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The Effect Of Technology Use On Productivity Growth

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  • Robert Mcguckin
  • Mary Streitwieser
  • Mark Doms

Abstract

This paper examines the relationship between the use of advanced technologies and productivity and productivity growth rates. We use data from the 1993 and 1988 Survey of Manufacturing Technology (SMT) to examine the use of advanced (computer based) technologies at two different points in time. We also are able to combine the survey data with the Longitudinal Research Database (LRD) to examine the relationships between plant performance, plant characteristics, and the use of advanced technologies. In addition, a subset of these plants were surveyed in both years, enabling us to directly associate changes in technology use with changes in plant productivity performance. The main findings of the study are as follows. First, diffusion is not the same across the surveyed technologies. Second, the adoption process is not smooth: plants added and dropped technologies over the six-year interval 1988-93. In fact, the average plant showed a gross change of roughly four technologies in achieving an average net increase of less than one new technology. In this regard, technology appears to be an experience good: plants experiment with particular technologies before deciding to add additional units or drop the technology entirely. We find that establishments that use advanced technologies exhibit higher productivity. This relationship is observed in both 1988 and 1993 even after accounting for other important factors associated with productivity: size, age, capital intensity, labor skill mix, and other controls for plant characteristics such as industry and region. In addition, the relationship between productivity and advanced technology use is observed both in the extent of technologies used and the intensity of their use. Finally, while there is some evidence that the use of advanced technologies is positively related to improved productivity performance, the data suggest that the dominant explanation for the observed cross-section relationship is that good performers are more likely to use advanced technologies than poorly performing operations.

Suggested Citation

  • Robert Mcguckin & Mary Streitwieser & Mark Doms, 1998. "The Effect Of Technology Use On Productivity Growth," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 7(1), pages 1-26.
  • Handle: RePEc:taf:ecinnt:v:7:y:1998:i:1:p:1-26
    DOI: 10.1080/10438599800000026
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    References listed on IDEAS

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    1. Zvi Griliches & Jacques Mairesse, 1995. "Production Functions: The Search for Identification," NBER Working Papers 5067, National Bureau of Economic Research, Inc.
    2. Dunne, Timothy & Schmitz, James A, Jr, 1995. "Wages, Employment Structure and Employer Size-Wage Premia: Their Relationship to Advanced-Technology Usage at US Manufacturing Establishments," Economica, London School of Economics and Political Science, vol. 62(245), pages 89-107, February.
    3. Mark Doms & Timothy Dunne & Kenneth R. Troske, 1997. "Workers, Wages, and Technology," The Quarterly Journal of Economics, Oxford University Press, vol. 112(1), pages 253-290.
    4. Ronald S. Jarmin, 1994. "Learning by Doing and Competition in the Early Rayon Industry," RAND Journal of Economics, The RAND Corporation, vol. 25(3), pages 441-454, Autumn.
    5. Dunne, Timothy & Haltiwanger, John & Troske, Kenneth R., 1997. "Technology and jobs: secular changes and cyclical dynamics," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 46(1), pages 107-178, June.
    6. Eric J. Bartelsman & Wayne Gray, 1996. "The NBER Manufacturing Productivity Database," NBER Technical Working Papers 0205, National Bureau of Economic Research, Inc.
    7. Cohen, Wesley M & Levinthal, Daniel A, 1989. "Innovation and Learning: The Two Faces of R&D," Economic Journal, Royal Economic Society, vol. 99(397), pages 569-596, September.
    8. Robert H Mcguckin & George A Pascoe, 1988. "The Longitudinal Research Database (LRD): Status And Research Possibilities," Working Papers 88-2, Center for Economic Studies, U.S. Census Bureau.
    9. Griliches, Zvi, 1986. "Economic data issues," Handbook of Econometrics,in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 3, chapter 25, pages 1465-1514 Elsevier.
    10. Doms, Mark & Dunne, Timothy & Roberts, Mark J., 1995. "The role of technology use in the survival and growth of manufacturing plants," International Journal of Industrial Organization, Elsevier, vol. 13(4), pages 523-542, December.
    11. David N. Beede & Kan H. Young, 1996. "Patterns of Advanced Technology Adoption and Manufacturing Performance: Employment Growth, Labor Productivity, and Employee Earnings," Development and Comp Systems 9604001, EconWPA.
    12. Baldwin, John R. & Diverty, Brent & Sabourin, David, 1995. "Technology Use and Industrial Transformation: Empirical Perspectives," Analytical Studies Branch Research Paper Series 1995075e, Statistics Canada, Analytical Studies Branch.
    13. McGuckin, Robert H, 1995. "Establishment Microdata for Economic Research and Policy Analysis: Looking beyond the Aggregates," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(1), pages 121-126, January.
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    Cited by:

    1. Sushanta K. Mallick & Shirley J. Ho, 2008. "On Network Competition And The Solow Paradox: Evidence From Us Banks," Manchester School, University of Manchester, vol. 76(s1), pages 37-57, September.
    2. Budzyński, Wojciech Stefan & Jankowski, Krzysztof Józef & Jarocki, Marcin, 2015. "An analysis of the energy efficiency of winter rapeseed biomass under different farming technologies. A case study of a large-scale farm in Poland," Energy, Elsevier, vol. 90(P2), pages 1272-1279.
    3. B.K. Atrostic & Sang V. Nguyen, 2002. "Computer Networks and U.S. Manufacturing Plant Productivity: New Evidence from the CNUS Data," Working Papers 02-01, Center for Economic Studies, U.S. Census Bureau.
    4. repec:pal:jorsoc:v:61:y:2010:i:2:d:10.1057_jors.2008.128 is not listed on IDEAS
    5. J. Bradford Jensen & Nathan Musick, 1996. "Trade, Technology, and Plant Performance," Industrial Organization 9603004, EconWPA.
    6. Dolage, D.A.R. & Sade, Abu Bakar & Ahmed, Elsadig Musa, 2010. "The influence of Flexible Manufacturing Technology adoption on productivity of Malaysian manufacturing industry," Economic Modelling, Elsevier, vol. 27(1), pages 395-403, January.
    7. Robert W. Fairlie, 2006. "The Personal Computer and Entrepreneurship," Management Science, INFORMS, vol. 52(2), pages 187-203, February.
    8. Sang Nguyen & B.K. Atrostic, 2006. "How Businesses Use Information Technology: Insights for Measuring Technology and Productivity," Working Papers 06-15, Center for Economic Studies, U.S. Census Bureau.
    9. Ethan Lewis, 2005. "Immigration, Skill Mix, and the Choice of Technique," Working Papers 05-04, Center for Economic Studies, U.S. Census Bureau.
    10. Indjikian, Rouben & Siegel, Donald S., 2005. "The Impact of Investment in IT on Economic Performance: Implications for Developing Countries," World Development, Elsevier, vol. 33(5), pages 681-700, May.
    11. Sang Nguyen & B.K. Atrostic, 2005. "Computer Investment, Computer Networks and Productivity," Working Papers 05-01, Center for Economic Studies, U.S. Census Bureau.
    12. Jensen, J Bradford & McGuckin, Robert H, 1997. "Firm Performance and Evolution: Empirical Regularities in the US Microdata," Industrial and Corporate Change, Oxford University Press, vol. 6(1), pages 25-47.
    13. Nathan Musick, 1998. "Heroic Plants: Persistently Rapid Job Creators in the Longitudinal Research Database - Their Distinguishing Characteristics and Contribution to Employment Growth," Industrial Organization 9811001, EconWPA.
    14. B. Atrostic, 2008. "Measuring U.S. innovative activity: business data at the U.S. Census Bureau," The Journal of Technology Transfer, Springer, vol. 33(2), pages 153-171, April.
    15. Markus Poschke & Alain Gabler, 2011. "Growth through Experimentation," 2011 Meeting Papers 643, Society for Economic Dynamics.
    16. B.K. Atrostic & John Gates, 2001. "U.S. Productivity and Electronic Processes in Manufacturing," Working Papers 01-11, Center for Economic Studies, U.S. Census Bureau.
    17. David N. Beede & Kan H. Young, 1996. "Patterns of Advanced Technology Adoption and Manufacturing Performance: Employment Growth, Labor Productivity, and Employee Earnings," Development and Comp Systems 9604001, EconWPA.
    18. B.K. Atrostic & Kazuyuki Motohashi & Sang Nguyen, 2008. "Computer Network Use and Firms' Productivity Performance: The United States vs. Japan," Working Papers 08-30, Center for Economic Studies, U.S. Census Bureau.
    19. Hans-Günther Vieweg & Thomas Fuchs & Reinhard Hild & Andreas Kuhlmann & Stefan Lachenmaier & Michael Reinhard & Uwe Christian Täger & Sebastian de Ramon & Jan-Egbert Sturm, 2005. "Stand und Perspektiven der "New Economy" in ausgewählten Mitgliedstaaten der EU aus deutscher Sicht," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 19.
    20. Baldwin, John R. & Sabourin, David, 2004. "The Effect of Changing Technology Use on Plant Performance in the Canadian Manufacturing Sector," Economic Analysis (EA) Research Paper Series 2004020e, Statistics Canada, Analytical Studies Branch.

    More about this item

    Keywords

    technology; productivity; JEL Classification: L1; L6; D92;

    JEL classification:

    • L1 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance
    • L - Industrial Organization

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