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Is Globalization Driving Efficiency? A Threshold Stochastic Frontier Panel Data Modeling Approach

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  • Camilla Mastromarco
  • Laura Serlenga
  • Yongcheol Shin

Abstract

Recently, Mastromarco, Serlenga and Shin (2010) propose a two-step approach to examine dynamic transmission mechanism under which globalization factors fos- ter technology efficiency. In this paper, we extend the MSS model by combining panel threshold regression technique advanced by Hansen (1999). This threshold stochastic frontier panel data model enables us to analyze regime-specific stochas- tic frontiers and complex time-varying patterns of technical efficiencies in a robust manner. Using a dataset of 44 countries over 1970-2007, we find that income elas- ticities of labour and capital and time-varying common efficiencies are substantially different under superior and inferior frontiers. Capital and labour inputs are more productive under superior frontier. More importantly, common efficiencies have steadily increased under superior frontier, but technical efficiency has monotoni- cally decreased for low income countries, supporting the so-called club convergence hypothesis. Furthermore, the VAR-based impulse response analyses suggest that openness factors through FDI and trade help the countries improve production technology and efficiency position relative to the frontier only after the country has reached a certain level of development.
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  • 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.
  • Handle: RePEc:bla:reviec:v:20:y:2012:i:3:p:563-579
    DOI: j.1467-9396.2012.01039.x
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    1. Rachel Griffith & Stephen Redding & John Van Reenen, 2004. "Mapping the Two Faces of R&D: Productivity Growth in a Panel of OECD Industries," The Review of Economics and Statistics, MIT Press, vol. 86(4), pages 883-895, November.
    2. Efthymios G. Tsionas, 2006. "Inference in dynamic stochastic frontier models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(5), pages 669-676.
    3. Caner, Mehmet & Hansen, Bruce E., 2004. "Instrumental Variable Estimation Of A Threshold Model," Econometric Theory, Cambridge University Press, vol. 20(05), pages 813-843, October.
    4. Hansen, Bruce E., 1999. "Threshold effects in non-dynamic panels: Estimation, testing, and inference," Journal of Econometrics, Elsevier, vol. 93(2), pages 345-368, December.
    5. Howitt, Peter & Mayer-Foulkes, David, 2005. "R&D, Implementation, and Stagnation: A Schumpeterian Theory of Convergence Clubs," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(1), pages 147-177, February.
    6. Sala-i-Martin, Xavier X, 1996. "The Classical Approach to Convergence Analysis," Economic Journal, Royal Economic Society, vol. 106(437), pages 1019-1036, July.
    7. Mastromarco Camilla & Laura Serlenga & Yongcheol Shin, 2013. "Globalisation and technological convergence in the EU," Journal of Productivity Analysis, Springer, vol. 40(1), pages 15-29, August.
    8. Coe, David T. & Helpman, Elhanan, 1995. "International R&D spillovers," European Economic Review, Elsevier, vol. 39(5), pages 859-887, May.
    9. Krishna G. Iyer & Alicia N. Rambaldi & Kam Ki Tang, 2008. "Efficiency externalities of trade and alternative forms of foreign investment in OECD countries," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(6), pages 749-766.
    10. Durlauf, Steven N & Johnson, Paul A, 1995. "Multiple Regimes and Cross-Country Growth Behaviour," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 10(4), pages 365-384, Oct.-Dec..
    11. David H. Romer & Jeffrey A. Frankel, 1999. "Does Trade Cause Growth?," American Economic Review, American Economic Association, vol. 89(3), pages 379-399, June.
    12. N. Gregory Mankiw & David Romer & David N. Weil, 1992. "A Contribution to the Empirics of Economic Growth," The Quarterly Journal of Economics, Oxford University Press, vol. 107(2), pages 407-437.
    13. Mei-Hui Wang & Tai-Hsin Huang, 2009. "Threshold effects of financial status on the cost frontiers of financial institutions in nondynamic panels," Applied Economics, Taylor & Francis Journals, vol. 41(26), pages 3389-3401.
    14. Bruce E. Hansen, 2000. "Sample Splitting and Threshold Estimation," Econometrica, Econometric Society, vol. 68(3), pages 575-604, May.
    15. Edwards, Sebastian, 1998. "Openness, Productivity and Growth: What Do We Really Know?," Economic Journal, Royal Economic Society, vol. 108(447), pages 383-398, March.
    16. Quah, Danny, 1997. "Empirics for Growth and Distribution: Stratification, Polarization, and Convergence Clubs," CEPR Discussion Papers 1586, C.E.P.R. Discussion Papers.
    17. Krugman, Paul, 1991. "Increasing Returns and Economic Geography," Journal of Political Economy, University of Chicago Press, vol. 99(3), pages 483-499, June.
    18. Kumbhakar, Subal C., 1990. "Production frontiers, panel data, and time-varying technical inefficiency," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 201-211.
    19. Sourafel Girma, 2005. "Absorptive Capacity and Productivity Spillovers from FDI: A Threshold Regression Analysis," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(3), pages 281-306, June.
    20. George Kapetanios & M. Hashem Pesaran, 2005. "Alternative Approaches to Estimation and Inference in Large Multifactor Panels: Small Sample Results with an Application to Modelling of Asset Returns," CESifo Working Paper Series 1416, CESifo Group Munich.
    21. Hansen, Bruce E, 1996. "Inference When a Nuisance Parameter Is Not Identified under the Null Hypothesis," Econometrica, Econometric Society, vol. 64(2), pages 413-430, March.
    22. Robert E. Hall & Charles I. Jones, 1999. "Why do Some Countries Produce So Much More Output Per Worker than Others?," The Quarterly Journal of Economics, Oxford University Press, vol. 114(1), pages 83-116.
    23. Seung Ahn & Young Lee & Peter Schmidt, 2007. "Stochastic frontier models with multiple time-varying individual effects," Journal of Productivity Analysis, Springer, vol. 27(1), pages 1-12, February.
    24. Borensztein, E. & De Gregorio, J. & Lee, J-W., 1998. "How does foreign direct investment affect economic growth?1," Journal of International Economics, Elsevier, vol. 45(1), pages 115-135, June.
    25. Schmidt, Peter & Sickles, Robin C, 1984. "Production Frontiers and Panel Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(4), pages 367-374, October.
    26. Cohen, Wesley M & Levinthal, Daniel A, 1989. "Innovation and Learning: The Two Faces of R&D," Economic Journal, Royal Economic Society, vol. 99(397), pages 569-596, September.
    27. Seung Ahn & Robin Sickles, 2000. "Estimation of long-run inefficiency levels: a dynamic frontier approach," Econometric Reviews, Taylor & Francis Journals, vol. 19(4), pages 461-492.
    28. Yélou, Clément & Larue, Bruno & Tran, Kien C., 2010. "Threshold effects in panel data stochastic frontier models of dairy production in Canada," Economic Modelling, Elsevier, vol. 27(3), pages 641-647, May.
    29. Nazrul Islam, 2003. "What have We Learnt from the Convergence Debate?," Journal of Economic Surveys, Wiley Blackwell, vol. 17(3), pages 309-362, July.
    30. Jonathan Temple, 1999. "The New Growth Evidence," Journal of Economic Literature, American Economic Association, vol. 37(1), pages 112-156, March.
    31. Quah, Danny T, 1997. "Empirics for Growth and Distribution: Stratification, Polarization, and Convergence Clubs," Journal of Economic Growth, Springer, vol. 2(1), pages 27-59, March.
    32. Cornwell, Christopher & Schmidt, Peter & Sickles, Robin C., 1990. "Production frontiers with cross-sectional and time-series variation in efficiency levels," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 185-200.
    33. Robert J. Barro, 2001. "Human Capital and Growth," American Economic Review, American Economic Association, vol. 91(2), pages 12-17, May.
    34. Pissarides, Christopher A, 1997. "Learning by Trading and the Returns to Human Capital in Developing Countries," World Bank Economic Review, World Bank Group, vol. 11(1), pages 17-32, January.
    35. Yongcheol Shin & Laura Serlenga, 2007. "Gravity models of intra-EU trade: application of the CCEP-HT estimation in heterogeneous panels with unobserved common time-specific factors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(2), pages 361-381.
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    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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