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Technological improvement rate estimates for all technologies: Use of patent data and an extended domain description

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  • Anuraag Singh
  • Giorgio Triulzi
  • Christopher L. Magee

Abstract

In this work, we attempt to provide a comprehensive granular account of the pace of technological change. More specifically, we survey estimated yearly performance improvement rates for nearly all definable technologies for the first time. We do this by creating a correspondence of all patents within the US patent system to a set of technology domains. A technology domain is a body of patented inventions achieving the same technological function using the same knowledge and scientific principles. We obtain a set of 1757 domains using an extension of the previously defined classification overlap method (COM). These domains contain 97.14% of all patents within the entire US patent system. From the identified patent sets, we calculated the average centrality of the patents in each domain to estimate their improvement rates, following a methodology tested in prior work. The estimated improvement rates vary from a low of 1.9% per year for the Mechanical Skin treatment - Hair Removal and wrinkles domain to a high of 228.8% per year for the Network management - client-server applications domain. We developed a one-line descriptor identifying the technological function achieved and the underlying knowledge base for the largest 50, fastest 20 as well as slowest 20 of these domains, which cover more than forty percent of the patent system. In general, the rates of improvement were not a strong function of the patent set size and the fastest improving domains are predominantly software-based. We make available an online system that allows for automated searching for domains and improvement rates corresponding to any technology of interest to researchers, strategists and policy formulators.

Suggested Citation

  • Anuraag Singh & Giorgio Triulzi & Christopher L. Magee, 2020. "Technological improvement rate estimates for all technologies: Use of patent data and an extended domain description," Papers 2004.13919, arXiv.org.
  • Handle: RePEc:arx:papers:2004.13919
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    1. Alessandro Nuvolari, 2004. "Collective invention during the British Industrial Revolution: the case of the Cornish pumping engine," Cambridge Journal of Economics, Cambridge Political Economy Society, vol. 28(3), pages 347-363, May.
    2. Nicholas Bloom & Charles I. Jones & John Van Reenen & Michael Webb, 2020. "Are Ideas Getting Harder to Find?," American Economic Review, American Economic Association, vol. 110(4), pages 1104-1144, April.
    3. Ruttan, Vernon W., 2000. "Technology, Growth, and Development: An Induced Innovation Perspective," OUP Catalogue, Oxford University Press, number 9780195118711.
    4. Bronwyn H. Hall & Zvi Griliches & Jerry A. Hausman, 1984. "Patents and R&D: Is There A Lag?," NBER Working Papers 1454, National Bureau of Economic Research, Inc.
    5. Fagerberg, Jan, 2000. "Technological progress, structural change and productivity growth: a comparative study," Structural Change and Economic Dynamics, Elsevier, vol. 11(4), pages 393-411, December.
    6. Bart Verspagen, 2007. "Mapping Technological Trajectories As Patent Citation Networks: A Study On The History Of Fuel Cell Research," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 10(01), pages 93-115.
    7. Richard Nelson, 1962. "The Link Between Science and Invention: The Case of the Transistor," NBER Chapters, in: The Rate and Direction of Inventive Activity: Economic and Social Factors, pages 549-584, National Bureau of Economic Research, Inc.
    8. Bronwyn H. Hall & Adam B. Jaffe & Manuel Trajtenberg, 2001. "The NBER Patent Citation Data File: Lessons, Insights and Methodological Tools," NBER Working Papers 8498, National Bureau of Economic Research, Inc.
    9. Farmer, J. Doyne & Lafond, François, 2016. "How predictable is technological progress?," Research Policy, Elsevier, vol. 45(3), pages 647-665.
    10. Henderson, Rebecca, 1995. "Of life cycles real and imaginary: The unexpectedly long old age of optical lithography," Research Policy, Elsevier, vol. 24(4), pages 631-643, July.
    11. Ayres, Robert U., 1994. "Toward a non-linear dynamics of technological progress," Journal of Economic Behavior & Organization, Elsevier, vol. 24(1), pages 35-69, June.
    12. David H. Autor, 2019. "Work of the Past, Work of the Future," AEA Papers and Proceedings, American Economic Association, vol. 109, pages 1-32, May.
    13. Béla Nagy & J Doyne Farmer & Quan M Bui & Jessika E Trancik, 2013. "Statistical Basis for Predicting Technological Progress," PLOS ONE, Public Library of Science, vol. 8(2), pages 1-7, February.
    14. Sagar, Ambuj D. & van der Zwaan, Bob, 2006. "Technological innovation in the energy sector: R&D, deployment, and learning-by-doing," Energy Policy, Elsevier, vol. 34(17), pages 2601-2608, November.
    15. Daron Acemoglu & James Robinson, 2010. "The Role of Institutions in Growth and Development," Review of Economics and Institutions, Università di Perugia, vol. 1(2).
    16. Way, Rupert & Lafond, François & Lillo, Fabrizio & Panchenko, Valentyn & Farmer, J. Doyne, 2019. "Wright meets Markowitz: How standard portfolio theory changes when assets are technologies following experience curves," Journal of Economic Dynamics and Control, Elsevier, vol. 101(C), pages 211-238.
    17. Funk, Jeffrey L. & Magee, Christopher L., 2015. "Rapid improvements with no commercial production: How do the improvements occur?," Research Policy, Elsevier, vol. 44(3), pages 777-788.
    18. Fagerberg, Jan, 1994. "Technology and International Differences in Growth Rates," Journal of Economic Literature, American Economic Association, vol. 32(3), pages 1147-1175, September.
    19. Magee, C.L. & Basnet, S. & Funk, J.L. & Benson, C.L., 2016. "Quantitative empirical trends in technical performance," Technological Forecasting and Social Change, Elsevier, vol. 104(C), pages 237-246.
    20. Robert J. Gordon, 2012. "Is U.S. Economic Growth Over? Faltering Innovation Confronts the Six Headwinds," NBER Working Papers 18315, National Bureau of Economic Research, Inc.
    21. Dosi, Giovanni, 1993. "Technological paradigms and technological trajectories : A suggested interpretation of the determinants and directions of technical change," Research Policy, Elsevier, vol. 22(2), pages 102-103, April.
    22. Robert J. Gordon, 2000. "Does the "New Economy" Measure Up to the Great Inventions of the Past?," Journal of Economic Perspectives, American Economic Association, vol. 14(4), pages 49-74, Fall.
    23. William D. Nordhaus, 2014. "The Perils of the Learning Model for Modeling Endogenous Technological Change," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
    24. Nordhaus, William D., 2007. "Two Centuries of Productivity Growth in Computing," The Journal of Economic History, Cambridge University Press, vol. 67(1), pages 128-159, March.
    25. Lafond, François & Greenwald, Diana & Farmer, J. Doyne, 2022. "Can Stimulating Demand Drive Costs Down? World War II as a Natural Experiment," The Journal of Economic History, Cambridge University Press, vol. 82(3), pages 727-764, September.
    26. Koen Frenken & Alessandro Nuvolari, 2004. "The early development of the steam engine: an evolutionary interpretation using complexity theory," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 13(2), pages 419-450, April.
    27. Arthur, W. Brian, 2007. "The structure of invention," Research Policy, Elsevier, vol. 36(2), pages 274-287, March.
    28. Roberto Fontana & Alessandro Nuvolari & Hiroshi Shimizu & Andrea Vezzulli, 2013. "Schumpeterian Patterns of Innovation and the Sources of Breakthrough Inventions: Evidence from a Data-set of R&D Awards," Economic Complexity and Evolution, in: Andreas Pyka & Esben Sloth Andersen (ed.), Long Term Economic Development, edition 127, pages 313-340, Springer.
    29. Timothy F. Bresnahan & Robert J. Gordon, 1996. "The Economics of New Goods," NBER Books, National Bureau of Economic Research, Inc, number bres96-1, May.
    30. Erik Brynjolfsson & Tom Mitchell & Daniel Rock, 2018. "What Can Machines Learn, and What Does It Mean for Occupations and the Economy?," AEA Papers and Proceedings, American Economic Association, vol. 108, pages 43-47, May.
    31. Argote, L. & Epple, D., 1990. "Learning Curves In Manufacturing," GSIA Working Papers 89-90-02, Carnegie Mellon University, Tepper School of Business.
    32. Jinyoung Kim & Gerald Marschke, 2004. "Accounting for the recent surge in U.S. patenting: changes in R&D expenditures, patent yields, and the high tech sector," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 13(6), pages 543-558.
    33. Frey, Carl Benedikt & Osborne, Michael A., 2017. "The future of employment: How susceptible are jobs to computerisation?," Technological Forecasting and Social Change, Elsevier, vol. 114(C), pages 254-280.
    34. Bart Verspagen, 1997. "Measuring Intersectoral Technology Spillovers: Estimates from the European and US Patent Office Databases," Economic Systems Research, Taylor & Francis Journals, vol. 9(1), pages 47-65.
    35. Rosenberg,Nathan, 1983. "Inside the Black Box," Cambridge Books, Cambridge University Press, number 9780521273671.
    36. Utterback, James M & Abernathy, William J, 1975. "A dynamic model of process and product innovation," Omega, Elsevier, vol. 3(6), pages 639-656, December.
    37. Triulzi, Giorgio & Alstott, Jeff & Magee, Christopher L., 2020. "Estimating technology performance improvement rates by mining patent data," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
    38. Koen Frenken, 2006. "Technological innovation and complexity theory," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 15(2), pages 137-155.
    39. Czarnitzki, Dirk & Hussinger, Katrin, 2004. "The Link Between R&D Subsidies, R&D Spending and Technological Performance," ZEW Discussion Papers 04-56, ZEW - Leibniz Centre for European Economic Research.
    40. Donghyun You & Hyunseok Park, 2018. "Developmental Trajectories in Electrical Steel Technology Using Patent Information," Sustainability, MDPI, vol. 10(8), pages 1-15, August.
    41. Gavin Sinclair & Steven Klepper & Wesley Cohen, 2000. "What's Experience Got to Do With It? Sources of Cost Reduction in a Large Specialty Chemicals Producer," Management Science, INFORMS, vol. 46(1), pages 28-45, January.
    42. Fleming, Lee & Sorenson, Olav, 2001. "Technology as a complex adaptive system: evidence from patent data," Research Policy, Elsevier, vol. 30(7), pages 1019-1039, August.
    43. Bergek, Anna & Jacobsson, Staffan & Carlsson, Bo & Lindmark, Sven & Rickne, Annika, 2008. "Analyzing the functional dynamics of technological innovation systems: A scheme of analysis," Research Policy, Elsevier, vol. 37(3), pages 407-429, April.
    44. Schilling, Melissa A. & Esmundo, Melissa, 2009. "Technology S-curves in renewable energy alternatives: Analysis and implications for industry and government," Energy Policy, Elsevier, vol. 37(5), pages 1767-1781, May.
    45. Hoisl, Karin & Stelzer, Tobias & Biala, Stefanie, 2015. "Forecasting technological discontinuities in the ICT industry," Research Policy, Elsevier, vol. 44(2), pages 522-532.
    46. R. J. Gordon., 2013. "Is U.S. Economic Growth Over? Faltering Innovation Confronts the Six Headwinds," VOPROSY ECONOMIKI, N.P. Redaktsiya zhurnala "Voprosy Economiki", vol. 4.
    47. Lee Fleming, 2001. "Recombinant Uncertainty in Technological Search," Management Science, INFORMS, vol. 47(1), pages 117-132, January.
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