A Tale of Two Housing Markets

By Scott Lucas

In Indianapolis, $167,000 can buy you, outright, a four-bedroom, three-bathroom home with a basketball hoop out front and a lawn in the back. That same amount wouldn’t even cover the down payment on a four-bedroom, three-bath house in San Jose, California, where the median price of a home hovers above $1 million. The difference is staggering but not surprising. There really are two different housing markets in the United States: one that serves California and a smattering of other highly coveted cities, and one for the rest of the nation.

A new report by real estate analytics firm Zillow makes that fact painfully obvious, offering a snapshot of the most- and least-affordable home-buying markets in the 35 largest metropolitan regions in United States. (Because of the multiple definitions used in different sources, I’m using “city” and “metropolitan area” as synonyms, even though they aren’t the same.)

Here’s the full list for the 35 largest metropolitan regions in the country:

“In much of the country, housing and mortgage affordability looks quite good,” says Aaron Terrazas, a senior economist at Zillow who was involved in the research. Not so in the Golden State: Six of 10 least-affordable regions are in California. San Jose ranks as the least affordable, directly followed by San Francisco, Los Angeles, and San Diego. Seattle comes in at number five, followed by Sacramento at six and Riverside at seven. Of the 10 most-affordable major cities, all are located in the industrial Midwest, which have weaker employment markets, Terrazas explains.

But in the Golden State, “housing supply has not kept pace for much of the past decade,” Terrazas says. In part, that has to do with a housing market in which new construction cratered during the Great Recession and still lags behind its peaks in the mid-1980s and early 2000s. The pace of new supply has been too slow to catch up with the state’s booming tech-led economy. And a thicket of state and local policies restricting development, mandating surprisingly low densities in major cities like San Francisco and preventing sprawl into greenfields. Those decisions may be defensible — few want to see a Bay Area that stretches endlessly to Stockton — but they have pushed the cost of housing beyond the reach of middle-income households.

To create the rankings, economists at Zillow calculated the down payment needed by a median-income household in each metropolitan area to purchase a median house (thus keeping with the common rule of thumb that a household should spend no more than 30 percent of its monthly income on housing). Because saving for a down payment is the biggest hurdle to homeownership, keeping to that limit places homeownership out of the hands of many in the least-affordable cities. For example, to make a down payment on the median house in San Jose, a median-income household would have to make a 49 percent down payment, totaling $614,000 — a daunting amount to save.

What makes prices in California cities so high? It can’t just be the Pacific Ocean. It might have something to do with local politics — few places are filled with more Democrats than San Francisco and New York, a fact that conservatives in places like Texas trumpet alongside their lower costs of housing. On the other hand, Riverside is reliably conservative yet high on the list, whereas liberal Austin is sometimes called the “blueberry in the tomato soup of Texas,” yet that city is much more affordable than its ideological cousins in the blue states.

Pulling in other sources of data suggests the beginning of answer: It’s the land use regulations.

The University of Pennsylvania’s Wharton Residential Land Use Regulation Index shows which cities heavily regulate their use of land and which are more lax. Published in 2007, the index represents a quantitative measurement of land use regulations in U.S. cities. The more heavily regulated land use is in a metropolitan area, the higher the price of land. For example, density restrictions that make for fewer units on the same plot of land or mandatory studies about a building’s effects on wind and shadows lead to higher costs, which you’d expect to be passed on to consumers.

(Two quick technical notes: The index’s values run from 1.79 for the most regulated city to –0.80 for the least regulated. We’re omitting results for cases in which there’s no Wharton Index value.)

If we plot the Wharton Index against the affordability measure, here is the result:

From this, we can see that as land regulation increases, homes become less affordable. At a Wharton Index of 0.0, we expect a city’s middle-tier down percentage to be 5.4 percent. As the Wharton Index rises to 1.0 — the equivalent of moving from Chicago’s or Atlanta’s policies to San Francisco’s or Seattle’s — the middle-tier down becomes 17.2 percent. In other words, once a city reaches about 0.5 on the scale — San Diego’s rating — the costs of its regulations start to put middle-class affordability at serious risk of passing the recommended threshold that they should be spending on housing.

Of course, regulations raise prices by slowing the production of housing supply. If fewer units are built than otherwise would be, prices will be higher than they might be otherwise. To test for that, Zillow helped me pull the data on housing construction from the U.S. Census. We looked at the amount of housing built from 2008 to 2018 for each metropolitan region. Some built a lot: Houston built 487,933 new units of housing in that time period. And some built fewer: San Jose built 64,330 units. Because different cities have different population sizes, we divided the amount of housing by the population size in 2018 as estimated by the U.S. Census. For example, the construction industry in Houston produced 0.07 new units per person, while the construction industry in San Jose built 0.04.

If we plot the per capita construction against housing affordability, here’s what we see:

This suggests that the more housing a city is building, the more affordable it is — maybe. (Honestly, the observations look more like they’re distributed at random.)

What about another explanation? Progressives in cities like San Francisco and New York often call out the impact of the high-tech industry on housing prices: By bringing a batch of high-paying jobs to the region, tech distorts the housing market, making it harder for people not employed in the industry to bid against those who are. So we compared the GINI index, which measures income inequality to housing affordability.

Are cities that are more unequal worse off on housing affordability? Here’s the result:

As the GINI coefficient rises, housing becomes more affordable. That is to say, the more equal a region’s income, the easier it is to buy a house there. That’s also intuitive. Although, just like the previous chart, the data looks more random here than anything else. Too much noise, not enough signal.

What does all this mean for a place like San Jose? “These decisions come with costs,” Terrazas says. “Create rules around land use, and it pushes up costs. The reality is most of Ohio’s cities have not seen dramatic employment or population growth. When there is not that growth, they don’t have to make those tough decisions.”