IDEAS home Printed from https://ideas.repec.org/p/wiw/wiwrsa/ersa05p641.html
   My bibliography  Save this paper

Technological change and industry competitiveness through the evolution of localised comparative advantages - The case of Italy

Author

Listed:
  • Daniela Palma
  • Alessandro Zini

Abstract

The influence of technological change on industry performances is nowadays being increasingly investigated under the broad category of "national systemic competitiveness". Moreover theoretical works have shown that the relationship between technology and economic performance not only takes different forms in different socio-economic contexts, but is also powerfully influenced by the way that innovation processes evolve over time along strongly localised patterns. The present study is focused on the evolution of trade competitiveness of the manufacturing sector in Italy over the past ten years and addresses to the role played by localised comparative advantages in shaping the model of national competitiveness. The data used in the analysis, drawn by the Enea Observatory on high tech industries, are based on trade statistics at the SITC five digit level and are spatially referenced to the Italy NUT3 regional partition. The effects of localised trade specialisation on manufacturing competitiveness are first assessed through spatial econometric tecniques. Spatial variation in the relationships found is further explored in order to give additional hints on the specific contribution of localised comparative advantages. According to major trends which have recently characterised manufacturing trade competitiveness in Italy, the analysis is expected to bring into evidence significant changes in the contribution of industrial localities to national competitiveness.

Suggested Citation

  • Daniela Palma & Alessandro Zini, 2005. "Technological change and industry competitiveness through the evolution of localised comparative advantages - The case of Italy," ERSA conference papers ersa05p641, European Regional Science Association.
  • Handle: RePEc:wiw:wiwrsa:ersa05p641
    as

    Download full text from publisher

    File URL: https://www-sre.wu.ac.at/ersa/ersaconfs/ersa05/papers/641.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Audretsch, David B & Feldman, Maryann P, 1996. "R&D Spillovers and the Geography of Innovation and Production," American Economic Review, American Economic Association, vol. 86(3), pages 630-640, June.
    2. Barnett,William A. & Powell,James & Tauchen,George E. (ed.), 1991. "Nonparametric and Semiparametric Methods in Econometrics and Statistics," Cambridge Books, Cambridge University Press, number 9780521370905.
    3. Barnett,William A. & Powell,James & Tauchen,George E. (ed.), 1991. "Nonparametric and Semiparametric Methods in Econometrics and Statistics," Cambridge Books, Cambridge University Press, number 9780521424318.
    4. Stefano Breschi & Daniela Palma, 1999. "Localised Knowledge Spillovers and Trade Competitiveness: The Case of Italy," Advances in Spatial Science, in: Manfred M. Fischer & Luis Suarez-Villa & Michael Steiner (ed.), Innovation, Networks and Localities, chapter 8, pages 155-180, Springer.
    5. Jan Fagerberg & Paolo Guerrieri & Bart Verspagen (ed.), 1999. "The Economic Challenge for Europe," Books, Edward Elgar Publishing, number 1821.
    6. Fredrik Sjöholm, 1996. "International transfer of knowledge: The role of international trade and geographic proximity," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 132(1), pages 97-115, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Daria Ciriaci & Daniela Palma, 2008. "The role of knowledge‐based supply specialisation for competitiveness: A spatial econometric approach," Papers in Regional Science, Wiley Blackwell, vol. 87(3), pages 453-475, August.
    2. Victor Aguirregabiria, 2006. "Another Look at the Identification of Dynamic Discrete Decision Processes: With an Application to Retirement Behavior," 2006 Meeting Papers 169, Society for Economic Dynamics.
    3. Lanot, Gauthier & Walker, Ian, 1998. "The union/non-union wage differential: An application of semi-parametric methods," Journal of Econometrics, Elsevier, vol. 84(2), pages 327-349, June.
    4. P. Kearns & A.R. Pagan, 1993. "Australian Stock Market Volatility: 1875–1987," The Economic Record, The Economic Society of Australia, vol. 69(2), pages 163-178, June.
    5. Victor Chernozhukov & Iván Fernández‐Val & Blaise Melly, 2013. "Inference on Counterfactual Distributions," Econometrica, Econometric Society, vol. 81(6), pages 2205-2268, November.
    6. SCHAFGANS, Marcia M.A. & ZINDE-WALSH, Victoria, 2007. "Robust Average Derivative Estimation," Cahiers de recherche 12-2007, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    7. Hartwig, Benny & Meinerding, Christoph & Schüler, Yves S., 2021. "Identifying indicators of systemic risk," Journal of International Economics, Elsevier, vol. 132(C).
    8. Charlier, Erwin & Melenberg, Bertrand & van Soest, Arthur, 2000. "Estimation of a censored regression panel data model using conditional moment restrictions efficiently," Journal of Econometrics, Elsevier, vol. 95(1), pages 25-56, March.
    9. Yingcun Xia & Wolfgang Härdle & Oliver Linton, 2009. "Optimal Smoothing for a Computationally and Statistically Efficient Single Index Estimator," SFB 649 Discussion Papers SFB649DP2009-028, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    10. George J. Jiang & Pieter J. van der Sluis, 1999. "Index Option Pricing Models with Stochastic Volatility and Stochastic Interest Rates," Review of Finance, European Finance Association, vol. 3(3), pages 273-310.
    11. McMillen, Daniel P., 2001. "Nonparametric Employment Subcenter Identification," Journal of Urban Economics, Elsevier, vol. 50(3), pages 448-473, November.
    12. Alexander Chudik & George Kapetanios & M. Hashem Pesaran, 2016. "Big Data Analytics: A New Perspective," CESifo Working Paper Series 5824, CESifo.
    13. Weichi Wu & Zhou Zhou, 2017. "Nonparametric Inference for Time-Varying Coefficient Quantile Regression," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(1), pages 98-109, January.
    14. Bas Donkers & Marcia M Schafgans, 2005. "A method of moments estimator for semiparametric index models," STICERD - Econometrics Paper Series 493, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    15. Robinson, P.M. & Iacone, F., 2005. "Cointegration in fractional systems with deterministic trends," Journal of Econometrics, Elsevier, vol. 129(1-2), pages 263-298.
    16. Nicolas Berman & Vincent Rebeyrol & Vincent Vicard, 2019. "Demand Learning and Firm Dynamics: Evidence from Exporters," The Review of Economics and Statistics, MIT Press, vol. 101(1), pages 91-106, March.
    17. William A. Barnett & Melvin J. Hinich & Piyu Yue, 2011. "The Exact Theoretical Rational Expectations Monetary Aggregate," World Scientific Book Chapters, in: Financial Aggregation And Index Number Theory, chapter 2, pages 53-84, World Scientific Publishing Co. Pte. Ltd..
    18. White, Halbert & Hong, Yongmiao, 1999. "M-Testing Using Finite and Infinite Dimensional Parameter Estimators," University of California at San Diego, Economics Working Paper Series qt9qz123ng, Department of Economics, UC San Diego.
    19. Stavros Degiannakis & Alexandra Livada & Epaminondas Panas, 2008. "Rolling-sampled parameters of ARCH and Levy-stable models," Applied Economics, Taylor & Francis Journals, vol. 40(23), pages 3051-3067.
    20. Chen, Songxi, 2012. "Estimation in semiparametric models with missing data," MPRA Paper 46216, University Library of Munich, Germany.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wiw:wiwrsa:ersa05p641. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Gunther Maier (email available below). General contact details of provider: http://www.ersa.org .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.