In my previous post I discussed the very high median household income in Howard County in 2012, and noted that median household income is only part of the story: It shows how a “middle income” household is doing, but doesn’t say anything about how income is distributed among the various households. How do we measure the relative distribution of income across households, and what does this measure say about Howard County?

Let’s go back to the tables I included in my previous post, repeated here for convenience. First, here’s Howard County vs. nearby counties and other jurisdictions:

RankCountyMedian Household IncomeGini Coefficient
1Loudoun County VA$117,8760.3670
2Howard County MD$108,8440.3909
3Fairfax County VA$107,0960.4229
5Arlington County VA$100,4740.4294
11Montgomery County MD$94,9650.4504
12Prince William County VA$93,7440.3710
15Charles County MD$90,8800.3937
18Anne Arundel County MD$89,1790.4119
19Calvert County MD$87,4490.4090
21St Marys County MD$86,3580.3779
38Alexandria city VA$81,1600.4404
39Frederick County MD$80,7650.3827
42Carroll County MD$80,0280.3858
90Prince Georges County MD$69,8790.3951
116District of Columbia$66,5830.5343
148Baltimore County MD$62,4440.4396
713Baltimore city MD$39,2410.5008

and then Maryland vs. other high-income states and the United States as a whole:

RankCountyMedian Household IncomeGini Coefficient
2New Jersey$69,6670.4718
5District of Columbia$66,5830.5343
8New Hampshire$63,2800.4298
United States$51,3710.4757

Note the third column of the above tables, the Gini coefficient. The Gini coefficient (or Gini index, as the Census Bureau refers to it) measures the distribution of income, as opposed to the level of income. Its calculation is a bit more complicated than that for median household income; rather than discuss it here I’ll just refer you to my previous explanation.

For present purposes you just need to know that the Gini index has values between 0 and 1 (or 0% and 100%, depending on the source), that a value of 0 corresponds to a completely equal distribution of income (all households’ income is the same) and a value of 1 (or 100%) corresponds to a completely unequal distribution of income (one household receives all income, all other households have none). In practice almost all societies have Gini index values somewhere between 0.30 and 0.60. Also note that the Gini coefficient can be computed based on before-tax income or after-tax income; the Census Bureau figures are computed using before-tax income.

Recall again that the Gini index measures distribution of income, not the level of income. So, for example, for 2012 Howard County had a Gini index of 0.3909. Since this was below the overall US value of 0.4757, distribution of income in Howard County was somewhat more equal than in the US as a whole. Catoosa County in Georgia had a Gini index of 0.3904, almost identical to that of Howard County, but its median household income was only $42,251, almost as low as that of Baltimore city. Howard County is a place where everyone is (relatively) equally rich, Catoosa County is a place where everyone is (relatively) equally poor.

This point also applies to places of relative income inequality as measured by the Gini index: For example, Fairfield County in Connecticut (mentioned in the previous post) has one of the highest Gini index values in the United States at 0.5459, along with a median household income of $79,841 (ranked 43 in the United States), while Richmond, Virginia, has almost the same Gini index (0.5347) but very low household income ($38,926, less than Baltimore City). Fairfield County is rich and unequal, Richmond poor and unequal.

Why is income inequality lower in Howard County—not to mention Loudoun County, which ranked 5th in the US in 2012 in terms of income equality? It’s simply that the economies in both counties are heavily driven by Federal spending, with many people in the counties working for either the government or a government contractor. At the low end government jobs pay better than equivalent private sector jobs, while at the high end they pay worse.

This is true of contractor jobs as well: For example, a skilled programmer will be paid well if they work for a government contract, especially if they have a security clearance, but not as well as if they worked for an investment bank or hedge fund. It’s true also of entrepreneurs: Most people can name several tech billionaires (for example, Steve Jobs, Jeff Bezos, Mark Zuckerberg, Larry Page and Sergey Brin) but would be hard-pressed to name any billionaires who made their fortunes through government contracting. (Ross Perot is the only one I can think of at the moment.)

The net effect is that the spread of incomes in Howard, Loudoun, and other suburban Maryland and Virginia counties is compressed relative to other places: fewer really poor people, and fewer really rich people, but lots of people making good incomes.

So is relative income equality only a function of a government-dominated economy? Not necessarily; for example, per Wikipedia Switzerland, a country in the top 5 of the Heritage Foundation Economic Freedom Index, has a Gini coefficient of 0.409, just a tad above Howard County’s, while South Korea, a country with a thriving export economy, has a Gini coefficient of 0.344, below Loudoun County’s and identical to that of Sherburne County, Minnesota, the US county with the least income inequality in 2012.1 (Again, note that these figures, like the US figures, are pre-tax; many countries have after-tax Gini coefficients below 0.3 due to very progressive tax structures and extensive social insurance programs.)

The conclusion, I think, is that income inequality is not simply driven by pure market forces but reflects cultural attitudes as well: social norms about what constitutes an adequate minimum wage (or indeed whether there should be a minimum wage at all), subjective judgements about how much CEOs and other senior managers contribute to a firm’s productivity compared to the typical employee, political decisions about how much government fiscal, monetary, and other policies should promote the interests of those who hold stock and other capital assets vs. those who do not, and so on. In 1993 the entire United States had a Gini coefficient of 0.389, comparable to that of Howard County today.2 Thus in one sense Howard County is not an outlier that doesn’t reflect the rest of America; it just reflects the America of twenty years ago rather than that of today.

UPDATE: Added Charles County, Calvert County, and St Marys County.

  1. Amusingly, Sherburne County is in rural central Minnesota near the presumed location of the fictional Lake Wobegon, where “all the children are above average.” ↩︎

  2. From the Census Bureau report P60-204, The Changing Shape of the Nation’s Income Distribution, Table 1. Note that comparisons prior to 1993 are problematic because the Census Bureau computed the Gini coefficient somewhat differently. ↩︎