Astral Codex Ten

Austin

77 min read

Austin

Article

Austin is a recurring place in the Astral Codex Ten archive, appearing 31 times across 31 issues between August 23, 2021 and April 01, 2026. The archive places it in contexts such as “AUSTIN, TX ( RSVP )”; “Aella (f / 29 / Austin)”; “Jason Crawford’s holding a Progress Studies conference in Austin March 4-6”. It most often appears alongside ACX, Boston, Berkeley.

Metadata

  • Category: Places
  • Mention count: 31
  • Issue count: 31
  • First seen: August 23, 2021
  • Last seen: April 01, 2026

Appears In

Source Context

Recovered passages from the original issue text. When the raw archive preserved outbound links inside the source passage, they are listed directly under the quote.

Meetups Everywhere 2021: Times And Places
August 23, 2021 · Original source
AUSTIN, TX (RSVP) Contact: Silas Barta, sbarta[at]gmail[dot]com Time: 1:30 PM, Saturday, October 2 Location: Tables in the park area by pond behind Central Market 4001 N. Lamar Coordinates: https://w3w.co/loosed.balloons.elastic
Inline links: RSVP, https://w3w.co/loosed.balloons.elastic
2022
January 28, 2022 · Original source
Aella (f / 29 / Austin) Alyssa (trans-f / 30 / SF) Damon (m / 34 / undetermined) Linch (m / 28 / SF) Nate (m / 30ish / Bay? Austin?) Rebecca (f / 30 / San Jose) Shaked (m / 30 / NYC)
Inline links: Aella, Alyssa, Damon, Linch, Nate, Rebecca, Shaked
Open Thread 209
January 31, 2022 · Original source
- Nectome hiring a lab assistant for brain preservation work - ML engineer looking for work in AI alignment (and other ML engineers: 1, 2, 3) - Rob Miles needs volunteer writers for his AI alignment explainer project - Steve Hsu’s Genomic Prediction needs coders and data scientists - Rachel was my wedding photographer and is very good, hire her for your photos - Jason Crawford’s holding a Progress Studies conference in Austin March 4-6. - Lots of cool people to date - Or if dating isn’t your style, how about a nice calculus textbook?
Inline links: hiring a lab assistant, looking for work in AI alignment, 1, 2, 3, needs volunteer writers, needs coders and data scientists, hire her for your photos, Progress Studies conference, people to date, calculus textbook
Austin Meetup Next Sunday
February 18, 2022 · Original source
I’ll be in Austin on Sunday, 2/27, and the meetup group there has kindly agreed to host me and anyone else who wants to show up.
Open Thread 212
February 21, 2022 · Original source
5: Sorry, Austin meetup location has unexpectedly changed to Moontower Cider Company, 1916 Tillery St, Austin, TX 78723. I’ll post this more prominently later this week, but I wanted to post it here too so people have more of a warning.
Austin Meetup Correction
February 25, 2022 · Original source
Austin meetup is still this Sunday, 2/27, 12-3.
Open Thread 213
February 28, 2022 · Original source
2: Thanks to everyone who attended to the Austin meetup today! As for the rest of you, probably I’ll see you at the next one, after you inevitably move to Austin like everyone else.
Spring Meetups In Seventy Cities
April 10, 2022 · Original source
AUSTIN, TX Contact: Silas Barta (sbarta@gmail.com) Date: June 4 Time: 12:00 PM Coordinates: https://plus.codes/862487GM+95 Location: Brewtorium, indoors, at the tables with signs. Address: 6015 Dillard Circle Suite A, Austin, TX, 78752
Inline links: https://plus.codes/862487GM+95
22
June 13, 2022 · Original source
4: This is crazy and over-optimistic, right?
Inline links: https://manifold.markets/Austin/will-manifold-ever-be-worth-1b
This is crazy and over-optimistic, right?
1: Andrew Eaddy and Clay Graubard gave a talk about prediction markets at big crypto conference Consensus in Austin earlier this month.
Inline links: gave a talk about prediction markets
LA and San Diego Meetups This Weekend
October 06, 2022 · Original source
Also coming up this weekend are meetups in Boise, Austin, Salt Lake City, Tokyo, Toulouse, Cologne, Rome, Hatten, Poznan, St. Louis, Rochester (NY), Seattle, Mumbai, and Oklahoma City. You can find times and places here.
Inline links: here
Open Thread 258
January 08, 2023 · Original source
7: People often ask me for psychiatrist/therapist recommendations. I don’t have any especially good ones, although a while back I got SSC readers to create this reference. But I notice there’s nobody in Austin on there and I have gotten an Austin-based request specifically. If anyone knows good psychiatrists, therapists, or couples counselors in Austin (or licensed to work in Texas), please let me know.
Inline links: this reference
Spring Meetups Everywhere 2023
April 10, 2023 · Original source
AUSTIN, TEXAS, USA Contact: Silas Barta Contact Info: sbarta[at]gmail[dot]com Time: Saturday, June 03rd, 12:00 PM Location: The Brewtorium, 6015 Dillard Cir A, Austin, TX 78752 Coordinates: https://plus.codes/862487GM+95 Event Link: https://www.lesswrong.com/events/HXxiXZ2xwDE9mK84L/austin-tx-acx-shelling-meetup-2023
Inline links: https://plus.codes/862487GM+95, https://www.lesswrong.com/events/HXxiXZ2xwDE9mK84L/austin-tx-acx-shelling-meetup-2023
Highlights From The Comments On Housing Density And Prices
May 10, 2023 · Original source
Makeshift housing in a North Dakota oil boom town (source) If each person creates half a job, the original 1,000 oilmen attract 500 service workers, those 500 attract another 250, and so on until population stabilizes at 2,000 people. In this model, if there are fewer than 2,000 houses in the town, demand exceeds supply (no matter what is going on in the rest of the country), but if there are more than 2,000, supply exceeds demand. So if we imagine Google’s presence as an oil-like resource, the extra demand for housing in the Bay should gradually decline: at some point, you will have finished housing the Google workers and the service workers who support them. But this isn’t right either, because Google isn’t a natural resource - it’s a company founded by Bay Area residents. If you got more Bay Area residents, you would (with some delay) get more Googles. Or: Austin gets lots of jobs from Tesla. Tesla wasn’t founded by Austinites. But it moved to Austin when it became a known “tech hub”, ie a place with lots of tech companies and tech employees. It wouldn’t have moved to Austin if Austin was still an uninhabited plain or a one-horse town. So as Austin got bigger, it attracted more tech companies. So in both the Bay Area case and the Austin case, having more people attracted more tech companies, either because the residents themselves found the company or because the company gets attracted to this newly bustling city. Potential counterargument: Each new Bay Area resident gives the Bay another lottery ticket to found the next Google. If having the first Google gets it an extra 1 million people, but there are 300 million people in the US, then those extra 1 million only give it a 1/300 chance of winning the next lottery. So even though the Bay Area won the lottery once, and this made it have high demand, this doesn’t mean the high demand will cause it to win more lotteries. If you win the lottery once, spend all your winnings on more lottery tickets, and keep doing this forever, you haven’t invented an infinite money printing machine, eventually you’ll just lose. Potential counter-counter-argument: the Bay got Google, and Facebook, and Apple, and . . . so these can’t all be separate lotteries. I think you should probably model it as a high-level lottery to become the next hub of a tech-sized industry, plus many low-level lotteries where once you’re the tech hub, you’re attracting lots of techies, and each techie gives you a ticket in a lottery where the denominator is the number of techies to found the next big tech company. And the Bay might have half the US’s techie population. So maybe here there is a self-sustaining lottery-winning cycle, at least until tech plays itself out and nobody wants any more tech companies. And that might take a long time. Tom (author of Tom Thought) writes: The primary drivers of demand for living in NYC are the specific opportunities available in NYC. It is true that on long time horizons, one of the reasons these opportunities have tended to collect in NYC is that it is a dense place. But those aren't the only reasons - NYC is much more important than other, bigger cities in other parts of the world for complex historical reasons. Even if a catastrophe were to wipe out half the city, there would still be a great deal of demand to live near important institutions like Broadway, Wall Street, Port of NY & NJ, Columbia, etc (assuming those institutions survived the catastrophe). Increasing the number of housing units has a very mechanical impact on how many people can live in the place. But it has only a second-order impact on the types of institutions that drive demand to live in the city. People don't just generically crave to live near other people for the most part (a handful of urbanist freaks like myself excepted). The Bay Area is a great example of this. It is much less populated than other much cheaper cities. Density isn't why people want to live there - it's access to a specific culture and specific institutions. Demand for that is not simply a function of density - some people want to be part of Bay Area culture and others don't. Adding more units will induce some demand as a second-order effect, but will bring prices down as a first-order effect. To relate this to your model: we might be able to say that the country has a certain number of abstract "culture points" that have been allocated to different cities by various historical forces. Each culture point a city has increases demand to live in that city by a certain amount. Adding more people to the city may allow it to generate additional culture points over time, or acquire culture points from other cities, but this doesn't happen right away, and is determined by a host of factors other than just density. Under this model, we expect a place like NYC to always cost much more than North Dakota (since NYC possesses a large number of culture points), but we would also expect that adding additional housing units to NYC would bring costs down (since there are now additional housing units per culture point). Perhaps this process will over time allow NYC to steal away some culture points from Chicago, Boston, or other cities, but this is a secondary effect. This just seems to be passing the buck. Yes, people move to New York because it has Broadway, Columbia University, and Wall Street. Why does it have those things? Because one in every X New York citizens founds a good artistic/educations/financial institution, and New York has a large population of employees to work at those institutions and customers to patronize those institutions. If Conanicut Island had a population of 10 million people instead of Manhattan, there would be lots of great institutions on Conanicut and it would have more culture points. I don’t think it’s a culture-point game and population/density just sort of occasionally redistributes culture points, I think to a first approximation culture points just track population/density. Maybe they track the population/density of upper class people better than the total population/density, but I don’t think this is a big enough distinction to sink the argument. 3. Comments About Chinese Ghost Cities Some people brought these up as a good natural experiment: the Chinese really did try building millions of houses on their equivalent of a North Dakota plain. What happened? Jeremiah Johnson (author of Infinite Scroll) writes: You currently seem like you're at the stage of understanding the thought experiments pretty well, but not understanding them on a DEEP level. For example with your hypothetical, this has actually happened before! Kind of. China built a bunch of 'ghost cities' basically out of nothing, and while there was an initial craze of speculation and tons of investment and building... nobody went to live in those cities most of the time. And now they're deeply distressed assets worth basically nothing. When nobody actually lives in the ghost city, it doesn't matter that they have super dense housing. There's no demand. (the only reason they might be worth something is that the CCP very, very much does not want to pop their huge housing bubble and is likely to bail out some of the parties involved) Parmenides (author of Last House On The Left) writes: I think your mixing up the agglomeration effects of density, which is what induces the demand, and the housing supply. You can't just build a city and expect people to move in, China has tried that. But if you have the agglomeration effects of density and shortage of housing due to artificial constraints, which we have all across the US, then you get dense areas with high housing costs. sdwr writes: Think of China's ghost cities / apartment blocks. Prices surely can't be that high there. Maybe the answer is that developers are good at their job, and build supply where theres demand for it? But several other people object that although the Western press made a big deal about Chinese ghost cities a few years ago, it mostly just took a couple of years for people to move in, and now at least some of them seem to be thriving. For example, Michael quotes the Wikipedia article, Under-occupied Developments In China: Reporting in 2018, Shepard noted that "Today, China’s so-called ghost cities that were so prevalently showcased in 2013 and 2014 are no longer global intrigues. They have filled up to the point of being functioning, normal cities". Ash Lael writes: I'm sceptical of the Chinese "ghost city" phenomenon. I haven't explored the issue rigorously but my impression is that in areas that were previously dismissed as "ghost cities" like Ordos Kangbashi, the population is now large and growing. I think we in the west are so used to infrastructure bottlenecks and short sightedness and anti-construction policies that the idea of it being possible to build the housing and infrastructure to accomodate expected demand ten years in the future is completely foreign to us. Perhaps building brand new cities before they are even needed is what the YIMBY utopia looks like. See also Bloomberg: China’s Ghost Cities Are Finally Stirring To Life After Years Of Empty Streets. This wasn’t trivial. It looks like the Chinese government had to put in some work to make people move in, including opening good schools and universities there. Probably if they had just built apartments in the middle of the desert and nothing else, they would have stayed empty. But that’s even more of a reductio ad absurdum than the original ghost city plan. Kangbashi, China’s most famous ghost city. What are housing prices like in the ghost city? Again from Bloomberg: Sitting on the southern outskirts of Inner Mongolia’s Ordos City (population 2.2 million), Kangbashi was the archetypal ghost city 10 years ago, with barren boulevards and empty buildings standing forlornly in the desert. Local officials are adamant that things have changed. They say 91% of homes in the district are occupied. In fact, after a yearslong construction freeze, the government approved six housing projects in 2020 and expects 3,000 homes to be built by the end of this year. Apartments in a new development are selling for 9,500 yuan per square meter, and downtown they go for 15,000 to 16,000 yuan, according to Liu Yueyue, 28, a salesman at a new residential development in the district’s northeast. “Would houses in a ghost town sell at such high prices?” asks Liu. Half of his customers come from outside Kangbashi, and most are parents who want to send their children to the well-regarded local schools, he says. Looking at this list of real estate prices across Chinese cities, Kangbashi seems squarely in the middle - for example, Wuhan and Xian are also in the 15,000 - 16,000 range. I claim this supports my argument: surely twenty years ago, houses in this particular deserted corner of Inner Mongolia would have been dirt cheap (if any even existed). But if you build a city there, it becomes just as expensive as any other city! Here it’s very obvious that the density caused the high prices instead of the other way around. Still, the Chinese housing market is weird, with significant vacancies even in expensive, well-developed cities. Paul Botts: No official vacancy rates are published in China and no specific definition of it exists there. Various think tanks and researchers both within that country and elsewhere have published estimates ranging from as low as 11 percent to as high as 24 percent. Those estimates have been for varying samples of Chinese cities, have used various definitions of housing vacancy rate, etc. The best (as in most systematic) estimate yet produced has come from researchers at a university in Liaoning. They used night-time urban lightsheds captured by a new (2018 launch) Chinese satellite having a new level of light sensing technology which allows separating out light from parks and plazas. They covered a large sample (49 cities), and made their sample representative of city type, city size, regions within China, etc. They also crossed-referenced with local housing data to ensure accurate balancing of their sample and to confirm that the satellite was successfully identifying light coming from housing blocks. They found vacancy rates of just under 20 percent in China's Tier 1 cities, and found rates above 20 percent in 40 of the 49 cities. They found the highest vacancy rates in western and northeastern cities, which are also the newest ones; that finding is consistent with the hypothesis of significant numbers of recently-built ghost cities. https://www.researchgate.net/publication/345092218_Housing_Vacancy_Rate_in_Major_Cities_in_China_Perspectives_from_Nighttime_Light_Data And Phil H (author of the blog Tang Poetry) writes: The price of housing in China has skyrocketed over the past few decades, as all those extra apartments have been built. I live in a pleasant but unremarkable southern city, and I paid London prices (about 4.5m yuan/$650k for a 1,300 sq ft flat). That seems to match Scott's hypothesis that high density leads to high prices. House prices here have risen much faster than incomes. They've risen in rural areas, too, but the increases in price in cities have been stratospheric. 4. Comments Accusing Me Of Not Considering Tokyo, Even Though I Included A Section In The Post On Why I Didn’t Think Tokyo Was Relevant I won’t name and shame people, but for example: You excluded Tokyo from your dataset. Tokyo has much higher density than SF and much lower price per sqft. Tokyo just kills this. Tokyo is bigger than New York and has significantly lower rent because they build more housing! This is in a wealthy country with even lower interest rates than the US. I don't think you have justified excluding non-US metros, like Tokyo, or Auckland. Doesn't this lead to the natural conclusion that there is a sufficient level of housing to build, and that the problem is that the USA's many metros are structured to prevent housing? It seems like you're just arguing that US metros are bad at building housing, which is also what Matt Yglesias is arguing. "Change my mind about housing, but don't mention Tokyo" is like saying "Change my mind about gun possession, but don't mention Switzerland." You can't test the effect of allowing new housing unless you're willing to look at cities that do, in fact, allow it. Tokyo and NYC both attract tons of new residents But Tokyo's housing rents have been stable, while NYC rents keep rising. Why? Tokyo has permissive housing construction laws. NYC makes building new housing almost illegal. Yes, dense cities are attractive, and that makes them get more dense over time. But it only makes them more expensive if you forbid new housing to keep up with the new residents. Tokyo! But I’m like the 10th person to bring it up… As I wrote on the original post (not even edited in! it’s been there the whole time!): I worry someone will bring up Tokyo as a counterexample. But I think Tokyo managed to build its way to low housing prices in the context of the rest of Japan also having good housing policy. Even if that isn’t true, Tokyo on its own is a quarter of the Japanese market, so it might be able to exhaust the entire pool of Japanese house-seekers by itself! That is, yes, you’re all correct that cities are only expensive in the context of more demand for city housing than the (NIMBY-constrained) city housing market can currently supply. You are all correct that if this problem were solved at the national level, then city housing would be cheap, and every additional city house would make it cheaper. My claim is that marginal changes - like Oakland building an extra 10,000 units, but everyone else staying the same - will most likely increase Oakland prices. Yes, if Oakland unilaterally built 50 million units, that would soak up the entire excess demand and probably lower prices everywhere (including Oakland). Yes, if the entire US switched to good housing policy at the same time, that would probably lower prices everywhere (including Oakland). But if we don’t do any of that stuff, and just build another 10,000 houses in Oakland, I think it would probably increase prices in Oakland. Some other people brought up that Japan has a declining population, and it’s much easier to have low house prices when your population is declining (compared to some previous time when number of houses presumably matched number of people), but ddd pointed out that people continue to migrate from the Japanese countryside to Tokyo, so its population continues to increase. Also, Mike (I’m stitching together two comments here): In a country with a declining population, you would expect that fewer homes are being built per capita because there's little to no competition for existing homes. But it's exactly the opposite! Japan builds far more homes per capita than the US does, despite their declining population […] As a result, the average Japanese home is very new and the average house is torn down and replaced after a relatively short 30 years. They're living in nice new homes for cheaper. 5. Comments Accusing Me Of Not Understanding Economics Maximum Limelihood Estimator writes: I think you're making a very common mistake here of confusing supply/demand with *quantity* supplied or quantity demanded. (This is very common! we teach students about this in micro 101 because it's so easy to make!) What you're seeing is that the quantity supplied is correlated with housing prices (true!). But this is very different from establishing that the supply curve--i.e. the amount of housing that would be produced at any given price, and what moves up/down when we regulate/deregulate supply--is positively correlated with price. Figuring out what supply curves look like is a lot less intuitive and requires some high-grade econometrics, which is why economists had to set up a whole commission just to study this particular problem (the Cowles Commission). In terms of resources for understanding how these concepts are different, a micro 101 textbook will cover this distinction. For the econometrics side of this, I've heard good things about Scott Cunningham's *Causal Inference Mixtape*, although I haven't personally used it. My claim is that increasing density within a city shifts the demand curve for housing within that city, because of increasing desirability. MLE later gets more on point: The effect you're discussing here is kind of real in a sense. When the marginal utility of housing increases for *other* people, density arguably becomes more desirable for me, which is kind of like the demand curve shifting up. These are called bandwagon goods and discussed here: http://econfac.bsu.edu/research/workingpapers/bsuecwp200804gisser.pdf In theory, the bandwagon effect could be so strong that parts of the demand curve are upward-sloping. Solutions like this are not, technically, prohibited by the laws of mathematics, just the laws of economics. (And arguably of physics--see paper for conditions where these kinds of bandwagon effects imply the amount of housing in the city would have to be negative). In practice, this effect exists but just can't overcome the normal, non-weird economics that says "making more of a good makes the prices fall." Again, I claim the existence of Manhattan vs. Conanicut shows that sometimes it does. I cannot find the words “housing”, “real estate”, or “land value” anywhere in that paper. Alex Poterack writes: There's two things going on here: confusing shifts in demand with movement along the demand curve, and getting causation backwards. You're assuming density causes prosperity, rather than prosperity causing density. There are ways the former can happen, but the bigger thing is that, for a wide range of historical reasons, you can make a lot of money in NYC and SF, so lots of people want to live there, so they get very dense. This is the prosperity shifting demand right, so at any given price, more people want to live there; this drives prices up, and they go higher the more fixed supply is. If you built a bunch of housing in Oakland, lots of people would move there because it's cheaper, which is movement along the demand curve; it's still the same number of people who want to live there at any price. Now, it's possible that the increased number of people living there makes the city more prosperous (this is the phenomenon of induced demand), which would shift demand right, but there are way more differences between NYC/SF and Oakland than just the density, so I don't think it would shift demand enough to offset this. In particular, if it's just a small increase in small, it's also a small increase in density, so there's almost no shift in demand (but there is movement along the curve). I still think this is missing my point, but I present it here in case anyone else is enlightened by it and wants to try further to convince me I’m making this mistake. 6. Comments By Famous People Who Potentially Have Good Opinions Scott Sumner is an economist and blogger; he writes: It is certainly the case that building more housing can make a city more desirable, and that this effect could be so strong that it overwhelms the price depressing impact of a greater quantity supplied. But studies suggest that this is not generally the case. Texas provides a nice case study. Among Texas’s big metro areas, Austin has the tightest restrictions on building and Houston is the most willing to allow dense infill development. Even though Houston is the larger city, house prices are far higher in Austin: Houston pretty much describes the “Oakland with more housing” outcome that Alexander views as somewhat far-fetched. Only in this case, it’s Austin with more housing. Alexander seems too quick to accept the, “If you build it they will come” idea—that you can build more housing and thereby boost demand so much that prices actually rise. I started the post with a graph of about 50 cities, showing a positive correlation between density and price. I’m having trouble seeing how Sumner’s point isn’t just “if you remove 48 of those cities and cherry-pick two, the relationship is negative”. My attempt to place Austin and Houston on the original graph, using Sumner’s data plus a few other things available online. Why weren’t they on there already? Maybe because the graph is metro areas and Sumner was talking about Austin and Houston as cities, but I’m not sure and agree this is confusing. Everyone knows Austin is more expensive than Houston because Austin is a trendy tech and culture hub and Houston isn’t (and relatedly, because Austin’s median family income is 50% higher than Houston’s). Unless someone wants to claim that its failure to build housing helped turn it into a trendy tech and culture hub, I don’t think there’s much point to this comparison. It’s true that Houston’s bigger size didn’t let it leapfrog over Austin to become a trendy tech and culture hub, which goes against some of what I claimed in the first part of this post. But I never claimed there would be a perfect 1-1 correlation between city size and trendiness, or that you could never find a pair of cities where one was bigger but the other was more trendy. Just that there would be a correlation. Moving on: Here’s the problem with this argument. It mixes up population change due to economic effects such as the benefits of agglomeration, with population changes due to regulatory changes such as less strict zoning. If you look at things this way, then the stylized facts work against Alexander’s argument. Over the past 50 years, increasingly strict zoning has reduced housing construction on big cities like New York and San Francisco. As a result, their populations have increased by less than in cities with less strict zoning, such as Houston. If Alexander were correct, then the price gap between the tightly controlled cities on the coast and the more laissez-faire cities of Middle America should have shrunk over time. Instead, the price gap has widened. New York and San Francisco were always more expensive than other cites, but with tighter zoning and less new construction the gap has become far wider. During the last fifty years, there was also deindustrialization and demographic sorting. This is just the Austin vs. Houston story all over again. Alexander is implicitly viewing this outcome as a “problem” for the city that builds more housing. They must sacrifice so that the rest of the country can gain. But in his scenario, Oakland is better off. Indeed if it were not better off, then why would more people choose to live in Oakland? In order for it to be true that building more housing boosts housing prices, it must also be true that the quality of existing houses (including neighborhood effects) rises by more than enough to offset the increase in supply. That means the new housing construction must make Oakland such a desirable place to live that the amenity effect overwhelms the quantity effect [...] Of course, economic change always has winners and losers. Here’s how I would describe the impact of allowing more housing construction in Oakland, in the unlikely event that this did raise housing prices: 1. America would benefit. 2. Oakland would benefit. 3. Poor people in America would benefit, in aggregate. 4. Affluent people in America would benefit, in aggregate. 5. Homeowners in Oakland would benefit. 6. Some renters in Oakland would benefit (from a more economically dynamic city.) 7. Some renters in Oakland would suffer from higher rents. In the much more likely case where new housing construction would lower prices, the impact described in #5 and #7 might reverse. Either way, there is no defensible argument for not building more housing in Oakland, regardless of the impact on price. If building more housing reduces its price, then there is a strong argument for allowing more housing construction. If building more housing raises its price, then the argument for more construction is even stronger. I agree with all this. Jeremiah Johnson is a co-founder of the Center for New Liberalism, host of the Neoliberal Podcast, and a YIMBY activist (not to be confused with Jeremiah “Liver-Eating” Johnson, who killed 300 Native Americans and ate their livers). He writes: Here's why you're wrong in a single sentence: Demand causes high prices, not new units. Prices are high in SF and NYC because those are desirable places to live for a huge number of people. People all over the country and the world would live there if they could, and prices reflect that. The fact that the densest cities are the most expensive is true. But the high prices are not caused by density - rather, the density and the high prices are both a consequence of crushingly high demand […] There's a feedback loop, but what matters here is the elasticity, which is less than one. We can measure this empirically. New housing lowers prices via the mechanism of adding supply, which is basic economics and how we expect markets to work. New housing could raise prices if it also made the city a more desirable place to live and shifted people's preferences, such that there was more demand to live there after the new housing is built. If you think it's unclear which of these effects would dominate, luckily we have empirical data that over and over and over shows adding housing supply does indeed lower prices on a local level. This is a fairly well established result that replicates well. edit: I'm actually thinking about drawing out the weighted DAG graphs here to make the conceptual stuff easier, but it would be pretty long. I'd love to do this as a guest post. I’m skeptical of the empirical results because they don’t match the much stronger “Manhattan vs. Conanicut island” empirical results, and if I try to think about why, the best explanation I can think of is that the Manhattan experiment has been going on longer (ie long enough for Manhattan’s extra residents to found businesses and institutions that attract new people). I’ve told him he can try pitching this guest post to me; in either case, I would be interested in seeing the graphs. Several other people also posted this graph that Johnson helped make famous: Hopefully by now you can predict my objection: the places in the southeast corner are mostly unfashionable red state Sun Belt cities; the places in the northwest corner are mostly trendy liberal coastal cities. My conclusion is that trendy liberal coastal cities are both more NIMBY and more desirable, and if you use this to draw any conclusions about housing policy you’ll just end up confused. But maybe I should take this same lesson to heart myself. Dense cities are mostly trendy liberal coastal cities; uninhabited tundra in North Dakota isn’t. Maybe the demand is just for trendy liberal coastal cities, and once you attain that status, extra density doesn’t matter that much. Maybe Oakland has already maxed out its “trendy liberal coastal city” status, and even if it became Manhattan-sized, it wouldn’t get any trendier, or would get trendier only with a long time lag. There are a few very trendy small coastal villages in California (think eg Sea Ranch); maybe these (rather than North Dakota) are the natural control group for San Francisco. I think they are still cheaper than SF, but maybe not by very much. Cameron Murray is a housing economist whose work some other commenters recommended; he also writes the blog Fresh Economic Thinking. He very kindly showed up and wrote: I think you are in general right that agglomeration effects are real, which is why bigger cities have higher value to residents. I agree that people move locations. But I think you can go a step further. If one city is growing faster and densifying, surely those people are not demanding homes in other cities and those cities build slower. This is part of the spatial equilibrium story that further makes claims about “build density and get cheap homes” less plausible. 7. My Final Thoughts + Poll Thanks to everyone who commented on this post and helped me refine my thoughts. I’m willing to concede the following points: It might be that only attracting the sort of educated people who found companies, universities, etc will make housing prices go up. Less educated people will take more jobs than they create and not ratchet up the city’s desirability level. (I’d previously told commenters talking about “gentrification” that it was irrelevant to the mechanism I was talking about here, but maybe it isn’t - maybe “gentrifiers” are the people creating more jobs and institutions than they consume, and so homes that attract them in particular will increase demand more than they increase supply? Maybe this discussion does reduce to the gentrification discussion?)
Inline links: source, Tom Thought, https://substackcdn.com/image/fetch/$s_!86gT!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F5788a8dd-c5ee-4111-be67-9c1533f7410b_335x172.png, Infinite Scroll, writes, Last House On The Left, writes, writes, quotes, Under-occupied Developments In China, writes, China’s Ghost Cities Are Finally Stirring To Life After Years Of Empty Streets., https://substackcdn.com/image/fetch/$s_!AAuI!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F5d6a6159-a16f-45e3-b15a-e62cb2c73336_1200x900.jpeg, this list of real estate prices across Chinese cities, Paul Botts, https://www.researchgate.net/publication/345092218_Housing_Vacancy_Rate_in_Major_Cities_in_China_Perspectives_from_Nighttime_Light_Data, Tang Poetry, writes, ddd pointed out, Mike, Maximum Limelihood Estimator, gets more on point, http://econfac.bsu.edu/research/workingpapers/bsuecwp200804gisser.pdf, writes, writes:, far higher in Austin, https://substackcdn.com/image/fetch/$s_!tAF8!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F03f2b338-da84-4d85-b71c-0ce2e02e10e1_685x559.png, https://substackcdn.com/image/fetch/$s_!mLwn!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F9cf942da-5716-49e8-a177-20140681e7fc_573x421.png, Center for New Liberalism, the Neoliberal Podcast, Jeremiah “Liver-Eating” Johnson, Johnson helped make famous, https://substackcdn.com/image/fetch/$s_!tg5t!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fc490a60a-3e97-4b73-9806-79bb967b5172_608x550.png, Sea Ranch, some other commenters, Fresh Economic Thinking, wrote
Kangbashi, China’s most famous ghost city. What are housing prices like in the ghost city? Again from Bloomberg: Sitting on the southern outskirts of Inner Mongolia’s Ordos City (population 2.2 million), Kangbashi was the archetypal ghost city 10 years ago, with barren boulevards and empty buildings standing forlornly in the desert. Local officials are adamant that things have changed. They say 91% of homes in the district are occupied. In fact, after a yearslong construction freeze, the government approved six housing projects in 2020 and expects 3,000 homes to be built by the end of this year. Apartments in a new development are selling for 9,500 yuan per square meter, and downtown they go for 15,000 to 16,000 yuan, according to Liu Yueyue, 28, a salesman at a new residential development in the district’s northeast. “Would houses in a ghost town sell at such high prices?” asks Liu. Half of his customers come from outside Kangbashi, and most are parents who want to send their children to the well-regarded local schools, he says. Looking at this list of real estate prices across Chinese cities, Kangbashi seems squarely in the middle - for example, Wuhan and Xian are also in the 15,000 - 16,000 range. I claim this supports my argument: surely twenty years ago, houses in this particular deserted corner of Inner Mongolia would have been dirt cheap (if any even existed). But if you build a city there, it becomes just as expensive as any other city! Here it’s very obvious that the density caused the high prices instead of the other way around. Still, the Chinese housing market is weird, with significant vacancies even in expensive, well-developed cities. Paul Botts: No official vacancy rates are published in China and no specific definition of it exists there. Various think tanks and researchers both within that country and elsewhere have published estimates ranging from as low as 11 percent to as high as 24 percent. Those estimates have been for varying samples of Chinese cities, have used various definitions of housing vacancy rate, etc. The best (as in most systematic) estimate yet produced has come from researchers at a university in Liaoning. They used night-time urban lightsheds captured by a new (2018 launch) Chinese satellite having a new level of light sensing technology which allows separating out light from parks and plazas. They covered a large sample (49 cities), and made their sample representative of city type, city size, regions within China, etc. They also crossed-referenced with local housing data to ensure accurate balancing of their sample and to confirm that the satellite was successfully identifying light coming from housing blocks. They found vacancy rates of just under 20 percent in China's Tier 1 cities, and found rates above 20 percent in 40 of the 49 cities. They found the highest vacancy rates in western and northeastern cities, which are also the newest ones; that finding is consistent with the hypothesis of significant numbers of recently-built ghost cities. https://www.researchgate.net/publication/345092218_Housing_Vacancy_Rate_in_Major_Cities_in_China_Perspectives_from_Nighttime_Light_Data And Phil H (author of the blog Tang Poetry) writes: The price of housing in China has skyrocketed over the past few decades, as all those extra apartments have been built. I live in a pleasant but unremarkable southern city, and I paid London prices (about 4.5m yuan/$650k for a 1,300 sq ft flat). That seems to match Scott's hypothesis that high density leads to high prices. House prices here have risen much faster than incomes. They've risen in rural areas, too, but the increases in price in cities have been stratospheric. 4. Comments Accusing Me Of Not Considering Tokyo, Even Though I Included A Section In The Post On Why I Didn’t Think Tokyo Was Relevant I won’t name and shame people, but for example: You excluded Tokyo from your dataset. Tokyo has much higher density than SF and much lower price per sqft. Tokyo just kills this. Tokyo is bigger than New York and has significantly lower rent because they build more housing! This is in a wealthy country with even lower interest rates than the US. I don't think you have justified excluding non-US metros, like Tokyo, or Auckland. Doesn't this lead to the natural conclusion that there is a sufficient level of housing to build, and that the problem is that the USA's many metros are structured to prevent housing? It seems like you're just arguing that US metros are bad at building housing, which is also what Matt Yglesias is arguing. "Change my mind about housing, but don't mention Tokyo" is like saying "Change my mind about gun possession, but don't mention Switzerland." You can't test the effect of allowing new housing unless you're willing to look at cities that do, in fact, allow it. Tokyo and NYC both attract tons of new residents But Tokyo's housing rents have been stable, while NYC rents keep rising. Why? Tokyo has permissive housing construction laws. NYC makes building new housing almost illegal. Yes, dense cities are attractive, and that makes them get more dense over time. But it only makes them more expensive if you forbid new housing to keep up with the new residents. Tokyo! But I’m like the 10th person to bring it up… As I wrote on the original post (not even edited in! it’s been there the whole time!): I worry someone will bring up Tokyo as a counterexample. But I think Tokyo managed to build its way to low housing prices in the context of the rest of Japan also having good housing policy. Even if that isn’t true, Tokyo on its own is a quarter of the Japanese market, so it might be able to exhaust the entire pool of Japanese house-seekers by itself! That is, yes, you’re all correct that cities are only expensive in the context of more demand for city housing than the (NIMBY-constrained) city housing market can currently supply. You are all correct that if this problem were solved at the national level, then city housing would be cheap, and every additional city house would make it cheaper. My claim is that marginal changes - like Oakland building an extra 10,000 units, but everyone else staying the same - will most likely increase Oakland prices. Yes, if Oakland unilaterally built 50 million units, that would soak up the entire excess demand and probably lower prices everywhere (including Oakland). Yes, if the entire US switched to good housing policy at the same time, that would probably lower prices everywhere (including Oakland). But if we don’t do any of that stuff, and just build another 10,000 houses in Oakland, I think it would probably increase prices in Oakland. Some other people brought up that Japan has a declining population, and it’s much easier to have low house prices when your population is declining (compared to some previous time when number of houses presumably matched number of people), but ddd pointed out that people continue to migrate from the Japanese countryside to Tokyo, so its population continues to increase. Also, Mike (I’m stitching together two comments here): In a country with a declining population, you would expect that fewer homes are being built per capita because there's little to no competition for existing homes. But it's exactly the opposite! Japan builds far more homes per capita than the US does, despite their declining population […] As a result, the average Japanese home is very new and the average house is torn down and replaced after a relatively short 30 years. They're living in nice new homes for cheaper. 5. Comments Accusing Me Of Not Understanding Economics Maximum Limelihood Estimator writes: I think you're making a very common mistake here of confusing supply/demand with *quantity* supplied or quantity demanded. (This is very common! we teach students about this in micro 101 because it's so easy to make!) What you're seeing is that the quantity supplied is correlated with housing prices (true!). But this is very different from establishing that the supply curve--i.e. the amount of housing that would be produced at any given price, and what moves up/down when we regulate/deregulate supply--is positively correlated with price. Figuring out what supply curves look like is a lot less intuitive and requires some high-grade econometrics, which is why economists had to set up a whole commission just to study this particular problem (the Cowles Commission). In terms of resources for understanding how these concepts are different, a micro 101 textbook will cover this distinction. For the econometrics side of this, I've heard good things about Scott Cunningham's *Causal Inference Mixtape*, although I haven't personally used it. My claim is that increasing density within a city shifts the demand curve for housing within that city, because of increasing desirability. MLE later gets more on point: The effect you're discussing here is kind of real in a sense. When the marginal utility of housing increases for *other* people, density arguably becomes more desirable for me, which is kind of like the demand curve shifting up. These are called bandwagon goods and discussed here: http://econfac.bsu.edu/research/workingpapers/bsuecwp200804gisser.pdf In theory, the bandwagon effect could be so strong that parts of the demand curve are upward-sloping. Solutions like this are not, technically, prohibited by the laws of mathematics, just the laws of economics. (And arguably of physics--see paper for conditions where these kinds of bandwagon effects imply the amount of housing in the city would have to be negative). In practice, this effect exists but just can't overcome the normal, non-weird economics that says "making more of a good makes the prices fall." Again, I claim the existence of Manhattan vs. Conanicut shows that sometimes it does. I cannot find the words “housing”, “real estate”, or “land value” anywhere in that paper. Alex Poterack writes: There's two things going on here: confusing shifts in demand with movement along the demand curve, and getting causation backwards. You're assuming density causes prosperity, rather than prosperity causing density. There are ways the former can happen, but the bigger thing is that, for a wide range of historical reasons, you can make a lot of money in NYC and SF, so lots of people want to live there, so they get very dense. This is the prosperity shifting demand right, so at any given price, more people want to live there; this drives prices up, and they go higher the more fixed supply is. If you built a bunch of housing in Oakland, lots of people would move there because it's cheaper, which is movement along the demand curve; it's still the same number of people who want to live there at any price. Now, it's possible that the increased number of people living there makes the city more prosperous (this is the phenomenon of induced demand), which would shift demand right, but there are way more differences between NYC/SF and Oakland than just the density, so I don't think it would shift demand enough to offset this. In particular, if it's just a small increase in small, it's also a small increase in density, so there's almost no shift in demand (but there is movement along the curve). I still think this is missing my point, but I present it here in case anyone else is enlightened by it and wants to try further to convince me I’m making this mistake. 6. Comments By Famous People Who Potentially Have Good Opinions Scott Sumner is an economist and blogger; he writes: It is certainly the case that building more housing can make a city more desirable, and that this effect could be so strong that it overwhelms the price depressing impact of a greater quantity supplied. But studies suggest that this is not generally the case. Texas provides a nice case study. Among Texas’s big metro areas, Austin has the tightest restrictions on building and Houston is the most willing to allow dense infill development. Even though Houston is the larger city, house prices are far higher in Austin: Houston pretty much describes the “Oakland with more housing” outcome that Alexander views as somewhat far-fetched. Only in this case, it’s Austin with more housing. Alexander seems too quick to accept the, “If you build it they will come” idea—that you can build more housing and thereby boost demand so much that prices actually rise. I started the post with a graph of about 50 cities, showing a positive correlation between density and price. I’m having trouble seeing how Sumner’s point isn’t just “if you remove 48 of those cities and cherry-pick two, the relationship is negative”. My attempt to place Austin and Houston on the original graph, using Sumner’s data plus a few other things available online. Why weren’t they on there already? Maybe because the graph is metro areas and Sumner was talking about Austin and Houston as cities, but I’m not sure and agree this is confusing. Everyone knows Austin is more expensive than Houston because Austin is a trendy tech and culture hub and Houston isn’t (and relatedly, because Austin’s median family income is 50% higher than Houston’s). Unless someone wants to claim that its failure to build housing helped turn it into a trendy tech and culture hub, I don’t think there’s much point to this comparison. It’s true that Houston’s bigger size didn’t let it leapfrog over Austin to become a trendy tech and culture hub, which goes against some of what I claimed in the first part of this post. But I never claimed there would be a perfect 1-1 correlation between city size and trendiness, or that you could never find a pair of cities where one was bigger but the other was more trendy. Just that there would be a correlation. Moving on: Here’s the problem with this argument. It mixes up population change due to economic effects such as the benefits of agglomeration, with population changes due to regulatory changes such as less strict zoning. If you look at things this way, then the stylized facts work against Alexander’s argument. Over the past 50 years, increasingly strict zoning has reduced housing construction on big cities like New York and San Francisco. As a result, their populations have increased by less than in cities with less strict zoning, such as Houston. If Alexander were correct, then the price gap between the tightly controlled cities on the coast and the more laissez-faire cities of Middle America should have shrunk over time. Instead, the price gap has widened. New York and San Francisco were always more expensive than other cites, but with tighter zoning and less new construction the gap has become far wider. During the last fifty years, there was also deindustrialization and demographic sorting. This is just the Austin vs. Houston story all over again. Alexander is implicitly viewing this outcome as a “problem” for the city that builds more housing. They must sacrifice so that the rest of the country can gain. But in his scenario, Oakland is better off. Indeed if it were not better off, then why would more people choose to live in Oakland? In order for it to be true that building more housing boosts housing prices, it must also be true that the quality of existing houses (including neighborhood effects) rises by more than enough to offset the increase in supply. That means the new housing construction must make Oakland such a desirable place to live that the amenity effect overwhelms the quantity effect [...] Of course, economic change always has winners and losers. Here’s how I would describe the impact of allowing more housing construction in Oakland, in the unlikely event that this did raise housing prices: 1. America would benefit. 2. Oakland would benefit. 3. Poor people in America would benefit, in aggregate. 4. Affluent people in America would benefit, in aggregate. 5. Homeowners in Oakland would benefit. 6. Some renters in Oakland would benefit (from a more economically dynamic city.) 7. Some renters in Oakland would suffer from higher rents. In the much more likely case where new housing construction would lower prices, the impact described in #5 and #7 might reverse. Either way, there is no defensible argument for not building more housing in Oakland, regardless of the impact on price. If building more housing reduces its price, then there is a strong argument for allowing more housing construction. If building more housing raises its price, then the argument for more construction is even stronger. I agree with all this. Jeremiah Johnson is a co-founder of the Center for New Liberalism, host of the Neoliberal Podcast, and a YIMBY activist (not to be confused with Jeremiah “Liver-Eating” Johnson, who killed 300 Native Americans and ate their livers). He writes: Here's why you're wrong in a single sentence: Demand causes high prices, not new units. Prices are high in SF and NYC because those are desirable places to live for a huge number of people. People all over the country and the world would live there if they could, and prices reflect that. The fact that the densest cities are the most expensive is true. But the high prices are not caused by density - rather, the density and the high prices are both a consequence of crushingly high demand […] There's a feedback loop, but what matters here is the elasticity, which is less than one. We can measure this empirically. New housing lowers prices via the mechanism of adding supply, which is basic economics and how we expect markets to work. New housing could raise prices if it also made the city a more desirable place to live and shifted people's preferences, such that there was more demand to live there after the new housing is built. If you think it's unclear which of these effects would dominate, luckily we have empirical data that over and over and over shows adding housing supply does indeed lower prices on a local level. This is a fairly well established result that replicates well. edit: I'm actually thinking about drawing out the weighted DAG graphs here to make the conceptual stuff easier, but it would be pretty long. I'd love to do this as a guest post. I’m skeptical of the empirical results because they don’t match the much stronger “Manhattan vs. Conanicut island” empirical results, and if I try to think about why, the best explanation I can think of is that the Manhattan experiment has been going on longer (ie long enough for Manhattan’s extra residents to found businesses and institutions that attract new people). I’ve told him he can try pitching this guest post to me; in either case, I would be interested in seeing the graphs. Several other people also posted this graph that Johnson helped make famous: Hopefully by now you can predict my objection: the places in the southeast corner are mostly unfashionable red state Sun Belt cities; the places in the northwest corner are mostly trendy liberal coastal cities. My conclusion is that trendy liberal coastal cities are both more NIMBY and more desirable, and if you use this to draw any conclusions about housing policy you’ll just end up confused. But maybe I should take this same lesson to heart myself. Dense cities are mostly trendy liberal coastal cities; uninhabited tundra in North Dakota isn’t. Maybe the demand is just for trendy liberal coastal cities, and once you attain that status, extra density doesn’t matter that much. Maybe Oakland has already maxed out its “trendy liberal coastal city” status, and even if it became Manhattan-sized, it wouldn’t get any trendier, or would get trendier only with a long time lag. There are a few very trendy small coastal villages in California (think eg Sea Ranch); maybe these (rather than North Dakota) are the natural control group for San Francisco. I think they are still cheaper than SF, but maybe not by very much. Cameron Murray is a housing economist whose work some other commenters recommended; he also writes the blog Fresh Economic Thinking. He very kindly showed up and wrote: I think you are in general right that agglomeration effects are real, which is why bigger cities have higher value to residents. I agree that people move locations. But I think you can go a step further. If one city is growing faster and densifying, surely those people are not demanding homes in other cities and those cities build slower. This is part of the spatial equilibrium story that further makes claims about “build density and get cheap homes” less plausible. 7. My Final Thoughts + Poll Thanks to everyone who commented on this post and helped me refine my thoughts. I’m willing to concede the following points: It might be that only attracting the sort of educated people who found companies, universities, etc will make housing prices go up. Less educated people will take more jobs than they create and not ratchet up the city’s desirability level. (I’d previously told commenters talking about “gentrification” that it was irrelevant to the mechanism I was talking about here, but maybe it isn’t - maybe “gentrifiers” are the people creating more jobs and institutions than they consume, and so homes that attract them in particular will increase demand more than they increase supply? Maybe this discussion does reduce to the gentrification discussion?)
Inline links: this list of real estate prices across Chinese cities, Paul Botts, https://www.researchgate.net/publication/345092218_Housing_Vacancy_Rate_in_Major_Cities_in_China_Perspectives_from_Nighttime_Light_Data, Tang Poetry, writes, ddd pointed out, Mike, Maximum Limelihood Estimator, gets more on point, http://econfac.bsu.edu/research/workingpapers/bsuecwp200804gisser.pdf, writes, writes:, far higher in Austin, https://substackcdn.com/image/fetch/$s_!tAF8!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F03f2b338-da84-4d85-b71c-0ce2e02e10e1_685x559.png, https://substackcdn.com/image/fetch/$s_!mLwn!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F9cf942da-5716-49e8-a177-20140681e7fc_573x421.png, Center for New Liberalism, the Neoliberal Podcast, Jeremiah “Liver-Eating” Johnson, Johnson helped make famous, https://substackcdn.com/image/fetch/$s_!tg5t!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fc490a60a-3e97-4b73-9806-79bb967b5172_608x550.png, Sea Ranch, some other commenters, Fresh Economic Thinking, wrote
Houston pretty much describes the “Oakland with more housing” outcome that Alexander views as somewhat far-fetched. Only in this case, it’s Austin with more housing. Alexander seems too quick to accept the, “If you build it they will come” idea—that you can build more housing and thereby boost demand so much that prices actually rise. I started the post with a graph of about 50 cities, showing a positive correlation between density and price. I’m having trouble seeing how Sumner’s point isn’t just “if you remove 48 of those cities and cherry-pick two, the relationship is negative”. My attempt to place Austin and Houston on the original graph, using Sumner’s data plus a few other things available online. Why weren’t they on there already? Maybe because the graph is metro areas and Sumner was talking about Austin and Houston as cities, but I’m not sure and agree this is confusing. Everyone knows Austin is more expensive than Houston because Austin is a trendy tech and culture hub and Houston isn’t (and relatedly, because Austin’s median family income is 50% higher than Houston’s). Unless someone wants to claim that its failure to build housing helped turn it into a trendy tech and culture hub, I don’t think there’s much point to this comparison. It’s true that Houston’s bigger size didn’t let it leapfrog over Austin to become a trendy tech and culture hub, which goes against some of what I claimed in the first part of this post. But I never claimed there would be a perfect 1-1 correlation between city size and trendiness, or that you could never find a pair of cities where one was bigger but the other was more trendy. Just that there would be a correlation. Moving on: Here’s the problem with this argument. It mixes up population change due to economic effects such as the benefits of agglomeration, with population changes due to regulatory changes such as less strict zoning. If you look at things this way, then the stylized facts work against Alexander’s argument. Over the past 50 years, increasingly strict zoning has reduced housing construction on big cities like New York and San Francisco. As a result, their populations have increased by less than in cities with less strict zoning, such as Houston. If Alexander were correct, then the price gap between the tightly controlled cities on the coast and the more laissez-faire cities of Middle America should have shrunk over time. Instead, the price gap has widened. New York and San Francisco were always more expensive than other cites, but with tighter zoning and less new construction the gap has become far wider. During the last fifty years, there was also deindustrialization and demographic sorting. This is just the Austin vs. Houston story all over again. Alexander is implicitly viewing this outcome as a “problem” for the city that builds more housing. They must sacrifice so that the rest of the country can gain. But in his scenario, Oakland is better off. Indeed if it were not better off, then why would more people choose to live in Oakland? In order for it to be true that building more housing boosts housing prices, it must also be true that the quality of existing houses (including neighborhood effects) rises by more than enough to offset the increase in supply. That means the new housing construction must make Oakland such a desirable place to live that the amenity effect overwhelms the quantity effect [...] Of course, economic change always has winners and losers. Here’s how I would describe the impact of allowing more housing construction in Oakland, in the unlikely event that this did raise housing prices: 1. America would benefit. 2. Oakland would benefit. 3. Poor people in America would benefit, in aggregate. 4. Affluent people in America would benefit, in aggregate. 5. Homeowners in Oakland would benefit. 6. Some renters in Oakland would benefit (from a more economically dynamic city.) 7. Some renters in Oakland would suffer from higher rents. In the much more likely case where new housing construction would lower prices, the impact described in #5 and #7 might reverse. Either way, there is no defensible argument for not building more housing in Oakland, regardless of the impact on price. If building more housing reduces its price, then there is a strong argument for allowing more housing construction. If building more housing raises its price, then the argument for more construction is even stronger. I agree with all this. Jeremiah Johnson is a co-founder of the Center for New Liberalism, host of the Neoliberal Podcast, and a YIMBY activist (not to be confused with Jeremiah “Liver-Eating” Johnson, who killed 300 Native Americans and ate their livers). He writes: Here's why you're wrong in a single sentence: Demand causes high prices, not new units. Prices are high in SF and NYC because those are desirable places to live for a huge number of people. People all over the country and the world would live there if they could, and prices reflect that. The fact that the densest cities are the most expensive is true. But the high prices are not caused by density - rather, the density and the high prices are both a consequence of crushingly high demand […] There's a feedback loop, but what matters here is the elasticity, which is less than one. We can measure this empirically. New housing lowers prices via the mechanism of adding supply, which is basic economics and how we expect markets to work. New housing could raise prices if it also made the city a more desirable place to live and shifted people's preferences, such that there was more demand to live there after the new housing is built. If you think it's unclear which of these effects would dominate, luckily we have empirical data that over and over and over shows adding housing supply does indeed lower prices on a local level. This is a fairly well established result that replicates well. edit: I'm actually thinking about drawing out the weighted DAG graphs here to make the conceptual stuff easier, but it would be pretty long. I'd love to do this as a guest post. I’m skeptical of the empirical results because they don’t match the much stronger “Manhattan vs. Conanicut island” empirical results, and if I try to think about why, the best explanation I can think of is that the Manhattan experiment has been going on longer (ie long enough for Manhattan’s extra residents to found businesses and institutions that attract new people). I’ve told him he can try pitching this guest post to me; in either case, I would be interested in seeing the graphs. Several other people also posted this graph that Johnson helped make famous: Hopefully by now you can predict my objection: the places in the southeast corner are mostly unfashionable red state Sun Belt cities; the places in the northwest corner are mostly trendy liberal coastal cities. My conclusion is that trendy liberal coastal cities are both more NIMBY and more desirable, and if you use this to draw any conclusions about housing policy you’ll just end up confused. But maybe I should take this same lesson to heart myself. Dense cities are mostly trendy liberal coastal cities; uninhabited tundra in North Dakota isn’t. Maybe the demand is just for trendy liberal coastal cities, and once you attain that status, extra density doesn’t matter that much. Maybe Oakland has already maxed out its “trendy liberal coastal city” status, and even if it became Manhattan-sized, it wouldn’t get any trendier, or would get trendier only with a long time lag. There are a few very trendy small coastal villages in California (think eg Sea Ranch); maybe these (rather than North Dakota) are the natural control group for San Francisco. I think they are still cheaper than SF, but maybe not by very much. Cameron Murray is a housing economist whose work some other commenters recommended; he also writes the blog Fresh Economic Thinking. He very kindly showed up and wrote: I think you are in general right that agglomeration effects are real, which is why bigger cities have higher value to residents. I agree that people move locations. But I think you can go a step further. If one city is growing faster and densifying, surely those people are not demanding homes in other cities and those cities build slower. This is part of the spatial equilibrium story that further makes claims about “build density and get cheap homes” less plausible. 7. My Final Thoughts + Poll Thanks to everyone who commented on this post and helped me refine my thoughts. I’m willing to concede the following points: It might be that only attracting the sort of educated people who found companies, universities, etc will make housing prices go up. Less educated people will take more jobs than they create and not ratchet up the city’s desirability level. (I’d previously told commenters talking about “gentrification” that it was irrelevant to the mechanism I was talking about here, but maybe it isn’t - maybe “gentrifiers” are the people creating more jobs and institutions than they consume, and so homes that attract them in particular will increase demand more than they increase supply? Maybe this discussion does reduce to the gentrification discussion?)
Inline links: https://substackcdn.com/image/fetch/$s_!mLwn!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F9cf942da-5716-49e8-a177-20140681e7fc_573x421.png, Center for New Liberalism, the Neoliberal Podcast, Jeremiah “Liver-Eating” Johnson, Johnson helped make famous, https://substackcdn.com/image/fetch/$s_!tg5t!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fc490a60a-3e97-4b73-9806-79bb967b5172_608x550.png, Sea Ranch, some other commenters, Fresh Economic Thinking, wrote
Meetups Everywhere 2023: Times & Places
August 25, 2023 · Original source
AUSTIN, TEXAS, USA Contact: Silas Barta Contact Info: sbarta[at]gmail[dot]com Time: Saturday, September 30th, 12:00 PM Location: Park area near stone tables behind Central Market at 4001 N. Lamar Blvd Coordinates: https://plus.codes/86248746+9C Group Link: https://groups.google.com/g/austin-less-wrong Notes: Feel free to bring kids/dogs. We will have tents set up for shade and provide food.
Inline links: https://plus.codes/86248746+9C, https://groups.google.com/g/austin-less-wrong
Spring Meetups Everywhere 2024
March 30, 2024 · Original source
AUSTIN, TEXAS, USA Contact: Silas Barta Contact Info: sbarta[at]gmail[dot]com Time: Saturday, May 25th, 12:00 PM Location: The Brewtorium, 6015 Dillard Cir A, Austin, TX 78752, we'll be inside somewhere, just look for the Austin LessWrong and ACX Meetup signs Coordinates: https://plus.codes/862487GM+96 Group Link: https://austinlesswrong.com/ Notes: You can park on the streets in front of Brewtorium or the Milk Bank lot next door. If it really gets full, use the nearby residential streets. We'll be there until at least 5pm!
Inline links: https://plus.codes/862487GM+96
Open Thread 330
May 20, 2024 · Original source
1: More meetups this week, including Austin, Bangalore, and Berlin. See the meetups list for more information.
Inline links: the meetups list
Highlights From The Comments On Mentally Ill Homeless People
July 18, 2024 · Original source
As long as it is an option to live on the street for free, lots of people will choose that option (or default to that option to avoid more difficult choices). Wherever they are permitted, encampment communities grow faster than Austin.
Open Thread 339
July 22, 2024 · Original source
1: I'm interested in expanding my biennial local ballot post into a community-wide effort to get an ACX slate for major US cities. Current plan is to ask the 5-10 biggest meetup groups to research for their city sometime in the autumn, then post a week or two before the election. This would probably be SF, Oakland, Berkeley, San Jose, LA, NYC, Seattle, Austin, Boston, Chicago. The main things I want to know now: when does your state release its voter information packet? Do other states have enough things on the ballot to keep this interesting, or is California unique there? Do these meetup groups feel up to working on this? Does anyone have any other suggestions or advice?
Inline links: biennial local ballot post
Meetups Everywhere 2024: Times & Places
August 29, 2024 · Original source
Contact: Felix Contact Info: ACXMeetupNashville[at]gmail[dot]com Time: Sunday, September 22nd, 01:00 PM New location: Rose Park Picnic Shelter #2 Coordinates: https://plus.codes/868M46V8+P5 Notes: Change of location! Entrance is on 12th Ave South, just north of Carter Lawrence Elementary. Go straight in and the picnic area and parking lot will be directly ahead. Texas AUSTIN, TEXAS, USA Contact: Silas Barta Contact Info: sbarta[at]gmail[dot]com Time: Saturday, October 05th, 12:00 PM Location: The park by Central Market, 4001 North Lamar, Austin, Texas. We will be by the stone tables. We will have a LessWrong and ACX sign and have some tents set up. You can also park in the parking lot at 3900 Guadalupe St (outside the fenced hospital area). Coordinates: https://plus.codes/86248746+9C Group Link: https://groups.google.com/g/austin-less-wrong Notes: Feel free to bring kids/dogs. We will provide lunch (soft tacos including vegan) and snacks and drinks.
Inline links: https://plus.codes/868M46V8+P5, https://plus.codes/86248746+9C, https://groups.google.com/g/austin-less-wrong
Contact: Silas Barta Contact Info: sbarta[at]gmail[dot]com Time: Saturday, October 05th, 12:00 PM Location: The park by Central Market, 4001 North Lamar, Austin, Texas. We will be by the stone tables. We will have a LessWrong and ACX sign and have some tents set up. You can also park in the parking lot at 3900 Guadalupe St (outside the fenced hospital area). Coordinates: https://plus.codes/86248746+9C Group Link: https://groups.google.com/g/austin-less-wrong Notes: Feel free to bring kids/dogs. We will provide lunch (soft tacos including vegan) and snacks and drinks.
Inline links: https://plus.codes/86248746+9C, https://groups.google.com/g/austin-less-wrong
Open Thread 349
September 30, 2024 · Original source
2: Late addition to Meetups Everywhere: Moscow on October 6, see link for more. Other meetups coming up this week include Philadelphia, Austin, Istanbul, Canberra, Budapest, and Warsaw. 3: If you haven’t already, vote for the winner of this year’s book review contest - voting closes Sunday, October 6. 4: And if you’re an ACX veteran, you might remember the winner of the very first book review contest - Lars Doucet’s review of Progress And Poverty, the book on Georgism. Since then, Lars has gone on to start a Georgism-inspired land valuation company, Valuebase, which has gotten investment from Sam Altman, Nat Friedman, and others. Now they’re recruiting paid interns, including: Technical interns: Ideal candidates have experience in programming, data science, machine learning, or AI, and are eager to work on real-world problems that scale across millions of properties.
Inline links: Meetups Everywhere, vote for the winner of this year’s book review contest, Lars Doucet’s review of, Valuebase
Ballots Everywhere: Call For Organizers, Times, & Dates
September 30, 2024 · Original source
Austin
Ballots Everywhere: Times And Places
October 04, 2024 · Original source
AUSTIN - Saturday, October 19th, 1:30 - 4:30 PM (but it “starts in earnest” at 2:30) - Central Market Cafe, 4001 N Lamar, Austin, TX - Contact sbarta@gmail.com
Open Thread 351
October 13, 2024 · Original source
3: Ballot meetups in Austin, Boston, Chicago, LA, Oakland, and SF this week, see here for details.
Inline links: here
ACX Local Voting Guides
October 22, 2024 · Original source
AUSTIN: Guide here BOSTON: Guide here CHICAGO: Guide here LOS ANGELES: Guide here NEW YORK CITY: Guide here OAKLAND/BERKELEY: Guide here PHILADELPHIA: Guide here SAN FRANCISCO: Guide here SEATTLE: Guide here
Inline links: Guide here, Guide here, Guide here, Guide here, Guide here, Guide here, Guide here, Guide here, Guide here
AUSTIN: Guide here. Part of the fun of this exercise is seeing what format each group came up with, so I appreciated Austin’s section of “Races Where You Should Consider Voting For The Other Party”, which highlighted elections where one candidate was so bad that even committed Dems/Republicans should consider crossing the aisle (usually this was because of corruption, like the candidate who “made millions of dollars off of oil companies that she is supposed to be responsible for enforcing rules on”). Highlight was their recommendation of Mayor Kirk Watson, even though “the [meetup] organizer's mom, a transportation engineer . . . has a long history sending Watson good highway designs that he vetoes because of his well-connected friends.”
Inline links: Guide here
Meetups Everywhere Spring 2025: Times & Places
March 25, 2025 · Original source
Contact: Silas Barta Contact Info: sbarta[a t]gmail[period]com Time: Saturday, May 24th, 12:00 PM Location: The Brewtorium, 6015 Dillard Cir A, Austin, TX 78752; We'll have a LessWrong sign at a long table indoors Coordinates: https://plus.codes/862487GM+96 Group Link: https://groups.google.com/g/austin-less-wrong/ Notes: Feel free to bring kids. We'll order shareable items for the group (fries and pretzels) and you can order from the food and drink menu.
Contact: Nate, Andrew, and Austin Contact Info: acx-everywhere-sf-spring-2025[ at]googlegroups[period]com Time: Saturday, April 5th, 2:00 PM Location: 1680 Mission St (Mox) Coordinates: https://plus.codes/849VQHCJ+82 Notes: Kids welcome!
Inline links: https://plus.codes/849VQHCJ+82
Contact: Matan Shtepel Contact Info: matan[period]shtepel[a t]gmail[period]com Time: Sunday, April 06th, 05:00 PM Location: We'll meet on the lawn in front of the tennis courts on CMU's campus. If it rains, we'll go into the the CMU university center (UC) which is open without key-card even on the weekend. We may eventually wander, so email me if you can't find us. Coordinates: https://plus.codes/87G2C3V4+2X Group Link: https://forms.gle/22YCsXAYFPbBCzvMA Notes: There is also a monthly ACX meetup group that meets at Bakery Square near the Google office. If you'd like to sign up for the email list to be notified of when they meet up, you can do that here: https://forms.gle/22YCsXAYFPbBCzvMA Texas AUSTIN Contact: Silas Barta Contact Info: sbarta[a t]gmail[period]com Time: Saturday, May 24th, 12:00 PM Location: The Brewtorium, 6015 Dillard Cir A, Austin, TX 78752; We'll have a LessWrong sign at a long table indoors Coordinates: https://plus.codes/862487GM+96 Group Link: https://groups.google.com/g/austin-less-wrong/ Notes: Feel free to bring kids. We'll order shareable items for the group (fries and pretzels) and you can order from the food and drink menu.
Inline links: https://plus.codes/87G2C3V4+2X, https://forms.gle/22YCsXAYFPbBCzvMA
Links For April 2025
April 22, 2025 · Original source
The article doesn’t explain why the board did such a poor job communicating their grievances, maybe it’s in the full book. It does sound like part of board’s problem was that they were leaning heavily on Mira Murati but she was playing both sides off against each other. 23: And the Forethought Institute has been putting out some great analysis lately, including Will AI R&D Automation Cause An Intelligence Explosion?, by Daniel Eth and Tom Davidson, and AI Enabled Coups: How A Small Group Could Use AI To Seize Power, by Tom Davidson, Lukas Finnveden, and Rose Hadshar. And here’s Davidson defending the coups paper on the 80,000 Hours podcast. 24: Agent Village is a sort of "reality show” where a group of AI agents has to work together to complete some easy-for-human tasks (currently: pick a charity and raise money for it) and you get to watch. 25: University of Austin promises approximately-automatic admission to anyone with a 1460+ on their SATs (or similar scores on other standardized tests). 26: Cremieux on birth order effects (X). His conclusion: “The birth order effect is social. It is driven by parental interactions and investments, and sibling interactions that are dynamic with respect to age.” 27: Claim from new paper, via Alex Tabarrok: “Prohibiting the FDA from regulating e-cigarettes reduced smoking attributable mortality by nearly 10% on average each year from 2011-2019 for a total savings of some 677,000 life-years, or approximately 1/3 the estimated benefit of early HIV/AIDS drugs through year 2000”. Related: FDA will not regulate lab-developed tests for the near future. 28: Bryan Caplan on Natal Con, the pronatalist conference in Austin. My strongest opinion on this is that they should either change the name or hold the next one in Natal, Brazil. 29: Am I living in a conservative filter bubble? I keep hearing how we need a “reckoning” over the government’s disastrous anti-COVID policies, but the latest YouGov polling suggests that large majorities of Americans continue to support those policies: 30: A California legislator proposed a bill that would ban OpenAI’s nonprofit → forprofit conversion, backed by a suspiciously specific interest group, the Coalition For AI Nonprofit Integrity. I assume this is either Elon Musk or our conspiracy; not sure which. But their plan was stymied when the legislature “amended” the bill to remove its entire text and replace it with unrelated text about airplane loans. The legislator apparently got cold feet after being warned it might inflict collateral damage on other companies, and because of the way the California legislature works it’s sometimes more efficient to turn doomed bills into other bills than to simply withdraw them. 31: EthnoGuessr is a GeoGuessr variant: it shows you pictures of an ethnic group, you click on the map where you think they’re from. Warning that if you play this too much you might get into race science. Their source, humanphenotypes.net, divides humanity into a hundred or so ethnic groups. Although they cite sources, I don’t understand the philosophical basis of the classification. Also, 100 images is so few that you start memorizing them after a while. I hope they move on to real pictures of real people in naturalistic situations. Remember, asking where someone is from ‘originally’ is a microaggression, but inferring it yourself based on their “mildly platyrrhine, high-rooted nose” is A-OK! 32: Farmkind has a new version of their calculator to determine meat offsets, eg how much do you have to donate to animal welfare charities to compensate for the animals you harm by eating meat. Does the average person really eat chicken 9x a week? 33: Not going to waste your time listing every bad thing Trump has done this month, but among the worst is sending innocent people to horrible Salvadorean prisons (including one person picked up because he had an autism awareness tattoo in honor of his brother, which they mistook for a gang tattoo), then refusing to bring them back. I have seen a couple of people defend denying immigrants due process; I assume they will not be moved by humanitarian arguments, but I think there are some more practical considerations: Zaid Jilani points out that if immigrants don’t get a right to due process, citizens also don’t get a right to due process, because the government can kidnap citizens, claim they’re immigrants, and the citizens can’t prove otherwise since they don’t get due process.
Inline links: https://substackcdn.com/image/fetch/$s_!WFgK!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F6448a778-3290-4c85-9480-d4f78f9be960_916x255.png, Will AI R&D Automation Cause An Intelligence Explosion?, AI Enabled Coups: How A Small Group Could Use AI To Seize Power, here’s, Agent Village, promises approximately-automatic admission, Cremieux on birth order effects (X), new paper, Alex Tabarrok, FDA will not regulate lab-developed tests for the near future, Bryan Caplan on Natal Con, Natal, Brazil, the latest YouGov polling, https://substackcdn.com/image/fetch/$s_!HGBp!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fd049433b-1cf5-442a-9d17-4be3a7846d61_760x370.png, Coalition For AI Nonprofit Integrity, “amended”, the way the California legislature works, EthnoGuessr, https://substackcdn.com/image/fetch/$s_!Y3AO!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fbde5185a-2b93-4c07-904b-66d2c2311a53_1140x1033.png, humanphenotypes.net, a new version of their calculator, including, Zaid Jilani
Open Thread 382
May 19, 2025 · Original source
1: ACX meetups this week in Oxford, Shanghai, and Austin. See the post for details.
Inline links: the post
Your Review: Alpha School
June 27, 2025 · Original source
In January 2025, the charter school application of “Unbound Academy”, a subsidiary of “2 Hour Learning, Inc”, lit up the education press: two hours of “AI‑powered” academics, 2.6x learning velocity, and zero teachers. Sympathetic reporters repeated the slogans; union leaders reached for pitchforks; Reddit muttered “another rich‑kid scam.” More sophisticated critics dismissed the pitch as “selective data from expensive private schools”.
Inline links: Unbound Academy, 2 Hour Learning, Inc, another rich‑kid scam
2-Hour Learning’s flagship school is the “Alpha School” in Austin Texas. The Alpha homepage makes three claims:
Inline links: Alpha homepage
“Powered by AI (not teachers).” If all of this makes your inner Bayesian flinch, you’re in good company. After twenty‑odd years of watching shiny education fixes wobble and crash—KIPP, AltSchool, Summit Learning, One-laptop-per-child, No child left behind, MOOCs, Khan‑for‑Everything—you should be skeptical. Either Alpha is (a) another program for the affluent propped up by selection effects, or (b) a clever way to turn children into joyless speed‑reading calculators. Those were, more or less, the two critical camps that emerged when Alpha’s parent company was approved to launch the tuition‑free Arizona charter school this past January. Unfortunately, the public evidence base on whether this is “real” is thin in both directions. Alpha’s own material is glossy and elliptical; mainstream coverage either repeats Alpha’s talking points, or attacks the premise that kids should even be allowed to learn faster than their peers. Until Raj Chetty installs himself in the hallway with a clipboard counting MAP percentiles it is hard to get real information on what exactly Alpha is doing, whether it is actually working beyond selection effects, and if there is anyway it could scale in a way that all the other education initiatives seemed to fail to do. I first heard about Alpha in May 2024, and in the absence of randomized‑controlled clarity, I did what any moderately obsessive parent with three elementary-aged kids and an itch for data would do: I moved the family across the country to Austin for a year and ran the experiment myself (unfortunately, despite trying my best we never managed to have identical twins, so I stopped short of running a proper control group. My wife was less disappointed than I was). Since last autumn I’ve collected the sort of on‑the‑ground detail that doesn’t surface in press releases, or is available anywhere online: long chats with founders, curriculum leads, “guides” (not teachers), Brazilian Zoom coaches, sceptical parents, ecstatic parents, and the kids who live inside the Alpha dashboard – including my own. I hope this seven-part review can help share what the program actually is and that this review is more open minded than the critics, but is something that would never get past an Alpha public relations gatekeeper: Starting Point: My Assumptions: how my views on elite private schools, tutoring and acceleration shaped the experiment (and this essay). WHAT is the existing education environment.
Meetups Everywhere 2025: Times and Places
August 29, 2025 · Original source
Contact: Amy Contact Info: amyelquest[a t]gmail[period]com Time: Saturday, October 4th, 1:00 PM Location: Next Level Brewing Company - I’ll bring a small ACX sign, there’s parking behind the brewery. Coordinates: https://plus.codes/867RX3GG+FH Texas AUSTIN Contact: Silas Barta Contact Info: sbarta[a t]gmail[period]com Time: Saturday, October 11th, 12:00 PM Location: The park by Central Market, 4001 North Lamar, Austin, Texas. We will be by the stone tables by the pond with tarps for shade. We will have a LessWrong and ACX sign and have some tents set up. You can also park in the parking lot at 3900 Guadalupe St (outside the fenced hospital area). Coordinates: https://plus.codes/86248746+9C Group Link: https://austinlesswrong.com/calendar/ Notes: Feel free to bring kids/dogs (though it's a bit of a walk to the indoor bathrooms). We'll provide breakfast tacos (including vegan) and other snacks and drinks. Feel free to bring more, but it's not expected.
Inline links: https://plus.codes/867RX3GG+FH, https://plus.codes/86248746+9C, https://austinlesswrong.com/calendar/
Contact: Silas Barta Contact Info: sbarta[a t]gmail[period]com Time: Saturday, October 11th, 12:00 PM Location: The park by Central Market, 4001 North Lamar, Austin, Texas. We will be by the stone tables by the pond with tarps for shade. We will have a LessWrong and ACX sign and have some tents set up. You can also park in the parking lot at 3900 Guadalupe St (outside the fenced hospital area). Coordinates: https://plus.codes/86248746+9C Group Link: https://austinlesswrong.com/calendar/ Notes: Feel free to bring kids/dogs (though it's a bit of a walk to the indoor bathrooms). We'll provide breakfast tacos (including vegan) and other snacks and drinks. Feel free to bring more, but it's not expected.
Inline links: https://plus.codes/86248746+9C, https://austinlesswrong.com/calendar/
Open Thread 402
October 06, 2025 · Original source
1: Meetups this week include Austin, Berlin, Canberra, Jakarta, Salt Lake City, Tel Aviv, and others - see the meetup post for more information.
Inline links: the meetup post
Meetups Everywhere Spring 2026: Times & Places
April 01, 2026 · Original source
Contact: Silas Barta Contact Info: sbarta[@]gmail[.]com Time: Saturday, May 30th, 12:00 PM Location: The Brewtorium, 6015 Dillard Cir A, Austin, TX 78752; will be at an indoor table with an ACX sign Coordinates: https://plus.codes/862487GM+96 Group Link: https://austinlesswrong.com/calendar/ Notes: Feel free to bring kids. Dogs are not allowed indoors. If parking fills up, you can park on the street in the neighborhood off Denson Drive.
Inline links: https://plus.codes/862487GM+96, https://austinlesswrong.com/calendar/
Contact: Daksh Contact Info: tyagid0[@]sewanee[.]edu Time: Saturday, April 11th, 2:00 PM Location: Stirling’s Coffee House porch Coordinates: https://plus.codes/867P634M+39 Notes: Please RSVP so I know how many people to expect and let Stirling’s know in advance if we’re going to be a big group! Texas AUSTIN Contact: Silas Barta Contact Info: sbarta[@]gmail[.]com Time: Saturday, May 30th, 12:00 PM Location: The Brewtorium, 6015 Dillard Cir A, Austin, TX 78752; will be at an indoor table with an ACX sign Coordinates: https://plus.codes/862487GM+96 Group Link: https://austinlesswrong.com/calendar/ Notes: Feel free to bring kids. Dogs are not allowed indoors. If parking fills up, you can park on the street in the neighborhood off Denson Drive.
Inline links: https://plus.codes/867P634M+39, https://plus.codes/862487GM+96, https://austinlesswrong.com/calendar/