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Knowledge Migration: A Cross-National Analysis

Author

Listed:
  • Luigi Aldieri

    (University of Naples Parthenope)

  • Concetto Paolo Vinci

    (University of Salerno)

Abstract

This study contributes to existing literature on the innovative activity of firms, examining how migration can be a channel for knowledge spillover. Indeed, the aim of the paper is to introduce a new variable, which is computed on the basis of the distribution of inventors across countries, according to patent data. The paper consists of a theoretical model and an empirical analysis, which is a cross-national analysis of the United States, Japan and Europe, based upon a new dataset of worldwide R&D-intensive manufacturing firms. We use data from all EU R&D investment scoreboard editions, which were issued every year from 2002 to 2010 by the JRC-IPTS. The empirical results suggest that the migration of inventors might enhance local innovation levels, by confirming the theoretical analysis propositions.

Suggested Citation

  • Luigi Aldieri & Concetto Paolo Vinci, 2016. "Knowledge Migration: A Cross-National Analysis," De Economist, Springer, vol. 164(2), pages 109-123, June.
    • Handle: RePEc:kap:decono:v:164:y:2016:i:2:d:10.1007_s10645-015-9269-5
    DOI: 10.1007/s10645-015-9269-5
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    References listed on IDEAS

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    Cited by:

    1. L. Aldieri & C. P. Vinci, 2018. "Innovation effects on employment in high-tech and low-tech industries: evidence from large international firms within the triad," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 8(2), pages 229-243, June.
    2. Luigi Aldieri & Concetto Paolo Vinci, 2017. "Quantile Regression for Panel Data: An Empirical Approach for Knowledge Spillovers Endogeneity," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 9(7), pages 106-113, July.
    3. Caviggioli, Federico & Jensen, Paul & Scellato, Giuseppe, 2020. "Highly skilled migrants and technological diversification in the US and Europe," Technological Forecasting and Social Change, Elsevier, vol. 154(C).

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    More about this item

    Keywords

    Knowledge spillovers; Innovation; Cross-national analysis;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • O4 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity

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