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:

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

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.

The top-line news (which you’ll no doubt read soon enough in mainstream news outlets) is that we’re number 2: at $108,844 Howard County had the second-highest median household income of any US county in 2012, topped only by Loudoun County, Virginia, at $117,876. (Incidentally, what is it with Howard County always coming in second? This time it was Loudoun County, last time it was Eden Prairie MN. When do we get to be first?)

This is a major jump up from 2011, in which Howard County was in fifth place (at $98,953). Loudoun County was also first in 2011 at $119,134, but unlike Howard its median household income has decreased since then. Note that you can’t directly compare the 2011 and 2012 figures, because they’re not adjusted for inflation, but the relative rankings would still be the same.

So much for the headlines; now for the rest of the story.

Here’s a comparison of how Howard County fared in 2012 relative to its neighboring counties in Maryland, the counties of Northern Virginia, and the two closest major cities (I’ll come back to the Gini coefficient in the fourth column later):

Here’s the top ten states for 2012, plus the figures for the US as a whole:

Now let’s talk about what these numbers mean. First, where do they come from, and how accurate are they? The figures above are from the Census Bureau’s American Community Survey (ACS), and are taken from tables B19013, “Median household income in the past 12 months (in 2012 inflation-adjusted dollars),” and B19083, “Gini index of income inequality,” respectively of the ACS 2012 1-year estimates. (“Gini index” is an alternate term for “Gini coefficient.” I’m using the latter term for consistency with my earlier posts.)

These are statistical estimates based on a limited sample, and have a substantial margin of error (plus or minus $2,972 in the case of the Howard County estimate). Thus the more accurate statement would be that the Howard County median household income for 2012 was somewhere in the range of $105,000–113,000, pretty much the same as Fairfax County.¹

The next point is that we need to distinguish between income and wealth: income is what enables you to pay your mortgage, while wealth is what enables you to not need a mortgage in the first place. Headlines to the effect that Howard County is the second-wealthiest county in the US are misleading; it may be that there are other counties in the US where median household wealth (as opposed to income) is higher. For example, places like Fairfield County, Connecticut, home of hedge fund billionaires, almost surely have higher average household wealth than Howard County, and their median household wealth may be higher as well.

Other points: Household income is typically used as a measure instead of per capita income because households are the basic economic unit in most cases, and particularly with respect to major purchases like housing. All other things being equal, places where there are lots of two-earner families will have higher median household income than places where there are a lot of singles or one-earner families.²

The median household income is that income such that half of all households make more and half of all households make less. This is a better measure than average household income because average income can be misleadingly skewed upward by the presence of a few extremely high-income households: If a billionaire moved onto your street the average income of you and your neighbors would skyrocket, but the income of the typical neighbor (one who’s in the middle of the list of all neighbors ranked by income) would not be affected. The median household income is thus best thought of as a measure of what it means to be “middle class” in a particular locality, at least in terms of income.

This is an important point and worth expanding on, especially in looking the major jump in Howard County median household income from 2011 to 2012. There are at multiple ways in which median household income could grow:

Households across the board could include more people earning income, due to a higher rate of people living together instead of alone and/or to non-working spouses entering the labor force. Households across the board could also have higher income due to wage increases or other boosts to income (for example, selling stock that had appreciated).

Alternatively, the relative mix of households might change. For example, it might be that the high cost of living drives lower-income families (those below the current median household income) to move out of a particular area, while at the same time the perceived quality of life (schools, parks, libraries, etc.) influences higher-income families (those above the current median household income) to move into the area.

Any or all of these effects could be behind the jump in Howard County median household income from 2011 to 2012; teasing out the real story would require a more in-depth analysis the Census data (one I’m not prepared to take on at this time).

A final point about median household income: It gives a reasonably good picture of how a “middle income” household is doing, but it doesn’t tell us anything about how income is distributed among the various households. For example, suppose that the bottom 10% or 20% of households (by income) had their incomes cut in half, while the top 10% or 20% of households had their incomes doubled. This would not change the median household income at all, since half of all households would still be below the previous median value, and half still above.

So how do we measure the relative distribution of income across households, and how does Howard County stand on this measure? That’s the topic of my next post.

UPDATE: Added Charles County, Calvert County, and St Marys County to the list.

Chris Jackman (cjackman@hotmail.com) - 2013-09-23 12:36

You left Calvert County, MD ($87,449) off your list.

hecker - 2013-09-24 12:36

You’re right, I left Calvert County off the list; in my defense, I was focusing on the counties immediately neighboring Howard, and forgot about Calvert, Charles and St Marys County. Incidentally, at $87,449 Calvert County is 19th on the list of highest-income counties; Charles County is 15th at $90,880 and St Marys is 21st at $86,358. (Their Gini coefficients are 0.409, 0.3937, and 0.3779 respectively.)

Chris Jackman (cjackman@hotmail.com) - 2013-09-24 12:43

I just thought that you may want to include them since you posted several VA counties that are also in the Washington-Baltimore CSA.

hecker - 2013-09-25 03:15

You’re right. I updated the post to include them.

I previously discussed use of the Gini coefficient as a way to measure income inequality (or equality, as the case may be), and promised to discuss why Howard County is noteworthy in this regard. In brief, Howard County is one of only seven counties in the US (out of 800 counties and other geographic areas) that rank in the top 5% (positions 1-40) for both median household income and income equality (as measured by the Gini coefficient):

(By way of comparison, the estimated Gini coefficient for the entire US in 2007 is 0.467, while the estimated US median household income in 2007 is $50,740.)

All of these counties share similar characteristics: They are formerly rural counties, relatively small in population (ranging from roughly 100,000 to 400,000), that are close enough to major cities to benefit from their economic growth but far enough away to exclude urban concentrations of poverty. Except for Douglas County (a suburb of Denver) and Scott County (a suburb of Minneapolis-St Paul), all are located near Washington DC. This points up the role of the Federal government as the economic engine of the region, providing lots of well-paying government and contractor jobs but at the same time not fostering an entrepreneurial culture that might produce more truly wealthy people.¹

Although people disagree on the exact causes, there’s general agreement that income inequality has been generally growing over the past few decades, both in the US as a whole and within Maryland specifically. Howard County has been no exception, but even so its current level of inequality, although higher than it was in former years, is apparently no greater than that for the US as a whole in 1967, the year Columbia was founded.²

Howard County’s high median household income and low Gini coefficient could be interpreted as an endorsement of the “Columbia vision”: Columbia and Howard County have achieved 21st century-leading prosperity accompanied by 1960s-level equality. But does the Columbia vision really have anything to with this?

As noted above, while its situation is special in the US as a whole, Howard County is joined in its relative good fortune by several other Maryland and Virginia counties, all standard garden-variety suburbs with no Jim Rouse-like figures present at the creation (as it were). Rouse was certainly an enlightened developer, but first and foremost he was a canny developer, and the fundamental reason for Columbia’s success was Rouse’s foresight in seeing over forty years ago that Howard County’s “location, location, location” positioned it for future prosperity.

Despite that, I think the (lingering) vision of what Columbia should be does influence public attitudes toward income inequality in Howard County, and may help account for some of the special characteristics of the debates over Columbia’s future. For example, I’m sure that many opponents of the WCI Plaza Residences were sincerely concerned about the architectural compatibility of a 22-story tower with Columbia Town Center as it is and (in their minds) should be. However I also think some of the opposition was due to unease as to what it meant for the Columbia vision to have rich people in $2M condos looming over the split-levels, townhouses, and apartments of the surrounding villages.

Having the truly wealthy and their luxurious dwellings sprinkled through western Howard is one thing, having them occupy the symbolic heart of Columbia would be quite another, and I can understand why some older Columbians may have been troubled at the thought of it. I think a similar unease may lie behind the concern expressed that future housing in Columbia Town Center would be monopolized by the “wealthy few.”

In my previous post I mentioned Fairfield County, Connecticut. As Jay Hancock wrote in a blog post a while back, though it has a high median household income Howard County isn’t really rich in the sense that other areas are. On the other hand Fairfield County (or, to be more precise, Greenwich and other towns within Fairfield County) is indeed rich, with a vengeance. (Or at least it was, before the recent financial crisis; I don’t know how it’s doing now.) Home to a number of hedge fund billionaires and other people who made their fortunes in financial services, in 2007 Fairfield County had a mean household income of over $130,000, ranked in the top 5% for median household income ($80,241), and in the bottom 5% for income equality (with a Gini coefficient of 0.534).

Fairfield County is in a sense Howard County as it might have been in an alternative world, if DC were like New York. (In this regard it’s also worth noting that in 2007 New York City surpassed DC in both median household income, $64,217 vs. $54,317, and income inequality, with a Gini coefficient of 0.603 vs. 0.542.) That Howard County isn’t Fairfield County in this world might be seen as an unalloyed blessing: We live in a more fair and equal society, and are more insulated from the vicissitudes of global capitalism.

However it can also be argued that Columbia and Howard County are giving up something in return, and that (within limits) they might benefit from an increased influx of true wealth and the inequality that accompanies it. That’s a subject I hope to address in a future post.

JessieX - 2008-11-17 05:22

Frank, From day one, your perspective and thinking has made me more curious and thoughtful. Thanks again for sharing how you look at things. And thanks for this interesting, albeit a bit nerdy, post. ;-) See you at the BlogTale party Thursday, http://www.socializr.com/event/738244444 ~jessiex

Frank Hecker - 2008-11-18 03:32

Jessie, thanks for stopping by. Sorry for the nerdiness, it’s just that sometimes having the numbers and understanding the concepts is important – otherwise it’s all just opinions!

In a previous post I discussed the concept of median income and how it avoids certain distortions inherent in mean (average) income. However median income by itself is not adequate to characterize the economic status of households in Howard County (or anywhere else for that matter). In particular, the median income just provides the “midpoint” for income, i.e., the income value for which 50% of the households make more and 50% make less; it does not address the question of how income is actually distributed among the various households.

For example, let’s go back to our simple 10-household example from the last post:

I’ve added two new columns of data, but otherwise the situation is as I described it previously: the ten households have an average income of $118,900 but a median income of $101,500, very similar to the actual numbers for Howard County.¹ Now let’s look at a second 10-household example:

As it happens, these ten households have exactly the same average income ($118,900, $1,189,000 divided by 10) and exactly the same median income ($101,500, halfway between $43,000 and $160,000) as in the first example. However the distribution of income looks very different; in its division of households between rich and poor it looks much more like Baltimore city or Washington, DC, than it does Howard County. Clearly this difference in income inequality is not captured by the median or mean income, or even by related measures like the difference between the mean and the median. How can we quantify this difference?

One commonly-used measure of income inequality is the so-called Gini coefficient or Gini index. The computation of the Gini coefficient is more complicated than that for mean or median income, but it’s still relatively straightforward and comprehensible. The key is to look at the numbers in the last two columns of the tables above, and especially the last column, cumulative share of household income.

The third column simply gives the share of household income going to that particular household. For example, in the first table household #1 has income of $16,000 against a total of $1,189,000 for all households, or 1.35% of all income; similarly household #10 has a 26.66% share of all income ($317,000 divided by $1,189,900), and so on for the other households. The fourth column then uses these figures to compute the share of income going to the poorest n% households. For example, household #1 has a 1.35% share of total income and household #2 has a 3.11% share, so the poorest 20% of households (i.e., households #1 and #2 out of 10 total households) have 4.46% of all income (1.35% plus 3.11%). Similarly we can add the income share figures for households #1 through #9 to determine that the poorest 90% of households have 73.34% of all income, with the remaining 10% of households (i.e., household #10) having 26.66% as noted above.

The cumulative share of income can be graphed as shown in the figure below. The red points show the values from the fourth column of the table above, with the red lines then connecting the dots to approximate a curve; if there were more households there would be more points and a correspondingly smoother curve.

Now let’s look at the graph for our second example from above:

Again the red points represent the values for cumulative share of income from the fourth column of the second table, with the red lines connecting the dots. What about the blue dots in both graphs? Those represent the ideal case where all the household incomes are equal, or nearly so. In that case the poorest 10% of households will have (almost) 10% of total household income, the poorest 20% will have (almost) 20% of income, and so on. The corresponding curve will then be a straight (or nearly straight) line, here shown in blue.

Note that as household income becomes more unequal, the curve of cumulative income share (the red curve) moves further and further away from the blue line representing perfect (or nearly perfect) income equality. This gives us a straightforward way to define the Gini coefficient: It’s the size of the blue-shaded area between the blue line and the red curve, expressed as a fraction (or percentage) of the total area under the blue line. For nearly equal income distributions the red curve will be very close to the blue line, and the Gini coefficient will be close to zero, while for very unequal income distributions the red curve will be far away from the blue line, and the Gini coefficient will approach one (or 100%).

In the first example the Gini coefficient is 0.38, nearly the same as the Gini coefficient of 0.379 for Howard County (see the Census ACS table 19083).² In the second example the Gini coefficient is 0.53. This is comparable to the Gini coefficient for the District of Columbia, which is 0.542. More interestingly for our purposes, it’s nearly the same as 0.534, the Gini coefficient for Fairfield County, Connecticut, a suburban county in the New York City metropolitan area that’s home to many hedge-fund managers and other wealthy financial services professionals.

Unlike DC, Fairfield County is a pretty affluent area overall; it has a median household income of $80,241 (somewhat lower than Howard County’s) and a mean household income of $130,397 (somewhat higher than Howard County’s).³

The following 10-household example roughly mirrors the Fairfield County household income breakdown:

The corresponding Gini coefficient diagram is as follows:

What makes Howard County special with respect to income inequality, and Fairfield County particularly interesting as a comparison? The answers to those questions will be the subject of part 2 of this two-part post.

johntindale - 2008-11-21 02:26

This is a very interesting, informative, and well documented site about income disparity in HoCo. Thank you for all the hard work, research, and analysis,

Flug - 2008-12-01 15:13

I really love your stats and your interpretation of the datas. Great work, as usual. I bet I would have had higher marks in statistic, if have found your blog earlier:)