间接影响——作为技术系数替代的正式定义和依赖程度

F. Coppens
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引用次数: 88

摘要

使用投入产出分析来计算最终需求变化的二次效应是众所周知的。这些“最终需求效应”可以使用技术系数和Leontief矩阵的逆来计算。本文提供了一种替代技术系数的方法。它的目标有三个。首先定义了所有的依赖程度,并展示了如何使用它们来计算次要效应。它们的定义基于一个输入输出表。其次,次要效应的概念扩展到所谓的间接效应。这些间接影响不仅与最终需求有关,而且与工业总产出有关。它显示了如何使用技术系数或依赖程度来计算这些间接影响。所使用的方法是所谓的假设提取方法的一种变体。避免重复计算,因此产生的乘数是“净乘数”。正式证明了技术系数和依赖程度在最近的投入产出表可用时给出相同的结果。如果不是这样,那么结果就不同了。很难说这两种估计中哪一种更好。由于技术系数已被广泛接受,因此给出了一些例子来证明使用依赖程度是合理的。最后解释了如何解决输入输出表不可用的问题。从供应-使用表开始,提供了一种“快速而简单的方法”来推断输入-输出表。比利时的投入产出表只公布那些能被5整除的年份,滞后三年,这一事实证明了这个主题的合理性。基于现有数据的简短实证分析表明,技术系数和依赖程度具有相当的性能,技术系数略有优势。这种表现是相对于“正确”的结果来衡量的,即使用现有的2000年投入产出表计算2000年的间接影响。这个结果被称为“正确的”,因为它没有对技术系数的稳定性和依赖程度做任何假设。实证分析还比较了使用最近的供应-使用表和使用旧的投入-产出表。供应-使用表平均高估了“正确”的结果。然而,他们往往是最接近“正确”的结果在第一级。由于这些结论是基于有限的数据,因此需要在获得更多数据后进行进一步分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Indirect Effects - A Formal Definition and Degrees of Dependency as an Alternative to Technical Coefficients
The use of input-output analysis for the computation of secondary effects of final demand changes is well-known. These 'final demand effects' can be calculated using technical coefficients and the inverse of the Leontief matrix. This paper offers an alternative to the use of technical coefficients. Its goal is threefold. First of all degrees of dependency are defined and it is shown how they can be used to compute secondary effects. Their definition is based on an input-output table. Secondly the concept of secondary effects is extended to what is called indirect effects. These indirect effects are not only related to final demand but to total industry output. It is shown how these indirect effects can be calculated using technical coefficients or degrees of dependency. The method used is a variant of the so-called Hypothetical Extraction Methods. Double counting is avoided, as such the resulting multipliers are 'net multipliers'. It is formally demonstrated that technical coefficients and degrees of dependency give the same results when a recent input-output table is available. If this is not the case then the results are different. It is impossible to say which of the two estimates is better. Since technical coefficients are already broadly accepted, some examples are given to justify the use of degrees of dependency. Finally it is explained how the unavailability of an input-output table can be solved. Starting from the supply-use tables a 'quick and dirty method' to infer an input-output table is provided. This topic is justified by the fact that for Belgium input-output tables are only published for those years that are divisible by five, with a three year lag. A short empirical analysis, based on currently available data, shows that technical coefficients and degrees of dependency have comparable performance, with a slight advantage for the technical coefficients. This performance is measured relative to a 'right' result, being the indirect effects for the year 2000 computed using the now available input-output table for the year 2000. This result is called 'right' because it does not make any assumptions on stability of technical coefficients nor of degrees of dependency. The empirical analysis also compares the use of a recent supply-use table to the use of an old input-output table. Supply-use tables on average overestimate the 'right' result. They are however often closest to the 'right' result at the first level. Since these conclusions are based on limited data further analysis is required as more data becomes available.
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