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On Testing Conditional Sigma - Convergence

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  • Peter Egger
  • Michael Pfaffermayr

Abstract

In a cross-section where the initial distribution of observations differs from the steady-state distribution and initial values matter, convergence is best measured in terms of "σ"-convergence over a fixed time period. For this setting, we propose a new simple Wald test for conditional "σ"-convergence. According to our Monte Carlo simulations, this test performs well and its power is comparable with the available tests of unconditional convergence. We apply two versions of the test to conditional convergence in the size of European manufacturing firms. The null hypothesis of no convergence is rejected for all country groups, most single economies, and for younger firms of our sample of 49,646 firms. Copyright (c) Blackwell Publishing Ltd and the Department of Economics, University of Oxford, 2007.

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Bibliographic Info

Article provided by Department of Economics, University of Oxford in its journal Oxford Bulletin of Economics and Statistics.

Volume (Year): 71 (2009)
Issue (Month): 4 (08)
Pages: 453-473

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Handle: RePEc:bla:obuest:v:71:y:2009:i:4:p:453-473

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Cited by:
  1. Nicola Pontarollo & Elisa Montresor & Francesco Pecci, 2012. "Sectoral productivity convergence between European regions: does space matter?," ERSA conference papers ersa12p559, European Regional Science Association.
  2. Shahram Amini & Michele Battisti & Christopher F. Parmeter, 2011. "Decomposing The Conditional Variance of Cross-Country Output," Working Papers, University of Miami, Department of Economics 2011-18, University of Miami, Department of Economics.
  3. Pfaffermayr, Michael, 2009. "Conditional [beta]- and [sigma]-convergence in space: A maximum likelihood approach," Regional Science and Urban Economics, Elsevier, Elsevier, vol. 39(1), pages 63-78, January.
  4. Badi H. Baltagi & Peter Egger & Michaela Kesina, 2014. "Sources of Productivity Spillovers: Panel Data Evidence from China," CESifo Working Paper Series 4812, CESifo Group Munich.

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