Published online by Cambridge University Press: 03 March 2009
This paper examines the proposition that U.S. manufacturing experienced biased technical change during the period 1850–1919. Tests for bias, in Hicksian terms, are conducted using the translog cost dual. Redefined census data permit these tests to be made at the two-digit level of industry classification and with four inputs considered—labor, capital, materials, and a residual factor input. The tests demonstrate that labor-saving and capital-using biases existed, but material-using biases also were present. Furthermore, the patterns of bias varied considerably from industry to industry and often were of such a magnitude as to overpower ordinary substitution effects.
1 Habakkuk, H. J., American and British Technology in the Nineteenth Century (Cambridge 1962).Google Scholar See also Rothbarth, Erwin, “Causes of the Superior Efficiency of the U.S.A. Industry as Compared with British Industry,” Economic Journal, 56 (09 1946), 383–90.Google Scholar
2 See Temin, Peter, “Labor Scarcity and the Problem of American Industrial Efficiency in the 1850's,” this Journal, 26 (09 1966), 277–98Google Scholar; Rosenberg, Nathan, “Anglo-American Wage Differences in the 1820's,” this Journal, 27 (06 1967), 221–29Google Scholar; Fogel, Robert, “The Specification Problem in Economic History,” this Journal, 27 (09 1967), 283–308;Google ScholarDrummond, Ian, “Labor Scarcity and the Problem of American Industrial Efficiency in the 1850's: A Comment,” this Journal, 27 (09 1967), 383–90;Google ScholarUselding, Paul, “Factor Substitution and Labor Productivity Growth in American Manufacturing, 1839–1899,” this Journal, 32 (09 1972), 670–81.Google Scholar See also Ames, Edward and Rosenberg, Nathan, “The Enfleld Arsenal in Theory and History,” Economic Journal, 78 (12 1968), 827–42;Google Scholar and Temin, Peter “Labor Scarcity in America,” Journal of Interdisciplinary History, 1 (Winter 1971), 251–64.Google Scholar This literature is summarized in David, Paul, Technical Choice, Innovation, and Economic Growth (Cambridge, 1975), chap. 1.Google Scholar
3 A thorough review of the issues can be found in Uselding, Paul, “Studies of Technology in Economic History,” in Research in Economic History, Supplement I, Gallman, Robert, ed. (Greenwich, CT., 1977), pp. 149–220.Google Scholar
4 Rosenberg, Nathan, on “Technological Change,” in Davis, Lance E., Easterlin, Richard A., Parker, William N., eds., American Economic Growth (New York, 1972), p. 241.Google Scholar See also Vedder, Richard, The American Economy in Historical Perspective (Belmont, CA, 1976), p. 281.Google Scholar
5 Uselding, Paul, “Factor Substitution,” p. 672.Google Scholar The empirical studies are: Uselding, Paul and Juba, Bruce, “Biased Technical Progress in American Manufacturing,” Explorations in Economic History, II (Fall 1973), 55–72;Google Scholar for the twentieth century, see David, Paul and van de Klundert, Theo, “Biased Efficiency Growth and Capital-Labour Substitution in the U.S., 1899–1960,” American Economic Review, 60 (06 1965), 357–94, and Abramovitz, Moses and David, Paul, “Economic Growth in America: History Parables and Realities,” De Economiste, 121 (05/06 1973), 251–72;Google Scholar and at the sectoral level, see Asher, Edward, “Industrial Efficiency and Biased Technical Change in American Manufacturing: The Case of Textiles in the 19th Century,” this Journal, 32 (06 1972), 431–42.Google Scholar
6 Binswanger, Hans P. and Ruttan, Vernon W., Induced Innovation: Technology, Innovation, Institutions and Development (Baltimore, 1978), pp. 13–14.Google Scholar
7 Habakkuk, H. J., American and British Technology, p. 95.Google Scholar
8 Rosenberg, Nathan, “Technological Change,” p. 251.Google Scholar
9 Berndt, Ernst and Wood, David, “Technology, Prices, and the Derived Demand for Energy,” The Review of Economics and Statistics, 57 (08. 1975), 259–68.Google Scholar
10 It is pertinent to note that the constructed data accord in a general manner with those of Niemi, Albert, State and Regional Patterns in American Manufacturing, 1860–1900 (Westport, CT, 1974).Google Scholar
11 Bateman, J. Fred and Weiss, Thomas, A Deplorable Scarcity: The Failure of Industrialization in the Slave Economy (Chapel Hill, NC, 1981).Google Scholar Also see Atack, Jeremy, Estimation of Economies of Scale in Nineteenth Century United States Manufacturing and the Form of the Production Function, unpublished Ph.D. dissertation, Indiana University, 1976, especially chap. 3.Google Scholar
12 For instance, Bateman and Weiss have taken samples for Florida and Texas from the manuscript census and recalculated the data. They then compared the recalculated data with the published data. They found, for example, that in Florida in 1850, 56 percent of total investment capital, 21 percent of employment, and 7 percent of output value were omitted from the published census tables. In Texas in 1850, the figures were 13 percent, 3 percent, and 2 percent, respectively. Their supposition is that the Florida figures probably define the outer boundary of that type of error, and that in most states, particularly those in the industrialized North, the error factor would be below that of Texas. This is only supposition inasmuch as similar recalculations have not been attempted for other states. Furthermore, there is the whole set of measurement errors that cannot be rectified by recalculations from the manuscript census.
13 The error terms are assumed to be multivariate normally distributed with a nonsingular variance-covariance matrix at each observation.Google Scholar
14 See Lower, Arthur R. M., The North American Assault on the Canadian Forest (Toronto, 1938).Google Scholar
15 Williamson, Samuel H., “The Growth of the Great Lakes as a Major Transportation Resource, 1870–1911,” Research in Economic History, vol. 2, Uselding, Paul, ed. (Greenwich, CT, 1977), pp. 178–82.Google Scholar
16 Allen, Robert C., “The Peculiar Productivity History of American Blast Furnaces, 1840–1913,” this Journal, 37 (09. 1977), 605–33.Google Scholar
17 Chi-squared tests on the mutual independence of bias type and the size of shares (defined either as the 1850 share or the mean share over the period) lead to the acceptance of the null-hypothesis that there was no connection between the type of bias and share size. So too, a Hotelling-Pabst test of the rate of bias and the size of share, by rankings, would not cause rejection of the null-hypothesis of independence.Google Scholar
18 The Allen own-elasticity of substitution (σii) and Allen cross-elasticity of substitution (σii) are given by:
19 See Berndt and Wood, “Technology,” and Humphry, D. B. and Moroney, J. R., “Substitution among Capital, Labor, and Natural Resource Products in American Manufacturing,” Journal of Political Economy, 83 (02 1975), 57–82.Google Scholar
20 Elasticities of factor demand are calculated as πii = θ~iσiis where θi is the estimated factor share and σii is the Allen own-elasticity of substitution. Detailed estimates of the Allen partial elasticities of substitution and the price elasticities of factor demand are available from the authors on request.Google Scholar
21 See Berndt and Wood, “Technology.”Google Scholar
22 A crude rate of total factor productivity was calculated to be 0.417 percent a year on average between 1850 and 1914 for all manufacturing. It was computed using a Divisia index where * indicates a rate of change, F is total factor productivity, and Q is real output. Prices to deflate current value of output were constructed in the same manner as those used to impute material prices. The weighted mean (weights being mean real output in each Sector) was computed and averaged over the period. It should be noted that the above figure should be viewed with caution especially if comparison is made with economy-wide measures of total factor productivity. It understates the value because of intra-industry shipments and overstates because of the value of shipments from manufacturing with reference to the economy as a whole. The year 1914 was used, rather than 1919, to eliminate the effects of World War I.Google Scholar
23 See the works cited in footnote 5.Google Scholar
24 Chandler, Alfred D. JrThe Visible Hand: The Managerial Revolution in American Business (Cambridge, MA, 1977), p. 347. In the sectors that he identifies as key sectors for mergers (SICs 20, 28, 32–36) and for the development of multi-function activity (SICs 20, 28, 29, 33, 35/6, 37), there is no strong similarity in the pattern of bias. Furthermore, since managerial salaries are included in the “other” factor, any bias toward greater use of managers might be expected to appear in βRI. As reported earlier, none of these sectors exhibited significant “other” -using or “other” -saving technical change, although any biased adoption of managers might be swamped by other effects included in this residual factor.Google Scholar
25 Uselding, Paul, “Factor Substitution,” p. 675.Google Scholar
26 Reference is to the literature originating from Habakkuk such as Rosenberg, Nathan, The Ameican can System of Manufactures (Chicago, IL, 1969)Google Scholar, and Harley, C. K., “Skilled Labour and the Choice of Technique in Edwardian Industry,” Explorations in Economic History, 11 (04 1974), 391–414.Google Scholar
27 For instance, see Berndt and Wood, “Technology,” and Binswanger, Hans, “The Measurement of Technical Change Biases with Many Factors of Production,” American Economic Review, 64 (12. 1974), 964–76.Google Scholar
28 Christensen, Laurits, Jorgenson, Dale, and Lau, Lawrence, “Conjugate Duality and the Transcendental Logarithmic Production Function,” Econometrica, 39 (07 1971), 259–68;Google Scholar and by the same authors, “Transcendental Logarithmic Production Frontiers,” The Review of Economics and Statistics, 55 (02 1973), 28–45.Google Scholar See also Binswanger, “Measurement of Technical Change Biases,” p. 967.Google Scholar
29 See Diewert, W. E., “Application of Duality Theory,” Intrilligator, M. and Kendrick, D., eds., Frontiers of Quantitative Economics, vol. 2 (Amsterdam, 1974), pp. 106–70 for a thorough interpretation.Google Scholar