The Difference Between Hedonic Imputation Indexes and Time Dummy Hedonic Indexes
AbstractStatistical offices try to match item models when measuring inflation between two periods. For product areas with a high turnover of differentiated models, however, the use of hedonic indexes is more appropriate since they include the prices and quantities of unmatched new and old models. The two main approaches to hedonic indexes are hedonic imputation (HI) indexes and dummy time hedonic (DTH) indexes. This study provides a formal analysis of the difference between the two approaches for alternative implementations of the T�rnqvist "superlative" index. It shows why the results may differ and discusses the issue of choice between these approaches.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. 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.
Bibliographic InfoPaper provided by International Monetary Fund in its series IMF Working Papers with number 06/181.
Date of creation: 01 Jul 2006
Date of revision:
Contact details of provider:
Postal: International Monetary Fund, Washington, DC USA
Phone: (202) 623-7000
Fax: (202) 623-4661
Web page: http://www.imf.org/external/pubind.htm
More information through EDIRC
Other versions of this item:
- Silver, Mick & Heravi, Saeed, 2007. "The Difference Between Hedonic Imputation Indexes and Time Dummy Hedonic Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 239-246, April.
- NEP-ALL-2006-11-25 (All new papers)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Ernst R. Berndt & Neal J. Rappaport, 2001. "Price and Quality of Desktop and Mobile Personal Computers: A Quarter-Century Historical Overview," American Economic Review, American Economic Association, vol. 91(2), pages 268-273, May.
- Silver, Mick & Heravi, Saeed, 2001. "Scanner Data and the Measurement of Inflation," Economic Journal, Royal Economic Society, vol. 111(472), pages F383-404, June.
- Ana Aizcorbe, 2003. "The stability of dummy variable price measures obtained from hedonic regressions," Finance and Economics Discussion Series 2003-05, Board of Governors of the Federal Reserve System (U.S.).
- Rosen, Sherwin, 1974. "Hedonic Prices and Implicit Markets: Product Differentiation in Pure Competition," Journal of Political Economy, University of Chicago Press, vol. 82(1), pages 34-55, Jan.-Feb..
- Kees Jan Van Garderen & Chandra Shah, 2002. "Exact interpretation of dummy variables in semilogarithmic equations," Econometrics Journal, Royal Economic Society, vol. 5(1), pages 149-159, June.
- Jack E. Triplett, 1999. "The Solow productivity paradox: what do computers do to productivity?," Canadian Journal of Economics, Canadian Economics Association, vol. 32(2), pages 309-334, April.
- Robert J. Hill & Daniel Melser, 2007. "Comparing House Prices Across Regions and Time: An Hedonic Approach," Discussion Papers 2007-33, School of Economics, The University of New South Wales.
- Raquel Arévalo Tomé & José María Chamorro Rivas, . "Geographic Heterogeneity in Housing. Evidence from Spain," Studies on the Spanish Economy 203, FEDEA.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Jim Beardow) or (Hassan Zaidi).
If references are entirely missing, you can add them using this form.