A challenge that YIMBY advocates face is that voters just don't understand supply and demand. 44% think building more housing INCREASES prices, while only 24% think it lowers prices
@stewbie_doobie@loomdoop also, see my above point about Berkeley rent falling faster than Alameda County in general
regional factors definitely matter, but can't easily explain the difference. Especially considering Berkeley has retained population better than the county
@stewbie_doobie@loomdoop It's actually reporting new leases in the rent control registry, which are initially rented at market rates
These are older apartment buildings, which tend to be cheaper, but what we're interested in is the *trends* which is an indicator of changes in market rates
@stewbie_doobie@loomdoop Did you read the article? :)
It's actually a hard question to causally identify b/c construction partially coincides with Bay Area COVID population decline
but then it's hard to explain why Berkeley's rent has fallen faster than Alameda County more broadly
@PippengerHarlo@jakeonrails@DrCameronMurray main reason is they applied the per-capita benefit to a fixed cohort of residents rather than a broader sample
their per capita figure assumes all of the benefits from being an incumbent since 1994, but new residents receive less bc of shorter exposure, selection, vacancy reset
@Aella_Girl you could run a survey on a random sample and then see if major results of the survey are validated by that random sample
that will increase confidence that the results aren't biased by unobservables
however nonresponse bias will be a problem for these topics
@Aella_Girl We have no way of telling whether those who fill the survey out are systematically different from the general population on unobservable, unmeasured characteristics.
You need a random sample of people in order to ensure that the results are not driven by these unobservables.
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