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A new method to estimate input-output tables by means of structural lags, tested on Spanish regions

机译:一种通过结构滞后估算投入产出表的新方法,已在西班牙地区进行了测试

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摘要

The RAS method extrapolates a single matrix to conform to new row and column totals. This paper proposes a cell-correction of RAS (CRAS) that uses the deviations of multiple RAS projections, to improve the projection of the input-output table (IOT) of a specific country or region. The new method is tested on eleven survey-based IOTs of Spanish regions for 1999-2005. CRAS is shown to outperform RAS when three to four survey IOTs are used that are close to the target IOT. When more IOTs are added, for most but not all regions, CRAS gradually becomes worse than applying RAS to the single best IOT.
机译:RAS方法外推单个矩阵以符合新的行和列的总数。本文提出了一种RAS单元格校正(CRAS),它使用多个RAS投影的偏差来改进特定国家或地区的投入产出表(IOT)的投影。在1999-2005年间,对西班牙地区的11种基于调查的物联网进行了测试。当使用三到四个接近目标IOT的调查IOT时,表明CRAS优于RAS。当添加更多的IOT时,对于大多数但不是全部区域,CRAS逐渐变得比将RAS应用于单个最佳IOT变得更糟。

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