@sadbusdriver.bsky.social

San Francisco, CA
Joined July 2012
Pi day comes once a year, but you’re always arbitrarily close to epsilon day
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Given how easy it is to estimate upward sloping demand curves that fit the data really well, I'm kind of surprised at the "AI will / can solve causal inference" takes. E.g., a regression of changes in home values on changes in supply gets an R2 of 0.88 and the wrong sign!
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not trying to dunk, but I think this is a thing people get tripped up on unless you think making hotels got cheaper (seems unlikely, but I genuinely don't know), the new hotels are responding to a shift in the *demand* curve and so supply should correlate positively with/ prices
NYC’s hotel inventory increased 73% between 2007-2021. Demand is (presumably) inelastic. A big reason we can’t have a real conversation about prices is that every major chain - Hilton, Marriott, Wyndham, Hyatt, Omni, Choice Hotels, etc - is using the same price-setting software.
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even in a competitive market, if demand for NYC tourism went up a lot, supply would respond, but unless supply is perfectly elastic, prices should go up. of course, algo pricing + collusion can happen on top of this, but supply increased so must be collusion isn't correct
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adding on to this, if you think supply is generally pretty inelastic, and yet it still increased by 73% (if anyone has a source plz lmk), it had to be that the demand shock was absolutely massive
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another way to see this @besttrousers , is that if you plot the coverage rates for the commercial data vs household income, you'll see that the coverage is much better in rich neighborhoods than poor ones. This is a large part of why Zillow et al diverge from census
if you compare median rents in the census, median rents of people who were evicted, and asking rents for a commercially available rental data source, the eviction data track the census. partly cause of asking rents but more cause the commercial data miss ~30% of the rental market
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so you end up with two issues about which units show up 1) selection within neighborhoods 2) selection across neighborhoods 2) can be kind of fixed depending on how Zillow et al do their market medians, but a lot of these reports are just grabbing the median *in their data*
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A brief thread on pricing power in rental markets: Without discussing whether large landlords have actually bought up an appreciable amount of housing, why would changes in ownership affect prices in the first place? Turns out, it's more complicated than people think.
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And, as a last note, even if you think that there's a rental market cartel, either through realPage or large investors, the best remedy would be to get as much supply onto the market as possible
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For the large part though, the supply people should be concerned with are all the houses that haven’t been built bc of supply restrictions, financing constraints, etc. and much less on the homes that have been bought
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Once again begging people to think about what the “correct” ratio of vacant homes to homeless people is. As a good starting point, it should be much higher because we should have far more vacant homes and far fewer homeless people
Blackstone is now the largest corporate landlord on Earth with over 300,000 homes in the U.S. Billionaires and corporations have bought millions of homes and either raised rents or left them as empty investments. There are 16 million vacant houses—28 for every homeless person.
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Me watching fans of chapelle roan freak out over her both-sidesing the presidential candidates: You wouldn’t last a minute in the asylum I was raised in (pro wrestling fan)
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Crazy that you can basically see the effect of NYCs 1961 downzoning right in the time series
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Given that Vancouver has been running sub 2% rental vacancy rates for about 30 years now, I don’t think anyone can really say they’ve built enough housing
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Canada, I think, uses a different methodology for vacancy rates than the US (or they just have really low expectations) but even they recommend at least a 3% rental vacancy rate which Vancouver has never had in 34 years
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