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EnglishThis paper assess the existence of club convergence across OECD over the period 1965-2004 by developing a two stage strategy, which employs information on clustering schemes - identified by a mapping analysis - and estimates a multiple equation dynamic panel model with non linearities and spatial dependence. Because of identification and collinearity problems, we introduce an entropy-based estimation procedure which simultaneously takes account of ill-posed and ill-conditioned inference problems. At the first stage, unobserved total factor productivity differentials across OECD countries are identified by specifying a mapping structure in a convergence model with non linearities and spatial dependence. At the second step of the analysis, we estimate a two-club spatial convergence model, where clubs correspond to subsets of total observations, as identified at the first stage of the analysis.
| Titolo: | GME Estimation with Non-Linearities and Spatial Dependence in Club Convergence Analysis |
| Autore/i: | BERNARDINI PAPALIA, ROSA; S. Bertarelli |
| Autore/i Unibo: | |
| Anno: | 2010 |
| Titolo del libro: | Info-Metrics Institute, Working Papers, American University Washington DC. USA |
| Pagina iniziale: | 1 |
| Pagina finale: | 41 |
| Abstract: | This paper assess the existence of club convergence across OECD over the period 1965-2004 by developing a two stage strategy, which employs information on clustering schemes - identified by a mapping analysis - and estimates a multiple equation dynamic panel model with non linearities and spatial dependence. Because of identification and collinearity problems, we introduce an entropy-based estimation procedure which simultaneously takes account of ill-posed and ill-conditioned inference problems. At the first stage, unobserved total factor productivity differentials across OECD countries are identified by specifying a mapping structure in a convergence model with non linearities and spatial dependence. At the second step of the analysis, we estimate a two-club spatial convergence model, where clubs correspond to subsets of total observations, as identified at the first stage of the analysis. |
| Data prodotto definitivo in UGOV: | 25-feb-2011 |
| Appare nelle tipologie: | 4.01 Contributo in Atti di convegno |
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