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In part 4, I noted that nearly all of the increase in real estate value relative to incomes has been due to regressive price and rent increases. Short-term cyclical fluctuations can raise or lower home prices across a market. Where the average price of homes has risen persistently because of supply obstructions, prices and rents rise proportionately more in poorer neighborhoods than in richer neighborhoods.
In Figure 14, the yellow line is the estimate of aggregate real estate value/income, and it tracks closely to the real Case-Shiller index. The darker line is the estimate of aggregate real estate value/income if all home prices had appreciated at the same rate as homes in the richest 10% of neighborhoods. We would still be moving cyclically around a flat mean of about 3x like the Case-Shiller index implies we had been doing for a century before. Case-Shiller is above 5x now, and that is almost entirely due to regressively rising rents.
Here, I will make 3 points that derive from this observation.
1. Regressive Costs Lead to Income-Correlated Migration
Housing poor cities look like income-rich cities, but much of that is a byproduct of poor families leaving. It’s failure masquerading as success.
Several of the metropolitan areas with the highest upward filtering rates now regularly lose population. According to the BEA, the Los Angeles metropolitan area has averaged about 0.7 percent population loss annually since 2017. It seems unlikely that the geographical capacity of Los Angeles is declining by about 0.7 percent annually. But, in any case, the point remains: Los Angeles housing valuations are related to the acquiescence to higher costs of the families who have chosen those costs over displacement in a city with shrinking capacity. The high cost of housing in Los Angeles is a signal of a novel form of poverty. It is the cost accepted by the remainers who have chosen not to be one of the millions of former residents who moved away. Average local incomes have risen, in large part, because poor families have moved away. In the amply housed 20th century that was reasonably described by spatial equilibrium and aspirational migration decisions, average local incomes rose because of families moving in.
In this way, supply constraints can raise local average incomes even where agglomeration economies and productivity are average or worse. We cannot assume that higher incomes are entirely the result of urban productivity, especially when the cities with expensive homes and high average incomes are now routinely shrinking, and their compositions are being changed as much by the characteristics of the families that are leaving as by those that arrive.
When upward filtering spread to other regions after 2008, it coincided with lower population growth, less housing construction, lower rates of migration into growing cities, and higher rates of outmigration from expensive cities. Both cross-sectionally and over long periods of time, high rents are correlated with lower housing production.
Obviously, some expensive cities are particularly high performing locations for some industries. Don’t take this as a denial of all urban productivity and locational demand. The point here is that under current housing conditions, rising incomes are not necessarily good evidence of rising productivity. With low enough construction, a city can become expensive and can even create inflated local income growth even if productivity-driven sources of income growth are below average.
2. Aggregate Data and Value-Weighted Averages Understate Rising Costs for the Average Family
An extreme example can help to illustrate this. Imagine a family with $1 million income and a family with $40,000 income, and both live in homes worth three times their incomes. The value-weighted average price-to-income is 3 times ($3,120,000/$1,040,000). If the home of the poor family doubles in value, then the aggregate value-weighted average price-to-income rises to 3.1 times ($3,240,000/$1,040,000). If the home of the rich family doubles in value, then the aggregate value-weighted price-to-income is 5.9 times ($6,120,000/$1,040,000). In both cases, one of the two families experiences a doubling in price-to-income, but that doubling only significantly affects the aggregate number when it happens to the rich family.
In the above example, averaging the price-to-income ratio of each family statistically conveys the average experience of the two families. In both cases, the average price-to-income rises from 3 to 4.5 times [(3+6)/2]. The value-weighted measure expresses information about the total marketplace. The equal-weighted measure expresses information about the experience of the average household.
Since rising housing costs and real estate valuations have been negatively correlated with incomes, the data have this bias. Figure 15 in the paper compares the equal-weighted change in home price/income ratios (the change experienced by the average family) to the value-weighted change (the change reported in aggregate measures).
Of course, the difference between these measures is greatest in the markets where homes are filtering up the most. Families in the average ZIP code of cities with more upward filtering rates live in a home that was worth about 4 years’ of income in 1999 and is now worth nearly 7 years’ income.
3. The Trend in Rents Is Also Regressive
Price trends include some cyclical noise. They also reflect changes in lending markets. After 2008, regulatory limits on mortgage access have reduced prices in poorer neighborhoods where families have a harder time getting approved for mortgages. So, regressive price appreciation also understates the regressive nature of housing shortages. Although, as I mentioned in Part 2, inflationary rents are associated with higher price/rent ratios, so in that way, price appreciation overstates the effect of housing shortages on the housing costs of renters.
Zillow maintains rent estimates from 2015 to today. Using those estimates at the ZIP code level and IRS average adjusted gross income estimates at the ZIP code level, I estimated the relative effect of rent inflation on real incomes. I estimated the change in incomes from 2015 to 2022 adjusted for inflation that includes rent and compared that to income growth after rental expenses, adjusted for inflation that doesn’t include rent.
National estimates of income growth don’t account for such local differences in rent inflation. From 2015 to 2022, the effect of regressive rent inflation on real income growth lowered the lowest income quintile by 15% while it had little effect on income growth in the highest quintile.
This is, in part, because rent is a larger portion of poor family’s incomes, and the BLS has done some work at estimating the effect of that issue. The added issue that my paper highlights is that the actual change in rents in poor neighborhoods has been systematically higher than in rich neighborhoods, even where those neighborhoods are just a few miles apart within a given city. Current public inflation measures are simply not built to handle this historically peculiar issue.
This must be one of the most important current factors driving public sentiment about economic growth and equity. In fact, new research is increasingly finding that a lack of adequate urban housing is a primary motivator for many of the recent challenges in the American economy. Economists Rebecca Diamond and Enrico Moretti find:
“(F)or college graduates, there is no relationship between consumption and local prices, suggesting that college graduates living in cities with high costs of living—including the most expensive coastal cities—enjoy a standard of living on average similar to college graduates with the same observable characteristics living in cities with low cost of living—including the least expensive Rust Belt cities. By contrast, we find a significant negative relationship between consumption and local prices for high school graduates and high school drop-outs, indicating that expensive cities offer lower standard of living than more affordable cities.”
The Diamond and Moretti findings concur: High real estate values reflect relative poverty. And, at this point in American trends, on net, that is all they reflect. High housing costs have been claiming all the urban productivity benefits of high-skill workers and more than all the urban productivity benefits of low-skill workers. The lower real living standards that Diamond and Moretti found are only the costs of the families that remain in the underhoused cities. The costs imposed on the millions of displaced and homeless families are more difficult to measure.