A pair-wise approach to output convergence between European regions
We apply the Pesaran (2007) pair-wise approach of convergence to the per capita outputs of 195 European regions for the period 1980-2006. Pesaran's approach is based on the computation of the percentage ratio of output gaps which fulfil a given convergence criterion. A high ratio will be interpreted in favour of convergence. In a first step, we define stochastic convergence between two regions as level stationarity of their output gap. Deviations from its equilibrium value will only have a temporary effect. Results from several usual unit root or stationarity tests show us that the percentage ratio of level stationary output gaps is low, which stands against this definition of convergence. However, this convergence criterion excludes the possibility of changes in output gap equilibrium value or catching up between regions. To fit these cases, we combine the pair-wise approach with unit root or stationarity tests with structural breaks. Structural breaks are modelled by dummies (Zivot and Andrews, 1992; Kurozumi,2002) or as smooth structural breaks (Christopoulos and León-Ledesma, 2009). Overall results are not changed as convergence is not accepted more often. Finally, we consider the autocorrelation function approach of Caggiano and Leonida (2009). Autocorrelations and their confidence intervals are estimated for each output gap. Convergence between two regions is accepted if their per capita output gap autocorrelations become nonsignificantly different from zero after some lag. Results show that a high percentage of regions satisfy this convergence criterion. Contrary to the conclusions which could be made from previous results, shocks to output gaps seem to disappear as time passes.
Year of publication: |
2011
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---|---|
Authors: | Le Pen, Yannick |
Published in: |
Economic Modelling. - Elsevier, ISSN 0264-9993. - Vol. 28.2011, 3, p. 955-964
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Publisher: |
Elsevier |
Keywords: | Growth Regional Convergence Pair-wise approach Unit root Structural breaks Autocorrelation function |
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