On Monday, I argued investment incentive policy is best understood within a political framework that takes seriously the electoral incentives state and local officials face. Looking through the New York Time's interactive database of investment incentives, it is striking how widely states vary in the amount of incentives offered. What explains this variation? One possible explanation is individual agency. Perhaps Texas has a very large incentive program because of the political influence of G. Brint Ryan; this is the implicit argument forwarded in the New York Times Investigative Series on Investment Incentives. Comparative political economists would point to institutional variation; differences in governance structures and how susceptible local governments are to corruption may explain the extent to which states pursue incentive programs.* Partisanship might matter too, although it is difficult to make the case that voters see incentives as clearly benefiting benefit at the expense of workers. Indeed, as I mentioned on Monday, experimental evidence suggests voters see incentives through the prism of job creation. This makes a partisan-based mechanism less plausible.
While people and institutions may help explain a portion of variation in incentive programs, I’d argue structural conditions are most important. (This probably won’t surprise readers of the blog – contributors here tend toward thinking about the world in such terms.) As I mentioned in Monday’s post, states and localities are working to attract jobs in a context of open capital markets. Consequentially, absent transaction costs, capital is mobile while labor is relatively fixed and this makes capital strong. Capital gets locational incentives because its exit option is credible. Labor, however, is captive so governments can tax it more. The problem with this view (besides the fact that suggesting governments face little pressure to reduce taxes on middle-class workers will get you laughed – and voted - out of Washington these days) is that the global economy, while open, is not frictionless. Transaction costs, or in network terms, negative externalities are important.
There is a large literature in economics on agglomeration effects – basically the idea that centers of economic activity form due to positive externalities generated by the success of a few enterprises.** In the 1950s, Detroit was perhaps the best example of one of these centers. Successful, large manufacturing enterprises require deep supply chains, preferably located with geographic convenience to reduce transportation costs and to decrease production times. Competitors often locate nearby to be better able to recruit management, design, and other knowledge workers. In network terms, when a fit enterprise center emerges, preferential attachment reinforces that center.
Today, thriving centers of economic activity in the US include New York City, the Silicon Valley, and perhaps even NC’s own Research Triangle Park. It is then not surprising that, according to the New York Times report, California is reducing its incentive program, which is already comparatively small at $112 per capita. New York and North Carolina have relatively low per capita incentive programs, $210 and $69 respectively. Compare that to the three largest incentive programs on a per capita basis – Alaska at $991, West Virginia at $845, and Texas at $759. Economic geography matters. The states with the largest incentive programs are those that either never generated large centers of economic activity, or whose centers have become obsolete as our economy has shifted from manufacturing to services.
Economic centers form due to a confluence of factors, some of which governments have control over and some that they don’t. Investments in education and infrastructure can provide a skilled workforce and inexpensive access to energy, telecommunication, water, and transportation networks. And, it is true that offering locational incentives may reduce governments’ ability to invest things that will actual increase their locality’s fitness. But, this ignores the fact that incentive programs are fundamentally designed undermine powerful network effects that concentrate economic activity. That is why they are so inefficient; because they are swimming against the current. Fitness is not the whole story – preferential attachment entrenches economic centers. So, incentives ultimately are big risks – if you are lucky, you may attract enough high-quality enterprises that you can build a thriving center. But, network dynamics are working against you.
* Nate Jensen pointed me to this particular NBER working paper , which finds evidence that corruption increases incentive programs.**See here (firewalled) for a review.