This file is part of IDEAS, which uses RePEc data


[ Papers | Articles | Software | Books | Chapters | Authors | Institutions | JEL Classification | NEP reports | Search | New papers by email | Author registration | Rankings | Volunteers | FAQ | Blog | Help! ]

Standard errors as weights in multilateral price indices

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
Hill, Robert
Timmer, Marcel (Groningen University)

Additional information is available for the following registered author(s):

Abstract

A number of multilateral methods for computing price indexes use bilateral comparisons as their basic building blocks. Some of these methods, such as the weighted-EKS and minimum-spanning-tree (MST) methods, give greater weight to those bilateral comparisons that are deemed more reliable (an adjustment that is particularly important for a heterogeneous set of countries). No consensus currently exists in the literature as to the best measure of reliability. Diewert (2002), in particular, proposes a number of reliability measures in an axiomatic setting. Existing measures (including all of Diewert’s), however, fail to penalize bilateral comparisons when there is a small overlap in the products priced by each country. It is exactly in such situations that weighted methods are potentially most useful, but only if the reliability measure penalizes bilateral comparisons containing lots of gaps. Using a stochastic model, we show how the standard errors on bilateral price indexes provide a natural measure of reliability that automatically penalizes comparisons containing lots of gaps. Furthermore, we link these standard errors with the existing literature by showing that they are a generalization of one of Diewert’s reliability measures. This finding provides an interesting new link between the axiomatic and stochastic approaches to index numbers. Also, these standard errors can be modified for use in consumer data sets below the basic-heading level (where no expenditure shares are available), a scenario of direct relevance to the latest round of the International Comparison Program (ICP) currently being undertaken at the World Bank. Finally, we apply our methodology to an international data set on agricultural production that contains a lot of gaps. Our results clearly demonstrate the appeal of weighted methods and the importance of adjusting the reliability measures for gaps in the data. Failure to do so may compromise weighted methods precisely in situations where they are most needed.

Download Info
To download:

If you experience problems downloading a file, check if you have the proper application to view it first. Information about this may be contained in the File-Format links below. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://irs.ub.rug.nl/ppn/275089428
File Format: application/pdf
File Function:
Download Restriction: no

Publisher Info
Paper provided by Groningen Growth and Development Centre, University of Groningen in its series GGDC Research Memorandum with number 200473.

Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Length:
Date of creation: 2004
Date of revision:
Handle: RePEc:dgr:rugggd:200473

Contact details of provider:
Postal: PO Box 800, 9700 AV Groningen
Phone: +31 50 363 7185
Fax: +31 50 363 3720
Email:
Web page: http://ggdc.eldoc.ub.rug.nl/
More information through EDIRC

For technical questions regarding this item, or to correct its listing, contact: (Joke Bulthuis).

Related research
Keywords:

Other versions of this item:

This paper has been announced in the following NEP Reports:
Statistics
Access and download statistics

Did you know? The RePEc project started in 1997. Its precursor, NetEc, dates back to 1993.

This page was last updated on 2009-12-16.


This information is provided to you by IDEAS at the Department of Economics, College of Liberal Arts and Sciences, University of Connecticut using RePEc data on a server sponsored by the Society for Economic Dynamics.