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Estimation errors in input–output tables and prediction errors in computable general equilibrium analysis
Institution:1. EUI Vitoria-Gasteiz of the University of the Basque Country (UPV/EHU), Spain;2. Computational Intelligence Group, UPV/EHU, Spain;3. ENGINE Centre, Wroc?aw University of Technology (WUT), Wybrze?e Wyspiańskiego 27, 50-370 Wroc?aw, Poland;1. Département de Physique, Laboratoire de Magnétisme et Physique des Hautes Energies, Faculté des Sciences, B.P. 1014, Rabat, Morocco;2. Département de Physique, Laboratoire de Physique de la Matière Condensée, Faculté des Sciences, Route Ben Maachou, 24000, El Jadida, Morocco
Abstract:We used 1995–2000–2005 linked input–output (IO) tables for Japan to examine estimation errors of updated IO tables and the resulting prediction errors in computable general equilibrium (CGE) analysis developed with updated IO tables. As we usually have no true IO tables for the target year and therefore need to estimate them, we cannot evaluate estimation errors of updated IO tables without comparing the updated ones with the true ones. However, using the linked IO tables covering three different years enables us to make this comparison. Our experiments showed that IO tables estimated with more detailed and recent data contained smaller estimation errors and led to smaller quantitative prediction errors in CGE analysis. Despite the quantitative prediction errors, prediction was found to be qualitatively correct. As for the performance of updating techniques of IO tables, a cross-entropy method often outperformed a least-squares method in IO estimation with only aggregate data for the target year but did not necessarily outperform the least-squares method in CGE prediction.
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