Readers of this blog will not be surprised at the idea that zoning and other restrictions drive up the cost of housing, and that this has many bad consequences on economic growth and inequality. The papers are especially noteworthy for much deeper implications.
Hsieh and Moretti:
...high productivity cities like New York and the San Francisco Bay Area have adopted stringent re- strictions to new housing supply, effectively limiting the number of workers who have access to such high productivity. Using a spatial equilibrium model and data from 220 metropolitan areas we find that these constraints lowered aggregate US growth by more than 50% from 1964 to 2009.1) The costs of regulation. The biggest problem in economics right now (yes, I mean that) is, How do we measure the growth consequences of regulation? Looking at the Western world's sclerotically slow growth rate, and listening to many anecdotes, it seems at least plausible that productive innovation is being strangled by byzantine bureacracy, captured by rent-seeking and anti-competitive forces. (Your other choices are, we just ran out of ideas, or some sort of endless "lack of demand.")
But how do we move past anecdote? How to we come up with "regulation is costing the economy x percentage points of growth?" Our statistical measurement system, GDP, unemployment, inflation, and so on, was beautifully designed in the 1940s to measure very Keynesian demand concepts. It isn't designed to answer the question of our time, how much growth is regulation costing us? We are flying in the dark. And Europe, perpetually in an Augustinian moment -- Lord, grant me structural reform, just not yet--is also.
Well, Hsieh and Moretti are doing it, and by doing so showing one path to answering the larger question.
Half of all US growth for a half century is an astounding amount. 1964: $3,734 trillion; 2009: $14,419 Trillion. Growth = 3.05% per year. At 6.1% per year, $3734 x (1.061)^(2009-1964)=$53.6 trillion dollars!
OK, maybe that's too huge. Well, read the paper and see how they came up with the number. If you don't like their assumptions make different ones. More important than this number is how they are coming up with answers to this, the most important question of economics.
2) Models and micro vs. macro
So how do they make the calculation? Roughly, they measure productivity in cities. They assume that people get higher wages in San Francisco because there are some very high productivity activities that have to be done here. They assume that business could expand and form here, and workers could move here and join in those high productivity activities, both earning higher wages and making more and better stuff for the rest of us. But those workers can't move, and businesses can't expand and form, because housing supply is restricted.
You can see grounds for objection.