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Globalisation and Technological Convergence in the EU

Author

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  • Camilla Mastromarco

    (Università di Bari)

  • Laura Serlenga

    (University of Bari and IZA)

  • Yongcheol Shin

    (University of York)

Abstract

We employ a two-step approach in investigating the dynamic transmission chan- nels under which globalization factors foster technical efficiency by combining a dynamic efficiency analysis in the stochastic frontier framework, and a time series approach based on VAR and spectral analysis. Using the dataset of the 18 EU countries over 1970-2004, we find that both import and FDI are significant factors in spreading efficiency externalities and thus accelerating technology catch-up in the EU. In particular, the impacts of the import are more prominent in the short-run while those of FDI play a more important role over the longer-run. Furthermore, the impacts of the import are pro-cyclical only in the short-run whereas those of FDI are pro-cyclical mostly over the medium- to the long-run. This evidence is broadly consistent with the sample observation that the recent slowdown of the EU productivity has been closely related to the corresponding FDI decline espe- cially after 2000. Hence, any protection-oriented policy will be likely to be more detrimental for the EU.

Suggested Citation

  • Camilla Mastromarco & Laura Serlenga & Yongcheol Shin, 2012. "Globalisation and Technological Convergence in the EU," SERIES 0041, Dipartimento di Economia e Finanza - Università degli Studi di Bari "Aldo Moro", revised Mar 2012.
  • Handle: RePEc:bai:series:economia-series41
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    1. Mastromarco, Camilla & Simar, Leopold, 2014. "Global Dependence and Productivity: A Robust Nonparametric World Frontier Analysis," LIDAM Discussion Papers ISBA 2014049, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    2. Fei Jin & Lung-fei Lee, 2020. "Asymptotic properties of a spatial autoregressive stochastic frontier model," Journal of Spatial Econometrics, Springer, vol. 1(1), pages 1-40, December.
    3. Humaira Raffat & Danish Ahmed Siddiqui, 2020. "Does Openness, and Productivity Matters for FDI: A Global Interactive Analysis Based on the Complementary Role of Institutions," Issues in Economics and Business, Macrothink Institute, vol. 6(2), pages 1-21, December.
    4. Bogdanov, Dmitrii & Toktarova, Alla & Breyer, Christian, 2019. "Transition towards 100% renewable power and heat supply for energy intensive economies and severe continental climate conditions: Case for Kazakhstan," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    5. Adam, Isabelle & Fazekas, Mihály, 2021. "Are emerging technologies helping win the fight against corruption? A review of the state of evidence," Information Economics and Policy, Elsevier, vol. 57(C).
    6. Sudeshna Ghosh Banerjee & Elisa Portale, 2014. "Tracking Access to Electricity," World Bank Publications - Reports 18413, The World Bank Group.
    7. Mastromarco, Camilla & Simar, Léopold, 2018. "Globalization and productivity: A robust nonparametric world frontier analysis," Economic Modelling, Elsevier, vol. 69(C), pages 134-149.
    8. Lee, Chi-Chuan & Huang, Tai-Hsin, 2017. "Cost efficiency and technological gap in Western European banks: A stochastic metafrontier analysis," International Review of Economics & Finance, Elsevier, vol. 48(C), pages 161-178.
    9. Emah Patrick Etokudoh & Mehraz Boolaky & Mridula Gungaphul, 2017. "Third Party Logistics Outsourcing: An Exploratory Study of the Oil and Gas Industry in Nigeria," SAGE Open, , vol. 7(4), pages 21582440177, October.
    10. Cem Ertur & Antonio Musolesi, 2017. "Weak and Strong Cross‐Sectional Dependence: A Panel Data Analysis of International Technology Diffusion," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(3), pages 477-503, April.
    11. Beyaert, Arielle & García-Solanes, José & Lopez-Gomez, Laura, 2019. "Do institutions of the euro area converge?," Economic Systems, Elsevier, vol. 43(3).
    12. Orea, Luis & Álvarez, Inmaculada C., 2019. "A new stochastic frontier model with cross-sectional effects in both noise and inefficiency terms," Journal of Econometrics, Elsevier, vol. 213(2), pages 556-577.
    13. Cern Ertur & Antonio Musolesi, 2012. "Spatial autoregressive spillovers vs unobserved common factors models. A panel data analysis of international technology diffusion," INRA UMR CESAER Working Papers 2012/9, INRA UMR CESAER, Centre d'’Economie et Sociologie appliquées à l'’Agriculture et aux Espaces Ruraux.
    14. Ramani, Shyama V. & Urias, Eduardo, 2018. "When access to drugs meets catch-up: Insights from the use of CL threats to improve access to ARV drugs in Brazil," Research Policy, Elsevier, vol. 47(8), pages 1538-1552.
    15. Cem Ertur & Antonio Musolesi, 2014. "Dépendance individuelle forte et faible : une analyse en données de panel de la diffusion internationale de la technologie," Working Papers halshs-01015208, HAL.
    16. Efthymios G. Tsionas & Panayotis G. Michaelides, 2016. "A Spatial Stochastic Frontier Model with Spillovers: Evidence for Italian Regions," Scottish Journal of Political Economy, Scottish Economic Society, vol. 63(3), pages 243-257, July.
    17. Camilla Mastromarco & Laura Serlenga & Yongcheol Shin, 2012. "Is Globalization Driving Efficiency? A Threshold Stochastic Frontier Panel Data Modeling Approach," Review of International Economics, Wiley Blackwell, vol. 20(3), pages 563-579, August.

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    More about this item

    Keywords

    Stochastic Frontier in Heterogeneous Panels; Time-Varying Efficiency; Globalisation Factors; Unobserved Factors; Spectral and Impulse Response Analyses;
    All these keywords.

    JEL classification:

    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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