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The Price of Housing in the United States, 1890-2006

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How do newly constructed housing price indices for 1890-2006 reveal trends in U.S. housing markets and explain uneven price growth over time?

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This video presents an overview of a study on housing prices and rental trends in the United States, highlighting a gap in existing literature regarding systematic data collection. The authors identified that previous research relied on limited data sources and methodologies, often leading to unreliable outcomes.

The study utilizes a new dataset derived from newspaper listings covering 30 mid-sized and large U.S. cities from 1890 to 2006. This video dataset aims to provide annual, city-level data that reflects contemporary market conditions, allowing for a more accurate analysis of long-term trends in housing prices and rents. The authors incorporated data from the Bureau of Labor Statistics and the U.S. Census, but addressed their limitations, such as infrequent surveys and geographic restrictions.

Key findings indicate that real rents have increased by about 20% over the century, challenging previous interpretations that suggested a decline. The study also reveals increased inflation in housing prices dating back to the late 1960s, earlier than previously documented. These findings have implications for the Consumer Price Index (CPI) as housing constitutes a significant portion of consumer budgets.

The authors discuss the broader economic significance of housing prices on living standards and wealth accumulation, noting substantial variations across different regions and cities. They suggest that housing investments, while generally more stable, yield lower returns than stocks.

The study was supported by the National Science Foundation and included collaborations with several researchers, allowing a large-scale data collection effort. The data is made freely available for future research, encouraging further exploration on housing cycles and affordability.

Lastly, the authors advocate for policymakers to consider the long-term trends in housing prices when crafting policies to address housing supply and affordability issues, stressing the importance of this data in understanding economic conditions affecting consumers.

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We wrote this study because we identified a,

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a gap in the literature.

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So, there are existing studies of house prices

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and rental prices over the long run in the United States.

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Um, but they, you know, people had,

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researchers had done their best.

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They had cobbled together various different sources,

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whatever was available at the time,

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using the best methodologies available at the time.

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Um, but we identified that, there's, other sources

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that could be used and that would allow us

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to have a more systematic data collection

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and would allow for a larger sample size

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that we could be more confident with the results

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and with the long run trends that we would, draw out

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of those data sets.

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We, particularly noticed this for rental prices.

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So since 1914, the Bureau of Labor Statistics has,

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done surveys, conducted surveys, where they,

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asked people about the rents

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that they pay on the units that they're in.

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Uh, but they do this for a limited range of cities,

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which has increased over time,

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but makes things difficult to compare across a very long,

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over a century time period.

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There were also some, some issues in terms of tenants

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who moved or didn't respond

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to the survey in a particular year,

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which made the data less reliable.

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Um, we also, wanted to construct a series, both

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for sales prices

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and rental prices that was very relevant for market rates.

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So we wanted to sort of ask the question, if you wanted

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to move to the average US city, you know,

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could you afford to do

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so at these various different time periods?

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Maybe you're looking to move to opt opportunity

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to access high wage, higher wages and good jobs,

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and could you actually do that?

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Could you afford, to live in these various places?

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And some of these previous data sets were not quite

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capturing current market conditions.

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They might capture them with a lag,

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but they, they weren't capturing exactly what we wanted

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to capture with our methodology, the existing data sources.

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Um, on the, on the sales side,

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on the house price side mostly,

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most notably is the case Schiller Vice Index

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that people have used quite extensively,

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and which again, goes also back to 1890.

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Uh, it did a great job with the data

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that was available at the time in terms of, computing,

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house prices and coming up

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with a national index over time.

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Uh, but that's the one that we are trying to improve on,

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of having annual data at the city level.

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Uh, that goes back also to 1890.

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The other main source that has been used is the US Census,

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which began asking about house prices

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and house rents, back in 1930.

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Uh, but that's of course only every decade.

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So it has limitations in how we can use that dataset.

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Uh, if we want to know things at a higher frequency,

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we're, we're going to need, need to have a different

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Approach. And

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we don't have any city level, annual data set

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for sales prices until about 1975 in the us.

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And so that was sort of the key, difference

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between the previous literature

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and what we've tried to do with our current paper.

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On the rental side, as I said there, the Bureau

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of Labor Statistics has put together data since 1914,

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but with these limitations

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and limited to a smaller range of cities, we are able

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to do cover, 30 cities in, in our, in our study,

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which has improved upon data availability.

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Our main goal was to have annual data city level

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over this long 12 decade time period that was,

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systematically collected with a large sample size

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and where we used the same consistent methodology across

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that whole, whole 12 decades.

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The hip hop dataset is now housed at the Philadelphia

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Federal Reserve Bank.

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We're very happy to partner with them

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and make this data freely available.

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The, the indexes are available for, for anybody to use

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or to just view on their site,

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and they've made it look very nice, I have to say.

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Um, and, and it's now called the Historical Housing Project

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on that site, I should point out.

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Um, and so yes, working with my co-authors, Ronan Lyons,

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who's at Trinity College, Dublin, Allison Scherzer,

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who's now at the Phil Philadelphia Federal Reserve,

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and David Atos, who's,

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finishing his PhD at University of Pittsburgh.

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Uh, the four of us collaborated on this huge project,

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and we identified a new source of data that could help us

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do this big project of systematic data collection

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for house prices and rents,

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which was using new newspaper listings, which is

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what people would've used if they are thinking

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of buying a house or renting a property from 1890

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through 2006.

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Once we get into the two thousands, you know,

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the internet comes along and competes for newspapers.

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So we haven't, yet, added maybe some,

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some internet listings.

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We may do that in the future, the near future,

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and we will certainly update the dataset when we,

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when we add more data.

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Uh, and so we were able to look at newspaper listings

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for 30 sort of mid-size

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and large US cities, 1890 to 2006.

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Um, and this project wouldn't have been possible without the

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four of us collaborating

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to get a National Science Foundation grant, which allowed us

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to hire a sort of army of maybe about 50,

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research assistants who worked on various aspects

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of the data collection.

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And it also wouldn't have been possible, maybe, you know,

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20 years ago before newspapers had been, scanned in

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and available online on a wide scale.

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We encourage people in the future if they want to expand

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what we've done, you know, now that we have AI technology

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as well, allowing us to search through all

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of these various texts that are available online.

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Uh, you know, some people

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who have more computer skills will definitely be able to,

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to expand upon our initial approach.

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Um, and so what we did was we went through these newspapers.

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We looked for listings that told us what the price was

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or the rent told us

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what the basic location within the city was

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and the size of the unit.

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And it also, most advertisements also give you a bunch

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of amenities and characteristics that,

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to sell the, the property.

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And so we record all of that.

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We then, run an analysis that controls

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for these different characteristics, the location

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and size being the most important ones,

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and allows us just to strip out the sort of annual variation

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that gives us the trend in house prices.

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And, housing rents the trend that's not driven just

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by the fact that, you know, house size changes over time,

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certain neighborhoods are more popular,

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and have more amenities and so cost more.

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So we've kind of stripped out that, component

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to construct these trends across cities.

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And so, you know, folks could work

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with the city level trends over time,

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or they could, use our national level in indexes

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where we sort of aggregate these things up

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to the national level, using these cities.

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And because we have mid-size

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and large cities, you know, we're representing a,

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a large fraction of the US population with this data set.

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We do a lot in this project,

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and not least the data product that comes out of it,

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but also with our findings.

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Um, we were very happy to be able to, update,

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two stylized facts in the literature

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that people had already kind of questioned.

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Uh, and so one of those was that, we do find

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that there's a ramp up in housing, prices

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during the 1920s, the interwar period.

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So we see a 1920s boom that's discussed in the literature,

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and we also see a bust during the Great Depression when it,

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of course, we would expect to see one.

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And so the previous data sets that had been put together due

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to various data limitations had actually not, they had very

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flat series during that time period, which was surprising

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to, economic historians of, of that period.

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So we were happy that our series seems to match,

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some other smaller studies, some case studies

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and the historical narrative for that time period.

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Um, another fact that we were able to sort of update on was,

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thinking about real rans.

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So this is rents where we've adjusted

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for general price inflation.

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Um, in the existing, bureau of Labor Statistics data,

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it had looked like real rents were actually declining over

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the 20th century,

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which I think certainly anecdotally is not sort of what,

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what people imagine, although of, of course, we're very,

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you know, in this time period of high sales, prices

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and rents, it's, it's hard to look back very far and,

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and imagine that they were ever any different.

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Um, but what we find is actually that real rents

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to have increased about 20% over this long century

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period that we look at.

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We think that conforms more to, again, the other narratives

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that we have in the literature

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and what economists had had previously, believed.

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Um, and more generally, you know, again,

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people have a sense that hes,

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prices have risen quite a bit in the recent time periods.

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Um, and, we do actually find more inflation in the,

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price series compared to the previous literature.

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We find that sort of the ramp up in sales prices,

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didn't just start with the sort of late eighties, nineties.

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We're actually seeing that from the late 1960s onwards.

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Uh, and so that's an update to the literature

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where we're seeing this uptick already, a couple

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of decades earlier than previously thought.

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Um, and in terms of thinking about, you know,

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what are the implications of finding this,

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somewhat higher, price inflation in sales prices and,

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and rental prices, you know, we, these are things

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that factor into the CPI, right?

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So, of course, housing is a large portion

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of the average consumer's budget,

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and, we need good accurate measures of, of

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that housing, right?

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Uh, and so having a different measure of that price is going

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to make some difference in, in the CPI measure.

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So we actually take that seriously in the paper.

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We do that calculation where we, put in our,

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rental price, inflation, which we find

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to be 3.5% per year.

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The nominal, the index is increasing in nominal terms,

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the existing, component of the CPI,

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they take the BLS measure,

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which increases about 2.6% per year.

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And so this actually makes a difference if we

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recompute the CPI.

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So we have prices increasing by about 3.3% annually.

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Uh, the existing measure would be about 3.1%.

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And that's important

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because, you know, we're basing our, our measures of cost

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of living and also our ideas of

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how much living standards have increased over the 20th

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century on these, these price measures.

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And so, you know, it's,

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it's not maybe a dramatic change,

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but if we're thinking about a 0.2 difference per year,

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that is going to add up over a century.

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Uh, and so we would argue our, our measures of,

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of living standards today should be revised downwards

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somewhat due to this, this result.

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We look at the richness of our data across cities,

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and we actually think about how house prices have tra

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changed, across cities over time,

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or within each city over time.

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Uh, and we've actually computed measures of our,

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total return to housing.

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And so this has two components.

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It has the capital gain component component,

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which is really about price appreciation, has,

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has your house appreciated in value over time, which

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of course, these days, everyone feels like they're an

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investor in their house, not just a consumer.

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And so we all want to achieve capital gains for our house.

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Um, and we also look at the rental yield.

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So how have rental prices changed relative to,

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house prices?

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So thinking about it as again, like if you're the landlord,

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you want some return each year in terms

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of your rental yield for your property.

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And so over this long time period, we find that,

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rental yields were very important in the early period,

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in terms of making up the total,

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the total return on housing.

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And then over time, it's really shifted toward the capital

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gain component being really important.

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Um, and again, that's not super surprising

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because house prices have appreciated so much over, over

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that time period, especially since World War ii.

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Uh, so that's probably what we would expect.

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We do find that, you know,

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across cities there's huge variation.

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And so in the paper, one nice thing we do is

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to split it up into regions

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because, you know,

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it does look like the east coast, the west coast.

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Those housing markets tend to, on average, do fairly well

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and have had quite a lot of, appreciation.

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Uh, places like Detroit have, you know, sort

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of not been a good investment from quite

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early in our time period.

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So even from sort of the late twenties, early thirties,

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when Detroit still seemed to be doing okay, you know,

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apart from the Great Depression,

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which was affecting everyone, we do see that,

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the total return there is is not very strong

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and negative in some, in some time periods.

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We think this is kind of interesting to show

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the variation in housing as an investment

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across these different cities that it is quite different.

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Um, and, housing in terms, if we compare it

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to the return to stocks, investing in stocks,

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usually stocks looks like a better investment.

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That's actually an area where we agree

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with the previous literature.

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Uh, we, we would be in broad agreement with that.

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Even, showing

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that we have more has price inflation in our data.

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Uh, the housing return tends

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to be more stable low compared to stocks.

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So that of course may be a reason why people,

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definitely like to invest in, in the housing market.

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We're very excited to put this data set out there

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to have it freely available for other researchers to use it,

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in the paper there's even some other areas of,

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00:14:23.585 --> 00:14:26.065
that we indicate people might work in.

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Uh, in particular, we think macro economists might be very

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interested in this data set

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and in thinking about how, the housing cycle is related

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to business cycle more generally.

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Um, that's also an area where,

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usually macro economists like high frequency data,

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and so they may be among the people who would like to go in

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and follow our methodology

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00:14:48.205 --> 00:14:49.985
and do, you know, maybe quarterly data

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instead of annual data.

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Uh, and we encourage them to do, to do that

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and to, to use that for their very testing, their,

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00:14:56.295 --> 00:14:59.125
their macro and housing finance models.

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Um, for our group, Ronan and Allison

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and I will be continuing to work in this area,

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00:15:05.785 --> 00:15:09.445
and a, a follow up paper that we're very excited about is

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to think about new measures of housing affordability.

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Not just the prices and the rents,

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but thinking about affordability as well.

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And, measures of affordability are usually very simple.

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00:15:21.265 --> 00:15:23.005
It, you know, we already have the price side

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and the rent side, and now we would be computing the wage

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00:15:26.275 --> 00:15:28.845
side and thinking about people's incomes.

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What do households look like?

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00:15:30.585 --> 00:15:32.205
How much could the typical household

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00:15:32.545 --> 00:15:34.445
or the typical wage earner afford

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00:15:34.985 --> 00:15:38.125
in these different time periods and across, across cities.

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00:15:38.305 --> 00:15:41.485
So we have some more data work to do to compute those,

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00:15:41.485 --> 00:15:43.325
measures over this long time period.

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00:15:44.065 --> 00:15:46.445
Um, and, but we're excited to do that.

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00:15:46.445 --> 00:15:48.365
We think that will be an important follow up

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to understanding housing markets more deeply

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and how it really affected the average person

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over this long, time period.

340
00:15:57.165 --> 00:16:00.225
Um, but yeah, there is also scope for, you know,

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00:16:00.595 --> 00:16:03.865
other academics, policy makers as well

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00:16:03.925 --> 00:16:07.505
to be looking at these data to get more context,

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00:16:07.775 --> 00:16:09.345
more long run understanding

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of what's been happening in housing markets.

345
00:16:12.565 --> 00:16:15.185
And, you know, as an economist, of course,

346
00:16:15.365 --> 00:16:17.585
who who's think started thinking about housing in recent

347
00:16:17.635 --> 00:16:19.785
years, we are always wanting

348
00:16:19.785 --> 00:16:22.225
to see policymakers coming up with new measures

349
00:16:22.225 --> 00:16:23.705
to increase housing supply.

350
00:16:24.285 --> 00:16:25.305
And so, you know,

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00:16:25.765 --> 00:16:27.785
it doesn't matter whether you live in Sacramento

352
00:16:27.785 --> 00:16:30.025
where I live, which actually has been at the forefront

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00:16:30.025 --> 00:16:31.705
of trying to increase housing supply

354
00:16:31.725 --> 00:16:33.305
and has actually seen some results

355
00:16:33.305 --> 00:16:36.025
with rents falling over the last year or two.

356
00:16:36.165 --> 00:16:37.585
I'm sure London has a big housing

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shortage and a big housing crunch.

358
00:16:39.645 --> 00:16:42.465
Uh, you know, I'm from Dublin Ronan as well,

359
00:16:42.815 --> 00:16:45.945
looking at these housing markets,

360
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we also have our own shortage over there as well.

361
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So we really hope that policymakers will pay attention

362
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to seeing this long run,

363
00:16:54.385 --> 00:16:56.505
inflation in house prices in particular.

364
00:16:57.005 --> 00:16:59.105
And, think about, okay,

365
00:16:59.535 --> 00:17:01.625
this is a really important issue in people's lives.

366
00:17:01.805 --> 00:17:04.385
It makes up a large portion of Peoples's budget.

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00:17:04.775 --> 00:17:07.145
It's also a large fraction of household wealth is

368
00:17:07.985 --> 00:17:09.225
captured in their, in their housing.

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And so it's a really important area

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where we need policymakers to be paying attention,

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to the latest information.

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