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Industry Localization, Distance Decay, and Knowledge Spillovers: Following the Patent Paper Trail

Author

Listed:
  • Octávio Figueiredo

    (Universidade do Porto)

  • Paulo Guimarães

    (American University of Sharjah)

  • Douglas Woodward

    (University of South Carolina)

Abstract

This paper investigates the hypothesis that knowledge spillovers increase where industries are localized. At the same time, we take a fresh look at the role of distance in knowledge diffusion. Our unique database combines U.S. county-level patent citation data with county-level establishment and employment data. Relying on a cited-citing gravity equation with high-dimensional fixed effects that control for multiple sources of observed and non-observed heterogeneity, we implement a Poisson pseudo-maximum-likelihood estimator. Our results confirm the negative role of distance uncovered in Jaffe, Trajtenberg & Henderson's (1993) pioneering work. We also find that knowledge spillovers correlate positively with industry localization and that the agglomeration of an industry can offset the effect of distance. Our approach to estimate the Poisson regression with two high-dimensional fixed effects may prove equally useful in applications to a variety of other problems in economics.

Suggested Citation

  • Octávio Figueiredo & Paulo Guimarães & Douglas Woodward, 2014. "Industry Localization, Distance Decay, and Knowledge Spillovers: Following the Patent Paper Trail," FEP Working Papers 521, Universidade do Porto, Faculdade de Economia do Porto.
    • Handle: RePEc:por:fepwps:521
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    JEL classification:

    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)
    • R39 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Other
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

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