First, let’s take a look at income growth. The correlation between income growth and house price growth is large (0.66) and statistically significant. As the chart shows, three of the four metros with most income growth (San Francisco, San Jose, and Seattle) are also among those that have experienced the highest growth in house prices, while many metros with low income growth have seen the smallest gain in house prices (Fresno, Calif., Memphis, Tenn., and Rochester). Yet there are many exceptions to this pattern: Sarasota, Fla., Oklahoma City, and Austin, Texas, have also had high income growth but have had lower price appreciation, while places like West Palm Beach, Ventura County, and Miami haven’t experienced much income growth but have seen strong price gains.

It’s not difficult to understand why such a tight correlation exists between income growth and price growth, but the relationship is likely more complex than you might think. As incomes rise, so do the mortgage amounts that homebuyers can get. Since homebuying is an auction-like process where the highest bidders win homes, income growth translates into higher home prices through increased consumption of housing. In turn, as home prices rise, employers need to increase their wages in order to retain employees. The kicker, though, is that growing incomes should only lead to increased home prices if supply is limited. When adequate supply is available, prices aren’t usually bid up because there are fewer buyers bidding against one another for any given home. This likely explains why income growth in the San Francisco Bay Area has been accompanied by strong home price growth, while income growth in Austin hasn’t.

Building on this (pun intended), we also find that metros with higher supply elasticity over the past 30 years have experienced less house appreciation, while metros with lower elasticity have experienced greater price appreciation. The correlation is also quite strong at -0.41 and statistically significant. As we discussed last month, elasticity is the measure of how much new housing is built relative to demand, and the strong negative correlation between supply elasticity and house price growth implies that much of the house price divergence we identified in the first section of the report can be explained by how much new housing was built in each of these markets over the past 30 years. We also tested for correlations with house price gains and 30-year population and employment growth. Both of these correlations were small and not statistically significant.