Hedonic Imputation Versus Time Dummy Hedonic Indexes
AbstractStatistical offices try to match item models when measuring inflation between two periods. However, for product areas with a high turnover of differentiated models, the use of hedonic indexes is more appropriate since they include unmatched new and old models. There are two main competing approaches to hedonic indexes are hedonic imputation (HI) indexes and dummy time hedonic (HD) indexes. This study provides a formal analysis of exactly why the results from the two approaches may differ and discusses the issue of choice between these approaches. An illustrative study for desktop PCs is provided.
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 07/234.
Date of creation: 01 Oct 2007
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:
- W. Erwin Diewert & Saeed Heravi & Mick Silver, 2009. "Hedonic Imputation versus Time Dummy Hedonic Indexes," NBER Chapters, in: Price Index Concepts and Measurement, pages 161-196 National Bureau of Economic Research, Inc.
- Erwin Diewert & Saeed Heravi & Mick Silver, 2008. "Hedonic Imputation versus Time Dummy Hedonic Indexes," NBER Working Papers 14018, National Bureau of Economic Research, Inc.
- C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
- C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
- E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
- O47 - Economic Development, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Measurement of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence
This paper has been announced in the following NEP Reports:
- NEP-ALL-2008-01-05 (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.:
- Jack Triplett, 2004. "Handbook on Hedonic Indexes and Quality Adjustments in Price Indexes: Special Application to Information Technology Products," OECD Science, Technology and Industry Working Papers 2004/9, OECD Publishing.
- Robert C. Feenstra & Matthew D. Shapiro, 2003. "Scanner Data and Price Indexes," NBER Books, National Bureau of Economic Research, Inc, number feen03-1.
- Feenstra, R.C., 1995.
"Exact Hedonic Price Indexes,"
95-11, California Davis - Institute of Governmental Affairs.
- Ariel Pakes, 2003.
"A Reconsideration of Hedonic Price Indexes with an Application to PC's,"
American Economic Review,
American Economic Association, vol. 93(5), pages 1578-1596, December.
- Ariel Pakes, 2002. "A Reconsideration of Hedonic Price Indices with an Application to PC's," NBER Working Papers 8715, National Bureau of Economic Research, Inc.
- Silver, Mick & Heravi, Saeed, 2005.
"A Failure in the Measurement of Inflation: Results From a Hedonic and Matched Experiment Using Scanner Data,"
Journal of Business & Economic Statistics,
American Statistical Association, vol. 23, pages 269-281, July.
- Silver, Mick & Heravi, Saeed, 2002. "A failure in the measurement of inflation: results from a hedonic and matched experiment using scanner data," Working Paper Series 0144, European Central Bank.
- W. Erwin Diewert, 2003. "Hedonic Regressions. A Consumer Theory Approach," NBER Chapters, in: Scanner Data and Price Indexes, pages 317-348 National Bureau of Economic Research, Inc.
- 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.
- Diewert, Erwin, 2010.
"Measuring Productivity in the Public Sector: Some Conceptual Problems,"
Economics working papers
erwin_diewert-2010-6, Vancouver School of Economics, revised 13 Jul 2010.
- W. Diewert, 2011. "Measuring productivity in the public sector: some conceptual problems," Journal of Productivity Analysis, Springer, vol. 36(2), pages 177-191, October.
- Raquel Arévalo Tomé & José María Chamorro Rivas, . "Geographic Heterogeneity in Housing. Evidence from Spain," Studies on the Spanish Economy 203, FEDEA.
- Mick Silver, 2009. "The Hedonic Country Product Dummy Method and Quality Adjustments for Purchasing Power Parity Calculations," IMF Working Papers 09/271, International Monetary Fund.
- Brachinger, Hans Wolfgang & Beer, Michael, 2009. "The Econometric Foundations of Hedonic Elementary Price Indices," DQE Working Papers 12, Department of Quantitative Economics, University of Freiburg/Fribourg Switzerland.
- de Haan, Jan & van der Grient, Heymerik A., 2011. "Eliminating chain drift in price indexes based on scanner data," Journal of Econometrics, Elsevier, vol. 161(1), pages 36-46, March.
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.