Tuesday, May 20, 2014

The catch 22 of revitalizing a struggling city

In Enrico Moretti's book, The New Geography of Jobs, he discusses two methods of encouraging job and population growth in a city; attract employers and skilled workers will follow or attract skilled workers and employers will follow. He talks about this being a catch 22 in the sense that employers are reluctant to locate in a struggling, low cost area for fear that workers won't show up and workers are similarly reluctant to locate in the same area for fear that jobs won't show up. Neither wants to be the first mover.

This situation can be modeled in a normal form game where the strategies are to locate in a struggling city or not.


In the game above there are two players, firms and labor. Labor is the column player and Firms are the row player. If both workers and firms decide to locate in the same area they each get a positive payoff of 2 (2 has no quantitative significance. It can be any positive number to signify that they both gain if they both locate in the same area.). This is because the struggling area has lower property costs. If you are a firm and you sell a tradeable good i.e. a product that is bought both inside and outside of your area (think cars, computers, consulting services etc.) then the lower property costs mean more profit since you sell your product at a nationally (or even internationally) set price. If you are a worker and you earn a wage based on the national/international price of the good/service your company sells then the lower housing prices mean you have more money to spend on other goods and services or even a larger house.

If only one of the players chooses to locate in an area they get a payoff of -2 while the other gets a payoff of 0. This is because there are costs to choosing a struggling area without the other player being present. Not only are you located in a city that is down e.g. Detroit when you could have located in an area that is doing better e.g. Columbus, OH, Atlanta, GA or even the suburbs of Detroit but there are additional costs as well. For the firm, these include training workers, higher search costs for workers, relocation packages for attracting workers, or potentially relocation costs for the firm if they decide to relocate to an area with better workers. For workers these include taking a job that doesn't match your skill set, longer search costs for a job, being more susceptible to labor shocks and, like firms, potential relocation costs to an area with more employers. The other player, the one who does not locate, gets a payoff of 0 because they presumably remain where they are and thus are no better or worse off than before.

The two equilibria in this game are {locate; locate} or {don't locate; don't locate}. So like Dr. Moretti says, it is possible that struggling cities will stay struggling even though both workers and firms could be better off if they both decided to locate in one. How can struggling cities make it more likely that firms and labor will decide to choose {locate; locate} over {don't locate; don't locate}?

On the one hand, city leaders can try to signal to workers that they are going to attract employers. They do this by giving tax breaks and other perks to firms if they locate in their area. On the other hand, city leaders can try to signal to firms that they are going to attract employees. They do this by redeveloping downtown and adding high price amenities that skilled workers are attracted to.

Both of these have costs in actual dollars and opportunity costs. If firms/labor are not convinced that labor/firms will locate there based on the incentives the city decides to provide then the city ends up at the {don't locate; don't locate} equilibrium and has spent a bunch of money for little or no benefit. Dr. Moretti mentions Cleveland, Santa Fe, and New Orleans as U.S. cities that have failed using the attract workers approach. He mentions St. Louis and Fremont, CA as cities that have failed using the attract employers approach.

There is likely no fail-proof, one size fits all solution for revitalizing struggling cities. I will have some more thoughts on this in later posts.

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