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Speaker 1: Well, you know, I just I don't know, Sophie. I

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Speaker 1: think that you're kind of being unfair when you say

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Speaker 1: the audience is just terrible people and you hate them

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Speaker 1: and you want to throw boiling water from a cast

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Speaker 1: iron skelet on them. I don't know that that's fair, Sophie.

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Speaker 1: That seems kind of mean to me. But Robert, I

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Speaker 1: would never say that was a direct quote from your diary.

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Speaker 1: That was that was weren't my words. That's what you said,

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Speaker 1: so you can't prove that. I mean, it was in

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Speaker 1: your blog. Well, who knows what's a blog it was?

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Speaker 1: I remember I followed you. Wow. Wow, I feel attacked

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Speaker 1: in my own podcast, my own podcast that I don't

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Speaker 1: with my own two hands. Unbelievable. Welcome to behind the mastause.

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Speaker 1: I guess it's Samantha big Bay. Robert evans Am slandered

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Speaker 1: to a terrible degree unfair early despite having never done

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Speaker 1: anything wrong never How are you doing, Samantha McVeigh. Hello.

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Speaker 1: I know again I aged myself with the zango reference,

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Speaker 1: so I know people are going to be like, oh

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Speaker 1: my god, what is wrong with you? You're welcome. I'm

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Speaker 1: really glad to throw it back at this early. Yeah, Samantha,

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Speaker 1: what's what's? What is? That's that's your whole that's your

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Speaker 1: whole question. What is? How is what? What is? But

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Speaker 1: how is it? Yeah? Exactly how is what? And what

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Speaker 1: is how? Is there an answer question? There never was

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Speaker 1: a r Are you asking if she's the host of

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Speaker 1: a podcast called stuff? Mom never told you? Is she? Well?

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Speaker 1: Is she? This is why I keep you around, Sophie.

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Speaker 1: I know that you've got this better than I do.

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Speaker 1: This has been a great introduction. Robert would never have

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Speaker 1: gotten there. I would have gotten there. I I love

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Speaker 1: our audience, I of all of everybody the statistically speaking,

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Speaker 1: So this is a podcast, it's about bad people. Normally,

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Speaker 1: we're doing a little bit of a different thing today, Samantha,

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Speaker 1: and I've brought you on. I've brought you on because,

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Speaker 1: as I can tell right now, you exist in a

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Speaker 1: black void. Based on your and I assume that that's

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Speaker 1: what goes on in the heart of anybody who understands math.

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Speaker 1: I feel like that was racist. Is that racist because

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Speaker 1: I'm a whoa? It's because you exist within a black void? Oh? Okay, okay, Jesus,

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Speaker 1: that is how we we have, like obviously for the

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Speaker 1: people listening to this podcast, there's a pretty good chance

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Speaker 1: they're renters. They're about third rent. Renters are about thirty

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Speaker 1: six percent of households nationwide, or or renter's head thirties

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Speaker 1: percent of households nationwide. Um, although those numbers are a

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Speaker 1: couple of years old. I don't know if it's that

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Speaker 1: was like pre pandemic. Um, do you rent or do

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Speaker 1: you own? Samantha, I now officially own because we were

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Speaker 1: kind of pushed out from the rental that I had

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Speaker 1: because he went up by Uh. I want to say

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Speaker 1: on our rent, Jesus Christ. So yeah, you have been.

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Speaker 1: That's what we're talking today about why the rent is

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Speaker 1: so damn high. Um, and some of the people who

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Speaker 1: are responsible. We're gonna try to drill into specific people

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Speaker 1: whenever possible, because that's our our bit. But I am

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Speaker 1: also in my first year of homeownership. I've been a

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Speaker 1: renter the first fifteen years of my adult life. UM,

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Speaker 1: And for me, I don't know about you. Most of

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Speaker 1: the living situations I was in were like the broadly criminal,

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Speaker 1: like illegal, like like the the landlord was breaking a

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Speaker 1: law and so my rent was cheaper. We actually liked

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Speaker 1: to tell this story a couple of we had to

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Speaker 1: like talk a City of Los Angeles inspector out of

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Speaker 1: reporting fire hazards in our apartment because we were like, dude,

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Speaker 1: i live a minute and a half away from santam

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Speaker 1: Anka and we're paying like a thousand bucks a month

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Speaker 1: for a room each, Like you gotta you gotta, like,

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Speaker 1: you gotta just keep quiet, Like we'll burn to death

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Speaker 1: if we burned to death. We'll risk life or death

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Speaker 1: for the situation because it's cheap, because it's cheap um.

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Speaker 1: But nothing is cheap anymore. It has gotten Rent has

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Speaker 1: gotten higher at a ridiculous rate since the pandemic, in particular,

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Speaker 1: not that it wasn't raising before, but it's really raised

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Speaker 1: a lot. Say, as you just said, you just we're

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Speaker 1: about to go up forty year over year. In Miami

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Speaker 1: and Tampa, rent is up about fifty of its pre

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Speaker 1: pandemic numbers, and nationwide, median rent has topped two thousand

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Speaker 1: dollars a month for the first time ever, which is

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Speaker 1: inside when I was, you know, a kid fourteen fifteen

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Speaker 1: years ago living in my first apart, two grand a

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Speaker 1: month is like that's a rich person's rent, Like like

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Speaker 1: that's a crazy rich. But I remember going to like

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Speaker 1: a friends apartment in Manhattan that was bucks a month

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Speaker 1: and being like, what the funk is wrong with you people? Right,

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Speaker 1: I'd be seven dollars a month for a three bedroom

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Speaker 1: like UM. Now, the fact that media and rent has

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Speaker 1: topped two thousand dollars a month is heavily influenced by

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Speaker 1: the poll of the big cities. These are very skewed

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Speaker 1: numbers that may not reflect most individual people's experience because

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Speaker 1: of how big some of the big cities are and

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Speaker 1: how high the rent is there. So San Francisco, Seattle,

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Speaker 1: New York, Los Angeles, Miami, etcetera. Are the places that

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Speaker 1: are skewing the numbers and the places where rent has

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Speaker 1: surged the most. But rent is still up basically everywhere.

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Speaker 1: It is currently increasing at the fastest rate since nineteen

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Speaker 1: eight six UM. And one of the things that happened

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Speaker 1: during the pandemic is we had all these people moving

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Speaker 1: to cities that they thought would be a better place

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Speaker 1: to live because it was remote work UM, which helped

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Speaker 1: spread out some of the increases UM. And there was

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Speaker 1: a brief period of time where evictions were tamped down

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Speaker 1: on somewhat by federal rental assistants, So even though rent

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Speaker 1: was rising, it was hard to kick people out of

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Speaker 1: their houses. But that has started to run out this

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Speaker 1: year and in eviction filings hit pre pandemic levels and

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Speaker 1: in many play has exceeded them greatly. So does that

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Speaker 1: have an impact. Does the impact of like what's called

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Speaker 1: pandemic pricing on rent have have an influence there where?

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Speaker 1: Like a lot of places, they especially in big cities

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Speaker 1: such as Los Angeles, New York, they were trying to

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Speaker 1: fill places, so they gave a lower price and then

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Speaker 1: the next year the increase was um offensively high. Yeah,

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Speaker 1: that's one of the things that experience. It's it's one

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Speaker 1: of the things that's contributed to evictions some cities. It's

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Speaker 1: like like Houston in particulars is one city I know

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Speaker 1: where eviction rate filings are like pre pandemic levels. Like

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Speaker 1: it's massively higher in a lot of cities. And this

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Speaker 1: is all that hit hard with that, And immediately as

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Speaker 1: as soon as it dropped, the amount of evictions that

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Speaker 1: came it was absurd and obscene. Yeah, and it and

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Speaker 1: that that's fed into the homelessness crisis. That's this huge

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Speaker 1: political thing. And also just like thing thing everywhere in

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Speaker 1: the country right now. Um, and it's you know, kind

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Speaker 1: of difficult to grock an absolute numbers how many house

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Speaker 1: those people and encampments and other situations, because those aren't

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Speaker 1: easily recorded in federal and state statistics. But homelessness is

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Speaker 1: surging in a number of American cities. And all of

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Speaker 1: this is ancillary to the question why is the rent

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Speaker 1: so damn high? Now, if you go to like the yeah,

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Speaker 1: exactly why is there? I know we're about to go

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Speaker 1: down to this. There's gonna be black Hawk mentioning, Zillo mentioning,

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Speaker 1: Airbnb mentioning. Are we going down these routes. We're gonna

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Speaker 1: be talking about some of these. We're gonna be talking

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Speaker 1: about a number of those. This is I want to

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Speaker 1: say right now. We're not gonna be this isn't going

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Speaker 1: to be a comprehensive list of all of the different

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Speaker 1: things affecting rent prices, focusing on some particularly bastardy ones.

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Speaker 1: But we'll cover a lot of it. So please don't

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Speaker 1: get on and be like, well you didn't cover this

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Speaker 1: or that. It's like, yeah, man, it's a big topic.

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Speaker 1: Like do you do you want us this to all

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Speaker 1: be just one boring broad overview of problems. You do

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Speaker 1: want us to drill into some weird, fucked up assholes,

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Speaker 1: which is what we're gonna Yeah, I got time today,

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Speaker 1: so let's go. Yeah. So, if you go to say,

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Speaker 1: the New York Times or most other big legacy see

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Speaker 1: publications to try to, like, you know, type into Google

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Speaker 1: why is the rent so damn high? You'll get various

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Speaker 1: versions of the same answer. And I'm gonna quote from

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Speaker 1: a New York Times article here. The origins of the

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Speaker 1: current homelessness crisis go back decades to policies that stop

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Speaker 1: the US from building enough housing. Experts said, seven million

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Speaker 1: extremely low income renters cannot get affordable homes, according to

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Speaker 1: the National Low Income Housing Coalition. Now, experts like these

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Speaker 1: tend to place a lot of the blame on what

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Speaker 1: we call nimbies, which stands for not in my backyard,

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Speaker 1: and it references the fact that in cities like San Francisco,

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Speaker 1: there's a lot of like upper class liberal types who

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Speaker 1: make it very hard to build anything besides single family

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Speaker 1: housing because they don't like big buildings and they don't

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Speaker 1: like being in a dense urban environment. Los Angeles County

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Speaker 1: devotes seventy six percent of its residential land to single

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Speaker 1: family homes, which is bug fuck uh. This leads to

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Speaker 1: sprawling cities, which also require huge road systems, lots of parking,

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Speaker 1: YadA YadA, and it leads to higher rent prices because

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Speaker 1: there's simply less space to build housing. The New York

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Speaker 1: Times also notes quote homeowners also often protest proposed housing,

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Speaker 1: effectively blocking it. They fear that more housing, particularly for

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Speaker 1: low income families, will change the makeup of their communities,

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Speaker 1: will reduce the values of their home. Now in San Francisco,

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Speaker 1: what David Chappelle did, supposedly, I know that was like

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Speaker 1: a small blue but it was a misunderstanding. But he

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Speaker 1: like blocked a housing, like yeah right, yeah, he said

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Speaker 1: it was a misunderstanding. George Lucas built a bunch of

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Speaker 1: low income housing specifically to funk with his neighbors, his

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Speaker 1: rich neighbors. He had had like noise complaint problems with

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Speaker 1: his rich neighbors as a result of like the studio

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Speaker 1: he ran, so to funk with them, he built a

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Speaker 1: bunch of low income housing in the neighborhood because he

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Speaker 1: knew it would piss off the other rich people. That's

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Speaker 1: so nice, yeah, based George lucast dot dot. Um, he's

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Speaker 1: a he's a he's a perfect unproblematic king. So yeah,

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Speaker 1: and there's like, are not the New York Times and stuff.

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Speaker 1: They're not wrong when they say that nimbies are part

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Speaker 1: of the problem. In San Francisco, there were recently a

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Speaker 1: bunch of protests to stop a project to convert a

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Speaker 1: hundred and thirty one room hotel in japan Town into

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Speaker 1: housing for homeless people. Um, like a bunch of ships

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Speaker 1: like that happens. California has about twenty three available affordable

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Speaker 1: homes for every hundred extremely low income renters, which is

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Speaker 1: makes it one of the worst of any state and

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Speaker 1: in terms of that problem. Um, so they're not wrong

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Speaker 1: when they say that, Like, yeah, the the nimbies are

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Speaker 1: a problem. People pro not allowing like multi family development

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Speaker 1: and lots and stuff is a huge problem. And I've

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Speaker 1: reluctantly come to see that. Like they have a point,

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Speaker 1: Uh I have. I don't want to I don't like

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Speaker 1: living in high density areas. I would prefer to live

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Speaker 1: out in the woods. Um. But but this argument is

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Speaker 1: broadly broadly correct. A huge part of the problem is

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Speaker 1: that there's denser cities is that we need to have

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Speaker 1: denser cities with more multi family z owning and residential areas. However,

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Speaker 1: there's also a lot of bullshit in the argument that

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Speaker 1: The New York Times is making here and in this

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Speaker 1: argument in general, because the way it tends to get pushed,

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Speaker 1: and it gets pushed by people like developers and by

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Speaker 1: intellectuals who take on the attitude of developers because the

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Speaker 1: developers are their uncles or whatever, is that all of

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Speaker 1: the homelessness problem is to blame on these liberal city

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Speaker 1: policies that just aren't letting developers develop enough. Um And

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Speaker 1: And while again zoning is a part of the issue,

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Speaker 1: this analysis excises a great deal of the actual problem.

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Speaker 1: For one thing, the whole we're not building enough housing

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Speaker 1: thing tends to lay all the blame on zoning and

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Speaker 1: these darn nimbies. Um. But one of the other problems

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Speaker 1: is that like there's not actually people to build that housing. Um.

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Speaker 1: This is this is a major problem in the industry.

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Speaker 1: And I'm gonna put from a right up on NPRS website.

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Speaker 1: By one estimate, the US is more than three million

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Speaker 1: homes short of the demand from would be homebuyers. Pandemic

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Speaker 1: related supply chain problems aren't helping. They're adding tens of

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Speaker 1: thousands of dollars in costs to the typical house. But

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Speaker 1: the roots of the problem go back much further to

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Speaker 1: the housing bubble collapse in two thousand eight, what I

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Speaker 1: call a blood bath happened, says Klaus, who's a contractor.

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Speaker 1: It was the worst housing market crash. It's the Great depression.

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Speaker 1: Many homebuilders went out of business. Claus was building houses

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Speaker 1: in Florida when the bottom fell out. A lot of

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Speaker 1: my trades people found other work, went and got retrained

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Speaker 1: for new jobs, in law enforcement, all sorts of jobs.

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Speaker 1: So the workplace force was somehow decimated, so more cops,

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Speaker 1: less construction workers, nobody to build the fucking houses that

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Speaker 1: they want to have build, which is not a problem

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Speaker 1: that you can lay on zoning or nimbies. That's because

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Speaker 1: we It's because there was a fraudulent like banking industry

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Speaker 1: that existed to sell people's subprime loans on houses that

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Speaker 1: were low quality, massive and built in terrible locations. And

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Speaker 1: when that fell apart, suddenly all of these people had

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Speaker 1: to find something else to do. And you can't blame

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Speaker 1: that on the fucking Nimbies in San Francisco, right, I mean,

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Speaker 1: there's all this conversation about funding as well as who

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Speaker 1: is actually going to be able to afford it? Is

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Speaker 1: it is it truly affordable in actuality, which it often

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Speaker 1: winds up not being because like we we have, there's

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Speaker 1: like loopholes a lot Like in Portland right now, there's

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Speaker 1: a building that's supposed to be affordable housing, but one

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Speaker 1: of like the deals the city gets as they get

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Speaker 1: or the gives the developers that they can increase rent

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Speaker 1: at a greater rate than other places could for a

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Speaker 1: certain set amount of years, which like, yeah, it's all

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Speaker 1: there's all these fucky ways that it affordable housing winds

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Speaker 1: up not being affordable that is not due to zoning

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Speaker 1: or they just back out of this. So we had

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Speaker 1: a whole project here called the Atlanta belt Line, which

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Speaker 1: is supposed to stretch around um our metro area, and

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Speaker 1: it was supposed to build up the city, have this

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Speaker 1: walkable area, maybe get a rail stage, and I don't know,

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Speaker 1: all these great things, but they had to buy out

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Speaker 1: a lot of the areas which is predominantly urban and therefore,

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Speaker 1: you know, it wasn't it was red line. Once upon

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Speaker 1: a time, and it's now valuable because it's within the city.

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Speaker 1: So they bought out these houses, pushing people out the

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Speaker 1: low um. But the deal they had was we're going

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Speaker 1: to put in affordable housing as well. They did not.

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Speaker 1: They actually backed down that they'll sub deal so much.

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Speaker 1: The originators who proposed this plan created this huge plan

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Speaker 1: that was gonna be a thirty year plan. It's still ongoing,

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Speaker 1: by the way, multi million dollars from the city, so

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Speaker 1: many things that they stepped down and said they were

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Speaker 1: no longer a part of this project because it went

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Speaker 1: so ugly and that people had come back with sorry,

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Speaker 1: just kidding, We're not giving you this property back. We're

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Speaker 1: just gonna make millions and millions and millions of dollars

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Speaker 1: without any going back to the city or the people

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Speaker 1: who we promised that we would help. Bad shocking. Yeah,

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Speaker 1: I mean, yeah, that's that sounds like the way it

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Speaker 1: tends to go. Um. So, yeah, we have this fucking

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Speaker 1: financial crash and home buying eventually slowly recovers after it,

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Speaker 1: but building rates never do right. They stay below normal

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Speaker 1: after the crash. This continues for like, you know, more

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Speaker 1: than a decade because the workers simply aren't there to

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Speaker 1: buy houses. So when millennials start to hit what should

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Speaker 1: have been their prime home buying years, not only our

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Speaker 1: houses more expensive than they had been, but there's less

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Speaker 1: houses being built. And that's again it's it's just not

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Speaker 1: due to zoning. It's the result of the home building

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Speaker 1: industry tanking because a bunch of people who should be

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Speaker 1: in prison sold and bundled up sub prime loans. And

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Speaker 1: then those same people go to people in the New

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Speaker 1: York Times pretending to be experts and say, no, we

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Speaker 1: gotta change the zoning so I can develop cities more.

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Speaker 1: And it's frustrating that that's the only argument you tend

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Speaker 1: to fucking here now. Even then, even if you like

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Speaker 1: because again the New York Times, the angle here is

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Speaker 1: not entirely wrong, but it also leaves a lot out,

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Speaker 1: even if you're just looking at their numbers, because the

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Speaker 1: numbers we see that are like, the US is missing

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Speaker 1: this many million homes, right, We're short three million homes

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Speaker 1: or seven million homes are if not kind of fucky,

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Speaker 1: which I would argue then at least presented in a

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Speaker 1: way that does not provide people with clarity as to

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Speaker 1: what the numbers actually mean. When I say the US

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Speaker 1: is short three million homes, which is something you here

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Speaker 1: on the New York Times a lot that suggests that, like, well,

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Speaker 1: there's three million people who don't have who can't get

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Speaker 1: housing because of sheer lack of availability, right or at

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Speaker 1: least x number of people. However, many people fit into

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Speaker 1: three million homes, and that's not really true. Uh, there's

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Speaker 1: a lot of people who they started, Yeah, from where

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Speaker 1: are these numbers? And who? I'm kind of confused. I'm like,

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Speaker 1: who actually says, all right, I've gone and taking a

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Speaker 1: statistics and we figured out that yes, this amount of

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Speaker 1: people need as much many houses. But do we actually

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Speaker 1: have a number on how did it come up to that? Yes,

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Speaker 1: we're about to get to that. I'm going to talk

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Speaker 1: to It does not work the way you would think

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Speaker 1: it does based on the way it tends to get summarized. Right. Um,

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Speaker 1: but yeah, there's there's folks will argue, just in general

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Speaker 1: that the problem is not the way it's often presented.

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Speaker 1: Kevin Drum is a writer from Mother Jones and I

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Speaker 1: think kind of on the more libertarian end of things

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Speaker 1: with a lefty tinge. His big claim to fame is

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Speaker 1: that he helped solidify the idea that there's a connection

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Speaker 1: between the drop and violent crime and the removal of

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Speaker 1: environmental lead, like getting lead out of gas. He's like

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Speaker 1: the journalist who is big on that, And he points

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Speaker 1: out that while construction never recovered after the two thousand

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Speaker 1: and eight crash, that's because the crash led to the

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Speaker 1: bursting of a housing bubble. And since housing was indeed

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Speaker 1: a bubble in that period, why would construction have returned

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Speaker 1: to the rate that it was being added at when

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Speaker 1: everyone lost their minds building trash houses as part of

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Speaker 1: a shell game, right, Like, maybe it's not, it's not.

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Speaker 1: The problem isn't that housing construction didn't return to previous

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Speaker 1: levels because those levels were insane and fundamentally based on

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Speaker 1: a rationality quote. During the early aughts, housing supply grew

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Speaker 1: far faster than population. After the bust, household formation caught

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Speaker 1: up by around two thousand thirteen, and since then, housing

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Speaker 1: supply has matched household growth and has exceeded population growth.

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Speaker 1: So do we have a housing shortage? Everyone keeps saying

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Speaker 1: we do, and the housing groupies keep yelling at me

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Speaker 1: that my chart is meaningless, But why, it sure looks

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Speaker 1: right to me. By the way, I was browsing through

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Speaker 1: some O e c D stats the other day looking

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Speaker 1: for healthcare information, and I happened to run into their

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Speaker 1: league rankings for housing. Guess how we compare based on

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Speaker 1: indicators such as rooms per house, basic facilities, and affordability.

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Speaker 1: The rankers is number one in the entire O e

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Speaker 1: c D group of rich countries for the year to twenty.

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Speaker 1: We must be doing something right and something wrong. According

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Speaker 1: to the O e c D, we rank second from

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Speaker 1: last among housing affordability for low income tenants. So what

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Speaker 1: he's saying is that, like, well, the evidence that like

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Speaker 1: we're short on housing is weaker than the evidence that

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Speaker 1: prices and housing are being jacked up and inflated. It's

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Speaker 1: like the there is inflated. It's like with the grocery store.

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Speaker 1: There is inflation that's affecting the price of your groceries.

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Speaker 1: Those grocery stores are also making record profits because they

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Speaker 1: have jacked up prices specifically to make more money with

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Speaker 1: the cover of inflation. Um yeah, drums Work is quoted

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Speaker 1: favorably by Brian Potter, who works in the wonky side

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Speaker 1: of the construction industry and writes a popular sub stack

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Speaker 1: for weirdo construction nerds who want to know about things

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Speaker 1: like why has wood gotten so expensive and why did

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Speaker 1: agriculture mechanize and not construction. He those are the kind

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Speaker 1: of things he writes about. He's also a member of

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Speaker 1: the Institute for Progress, which is a right wing libertarian

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Speaker 1: shaded think tank who pushed the idea that a lot

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Speaker 1: of social and political policy should be tested by being

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Speaker 1: prominent people tweet shit. What I'm trying to say is

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Speaker 1: that I'm not going to totally back this guy up,

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Speaker 1: but he certainly knows more about construction than me. He

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Speaker 1: has an angle, which is why I laid out what

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Speaker 1: he writes for. But he does. He does the best

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Speaker 1: job I've seen of answering the question of like, what

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Speaker 1: does a statistic like we're three million houses short really mean? Quote.

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Speaker 1: We'll start with some context. The US has roughly three

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Speaker 1: dred and thirty million people living in roughly onety one

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Speaker 1: million homes, or about point four two homes per person.

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Speaker 1: This puts the U S slightly before below the O

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Speaker 1: E c D average of homes per capita. One thing

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Speaker 1: worth noting about this is that previous rates of homebuilding

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Speaker 1: in the U S were partly driven by falling average

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Speaker 1: household size. But there's a limit to how much average

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Speaker 1: household size can fall. You can only add so many

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Speaker 1: new households to a given population size. At the extreme end,

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Speaker 1: you can't have more households than there are people. Average

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Speaker 1: household size can't be less than one. And in a

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Speaker 1: world where a children live with their parents until they're

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Speaker 1: eighteen and be most people live with a romantic partner,

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Speaker 1: and see the population isn't declining. Is a world with

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Speaker 1: a higher floor on how small the average household can get.

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Speaker 1: What happens if this world changes to one where the

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Speaker 1: average household sizes too. In the final condition, you'll be

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Speaker 1: building twice as many houses. If you add four people

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Speaker 1: to the population, you're now building two homes instead of one.

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Speaker 1: But to get to that second world, you need to

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Speaker 1: build one hundred additional houses. Even if this process takes

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Speaker 1: fifty years, that's an extra two houses per year on

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Speaker 1: top of the ones you're already building, which will temporarily

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Speaker 1: juice your building rate. But once you work through that backlog,

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Speaker 1: you're building right will drop off. Turning back to the

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Speaker 1: real world, in nineteen sixty the US had a population

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Speaker 1: of a hundred and eighty million with an average household

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Speaker 1: size of three point three three. By nineteen eighty, average

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Speaker 1: household size had dropped to two point seven six. This

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Speaker 1: means that between nineteen sixty and nineteen eighty, over five

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Speaker 1: hundred and fifty thousand homes per year were needed just

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Speaker 1: to keep up with changes in household size. By contrast,

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Speaker 1: from two thousand one to twenty one, average household size

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Speaker 1: only went from two point five six to two point

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Speaker 1: five one. We thus can't infer much from the fact

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Speaker 1: that US home building rates per apoda are lower than

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Speaker 1: they were in the past, because we would expect that

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Speaker 1: to happen at some point soon regardless are you are

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Speaker 1: you do you see what he's saying there? Explain it

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Speaker 1: to me because I'm trying to Yeah, this is very

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Speaker 1: this is this is this is very wonky. I don't

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Speaker 1: know any other way to say. But the gist of

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Speaker 1: what he's saying is the average from like the the

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Speaker 1: sixties to the eighties, household sizes on average got smaller,

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Speaker 1: which means more people were living in more houses, so

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Speaker 1: there were fewer people on average per house that the

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Speaker 1: number of like people per house. By comparison, barely changed

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Speaker 1: at all from two thousand and one to two one,

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Speaker 1: so we didn't. It would have been unreasonable for the

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Speaker 1: housing rate to continue at the same rate it had

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Speaker 1: been from the sixties to the eighties, because we were

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Speaker 1: not like, the household size was not decreasing by a much, right,

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00:21:53,320 --> 00:21:57,040
Speaker 1: the social changes that led to us having more smaller

430
00:21:57,080 --> 00:22:00,399
Speaker 1: households had already happened, and so it would have been

431
00:22:00,480 --> 00:22:06,120
Speaker 1: unnecessary housing to a large extent. Um, it's you basically,

432
00:22:06,119 --> 00:22:08,680
Speaker 1: you can't infer a housing shortage by looking at housing

433
00:22:08,680 --> 00:22:12,480
Speaker 1: construction rates in isolation, which a lot of people do. Um,

434
00:22:12,560 --> 00:22:15,320
Speaker 1: And it's it's you know. I think the point here

435
00:22:15,359 --> 00:22:18,200
Speaker 1: is that there's a lot of money in convincing you

436
00:22:18,440 --> 00:22:20,600
Speaker 1: that this problem is simple and that the only thing

437
00:22:20,640 --> 00:22:24,200
Speaker 1: to do is deregulate. Right, If we deregulate construction, if

438
00:22:24,200 --> 00:22:28,320
Speaker 1: we deregulate zoning restrictions, that will solve the problem. Right

439
00:22:28,640 --> 00:22:31,600
Speaker 1: And and what what and obviously, like Potter I think

440
00:22:31,720 --> 00:22:34,359
Speaker 1: is because he does conclude that like zoning changes are

441
00:22:34,440 --> 00:22:38,040
Speaker 1: one aspect of helping with the crisis that we're in

442
00:22:38,119 --> 00:22:41,479
Speaker 1: right now. But the thing that he and Drum are

443
00:22:41,480 --> 00:22:43,960
Speaker 1: both saying is that the people who are saying this

444
00:22:44,040 --> 00:22:46,199
Speaker 1: is just about a lack of households or a lack

445
00:22:46,240 --> 00:22:50,320
Speaker 1: of quote unquote affordable households aren't actually looking at the

446
00:22:50,400 --> 00:22:53,560
Speaker 1: numbers as they really exist. They're they're taking like these

447
00:22:53,640 --> 00:22:58,520
Speaker 1: kind of broad summaries, um, and they're trying to torque

448
00:22:58,560 --> 00:23:01,680
Speaker 1: the actual numbers to say something that they don't, um,

449
00:23:01,720 --> 00:23:03,600
Speaker 1: in order to make a more simple in order to

450
00:23:03,600 --> 00:23:06,800
Speaker 1: present a simpler picture. Right. And it's a picture, specifically,

451
00:23:07,040 --> 00:23:10,919
Speaker 1: it is a picture that reduces the problem and removes

452
00:23:10,960 --> 00:23:15,760
Speaker 1: solutions like rent control and eviction moratoriums. Right, That's what's

453
00:23:15,800 --> 00:23:20,520
Speaker 1: going on here. Um. And yeah, there's there's a lot else.

454
00:23:20,840 --> 00:23:23,119
Speaker 1: One of the other major issues here is that And

455
00:23:23,160 --> 00:23:25,080
Speaker 1: this is something that Potter points out. When we're talking

456
00:23:25,080 --> 00:23:27,920
Speaker 1: about missing housing, we're not talking about a lack of houses.

457
00:23:27,960 --> 00:23:29,399
Speaker 1: Like you'll hear a lot of people say there's x

458
00:23:29,480 --> 00:23:32,040
Speaker 1: number of empty houses in the United States, more than enough,

459
00:23:32,720 --> 00:23:37,640
Speaker 1: and and that is true, but that's not necessarily vacant housing. Right.

460
00:23:37,760 --> 00:23:40,439
Speaker 1: Vacant housing is housing that is on the market and

461
00:23:40,480 --> 00:23:43,919
Speaker 1: available for people to purchase. And right now, the US

462
00:23:44,000 --> 00:23:47,159
Speaker 1: does have a historically low vacancy rate, so there are

463
00:23:47,320 --> 00:23:51,280
Speaker 1: fewer houses like per capita, fewer houses available for people

464
00:23:51,320 --> 00:23:53,560
Speaker 1: to rent than there have been in the past, even

465
00:23:53,560 --> 00:23:56,280
Speaker 1: though there's plenty of actual empty houses, because if those

466
00:23:56,280 --> 00:23:58,679
Speaker 1: houses aren't available to be rented, they're not vacant. And

467
00:23:58,720 --> 00:24:01,639
Speaker 1: a big reason why there's so much empty housing that

468
00:24:01,800 --> 00:24:06,679
Speaker 1: is not technically vacant is Airbnb. Yep. Yeah, so that

469
00:24:06,840 --> 00:24:10,080
Speaker 1: is a major factor here. Yeah, yeah, and we're going

470
00:24:10,119 --> 00:24:13,320
Speaker 1: to talk about that. But first, you know what's not Airbnb?

471
00:24:14,920 --> 00:24:19,720
Speaker 1: Maybe we were awkward. Any of our sponsors, probably Sophie.

472
00:24:19,720 --> 00:24:22,720
Speaker 1: Are we sponsored by Airbnb? Not that we would were,

473
00:24:22,960 --> 00:24:25,480
Speaker 1: not that we would have approved or signed off on,

474
00:24:25,720 --> 00:24:28,359
Speaker 1: but like we don't. We don't have control of the

475
00:24:28,680 --> 00:24:34,520
Speaker 1: m's randomly and Airbnb. Yeah, look, if you if you here,

476
00:24:34,600 --> 00:24:37,600
Speaker 1: here's what I'll say. If you hear an Airbnb ad

477
00:24:37,720 --> 00:24:43,080
Speaker 1: on the podcast, um, find your nearest Airbnb rental and

478
00:24:43,320 --> 00:24:46,680
Speaker 1: Hukamolotov cocktail through the window, whether or not there's people inside,

479
00:24:46,680 --> 00:24:50,360
Speaker 1: it doesn't matter to us legally. This is a joke. Yep.

480
00:24:52,000 --> 00:24:54,640
Speaker 1: I'm just gonna send the background here. Yeah, it's fine,

481
00:24:54,720 --> 00:24:59,480
Speaker 1: it's fine, it's fine, said something on fire today. Yeah,

482
00:25:00,080 --> 00:25:02,480
Speaker 1: I feel like I feel like that mean, if everything's

483
00:25:02,520 --> 00:25:04,560
Speaker 1: fine with the dog in the fire, and that's my

484
00:25:04,680 --> 00:25:07,200
Speaker 1: face right now. Everything's fine. That is your face right now.

485
00:25:07,440 --> 00:25:19,400
Speaker 1: You know what, I'm going to enjoy this moment. Oh gosh,

486
00:25:19,840 --> 00:25:24,920
Speaker 1: what a great day to be an American? When well,

487
00:25:26,880 --> 00:25:29,560
Speaker 1: I did when I watched those Philly fans sliding down

488
00:25:29,600 --> 00:25:32,480
Speaker 1: those greased up light poles. Every time I see Philadelphia

489
00:25:32,560 --> 00:25:34,919
Speaker 1: celebrate anything, I'm proud to be in a manner. I

490
00:25:35,000 --> 00:25:39,320
Speaker 1: was proud of the uh the New Yorkers at the

491
00:25:40,119 --> 00:25:46,840
Speaker 1: Yankees Astros game that heckled Ted Cruz. Proud of that too.

492
00:25:47,200 --> 00:25:50,720
Speaker 1: And I'm proud of Forbes for reporting on how bad

493
00:25:50,800 --> 00:25:54,680
Speaker 1: airbnb s are for housing vacancy rates, and I'm gonna

494
00:25:54,720 --> 00:25:57,560
Speaker 1: quote from them now. Research conducted by the Harvard Business

495
00:25:57,560 --> 00:25:59,840
Speaker 1: Review across the US found that airbnb is having a

496
00:26:00,000 --> 00:26:03,360
Speaker 1: intrimental impact on the housing stock as it encourages landlords

497
00:26:03,400 --> 00:26:05,800
Speaker 1: to move their properties out from the long term rental

498
00:26:06,000 --> 00:26:08,639
Speaker 1: and for sale markets and into the short term rental market.

499
00:26:08,920 --> 00:26:11,280
Speaker 1: A separate US study found that a one percent increase

500
00:26:11,320 --> 00:26:14,320
Speaker 1: in Airbnb listings leads to a point zero one eight

501
00:26:14,359 --> 00:26:17,000
Speaker 1: increase in rents and a point zero to six increase

502
00:26:17,000 --> 00:26:19,040
Speaker 1: in house prices. It may not seem like much on

503
00:26:19,080 --> 00:26:21,040
Speaker 1: the surface, but there's a cost creep for those looking

504
00:26:21,080 --> 00:26:25,879
Speaker 1: to rent long term or buy. So it's just again,

505
00:26:26,080 --> 00:26:28,120
Speaker 1: I'm not saying The Times is wrong when they say

506
00:26:28,119 --> 00:26:30,240
Speaker 1: that nimbies are part of the problem we have here,

507
00:26:30,480 --> 00:26:34,880
Speaker 1: but be cautious whenever somebody talks about the housing shortage

508
00:26:34,880 --> 00:26:37,399
Speaker 1: issue and just throws that out there or just frames

509
00:26:37,400 --> 00:26:39,760
Speaker 1: it as a how to housing shortage issue, right, rather

510
00:26:39,800 --> 00:26:42,439
Speaker 1: than a costs are creeping up because a bunch of

511
00:26:42,480 --> 00:26:45,600
Speaker 1: different kinds of capitalists are finding new ways to fund people,

512
00:26:45,960 --> 00:26:50,800
Speaker 1: which is the thing that's actually happening. Yeah. Um, Another

513
00:26:50,840 --> 00:26:54,240
Speaker 1: thing that's happening is that rent, like the rent surge,

514
00:26:54,359 --> 00:26:56,040
Speaker 1: and like the way it looks and stuff. And the

515
00:26:56,040 --> 00:26:58,679
Speaker 1: fact that the fact that the rent surge is being

516
00:26:58,720 --> 00:27:02,080
Speaker 1: attributed to a lack of housing construction and whatnot and

517
00:27:02,240 --> 00:27:06,199
Speaker 1: zoning issues, Um, that's heavily skewed by outlier cities, by

518
00:27:06,200 --> 00:27:09,400
Speaker 1: San Francisco. In other words, rent is increasing everywhere, right,

519
00:27:09,520 --> 00:27:11,840
Speaker 1: Everyone in every city is dealing with rent prices that

520
00:27:11,880 --> 00:27:15,760
Speaker 1: are surging. Rent prices that are surging in San Francisco

521
00:27:15,880 --> 00:27:18,520
Speaker 1: and a couple of other big cities because of zoning issues.

522
00:27:18,720 --> 00:27:22,159
Speaker 1: But rint prices in Atlanta or in Houston are not

523
00:27:22,200 --> 00:27:25,120
Speaker 1: necessarily surging because of those issues, but because of how

524
00:27:25,200 --> 00:27:27,600
Speaker 1: big like San Francisco and New York are and how

525
00:27:27,680 --> 00:27:31,040
Speaker 1: much it their outliers, And they fucked the data up,

526
00:27:31,080 --> 00:27:33,960
Speaker 1: and so the picture they present in large is not

527
00:27:34,119 --> 00:27:37,520
Speaker 1: accurate to why is most people's rent raising? Right? Does

528
00:27:37,560 --> 00:27:40,920
Speaker 1: that make sense? Yeah? And I'm gonna I'm gonna quote

529
00:27:40,920 --> 00:27:45,119
Speaker 1: again from Potters analysis here there's essentially zero correlation. The

530
00:27:45,160 --> 00:27:48,080
Speaker 1: metros with the largest rent increases had added population and

531
00:27:48,119 --> 00:27:51,520
Speaker 1: added housing ratios no different than metros with smaller rent increases.

532
00:27:51,880 --> 00:27:53,840
Speaker 1: For example, for instance, between two thousand and one and

533
00:27:53,880 --> 00:27:56,600
Speaker 1: two thousand nineteen, the San Francisco Bay Area added around

534
00:27:56,600 --> 00:27:59,119
Speaker 1: three hundred and thirty six thousand people, but only built

535
00:27:59,200 --> 00:28:02,560
Speaker 1: nine thousand new housing units. This gives an added population

536
00:28:02,640 --> 00:28:05,520
Speaker 1: added housing ratio of about three point five four, much

537
00:28:05,600 --> 00:28:08,600
Speaker 1: higher than both the national and regional average household size.

538
00:28:08,840 --> 00:28:11,040
Speaker 1: This seems like it would indicate many more households than

539
00:28:11,080 --> 00:28:13,480
Speaker 1: homes got added, which we'd expect to push prices up,

540
00:28:13,640 --> 00:28:16,360
Speaker 1: and indeed, San Francisco saw a rent increase of over

541
00:28:16,440 --> 00:28:19,159
Speaker 1: fifty three during this period, one of the highest in

542
00:28:19,200 --> 00:28:22,639
Speaker 1: the country. The problem. The Atlanta metro area saw almost

543
00:28:22,720 --> 00:28:25,960
Speaker 1: the same added population over added housing ratio, but it

544
00:28:26,000 --> 00:28:28,920
Speaker 1: had a much lower rent increase. Atlanta added six hundred

545
00:28:28,960 --> 00:28:31,320
Speaker 1: and fifty three thousand people over the same time period

546
00:28:31,520 --> 00:28:33,639
Speaker 1: and only built a hundred and eighty six thousand homes

547
00:28:33,680 --> 00:28:36,440
Speaker 1: for an added population added housing ratio of three point

548
00:28:36,440 --> 00:28:39,680
Speaker 1: five one, and Miami added almost five hundred thousand people

549
00:28:39,720 --> 00:28:42,160
Speaker 1: but only ninety eight thousand homes for an added population

550
00:28:42,200 --> 00:28:45,360
Speaker 1: housing ratio of over five. But Atlanta and Miami saw

551
00:28:45,360 --> 00:28:50,440
Speaker 1: rent increases of just two and seventeen percent, respectively, So again,

552
00:28:50,880 --> 00:28:53,560
Speaker 1: it's just not as simple as that number alone. And

553
00:28:53,640 --> 00:28:56,120
Speaker 1: I don't know, I'm probably harping on this too much,

554
00:28:56,240 --> 00:28:57,760
Speaker 1: so we're we're going to get out of the number

555
00:28:57,760 --> 00:29:00,640
Speaker 1: ship now. I I apologize. I just wanted to make

556
00:29:00,640 --> 00:29:03,200
Speaker 1: the point that the people who just say this is

557
00:29:03,240 --> 00:29:06,040
Speaker 1: all about zoning, this is all about housing construction, are

558
00:29:06,080 --> 00:29:08,840
Speaker 1: trying to funk you, right like they are trying to

559
00:29:09,000 --> 00:29:11,800
Speaker 1: enable others to fuck you, and you should not take

560
00:29:11,840 --> 00:29:14,080
Speaker 1: them at their word. I mean, this is the classic

561
00:29:14,120 --> 00:29:16,480
Speaker 1: trick and trying to blame someone else so that the

562
00:29:16,480 --> 00:29:19,000
Speaker 1: people who are actually profiting and making the most money

563
00:29:19,120 --> 00:29:21,920
Speaker 1: look innocent, kind of like the whole recycling bit. We know,

564
00:29:22,320 --> 00:29:24,360
Speaker 1: we know what, Like they're trying to blame the individual

565
00:29:24,400 --> 00:29:27,560
Speaker 1: and severalizing these huge corporations are fucking over the environment,

566
00:29:27,640 --> 00:29:29,000
Speaker 1: but they don't want to talk about it because they

567
00:29:29,000 --> 00:29:31,240
Speaker 1: don't want to lose money. So this is how we're

568
00:29:31,240 --> 00:29:33,760
Speaker 1: gonna we scope this. Yeah, we're going to We're gonna

569
00:29:33,760 --> 00:29:36,120
Speaker 1: scope this is like there's too much regulation, not like yeah,

570
00:29:36,120 --> 00:29:38,360
Speaker 1: but you guys are also jacking the prices up, right,

571
00:29:38,400 --> 00:29:41,880
Speaker 1: like you're you're also like you're also like colluding to

572
00:29:42,000 --> 00:29:45,920
Speaker 1: fun people over by. Yeah anyway, and you're doing ship

573
00:29:45,960 --> 00:29:48,960
Speaker 1: like Airbnb, like you've done a capitalists that found a

574
00:29:48,960 --> 00:29:50,920
Speaker 1: bunch of different ways to funk with housing in the

575
00:29:51,000 --> 00:29:53,960
Speaker 1: last fifteen years. And it's not just a construction issue

576
00:29:54,040 --> 00:29:57,960
Speaker 1: or z anyway saying that rents high because of the

577
00:29:58,480 --> 00:30:02,560
Speaker 1: lack of quantity of places available, but like it's really

578
00:30:02,600 --> 00:30:05,200
Speaker 1: not the case. No, otherwise it would be raising its

579
00:30:05,200 --> 00:30:11,320
Speaker 1: similar rates in these other cities where the numbersome. Yeah yeah, yeah,

580
00:30:11,360 --> 00:30:19,000
Speaker 1: So anyway, you can whatever umi rent you wrote that

581
00:30:19,120 --> 00:30:23,120
Speaker 1: your rent is too damn high. Is too damn high,

582
00:30:23,200 --> 00:30:25,800
Speaker 1: And there's a number of reasons for it. And anyone

583
00:30:25,840 --> 00:30:28,200
Speaker 1: trying to say it's this one simple thing that is

584
00:30:28,240 --> 00:30:31,280
Speaker 1: also really good for developers is probably trying to fuck you.

585
00:30:31,600 --> 00:30:34,200
Speaker 1: So now we're going to start talking about assholes, which

586
00:30:34,240 --> 00:30:38,720
Speaker 1: is fun and more more are strong suit than numbers.

587
00:30:39,000 --> 00:30:40,920
Speaker 1: So the first thing you need to know about, or

588
00:30:40,960 --> 00:30:42,480
Speaker 1: the first person you need to know about, is a

589
00:30:42,520 --> 00:30:46,520
Speaker 1: guy named Jeffrey Roper. Jeffrey is a businessman who describes

590
00:30:46,560 --> 00:30:49,960
Speaker 1: himself as a numbers nerd and formerly worked as Alaska

591
00:30:50,000 --> 00:30:54,080
Speaker 1: Airlines as director of revenue management in the nineteen eighties. Now, anybody,

592
00:30:54,120 --> 00:30:56,800
Speaker 1: anybody who says there are a numbers guy to you,

593
00:30:57,360 --> 00:30:59,800
Speaker 1: just like them immediately. I don't know, I like, I

594
00:30:59,800 --> 00:31:02,840
Speaker 1: like my accountant, the guy who does something. But if

595
00:31:02,880 --> 00:31:05,720
Speaker 1: somebody like if that's their first thing that they want

596
00:31:05,760 --> 00:31:08,920
Speaker 1: you to know about them, red flag, red flag flag

597
00:31:09,680 --> 00:31:13,680
Speaker 1: date that person. Okay, So having the last name Roper,

598
00:31:13,840 --> 00:31:15,440
Speaker 1: that makes me think of the guy who used to

599
00:31:15,440 --> 00:31:18,959
Speaker 1: be Ebert's friend and probably killed him. That's my head.

600
00:31:19,120 --> 00:31:23,600
Speaker 1: They mentioned anything about like their credit throwback, I'm just

601
00:31:23,760 --> 00:31:26,560
Speaker 1: I'm just saying they mentioned anything about their credit score,

602
00:31:26,560 --> 00:31:29,000
Speaker 1: if they mentioned anything about numbers, that they sure anything

603
00:31:29,040 --> 00:31:32,920
Speaker 1: like that in their dating profile. Do not match with them. Wait,

604
00:31:33,000 --> 00:31:36,640
Speaker 1: have you had someone girl put the credit score? Gosh yeah,

605
00:31:36,640 --> 00:31:39,000
Speaker 1: more more more when I was more, when I was

606
00:31:39,040 --> 00:31:42,720
Speaker 1: living in Los Angeles. But okay, yeah, that was a thing.

607
00:31:42,960 --> 00:31:46,880
Speaker 1: Maybe maybe Lantis are not impressive, so therefore they out

608
00:31:46,920 --> 00:31:49,120
Speaker 1: on purpose. I don't know, because I did not say that.

609
00:31:49,120 --> 00:31:51,080
Speaker 1: That's a new one to say. All right, Robert tell

610
00:31:51,120 --> 00:31:56,400
Speaker 1: us about the numbers. Get our money is what we're

611
00:31:56,440 --> 00:32:00,960
Speaker 1: calling him. Actually our money. Okay, tell us about our money. Yeah, yeah,

612
00:32:01,080 --> 00:32:02,960
Speaker 1: so he's a numbers nerd. He used to work as

613
00:32:03,000 --> 00:32:05,960
Speaker 1: Alaska Airlines director of revenue management in the nineteen eighties.

614
00:32:06,000 --> 00:32:09,280
Speaker 1: And look, Alaska is like the least shitty domestic airline

615
00:32:09,280 --> 00:32:14,640
Speaker 1: that we have, but when dragging people off the plane,

616
00:32:14,720 --> 00:32:18,840
Speaker 1: So yeah, they don't do that now, I will say this.

617
00:32:19,080 --> 00:32:23,040
Speaker 1: They absolutely while Roper was director of revenue management, robbed

618
00:32:23,120 --> 00:32:25,160
Speaker 1: us all of about a billion dollars back in the

619
00:32:25,240 --> 00:32:27,520
Speaker 1: nineteen eighties. So we're gonna talk about how that happens,

620
00:32:27,560 --> 00:32:31,360
Speaker 1: like robbed us consumers, like stole illegally, criminally stole a

621
00:32:31,400 --> 00:32:35,000
Speaker 1: billion dollars. It's cool, Yeah, so compete. They're not the

622
00:32:35,000 --> 00:32:37,840
Speaker 1: only actually with a number of airlines stole collectively a billion,

623
00:32:37,880 --> 00:32:41,000
Speaker 1: but Alaska was kind of leading the pack anyway, competing airlines.

624
00:32:41,080 --> 00:32:45,240
Speaker 1: What happened is competing airlines started using price setting software

625
00:32:45,520 --> 00:32:47,800
Speaker 1: and they're different computers would all kind of share data

626
00:32:47,880 --> 00:32:50,560
Speaker 1: on planned routes and prices with each other to make

627
00:32:50,600 --> 00:32:54,520
Speaker 1: sure that like nobody was undercutting anyone else. And Jeffrey

628
00:32:54,560 --> 00:32:56,600
Speaker 1: was a big part of this. He brings in price

629
00:32:56,640 --> 00:32:59,360
Speaker 1: setting software to Alaska and he helps set up this system,

630
00:32:59,600 --> 00:33:03,120
Speaker 1: which they're very happy with because it helps avoid a

631
00:33:03,200 --> 00:33:05,760
Speaker 1: price war in the nineteen eighties. And when you frame

632
00:33:05,800 --> 00:33:07,200
Speaker 1: it as a price war, it sounds like, oh, they

633
00:33:07,240 --> 00:33:09,600
Speaker 1: avoided a price war with this software. That's good. No,

634
00:33:09,760 --> 00:33:13,320
Speaker 1: it's not. What a price war is is companies competing

635
00:33:13,640 --> 00:33:16,200
Speaker 1: to give you the best price so that you will

636
00:33:16,320 --> 00:33:19,640
Speaker 1: choose their service. Right, it's good for consumers when a

637
00:33:19,720 --> 00:33:22,280
Speaker 1: price war occurs. When you avoid a price war, it

638
00:33:22,320 --> 00:33:26,040
Speaker 1: means you're getting fucked, right, price war amongst each other.

639
00:33:26,280 --> 00:33:29,120
Speaker 1: So they cannot have to compete for businesses unless they're

640
00:33:29,160 --> 00:33:31,400
Speaker 1: in like I'm guessing they're doing like the prices right

641
00:33:31,520 --> 00:33:34,320
Speaker 1: type of where this's just a dollar less Yeah. That

642
00:33:34,800 --> 00:33:37,920
Speaker 1: that well, that normally what would happen is you would

643
00:33:37,920 --> 00:33:39,440
Speaker 1: not it would kind of be a little bit of

644
00:33:39,440 --> 00:33:42,239
Speaker 1: a black box, and they would set their rates just

645
00:33:42,280 --> 00:33:44,040
Speaker 1: based on this is what we think is fair, and

646
00:33:44,080 --> 00:33:46,640
Speaker 1: then kind of over time as they see what consumers

647
00:33:46,640 --> 00:33:48,280
Speaker 1: are choosing, you know, than like maybe we need to

648
00:33:48,320 --> 00:33:50,200
Speaker 1: lower rates or maybe we can raise them a little.

649
00:33:50,640 --> 00:33:54,200
Speaker 1: What they're doing with these softwares is they're all communicating

650
00:33:54,320 --> 00:33:56,240
Speaker 1: with each other to be like, this is what we

651
00:33:56,280 --> 00:33:59,200
Speaker 1: are charging. Oh, we can all afford to charge more,

652
00:33:59,560 --> 00:34:02,840
Speaker 1: So the prices just start raising, and just start raising,

653
00:34:02,880 --> 00:34:05,800
Speaker 1: and just start raising. Right. Price wars occur when corporations

654
00:34:05,840 --> 00:34:09,080
Speaker 1: fight to lower prices while still staying profitable. Um, this

655
00:34:09,160 --> 00:34:12,520
Speaker 1: is good, broadly speaking for consumers. If capitalism worked the

656
00:34:12,560 --> 00:34:15,319
Speaker 1: way my high school textbook said it did, then this

657
00:34:15,360 --> 00:34:17,239
Speaker 1: would this would be an example of why it's a

658
00:34:17,280 --> 00:34:20,080
Speaker 1: good system. Right. But that's not what happens. What really

659
00:34:20,120 --> 00:34:23,080
Speaker 1: happens is that companies like these airlines do things called

660
00:34:23,400 --> 00:34:27,400
Speaker 1: do so what's called price fixing, which is illegal Alaska

661
00:34:27,600 --> 00:34:30,279
Speaker 1: under while you know, this system that Roper helps set

662
00:34:30,360 --> 00:34:34,160
Speaker 1: up is illegal price fixing. The Department of Justice says

663
00:34:34,200 --> 00:34:37,120
Speaker 1: these companies are all illegally fixing prices. I'm not like

664
00:34:37,480 --> 00:34:39,840
Speaker 1: declaring this price fixing because I don't like it. The

665
00:34:39,880 --> 00:34:44,280
Speaker 1: Department of Justice says they did a crime. Did anybody

666
00:34:44,320 --> 00:34:48,440
Speaker 1: actually get absolutely not, well a little bit so. The

667
00:34:49,040 --> 00:34:51,920
Speaker 1: d o J accuses Alaska and several other airlines of

668
00:34:52,000 --> 00:34:56,120
Speaker 1: artificially inflating prices using this system, which costs taxpayers about

669
00:34:56,120 --> 00:34:59,640
Speaker 1: a billion dollars between nineteen and nineteen or ninety two.

670
00:35:00,080 --> 00:35:04,080
Speaker 1: The government gets settlements and consent decrees out of eight airlines,

671
00:35:04,120 --> 00:35:07,920
Speaker 1: including Alaska, which is like, again, when you're a big

672
00:35:07,960 --> 00:35:10,440
Speaker 1: company and you have lawyers, nobody goes to prison for

673
00:35:10,480 --> 00:35:15,600
Speaker 1: this ship. Sometimes you'd kick a government some money. Yeah, exactly. Now,

674
00:35:15,719 --> 00:35:19,200
Speaker 1: during this investigation, federal agents remove a computer and documents

675
00:35:19,239 --> 00:35:22,200
Speaker 1: from Roper's office because again he's kind of one of

676
00:35:22,200 --> 00:35:24,600
Speaker 1: the ringleaders of this. He will later claim in an

677
00:35:24,680 --> 00:35:27,160
Speaker 1: interview quote, we all got called up before the Department

678
00:35:27,200 --> 00:35:29,680
Speaker 1: of Justice in the early nineteen eighties because we were colluding.

679
00:35:29,920 --> 00:35:36,200
Speaker 1: We had no idea, of course, of course, Yeah, sure, buddy, Yes,

680
00:35:36,280 --> 00:35:38,799
Speaker 1: I'm certain you had no idea what that was. Oh

681
00:35:38,840 --> 00:35:41,520
Speaker 1: my god, we were price fixing. I don't know all

682
00:35:41,560 --> 00:35:46,920
Speaker 1: our price fixing was price fixing. I didn't know. It

683
00:35:46,960 --> 00:35:48,720
Speaker 1: seemed like we were just making a lot of money.

684
00:35:49,200 --> 00:35:52,759
Speaker 1: We're just so good. It's very funny that he says that, um,

685
00:35:52,960 --> 00:35:57,640
Speaker 1: nobody gets really punished again. Whatever. Whatever settlements they make

686
00:35:57,680 --> 00:36:00,680
Speaker 1: are kind of slap on the wristy. After the Roper

687
00:36:00,800 --> 00:36:03,640
Speaker 1: leaves the United States for Central and Eastern Europe to

688
00:36:03,760 --> 00:36:06,880
Speaker 1: funk with people's lives in post Soviet Europe, he's he's helping.

689
00:36:07,280 --> 00:36:09,720
Speaker 1: He's one of these capitalists who goes over there because

690
00:36:09,719 --> 00:36:12,080
Speaker 1: he's like, there's a lot of money to be made

691
00:36:12,360 --> 00:36:15,360
Speaker 1: in setting the stage for Vladimir Putin's rise to power

692
00:36:15,480 --> 00:36:20,080
Speaker 1: by fucking with all these newly privatized industries and siphoning

693
00:36:20,600 --> 00:36:24,480
Speaker 1: money and access to future money away from any kind

694
00:36:24,520 --> 00:36:27,080
Speaker 1: of like regular people or social safety net that might

695
00:36:27,080 --> 00:36:31,400
Speaker 1: be built, which will create ideal grounds for authoritarianism. Anyway,

696
00:36:31,400 --> 00:36:34,319
Speaker 1: it's whatever, it's good. Stuff made money, he made. He

697
00:36:34,360 --> 00:36:35,640
Speaker 1: makes a lot of money doing this. And then he

698
00:36:35,640 --> 00:36:37,680
Speaker 1: gets back to the US and he's like, you know what,

699
00:36:37,760 --> 00:36:40,520
Speaker 1: I realized, the US apartment rental industry is stuck in

700
00:36:40,560 --> 00:36:43,240
Speaker 1: the past. It looks like these emerging markets over in Europe.

701
00:36:43,280 --> 00:36:46,719
Speaker 1: You know, it's it's old fashioned, it's too slow. And

702
00:36:46,920 --> 00:36:50,000
Speaker 1: the thing that he finds that really discusts him is

703
00:36:50,040 --> 00:36:53,480
Speaker 1: that apartment managers are quote basically pricing their product on

704
00:36:53,520 --> 00:36:57,440
Speaker 1: a paper napkin, which he seems to have found viscerally offensive. Now,

705
00:36:57,480 --> 00:37:01,040
Speaker 1: what's going on here is that to some extent, renting

706
00:37:01,120 --> 00:37:03,200
Speaker 1: is more of a human business back then, so people

707
00:37:03,239 --> 00:37:06,719
Speaker 1: are like coming in and sitting down and their landlord saying, well,

708
00:37:06,760 --> 00:37:08,960
Speaker 1: like this is what again? You know, there's haggling and

709
00:37:09,000 --> 00:37:12,200
Speaker 1: stuff and back and forth. And you know, if you've

710
00:37:12,239 --> 00:37:14,360
Speaker 1: ever haggled with a small landlord or gotten going to

711
00:37:14,360 --> 00:37:16,279
Speaker 1: give you a break because like ship got sucked up

712
00:37:16,280 --> 00:37:17,799
Speaker 1: in your life, you know what I'm talking about. Right.

713
00:37:18,680 --> 00:37:21,480
Speaker 1: You can say what you will about how inherently predatory,

714
00:37:21,520 --> 00:37:24,080
Speaker 1: you know, landlording is or isn't or whatever, But like,

715
00:37:24,320 --> 00:37:26,880
Speaker 1: at the end of the day, it's better when you

716
00:37:27,000 --> 00:37:29,319
Speaker 1: can be a human being sitting across the table from

717
00:37:29,360 --> 00:37:33,920
Speaker 1: another human being, because sometimes that matters, right like sometimes

718
00:37:33,960 --> 00:37:37,480
Speaker 1: sometimes like small landlords can be shitty and terrible too.

719
00:37:37,719 --> 00:37:40,560
Speaker 1: But as a general rule, I always every time I

720
00:37:40,600 --> 00:37:42,600
Speaker 1: had the least from a huge company, I found the

721
00:37:42,680 --> 00:37:45,680
Speaker 1: monolithic slow to respond to problems and cruel in their

722
00:37:45,719 --> 00:37:47,920
Speaker 1: application of things like fees and penalties. Where I was

723
00:37:47,960 --> 00:37:51,320
Speaker 1: able to like talk shit out of little landlords. And

724
00:37:51,320 --> 00:37:54,440
Speaker 1: and you know now that I never had a small landlord.

725
00:37:54,440 --> 00:37:56,839
Speaker 1: Fucking steel shipped from me. But if I prefer one

726
00:37:56,920 --> 00:37:59,640
Speaker 1: situation to the other, right, I think out of the

727
00:37:59,640 --> 00:38:03,320
Speaker 1: twenty twenty years that I rented, one one was a

728
00:38:03,440 --> 00:38:06,520
Speaker 1: big corporation and I hated it. It fucking sucks. I

729
00:38:06,520 --> 00:38:08,200
Speaker 1: want to at least be able to call my goddamn

730
00:38:08,280 --> 00:38:10,919
Speaker 1: landlord on the phone and get a person and deal

731
00:38:10,960 --> 00:38:13,000
Speaker 1: with a problem. You know. Well I also had the

732
00:38:13,040 --> 00:38:16,480
Speaker 1: agil problem where the guy who came to fix things,

733
00:38:16,520 --> 00:38:18,200
Speaker 1: a maintenance man, it was hitting on me. So I

734
00:38:18,200 --> 00:38:22,399
Speaker 1: hadn't just come into my house. So yeah, I had

735
00:38:22,760 --> 00:38:25,719
Speaker 1: there was that I had the handyman my last yet

736
00:38:25,800 --> 00:38:28,160
Speaker 1: and my last one didn't hit on me. No, no, no,

737
00:38:28,360 --> 00:38:30,440
Speaker 1: he would let He would come in and lecture me

738
00:38:30,520 --> 00:38:33,680
Speaker 1: about life choices and tell me about you know, he

739
00:38:33,760 --> 00:38:39,719
Speaker 1: was just really misogynistic. It was I think it's it's

740
00:38:39,760 --> 00:38:44,520
Speaker 1: equally bad. I had a gloriously opposite experience. And so

741
00:38:44,719 --> 00:38:48,239
Speaker 1: when I was renting a slum it was legally his

742
00:38:48,239 --> 00:38:50,319
Speaker 1: own servants quarters. It was one room. I lived in

743
00:38:50,360 --> 00:38:55,400
Speaker 1: it with two other men. Um falling apart the ceiling

744
00:38:55,440 --> 00:38:59,040
Speaker 1: collapsed on me while I was showering. Um, And the

745
00:38:59,120 --> 00:39:02,080
Speaker 1: next day I called the landlord and I'm like, hey,

746
00:39:02,560 --> 00:39:06,440
Speaker 1: the ceiling fell in on me. Whif I was shower well,

747
00:39:06,840 --> 00:39:09,400
Speaker 1: it was like nighttime. I tend to shower like it

748
00:39:09,480 --> 00:39:13,120
Speaker 1: was like it was like it was like something like that. Immediately,

749
00:39:13,640 --> 00:39:15,560
Speaker 1: I don't remember if I called him. Maybe I called

750
00:39:15,560 --> 00:39:17,640
Speaker 1: immediately and he wasn't right anyway, I get, I get

751
00:39:17,640 --> 00:39:19,120
Speaker 1: in touch with him and he's like, i'll get I'll

752
00:39:19,120 --> 00:39:21,880
Speaker 1: get my guy right over. So he sends over a

753
00:39:21,920 --> 00:39:24,080
Speaker 1: repair man and he's just kind of this like old

754
00:39:24,160 --> 00:39:26,120
Speaker 1: hippie looking dude and he comes over and he looks

755
00:39:26,200 --> 00:39:27,960
Speaker 1: up at the hole and he's like, yeah, we're not

756
00:39:28,000 --> 00:39:29,960
Speaker 1: gonna be able to fix this for a while. And

757
00:39:30,000 --> 00:39:32,320
Speaker 1: then he says, do you want to buy some weed?

758
00:39:32,560 --> 00:39:35,799
Speaker 1: And I said yes, And he was selling fifty dollar

759
00:39:35,880 --> 00:39:39,000
Speaker 1: rounds as of pretty solid popcorn that's like mids. It

760
00:39:39,080 --> 00:39:41,319
Speaker 1: was good, it was a good deal. It was worth it.

761
00:39:41,320 --> 00:39:43,400
Speaker 1: It was like several months where we didn't have a

762
00:39:43,440 --> 00:39:46,919
Speaker 1: ceiling over the shower, but it was a pretty good

763
00:39:46,960 --> 00:39:49,120
Speaker 1: weed hook up. We were poor as ship, so a

764
00:39:49,239 --> 00:39:51,959
Speaker 1: fifty dollar rounds and mids that's not a bad deal.

765
00:39:52,120 --> 00:39:56,000
Speaker 1: You know, well, it must be wonderful to you. Don't

766
00:39:56,000 --> 00:39:59,000
Speaker 1: get that. You don't get that experience with a big

767
00:39:59,040 --> 00:40:03,200
Speaker 1: corporate landlord. That's the kind of landlord you get when

768
00:40:03,200 --> 00:40:05,880
Speaker 1: your landlord is yeah, breaking a number of different laws.

769
00:40:05,920 --> 00:40:11,520
Speaker 1: But basically, chill, um, look get this is I yeah again.

770
00:40:11,560 --> 00:40:14,120
Speaker 1: You can have whatever Marxist opinions you want to have

771
00:40:14,160 --> 00:40:17,440
Speaker 1: on landlords. I'm talking about like, from a human being perspective,

772
00:40:17,520 --> 00:40:20,560
Speaker 1: it's always better to deal with a person than a

773
00:40:20,680 --> 00:40:27,520
Speaker 1: giant edifice. So whatever. Um. Jeffrey Roper's entire business attitude

774
00:40:27,600 --> 00:40:30,799
Speaker 1: revolves around making that kind of thing where like, if

775
00:40:30,800 --> 00:40:32,880
Speaker 1: you're living on the margins, you can kind of skate

776
00:40:32,920 --> 00:40:35,600
Speaker 1: by because you're able to like talk to someone on

777
00:40:35,640 --> 00:40:38,080
Speaker 1: a human level. He wants to make that impossible, right,

778
00:40:38,160 --> 00:40:43,440
Speaker 1: because that that is a barrier to profits. Exactly exactly,

779
00:40:44,040 --> 00:40:47,439
Speaker 1: you have predicted where we're going here. So in two

780
00:40:47,440 --> 00:40:50,320
Speaker 1: thousand four he gets hired by a company called real

781
00:40:50,400 --> 00:40:54,440
Speaker 1: Page as its principal scientist. They bought software from Camden

782
00:40:54,480 --> 00:40:57,080
Speaker 1: Property Trust, which is a large owner of apartment buildings,

783
00:40:57,080 --> 00:40:59,960
Speaker 1: that was supposed to help them maximize profits. Now, pretty

784
00:41:00,080 --> 00:41:02,279
Speaker 1: sleep back in the Napkin days will call him. Even

785
00:41:02,320 --> 00:41:05,200
Speaker 1: big corporate apartment managers had kind of been left to guests,

786
00:41:05,320 --> 00:41:07,880
Speaker 1: you know. They they Even if you were working with

787
00:41:07,920 --> 00:41:10,440
Speaker 1: a big corporation, it was still kind of like eventually

788
00:41:10,520 --> 00:41:12,360
Speaker 1: some guy's gonna sit down and just kind of guess

789
00:41:12,600 --> 00:41:15,400
Speaker 1: what he thinks he can get out of you, right um.

790
00:41:15,640 --> 00:41:17,680
Speaker 1: Roper knew that he could do better, just as he'd

791
00:41:17,680 --> 00:41:21,480
Speaker 1: done in Alaska by introducing machines and price fixing to

792
00:41:21,560 --> 00:41:24,839
Speaker 1: the well legally not price fixing yet, although it might

793
00:41:24,880 --> 00:41:27,239
Speaker 1: prove to be price fixing in the future. We'll see

794
00:41:27,280 --> 00:41:29,440
Speaker 1: what the d o J says. But legally he has

795
00:41:29,480 --> 00:41:32,560
Speaker 1: not committed price fixing in the rental industry to an

796
00:41:32,560 --> 00:41:35,080
Speaker 1: extent that has been proven. I'm gonna quote from a

797
00:41:35,080 --> 00:41:39,680
Speaker 1: pro publica investigation. Roper quickly realized he required data, a

798
00:41:39,680 --> 00:41:42,520
Speaker 1: lot of data to get the algorithm working properly. He

799
00:41:42,560 --> 00:41:45,160
Speaker 1: began building a master data warehouse that pulled in client

800
00:41:45,239 --> 00:41:48,640
Speaker 1: data from other real page applications, such as those releasing managers.

801
00:41:48,880 --> 00:41:51,320
Speaker 1: A proof of concept version of the software had performed

802
00:41:51,320 --> 00:41:54,360
Speaker 1: well in tests at townhouses Camden offered for rent in

803
00:41:54,400 --> 00:41:56,920
Speaker 1: its home city in the of Houston. At the time,

804
00:41:56,960 --> 00:41:59,800
Speaker 1: the street behind Camden's townhouses was shut down while to

805
00:41:59,840 --> 00:42:02,520
Speaker 1: grow Shy Store was being built. Leasing staff wanted to

806
00:42:02,560 --> 00:42:04,840
Speaker 1: discount rent for the town houses because of the nuisance,

807
00:42:04,840 --> 00:42:08,480
Speaker 1: said Kip Zacharias, who worked with Camden as a consultant. Instead,

808
00:42:08,600 --> 00:42:11,440
Speaker 1: yield Star, which is the company that's selling the software,

809
00:42:11,600 --> 00:42:14,440
Speaker 1: suggested boosting rents. We were like, guys, just try it.

810
00:42:14,560 --> 00:42:17,759
Speaker 1: Zacharias said. The units ended up renting for significantly more

811
00:42:17,760 --> 00:42:19,920
Speaker 1: than staff and expected. He said that was kind of

812
00:42:19,960 --> 00:42:22,120
Speaker 1: the Eureka moment. If you listen to your gut, you

813
00:42:22,120 --> 00:42:25,400
Speaker 1: would have lowered your price. Such agents sometimes hesitated to

814
00:42:25,440 --> 00:42:28,279
Speaker 1: push prints higher. Roper said they were often peers of

815
00:42:28,320 --> 00:42:30,959
Speaker 1: the people they were renting to. We said, there's way

816
00:42:30,960 --> 00:42:33,719
Speaker 1: too much empathy going on here. This is one of

817
00:42:33,719 --> 00:42:36,120
Speaker 1: the reasons why we wanted to get pricing off site,

818
00:42:36,400 --> 00:42:40,000
Speaker 1: unimpeded by human worries. Yield Stars price increases sometimes yet

819
00:42:40,080 --> 00:42:43,600
Speaker 1: led to more attendants leaving. So He's literally is saying

820
00:42:43,600 --> 00:42:45,759
Speaker 1: what you were saying. There's too much empathy in the

821
00:42:45,800 --> 00:42:48,560
Speaker 1: process as it exists. We gotta get rid of that

822
00:42:48,600 --> 00:42:52,239
Speaker 1: ship so we can really fuck people right right. We

823
00:42:52,280 --> 00:42:54,080
Speaker 1: need We need to get all the human aspect. I

824
00:42:54,200 --> 00:42:58,520
Speaker 1: like that, don't be human if you're or if you're

825
00:42:58,520 --> 00:43:01,440
Speaker 1: just a person at a leasing office with discretion and

826
00:43:01,640 --> 00:43:03,880
Speaker 1: a person comes in and they're like, you know, they

827
00:43:03,920 --> 00:43:06,160
Speaker 1: reminding your mom and your aunt, your cousin and your friend,

828
00:43:06,280 --> 00:43:08,319
Speaker 1: or like you know you have a good rapport with them,

829
00:43:08,400 --> 00:43:09,640
Speaker 1: They're like, yeah, I want to make sure you get

830
00:43:09,640 --> 00:43:11,640
Speaker 1: a good deal, like I work. Again, I've had that

831
00:43:11,719 --> 00:43:16,640
Speaker 1: happen to me. Um It's it's like this is and

832
00:43:16,640 --> 00:43:18,680
Speaker 1: and the system, by the way, that system that when

833
00:43:18,680 --> 00:43:21,440
Speaker 1: I'm describing was not idyllic. It was still Badrick was

834
00:43:21,480 --> 00:43:25,160
Speaker 1: still too high, but this has made it much worse. Right,

835
00:43:25,640 --> 00:43:28,040
Speaker 1: So he's the one that began like, no, really, every

836
00:43:28,160 --> 00:43:32,360
Speaker 1: year you should increase and they'll never question it. We

837
00:43:32,480 --> 00:43:36,080
Speaker 1: just do it to every single person uniformly, and then

838
00:43:36,280 --> 00:43:38,520
Speaker 1: you know, nobody's it's not personal. This is just the

839
00:43:39,400 --> 00:43:41,120
Speaker 1: price of housing now, and this is just the way

840
00:43:41,160 --> 00:43:42,640
Speaker 1: that it works. And you know, we're just trying to

841
00:43:42,840 --> 00:43:45,840
Speaker 1: We found that you're underneath the the and this is

842
00:43:45,840 --> 00:43:47,600
Speaker 1: what it means. Also, when like you get that letter

843
00:43:47,680 --> 00:43:50,440
Speaker 1: saying you know your house is under priced or lower

844
00:43:50,440 --> 00:43:52,759
Speaker 1: than like market value or whatever, so we have to

845
00:43:52,800 --> 00:43:55,560
Speaker 1: increase it by x amount. That's what the value they're

846
00:43:55,600 --> 00:43:58,400
Speaker 1: quoting on is the ship that this software hands them,

847
00:43:58,400 --> 00:44:04,560
Speaker 1: which is not necessarily a real thing. It is a

848
00:44:04,640 --> 00:44:08,000
Speaker 1: thing that the machine calculated by doing a machine version

849
00:44:08,080 --> 00:44:10,520
Speaker 1: of price fixing. That again, as of yet has not

850
00:44:10,680 --> 00:44:12,840
Speaker 1: been ruled to be price fixing by the d o J,

851
00:44:13,200 --> 00:44:15,680
Speaker 1: but may prove to be ruled price fixing by the

852
00:44:15,760 --> 00:44:19,600
Speaker 1: d o J in the near future. We'll see, okay.

853
00:44:19,800 --> 00:44:22,920
Speaker 1: Camden noted their turnover was about fifteen percent higher in

854
00:44:23,000 --> 00:44:25,719
Speaker 1: two thousand six after it started using yield Star, which

855
00:44:25,760 --> 00:44:30,200
Speaker 1: is again that's the software that Roper is managing. Despite this,

856
00:44:30,320 --> 00:44:34,160
Speaker 1: revenue grew by seven point four percent, So fifteen percent

857
00:44:34,320 --> 00:44:37,600
Speaker 1: of their of their clients like leave the apartments that

858
00:44:37,600 --> 00:44:42,279
Speaker 1: they're in, or more of the clients leave their apartments

859
00:44:42,320 --> 00:44:45,920
Speaker 1: that year, like don't renew their leases. But revenue still grows.

860
00:44:46,320 --> 00:44:48,440
Speaker 1: And that all sounds fine when you treat it like numbers,

861
00:44:48,520 --> 00:44:50,880
Speaker 1: right that like, oh, we had more turnover the number,

862
00:44:50,880 --> 00:44:53,880
Speaker 1: but revenue still grew. But that fifteen percent of tenants

863
00:44:53,880 --> 00:44:56,239
Speaker 1: who turned over includes people who got evicted because they

864
00:44:56,280 --> 00:44:58,040
Speaker 1: couldn't pay their rent and people who had to leave

865
00:44:58,040 --> 00:45:00,160
Speaker 1: a neighborhood or even a city they loved because had

866
00:45:00,160 --> 00:45:03,000
Speaker 1: been priced out. And it also the added rent that

867
00:45:03,040 --> 00:45:05,920
Speaker 1: these people paid. The reason why profits were still up

868
00:45:06,200 --> 00:45:08,880
Speaker 1: means money those tenants aren't spending elsewhere money, They're not

869
00:45:08,920 --> 00:45:11,920
Speaker 1: saving for a house themselves or contributing to the local economy,

870
00:45:12,160 --> 00:45:14,839
Speaker 1: rather than pumping more cash into a massive corporation whose

871
00:45:14,840 --> 00:45:18,120
Speaker 1: shareholders all live far away from the communities where this

872
00:45:18,200 --> 00:45:23,520
Speaker 1: decision is impacted. Yep Rick Campo of Camden Property Trust

873
00:45:23,640 --> 00:45:25,640
Speaker 1: is one of the people who doesn't see things this way.

874
00:45:25,800 --> 00:45:28,600
Speaker 1: He summarized the impact of yield Star like this. The

875
00:45:28,640 --> 00:45:30,880
Speaker 1: net effect of driving revenue and pushing people out was

876
00:45:30,880 --> 00:45:33,200
Speaker 1: ten million dollars in income. I think that shows that

877
00:45:33,280 --> 00:45:35,080
Speaker 1: keeping the heads and beds above all else it's not

878
00:45:35,120 --> 00:45:37,920
Speaker 1: always the best strategy. Wait, yeah, man, we put some

879
00:45:37,960 --> 00:45:40,000
Speaker 1: people on the street, but we made ten million dollars

880
00:45:42,120 --> 00:45:45,200
Speaker 1: the people. It's funny. So pro Publica does this big

881
00:45:45,200 --> 00:45:48,279
Speaker 1: investigation and they're the ones who bust this story. They

882
00:45:48,640 --> 00:45:51,320
Speaker 1: find this quote from Campo where he's like, heads and beds,

883
00:45:51,360 --> 00:45:54,359
Speaker 1: fuck it. Uh, and they're like, hey, this this kind

884
00:45:54,360 --> 00:45:59,640
Speaker 1: of makes you sound like a monster, kind of I think, yeah,

885
00:45:59,760 --> 00:46:03,640
Speaker 1: I'm gonna quote from their article Campo Toad Pro Publica.

886
00:46:03,719 --> 00:46:06,879
Speaker 1: It sounds awful and doesn't reflect how here Camden views

887
00:46:06,880 --> 00:46:09,920
Speaker 1: renters today. We fundamentally believe our customers and the most

888
00:46:09,960 --> 00:46:12,320
Speaker 1: important part of the business, he said. We're not about

889
00:46:12,360 --> 00:46:15,680
Speaker 1: pushing people out. Of course, you think customers are important,

890
00:46:15,880 --> 00:46:19,560
Speaker 1: They're the ones you're jacking money from. Like customers are

891
00:46:19,600 --> 00:46:22,960
Speaker 1: important to Camden the way somebody with a nice watch

892
00:46:23,040 --> 00:46:25,840
Speaker 1: is important to a man with a handgun and a

893
00:46:25,920 --> 00:46:30,919
Speaker 1: fucking desire to get a fixed by robbing him at gunpoint. Like, yeah,

894
00:46:31,000 --> 00:46:33,800
Speaker 1: that guy is important to him. The liquor store I

895
00:46:33,880 --> 00:46:36,320
Speaker 1: might rob later tonight is important to me. And this

896
00:46:36,520 --> 00:46:39,560
Speaker 1: is that same level of like child up twinning kid

897
00:46:39,680 --> 00:46:43,440
Speaker 1: children to work and you're like, yeah, about what you

898
00:46:43,480 --> 00:46:46,239
Speaker 1: think it is in their excuses, Like no, but if

899
00:46:46,239 --> 00:46:48,600
Speaker 1: the children didn't work for low wages, their family wouldn't

900
00:46:48,600 --> 00:46:52,520
Speaker 1: have any money. We're doing a good thing, We're helping

901
00:46:52,560 --> 00:46:58,400
Speaker 1: him out. Um yeah, it's it's it's ghoul logic, and

902
00:46:58,440 --> 00:47:00,160
Speaker 1: it's I also, I don't want to I don't want

903
00:47:00,200 --> 00:47:03,040
Speaker 1: to be unfair here and compare a guy like Rick

904
00:47:03,120 --> 00:47:06,080
Speaker 1: Campo to somebody who robs people at gunpoint or holds

905
00:47:06,120 --> 00:47:09,440
Speaker 1: up liquor stores because that individual robbing people at gunpoint.

906
00:47:09,480 --> 00:47:14,040
Speaker 1: You're holding up liquor stores. That's honest work, right you know? Yeah, no, no, no,

907
00:47:14,080 --> 00:47:17,200
Speaker 1: that's it's unfair to the guy with the person who

908
00:47:17,320 --> 00:47:19,960
Speaker 1: was desperate and trying to get anything. All right, I

909
00:47:20,000 --> 00:47:22,560
Speaker 1: got you down. I'll take that. Yeah, I'll take that.

910
00:47:23,000 --> 00:47:25,719
Speaker 1: And again, that's a human interaction as a general where

911
00:47:25,760 --> 00:47:31,279
Speaker 1: you can probably talk your way out of the worst. Yeah. Yeah,

912
00:47:31,440 --> 00:47:34,040
Speaker 1: it's not an algorithm deciding whether or not you get

913
00:47:34,080 --> 00:47:37,640
Speaker 1: stuck up, you know, because you know it's not heads

914
00:47:37,640 --> 00:47:41,360
Speaker 1: and beds. Yeah, exactly. Um, speaking of heads and beds,

915
00:47:41,880 --> 00:47:45,000
Speaker 1: we sell a lot of mattresses on this podcast, we do,

916
00:47:45,120 --> 00:47:47,960
Speaker 1: but I have yet to give one. Yeah. Yeah, they're

917
00:47:47,960 --> 00:47:52,040
Speaker 1: not get like they used to. That's what I'll say. Yeah, sounds,

918
00:47:53,080 --> 00:48:05,759
Speaker 1: let's get to ads. We're back. Uh good times. So

919
00:48:06,400 --> 00:48:10,160
Speaker 1: Campo Rick Campo by the way, asshole name that's a

920
00:48:10,239 --> 00:48:13,600
Speaker 1: jeris right, you can tell fucking Rick Campo. You know, Rick,

921
00:48:14,000 --> 00:48:18,120
Speaker 1: your job is selling time shares in Florida to elderly

922
00:48:18,200 --> 00:48:20,640
Speaker 1: people with dementia who don't know where they are. Like,

923
00:48:20,719 --> 00:48:25,440
Speaker 1: that's what you do. Radio personality that just screams at

924
00:48:25,480 --> 00:48:29,399
Speaker 1: people and then tries to like he's not a racist asshole. Yeah,

925
00:48:29,480 --> 00:48:31,600
Speaker 1: Rick Campo, the guy whose job is to get up

926
00:48:31,600 --> 00:48:40,920
Speaker 1: at six am and say the in word before playing um.

927
00:48:40,960 --> 00:48:43,920
Speaker 1: So obviously he says that they're not about pushing people out.

928
00:48:43,960 --> 00:48:46,319
Speaker 1: But that is objectively what the software did, and it

929
00:48:46,320 --> 00:48:49,800
Speaker 1: began to take off like wildfire in the real estate industry,

930
00:48:50,040 --> 00:48:52,239
Speaker 1: which led to articles about it like this in the

931
00:48:52,360 --> 00:48:56,960
Speaker 1: landlord focused news website yield pro. Yields is the profits

932
00:48:56,960 --> 00:48:59,440
Speaker 1: you jack out of people for housing which they will

933
00:48:59,440 --> 00:49:03,160
Speaker 1: die without. Yeah, so here's them writing about this positively.

934
00:49:03,880 --> 00:49:07,040
Speaker 1: Equity Residential which completed installation of l r So l

935
00:49:07,160 --> 00:49:09,080
Speaker 1: r O is the other kind of software. There's the

936
00:49:09,120 --> 00:49:10,920
Speaker 1: yield Star and there's l r RO. There's the two,

937
00:49:10,920 --> 00:49:13,600
Speaker 1: and they both do this. They're both competing at this point,

938
00:49:13,600 --> 00:49:16,520
Speaker 1: competing software, so it's talking about both of them. Equity

939
00:49:16,560 --> 00:49:19,680
Speaker 1: Residential which complete completed installation of l R RO across

940
00:49:19,760 --> 00:49:22,160
Speaker 1: across its hundred and sixty five thousand, seven hundred and

941
00:49:22,200 --> 00:49:25,480
Speaker 1: sixteen unit portfolio and Q four two thousand six found

942
00:49:25,480 --> 00:49:28,520
Speaker 1: it extremely useful. Through the turning point in the apartment market,

943
00:49:28,800 --> 00:49:31,160
Speaker 1: we've raised rents hundreds of dollars in some markets. And

944
00:49:31,200 --> 00:49:33,359
Speaker 1: I don't think people on site, given the way we'd

945
00:49:33,360 --> 00:49:35,360
Speaker 1: trained them to think about pricing, would have had the

946
00:49:35,360 --> 00:49:37,879
Speaker 1: courage to push it as aggressively as this program has,

947
00:49:38,239 --> 00:49:41,480
Speaker 1: CEO David neither Cut told panelists during a Deutsche Bank

948
00:49:41,520 --> 00:49:45,640
Speaker 1: conference in January. Keith Odin, Camden Property Trust President and CEO,

949
00:49:45,800 --> 00:49:48,239
Speaker 1: agreed it's not in their DNA to raise pricing a

950
00:49:48,320 --> 00:49:50,400
Speaker 1: hundred and fifty to two hundred dollars per unit on

951
00:49:50,440 --> 00:49:52,960
Speaker 1: a lease turn. He said. Camden completed roll out of

952
00:49:53,000 --> 00:49:55,520
Speaker 1: yield Star across its sixty four thousand, three hundred and

953
00:49:55,520 --> 00:49:58,319
Speaker 1: eighty four unit portfolio in the Q four two thousand five.

954
00:49:58,560 --> 00:50:01,880
Speaker 1: Both Camden and Equity so far report one lifts to

955
00:50:01,920 --> 00:50:04,080
Speaker 1: net operating income that they attribute to the use of

956
00:50:04,160 --> 00:50:06,840
Speaker 1: yield Star and l r OH respectively. And again this

957
00:50:06,920 --> 00:50:09,560
Speaker 1: is the very start of it. Because these these algorithms,

958
00:50:09,600 --> 00:50:11,879
Speaker 1: the way they work, like any other algorithm, they get

959
00:50:12,160 --> 00:50:14,919
Speaker 1: more effective at the thing they do the more often

960
00:50:14,960 --> 00:50:16,839
Speaker 1: they do it, the more data they get right. So

961
00:50:16,880 --> 00:50:19,759
Speaker 1: that's again, they get better at raising rent by more

962
00:50:19,880 --> 00:50:22,960
Speaker 1: the longer they're doing it, and the more they I'm guessing,

963
00:50:22,960 --> 00:50:25,200
Speaker 1: and the more they are rented, like raising the prices

964
00:50:25,239 --> 00:50:26,799
Speaker 1: as it gets higher and higher, they're going to use

965
00:50:26,800 --> 00:50:30,960
Speaker 1: that as all prices everywhere else, right because again they're

966
00:50:31,000 --> 00:50:35,319
Speaker 1: price fixing, but not legally, so don't sue us. Yeah,

967
00:50:35,360 --> 00:50:37,799
Speaker 1: I just wanted to say everything that you name, the corporations,

968
00:50:37,840 --> 00:50:40,960
Speaker 1: individuals are all the bad guys in history of the

969
00:50:40,960 --> 00:50:44,480
Speaker 1: world right now, So yeah, these are bad guys. Yes.

970
00:50:44,800 --> 00:50:47,080
Speaker 1: So if you are currently in an apartment complex that

971
00:50:47,120 --> 00:50:49,759
Speaker 1: you've seen your rise by a surprising amount, you want

972
00:50:49,760 --> 00:50:51,719
Speaker 1: to look into whether or not your landlord uses l

973
00:50:51,800 --> 00:50:55,040
Speaker 1: r O or yield Star. And while many companies don't

974
00:50:55,120 --> 00:50:57,400
Speaker 1: use these programs, the fact that they're in use in

975
00:50:57,520 --> 00:51:01,479
Speaker 1: major markets increases pricing for everybody. As one real estate

976
00:51:01,520 --> 00:51:04,440
Speaker 1: executive told Yield pro in two thousand seven, a rising

977
00:51:04,480 --> 00:51:08,360
Speaker 1: tide lifts all boats. The way Jeffrey Roper sees it,

978
00:51:08,520 --> 00:51:11,680
Speaker 1: landlords who don't jack their prices up are ripping off

979
00:51:11,760 --> 00:51:15,239
Speaker 1: all the other landlords. Quote, if you have idiots undervaluing,

980
00:51:15,320 --> 00:51:18,400
Speaker 1: it costs the whole system, which is the same logic

981
00:51:18,440 --> 00:51:21,640
Speaker 1: that led to the price fixing ga with the airlines. Right. Yea,

982
00:51:23,160 --> 00:51:25,799
Speaker 1: my face is turning red. My face is turning red.

983
00:51:25,960 --> 00:51:28,400
Speaker 1: Is this dark void of mind. My face is turning.

984
00:51:28,960 --> 00:51:34,680
Speaker 1: Why anybody who says they're a numbers nerd, because it's

985
00:51:34,719 --> 00:51:36,920
Speaker 1: one of those things if you've got if this guy's

986
00:51:36,920 --> 00:51:38,520
Speaker 1: logic is being I don't know, if he's like works

987
00:51:38,560 --> 00:51:41,480
Speaker 1: for a company that makes premium bourbon, right, and like

988
00:51:41,600 --> 00:51:44,120
Speaker 1: he's he's applying this logic to like get the most

989
00:51:44,160 --> 00:51:47,359
Speaker 1: profits out of people who want to buy nice bourbon whatever, right,

990
00:51:47,760 --> 00:51:56,280
Speaker 1: Like it's discretionary, and people die if they don't have housing. Like, yeah,

991
00:51:56,320 --> 00:51:58,200
Speaker 1: because a lot of this house, these houses that are

992
00:51:58,200 --> 00:52:01,720
Speaker 1: for red who are with the more personable, are probably

993
00:52:01,960 --> 00:52:04,799
Speaker 1: not in its safet. Yes, the fire hazards like half

994
00:52:04,840 --> 00:52:06,360
Speaker 1: of the houses I lived in when I was a

995
00:52:06,440 --> 00:52:10,080
Speaker 1: renter exactly, Like there's so many things like that happened,

996
00:52:10,120 --> 00:52:14,319
Speaker 1: and you're like, you literally are giving up safety for

997
00:52:14,440 --> 00:52:16,719
Speaker 1: the price once again, as you would say, you're like,

998
00:52:16,840 --> 00:52:19,520
Speaker 1: you know, I'm living in a place that doesn't wanted

999
00:52:19,560 --> 00:52:22,160
Speaker 1: in a nice neighborhood for nothing, you know, or not

1000
00:52:22,280 --> 00:52:26,360
Speaker 1: that that was not a particularly nice later on, not

1001
00:52:26,400 --> 00:52:29,040
Speaker 1: that we connect now it was okay, Um, so the

1002
00:52:29,360 --> 00:52:34,560
Speaker 1: way Jeffrey Ropers sees it, Yeah, so anyway, initially Roper's competition,

1003
00:52:34,560 --> 00:52:36,680
Speaker 1: and this horrible business was l r O or Lease

1004
00:52:36,719 --> 00:52:39,840
Speaker 1: Rent Options, right. I quoted about them earlier, but yield

1005
00:52:39,880 --> 00:52:43,200
Speaker 1: Start purchased l r O in two thousand seventeen with

1006
00:52:43,239 --> 00:52:46,560
Speaker 1: the Justice Department's acquiescence. They were flagged for high level

1007
00:52:46,600 --> 00:52:51,200
Speaker 1: review but ultimately passed pro publica rights. The approval allowed

1008
00:52:51,239 --> 00:52:54,560
Speaker 1: Real Page to acquire its only significant competitor, Roper said,

1009
00:52:54,680 --> 00:52:57,319
Speaker 1: adding I was surprised the d o J let that

1010
00:52:57,360 --> 00:53:03,200
Speaker 1: go through. So did I say, are you really surprised,

1011
00:53:03,920 --> 00:53:09,120
Speaker 1: like those organizations bought that we? I mean, that should

1012
00:53:09,120 --> 00:53:11,920
Speaker 1: tell you what a fucking scam this is? Right? That

1013
00:53:12,040 --> 00:53:14,840
Speaker 1: like even he's being like, yeah, man, I can't believe

1014
00:53:14,880 --> 00:53:16,960
Speaker 1: they didn't call that price fixing. I can believe they

1015
00:53:17,000 --> 00:53:21,000
Speaker 1: said that wasn't monopolies. It's fucked up what we did.

1016
00:53:22,080 --> 00:53:25,320
Speaker 1: So Real Page was pricing one and a half million units,

1017
00:53:25,320 --> 00:53:28,080
Speaker 1: and the acquisition of l r OH would double that. Uh.

1018
00:53:28,120 --> 00:53:30,840
Speaker 1: Steve Win Real Pages CEO at the point, at that

1019
00:53:30,880 --> 00:53:33,839
Speaker 1: point set into two thousand seventeen investor conference, I don't

1020
00:53:33,840 --> 00:53:37,320
Speaker 1: think there's any concentration enough concentration of buying or pricing

1021
00:53:37,320 --> 00:53:41,960
Speaker 1: power here to warrant the d o J stepping in Um. Yeah,

1022
00:53:42,239 --> 00:53:47,120
Speaker 1: so that's cool. Um And uh they made a lot

1023
00:53:47,160 --> 00:53:51,560
Speaker 1: of money Real Pages influence that year, like um. They

1024
00:53:52,320 --> 00:53:55,479
Speaker 1: The firm's target market was multi family buildings with five

1025
00:53:55,600 --> 00:53:58,600
Speaker 1: or more units UM, made up nineteen million of the

1026
00:53:58,640 --> 00:54:02,279
Speaker 1: nation's forty million units UM, and a huge share of

1027
00:54:02,280 --> 00:54:05,320
Speaker 1: those buildings were owned by firms backed by Wall Street investors,

1028
00:54:05,480 --> 00:54:08,279
Speaker 1: who are the first adopters of this pricing software. Right,

1029
00:54:08,320 --> 00:54:10,920
Speaker 1: so he is he is specifically going to jack up

1030
00:54:10,920 --> 00:54:16,040
Speaker 1: the pricing of like housing for families that is traditional,

1031
00:54:16,120 --> 00:54:18,799
Speaker 1: like should have been more affordable. Right, Like he's he's

1032
00:54:18,840 --> 00:54:22,640
Speaker 1: actually directly this business directly is targeting and jacking at

1033
00:54:22,680 --> 00:54:25,799
Speaker 1: the prices of what we call affordable housing. Again, not

1034
00:54:25,880 --> 00:54:29,560
Speaker 1: all his owning issue. So real Page renamed its combined

1035
00:54:29,640 --> 00:54:32,640
Speaker 1: pricing software AI Revenue Management, and by the end of

1036
00:54:32,680 --> 00:54:36,000
Speaker 1: twenty the firm was reporting in an SEC Commission filing

1037
00:54:36,680 --> 00:54:39,280
Speaker 1: that its clients used its services and products to manage

1038
00:54:39,400 --> 00:54:43,080
Speaker 1: nineteen points seven million rental units of all types, including

1039
00:54:43,120 --> 00:54:47,600
Speaker 1: single family homes. The private equity firm Tom Bravo brought

1040
00:54:47,640 --> 00:54:49,959
Speaker 1: the company public a few months later for ten point

1041
00:54:50,000 --> 00:54:57,279
Speaker 1: to billion dollars. And again, it's all that's all, that's

1042
00:54:57,400 --> 00:55:00,520
Speaker 1: enough to affect everyone, right, twenty million houses units, that's

1043
00:55:00,600 --> 00:55:06,080
Speaker 1: enough to raise everybody's rent price. And named Kimden, so

1044
00:55:06,120 --> 00:55:11,839
Speaker 1: are talking about the Camden to apartment complexes that are everywhere. Yes, yes, okay, okay,

1045
00:55:11,200 --> 00:55:16,800
Speaker 1: they brought this monster software into the world, like listening

1046
00:55:18,719 --> 00:55:24,239
Speaker 1: right there. Burn it down, yeah, burn burnt down, burn

1047
00:55:24,320 --> 00:55:32,400
Speaker 1: it down. Um, it's it's cool, so cool cool, the

1048
00:55:32,400 --> 00:55:36,960
Speaker 1: good the good stuff is that I don't know. Um. Basically,

1049
00:55:38,320 --> 00:55:41,080
Speaker 1: the attitude these companies were able to realize because of

1050
00:55:41,160 --> 00:55:45,600
Speaker 1: this software is that previously, even though they all always

1051
00:55:45,680 --> 00:55:47,480
Speaker 1: wanted to get as much money as they could have people,

1052
00:55:47,600 --> 00:55:50,640
Speaker 1: the number one priority was keeping occupancy full. Right, So

1053
00:55:50,680 --> 00:55:52,840
Speaker 1: we'll make deals with people, will cut prices if we

1054
00:55:52,880 --> 00:55:55,280
Speaker 1: can get another person another unit, right, because the worst

1055
00:55:55,280 --> 00:55:57,320
Speaker 1: thing is an empty unit, right, An empty unit is

1056
00:55:57,360 --> 00:56:01,960
Speaker 1: just a total waste of money this software and Roper

1057
00:56:02,120 --> 00:56:05,000
Speaker 1: comes in, and Roper's attitude is, no, it's not empty

1058
00:56:05,120 --> 00:56:07,360
Speaker 1: units are fine as long as we're jacking up the

1059
00:56:07,400 --> 00:56:10,080
Speaker 1: prices of other units more if we have to keep

1060
00:56:10,080 --> 00:56:12,160
Speaker 1: more units empty. As long as we're getting more total

1061
00:56:12,200 --> 00:56:14,719
Speaker 1: money out of the built the complex, that's all that

1062
00:56:14,800 --> 00:56:19,719
Speaker 1: fucking matters. Um. And what this actually means in in

1063
00:56:20,239 --> 00:56:22,600
Speaker 1: reality is that people are winding up on the street

1064
00:56:22,640 --> 00:56:24,520
Speaker 1: or they're being forced to move or forced to double

1065
00:56:24,560 --> 00:56:26,840
Speaker 1: and triple up somewhere else just to survive. And profits

1066
00:56:26,840 --> 00:56:29,560
Speaker 1: still raised for the company because everyone who gets to

1067
00:56:29,560 --> 00:56:31,840
Speaker 1: stay in housing is just getting built for more money.

1068
00:56:32,160 --> 00:56:34,600
Speaker 1: And one analysis pro Publica did if a building owned

1069
00:56:34,600 --> 00:56:36,840
Speaker 1: by a company that used yield Star next door to

1070
00:56:36,880 --> 00:56:39,560
Speaker 1: a building that didn't rent for the yield Star building

1071
00:56:39,840 --> 00:56:45,040
Speaker 1: rose since two thousand twelve as opposed to thirty three. So, like,

1072
00:56:45,120 --> 00:56:47,920
Speaker 1: these are substantial increases. And you've got to also admit

1073
00:56:48,520 --> 00:56:51,000
Speaker 1: or a note that like the average and that like

1074
00:56:51,080 --> 00:56:53,760
Speaker 1: the gap between yield Star and non yield Star buildings

1075
00:56:53,880 --> 00:56:58,319
Speaker 1: is higher because the average rental price is also being

1076
00:56:58,320 --> 00:57:02,480
Speaker 1: affected by the fucking yield Star price. Right, Like, it's

1077
00:57:02,480 --> 00:57:04,680
Speaker 1: not just that yield Star buildings are higher than non

1078
00:57:04,760 --> 00:57:08,160
Speaker 1: it's that they're raising rental prices for everybody because the

1079
00:57:08,160 --> 00:57:12,360
Speaker 1: whole market is. Because that's the conversation is that, yeah,

1080
00:57:12,400 --> 00:57:16,080
Speaker 1: these look well, I say, that's this all inclusive maintenance

1081
00:57:16,160 --> 00:57:20,840
Speaker 1: apartment complexes. They have their steady prices with no negotiations.

1082
00:57:20,880 --> 00:57:24,479
Speaker 1: But even though they're significantly higher, whatever you were paying

1083
00:57:24,480 --> 00:57:27,040
Speaker 1: with these mom and pop landlords is still going to

1084
00:57:27,200 --> 00:57:29,480
Speaker 1: increase because no matter what, even if it was like

1085
00:57:29,680 --> 00:57:33,919
Speaker 1: let's say it's cheap eight doing is still significantly cheaper

1086
00:57:33,920 --> 00:57:37,960
Speaker 1: thanment that that's gone in. So it sounds cheaper, which

1087
00:57:38,000 --> 00:57:41,400
Speaker 1: is what's happened everywhere. Yeah, because the form is that

1088
00:57:41,480 --> 00:57:44,120
Speaker 1: I left literally is cheaper than everywhere in Atlanta. But

1089
00:57:44,120 --> 00:57:51,120
Speaker 1: it's still went exactly. So everything's good. It is it

1090
00:57:51,840 --> 00:57:57,760
Speaker 1: fee that's good. Things are fine. We should everything. It

1091
00:57:57,800 --> 00:58:01,919
Speaker 1: should always be acceptable to turn things that to turn

1092
00:58:02,040 --> 00:58:05,880
Speaker 1: pricing for things that people die without into a fucking

1093
00:58:05,920 --> 00:58:10,640
Speaker 1: algorithm game, just like everything else that's terrible in our society. Um,

1094
00:58:10,920 --> 00:58:14,200
Speaker 1: people die, and like risk, there's the safety for white

1095
00:58:14,200 --> 00:58:16,920
Speaker 1: men to get continue to get rich. That's amazing. I

1096
00:58:17,040 --> 00:58:19,040
Speaker 1: love that. That's my favorite thing to do. You know,

1097
00:58:19,080 --> 00:58:21,280
Speaker 1: it's not just white men. You have to assume they're

1098
00:58:21,320 --> 00:58:24,200
Speaker 1: not all white, you know. So that's fine, that's true,

1099
00:58:24,240 --> 00:58:29,200
Speaker 1: that's true. Yeah, it's good. So anyway, we're gonna talk

1100
00:58:29,240 --> 00:58:32,920
Speaker 1: about an even more entertaining piece of ship next episode,

1101
00:58:33,000 --> 00:58:36,040
Speaker 1: and we're going to talk about some other important stuff

1102
00:58:36,080 --> 00:58:42,200
Speaker 1: including uh which call it rent control. But yeah, that's

1103
00:58:42,240 --> 00:58:45,040
Speaker 1: those are oh yeah, yeah. In some places, although yeah,

1104
00:58:45,080 --> 00:58:47,680
Speaker 1: there's some fun going on there too, but yeah, this

1105
00:58:47,800 --> 00:58:50,720
Speaker 1: is uh. These are some of the assholes who have

1106
00:58:50,800 --> 00:58:53,840
Speaker 1: made rent be so damn high. And also the assholes,

1107
00:58:54,680 --> 00:58:57,720
Speaker 1: the assholes who because the assholes in this that you know,

1108
00:58:58,000 --> 00:59:00,760
Speaker 1: Roper is the one we're really digging into this episode,

1109
00:59:01,120 --> 00:59:03,640
Speaker 1: but other assholes are just like all of the journalists

1110
00:59:03,640 --> 00:59:07,240
Speaker 1: who blithely report like, well, experts say there's just not

1111
00:59:07,360 --> 00:59:09,959
Speaker 1: enough housing and we have to change voting. It's like, no, no, no,

1112
00:59:10,080 --> 00:59:12,240
Speaker 1: not that that's not part of the issue, but don't

1113
00:59:12,280 --> 00:59:16,640
Speaker 1: pretend that that's everything that's going on, you fucking dishonest pricks.

1114
00:59:18,720 --> 00:59:20,440
Speaker 1: I'm gonna have to go run or something. And what

1115
00:59:20,480 --> 00:59:22,840
Speaker 1: do what do I do? Yeah? I don't know, go

1116
00:59:22,920 --> 00:59:25,960
Speaker 1: rent a house. Everybody go out and sign a lease.

1117
00:59:26,760 --> 00:59:33,080
Speaker 1: I quit? Yeah, Sam, anything you wanna you wanna plug? Oh? Sure,

1118
00:59:33,400 --> 00:59:37,560
Speaker 1: um let me get gather my thoughts. Yes, you can

1119
00:59:37,600 --> 00:59:41,080
Speaker 1: come find me at my podcast with Annie stuff. Mom

1120
00:59:41,120 --> 00:59:42,880
Speaker 1: never told you if you like to talk about feminist

1121
00:59:42,920 --> 00:59:46,680
Speaker 1: issues where you want to rage about how the US

1122
00:59:46,720 --> 00:59:49,360
Speaker 1: hate women. Um, a lot of people hate women apparently

1123
00:59:49,360 --> 00:59:52,840
Speaker 1: in general, and those who identify as female, you know,

1124
00:59:52,920 --> 00:59:57,080
Speaker 1: they think they do essentially or any issues dealing with

1125
00:59:57,320 --> 01:00:02,680
Speaker 1: those who identify as female. Come on over, let's to us. Um. Yeah. Also,

1126
01:00:02,680 --> 01:00:05,160
Speaker 1: you can find me on Instagram McVeigh dot sam or

1127
01:00:05,240 --> 01:00:08,720
Speaker 1: on Twitter I believe McVeigh Samantha. Yeah, you can see

1128
01:00:08,760 --> 01:00:15,360
Speaker 1: pictures of my dog. Well, go with christ my children,

1129
01:00:16,040 --> 01:00:18,960
Speaker 1: and we'll be back for for a part two on Thursday.

1130
01:00:19,160 --> 01:00:27,000
Speaker 1: Hell yeah, well maybe let's just happen o Goodbye. Behind

1131
01:00:27,040 --> 01:00:29,840
Speaker 1: the Bastards is a production of cool Zone Media. For

1132
01:00:29,960 --> 01:00:32,720
Speaker 1: more from cool zone Media, visit our website cool zone

1133
01:00:32,760 --> 01:00:35,600
Speaker 1: media dot com, or check us out on the I

1134
01:00:35,680 --> 01:00:39,000
Speaker 1: Heart Radio app, Apple Podcasts, or wherever you get your podcasts.