• anon6789@lemmy.world
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    1 month ago

    Here’s a quick info dump for you. I don’t have a chance to break this down to see how easy/hard it would be to match the homeless population with available units per state, and my definition of which of these unused homes are actually available for use at a given time may differ from the next person. But I was curious how reliable their numbers were and then to see if anyone had any takes on the data.

    Census.gov

    Census.gov

    Nearly 327,000 people in the United States experiencing homelessness lived in shelters… The sheltered population is an estimate of the population experiencing homelessness that stay in emergency and transitional shelters. It is not a complete count of the total U.S. population experiencing homelessness, which the Department of Housing and Urban Development (HUD) estimated was 582,500 in 2022.

    • huginn@feddit.it
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      1 month ago

      The only statistic that matters is sold not occupied and even that is only useful if it excludes houses that just haven’t been moved into yet.

      The majority of those figures are just showing that houses are unoccupied in resort towns because there’s nothing there half the year or that houses sit empty for a month while a new renter is sorted out or a new owner is moving in.

      We don’t need to shove the homeless into a remote resort town where they have no access to services - we need more housing in our cities where support networks can help those in need.

      The fact is that there arent enough houses to house every homeless person in the USA and maintain sufficient housing stock for people to move houses.

      Anything below a 5% vacancy rate is considered a housing shortage - it indicates there’s too much demand for housing and not enough supply.

      Very few American cities are sitting at or above 5% vacancy.

      • anon6789@lemmy.world
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        1 month ago

        Yup, your first 2 paragraphs are touched on in the link.

        Also agree on your other points. I wonder how many basic functioning towns we could build for what we spend assisting or harassing the homeless and the migrants… I feel it should be straightforward to get them integrated into the economy with an organized boost in resources made in a holistic approach.

        What we do with unhoused mentally ill or ones that are homeless by choice is well beyond what I’m qualified to discuss, but I imagine the bulk would welcome being helped constructively.

    • Fedizen@lemmy.world
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      1 month ago

      isnt like 20% the historic vacancy rate for the real estate market? What is the change here?

      • anon6789@lemmy.world
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        1 month ago

        Looks to be about 145 million homes.

        If 15 million are unoccupied, that’s a hair over 10 percent.

        The “Other” line of 4 million homes sounds like the ones that either aren’t in the process of being rented or sold and aren’t someone’s second home.

        What percentage of those homes are habitable in their current state is also something we don’t have info on.

    • shalafi@lemmy.world
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      1 month ago

      I wonder why the liberal states are clearly worse off. Also, our very poorest states (WV, LA, MS) seem best.

      EDIT: Classic lemmy. “Is that a criticism of liberals?! Not around here pal!” Just pointing out what the maps clearly shows and was wondering. Good explanation before, but I still have a question regarding the numbers.

      • anon6789@lemmy.world
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        1 month ago

        This is a case where correlation and causation are important.

        Grabbed this quick example from Coursera here:

        Causation indicates that one event causes another. Correlation only identifies that there is a relationship between two events or outcomes.

        If you were to collect data on the sale of ice cream cones and swimming pools throughout the year, you would likely find a strong positive correlation between the two as sales of both increase during the summer months. If you make the mistake of assuming correlation implies causation, you would incorrectly claim that an increase in ice cream cone sales causes people to buy swimming pools. However, this isn’t the case since you can attribute the increase in both to another variable—likely the warmer weather people experience during the summer. So although a correlation is present, you can’t support causation.

        In another correlation versus causation example, it may not be as easy to identify whether causation is present with two variables. For example, you could find a correlation between the amount someone exercises and their reported levels of happiness. While it’s possible an increase in exercise is causing an increase in happiness, you can’t say for sure that it’s the cause since there could be another unknown variable that has a more significant influence on a person’s mood.

        The homeless chart per state is of the number of people in shelters.

        Correlation could indicate the poor states have less homeless.

        Causation could indicate the reason they have less homeless in shelters is because the have no shelters.

        If you look at many of these poor states, you may find less shelter and services exist for the homeless, homeless is more punished by law, or other factors making it less likely for someone to stay there or to be counted as homeless there.

        This is why many say you can make a chart show anything you want it to, and you need to be critical when looking at people’s data.

        I hope this was helpful!

        • shalafi@lemmy.world
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          1 month ago

          Ah! Fewer shelters in poorer states makes sense. But I gathered that shelter info was used to extrapolate the total number of homeless.

          Also, the map would make one wonder why there are so many homeless in the colder states. That wouldn’t make sense.

          • anon6789@lemmy.world
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            1 month ago

            I didn’t pull the HUD data to dive too much into it. The link to the source I gave had this though for your second question:

            [One source of data was places] That provide temporary shelter during extremely cold weather (like churches). This category does not include shelters that operate only in the event of a natural disaster.

            They may also be unemployed seasonal labor, so they have work sometimes (agriculture, tourism, ranching, etc) but not enough year round income. Just guessing on that, I’m not much familiar with Montana and the Dakotas.

            Check out the full info at the links though. I’m a but sleep deprived to do much in depth analysis on this today. 😔