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A heterogeneous coefficient approach to the knowledge production function

Author

Listed:
  • Corinne Autant-Bernard

    (GATE Lyon Saint-Étienne - Groupe d'Analyse et de Théorie Economique Lyon - Saint-Etienne - ENS de Lyon - École normale supérieure de Lyon - Université de Lyon - UL2 - Université Lumière - Lyon 2 - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon - UJM - Université Jean Monnet - Saint-Étienne - CNRS - Centre National de la Recherche Scientifique)

  • James P. Lesage

    (Texas State University)

Abstract

Past literature has used conventional spatial autoregressive panel data models to relate patent production output to knowledge production inputs. However, research conducted on regional innovation systems points to regional disparities in both regions’ ability to turn their knowledge inputs into innovation and to access external knowledge. Applying a heterogeneous coefficients spatial autoregressive panel model, we estimate region-specific knowledge production functions (KPFs) for 94 NUTS-3 regions in France using a panel covering 21 years from 1988 to 2008 and four high-technology industries. A great deal of regional heterogeneity in the KPF relationship exists across regions, providing new insights regarding spatial spillin and spillout effects between regions.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Corinne Autant-Bernard & James P. Lesage, 2017. "A heterogeneous coefficient approach to the knowledge production function," Post-Print halshs-01661087, HAL.
    • Handle: RePEc:hal:journl:halshs-01661087
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    Cited by:

    1. Keisuke Kondo, 2022. "Spatial dependence in regional business cycles: evidence from Mexican states," Journal of Spatial Econometrics, Springer, vol. 3(1), pages 1-46, December.
    2. Sarah Ferreira & Renato Garcia & Veneziano Araujo, 2025. "Similarities and differences in regional determinants of university and industry patents: an analysis of Brazil from 2003 to 2018," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 74(1), pages 1-38, March.
    3. Alberto Gude & Inmaculada Álvarez & Luis Orea, 2018. "Heterogeneous spillovers among Spanish provinces: a generalized spatial stochastic frontier model," Journal of Productivity Analysis, Springer, vol. 50(3), pages 155-173, December.
    4. LeSage, James P. & Chih, Yao-Yu, 2018. "A Bayesian spatial panel model with heterogeneous coefficients," Regional Science and Urban Economics, Elsevier, vol. 72(C), pages 58-73.

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    Keywords

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    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • O52 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Europe
    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)

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