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引用次数: 0
摘要
先进国家的国家统计局(NSIs)一般都在其国民账户中采用链式链接。美国在其国民经济核算中使用了链式费雪,这是超等指数的一个例子。然而,费雪只是无数个超等指数中的一个。因此,一个重要的问题是产出增长的估计值对指数的选择有多敏感。我们通过研究 1987-2020 年 BEA/BLS 行业级综合生产账户的数据来分析这一问题。该数据集提供了上位指数和其他指数的估计值。测试了实际 GDP 增长对超标指数中关键参数值的敏感性。此外,还分析了不同的上位指数在多大程度上满足了价值一致性和总量一致性的理想特征。链式链接的可取性并不仅仅来自于超标指数的使用。因此,我还比较了这些相同指数的链式和非链式版本。最后,欧洲采用了与美国不同的产出衡量方法,即链式拉斯佩尔指数与链式费雪指数。我将研究如果采用欧洲方法,美国的估计值会有多大不同。
To chain or not to chain? measuring real GDP in the US and the choice of index number
National Statistical Institutes (NSIs) in advanced countries have generally adopted chain-linking in their national accounts. The United States uses a chained Fisher, an example of a superlative index number, in its national accounts. However the Fisher is only one of an infinite number of superlative index numbers. So an important issue is how sensitive are the estimates of output growth to the choice of index number. This issue is analysed by examining data from the BEA/BLS industry-level integrated production account, 1987–2020. Estimates of superlative and other index numbers are presented for this dataset. The sensitivity of real GDP growth to the value of the crucial parameter in a superlative index number is tested. The extent to which the desirable characteristics of value consistency and aggregation consistency are satisfied for different superlative index numbers is also analysed. The desirability of chain-linking does not follow automatically just from the use of superlative indices. So I also compare chained and unchained versions of these same index numbers. Finally, Europe uses a different approach to output measurement to the US, chained Laspeyres versus chained Fisher. I look at how different US estimates would be if they employed European methodology.
期刊介绍:
The Journal of Productivity Analysis publishes theoretical and applied research that addresses issues involving the measurement, explanation, and improvement of productivity. The broad scope of the journal encompasses productivity-related developments spanning the disciplines of economics, the management sciences, operations research, and business and public administration. Topics covered in the journal include, but are not limited to, productivity theory, organizational design, index number theory, and related foundations of productivity analysis. The journal also publishes research on computational methods that are employed in productivity analysis, including econometric and mathematical programming techniques, and empirical research based on data at all levels of aggregation, ranging from aggregate macroeconomic data to disaggregate microeconomic data. The empirical research illustrates the application of theory and techniques to the measurement of productivity, and develops implications for the design of managerial strategies and public policy to enhance productivity.
Officially cited as: J Prod Anal