American Inequality: The Role of Technology and Government

James Galbraith and Travis Hale look at the distribution of income on a county by county basis and find that geographic income inequality tracks the NASDAQ to a "remarkable degree." But there is another factor as well. Counties with defense related industry "went from rich to richer" indicating that "[g]overnment contracts ... have been the one major source of regional enrichment and redistribution under Bush." This is from Economist's Voice:

American Inequality: From IT Bust to Big Government Boom, by James K. Galbraith and J. Travis Hale, Economists’ Voice: The American economy is not a monolith, but a kaleidoscope. Things change, and so does the geographic distribution of income. Some counties prosper, others suffer; much depends on the rise and fall of crops, oil, steel and computers—and on where those activities are found.

For roughly a quarter century, between 1974 and 2000, income inequality between counties rose steadily, and in the last years of the century certain high-technology counties, notably in Northern California, grew exceptionally rich. In 2000 the trend reversed, and county incomes began to converge.

It might be tempting to credit the Bush Administration with a benign reversal of what had been a disturbing trend. We doubt this interpretation. Instead, for good or ill, geographic inequality in America tracks the NASDAQ, to a remarkable degree.

And yet, under Bush, some counties have defied the convergence trend. Which ones are these? While incomes in Silicon Valley deflated, the counties around Washington D.C. and several other defense-based locations went from rich to richer. Government contracts, in short, have been the one major source of regional enrichment and redistribution under Bush, with the nation’s capital region being the one big winner.

Overall Trends in County Income Inequality

Over the past three decades, income inequality between counties has risen considerably. Compared to each other and to the national average, the rich counties are richer and the poorest counties are poorer than they were a generation back. This trend is seen in the upward rise of the solid line in Figure 1, which gives Theil’s T statistic as a measure of income inequality between counties. Details of the calculation are [here]. . Since 2000, this form of income inequality has fallen. Put differently, the county you live in now matters less to your income than it did six years ago.

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Interestingly, this form of inequality tracks the fortunes of high technology quite well. ... Figure 1 shows the natural logarithm of the NASDAQ Composite, average monthly closings, 1971-2004, as compared to the between-counties income inequality index. The correlation is .955 and one is put in mind of Thoreau’s remark that some circumstantial evidence is quite strong, “as when you find a trout in the milk.”

Winners and Losers in the Bush Administration Through 2004

Between 2000 and 2004, in the wake of the of the IT bust, aggregate between-county income inequality declined, and income inequality measured between individuals remained roughly constant. Not every county converged toward the average, however. Table 1 lists the ten counties with the largest decreases and the ten with the largest increases in their Theil elements from 2000 to 2004. A county’s Theil element in any given year may be positive or negative. If the county’s average income is greater than the national average, the element will be positive, otherwise zero (if income equals the average), or negative (if income falls below the average). We interpret an increase in an already positive Theil element as being an indication that a rich county has gotten richer relative to the average.

Both the winners and losers in Table 1 tell a story; that of the losers will probably surprise no one. The left side of Table 1 has a distinctly technological flavor. Eight of these ten counties host at least one firm listed on the CNET Tech Index, and 51 of the 80 index firms are located in the 50 counties with the largest negative Theil element changes over this period. Thus the losing counties in the 21st century largely reflect the IT slide that has been so widely reported. The right side of Table 1 contains some news: it shows the counties with the most significant relative income growth from 2000 to 2004. So, what links these winning counties together?

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First, we must mention a couple of caveats. The presence of Los Angeles County at the top of the list is an anomaly. In 2000, for reasons unknown to us, average income in Los Angeles was two percentage points below the national average, whereas in every other year from 1999 to 2004 the county was within one-half of one percent of the national average. Also Philadelphia’s gains during this period actually reduced between-county inequality, as average income in Philadelphia grew from 83% of the national average in 2000 to 90% in 2004. In other words, the increasing Theil element in this case was simply less negative, not more positive, than before.

In the other eight counties, average incomes were higher than the national average in 2000 and rose through 2004. Of these counties, four contain or are near to the nation’s capital (DC, Fairfax, Montgomery, Baltimore). Two contain state capitals (Davidson, Suffolk). San Diego County is home to several Navy installations, and Orange County is a poster-child for the ongoing—but perhaps soon-to-burst—housing bubble.

The economic effect of the Bush years on the Baltimore-Washington region is not limited to the four counties in the top ten. Among the top 35 gainers, there are five more in the immediate vicinity: Anne Arundel, Maryland (16); Prince George’s, Maryland (21); Baltimore (Independent City), Maryland (27); Arlington, Virginia (29); and Alexandria (Independent City), Virginia (34). Conversely, none of the top-50 element declines from 2000 to 2004 come from counties near the District of Columbia.

In short, government spending (especially for the military) provides the main thread visibly linking the economic winners of the Bush years.

Conclusions

Along with the technology bust and the slide of the NASDAQ, there came a reversal in 2000 of the steady march of roughly a quarter century of rising geographic income inequality in America.

This reversal predates the Bush administration and its normative significance is unclear: it mainly reflects the end of the technology boom.

In the Bush years, a concentration of increasing income around Washington D.C. appears to reflect the vast growth in federal government spending. This spending contributed to increased housing prices and credit expansion in and around the capital, creating new winners in the private sector in that region. Much of this spending is related to the growth of military and intelligence activities, though federal civilian spending also grew rapidly in 2003–2004; there was undoubtedly also substantial growth in spending by private sector lobbies. The ultimate economic consequences should, of course, be judged in part by the worth of the activities undertaken. However, it is already clear that the Bush years so far have engendered no very broad revival of private-sector economic initiative; a main economic beneficiary of government spending was the government itself and those associated with it. Given the anti-government rhetoric of the administration, this is, well, ironic.

References and Further Reading

Bureau of Economic Analysis (2006) “Regional Economic Accounts,” Washington: U.S. Department of Commerce. Available at: http://www.bea.gov/bea/regional/spi.

Galbraith, James K. and J. Travis Hale (2006) “The Changing Geography of American Inequality: From IT Bust to Big Government Boom,” The University of Texas Inequality Project Working Paper No. 40, October 23. Available at: http://utip.gov.utexas.edu/papers/utip_40.pdf.

National Institute of Standards and Technology (2002) “Counties and Equivalent Entities of the United States, Its Possessions, and Associated Areas,” Washington: U.S. Department of Commerce. Available at: http://www.itl.nist.gov/fipspubs/fip6-4.htm.

Shapiro, Robert J. (2002) “The American Economy Following the Information-Technology Bubble and Terrorist Attacks,” Fujitsu Research Institute Economic Review 6(1): 105–15.

U.S. Census Bureau (2005) “Table H-4. Gini Ratios for Households, by Race and Hispanic Origin of Householder: 1967 to 2003,” Washington: U.S. Department of Commerce. Available at: http://www.census.gov/hhes/www/income/histinc/h04.html.