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Modelling the joint impact of R and D and ICT on productivity: A frontier analysis approach

Author

Listed:
  • Fabio Pieri

    ()

  • Michela Vecchi
  • Francesco Venturini

    ()

Abstract

This study explores the channels through which technological investments affect productivity performance of industrialized economies. Using a Stochastic Frontier Model (SFM) we estimate the productivity effects of R\D and ICT for a large sample of OECD industries between 1973 and 2007, identifying four channels of transmission: input accumulation, technological change, technical efficiency and spillovers. Our results show that ICT has been particularly effective in reducing production inefficiency and in generating inter-industry spillovers, while R\D has raised the rate of technical change and favoured knowledge spillovers within sectors. We also quantify the contribution of technological investments to output and TFP growth documenting that R\D and ICT accounted for almost 95% of TFP growth in the OECD area.

Suggested Citation

  • Fabio Pieri & Michela Vecchi & Francesco Venturini, 2017. "Modelling the joint impact of R and D and ICT on productivity: A frontier analysis approach," DEM Working Papers 2017/13, Department of Economics and Management.
  • Handle: RePEc:trn:utwprg:2017/13
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    1. Markus Eberhardt & Christian Helmers & Hubert Strauss, 2013. "Do Spillovers Matter When Estimating Private Returns to R&D?," The Review of Economics and Statistics, MIT Press, vol. 95(2), pages 436-448, May.
    2. Jakob Madsen, 2008. "Semi-endogenous versus Schumpeterian growth models: testing the knowledge production function using international data," Journal of Economic Growth, Springer, vol. 13(1), pages 1-26, March.
    3. Cette, Gilbert & Fernald, John & Mojon, Benoît, 2016. "The pre-Great Recession slowdown in productivity," European Economic Review, Elsevier, vol. 88(C), pages 3-20.
    4. Michael Webb & John Van Reenen & Charles Jones & Nicholas Bloom, 2017. "Are Ideas Getting Harder to Find?," 2017 Meeting Papers 566, Society for Economic Dynamics.
    5. M. Hashem Pesaran, 2006. "Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure," Econometrica, Econometric Society, vol. 74(4), pages 967-1012, July.
    6. Harald Badinger & Peter Egger, 2016. "Productivity Spillovers Across Countries and Industries: New Evidence From OECD Countries," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(4), pages 501-521, August.
    7. Rachel Griffith & Stephen Redding & John Van Reenen, 2004. "Mapping the Two Faces of R&D: Productivity Growth in a Panel of OECD Industries," The Review of Economics and Statistics, MIT Press, vol. 86(4), pages 883-895, November.
    8. Nicholas Bloom & Mark Schankerman & John Van Reenen, 2013. "Identifying Technology Spillovers and Product Market Rivalry," Econometrica, Econometric Society, vol. 81(4), pages 1347-1393, July.
    9. Zvi Griliches, 1998. "Issues in Assessing the Contribution of Research and Development to Productivity Growth," NBER Chapters,in: R&D and Productivity: The Econometric Evidence, pages 17-45 National Bureau of Economic Research, Inc.
    10. repec:eee:ecolet:v:156:y:2017:i:c:p:92-94 is not listed on IDEAS
    11. Haskel, Jonathan & Wallis, Gavin, 2013. "Public support for innovation, intangible investment and productivity growth in the UK market sector," Economics Letters, Elsevier, vol. 119(2), pages 195-198.
    12. repec:bla:revinw:v:63:y:2017:i::p:s49-s67 is not listed on IDEAS
    13. Caudill, Steven B. & Ford, Jon M., 1993. "Biases in frontier estimation due to heteroscedasticity," Economics Letters, Elsevier, vol. 41(1), pages 17-20.
    14. 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.
    15. Samaniego, Roberto M., 2007. "R D And Growth: The Missing Link?," Macroeconomic Dynamics, Cambridge University Press, vol. 11(05), pages 691-714, November.
    16. Marcel P. Timmer & Bart van Ark, 2005. "Does information and communication technology drive EU-US productivity growth differentials?," Oxford Economic Papers, Oxford University Press, vol. 57(4), pages 693-716, October.
    17. Robert J. Gordon, 2016. "Perspectives on The Rise and Fall of American Growth," American Economic Review, American Economic Association, vol. 106(5), pages 72-76, May.
    18. Henry, Michael & Kneller, Richard & Milner, Chris, 2009. "Trade, technology transfer and national efficiency in developing countries," European Economic Review, Elsevier, vol. 53(2), pages 237-254, February.
    19. Venturini Francesco, 2007. "ICT and Productivity Resurgence: A Growth Model for the Information Age," The B.E. Journal of Macroeconomics, De Gruyter, vol. 7(1), pages 1-26, August.
    20. Kevin J. Fox & Thomas Niebel & Mary O'Mahony & Marianne Saam, 2017. "The Contribution of Intangible Assets to Sectoral Productivity Growth in the EU," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 63, pages 49-67, February.
    21. Mary O'Mahony & Michela Vecchi, 2005. "Quantifying the Impact of ICT Capital on Output Growth: A Heterogeneous Dynamic Panel Approach," Economica, London School of Economics and Political Science, vol. 72(288), pages 615-633, November.
    22. Mary O'Mahony & Marcel P. Timmer, 2009. "Output, Input and Productivity Measures at the Industry Level: The EU KLEMS Database," Economic Journal, Royal Economic Society, vol. 119(538), pages 374-403, June.
    23. Subodh Kumar & R. Robert Russell, 2002. "Technological Change, Technological Catch-up, and Capital Deepening: Relative Contributions to Growth and Convergence," American Economic Review, American Economic Association, vol. 92(3), pages 527-548, June.
    24. Bos, Jaap W.B. & Economidou, Claire & Sanders, Mark W.J.L., 2013. "Innovation over the industry life-cycle: Evidence from EU manufacturing," Journal of Economic Behavior & Organization, Elsevier, vol. 86(C), pages 78-91.
    25. Lipsey, Richard G. & Carlaw, Kenneth I. & Bekar, Clifford T., 2005. "Economic Transformations: General Purpose Technologies and Long-Term Economic Growth," OUP Catalogue, Oxford University Press, number 9780199290895.
    26. L. Becchetti & David Bedoya & L. Paganetto, 2003. "ICT Investment, Productivity and Efficiency: Evidence at Firm Level Using a Stochastic Frontier Approach," Journal of Productivity Analysis, Springer, vol. 20(2), pages 143-167, September.
    27. Hung-jen Wang & Peter Schmidt, 2002. "One-Step and Two-Step Estimation of the Effects of Exogenous Variables on Technical Efficiency Levels," Journal of Productivity Analysis, Springer, vol. 18(2), pages 129-144, September.
    28. Venturini, Francesco, 2012. "Looking into the black box of Schumpeterian growth theories: An empirical assessment of R&D races," European Economic Review, Elsevier, vol. 56(8), pages 1530-1545.
    29. Erik Brynjolfsson & Lorin M. Hitt, 2003. "Computing Productivity: Firm-Level Evidence," The Review of Economics and Statistics, MIT Press, vol. 85(4), pages 793-808, November.
    30. Griliches, Zvi, 1988. "Productivity Puzzles and R&D: Another Nonexplanation," Journal of Economic Perspectives, American Economic Association, vol. 2(4), pages 9-21, Fall.
    31. Chudik, Alexander & Fratzscher, Marcel, 2011. "Identifying the global transmission of the 2007-2009 financial crisis in a GVAR model," European Economic Review, Elsevier, vol. 55(3), pages 325-339, April.
    32. Ugur, Mehmet & Trushin, Eshref & Solomon, Edna & Guidi, Francesco, 2016. "R&D and productivity in OECD firms and industries: A hierarchical meta-regression analysis," Research Policy, Elsevier, vol. 45(10), pages 2069-2086.
    33. John W. Kendrick & Beatrice N. Vaccara, 1980. "New Developments in Productivity Measurement," NBER Books, National Bureau of Economic Research, Inc, number kend80-1, December.
    34. Robert Inklaar & Marcel P. Timmer & Bart van Ark, 2008. "Market services productivity across Europe and the US," Economic Policy, CEPR;CES;MSH, vol. 23, pages 139-194, January.
    35. Saeed Moshiri & Wayne Simpson, 2011. "Information technology and the changing workplace in Canada: firm-level evidence," Industrial and Corporate Change, Oxford University Press, vol. 20(6), pages 1601-1636, December.
    36. Chun, Hyunbae & Kim, Jung-Wook & Lee, Jason, 2015. "How does information technology improve aggregate productivity? A new channel of productivity dispersion and reallocation," Research Policy, Elsevier, vol. 44(5), pages 999-1016.
    37. 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.
    38. 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.
    39. John W. Kendrick & Beatrice N. Vaccara, 1980. "Introduction to "New Developments in Productivity Measurement"," NBER Chapters,in: New Developments in Productivity Measurement, pages 1-14 National Bureau of Economic Research, Inc.
    40. Camilla Mastromarco & Laura Serlenga & Yongcheol Shin, 2016. "Modelling Technical Efficiency in Cross Sectionally Dependent Stochastic Frontier Panels," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(1), pages 281-297, January.
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    Keywords

    Research and Development; Information and Communication Technology; Productivity; Stochastic frontier models;

    JEL classification:

    • O14 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Industrialization; Manufacturing and Service Industries; Choice of Technology
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence

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