Globalisation and Technological Convergence in the EU

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.

[1]  J. Tybout.  Linking trade and productivity : new research directions , 1992 .

[2]  C. Lovell,et al.  Stochastic Frontier Analysis: Frontmatter , 2000 .

[3]  Y. Shin,et al.  Probabilistic forecasting of output growth, inflation and the balance of trade in a GVAR framework , 2012 .

[4]  G. Battese,et al.  Prediction of firm-level technical efficiencies with a generalized frontier production function and panel data , 1988 .

[5]  M. Pesaran.  General diagnostic tests for cross-sectional dependence in panels , 2004, Empirical Economics.

[6]  Christophe Croux,et al.  A Measure of Comovement for Economic Variables: Theory and Empirics , 1999, Review of Economics and Statistics.

[7]  M. Busse,et al.  Foreign Direct Investment, Regulations and Growth , 2006 .

[8]  P. Romer.  Endogenous Technological Change , 1989, Journal of Political Economy.

[9]  A. U.S.,et al.  FORMULATION AND ESTIMATION OF STOCHASTIC FRONTIER PRODUCTION FUNCTION MODELS , 2001 .

[10]  W. Meeusen,et al.  Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error , 1977 .

[11]  Robin C. Sickles,et al.  A NEW PANEL DATA TREATMENT FOR HETEROGENEITY IN TIME TRENDS , 2012, Econometric Theory.

[12]  G. Battese,et al.  A model for technical inefficiency effects in a stochastic frontier production function for panel data , 1995 .

[13]  P. Schmidt,et al.  Production frontiers with cross-sectional and time-series variation in efficiency levels , 1990 .

[14]  D. B. Preston.  Spectral Analysis and Time Series , 1983 .

[15]  C. I. Jones,et al.  Productivity across industries and countries : time series theory and evidence , 1996 .

[16]  F. Canova,et al.  Trade Interdependence and the International-Business Cycle , 1993 .

[17]  E. Prescott,et al.  Postwar U.S. Business Cycles: An Empirical Investigation , 1997 .

[18]  D. Weil,et al.  A Contribution to the Empirics of Economic Growth Author ( s ) : , 2008 .

[19]  Peter Schmidt,et al.  Stochastic frontier models with multiple time-varying individual effects , 2007 .

[20]  M. Good.  Technology and Trade , 1996 .

[21]  Anthony L Bertapelle.  Spectral Analysis of Time Series. , 1979 .

[22]  Vietnamese Manufacturing Firms.  STOCHASTIC FRONTIER ANALYSIS OF , 2014 .

[23]  S. Kumbhakar,et al.  A Generalized Production Frontier Approach for Estimating Determinants of Inefficiency in U.S. Dairy Farms , 1991 .

[24]  Camilla Mastromarco,et al.  Regional Business Cycles in Italy , 2002, Comput. Stat. Data Anal..

[25]  David D. VanHoose,et al.  Openness, Central Bank Independence, and the Sacrifice Ratio , 2005 .

[26]  Daniel A. Levinthal,et al.  Innovation and Learning: The Two Faces of R&D , 1989 .

[27]  G. Grossman,et al.  Innovation and growth in the global economy , 1993 .

[28]  Robert J. Barro,et al.  Human Capital and Growth , 2001 .

[29]  L. R. Christensen,et al.  THE ECONOMIC THEORY OF INDEX NUMBERS AND THE MEASUREMENT OF INPUT, OUTPUT, AND PRODUCTIVITY , 1982 .

[30]  Léopold Simar,et al.  Semiparametric efficient estimation of dynamic panel data models , 2007 .

[31]  K. Tang,et al.  Efficiency externalities of trade and alternative forms of foreign investment in OECD countries , 2008 .

[32]  U. Woitek,et al.  Real Business Cycles of Sticky Prices? The Impact of Technology Shocks on US Manufacturing , 2000 .

[33]  S. Redding,et al.  Technological convergence, R&D, trade and productivity growth , 2005 .

[34]  R. Nelson,et al.  Investment in humans, technological diffusion and economic growth , 1965 .

[35]  Yongcheol Shin,et al.  Gravity models of intra-EU trade: application of the CCEP-HT estimation in heterogeneous panels with unobserved common time-specific factors , 2007 .

[36]  Robin C. Sickles,et al.  Estimation of long-run inefficiency levels: a dynamic frontier approach , 2000 .

[37]  E. Prasad,et al.  How Does Globalization Affect the Synchronization of Business Cycles? , 2003, SSRN Electronic Journal.

[38]  D. Romer,et al.  Does Trade Cause Growth , 1999 .

[39]  Young,et al.  INVESTMENT IN HUMANS, TECHNOLOGICAL DIFFUSION , 2002 .

[40]  T. Garrett,et al.  Aggregated vs. Disaggregated Data in Regression Analysis: Implications for Inference , 2002 .

[41]  M. Pesaran.  Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure , 2004, SSRN Electronic Journal.

[42]  Barry Eichengreen.  Productivity Growth, the New Economy, and Catching Up , 2004 .

[43]  Efthymios G. Tsionas,et al.  Inference in dynamic stochastic frontier models , 2006 .

[44]  A. Ciccone,et al.  TRADE AND PRODUCTIVITY , 2006 .

[45]  P. Schmidt,et al.  Production Frontiers and Panel Data , 1984 .

[46]  Christopher Taylor.  Foreign Direct Investment and the Euro: The First Five Years , 2007 .

[47]  P. Segerstrom.  Innovation, Imitation, and Economic Growth , 1991, Journal of Political Economy.

[48]  U. Woitek,et al.  Real business cycles, sticky wages or sticky prices? The impact of technology shocks on US manufacturing , 2005 .

[49]  M. Pesaran,et al.  Weak and Strong Cross-Section Dependence and Estimation of Large Panels , 2009, SSRN Electronic Journal.

[50]  Peter Schmidt,et al.  One-Step and Two-Step Estimation of the Effects of Exogenous Variables on Technical Efficiency Levels , 2002 .

[51]  Boyan Jovanovic,et al.  The Growth and Diffusion of Knowledge , 1989 .

[52]  J. Bai,et al.  Panel Data Models With Interactive Fixed Effects , 2009 .

[53]  Elhanan Helpman,et al.  International R&D spillovers , 1995 .

[54]  Y. Shin,et al.  Generalized Impulse Response Analysis in Linear Multivariate Models , 1998 .

[55]  S. Kumbhakar.  Production frontiers, panel data, and time-varying technical inefficiency , 1990 .

[56]  Ana Beatriz Galvão,et al.  The Transmission Mechanism in a Changing World , 2003 .

[57]  C. I. Jones,et al.  Why Do Some Countries Produce so Much More Output Per Worker than Others? , 1998 .

[58]  Bert M. Balk,et al.  The Residual: On Monitoring and Benchmarking Firms, Industries, and Economies with Respect to Productivity , 2001 .

[59]  S. Edwards.  Openness, Productivity and Growth: What Do We Really Know? , 1997 .

[60]  George Kapetanios,et al.  Alternative Approaches to Estimation and Inference in Large Multifactor Panels: Small Sample Results with an Application to Modelling of Asset Returns , 2005, SSRN Electronic Journal.