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Speaker 1: This is Masters in Business with Barry Ridholts on Bloomberg Radio.

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Speaker 1: This week on the podcast, I have a special guest,

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Speaker 1: and you are going to wank out on everything we discuss.

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Speaker 1: If you're at all interested in where do I begin? Mortgages,

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Speaker 1: the housing market, real estate demographics, economics, um securitization. I

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Speaker 1: go deep into the weeds with my guest. His name

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Speaker 1: is Lynn Kiefer. He is the deputy chief economist at

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Speaker 1: Freddie Mac. For those of you who are longtime readers

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Speaker 1: of mine, you know I have been somewhat fascinated by

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Speaker 1: the housing market and how we put together the entire

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Speaker 1: mortgage industry and and how that drives the economy and

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Speaker 1: vice versa, how the economy drives housing. Sometimes the tail

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Speaker 1: does wag the dog, and that was a key aspect

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Speaker 1: of what took place during the financial crisis. Our entire

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Speaker 1: conversation today is really post crisis, what's taken place, how

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Speaker 1: Fanny Many and Freddie Mack in particular, have changed, and

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Speaker 1: what it means to uh not only the growth of

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Speaker 1: the housing sector but the entire economy. So, with no

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Speaker 1: further ado, my conversation with Lenn Keefer, Deputy chief Economist

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Speaker 1: at Freddie Mack. My special guest today is Lenn Keefer.

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Speaker 1: He is the deputy chief economist at Freddie Mack, one

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Speaker 1: of the two giant government sponsored entities that securitizes most

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Speaker 1: of the mortgages here in the United States. He comes

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Speaker 1: to us UH with a BA in economics from the

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Speaker 1: University of Kentucky and a PhD from Ohio State. Lenn Keefer,

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Speaker 1: Welcome to Bloomberg. Hey, happy to be here. So I've

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Speaker 1: been following you on Twitter for a while. We'll get

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Speaker 1: to that in a little bit. I just have to

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Speaker 1: begin with your bio, which says, quote, I help people

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Speaker 1: understand the economy, housing and mortgage markets. That's a noble goal.

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Speaker 1: But how can any single economists accomplish that? Yeah, very

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Speaker 1: That's really tough to do. That's more of a mission statement.

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Speaker 1: You know what I tried, How I try to organize myself,

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Speaker 1: how you know, my public life, what I'm trying to

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Speaker 1: do UH, and I think we have some success doing that.

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Speaker 1: There's really sort of two areas where I focus on

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Speaker 1: to try to help people understand what's going on. Part

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Speaker 1: of my role at Freddie Mack is to help, you know,

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Speaker 1: be a company spokesperson to go out and talk to

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Speaker 1: you know, our various business partners. We have events where

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Speaker 1: you know, we bring together real estate agents, loan officers,

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Speaker 1: um others, and you know, those folks are often very

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Speaker 1: active in the marketplace, but they want to hear, you know,

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Speaker 1: from an economist, to get a sense of sort of

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Speaker 1: a bigger, broader perspective on what's going on, what's happening

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Speaker 1: in the global macroeconomy, and so helping those folks understand,

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Speaker 1: give them our perspective from what we do in our

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Speaker 1: research and what we find, I think is part of

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Speaker 1: the way we helped do that. And then a second

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Speaker 1: hat I wear is to help folks inside the company.

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Speaker 1: So at Freddie Mac, folks that are really thinking about

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Speaker 1: sort of the mortgage market, the housing market in the

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Speaker 1: United States very carefully give them sort of an economics

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Speaker 1: perspective how to make sense of the trends, what's happening,

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Speaker 1: and how the market maybe headed in the future. I

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Speaker 1: left out of your bio that you were a professor

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Speaker 1: at George Mason. How did you transition from academia to

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Speaker 1: Freddie Mack. Yeah, so it was it was an interesting transition,

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Speaker 1: you know, I went to Ohio State, and after I graduated,

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Speaker 1: I actually went to West Texas, Texas Tech University UH

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Speaker 1: and was there as a tenure track professor in their program.

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Speaker 1: My wife is also an economist. We met at at

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Speaker 1: Ohio State and she took a job in d C,

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Speaker 1: and I decided that I would follow her. Better job

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Speaker 1: opportunities in the d C metro than West Texas for economists,

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Speaker 1: and so I followed her to the d C area

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Speaker 1: and then eventually ended up at Freddie Mack. So I

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Speaker 1: mentioned earlier your Twitter feed, you just fill it with

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Speaker 1: these most delightful charts that a lot of other people

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Speaker 1: don't use. It's not just this is the number of

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Speaker 1: new homes that have been sold. They're very different, insightful

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Speaker 1: reveals as to what's going on beneath the surface um

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Speaker 1: of the housing market. A lot of big companies, and

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Speaker 1: I include Freddie Mack as really more of a private company.

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Speaker 1: They're not so keen on senior people being out on

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Speaker 1: social media. How have you worked this out with with

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Speaker 1: Freddie Mack? Are they um encouraging or they nervous? How

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Speaker 1: how do you interact with them on the social side. Yeah,

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Speaker 1: actually it was the Freddie mac Communications folks who actually

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Speaker 1: encouraged me to actually get started on Twitter in particular,

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Speaker 1: because we view it as you know, it's a great

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Speaker 1: way to get you know, sort insights out. We do

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Speaker 1: a lot of analysis, data analysis, A lot of that

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Speaker 1: tends to get siloed within the organization. Uh and since

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Speaker 1: we're already producing a lot of that in formation, a

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Speaker 1: lot of that is based on public data. I think

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Speaker 1: those observations which are already things we did and sort

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Speaker 1: of other research avenues. I think we're Twitter was a

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Speaker 1: great platform to be able to share that insights and information,

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Speaker 1: and so they've been supportive of you know, me engaging

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Speaker 1: in that and trying to get you know, conversation, go

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Speaker 1: and share our insights, share our perspective, share some of

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Speaker 1: the things that we're seeing in the housing market, because

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Speaker 1: I think within Freddie Mack we have an interesting perspective.

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Speaker 1: We have a lot of data, a lot of really

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Speaker 1: smart people, a lot of insights, and so distilling some

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Speaker 1: of that down into the public conversation around the housing

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Speaker 1: and mortgage market and the economy is I think well

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Speaker 1: within sort of my role in the company, and they've

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Speaker 1: still have been supportive of that, and your Twitter handle

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Speaker 1: is at Lynn Keefer k I E F E R

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Speaker 1: I actually the other day retweeted graphic you showed and

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Speaker 1: the charts use They're just a fascinating combination of annual

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Speaker 1: color coded mortgage rates and then showing on a continual time.

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Speaker 1: How do you how do you source these things? Are

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Speaker 1: you're doing this old in the house? Where do you

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Speaker 1: create these? Yeah? So I actually create a lot of

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Speaker 1: them myself. You know, I'm a big fan of data visualization.

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Speaker 1: You know, asked earlier about the transition from an academic

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Speaker 1: world to an industry world, and one of the key

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Speaker 1: fundamental differences between an academic approach economics and a more

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Speaker 1: industry focused approach is, you know, the really importance of

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Speaker 1: being salient, being clear, and having a crisp communication and

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Speaker 1: so in data visualization, which I think is really undergoing

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Speaker 1: a renaissance, you know, with all the computing technology, all

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Speaker 1: the great ideas that people have has really I think

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Speaker 1: shifted sort of where you know, the dialogue can be

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Speaker 1: in terms of information design, how you present information, and

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Speaker 1: so thinking about a new interesting ways to present the

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Speaker 1: same data. Because you know, I've been working on our

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Speaker 1: mortgage rate survey for close on five years now over

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Speaker 1: five years, you know, we have a weekly mortgage rights.

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Speaker 1: Every week we have a mortgage rate. So trying to

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Speaker 1: come up with what's a new perspective, what's interesting to

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Speaker 1: see about that, what's a different way, How can I

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Speaker 1: turn this data and try to look at it in

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Speaker 1: a slightly different way to get a new insight um

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Speaker 1: is challenging and so I think data visualization and building

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Speaker 1: graphs and interesting charts is a way to do it.

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Speaker 1: And the great news is is that there's a whole

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Speaker 1: ton of people out there who are active. You know,

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Speaker 1: they share things either through blogs or social media on

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Speaker 1: Twitter that give me a lot of ideas. And in

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Speaker 1: the world we're in today, a lot of the code

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Speaker 1: that they use to create those charts are open source,

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Speaker 1: so it's relatively easy to pick that up and extend it,

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Speaker 1: to tweak it, to apply it, you know, take something

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Speaker 1: from genomics or biology and apply to economics and finance.

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Speaker 1: I think that's a that's a really rich environment. And

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Speaker 1: so one of the positive aspects of the social media

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Speaker 1: is the ability to sort of quickly share that information

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Speaker 1: and to get it to a broader audience that what

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Speaker 1: you might get if you're too siloed within you know

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Speaker 1: mortgage finance. Well, well you do a great job. I'm

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Speaker 1: absolutely um entranced by all of your UM graphics and

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Speaker 1: always tell people follow at Lynn Kiefer. Let's talk a

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Speaker 1: little bit about the entire process of mortgage securitization, which

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Speaker 1: really dates back to the post Great Depression era, back

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Speaker 1: when mortgages were three years interest only and if you

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Speaker 1: couldn't roll them over, well you were in deep trouble.

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Speaker 1: You would end up losing the house. That was a

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Speaker 1: big part of what happens uh during the and following

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Speaker 1: the Great Depression, and why we have mortgage giants like

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Speaker 1: Freddie Mack and Fanny May tell us about the process

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Speaker 1: of securitizing a mortgage. How does that start and and

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Speaker 1: what is the thought process like when your firm is

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Speaker 1: doing that. Yeah, so, I think what's really important is

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Speaker 1: sort of the interface between Freddie Mack and the primary

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Speaker 1: market or the originators, the institutions that are actually making

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Speaker 1: the loans, because we had Freddie or Fannie May don't

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Speaker 1: actually originate loans. We are active in the secondary market,

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Speaker 1: but we're heavily involved, you know, with the originators in

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Speaker 1: terms of sort of the types of products that are

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Speaker 1: acceptable that we will you know, securities and will fund

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Speaker 1: and so that sort of interaction sort of is very

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Speaker 1: much sort of the sort of very beginning stages, even

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Speaker 1: at the sort of underwriting and sort of the processing.

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Speaker 1: There's a large part of Freddie Mack who deals with

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Speaker 1: you know, loan operations, how do how do we take

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Speaker 1: on loans, how do we do how do we help

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Speaker 1: the originators you know, underwrite their loans through automated underwriting

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Speaker 1: systems often UH and then those loans get originated, and

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Speaker 1: then we of course then put them into securitizations, which

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Speaker 1: we've been doing for quite quite some time. And what's

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Speaker 1: been relatively new that folks you know that aren't active

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Speaker 1: in the sort of this space might not recognize, but

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Speaker 1: it was actually I think fundamentally important for how the

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Speaker 1: mortgage finance system has changed over the last decade is

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Speaker 1: that we have really begun to be active in a

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Speaker 1: credit transfer market where trendy mac actually takes the credit

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Speaker 1: risk associated with the mortgages, which traditionally we would hold

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Speaker 1: UH and distribute it through investors either through you know,

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Speaker 1: senior sub securitizations or through reinsurance market and so that

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Speaker 1: sort of those transactions, both on a single and multi

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Speaker 1: family side, have really helped to sort of, you know,

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Speaker 1: disperse the credit risk and sort of get it to

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Speaker 1: a broader market, which can ultimately help to bring you

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Speaker 1: cost down for taxpayers, uh, and also for you know, borrowers.

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Speaker 1: So let's drill down on that a little bit. And

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Speaker 1: I know some people are listening and saying, gee, that

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Speaker 1: sounds awfully complicated, but it really isn't quite as complicated

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Speaker 1: as the as the jargon makes it sound. Banks originate mortgages,

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Speaker 1: and these days it's primarily banks. Uh. They'll they'll write

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Speaker 1: a mortgage, which means they're giving somebody half a million

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Speaker 1: dollars or so to buy a house. Now they have

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Speaker 1: a piece of paper that says, we have a lean

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Speaker 1: against this house, but the buyer owes US five thousand dollars.

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Speaker 1: Now we're out of money, So if we want to

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Speaker 1: make another loan, we have to sell that mortgage to

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Speaker 1: somebody else, get the five thousand, and now make yet

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Speaker 1: a second loan, and do that over and over again.

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Speaker 1: So the entities buying these mortgages then put them into

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Speaker 1: a securitized product which they send cell to Wall Street

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Speaker 1: and others who were willing to take broadly diversified risk

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Speaker 1: it geographically and other factors in order to capture some

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Speaker 1: sort of a yield. Is that am I oversimplifying that?

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Speaker 1: Or is that pretty pretty decent? That's a great job

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Speaker 1: right now. That's so. Now let's talk about the next step,

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Speaker 1: which I don't know how how much this existed pre

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Speaker 1: financial crisis, and and we should clarify you've only been

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Speaker 1: at for an iMac since after the crisis. You weren't

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Speaker 1: there during that kind of crazy few years. That's right.

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Speaker 1: I joined the company in October two thousand nine, which

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Speaker 1: is about a year after the conservatorship, which is in

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Speaker 1: two thousand eight, about a decade ago. So this credit

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Speaker 1: transfer risk, how does that operate? Who are the buyers

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Speaker 1: of this and what are they actually um on the

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Speaker 1: hook for when they're taking this risk? Yeah, so this

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Speaker 1: is very new. I mean there were attempts I think

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Speaker 1: to start this market going, you know, in the past

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Speaker 1: or even in the early two thousand's, but it really

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Speaker 1: got started I think on the multi family side in

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Speaker 1: two thousand nine, which would you know, risk sharing essentially

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Speaker 1: between Freddie Mack and investors UH and then in the

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Speaker 1: single family side around two thousands twelve or two thousand

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Speaker 1: and thirteen. And what this is is traditionally, under that

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Speaker 1: model that you described where Freddie mac would buy the

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Speaker 1: loans and then securitize them, the investors of those securities

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Speaker 1: were really just buying interest rate risk. The credit risk

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Speaker 1: was guaranteed so by the government's entity, by Freddy or

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Speaker 1: Fannie UH, and so we would guarantee that the credit risk.

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Speaker 1: So in the event of the default, if the you know,

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Speaker 1: borrower defaulted on their home UH, the investors would get

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Speaker 1: paid back the principle, and so then the credit losses

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Speaker 1: would be taken by the entities. UH. Since then, we've

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Speaker 1: begun to realize that maybe holding all that credit risk

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Speaker 1: and one single gigantic UH two single gigantic organizations may

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Speaker 1: not be the most efficient way to structure it. And

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Speaker 1: so the idea was, well, how can we divert sell

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Speaker 1: that to a diversified marketplace, just like with interest rate

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Speaker 1: risk on the mortgage bonds. Could we sell the credit

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Speaker 1: risk to investors? Could they understand sort of okay, what

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Speaker 1: are the likelihood of default? How how would I understand

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Speaker 1: that risk? Once they got a hand along that risk.

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Speaker 1: They may be willing to then uh purchase these credit

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Speaker 1: risk transfer securities or reinsurance contracts where in the event

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Speaker 1: of a default, it's not only Freddie Mcrofannie May that

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Speaker 1: has to help make up the loss, it's also these

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Speaker 1: other investors. So what do they get if they're paying

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Speaker 1: for that, They're paying for the right to actually be

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Speaker 1: on the hook if there's a credit to full what's

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Speaker 1: the upside to them? Well, they get some yield in

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Speaker 1: that right, So they have to pay for that. So

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Speaker 1: there's you know, the auctions, those bonds are are auctioned off,

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Speaker 1: and so there's the market sort of in some sense

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Speaker 1: it determines what the price of that credit risk is,

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Speaker 1: which is is very new, uh, and so that's where

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Speaker 1: sort of I think Freddie Mack was very much a

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Speaker 1: leader in trying to get this market started, because initially

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Speaker 1: folks really didn't have a sense, well, well, how do

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Speaker 1: how does credit risks look? Uh? What what are the

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Speaker 1: losses may be gonna look like? And so back you know,

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Speaker 1: uh early we started releasing a lot of information to investors,

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Speaker 1: information on you know, mortgage historical performance data that was

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Speaker 1: historically kept within the UH enterprise but actually we put

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Speaker 1: it out publicly. It's actually available on the website. You

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Speaker 1: go to Freddie Mac dot com right now you can

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Speaker 1: go get a loan level file that gives you information

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Speaker 1: on not only the loans that were originated, but also

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Speaker 1: their subsequent performance and even information on their losses. And

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Speaker 1: that's very important for the marketplace so that they can

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Speaker 1: then use that data, build models, analyze it so when

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Speaker 1: they look at new originations, can use that historical data

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Speaker 1: to get a sense for what credit losses could look

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Speaker 1: like in the future when they're deciding, you know, what

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Speaker 1: to bid for these securities or insurance contracts. So in

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Speaker 1: the old days, a buyer of a secure ice product

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Speaker 1: out of the either Freddie Mett Mac or Fannie May

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Speaker 1: was taking interest rate risk, and theoretically they were taking

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Speaker 1: credit risk, but the assumption was the full faith and

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Speaker 1: credit of the United States stood behind it. So really

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Speaker 1: they weren't taking a whole lot of credit risk. Am

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Speaker 1: I over simple? Well, I think a little bit. They wouldn't.

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Speaker 1: Even in the case of the traditional securitization, it's more

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Speaker 1: counterparty or it's not credit risk on the borrower or

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Speaker 1: the counterparty risk. Could Freddie Mcrofannie may pay their obligations.

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Speaker 1: So that was really the rest of the assumption was

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Speaker 1: that they had to implicit guarantee the assumption. Quite interesting.

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Speaker 1: Let's talk a little bit about how Freddie Mack and

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Speaker 1: the other government sponsored enterprises have changed post crisis. What

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Speaker 1: what do you see the biggest changes at Freddie mac

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Speaker 1: have been. Yeah, so I think, you know, starting back,

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Speaker 1: you know, at the tenure of our curren CEO, Don Layton,

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Speaker 1: when he had come in in round two thousand and

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Speaker 1: eleven or so, I think he really brought a real

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Speaker 1: focus on culture of the institution of Freddie Mack and

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Speaker 1: how you know, we could have a commercial minded focus.

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Speaker 1: He had come from Chase and JP Morgan and eBay,

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Speaker 1: and so he brought a real commercial mindedness to the

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Speaker 1: enterprise and a real focus on being an efficient organization,

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Speaker 1: have an organization that was focused on customer with an

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Speaker 1: eye to potentially, in some future state perhaps being more

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Speaker 1: competitive than maybe we had been in the past. And

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Speaker 1: so that really took some time to really get that going.

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Speaker 1: But I've really seen that go through the organization and

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Speaker 1: and really I think about it in my work, how

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Speaker 1: I try to bring you know, the economics to you know,

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Speaker 1: either help our business partners internally or help folks you know,

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Speaker 1: externally and really have that kind of I think a

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Speaker 1: real customer focus, which was I think a real focus

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Speaker 1: and direction there uh that we've certainly had, but it

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Speaker 1: wasn't at the top, and that I think really brought

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Speaker 1: itself down and really got folks really focusing on how

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Speaker 1: can we be efficient, how can we know help make

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Speaker 1: this Freddie Mac better? While we are continuing to evolve.

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Speaker 1: As I mentioned, we talked about the credit risk transfer,

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Speaker 1: another innovative things that are going on as the market

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Speaker 1: short of continues to change. You referenced UM the conservatorship

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Speaker 1: which took place before you joined UM. Since that took place,

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Speaker 1: Freddie Mac has returned a hundred and twelve billion dollars

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Speaker 1: back to taxpayers, sixty more than they received during the crisis.

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Speaker 1: Is Freddie Mack giant cash cow? That sounds like that's

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Speaker 1: a lot of money. That is a lot of money.

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Speaker 1: I mean. Part of the thing that was interested coming

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Speaker 1: to Freddie Mack from an academic is the scale Freddie

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Speaker 1: Mack has. You know, I think over just over two

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Speaker 1: trillion dollars in our guarantee portfolio. That's you know, mortgages

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Speaker 1: that are in our securities. Um, a couple of trillion

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Speaker 1: more and you'll be up to black Rock and Vanguard levels. Uh.

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Speaker 1: But you know there's a lot of zeros. Uh. And

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Speaker 1: there's one in five roughly one in five home loans

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Speaker 1: in the country. I mean, it's just a huge scale. Um,

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Speaker 1: but a lot of sort of the uh you know,

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Speaker 1: one in five home loans in the country. That's an

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Speaker 1: amazing number. Yeah, I mean, it's just we have thousands

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Speaker 1: of seller services who deliver loans to us. It's just

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Speaker 1: a huge operation on a very very large scale, which

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Speaker 1: is some of the power of sort of the securitization

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Speaker 1: and the ability to sort of tap global capital markets,

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Speaker 1: which ultimately leads to benefits for borrowers. The thirty year

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Speaker 1: fixed rate mortgage and the lower rates which are going

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Speaker 1: to I think be a continued focus given sort of

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Speaker 1: the markets has seen interest rates drift higher over the

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Speaker 1: last year. So I mentioned previously, you put up this

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Speaker 1: lovely chart on Twitter about mortgage rates are now back

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Speaker 1: to levels not seen since two thousand eleven. But really,

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Speaker 1: by any traditional measure of mortgage rates, the cost of

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Speaker 1: borrowing to buy a house is still relatively inexpensive, isn't it?

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Speaker 1: It is from a historical perspective. We I mentioned we

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Speaker 1: work on what we call the primary mortgage market surveys,

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Speaker 1: are weekly mortgage rate survey that attracts. You know, what's

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Speaker 1: the third year fixed rate mortgage on average across the country.

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Speaker 1: You've been doing it since seventy one? Approximately? What is

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Speaker 1: a mortgage rate for the typical thirty year fixed these days? Uh,

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Speaker 1: it's around four seventy four point seven five still under

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Speaker 1: five now. I recall back in the two thousands, when

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Speaker 1: mortgage rates broke five percent to the downside, people were like,

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Speaker 1: oh my goodness, this is incredibly inexpensive. Have we just

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Speaker 1: gotten spoiled? We've benefited, I think from low mortgage interest rates.

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Speaker 1: But one of the challenges is, you know, you think

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Speaker 1: about where the marketplace is today and a lot of

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Speaker 1: buyers showing up, our first time buyers, they were in

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Speaker 1: high school perhaps or college when that was. They don't

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Speaker 1: remember for them. You know, a mortgage even a four

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Speaker 1: percent is relatively high and five you know, we we

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Speaker 1: I mentioned we work on the survey. You know, we

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Speaker 1: have some staff that help us, junior staff that are

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Speaker 1: relatively young. Uh. You know, I'm afraid we're gonna get

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Speaker 1: a five percent mortgage rate. We may have uh, and

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Speaker 1: they're gonna ask me, is this some dat air? Is

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Speaker 1: this even possible? Uh? And so yes, from a historic perspective,

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Speaker 1: long run rates are very low, but in the relative

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Speaker 1: to recent years a little bit higher. So that raises

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Speaker 1: the question how high can rates tick up before it

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Speaker 1: begins to crimp the entire housing market, which is one

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Speaker 1: of the biggest sectors in the economy. You know, we

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Speaker 1: have been seeing home sales, for example, increase year after year.

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Speaker 1: We had the best year in a decade in seventeen,

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Speaker 1: and when we started the year, we were forecasting to

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Speaker 1: see a modest increase in overall home sales. In eighteen,

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Speaker 1: rates rose u uh. And that has I think cool

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Speaker 1: activity a little bit. You know, definitely, there's some momentum

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Speaker 1: stalled a little bit in the summer of I think

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Speaker 1: a lot of that had to do with the impact

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Speaker 1: of rates. Because the broader economy is doing very well.

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Speaker 1: The employment market is very good, lot of job growth,

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Speaker 1: we're seeing incomes pick up, confidence is high. The real

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Speaker 1: two things are impeding sort of, the overall housing market

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Speaker 1: it's high home prices and then high interest rates, which

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Speaker 1: both make it difficult for potential buyers. What is the

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Speaker 1: key driver of home prices is that demographics, the overall economy,

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Speaker 1: interest rates, some combination what makes prices of homes go

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Speaker 1: up and down. Well, I'm an economist, I gotta say everything.

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Speaker 1: But but in the current environment, I mean what what

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Speaker 1: I believe and many other housing economists also believe, is

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Speaker 1: that the real challenge in the current marketplaces of big

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Speaker 1: imbalance between housing demand and housing supply. There's just not

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Speaker 1: enough housing, not just homes, it's also apartments. Just overall,

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Speaker 1: how housing in the United States, after a decade of

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Speaker 1: slow building is still way below what we need and affect.

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Speaker 1: Some research my team is working on is to calculate

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Speaker 1: just how far we are an aggregate short of what

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Speaker 1: we need. So there's a there's a big imbalance in

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Speaker 1: the housing market between supply and demand. The United States

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Speaker 1: is just building too few housing units relative to what

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Speaker 1: our growing population needs. Is not just single family homes,

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Speaker 1: also apartments. And you see that in the rental market

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Speaker 1: as well. So home prices and rents rising above income.

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Speaker 1: Has been doing that for several years, and that is

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Speaker 1: creating a lot of pressure and housing markets. That's driving

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Speaker 1: I think the primary factor that's driving higher home price.

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Speaker 1: Let's delve into that issue of why we have now

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Speaker 1: an undersupply of of both homes and multi family units.

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Speaker 1: Some of it very regional, depends on a little bit

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Speaker 1: of nimby. You look at San Francisco and parts of

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Speaker 1: New York. People are reluctant to allow new projects to

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Speaker 1: go up. They don't want their views blocked, they don't

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Speaker 1: want more concentration, more traffic. Some of it is uh

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Speaker 1: not a whole lot of economic mobility is one of

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Speaker 1: the issues that that we've looked at. But really the

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Speaker 1: key question is we had so much overbuilding going on

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Speaker 1: in oh four, oh five, oh six. Have we burnt

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Speaker 1: off that excess supply? Are we now really running a

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Speaker 1: full deficit relative to household formation? That's that's what I

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Speaker 1: believe now. There's a little bit to unpacked there, because

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Speaker 1: if you took all the housing units in the country

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Speaker 1: and we matched up all the people, there might be

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Speaker 1: a little bit of balance. And what the challenges that

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Speaker 1: a lot of the housing units that are currently available

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Speaker 1: or in places where there's not a lot of jobs

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Speaker 1: and so the fact that you have sort of a

432
00:22:39,160 --> 00:22:41,840
Speaker 1: lot of you know, housing in parts of the Midwest

433
00:22:41,880 --> 00:22:45,280
Speaker 1: and Northeast that are seeing population decline doesn't really help out.

434
00:22:45,320 --> 00:22:48,560
Speaker 1: When you have hot housing markets places like California or

435
00:22:48,600 --> 00:22:51,800
Speaker 1: in Texas and some places, building is wrapping up, but

436
00:22:51,800 --> 00:22:55,040
Speaker 1: it's still struggling to match. So you're seeing that real pressure.

437
00:22:55,040 --> 00:22:58,400
Speaker 1: They're pushing up home prices. Is there anything we can

438
00:22:58,440 --> 00:23:02,640
Speaker 1: do to facilitate the construt ouction of more residential real estate.

439
00:23:02,680 --> 00:23:04,800
Speaker 1: I mean, clearly there's going to be in need as

440
00:23:04,840 --> 00:23:09,240
Speaker 1: our population continues to grow. There are things, um, and

441
00:23:09,280 --> 00:23:11,040
Speaker 1: there's things In fact, Freddie Mack has been looking at

442
00:23:11,040 --> 00:23:13,800
Speaker 1: in particular part of a small component, but an important

443
00:23:13,840 --> 00:23:16,800
Speaker 1: components around manufactured housing, which in a lot of places

444
00:23:16,800 --> 00:23:19,600
Speaker 1: about of rural areas, Uh, that can be a very

445
00:23:19,600 --> 00:23:23,000
Speaker 1: affordable product. And so finding ways to finance that is

446
00:23:23,040 --> 00:23:25,960
Speaker 1: I think an important contribution. Although in aggregate that's going

447
00:23:26,040 --> 00:23:28,040
Speaker 1: to be marginal. But you've got to start adding up

448
00:23:28,040 --> 00:23:31,200
Speaker 1: marginal things because I think, uh, there's no national policy

449
00:23:31,280 --> 00:23:33,120
Speaker 1: I think that can fix it. On the supply side,

450
00:23:33,119 --> 00:23:35,040
Speaker 1: a lot of it has to do with local zoning

451
00:23:35,400 --> 00:23:37,639
Speaker 1: or a lack of labor uh, and so that I

452
00:23:37,640 --> 00:23:41,159
Speaker 1: think we're seeing overall economy is shortages of labor across

453
00:23:41,160 --> 00:23:44,920
Speaker 1: the board, really in construction because I know, again going

454
00:23:44,960 --> 00:23:48,359
Speaker 1: back to the early two thousands, a lot of the

455
00:23:48,400 --> 00:23:52,080
Speaker 1: construction workers might not have been here legally, and those

456
00:23:52,080 --> 00:23:55,360
Speaker 1: folks will all left the country during the financial crisis

457
00:23:55,640 --> 00:23:58,479
Speaker 1: and apparently have not come back. Is this still an

458
00:23:58,520 --> 00:24:02,239
Speaker 1: ongoing dreg on on home manufacturing. We absolutely lack of

459
00:24:02,400 --> 00:24:04,399
Speaker 1: a labor is a key challenge. And part of the

460
00:24:04,520 --> 00:24:07,240
Speaker 1: challenge is also the skilled labor that's available in the

461
00:24:07,240 --> 00:24:11,320
Speaker 1: construction industry is also facing you knows, competing demands in

462
00:24:11,400 --> 00:24:13,920
Speaker 1: terms of remodeling. We've got a lot of boomers. We've

463
00:24:13,920 --> 00:24:15,679
Speaker 1: looked at sort of the housing stock as it is

464
00:24:15,760 --> 00:24:18,000
Speaker 1: relative to the needs of a lot of seniors who

465
00:24:18,000 --> 00:24:20,640
Speaker 1: are looking to age in place, UH, and they need

466
00:24:20,680 --> 00:24:22,640
Speaker 1: to do remodeling to their house to make it sort

467
00:24:22,680 --> 00:24:25,600
Speaker 1: of conform to what they're gonna need. And that sort

468
00:24:25,640 --> 00:24:28,800
Speaker 1: of competes away limited construction workers as well, because that's

469
00:24:28,800 --> 00:24:32,879
Speaker 1: a relatively low productivity UH area. So that means you

470
00:24:32,920 --> 00:24:36,639
Speaker 1: need more workers to do more a similar amount, and

471
00:24:36,640 --> 00:24:39,840
Speaker 1: so that puts again more pressure. But across the board,

472
00:24:40,520 --> 00:24:44,480
Speaker 1: home builders are having a hard time finding work skilled

473
00:24:44,560 --> 00:24:47,240
Speaker 1: labor in particular that they need to match and ramp

474
00:24:47,359 --> 00:24:49,600
Speaker 1: up production. You know, I could always tell when we're

475
00:24:49,720 --> 00:24:53,439
Speaker 1: later in the economic cycle when you go to higher

476
00:24:53,560 --> 00:24:57,520
Speaker 1: contractors and other people just to put on a new roof,

477
00:24:57,600 --> 00:25:01,040
Speaker 1: for do landscaping at a home, and the very difficult

478
00:25:01,080 --> 00:25:05,440
Speaker 1: to find. But I noticed that much earlier this cycle,

479
00:25:05,520 --> 00:25:08,560
Speaker 1: and I didn't put together, oh it's a labor shortage.

480
00:25:08,560 --> 00:25:11,560
Speaker 1: It's not just that the the economy's heating up that

481
00:25:11,560 --> 00:25:15,360
Speaker 1: that's really a very interesting observation on your part. Let

482
00:25:15,359 --> 00:25:19,720
Speaker 1: me ask you a bit about the bifurcated housing market.

483
00:25:19,760 --> 00:25:22,760
Speaker 1: We've had a bit of a bifurcated recovery. If you

484
00:25:22,800 --> 00:25:25,720
Speaker 1: were in the right geography or the right career or

485
00:25:25,720 --> 00:25:29,320
Speaker 1: the right um education level, you did pretty well in

486
00:25:29,359 --> 00:25:33,440
Speaker 1: this recovery. And if you weren't, you didn't. We see

487
00:25:33,520 --> 00:25:36,800
Speaker 1: sort of a parallel development and housing. There are housing

488
00:25:36,840 --> 00:25:40,480
Speaker 1: winning areas and housing not so winning areas. Are you

489
00:25:40,520 --> 00:25:45,439
Speaker 1: seeing something similar to those anecdotal observations? Absolutely? You know,

490
00:25:45,480 --> 00:25:47,760
Speaker 1: we spent a lot of time thinking about home prices

491
00:25:47,800 --> 00:25:49,320
Speaker 1: and what the trends are because I think it tells

492
00:25:49,320 --> 00:25:51,800
Speaker 1: you a lot about what's happening, Uh, not everything, but

493
00:25:51,840 --> 00:25:53,399
Speaker 1: it tells you a lot. And if you look at

494
00:25:53,440 --> 00:25:56,440
Speaker 1: sort of the national home prices have been rising somewhere

495
00:25:56,480 --> 00:25:59,760
Speaker 1: around six percent, depending on the particular index, but a

496
00:25:59,800 --> 00:26:01,720
Speaker 1: lot them are showing a similar trend of around six

497
00:26:01,760 --> 00:26:05,240
Speaker 1: percent nationally. But you go to the subnational level, you know,

498
00:26:05,280 --> 00:26:08,040
Speaker 1: to certain metro areas, it's easily double that. It's on fire,

499
00:26:08,240 --> 00:26:12,600
Speaker 1: on fire, Seattle of Las Vegas, in fact, very very

500
00:26:12,600 --> 00:26:15,200
Speaker 1: strong house price growth there, whereas you go to parts

501
00:26:15,200 --> 00:26:18,320
Speaker 1: of the Midwest and Northeast, much more moderate house price growth.

502
00:26:18,520 --> 00:26:21,639
Speaker 1: What conclusion should we drew about from that, Well, there

503
00:26:21,640 --> 00:26:23,480
Speaker 1: are two things that we've sort of looked at at that.

504
00:26:24,600 --> 00:26:27,600
Speaker 1: One is, for a lot of the young adults in

505
00:26:27,640 --> 00:26:31,000
Speaker 1: this country, these rising housing costs are real challenge. You know,

506
00:26:31,119 --> 00:26:32,800
Speaker 1: if you're a homeowner and home prices go up a lot,

507
00:26:32,840 --> 00:26:34,600
Speaker 1: while you get a lot of equity, but if you're

508
00:26:34,640 --> 00:26:38,879
Speaker 1: a new potential first time buyer or renter, even higher

509
00:26:38,920 --> 00:26:42,400
Speaker 1: housing costs are really just make it tougher. Already for

510
00:26:42,440 --> 00:26:44,639
Speaker 1: a generation you know that's had I think a pretty

511
00:26:44,640 --> 00:26:47,200
Speaker 1: tough economic environment. Sure, they came of age right in

512
00:26:47,240 --> 00:26:50,000
Speaker 1: the middle of the financial crisis, and that leaves a lasting,

513
00:26:50,440 --> 00:26:52,840
Speaker 1: lasting impact. Absolutely. In fact, one of the things we

514
00:26:52,840 --> 00:26:54,960
Speaker 1: looked at was what about household formation, because there's been

515
00:26:54,960 --> 00:26:57,399
Speaker 1: a lot of trend of young adults doubling off they

516
00:26:57,400 --> 00:27:01,000
Speaker 1: live with roommates or uh, non build spend parents basement

517
00:27:01,040 --> 00:27:04,399
Speaker 1: as well. I mean, it's huge numbers. The percentages are

518
00:27:04,600 --> 00:27:06,159
Speaker 1: might seem small, but you add of the numbers as

519
00:27:06,240 --> 00:27:09,879
Speaker 1: millions of people. Uh. In fact, we estimated that about

520
00:27:10,040 --> 00:27:12,440
Speaker 1: if you look at the thirty four year old population,

521
00:27:12,800 --> 00:27:17,040
Speaker 1: there's about one point six million fewer households than what

522
00:27:17,119 --> 00:27:19,360
Speaker 1: you would have if we were living in an economic

523
00:27:19,440 --> 00:27:22,680
Speaker 1: environment like the early two thousands. Now, I was under

524
00:27:22,680 --> 00:27:25,639
Speaker 1: the impression that we've started to see that reverse, that

525
00:27:25,840 --> 00:27:30,119
Speaker 1: new household formations are occurring, and millennials are getting married,

526
00:27:30,520 --> 00:27:34,240
Speaker 1: perhaps later than prior generations, but the worst effects of

527
00:27:34,280 --> 00:27:38,080
Speaker 1: the Great Financial Crisis in that space are unwinding. Uh.

528
00:27:38,480 --> 00:27:40,800
Speaker 1: Am I more or less right with that? Or I

529
00:27:40,840 --> 00:27:42,679
Speaker 1: think so? I mean we're seeing that. Part of it

530
00:27:42,720 --> 00:27:44,240
Speaker 1: is sort of is you have a shock and is

531
00:27:44,240 --> 00:27:46,520
Speaker 1: it permanent? And if you look at life cycle evidence, Unfortunately,

532
00:27:46,560 --> 00:27:48,720
Speaker 1: some of the evidence commosly looked at, it suggests that

533
00:27:48,760 --> 00:27:51,240
Speaker 1: these effects are long lasting. They linger for a long

534
00:27:51,280 --> 00:27:53,320
Speaker 1: long time. They linger because you get behind in the

535
00:27:53,400 --> 00:27:55,800
Speaker 1: job market, you take a come in at a lower salary,

536
00:27:55,800 --> 00:27:58,040
Speaker 1: and that may have a permanent effect, but you are healing.

537
00:27:58,359 --> 00:28:00,000
Speaker 1: Labor market is heating up. We've seen a lot of

538
00:28:00,040 --> 00:28:03,240
Speaker 1: job growth and we are seeing even within our own data,

539
00:28:03,400 --> 00:28:06,040
Speaker 1: upward trends the first time home buyers. So they are

540
00:28:06,080 --> 00:28:08,240
Speaker 1: showing up in the marketplace. They're showing up his renters,

541
00:28:08,240 --> 00:28:10,919
Speaker 1: they're showing up his home buyers. But they still got

542
00:28:10,960 --> 00:28:13,240
Speaker 1: a lot of ground to make up as a group.

543
00:28:13,280 --> 00:28:15,000
Speaker 1: And so teasing out how much of that is just

544
00:28:15,080 --> 00:28:17,600
Speaker 1: aging and how much of that is actual catching up

545
00:28:17,640 --> 00:28:19,600
Speaker 1: as part of sort of the challenge and what economists

546
00:28:19,640 --> 00:28:21,800
Speaker 1: like me can help sort of provide some analysis on

547
00:28:22,320 --> 00:28:24,200
Speaker 1: UH And so we're seeing that. But if you think

548
00:28:24,200 --> 00:28:26,080
Speaker 1: about the future of the U. S. Housing market, I'm

549
00:28:26,119 --> 00:28:29,479
Speaker 1: fundamentally optimistic. And the reason why it's because we have

550
00:28:29,680 --> 00:28:31,919
Speaker 1: a large amount of pent up demand and if the

551
00:28:31,920 --> 00:28:35,199
Speaker 1: economy stays, you know, relatively strong, we should continue to

552
00:28:35,200 --> 00:28:37,680
Speaker 1: see that demand showing up over you know, the next

553
00:28:37,760 --> 00:28:41,240
Speaker 1: few years. So let me take that in extent that

554
00:28:41,320 --> 00:28:45,320
Speaker 1: to a different question. Market bottomed in oh nine, We've

555
00:28:45,320 --> 00:28:48,640
Speaker 1: had a really long run since then, the economy has expanded,

556
00:28:49,040 --> 00:28:52,560
Speaker 1: albeit below historic trend, but for a very long time.

557
00:28:53,360 --> 00:28:56,840
Speaker 1: To me, then implies that this isn't the latter stages

558
00:28:56,960 --> 00:29:00,280
Speaker 1: that we're really ramping up here. I'm hearing from you.

559
00:29:00,360 --> 00:29:03,719
Speaker 1: There's a ton of headroom in the housing market. This

560
00:29:03,800 --> 00:29:07,840
Speaker 1: can continue to trend in a positive direction for a

561
00:29:07,880 --> 00:29:10,400
Speaker 1: good couple or more years. It's not like housing is

562
00:29:10,440 --> 00:29:12,720
Speaker 1: peaking and is about to roll over. There's a lot

563
00:29:12,720 --> 00:29:14,920
Speaker 1: of room to grow here, isn't there. I think so

564
00:29:15,320 --> 00:29:17,719
Speaker 1: there is a challenge, you know, if rates continue, mortgage

565
00:29:17,720 --> 00:29:20,640
Speaker 1: interest rates continue to rise, I think that will slow

566
00:29:21,000 --> 00:29:23,400
Speaker 1: the growth, but there's still I think enough headroom that

567
00:29:23,480 --> 00:29:25,920
Speaker 1: you could have modest growth over the next couple of years.

568
00:29:25,920 --> 00:29:28,440
Speaker 1: In terms of home sales, I think housing construction has

569
00:29:28,480 --> 00:29:31,640
Speaker 1: a lot of room for improvement to match demand. You'll

570
00:29:31,640 --> 00:29:34,959
Speaker 1: probably will see home price growth moderate just because from

571
00:29:35,000 --> 00:29:37,760
Speaker 1: an affordability perspective, and as we get some more supply

572
00:29:38,240 --> 00:29:40,720
Speaker 1: online that will help moderate the price growth. But I

573
00:29:40,760 --> 00:29:43,360
Speaker 1: still think we're going to see a pretty good housing

574
00:29:43,440 --> 00:29:46,160
Speaker 1: market over the next couple of years. If the economy

575
00:29:46,240 --> 00:29:48,200
Speaker 1: is sort of stays on track. What can you tell

576
00:29:48,280 --> 00:29:53,120
Speaker 1: us about how mortgage origination has evolved since the financial crisis.

577
00:29:53,560 --> 00:29:56,200
Speaker 1: I think one of the key factors is that costs

578
00:29:56,240 --> 00:29:59,160
Speaker 1: pressures in the mortgage origination space have risen a lot

579
00:29:59,200 --> 00:30:03,280
Speaker 1: with increased clients cost but also other costs. The cost

580
00:30:03,320 --> 00:30:06,640
Speaker 1: to originate a mortgage has increased quite a lot, and

581
00:30:06,680 --> 00:30:08,960
Speaker 1: so you're seeing that it's quite a bit of consolidation

582
00:30:09,000 --> 00:30:12,040
Speaker 1: in the mortgage space, and I think that may continue

583
00:30:12,040 --> 00:30:15,040
Speaker 1: as some of the smallest players may find that it's

584
00:30:15,080 --> 00:30:17,959
Speaker 1: been more economical for them to either merge, but in

585
00:30:18,040 --> 00:30:19,920
Speaker 1: general sort of that's one of the areas where I

586
00:30:19,920 --> 00:30:22,120
Speaker 1: think Freddie Mack can offer some help in the sense

587
00:30:22,160 --> 00:30:24,840
Speaker 1: of trying to help provide technology and tools that can

588
00:30:24,880 --> 00:30:27,680
Speaker 1: help make the mortgage origination and then selling that into

589
00:30:27,680 --> 00:30:30,960
Speaker 1: the secondary market easier, can help to relieve some of

590
00:30:31,000 --> 00:30:33,640
Speaker 1: that cost pressure. I think it's fundamentally important things we've

591
00:30:33,640 --> 00:30:36,280
Speaker 1: already been doing but are continuing to focus on that

592
00:30:36,360 --> 00:30:40,360
Speaker 1: I think will ultimately help UH provide, you know, lower

593
00:30:40,400 --> 00:30:43,480
Speaker 1: cost mortgages for borrowers. Can you stick around a little bit,

594
00:30:43,520 --> 00:30:46,120
Speaker 1: I'll have a ton more questions for you. Absolutely. We

595
00:30:46,200 --> 00:30:49,440
Speaker 1: have been speaking with Lenn Kiefer. He is the deputy

596
00:30:49,520 --> 00:30:53,960
Speaker 1: Chief economist at Freddie Mac. If you enjoy this conversation well,

597
00:30:54,000 --> 00:30:56,120
Speaker 1: then be sure to check out our podcast after its

598
00:30:56,440 --> 00:30:59,200
Speaker 1: where we keep the tape rolling and continue discussing all

599
00:30:59,280 --> 00:31:05,680
Speaker 1: things mortgage related. You can find that at iTunes, Stitcher, Overcast,

600
00:31:05,720 --> 00:31:09,760
Speaker 1: Bloomberg dot com, wherever final podcasts are sold. We love

601
00:31:09,800 --> 00:31:14,080
Speaker 1: your comments, feedback and suggestions right to us at m

602
00:31:14,120 --> 00:31:17,640
Speaker 1: IB podcast at Bloomberg dot net. Check out my daily

603
00:31:17,720 --> 00:31:21,040
Speaker 1: column at Bloomberg dot com slash Opinion. You can follow

604
00:31:21,080 --> 00:31:24,520
Speaker 1: me on Twitter at rid Halts. I'm Barry rid Halts.

605
00:31:24,640 --> 00:31:37,760
Speaker 1: You're listening to Masters in Business on Bloomberg Radio. Welcome

606
00:31:37,760 --> 00:31:40,080
Speaker 1: to the podcast, Glynn, Thank you so much for doing this.

607
00:31:40,240 --> 00:31:45,120
Speaker 1: I am a housing geek. I'm really fascinated by this topic. UM.

608
00:31:45,160 --> 00:31:48,920
Speaker 1: I wrote a book for you that was the manifestation

609
00:31:49,080 --> 00:31:55,560
Speaker 1: of of that geekdom, called Bailout Nation. UM. But one

610
00:31:55,560 --> 00:31:58,040
Speaker 1: of the things that I think listeners should be aware

611
00:31:58,080 --> 00:32:02,520
Speaker 1: of relative to the conservatorship of Fannie Mae and Freddie

612
00:32:02,560 --> 00:32:08,000
Speaker 1: Mack was when the FEDS rescued the two g s s,

613
00:32:08,520 --> 00:32:11,760
Speaker 1: they put a whole bunch of conditions on them. They're

614
00:32:11,760 --> 00:32:14,240
Speaker 1: not allowed to lobby Congress. There there's just a whole

615
00:32:14,320 --> 00:32:18,560
Speaker 1: run of things they couldn't do for some reason they

616
00:32:18,600 --> 00:32:22,760
Speaker 1: couldn't remember. Congress never got around to putting the same

617
00:32:22,800 --> 00:32:27,040
Speaker 1: sort of restrictive conditions on Bank America or Goldman Sachs

618
00:32:27,160 --> 00:32:30,160
Speaker 1: or any of the other big entities that were lobbying

619
00:32:30,280 --> 00:32:33,480
Speaker 1: every bit as aggressively as the g s S were

620
00:32:33,480 --> 00:32:38,280
Speaker 1: a pre crisis, So they kind of imposed one set

621
00:32:38,320 --> 00:32:41,440
Speaker 1: of rules for the g c s and ignored the

622
00:32:41,480 --> 00:32:48,080
Speaker 1: bank's roles in lobbying Congress for some really, um let's

623
00:32:48,120 --> 00:32:52,520
Speaker 1: just call a generous regulatory oversight that that contributed in

624
00:32:52,600 --> 00:32:56,240
Speaker 1: some way to the to the UH financial crisis. So

625
00:32:56,440 --> 00:32:59,440
Speaker 1: a lot of questions that people who know who I

626
00:32:59,480 --> 00:33:02,480
Speaker 1: am and what I've written about right around now, they're

627
00:33:02,520 --> 00:33:04,880
Speaker 1: probably thinking, how come results isn't asking him any of

628
00:33:04,880 --> 00:33:09,680
Speaker 1: these questions. It's because you're not allowed by congressional mandate

629
00:33:10,080 --> 00:33:14,400
Speaker 1: to discuss that. Am I overstating that? Or aside from

630
00:33:14,400 --> 00:33:17,560
Speaker 1: the fact you weren't there during the crisis, but there

631
00:33:17,560 --> 00:33:20,520
Speaker 1: are restrictions as to what you can publicly state. Are

632
00:33:20,560 --> 00:33:22,640
Speaker 1: you allowed to answer that or you restricted on that?

633
00:33:23,400 --> 00:33:24,720
Speaker 1: I can answer that, Barry. I mean one of the

634
00:33:24,800 --> 00:33:27,800
Speaker 1: things I try to do, and I think It's important

635
00:33:28,480 --> 00:33:31,400
Speaker 1: is to not you know, over specify what my expertise is.

636
00:33:31,400 --> 00:33:34,080
Speaker 1: So I'm focused on the housing and mortgage market, the economy,

637
00:33:34,280 --> 00:33:37,320
Speaker 1: the economics of that, um, the policy stuff that's really

638
00:33:37,360 --> 00:33:39,560
Speaker 1: other groups if they need an economist to talk about

639
00:33:39,600 --> 00:33:41,920
Speaker 1: what might be the policy, you know, economic implications. I

640
00:33:42,000 --> 00:33:44,520
Speaker 1: might do analysis, but but a lot of that is

641
00:33:44,560 --> 00:33:46,360
Speaker 1: sort of not my area, and so I try to

642
00:33:46,360 --> 00:33:48,840
Speaker 1: stay in my lane and focus on the economy or

643
00:33:48,880 --> 00:33:51,440
Speaker 1: what the mortgage market is doing. Totally fair, can we

644
00:33:51,480 --> 00:33:54,200
Speaker 1: understand that? So let's let's stay in your lane and

645
00:33:54,560 --> 00:33:57,040
Speaker 1: stick to it. The one question I don't know if

646
00:33:57,080 --> 00:33:59,560
Speaker 1: you can ask, but I think it's it's really intriguing.

647
00:34:00,840 --> 00:34:04,040
Speaker 1: For a long time, homeownership was the cornerstone of the

648
00:34:04,040 --> 00:34:09,600
Speaker 1: American economy. Speaking generally within your lane, what are your

649
00:34:09,640 --> 00:34:14,040
Speaker 1: thoughts about this? Is the housing safter still a key

650
00:34:14,120 --> 00:34:16,120
Speaker 1: part of the economy. Is it going to continue to

651
00:34:16,160 --> 00:34:18,960
Speaker 1: be for the foreseeable future? How do you how do

652
00:34:18,960 --> 00:34:22,759
Speaker 1: you fit this into the overall um economic growth that

653
00:34:22,800 --> 00:34:25,520
Speaker 1: we're seeing. Yeah, you know, a couple of years ago,

654
00:34:26,200 --> 00:34:29,640
Speaker 1: uh HUD Housing and Urban Development, they put together a

655
00:34:29,640 --> 00:34:33,640
Speaker 1: publication invited some researchers to write on the provocative title,

656
00:34:33,680 --> 00:34:35,920
Speaker 1: could the homeownership rate in the United States fall below

657
00:34:37,280 --> 00:34:43,439
Speaker 1: what is it currently? And that was peaked almost like yeah,

658
00:34:43,760 --> 00:34:46,120
Speaker 1: right in the middle of oh six O seven something

659
00:34:46,160 --> 00:34:48,799
Speaker 1: like that. Yeah, yeah, I actually peaked an O four

660
00:34:48,880 --> 00:34:50,400
Speaker 1: and then a no. Six again it sort of hit

661
00:34:50,520 --> 00:34:53,560
Speaker 1: around that sixty nine rate double top. But they were

662
00:34:53,600 --> 00:34:56,239
Speaker 1: they were really focused on, Oh, this analysis was saying, oh,

663
00:34:56,239 --> 00:34:58,560
Speaker 1: could the homeownership rate you know, drop two levels that

664
00:34:58,600 --> 00:35:01,200
Speaker 1: we haven't seen since you know then I team teen fifties,

665
00:35:01,200 --> 00:35:03,000
Speaker 1: and so we took that up and did some analysis

666
00:35:03,040 --> 00:35:05,000
Speaker 1: to try and see and look at that and say,

667
00:35:05,040 --> 00:35:07,879
Speaker 1: it doesn't seem the case. I mean, it may it's

668
00:35:07,960 --> 00:35:10,319
Speaker 1: unlikely that the United States is gonna see a home

669
00:35:10,360 --> 00:35:13,520
Speaker 1: ownership right back around six, given sort of demographics and

670
00:35:13,560 --> 00:35:17,719
Speaker 1: other forces. But I think there's some upward momentum because

671
00:35:17,719 --> 00:35:20,480
Speaker 1: we've got an aging population that tends to have homeownership,

672
00:35:20,600 --> 00:35:24,320
Speaker 1: and the populations that may have traditionally had lower homeownership

673
00:35:24,400 --> 00:35:27,360
Speaker 1: rates may see that tick up modestly. And so I

674
00:35:27,400 --> 00:35:29,600
Speaker 1: think that's an important part of sort of the American

675
00:35:29,800 --> 00:35:32,759
Speaker 1: you know, economic life. I think home ownership is not

676
00:35:32,840 --> 00:35:35,120
Speaker 1: for everyone, and everything's not Everyone doesn't need to have that,

677
00:35:35,160 --> 00:35:36,680
Speaker 1: but a lot of people aspire to that, and so

678
00:35:36,800 --> 00:35:40,239
Speaker 1: making that possible I think in a responsible way is

679
00:35:40,320 --> 00:35:43,440
Speaker 1: an important thing to do. But sort of a particular

680
00:35:43,520 --> 00:35:45,399
Speaker 1: target or a number or something like that, I don't

681
00:35:45,440 --> 00:35:47,120
Speaker 1: think that's that's the way to think about. It's really

682
00:35:47,120 --> 00:35:49,000
Speaker 1: to think about. Is the economy sort of providing the

683
00:35:49,000 --> 00:35:52,280
Speaker 1: opportunity for folks who have good credit who would qualify

684
00:35:52,320 --> 00:35:55,319
Speaker 1: for mortgage. Are they able to get sort of mortgage

685
00:35:55,320 --> 00:35:59,640
Speaker 1: credit and financing? So you reference changes in some of

686
00:35:59,640 --> 00:36:04,279
Speaker 1: them graphics. Let's dive into that a little bit. You know,

687
00:36:04,480 --> 00:36:07,000
Speaker 1: if you bought a house in the fifties or sixties,

688
00:36:07,360 --> 00:36:12,480
Speaker 1: you had a huge demographic tail wind at your back. Uh,

689
00:36:12,520 --> 00:36:15,000
Speaker 1: and a lot of people who are retiring over the

690
00:36:15,080 --> 00:36:18,920
Speaker 1: past couple of years got to benefit from a country

691
00:36:19,000 --> 00:36:21,080
Speaker 1: that had I don't know, a hundred and fifty million

692
00:36:21,120 --> 00:36:23,440
Speaker 1: people and now are well over three and a quarter

693
00:36:23,880 --> 00:36:29,680
Speaker 1: million people. What is the impact on housing if fertility

694
00:36:29,760 --> 00:36:32,640
Speaker 1: rates continue to fall and we end up with a

695
00:36:32,840 --> 00:36:37,400
Speaker 1: fairly level population. If we don't see population growth, well

696
00:36:37,480 --> 00:36:40,600
Speaker 1: you have to replace old, decrepit homes. But really that's

697
00:36:40,600 --> 00:36:43,680
Speaker 1: a key driver, isn't it. That's absolutely the case, Although

698
00:36:43,719 --> 00:36:46,280
Speaker 1: I think we have to a little bit of caution.

699
00:36:46,400 --> 00:36:48,759
Speaker 1: Right back in the eighties or nineties, some economists wrote

700
00:36:48,800 --> 00:36:50,719
Speaker 1: sort of looked at the housing marketing, we're suggesting, oh,

701
00:36:50,760 --> 00:36:53,560
Speaker 1: the housing markets gonna crash in the nineties. Uh. And

702
00:36:53,600 --> 00:36:56,200
Speaker 1: they were think based on off of historical demographic trends.

703
00:36:56,239 --> 00:36:58,160
Speaker 1: But what they didn't account for was the fact that

704
00:36:58,239 --> 00:37:01,200
Speaker 1: people were living longer and healthy lives. And so one

705
00:37:01,200 --> 00:37:03,000
Speaker 1: of the key things we've seen is that, you know,

706
00:37:03,040 --> 00:37:06,680
Speaker 1: the boomer generation has been the healthiest generation. They are

707
00:37:06,719 --> 00:37:09,719
Speaker 1: living longer, they're intending to live longer, and so you're

708
00:37:09,719 --> 00:37:12,719
Speaker 1: not gonna necessarily see the same falloff in you know

709
00:37:12,920 --> 00:37:15,920
Speaker 1: or supply coming online from you know, boomers you know

710
00:37:15,960 --> 00:37:18,719
Speaker 1: moving to you know, out of home ownership or out

711
00:37:18,719 --> 00:37:21,799
Speaker 1: of their apartments. Uh, that's probably not gonna happen. Where

712
00:37:21,800 --> 00:37:25,000
Speaker 1: it will happen later. Well, well, now, let's assume the

713
00:37:25,080 --> 00:37:30,439
Speaker 1: longevity factor is part of the demographic question. Wouldn't that

714
00:37:30,600 --> 00:37:33,319
Speaker 1: just change the type of home ownership. You'll see more

715
00:37:33,360 --> 00:37:38,480
Speaker 1: people in either active retirement communities or assisted living facilities,

716
00:37:38,840 --> 00:37:42,120
Speaker 1: or communities where you still own your own home, but

717
00:37:42,640 --> 00:37:47,160
Speaker 1: it's geared more for a different age lifestyle. You may

718
00:37:47,200 --> 00:37:48,880
Speaker 1: although I think that's a little bit later because the

719
00:37:48,880 --> 00:37:50,840
Speaker 1: boomers as a generation, some of them are still I

720
00:37:50,840 --> 00:37:53,640
Speaker 1: think the youngest are still in their fifties, so they

721
00:37:53,680 --> 00:37:56,680
Speaker 1: still have I think the active lifestyle is more like

722
00:37:56,760 --> 00:37:59,120
Speaker 1: if you look at the amenities for example, UH folks,

723
00:37:59,200 --> 00:38:01,839
Speaker 1: economists have survey's sort of folks in that fifty five

724
00:38:01,840 --> 00:38:03,960
Speaker 1: plus generation, what are they looking for in terms of housing,

725
00:38:04,360 --> 00:38:07,480
Speaker 1: Very similar to the basket of sort of amenities that

726
00:38:07,920 --> 00:38:10,879
Speaker 1: UH millennials want, with the sole exception they're not looking

727
00:38:10,880 --> 00:38:14,680
Speaker 1: for so much for playgrounds. But but but overall, you know,

728
00:38:14,719 --> 00:38:16,759
Speaker 1: they're they're looking for the same basket and they are

729
00:38:16,800 --> 00:38:19,319
Speaker 1: broadly speaking much healthier, and so they're sort of not

730
00:38:19,360 --> 00:38:21,600
Speaker 1: moving assisted living and that sort of that that end

731
00:38:21,600 --> 00:38:24,920
Speaker 1: of life is in his generation is more you know,

732
00:38:25,000 --> 00:38:27,799
Speaker 1: several decades out in terms of where the boomers are

733
00:38:27,840 --> 00:38:31,000
Speaker 1: in general, and so I think that's gonna boost overall

734
00:38:31,040 --> 00:38:34,239
Speaker 1: demand effects of an an economists in our department have

735
00:38:34,280 --> 00:38:36,279
Speaker 1: looked at that, and it's going to have a very

736
00:38:36,320 --> 00:38:39,200
Speaker 1: large effect on sort of taking supply that would otherwise

737
00:38:39,200 --> 00:38:41,799
Speaker 1: be available for millennials out of the market. And that's

738
00:38:41,800 --> 00:38:44,719
Speaker 1: why I believe housing markets still needs to build more

739
00:38:44,960 --> 00:38:48,399
Speaker 1: units to supply the population. So you're not seeing demographic

740
00:38:48,440 --> 00:38:51,359
Speaker 1: headwinds like a number of people. Harry Dent is one

741
00:38:51,480 --> 00:38:56,400
Speaker 1: some other people have written, you know, the coming population crash. Um,

742
00:38:56,440 --> 00:38:58,640
Speaker 1: you're not seeing that sort of thing anywhere off in

743
00:38:58,640 --> 00:39:00,840
Speaker 1: the future, not in the not in the twenties. Perhaps

744
00:39:00,840 --> 00:39:06,000
Speaker 1: in all right and um. You had mentioned previously multi

745
00:39:06,040 --> 00:39:12,440
Speaker 1: family mortgages, way back when the typical Fannie may or

746
00:39:12,480 --> 00:39:16,960
Speaker 1: Freddie Mac securitized mortgage was a single family home. Tell

747
00:39:17,040 --> 00:39:20,240
Speaker 1: us a little bit about when the idea of multi

748
00:39:20,239 --> 00:39:26,120
Speaker 1: family financing came about. Oh, well, I think there's different opponents,

749
00:39:26,160 --> 00:39:28,120
Speaker 1: but I think one of the important innovations that that

750
00:39:28,239 --> 00:39:30,120
Speaker 1: was made was the credit risk transfer. We talked a

751
00:39:30,120 --> 00:39:32,120
Speaker 1: little bit about that about selling to investors. The credit

752
00:39:32,200 --> 00:39:35,640
Speaker 1: risk actually started in our multifamily division. They were ahead

753
00:39:35,680 --> 00:39:38,200
Speaker 1: of the single family in terms of placing those those

754
00:39:38,360 --> 00:39:40,239
Speaker 1: more mortgages into securities. I believe it was around two

755
00:39:40,239 --> 00:39:42,600
Speaker 1: thousand nine we started what we call our K deals,

756
00:39:42,600 --> 00:39:45,719
Speaker 1: which were those multi K deals. That's just the name

757
00:39:45,760 --> 00:39:50,120
Speaker 1: of the security that securitizes multi family loans and sells

758
00:39:50,160 --> 00:39:54,359
Speaker 1: that credit risk to investors. How big aspect of the

759
00:39:54,400 --> 00:40:00,000
Speaker 1: business of Freddy MCCA are multi family mortgage securitization H

760
00:40:01,320 --> 00:40:03,359
Speaker 1: I don't have the number on the is it one,

761
00:40:03,360 --> 00:40:06,440
Speaker 1: I let me react. Is it a tiny niche or

762
00:40:06,560 --> 00:40:10,920
Speaker 1: is it UH half decent and growing slice of the business.

763
00:40:11,120 --> 00:40:14,160
Speaker 1: It's absolutely been growing. I think Freddie has been the

764
00:40:14,280 --> 00:40:19,040
Speaker 1: largest supplier multifamily financing in the overall marketplace in recent years,

765
00:40:19,080 --> 00:40:22,920
Speaker 1: and we've senancing or securitizing other fundings providing funding for

766
00:40:22,960 --> 00:40:24,840
Speaker 1: the multi family market. If you look at sort of

767
00:40:24,840 --> 00:40:29,120
Speaker 1: how where does the funding for multifamily UH apartments come from?

768
00:40:29,160 --> 00:40:32,680
Speaker 1: You can look at life insurance companies, banks, uh, Fannie MAE,

769
00:40:32,760 --> 00:40:35,080
Speaker 1: and Freddie Macfreddie I think was the largest single source

770
00:40:35,520 --> 00:40:38,960
Speaker 1: of funding in that marketplace in certain recent years UM.

771
00:40:39,120 --> 00:40:42,239
Speaker 1: And so that's been a large and growing business. Now

772
00:40:42,239 --> 00:40:45,560
Speaker 1: compared to our single family business, it's relatively small, just

773
00:40:45,560 --> 00:40:48,319
Speaker 1: because the single family business is a lot larger in

774
00:40:48,400 --> 00:40:52,160
Speaker 1: terms of the overall sort of mortgage finance for the

775
00:40:52,239 --> 00:40:54,760
Speaker 1: United States. One of the things that was pretty obvious

776
00:40:54,840 --> 00:40:58,960
Speaker 1: when we looked at the data post crisis was that, well,

777
00:40:59,000 --> 00:41:01,640
Speaker 1: you have certain number of these existing homes and typically

778
00:41:02,400 --> 00:41:04,960
Speaker 1: UM when you look at existing home sales, new home

779
00:41:05,000 --> 00:41:07,480
Speaker 1: sales or something like a sixth or a seventh of that,

780
00:41:08,320 --> 00:41:11,560
Speaker 1: But the big change was the rise of of multi

781
00:41:11,600 --> 00:41:15,440
Speaker 1: family homes, apartment buildings, any sort of rental as opposed

782
00:41:15,440 --> 00:41:19,319
Speaker 1: to ownership. Is that trend continuing or is that kind

783
00:41:19,320 --> 00:41:22,319
Speaker 1: of leveled off? As as the economy has gotten better,

784
00:41:22,760 --> 00:41:24,800
Speaker 1: I think you're starting to see a very beginning. The

785
00:41:24,880 --> 00:41:26,879
Speaker 1: data is and all all there. Yeah, I would sort

786
00:41:26,920 --> 00:41:28,680
Speaker 1: of have to see, but I think you're seeing some

787
00:41:28,760 --> 00:41:30,719
Speaker 1: leveling all for sure. There isn't so much as a

788
00:41:30,760 --> 00:41:33,239
Speaker 1: movement as we saw back in the early crisis. Here

789
00:41:33,280 --> 00:41:34,920
Speaker 1: is two thousand ten, there was a big shift of

790
00:41:34,920 --> 00:41:38,480
Speaker 1: single family homes, for example, from ownership to rentorship. Some

791
00:41:38,560 --> 00:41:41,200
Speaker 1: of that has remained in rentorship, but you're seeing the

792
00:41:41,200 --> 00:41:43,520
Speaker 1: home ownership break take off a little bit. We may

793
00:41:43,560 --> 00:41:46,280
Speaker 1: continue to see some some uptrend there and some shifting

794
00:41:46,320 --> 00:41:48,360
Speaker 1: of those homes, but not in any big way in

795
00:41:48,400 --> 00:41:51,680
Speaker 1: any data that I've seen. One of the cheapest sectors

796
00:41:51,800 --> 00:41:55,680
Speaker 1: of the US stock market has been the home builders.

797
00:41:56,200 --> 00:42:01,840
Speaker 1: They are unloved and unwanted, and therefore are very inexpensive.

798
00:42:02,600 --> 00:42:04,560
Speaker 1: If if you were going to make a bet as

799
00:42:04,600 --> 00:42:09,240
Speaker 1: to when home building might start to revert back to normal,

800
00:42:09,719 --> 00:42:11,960
Speaker 1: when we look at a long term chart. We're still

801
00:42:11,960 --> 00:42:16,200
Speaker 1: below the levels that prior recessions bottom Dad, if you

802
00:42:16,239 --> 00:42:19,560
Speaker 1: go back forty years. It's amazing that not only did

803
00:42:19,640 --> 00:42:23,120
Speaker 1: we hit the level where we usually you know, um

804
00:42:23,280 --> 00:42:26,480
Speaker 1: touch basement during recession, we went straight through it and

805
00:42:26,520 --> 00:42:29,319
Speaker 1: down below and we still haven't gotten back up over

806
00:42:29,360 --> 00:42:32,239
Speaker 1: those levels. It's it's quite astonishing. Yeah. Yeah, you mentioned

807
00:42:32,280 --> 00:42:33,920
Speaker 1: some of the charts that I share on Twitter. One

808
00:42:33,920 --> 00:42:35,560
Speaker 1: of my favorite recent ones because it was striking to

809
00:42:35,600 --> 00:42:37,560
Speaker 1: me when I put this together, was to look at

810
00:42:38,239 --> 00:42:41,719
Speaker 1: the housing supplies. You add up single family homes, apartments,

811
00:42:41,920 --> 00:42:44,680
Speaker 1: manufactured homeshipments in the United States, which the Census is

812
00:42:44,719 --> 00:42:47,680
Speaker 1: tracked that since nineteen and you ask sort of for

813
00:42:47,760 --> 00:42:51,279
Speaker 1: full year, the US added about one point to five

814
00:42:51,360 --> 00:42:54,480
Speaker 1: million units, which is up from every year since two

815
00:42:54,480 --> 00:42:58,640
Speaker 1: thousand eight. However, if you compare that number against all

816
00:42:58,719 --> 00:43:01,520
Speaker 1: of the years prior to two thousand eight, only one year,

817
00:43:01,880 --> 00:43:06,960
Speaker 1: one single year, did the US add fewer overall homes, apartments,

818
00:43:06,960 --> 00:43:10,760
Speaker 1: and manufactured homes. And that was two when mortgage interest

819
00:43:10,840 --> 00:43:14,279
Speaker 1: rates had spiked the FED was trying to kill off inflation, uh,

820
00:43:14,320 --> 00:43:17,839
Speaker 1: and folks were really struggling in that year. So, which

821
00:43:17,840 --> 00:43:20,040
Speaker 1: is the best year in all about a decade, comparable

822
00:43:20,040 --> 00:43:22,600
Speaker 1: to two in terms of the overall level of building.

823
00:43:23,160 --> 00:43:27,200
Speaker 1: That's that's there's some room for improvement there. I'm scrolling

824
00:43:27,239 --> 00:43:31,879
Speaker 1: through your Twitter feed looking at housing supply and it's

825
00:43:32,480 --> 00:43:34,719
Speaker 1: it's the wrong thing to search FORO because every other

826
00:43:35,320 --> 00:43:38,240
Speaker 1: chart has it. But there are really some amazing data

827
00:43:38,320 --> 00:43:45,239
Speaker 1: points um between population growth and unemployment rate and home prices.

828
00:43:45,040 --> 00:43:49,200
Speaker 1: It's fascinating. I want to reiterate to listeners that they

829
00:43:49,239 --> 00:43:52,239
Speaker 1: should they should uh follow you on Twitter because you

830
00:43:52,280 --> 00:43:56,040
Speaker 1: really put up a tremendous run um of charts. They're

831
00:43:56,040 --> 00:44:00,719
Speaker 1: really quite fascinating. So, um, let me let me ask

832
00:44:00,760 --> 00:44:03,640
Speaker 1: you a broad question that I didn't get too earlier.

833
00:44:04,320 --> 00:44:07,279
Speaker 1: If you had to pick this single most important development

834
00:44:07,440 --> 00:44:11,440
Speaker 1: in the housing finance system over the past decade, what

835
00:44:11,520 --> 00:44:13,880
Speaker 1: would that be. I absolutely think it has to be

836
00:44:13,880 --> 00:44:17,400
Speaker 1: the credit risk transfer, because that's really changed the model

837
00:44:17,440 --> 00:44:20,719
Speaker 1: for you know, the secondary market financing taking a tremendous

838
00:44:20,719 --> 00:44:24,000
Speaker 1: amount of credit risk that was concentrated and Freddie Mack

839
00:44:24,040 --> 00:44:27,680
Speaker 1: and Fannie May and now you have distributed broadly, which

840
00:44:27,719 --> 00:44:30,200
Speaker 1: I think has the potential to really, you know, reduce

841
00:44:30,280 --> 00:44:34,040
Speaker 1: overall risk and the overall housing or finance system by

842
00:44:34,200 --> 00:44:38,080
Speaker 1: creating diversification and so that getting investors comfortable with that,

843
00:44:38,200 --> 00:44:40,799
Speaker 1: getting them to actually, you know, take on that and

844
00:44:41,120 --> 00:44:44,560
Speaker 1: invest in those securities. There's been very brisk demand for those.

845
00:44:44,920 --> 00:44:48,920
Speaker 1: I think has really I think changed fundamentally sort of

846
00:44:48,920 --> 00:44:52,480
Speaker 1: how the US housing finance system operates and how it

847
00:44:52,520 --> 00:44:55,800
Speaker 1: will go look going forward. And that's a cost efficient

848
00:44:56,000 --> 00:45:00,000
Speaker 1: transfer mechanism. It seems kind of complicated to maybe because

849
00:45:00,120 --> 00:45:02,480
Speaker 1: it's it's a little new and I'm not familiar with

850
00:45:02,520 --> 00:45:06,080
Speaker 1: credit risk transfer, But how how efficient is that? Yeah?

851
00:45:06,120 --> 00:45:07,480
Speaker 1: You know, I think one of the important things is

852
00:45:07,480 --> 00:45:10,520
Speaker 1: getting investors, you know, confident about sort of the data,

853
00:45:10,600 --> 00:45:12,320
Speaker 1: confident about the housing market. One of the things I

854
00:45:12,360 --> 00:45:14,680
Speaker 1: did recently, you know, is travel and spoke with you know,

855
00:45:14,719 --> 00:45:18,480
Speaker 1: to UH investors in that marketplace. So we've at different

856
00:45:18,480 --> 00:45:21,319
Speaker 1: events to help folks sort of understand better sort of

857
00:45:21,320 --> 00:45:23,480
Speaker 1: how the housing market looks. How do you think about that?

858
00:45:23,520 --> 00:45:26,160
Speaker 1: How would you understand historical data? All of that. I

859
00:45:26,200 --> 00:45:29,160
Speaker 1: think that's where communication and getting that data and information

860
00:45:29,160 --> 00:45:32,279
Speaker 1: out there is fundamentally important. Because you have more transparency,

861
00:45:32,360 --> 00:45:34,840
Speaker 1: Folks can analyze that data, they can look at it,

862
00:45:34,840 --> 00:45:37,320
Speaker 1: they can build their own models. That's going to create,

863
00:45:37,640 --> 00:45:40,560
Speaker 1: you know, a better confidence in the marketplace and sort

864
00:45:40,600 --> 00:45:44,840
Speaker 1: of the willingness to take on that investment. Quite interesting.

865
00:45:45,280 --> 00:45:48,640
Speaker 1: So this current dare I call it a housing boom?

866
00:45:48,680 --> 00:45:50,399
Speaker 1: I don't know if I could call it that, but

867
00:45:51,080 --> 00:45:57,319
Speaker 1: this most recent leg up in housing despite higher interest rates. Um,

868
00:45:57,400 --> 00:46:01,399
Speaker 1: how is this different than prior economic cycles? What what

869
00:46:01,480 --> 00:46:07,400
Speaker 1: makes this housing cycle somewhat unique? I think the major

870
00:46:07,480 --> 00:46:10,959
Speaker 1: difference is just the depths to which housing construction fell off,

871
00:46:11,440 --> 00:46:13,800
Speaker 1: and so the fact that we built so few units

872
00:46:13,840 --> 00:46:17,200
Speaker 1: for so long helped to correct for some overbuilding in

873
00:46:17,200 --> 00:46:20,680
Speaker 1: certain markets uh last decade and then even more so,

874
00:46:21,120 --> 00:46:22,839
Speaker 1: And so that I think creates a little bit different

875
00:46:22,880 --> 00:46:25,680
Speaker 1: in terms of the sensitivity because you have not only

876
00:46:25,680 --> 00:46:28,200
Speaker 1: that lack of building, but you also have this tremendous

877
00:46:28,200 --> 00:46:32,399
Speaker 1: demographic tail wind from the millennial generation, who are really

878
00:46:32,480 --> 00:46:36,719
Speaker 1: hitting those peak home buying years right around now. We're

879
00:46:36,719 --> 00:46:38,600
Speaker 1: actually a couple of years later. That's why I'm still

880
00:46:38,640 --> 00:46:41,000
Speaker 1: optimistic about the next couple of years, because you know,

881
00:46:41,080 --> 00:46:43,360
Speaker 1: the median age of the first time HomeBuyer is about

882
00:46:43,400 --> 00:46:46,799
Speaker 1: thirty one, I think the meeting age of millennial nine.

883
00:46:46,920 --> 00:46:48,520
Speaker 1: So you still got a couple of years of really

884
00:46:48,560 --> 00:46:51,240
Speaker 1: to that peak demand really starts hitting the housing market,

885
00:46:51,560 --> 00:46:54,200
Speaker 1: and so that I think has helped the overall market

886
00:46:54,800 --> 00:46:59,279
Speaker 1: remain robust despite higher interest rates and very rapid home

887
00:46:59,280 --> 00:47:03,239
Speaker 1: price growth in lot of markets. Quite fascinating. I know,

888
00:47:03,360 --> 00:47:05,760
Speaker 1: I only have you for a finite amount of time.

889
00:47:05,920 --> 00:47:09,320
Speaker 1: Let me jump to my favorite questions that I ask

890
00:47:09,400 --> 00:47:13,120
Speaker 1: all of my guests. Tell us the most important thing

891
00:47:13,200 --> 00:47:17,520
Speaker 1: that we don't know about you. Yeah, I think now

892
00:47:17,600 --> 00:47:19,600
Speaker 1: people who know me personally will know this, but in general,

893
00:47:19,640 --> 00:47:22,359
Speaker 1: sort of in public, they may not realize this is that,

894
00:47:22,600 --> 00:47:26,280
Speaker 1: uh my, I'm probably the second best economist in my household.

895
00:47:27,719 --> 00:47:30,000
Speaker 1: That when I come home, my wife she's also an economist.

896
00:47:30,440 --> 00:47:33,040
Speaker 1: She works actually around housing related issues. She had you know,

897
00:47:33,080 --> 00:47:35,400
Speaker 1: credit risk and things like that. She's a real expert

898
00:47:35,400 --> 00:47:37,319
Speaker 1: on that. And so when I when I come home,

899
00:47:37,360 --> 00:47:39,120
Speaker 1: you know, I have great discussions at work, but I

900
00:47:39,120 --> 00:47:42,640
Speaker 1: can have other discussions you know at home talking about statistics, econometrics,

901
00:47:43,120 --> 00:47:45,879
Speaker 1: things like that. Uh. It's real, you know, exciting talk

902
00:47:46,000 --> 00:47:50,440
Speaker 1: there at home, dinner table conversation. But uh, and that

903
00:47:50,520 --> 00:47:52,200
Speaker 1: I think is really like I kind of I think

904
00:47:52,200 --> 00:47:54,239
Speaker 1: of it as a superpower because it's really you know,

905
00:47:54,320 --> 00:47:56,680
Speaker 1: gives me sort of a real rich, I think perspective

906
00:47:56,680 --> 00:47:59,840
Speaker 1: on things because she's also very you know, clear to

907
00:48:00,000 --> 00:48:01,520
Speaker 1: all me sort of when things are kind of nonsense

908
00:48:01,560 --> 00:48:02,960
Speaker 1: and I'm not making a lot of sense. So she

909
00:48:03,000 --> 00:48:05,359
Speaker 1: has that that perspective, which is great. I was gonna ask,

910
00:48:05,400 --> 00:48:09,400
Speaker 1: how often are you to fundamentally disagreeing about basic tenants

911
00:48:09,400 --> 00:48:12,799
Speaker 1: in in the housing market? Uh, not not too much,

912
00:48:12,840 --> 00:48:15,839
Speaker 1: because she's often right. So I'm I listened to her

913
00:48:15,920 --> 00:48:18,200
Speaker 1: very carefully. You've been married for a long time, I

914
00:48:18,200 --> 00:48:21,080
Speaker 1: could tell. So tell us about your early mentors who

915
00:48:21,080 --> 00:48:24,319
Speaker 1: helped guide your career. Yeah, there too, that that I

916
00:48:24,320 --> 00:48:27,759
Speaker 1: would come to mind that I think are particularly important. Uh.

917
00:48:27,840 --> 00:48:29,680
Speaker 1: If I look at my sort of graduate training at

918
00:48:30,200 --> 00:48:33,600
Speaker 1: Ohio State, Bill Dupor was my advisory, my thesis advisor

919
00:48:33,920 --> 00:48:36,400
Speaker 1: sort of really helped train me and sort of understanding

920
00:48:36,400 --> 00:48:38,759
Speaker 1: and thinking like an economist to bring sort of a

921
00:48:38,760 --> 00:48:43,239
Speaker 1: macroeconomic perspective and understand sort of the models and approaches

922
00:48:43,280 --> 00:48:48,240
Speaker 1: that economists use. That was very important sort of forming

923
00:48:48,480 --> 00:48:50,600
Speaker 1: sort of my thinking as an economist. But then very

924
00:48:50,640 --> 00:48:52,840
Speaker 1: important was when I started at Freddy Mack because we

925
00:48:52,840 --> 00:48:55,240
Speaker 1: talked a little bit about sort of transition to industry,

926
00:48:55,480 --> 00:48:58,120
Speaker 1: and here I was this guy I uh come to

927
00:48:58,160 --> 00:49:00,680
Speaker 1: the market, I was didn't have a lot of industry

928
00:49:00,719 --> 00:49:02,799
Speaker 1: experience that had some kind of theoretical stuff. So my

929
00:49:02,920 --> 00:49:05,160
Speaker 1: first hiring, the guy who hired me a Freddie M

930
00:49:05,440 --> 00:49:08,319
Speaker 1: guy named Dave Roda is still there, uh in a

931
00:49:08,320 --> 00:49:11,560
Speaker 1: different role, but it was really helpful in getting me

932
00:49:11,680 --> 00:49:15,040
Speaker 1: sort of transition to industry to help understand sort of

933
00:49:15,040 --> 00:49:17,520
Speaker 1: think through sort of how the industry is working, how

934
00:49:17,600 --> 00:49:20,200
Speaker 1: the business people are thinking as an economist. He's an

935
00:49:20,200 --> 00:49:22,480
Speaker 1: economist too, uh, And I still see him at lunch

936
00:49:22,520 --> 00:49:24,480
Speaker 1: sometimes and I always have a great conversation whenever I

937
00:49:24,480 --> 00:49:29,520
Speaker 1: see him. Interesting. Uh, what about investors who influenced the

938
00:49:29,520 --> 00:49:36,320
Speaker 1: way you look at housing, real estate, that entire market. Yeah,

939
00:49:36,360 --> 00:49:38,640
Speaker 1: so there are a lot of folks at freddie who

940
00:49:38,719 --> 00:49:40,840
Speaker 1: sort of have a lot of expertise about capital markets

941
00:49:40,880 --> 00:49:43,719
Speaker 1: and that execution, you know. As the economist, I some

942
00:49:43,880 --> 00:49:46,040
Speaker 1: types of some exposure to that, but I really got

943
00:49:46,040 --> 00:49:48,759
Speaker 1: a lot of information from that from our former chief economist,

944
00:49:49,239 --> 00:49:53,040
Speaker 1: Sean mcketty, who he's moved back to the capital market side, um,

945
00:49:53,239 --> 00:49:55,160
Speaker 1: and so he sort of had a lot of perspective

946
00:49:55,160 --> 00:49:57,520
Speaker 1: and information on sort of how sort of the capital

947
00:49:57,520 --> 00:49:59,920
Speaker 1: markets guys are thinking. You know, he'd worked on the street,

948
00:50:00,080 --> 00:50:03,240
Speaker 1: So how does you know street investors think about stuff, which, um,

949
00:50:03,280 --> 00:50:05,439
Speaker 1: as you know, from a pure economics background, I didn't

950
00:50:05,440 --> 00:50:07,400
Speaker 1: have that same perspective. Had a lot of great stories

951
00:50:08,160 --> 00:50:10,120
Speaker 1: about how things went, and so that really I think

952
00:50:10,160 --> 00:50:14,640
Speaker 1: provided a lot of uh valuable insights into how sort

953
00:50:14,640 --> 00:50:17,359
Speaker 1: of folks are thinking and even today how they're thinking,

954
00:50:17,400 --> 00:50:20,640
Speaker 1: because I can ask him what he's seeing. So let's

955
00:50:20,680 --> 00:50:24,319
Speaker 1: talk about everybody's favorite question. Tell us about some of

956
00:50:24,360 --> 00:50:28,239
Speaker 1: your favorite books. What do you read, be they economics

957
00:50:28,320 --> 00:50:31,239
Speaker 1: or housing or or not fiction non fiction? What are

958
00:50:31,239 --> 00:50:33,440
Speaker 1: you enjoying? Well, I don't know how you separate the

959
00:50:33,440 --> 00:50:39,960
Speaker 1: economics from the fiction. Uh. Sometimes that's certainly can be

960
00:50:40,000 --> 00:50:41,960
Speaker 1: a challenge, you know, I mean, this is the stories.

961
00:50:42,480 --> 00:50:45,000
Speaker 1: But actually I think there's one book I think is

962
00:50:45,080 --> 00:50:48,319
Speaker 1: really important, uh, that I really appreciate. I come back

963
00:50:48,320 --> 00:50:50,200
Speaker 1: to constantly is a is a book called The Visual

964
00:50:50,239 --> 00:50:54,640
Speaker 1: Display of Quantitative Information from Edward Tufty, who was a

965
00:50:55,160 --> 00:50:58,759
Speaker 1: professor on data visualization. You mentioned my charts, sort of

966
00:50:58,760 --> 00:51:01,200
Speaker 1: my sort of beginning to come to to to put

967
00:51:01,239 --> 00:51:03,759
Speaker 1: those together was attending one of his Uh, he does

968
00:51:03,800 --> 00:51:06,560
Speaker 1: seminars and reading his books and really was an eye

969
00:51:06,560 --> 00:51:08,759
Speaker 1: opener for thinking about how can we know as a

970
00:51:08,840 --> 00:51:13,600
Speaker 1: data analysts scientists to think think can communicate that information

971
00:51:13,960 --> 00:51:17,520
Speaker 1: to an audience with clarity and precision, but still have

972
00:51:17,840 --> 00:51:22,640
Speaker 1: a lot of complexity and insight. His his work is

973
00:51:22,680 --> 00:51:27,239
Speaker 1: always fantastic. That book is still a regular seller on Amazon,

974
00:51:27,840 --> 00:51:30,160
Speaker 1: and it's something like fifty or sixty hours. It is

975
00:51:30,160 --> 00:51:33,160
Speaker 1: not an inexpensive book. The The other one of his

976
00:51:33,320 --> 00:51:36,920
Speaker 1: that I have at home is Information is Beautiful, which

977
00:51:36,960 --> 00:51:41,520
Speaker 1: is really a lovely a lovely exposition any other books

978
00:51:41,560 --> 00:51:44,040
Speaker 1: you want to mention anything else you're reading just for fun,

979
00:51:44,680 --> 00:51:47,479
Speaker 1: well for fun, but it's been helpful. There's a book

980
00:51:47,480 --> 00:51:50,879
Speaker 1: by Stephen Pinker called A Sense of Style, which because

981
00:51:50,920 --> 00:51:52,680
Speaker 1: a lot of what I do is communicate, And one

982
00:51:52,719 --> 00:51:54,400
Speaker 1: of the sort of areas that I'm really focused on

983
00:51:54,440 --> 00:51:56,360
Speaker 1: and thinking about a lot is how can I be

984
00:51:56,400 --> 00:51:58,960
Speaker 1: a better you know, presenter, How gonna be a better communicator?

985
00:51:59,000 --> 00:52:01,799
Speaker 1: How can be a better writer? And and in that book, um,

986
00:52:01,840 --> 00:52:03,200
Speaker 1: he has there's a lot of great stuff. There were

987
00:52:03,239 --> 00:52:06,120
Speaker 1: one part in particular that I think applies to economists.

988
00:52:06,120 --> 00:52:07,640
Speaker 1: I share it with my team when we talk about

989
00:52:07,640 --> 00:52:10,360
Speaker 1: how can we communicate to our business partners the general

990
00:52:10,360 --> 00:52:14,000
Speaker 1: audience is this idea of the curse of knowledge, where

991
00:52:14,080 --> 00:52:18,719
Speaker 1: when you, as an expert know something, you have difficulty

992
00:52:18,840 --> 00:52:21,279
Speaker 1: imagining what it's like not to know that. And so

993
00:52:21,400 --> 00:52:23,600
Speaker 1: that a lot of like why do academics right terrible?

994
00:52:23,680 --> 00:52:26,719
Speaker 1: Was the curse of that because they know a lot

995
00:52:26,760 --> 00:52:29,040
Speaker 1: and they can't have a hard time empathizing with folks

996
00:52:29,080 --> 00:52:32,160
Speaker 1: who don't. And so keeping that in mind and having

997
00:52:32,160 --> 00:52:35,520
Speaker 1: that empathy, I think is key to becoming a better communicator.

998
00:52:35,800 --> 00:52:38,720
Speaker 1: And so I really enjoy that exposition and other stuff

999
00:52:38,800 --> 00:52:41,239
Speaker 1: in that book is is great too. There is a

1000
00:52:41,360 --> 00:52:45,080
Speaker 1: famous VC and I won't name drop, but he refers

1001
00:52:45,160 --> 00:52:49,160
Speaker 1: to something very parallel, which is when they have start

1002
00:52:49,239 --> 00:52:54,560
Speaker 1: up entrepreneurs requesting um venture investments. He goes one of

1003
00:52:54,600 --> 00:52:57,560
Speaker 1: the he had mentioned one of the things he noticed

1004
00:52:58,160 --> 00:53:01,640
Speaker 1: was the tendency for people who really understood their space

1005
00:53:02,080 --> 00:53:05,560
Speaker 1: and they saw the whole tenure vision to be frustrated

1006
00:53:05,719 --> 00:53:08,399
Speaker 1: that the vcs, how could you not see this? It's

1007
00:53:08,400 --> 00:53:12,520
Speaker 1: so obvious? And now I'm contextualizing that as the curse

1008
00:53:12,600 --> 00:53:15,799
Speaker 1: of the curse of knowledge. That that's quite fascinating, and

1009
00:53:15,800 --> 00:53:20,799
Speaker 1: some of us are more cursed than very funny. Um,

1010
00:53:20,840 --> 00:53:23,279
Speaker 1: what is it about the housing market today that has

1011
00:53:23,320 --> 00:53:27,200
Speaker 1: you excited? Well, so the housing market overall, I mean,

1012
00:53:27,239 --> 00:53:29,120
Speaker 1: I think there's the potential. We talk a lot about

1013
00:53:29,200 --> 00:53:31,560
Speaker 1: demand if I think about it for more from an

1014
00:53:31,960 --> 00:53:34,959
Speaker 1: economist shop or industry shop, I think there's a huge

1015
00:53:35,000 --> 00:53:38,319
Speaker 1: amount of data and information that we are just at

1016
00:53:38,320 --> 00:53:41,359
Speaker 1: the beginning of. You think about big data, the type

1017
00:53:41,400 --> 00:53:44,239
Speaker 1: of information that is becoming available or is available that

1018
00:53:44,280 --> 00:53:47,560
Speaker 1: has not yet been fully tapped in mind, I think

1019
00:53:47,560 --> 00:53:49,959
Speaker 1: that is a huge area of growth. That's an area

1020
00:53:50,000 --> 00:53:52,799
Speaker 1: focus at the firm. Area of focus for myself from

1021
00:53:52,840 --> 00:53:56,279
Speaker 1: a machine learning data analysis programming, how to deal with

1022
00:53:56,280 --> 00:53:58,359
Speaker 1: that information and how to consume it, how to think

1023
00:53:58,360 --> 00:54:01,040
Speaker 1: about it. The economics profession is starting to come to

1024
00:54:01,120 --> 00:54:03,799
Speaker 1: grips with how do you model that, which I think

1025
00:54:03,840 --> 00:54:05,760
Speaker 1: we're a little slow, I think in some of those areas,

1026
00:54:05,800 --> 00:54:08,440
Speaker 1: But there's a lot of exciting work in that dimension,

1027
00:54:08,719 --> 00:54:11,360
Speaker 1: and I think it is only going to grow in

1028
00:54:11,400 --> 00:54:16,680
Speaker 1: ways we cannot even imagine today. Quite quite interesting. Tell

1029
00:54:16,760 --> 00:54:19,720
Speaker 1: us about a time you failed and what you learned

1030
00:54:19,800 --> 00:54:24,879
Speaker 1: from the experience. Yeah, So when I came to from

1031
00:54:25,000 --> 00:54:27,960
Speaker 1: Left Texas and came to the Washington, d C. Area.

1032
00:54:28,360 --> 00:54:31,440
Speaker 1: I was unemployed for about fifteen months between sort of

1033
00:54:31,440 --> 00:54:34,160
Speaker 1: my professor job and getting hired on at Freddie. You know,

1034
00:54:34,239 --> 00:54:35,640
Speaker 1: there's a lot of times where I was sort of

1035
00:54:35,680 --> 00:54:37,520
Speaker 1: looking for a job. Now it didn't help that I was.

1036
00:54:37,680 --> 00:54:39,879
Speaker 1: That was in two thousand and eight and nine, when

1037
00:54:40,000 --> 00:54:42,600
Speaker 1: the economy was in a very tough spot in UH

1038
00:54:42,680 --> 00:54:45,040
Speaker 1: finance was sort of particularly an industry that was in

1039
00:54:45,080 --> 00:54:47,319
Speaker 1: a lot of distress. But you know, I had a

1040
00:54:47,320 --> 00:54:49,520
Speaker 1: hard time. I was coming from an academic background. There

1041
00:54:49,520 --> 00:54:52,279
Speaker 1: weren't academic jobs, wasn't I was trying to transition into

1042
00:54:52,280 --> 00:54:55,200
Speaker 1: industry and really just sort of not matching up, not

1043
00:54:55,360 --> 00:54:58,440
Speaker 1: able to communicate clearly to the to the potential you

1044
00:54:58,480 --> 00:55:00,239
Speaker 1: know jobs. I think I would have been able to

1045
00:55:00,239 --> 00:55:02,399
Speaker 1: do a lot of jobs with the opportunities were tough.

1046
00:55:02,400 --> 00:55:06,360
Speaker 1: It's very competitive, and so continuously sort of coming up short,

1047
00:55:06,800 --> 00:55:09,439
Speaker 1: you know, and then doing that for a long time

1048
00:55:09,560 --> 00:55:12,720
Speaker 1: until finally, as I mentioned, David Freddie gave me a chance.

1049
00:55:13,280 --> 00:55:16,160
Speaker 1: Um with some resistance. I think internally they were skeptical

1050
00:55:16,600 --> 00:55:18,760
Speaker 1: in the group. I think I want them over eventually,

1051
00:55:19,080 --> 00:55:21,600
Speaker 1: but you know sort of how how I would turn out,

1052
00:55:21,680 --> 00:55:24,839
Speaker 1: and so I think that sort of experience. It gave

1053
00:55:24,880 --> 00:55:26,400
Speaker 1: me a little bit of edge to think about. Okay,

1054
00:55:26,400 --> 00:55:28,360
Speaker 1: maybe I could be you know, unemployed again, So how

1055
00:55:28,400 --> 00:55:31,319
Speaker 1: would I keep myself competitive? How to keep myself uh,

1056
00:55:31,360 --> 00:55:34,480
Speaker 1: sort of avoiding that, you know, that idleness for a

1057
00:55:34,520 --> 00:55:39,400
Speaker 1: longer time. Interesting. So what perspective changes in the mortgage

1058
00:55:39,480 --> 00:55:41,960
Speaker 1: market are are you looking forward to? What what do

1059
00:55:42,040 --> 00:55:47,200
Speaker 1: you think is the next set of changes that could

1060
00:55:47,200 --> 00:55:49,960
Speaker 1: have a big positive impact. Well, as I mentioned, I

1061
00:55:50,000 --> 00:55:52,759
Speaker 1: think this data, the data, integrating this data and information.

1062
00:55:52,960 --> 00:55:56,120
Speaker 1: I mean there are tons of information already collected that

1063
00:55:56,239 --> 00:55:59,080
Speaker 1: could be used either to help streamline the process of

1064
00:55:59,080 --> 00:56:02,560
Speaker 1: origination to or costs. I mentioned origination costs have risen

1065
00:56:02,600 --> 00:56:05,319
Speaker 1: a lot. Could we unlock that? I find ways to

1066
00:56:05,320 --> 00:56:09,319
Speaker 1: to use information technology to streamline the processes. I think

1067
00:56:09,320 --> 00:56:11,480
Speaker 1: we're getting some traction on that. But I think that

1068
00:56:11,800 --> 00:56:15,040
Speaker 1: and then tapping that information to effectively understand credit risk,

1069
00:56:15,120 --> 00:56:17,640
Speaker 1: to understand where the market may be headed, I think

1070
00:56:17,760 --> 00:56:21,600
Speaker 1: is enormously important. So what do you do outside of

1071
00:56:21,600 --> 00:56:26,399
Speaker 1: the office for fun, to relax, to just kick back? Yeah, so, uh,

1072
00:56:26,480 --> 00:56:29,120
Speaker 1: I like to you know, do programming on the side,

1073
00:56:29,160 --> 00:56:31,040
Speaker 1: not economics. You know, some of the stuff on the

1074
00:56:31,280 --> 00:56:33,760
Speaker 1: Twitter is actually just me sort of messing around, playing,

1075
00:56:33,800 --> 00:56:37,640
Speaker 1: exploring the ideas. I have two small children who have

1076
00:56:37,719 --> 00:56:39,759
Speaker 1: plenty of ideas for what I could be doing, but

1077
00:56:39,800 --> 00:56:41,480
Speaker 1: they know they're great fun. I mean, I have a

1078
00:56:41,600 --> 00:56:44,680
Speaker 1: have a blast hanging out with them. Uh. And then

1079
00:56:44,760 --> 00:56:46,680
Speaker 1: you know, trying to find some time with the family.

1080
00:56:46,719 --> 00:56:49,400
Speaker 1: I think that's that's I really precious, especially as the

1081
00:56:49,640 --> 00:56:51,360
Speaker 1: kids are so young now and it doesn't last so

1082
00:56:51,400 --> 00:56:55,080
Speaker 1: long for sure. So let's talk a little bit about

1083
00:56:55,440 --> 00:56:59,719
Speaker 1: career advice. If a millennial or recent college grad came

1084
00:56:59,760 --> 00:57:03,280
Speaker 1: to you and said, I'm interested in the housing slash

1085
00:57:03,520 --> 00:57:07,280
Speaker 1: mortgage market, what sort of advice would you give them? Um,

1086
00:57:07,320 --> 00:57:10,280
Speaker 1: So if they were an economist or even a financial analyst,

1087
00:57:10,280 --> 00:57:12,120
Speaker 1: which is a lot of the roles. We actually um

1088
00:57:12,320 --> 00:57:17,000
Speaker 1: work with some new hires in the company in different aspects,

1089
00:57:17,040 --> 00:57:18,920
Speaker 1: and so I do talk to some of some folks.

1090
00:57:19,560 --> 00:57:22,600
Speaker 1: Or we have a rotational program where uh, new college

1091
00:57:22,680 --> 00:57:25,280
Speaker 1: hires will come in and they'll rotate through different groups

1092
00:57:25,320 --> 00:57:26,880
Speaker 1: for about six months at a time. It's a great

1093
00:57:26,920 --> 00:57:29,160
Speaker 1: program where they can learn sort of what happens at

1094
00:57:29,200 --> 00:57:32,240
Speaker 1: Freddie Mack. What are different roles accounting, finance, and sometimes

1095
00:57:32,280 --> 00:57:35,520
Speaker 1: they hang out with economists UH and work UH. When

1096
00:57:35,520 --> 00:57:37,600
Speaker 1: I talk to those folks and folks that are interested

1097
00:57:37,600 --> 00:57:40,360
Speaker 1: in going forward in the career. From my perspective, one

1098
00:57:40,440 --> 00:57:43,080
Speaker 1: of the best skills to have and to be able

1099
00:57:43,120 --> 00:57:46,160
Speaker 1: to sort of leverage is sort of quantitative sort of programming,

1100
00:57:46,560 --> 00:57:50,320
Speaker 1: statistical analysis, UH, and sort of that sort of area.

1101
00:57:50,400 --> 00:57:52,560
Speaker 1: So anything you can do to pick up some programming,

1102
00:57:52,600 --> 00:57:55,000
Speaker 1: I think is incredibly important in particularly if you want

1103
00:57:55,040 --> 00:57:58,360
Speaker 1: to go in an analysis role. UH. On understanding statistics

1104
00:57:58,360 --> 00:58:00,320
Speaker 1: if you're thinking about going into an economic makes more

1105
00:58:00,320 --> 00:58:04,680
Speaker 1: applied role. More you know, applied statistic econometrics is hugely important.

1106
00:58:04,720 --> 00:58:08,440
Speaker 1: That that is probably good advice for any field, regardless

1107
00:58:08,480 --> 00:58:11,200
Speaker 1: of whether or not it's it's finance related. A little

1108
00:58:11,200 --> 00:58:13,600
Speaker 1: bit of programming, a little bit of statistical analysis goes

1109
00:58:13,640 --> 00:58:16,520
Speaker 1: a long way. And our final question, what is it

1110
00:58:16,560 --> 00:58:21,440
Speaker 1: that you know about the world of mortgages and securitization

1111
00:58:21,680 --> 00:58:24,960
Speaker 1: and real estate today that you wish you knew fifteen

1112
00:58:25,040 --> 00:58:29,200
Speaker 1: years ago when you were really just getting started. I

1113
00:58:29,240 --> 00:58:31,960
Speaker 1: think it's an enormously complex field, and I think the

1114
00:58:32,040 --> 00:58:36,400
Speaker 1: ability to distill complex things, not make them extra complicated,

1115
00:58:36,400 --> 00:58:39,520
Speaker 1: but actually make them simpler is enormously important. And so

1116
00:58:39,560 --> 00:58:41,520
Speaker 1: when it started out, I was really you know, focused

1117
00:58:41,520 --> 00:58:44,120
Speaker 1: on the complexity because that's from an academic background where

1118
00:58:44,120 --> 00:58:46,200
Speaker 1: you go. But really people don't have time for that,

1119
00:58:46,320 --> 00:58:48,080
Speaker 1: you know, in the industry. They want to have answers.

1120
00:58:48,080 --> 00:58:50,160
Speaker 1: They got a lot of pressures. And so finding out

1121
00:58:50,280 --> 00:58:54,000
Speaker 1: you know, really having that uh empathy, sort of avoiding

1122
00:58:54,000 --> 00:58:56,080
Speaker 1: the cursive knowledge as you speak, but to try to

1123
00:58:56,120 --> 00:58:59,160
Speaker 1: really get to the heart of the problem quickly, uh,

1124
00:58:59,200 --> 00:59:02,200
Speaker 1: and the amount importance of that, like number one, almost

1125
00:59:02,280 --> 00:59:04,680
Speaker 1: number one, And when you're approaching a problem or you're

1126
00:59:04,680 --> 00:59:06,840
Speaker 1: gonna meet with someone is trying to really get to

1127
00:59:06,840 --> 00:59:09,400
Speaker 1: the point and really focus on the answer and deliver

1128
00:59:09,520 --> 00:59:11,920
Speaker 1: on that, and to have some sense of what they

1129
00:59:11,960 --> 00:59:14,320
Speaker 1: know and what you know and they don't know, uh,

1130
00:59:14,360 --> 00:59:16,560
Speaker 1: to sort of align that, to have a real appreciation

1131
00:59:16,600 --> 00:59:18,680
Speaker 1: for that and how that can take. You know, if

1132
00:59:18,680 --> 00:59:20,919
Speaker 1: you have an okay answer, but you combine it with great,

1133
00:59:21,040 --> 00:59:24,640
Speaker 1: you know, clearer communication is sometimes a lot better, often

1134
00:59:24,640 --> 00:59:26,800
Speaker 1: a lot better than having a fantastic answer than nobody

1135
00:59:26,840 --> 00:59:32,680
Speaker 1: can understand. Right. Um, never let the good the perfect

1136
00:59:32,680 --> 00:59:34,840
Speaker 1: be the enemy of the goods, so to speak. Quite

1137
00:59:34,920 --> 00:59:38,360
Speaker 1: quite interesting stuff we have been speaking with Lynn Kiefer.

1138
00:59:38,800 --> 00:59:42,480
Speaker 1: He is the deputy chief Economist at Freddie Mac. If

1139
00:59:42,520 --> 00:59:44,920
Speaker 1: you enjoy this conversation, we'll be sure to look up

1140
00:59:44,920 --> 00:59:47,760
Speaker 1: an intro Down an Inch on Apple iTunes, where you

1141
00:59:47,800 --> 00:59:50,600
Speaker 1: can find any of the other two hundred and twenty

1142
00:59:50,720 --> 00:59:55,040
Speaker 1: plus such conversations we have had over the previous four

1143
00:59:55,040 --> 01:00:00,600
Speaker 1: plus years. We love your comments, feedback, end suggestions. Write

1144
01:00:00,640 --> 01:00:04,520
Speaker 1: to us at M I B Podcast at Bloomberg dot net.

1145
01:00:05,160 --> 01:00:07,280
Speaker 1: I would be remiss if I did not thank the

1146
01:00:07,320 --> 01:00:11,720
Speaker 1: team that helps put together this podcast each week. Attika

1147
01:00:11,800 --> 01:00:16,720
Speaker 1: val Brun is our project manager, Medina Parwana is my producer.

1148
01:00:16,800 --> 01:00:20,080
Speaker 1: Taylor Riggs is our booker. Michael Batnick is our head

1149
01:00:20,080 --> 01:00:24,440
Speaker 1: of research. I'm Barry Retolts. You've been listening to Masters

1150
01:00:24,440 --> 01:00:26,440
Speaker 1: in Business on Bloomberg Radio.