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The Quality of Services in Company Towns: Sanitation in Coal Towns During the 1920s

Published online by Cambridge University Press:  03 March 2009

Price V. Fishback
Affiliation:
Associate Professor of Economics, University of Georgia, Athens, GA 30602, and Visiting Professor of Economics, University of Texas at Austin
Dieter Lauszus
Affiliation:
Professor of Economics, Universitaet Bielefeld, West Germany

Abstract

Coal company towns were infamous, being described as exploitive, and charged with providing low-quality services, like sanitation. Yet, the quality of sanitation in coal towns in 1922 appears similar to that in cities of similar size, although lagging behind that in major cities. Within the coal region, company and independent towns provided similar levels of sanitation. The quality of sanitation in company towns varied in response to cost-related factors, including town age, population, and natural location. Meanwhile, workers were mobile and demanded compensating increases in wage rates in towns with lower-quality sanitation and higher rents.

Type
Articles
Copyright
Copyright © The Economic History Association 1989

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References

Earlier versions of this article were presented at the 1986 Cliometrics Conference, the 1986 University of Georgia Department of Economics Summer Seminar, the Economic History Association Meetings and Clemson University in 1987, and the University of Texas at Austin and University of New Mexico in 1988. The authors would like to thank Scott Atkinson, John Brown, Louis Cain, Cletus Coughlin, Christian Dustmann, Mason Gerety, Caren Ginsberg, Claudia Goldin, Robert Higgs, Gary Libecap, Hugh Nourse, Anthony O'Brien, Raymond Sauer, Dan Slesnick, Richard Sutch, Joseph Terza, Ron Warren, Paul Wilson, and anonymous referees for helpful comments and criticisms on earlier drafts. Financial support for the completion of this project was provided by the Earhart Foundation.

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11 The house rent (r) might be endogenous to the system in two ways. First, employers might recover some of the costs of sanitation by charging higher house rents. Second, if the company has a local monopoly on housing, rent becomes a function of the number of miners. The comparative statics for the remaining parameters are not affected by either of these changes. In the empirical section we experimented with omitting rent from the regressions and by replacing the wage variable with a net wage variable, the monthly wage minus the monthly rent. The qualitative results in the alternative regressions were basically the same as those reported in Tables 1 and 2. We chose to report the equations with rent included because we could explicitly test the extent to which wages adjusted to compensate for higher rents.

12 Descriptions of the substantial movement of miners between towns, particularly in nonunion districts can be found in Price Fishback, V., “Employment Conditions of Blacks in the Coal Industry, 1900–1930” (Ph.D. diss., University of Washington, 1983), pp. 6065;Google ScholarCorbin, David, Life, Work, and Rebellion in the Coal Fields: The Southern West Virginia Miners, 1880–1922 (Chicago, 1981), pp. 4043;Google Scholar U.S. Senate, U.S. Immigration Commission, Report on Immigrants in Industries, Part I: Bituminous Coal Mining, 61st Congress, 2nd session (Washington, D.C., 1911), vol. 1, P. 164; and vol. 2, pp. 27, 149, 151–52, 155, 158, 218.Google Scholar

13 The LOCALE rating also contains a measure of accessibility.

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20 The frequency distributions of the sanitation ratings are reported in the Appendix, Section II. Since the ratings are bounded by zero and 100, we also ran regressions where we used a logit transformation of the sanitation ratings. The results were very similar to those reported in Tables 1 and 2.

21 The population variable is treated here as an exogenous variable affecting the company's costs of providing sanitation. The size of the town's population might be endogenous because the population is strongly correlated to the number of workers at the mine. We ran additional regressions where we replaced the population variable with population predictions from an instrument equation. The basic qualitative results are similar to those reported in Tables 1 and 2.

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