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June 1993, Vol. 116, No. 6
Robert C. Shelburne and Robert W. Bednarzik
U .S. manufacturing activity, both in general and for specific industries, has a tendency to concentrate in certain geographic areas. The phenomenon was described as early as 1900 and 1905 in the Census of Manufactures.1 An implication of such clustering is that reemployment is likely to be more difficult when a worker loses a job in an industry that is geographically concentrated.
This article provides some estimates of geographic clustering by industrial sector and shows how certain industry characteristics are related to geographic concentration. It also discusses some uses for the estimates in understanding labor market adjustments problems in industries that are intensively involved in international trade.
Methodology and data
We estimated geographic concentration of employment by industry using a Gini coefficient, a useful summary measure of the degree of concentration of a variable.2 If employment in a sector is located in each State in the exact proportion to the total State employment, then there is no tendency toward concentration in that sector, and Gini coefficient is given a value of zero. If, however, all the employment in an industry is located within one State, then the Gini would approach its upper limit of 1. The employment pattern in most industries falls somewhere in between these two extremes; thus, the Gini will be somewhere between 0 and 1. (See the appendix for how the Gini index we used was actually derived.)
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1 Joseph Lewis, "The Localization of Industries," Manufactures: 1905 (Washington, Bureau of the Census, 1907)
2 See Robert C. Shelburne and Robert W. Bednarzik, The Geographical Concentration of Employment and its Implications for Trade and Adjustment (Washington, Bureau of International Labor Affairs, 1992), originally presented at the Southwestern Economics Association in San Antonio in March 1992. In this paper, we included average Ginis for all two-, three-, and four-digit SIC industries. Geographic Gini indexes are used by Paul Krugman, in Geography and Trade (Cambridge, MA, MIT Press, 1991).
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