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Testing R&D-Based Endogenous Growth Models

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  • Peter K. Kruse-Andersen

    (Department of Economics, University of Copenhagen)

Abstract

R&D-based growth models are tested using US data for the period 1953-2014. A general growth model is developed which nests the model varieties of interest. The model implies a cointegrating relationship between multifactor productivity, research intensity, and employment. This relationship is estimated using cointegrated VAR models. The results provide evidence against the widely used fully endogenous variety and in favor of the semi-endogenous variety. Forecasts based on the empirical estimates suggest that the slowdown in US productivity growth will continue. Particularly, the annual long-run growth rate of GDP per worker converges to between zero and 1.1 pct.

Suggested Citation

  • Peter K. Kruse-Andersen, 2017. "Testing R&D-Based Endogenous Growth Models," Discussion Papers 17-05, University of Copenhagen. Department of Economics.
    • Handle: RePEc:kud:kuiedp:1705
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    References listed on IDEAS

    as
    1. Venturini, Francesco, 2012. "Product variety, product quality, and evidence of endogenous growth," Economics Letters, Elsevier, vol. 117(1), pages 74-77.
    2. Segerstrom, Paul S, 1998. "Endogenous Growth without Scale Effects," American Economic Review, American Economic Association, vol. 88(5), pages 1290-1310, December.
    3. Paul M. Romer, 1994. "The Origins of Endogenous Growth," Journal of Economic Perspectives, American Economic Association, vol. 8(1), pages 3-22, Winter.
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    Cited by:

    1. Growiec, Jakub, 2022. "R&D capital: An engine of growth," Economics Letters, Elsevier, vol. 217(C).
    2. Gerlagh, Reyer, 2022. "Climate, Technology, Family Size; on the Crossroad between Two Ultimate Externalities," Other publications TiSEM b6d5b02f-4624-46fd-836a-b, Tilburg University, School of Economics and Management.
    3. Gerlagh, Reyer, 2023. "Climate, technology, family size; on the crossroad between two ultimate externalities," European Economic Review, Elsevier, vol. 152(C).
    4. Jakub Growiec, 2019. "The Hardware–Software Model: A New Conceptual Framework of Production, R&D, and Growth with AI," Working Paper series 19-18, Rimini Centre for Economic Analysis.
    5. Gerlagh, Reyer, 2022. "Climate, Technology, Family Size; on the Crossroad between Two Ultimate Externalities," Discussion Paper 2022-027, Tilburg University, Center for Economic Research.
    6. Jakub Growiec, 2018. "The Digital Era, Viewed From a Perspective of Millennia of Economic Growth," KAE Working Papers 2018-034, Warsaw School of Economics, Collegium of Economic Analysis.

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    More about this item

    Keywords

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    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • O41 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - One, Two, and Multisector Growth Models
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence
    • O51 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - U.S.; Canada

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