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Changes in the productive efficiency of U.S. flour mills in the late nineteenth century: an input-distance-function approach

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Listed:
  • Yongseung Han

    (University of North Georgia)

  • Arthur Snow

    (University of Georgia)

  • Ronald S. Warren

    (University of Georgia)

Abstract

The productive efficiency of the U.S. flour milling industry increased substantially between 1850 and 1880. Specifically, a typical flour mill in 1880 was able to produce the same value of output as a mill in 1850 with 25 percent fewer factor inputs. We use the concept of the cone technology, combined with an input-distance-function approach, to decompose this increase in productive efficiency into changes in technical efficiency, technological progress, and changes in scale efficiency, assuming unchanged allocative efficiency in combining inputs. We find that the average technical efficiency of flour mills was essentially constant throughout the period, implying that almost all the gains in productive efficiency were due to improvements in scale efficiency occasioned by more fully exploiting increasing returns. Furthermore, productive efficiency was positively related to mill size as larger mills were better able to take advantage of both economies of scale and technological progress. These results provide evidence in support of an important role for the increased scale of production in providing the preconditions for the emergence in the early twentieth century of an oligopolistic market structure in the U.S. flour milling industry.

Suggested Citation

  • Yongseung Han & Arthur Snow & Ronald S. Warren, 2021. "Changes in the productive efficiency of U.S. flour mills in the late nineteenth century: an input-distance-function approach," Journal of Productivity Analysis, Springer, vol. 56(2), pages 115-132, December.
  • Handle: RePEc:kap:jproda:v:56:y:2021:i:2:d:10.1007_s11123-021-00615-y
    DOI: 10.1007/s11123-021-00615-y
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    as
    1. Léopold Simar & Valentin Zelenyuk, 2011. "Stochastic FDH/DEA estimators for frontier analysis," Journal of Productivity Analysis, Springer, vol. 36(1), pages 1-20, August.
    2. Phill Wheat & Alexander D. Stead & William H. Greene, 2019. "Robust stochastic frontier analysis: a Student’s t-half normal model with application to highway maintenance costs in England," Journal of Productivity Analysis, Springer, vol. 51(1), pages 21-38, February.
    3. Zelenyuk, Valentin, 2006. "Aggregation of Malmquist productivity indexes," European Journal of Operational Research, Elsevier, vol. 174(2), pages 1076-1086, October.
    4. Atack, Jeremy, 1986. "Firm Size and Industrial Structure in the United States During the Nineteenth Century," The Journal of Economic History, Cambridge University Press, vol. 46(2), pages 463-475, June.
    5. Stevenson, Rodney E., 1980. "Likelihood functions for generalized stochastic frontier estimation," Journal of Econometrics, Elsevier, vol. 13(1), pages 57-66, May.
    6. William J. Collins & Robert A. Margo, 2015. "Enterprising America: Businesses, Banks, and Credit Markets in Historical Perspective," NBER Books, National Bureau of Economic Research, Inc, number coll13-1, January-J.
    7. Atkinson, Scott E. & Primont, Daniel, 2002. "Stochastic estimation of firm technology, inefficiency, and productivity growth using shadow cost and distance functions," Journal of Econometrics, Elsevier, vol. 108(2), pages 203-225, June.
    8. James, John A., 1983. "Structural Change in American Manufacturing, 1850–1890," The Journal of Economic History, Cambridge University Press, vol. 43(2), pages 433-459, June.
    9. Bert Balk, 2001. "Scale Efficiency and Productivity Change," Journal of Productivity Analysis, Springer, vol. 15(3), pages 159-183, May.
    10. Christopher F. Parmeter & Valentin Zelenyuk, 2019. "Combining the Virtues of Stochastic Frontier and Data Envelopment Analysis," Operations Research, INFORMS, vol. 67(6), pages 1628-1658, November.
    11. Atack, Jeremy & Bateman, Fred & Margo, Robert A., 2008. "Steam power, establishment size, and labor productivity growth in nineteenth century American manufacturing," Explorations in Economic History, Elsevier, vol. 45(2), pages 185-198, April.
    12. Layer, Kevin & Johnson, Andrew L. & Sickles, Robin C. & Ferrier, Gary D., 2020. "Direction selection in stochastic directional distance functions," European Journal of Operational Research, Elsevier, vol. 280(1), pages 351-364.
    13. Chang-Tai Hsieh & Peter J. Klenow, 2009. "Misallocation and Manufacturing TFP in China and India," The Quarterly Journal of Economics, Oxford University Press, vol. 124(4), pages 1403-1448.
    14. Olley, G Steven & Pakes, Ariel, 1996. "The Dynamics of Productivity in the Telecommunications Equipment Industry," Econometrica, Econometric Society, vol. 64(6), pages 1263-1297, November.
    15. Amsler, Christine & Prokhorov, Artem & Schmidt, Peter, 2016. "Endogeneity in stochastic frontier models," Journal of Econometrics, Elsevier, vol. 190(2), pages 280-288.
    16. William C. Horrace & Peter Schmidt, 2000. "Multiple comparisons with the best, with economic applications," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(1), pages 1-26.
    17. Sickles,Robin C. & Zelenyuk,Valentin, 2019. "Measurement of Productivity and Efficiency," Cambridge Books, Cambridge University Press, number 9781107036161, May.
    18. By RICHARD PERREN, 1990. "Structural change and market growth in the food industry: flour milling in Britain, Europe, and America, 1850-1914," Economic History Review, Economic History Society, vol. 43(3), pages 420-437, August.
    19. Banker, Rajiv D., 1984. "Estimating most productive scale size using data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 17(1), pages 35-44, July.
    20. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
    21. Efthymios G. Tsionas & Subal C. Kumbhakar & Emir Malikov, 2015. "Estimation of Input Distance Functions: A System Approach," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 97(5), pages 1478-1493.
    22. Atack, Jeremy, 1979. "Fact in fiction? The relative costs of steam and water power: a simulation approach," Explorations in Economic History, Elsevier, vol. 16(4), pages 409-437, October.
    23. Baltagi, Badi H & Griffin, James M, 1988. "A General Index of Technical Change," Journal of Political Economy, University of Chicago Press, vol. 96(1), pages 20-41, February.
    24. Saloutos, Theodore, 1946. "The Spring-Wheat Farmer in a Maturing Economy 1870–1920," The Journal of Economic History, Cambridge University Press, vol. 6(2), pages 173-190, November.
    25. Svend Rasmussen, 2010. "Scale efficiency in Danish agriculture: an input distance--function approach," European Review of Agricultural Economics, Foundation for the European Review of Agricultural Economics, vol. 37(3), pages 335-367, September.
    26. Robin Sickles & David Good & Lullit Getachew, 2002. "Specification of Distance Functions Using Semi- and Nonparametric Methods with an Application to the Dynamic Performance of Eastern and Western European Air Carriers," Journal of Productivity Analysis, Springer, vol. 17(1), pages 133-155, January.
    27. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    28. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    29. Atkinson, Scott E & Cornwell, Christopher, 1994. "Estimation of Output and Input Technical Efficiency Using a Flexible Form and Panel Data," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 35(1), pages 245-255, February.
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