The Competitiveness Index is a Grab Bag of Variables
Confusing Cause and Effect
The most serious problem with Beacon Hill Institute’s (BHI) indices is that they indiscriminately mix the measurement of variables that cause outcomes with the outcomes themselves. They claim that their index measures the “policies and conditions” in a state that make it more likely to compete successfully for economic growth, and their validity test is how well it predicts increases in per capita income. Yet a number of BHI’s variables are in fact not potential causes of economic growth, but instead the outcomes of growth or part of the very definition of growth, such as the share of adults in the labor force, budget surpluses, initial public offerings, exports, and new firms.
These measures don’t make sense. For example, economic growth creates more job opportunities, which draw people into the labor market; higher labor force participation rates are a result of, not a cause of, growth. Government budget surpluses are a result of robust income and revenue growth, not a cause (in fact, a budget surplus can be a drag on economic growth). The growth of new firms and the volume of exports are part of the very definition of economic growth (remember that consumption + private investment + government spending + net exports = Gross Domestic Product), not causes. In other words, it makes no sense to say that growth in exports cause growth in exports.
More Circular Thinking–Using Higher Income to Predict Higher Income
A number of the variables simply correlate with high income, rather than serving as causes of economic growth: the percent of households with cell phones or high-speed broadband, bank deposits per capita, and the prevalence of high-paid workers such as scientists, engineers, and high-tech workers. Not surprisingly, where people earn more money, they are more likely to have internet and cell phones and have more money in the bank. And of course states with lots of high wage workers have higher per capita income.
Other BHI variables measure the results of slow growth or low income, such as the percent of households that are uninsured and the infant mortality rate. Surely high infant mortality rates are a result of poverty, not a cause of poverty, and finding that states with high unemployment rates have lower average incomes proves nothing as losing your job is a sure-fire way to lower your income. And a high unemployment rate is usually the result of slow economic growth, or economic decline, not a cause of it.
As Richard Sims has pointed out, the inclusion of variables that measure outcomes rather than causes, “…is profoundly circular logic and is equivalent to saying ‘we measure things that indicate how well off you are, therefore if you increase these things you will be better off.’”1 The mishmash of causal and outcome variables used by BHI makes the index meaningless.
Variables with Ambiguous Import
Other variables in BHI’s index are more ambiguous, much like the question about the chicken or the egg and which came first. For example, high bond ratings are partly the result of economic prosperity, which brings with it a growing tax base, ample tax revenues and lower probabilities that governments will default on debt. At the same time, high bond ratings may be indicative of sound government budgeting practices. Either way, it may indicate stability of tax rates and spending, which may be appealing to businesses.
Another example of this is rent levels, which may be the result of past growth but may also affect economic growth. Low rents might be appealing to someone considering relocation, but they may also reflect a long-term sluggishness in the local economy. Rents, in fact, are sometimes used by economists to measure the overall attractiveness of a locality, since high rents are sustainable only where there is high demand for housing and enough good-paying jobs to support the payments. People want to live there, and can afford to. High rents may be the result of past growth, though they may also at some point become a constraint on future growth.
Other variables used in the BHI index are questionable as well.
For example, air travelers per capita is supposed to be a “sign of a developed infrastructure” but can easily be biased. Passengers per capita just doesn’t capture what is important to businesses, which is the frequency of non-stop flights to important destinations, status as an airline hub, and lots of competition producing low air fares. High tourist travel such as in Las Vegas or Orlando or an airport located in one state that serves a large multi-state metro area, such as the Cincinnati/Northern Kentucky Airport in the small town of Covington, Kentucky, produces a very high number of passengers per resident.
Then there is the indicator of percent of population that is foreign born, included on the grounds that “the more foreigners relative to the native-born population, the more motivated the workforce.” This is a dubious supposition; Beacon Hill provides no support for the contention.
1. Richard Sims, “A Grain of Salt: A Critical Review of the Beacon Hill Institute’s State Competitiveness Report.” Washington, D.C.: Institute on Taxation and Economic Policy, 2003.