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.
GME Estimation with Non-Linearities and Spatial Dependence in Club Convergence Analysis / Bernardini Papalia R.; S. Bertarelli. - ELETTRONICO. - (2010), pp. 1-41. (Intervento presentato al convegno Info-Metrics: Theory and Applications in the Social Sciences tenutosi a American University, Washington DC, USA nel September 24-25).
GME Estimation with Non-Linearities and Spatial Dependence in Club Convergence Analysis
BERNARDINI PAPALIA, ROSA;
2010
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.