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Antebellum Southern White Fertility: A Demographic and Economic Analysis

Published online by Cambridge University Press:  11 May 2010

Abstract

This paper investigates the decline and regional differential in antebellum southern white fertility using published census materials and the 1860 population schedules. Demographic analysis is conducted with a synthetic total fertility rate that has four components: age at first birth, age at last surviving birth, surviving-child spacing, and the proportion of women who eventually have surviving children. The socioeconomic analysis employs regressions and focuses on causes of the underlying changes in the components. Family limitation appears to have been unimportant in this population. The distribution of wealth was.probably an important factor shaping the time trend and regional differential in fertility.

Type
Articles
Copyright
Copyright © The Economic History Association 1980

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References

The author is Assistant Professor of. Economics at Ohio State University. This paper is based on a portion of his Ph.D. dissertation prepared for the Economics Department at the University of Chicago. The members of his committee, Robert Fogel, Marc Nerlove, and T.W. Schultz, as well as Stanley Engerman and anonymous referees, contributed to the development of the material. The research was supported by the National Science Foundation, the National Institute of Mental Health, the Rockefeller Foundation through a grant to the University of Chicago for the Study of the Economics of Population and Family Decision-Making, and Ohio State University.

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11 The contents of the various census schedules are discussed in Wright, Carroll D., The History and Growth of the United States Census (Washington, D.C., 1900)Google Scholar.

12 The states are Alabama, Arkansas, Delaware, Florida, Georgia, Kentucky, Louisiana, Maryland, Mississippi, Missouri, North Carolina, South Carolina, Tennessee, Texas, and Virginia.

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15 A more complete discussion of the biases can be found in , Steckel, Economics, pp: 9699Google Scholar.

16 The measure is discussed in Trussell, James and Steckel, Richard, “The Age of Slaves at Menarche and Their first Birth,” Journal of Interdisciplinary History, 8 (Winter 1978), 477505CrossRefGoogle ScholarPubMed.

17 The slave infant mortality rate calculated from plantation records is 233 per thousand. Approximately 201 of every thousand children who survived to age 1 did not survive to age 5. Although it is recognized that slave and white mortality rates may have differed, these data suggest that a figure in the neighborhood of 40 percent is not unreasonable. The slave mortality rates are discussed in Steckel, Richard H., “Slave Mortality: Analysis of Evidence from Plantation Records,” Social Science His tory, (3 10 1979), 86114Google Scholar.

18 The estimate equals where qi is the probability of not living to age i, p (ai) is the relative frequency of aj, and a'j represents the average age of two adjacent surviving children. The values of qi are the averages of linear interpolation of male and female death rates from Evans, Robert Jr, “The Economics of American Negro Slavery,” in Universities-National Bureau Committee for Economic Research, Aspects of Labor Economics (Princeton, 1962), p. 212Google Scholar. The technique is relatively crude because it does not allow for multiple deaths between surviving births or for departures from the household. Consequently, the figure of 30.7 is probably an underestimate.

19 The elasticity of R with respect to S is -(L-F)/(L-F+S), which is slightly less than one in absolute value.

20 The relative importance of each component was determined using an equation for the percentage change in R. The equation is:

21 Henry, Louis, Anciennes families genevoises, Cahier No. 26 (Paris, 1956), pp. 8793.Google Scholar; Wrigley, Edward A, “Family Limitation in Pre-Industrial England,” Economic History Review, 2nd series, 20 (04 1966), 82109Google Scholar.

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28 T'ien, H. Yuan, “A Demographic Aspect of Interstate Variations in American Fertility, 1800–1860,” Milbank Memorial Fund Quarterly, 37 (01 1959), 4959Google Scholar; , Forster and , Tucker, Economic Opportunity, p. 64Google Scholar; , Leet, “Determinants,” 371–75Google Scholar. The results of Forster and Tucker and Leet are mixed with regard to the statistical significance of the sex ratio.

29 The Herfindahl index is used in studies of industrial organization to measure the concentration of sales within an industry. A discussion of measures of concentration can be found in Stigler, George J., The Organization of Industry (Homewood, IL, 1968), pp. 2938Google Scholar. The number of seats for each denomination is given in U. S. Census Office, Statistics of the United States in 1860, pp. 352496. Sample values of the index range from.180 to.596Google Scholar.

30 A logistic probability model was chosen for estimation purposes because the dependent variable is dichotomous. The model is discussed in , Steckel, Economics, pp. 135–39Google Scholar. The advantages of the model are discussed in Nerlove, Marc and Press, S. James, “Univariate and Multivariate Log-Linear and Logistic Models,” R-1306-EDA/NIH (Santa Monica, 1973), pp. 39Google Scholar. The variables shown were selected by a step-wise procedure. The absence of the variable representing foreign birth indicates that the coefficient is statistically insignificant.

31 In these and similar calculations, the other independent variables are evaluated at their sample means.

32 Individuals who lived alone or who resided with a nuclear family are considered separate families. Unfortunately, data that permit the calculation of net worth are not available.

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34 There are insufficient observations to distinguish among city sizes.

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36 Similar results were obtained with R as the dependent variable.

37 The calculations and related assumptions are discussed in detail in , Steckel, Economics, pp. 162–66Google Scholar.

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40 Easterlin, et al., “Farms and Farm Families,” p. 65Google Scholar.

41 , Steckel, Economics, p, 103Google Scholar.

42 Hajnal, John, “European Marriage Patterns in Perspective,” pp. 101–43 inGoogle Scholar Glass and Eversley, eds., Population in History.