A few weeks ago, I had a good time taking apart anti-anti-sprawl critic Wendell Cox's self-referential analysis supposedly showing that highly regulated metropolises have higher housing costs because they are highly regulated. ("Wendell Cox's Voodoo Economics.") In sum, Cox concluded that because any variation in housing cost must be due to regulation, all variation in housing cost must therefore be due to regulation.
One thing Cox didn't consider was the possibility that higher housing prices might have something to do with higher incomes. It stands to reason that metros with higher incomes might have higher housing prices. As the average homebuyer knows, the question of how big a mortgage you can carry – and therefore how much you can pay for a house – is directly connected to how much money you make.
So it was a little surprising to see Cox's New Geography piece the other day, which analyzed income trends in 28 large metros from 2000 and 2009. The changes in income were all over the place and Cox seemed a bit baffled by the whole thing (why would incomes in Atlanta and San Jose go down so much, while they went up so much in Baltimore and Pittsburgh?). One thing that struck me is that most of the metros Cox looked at in his income analysis were also metros he looked at in his housing price analysis. Since Cox didn't bother to draw the connection, I decided to do it myself.
In his housing analysis (which was based on 2010 data), Cox picked 11 metros – six of which he characterized as having strict land use regulations and five of which he characterized as having looser land-use regulations. He concluded that the strictly regulated metros had much higher home prices than they "should," while in the other metros the home prices were just about right. (His definition of "should" meant calculating construction cost for the average home in each metro area and then adding 25% to cover what he believes the cost of land and regulation "should" be.)
In his income analysis of 28 metros, Cox used five of his "highly regulated" metros – Washington-Baltimore (which were combined in the housing price analysis but separate in the income analysis), San Diego, Seattle, Portland, and Minneapolis-St. Paul. He also used three of his loosely regulated metros – Houston, Dallas-Fort Worth, and Atlanta. He used 2009 data for income, which lines up pretty well with 2010 data for home prices.
So, I thought it would be interesting to compare the difference in income in Cox's metros to the difference in home prices. I used his three loosely regulated metros. On the highly regulated metros, I wanted a comparable number, so I threw out San Diego (which even Cox's fans admit is a weird outlier) as well as Minneapolis-St. Paul, which I personally think isn't very highly regulated and is much smaller than the three loosely regulated metros. I left in Baltimore and Washington (which I counted twice in the housing to make up for the fact that the income numbers were separate) as well as Seattle (a pretty good comparable in size to the three loosely regulated metros) and Portland (because, while it's small, it's everybody's favorite example of regulation). Admittedly, I wound up with one big metro in the Mid-Atlantic and two in the Northwest. But the other three are all in Texas and Georgia, so it seemed fair.
In a nutshell, here's what I found:
In 2010, the average home price in the four highly regulated metros was 38.9% higher than the average home price in the three loosely regulated metros.
But – and here's the interesting thing – the median income in the highly regulated metros was 20.6% higher than the median income in the three loosely regulated metros.
Cox's "growth management" metros have higher home prices. But they also have higher incomes. You can't draw a causal connection from my back-of-the-envelope analysis, but you could certainly hypothesize that about half of the additional home price (20% out of the 40%) is due to higher incomes. This would mean that somewhere between 0% and 20% would be due to stiffer regulation. There may be other factors, such as overall availability of land supply because of topography and public land ownership (a particular issue in Seattle).
I can't say for sure, but this smells right to me. Some years ago when Rolf Pendall and I reviewed the literature on urban growth boundaries, we came to the conclusion that – to vastly oversimplify – the evidence showed that UGBs increase home price somewhere between a little and a lot. So I'll stipulate right now: Stiff regulation adds somewhere between 0% and 20% to the price of a house.
Remember, this is all based on Cox's own data and analysis – from two different pieces of research that he never put together.
The other funny thing about his metro income analysis is that he does truly seem baffled by the fact that metros with stagnant populations (like Pittsburgh) are seeing their median incomes go up, while metros with growing populations (like Atlanta) are seeing their median incomes go down. He wants to use this data to also refute the smart growth crowd – his basic argument being that this data proves prosperity doesn't like in a big, populous central city and that regional prosperous may depend on decentralization and sprawl in the suburbs, where the population is still increasing in some of these metros.
But that's old-fashioned thinking – the kind that equates prosperity with population. As Pittsburgh and Baltimore and Cox's own St. Louis have proven, you can increase incomes and wealth without increasing population – because the measure of prosperity in America today is not the number of people but the skill and creativity they bring to creating wealth. The "growth without growth" phenomenon is very real, as I noted in a recent Planetizen column excerpted from my book Romancing The Smokestack – and it reveals that the old pro/anti sprawl debate is virtually irrelevant when we talk about economic well-being.