Multilateral Comparisons of Productivity, Terms‐of‐Trade and Factor Accumulation
Alice Shiu
Review of Income and Wealth, 2003, vol. 49, issue 1, 35-52
Abstract:
This paper proposes a new approach for multilateral comparisons using index numbers. The new approach combines two recently‐proposed innovative techniques to examine differences among economies at various levels. The Minimum Spanning Tree algorithm, based on the idea of minimizing substitution bias of bilateral comparisons, provides a possible ordering for panel data. Making use of the suggested ordering, bilateral Törnqvist price and quantity indexes are calculated and multilateral indexes are obtained by chaining. An index‐number based approach is then used to decompose the differences in GDP at the bilateral level. Different sources that contribute to the differences in GDP are considered: productivity differences, terms of trade differences, factor endowments differences and domestic output price differences. The newly formed indexes are base‐invariant which provides strong support for using the technique for multilateral comparisons. An illustration of the technique using data from China and four OECD countries is included.
Date: 2003
References: Add references at CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
https://doi.org/10.1111/1475-4991.00073
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:bla:revinw:v:49:y:2003:i:1:p:35-52
Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=0034-6586
Access Statistics for this article
Review of Income and Wealth is currently edited by Conchita D'Ambrosio and Robert J. Hill
More articles in Review of Income and Wealth from International Association for Research in Income and Wealth Contact information at EDIRC.
Bibliographic data for series maintained by Wiley Content Delivery ().