{"title":"To chain or not to chain? measuring real GDP in the US and the choice of index number","authors":"Nicholas Oulton","doi":"10.1007/s11123-024-00732-4","DOIUrl":null,"url":null,"abstract":"<p>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.</p>","PeriodicalId":16870,"journal":{"name":"Journal of Productivity Analysis","volume":"104 1","pages":""},"PeriodicalIF":2.3000,"publicationDate":"2024-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Productivity Analysis","FirstCategoryId":"96","ListUrlMain":"https://doi.org/10.1007/s11123-024-00732-4","RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BUSINESS","Score":null,"Total":0}
引用次数: 0
Abstract
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