August, 2001, Vol. 124, No. 8
Précis from past issues
The 20 largest metropolitan areas accounted for just under 45 percent of the U.S. population in 2000, but for 65 percent of the headquarters of large public corporations, according to Thomas Klier and William Testa’s recent Chicago Fed Letter. These metropolitan areas appreciate the headquarters because they employ relatively large numbers of highly skilled white-collar workers and generate demand for a wide range of high-end business services.
Conversely, the firms appreciate the access not only to the skilled professional workforces and business services resources of large cities, but also the communication and transportation infrastructures needed to administer their dispersed operations.
New York, Chicago, and San Francisco are the three metropolitan areas hosting the largest number of headquarters. New York, in fact, has more than twice the number of headquarters as second-place Chicago. San Francisco was the area that experienced the greatest gain in headquarters with a net gain of 39. As a result, San Francisco moved up three ranking spots to third place.
In the June issue of this Review, Thomas W. Hale described the difficulties researchers would encounter attempting to use the type of subjective self-report of disability status that appears in parts of the Current Population Survey. In their NBER working paper, "What do Self-Reported, Objective Measures of Health Measure?" Michael Baker, Mark Stabile, and Catherine Deri provide a similarly critical analysis of more specific techniques for measuring health status in personal surveys.
Their results, based on an analysis of matched Canadian National Population Health Survey (NPHS) and Ontario Health Insurance Plan (OHIP) data, show that there is substantial error in self-reports of specific chronic health conditions. Such specific questioning has been thought to provide a better measure of health status than self-reports of one’s "global" or general health status. However, Baker, Stabile, and Deri find that "for many of the diseases more than 50 percent of the individuals who have a positive doctor’s diagnosis in the OHIP data fail to report having the disease in the NPHS data. Similarly, we find that more than 50 percent of individuals who report having a disease in the NPHS have no corresponding doctor’s diagnosis in the OHIP records."
It may be that the oft-remarked refusal of measured productivity to soar immediately after the invention of the microchip is the extension of a common historical pattern. "In many ways," suggest Kevin L. Klieson and David C. Wheelock, "the absence of immediate productivity improvement with the advent of information processing technology was not unlike earlier experiences with general purpose technologies." Their article in The Regional Economist quarterly from the St. Louis Fed goes on to review historical research on the English and American Industrial Revolutions.
In the English case, for example, Klieson and Wheelock cite evidence that "at the height of the British Industrial Revolution (1760–1830) output per capita grew less than 0.5 percent per year on average, about the same rate as during 1700–60." It was, they report, during the next 4 decades—1830–70—that per capita productivity growth quadrupled.
Even more striking was the evolution of the defining invention of that Revolution—the steam engine. The steam engine was first demonstrated in 1712, but it was not until 1765 that the steam engine was developed into a device that could be used to power a factory. Given this historical perspective, Klieson and Wheelock are encouraged about the puzzle posed by the gap between the invention of the microchip—the defining invention of the computer revolution sweeping today’s economy—in the 1970s and the lag until the latter half of the 1990s of an acceleration on productivity growth. "More important," they assert, "the evidence suggests that a significant portion of the faster rates of labor productivity growth stems from an acceleration of [total factor productivity] growth."
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