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Global economy dynamics? Panel data approach to spillover effects

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  • Daco, Gregory
  • Hernandez Martinez, Fernando
  • Hsu, Li-Wu

Abstract

Over the past year, there has been considerable debate about how the slowing of the United States and other major developed economies affects output growth across the world. The main purpose of this paper is to establish relevant conclusions on how the U.S., Euro Area and Japan gross domestic product growth affect international business cycle fluctuations, with the objective of identifying the main factors that influence spillovers into other countries. Using panel data regression, we conclude that output growth in the U.S. and Euro area are significant in explaining output growth across countries. Depending on the specifications, trade linkages play a significant role while financial linkages with respect to the three regions does not (except in one particular specification). There are signs of potential omitted variable bias in some regression indicating that some relevant variables have not been taken into account. There is also clear evidence of a structural change in the transmission mechanism of shocks after 1985 – since when shocks have become more country-specific.

Suggested Citation

  • Daco, Gregory & Hernandez Martinez, Fernando & Hsu, Li-Wu, 2009. "Global economy dynamics? Panel data approach to spillover effects," MPRA Paper 18043, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:18043
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    File URL: https://mpra.ub.uni-muenchen.de/18043/1/MPRA_paper_18043.pdf
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    References listed on IDEAS

    as
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    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Output Growth; Trade and Financial Linkages; Structural Break; Cross- Section Panel Data.;
    All these keywords.

    JEL classification:

    • F40 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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