflation indexes are wrong and over the years have been much more wrong on the side of understating inflation than on the other side (and always erring in the same direction cannot be explained by the normal error in the method).

        Mind you, this is not massive rigging of inflation with 10%+ “adjustments”, it’s more 1% here, 0.5% there, which over decades adds up to a 100%+ cummulative error.