Hedonic Imputation versus Time Dummy Hedonic Indexes
In: Price Index Concepts and Measurement
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 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 (HD) indexes. This study provides a formal analysis of the difference between the two approaches for alternative implementations of an index that uses weighting that is comparable to the weighting used by the TÃ¶rnqvist superlative index in standard index number theory. This study shows exactly why the results 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.
This chapter was published in:
This item is provided by National Bureau of Economic Research, Inc in its series NBER Chapters with number 5073.
Contact details of provider:
Postal: National Bureau of Economic Research, 1050 Massachusetts Avenue Cambridge, MA 02138, U.S.A.
Web page: http://www.nber.org
More information through EDIRC
Other versions of this item:
- W. E. Diewert & Mick Silver & Saeed Heravi, 2007. "Hedonic Imputation versus Time Dummy Hedonic Indexes," IMF Working Papers 07/234, International Monetary Fund.
- 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
- 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
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.:
- 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.
- Feenstra, R.C., 1995.
"Exact Hedonic Price Indexes,"
Department of Economics
95-11, California Davis - Department of Economics.
- 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, December.
- 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.
- 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.
- 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.
- 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.
- 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.
- Raquel Arévalo Tomé & José María Chamorro Rivas, . "Geographic Heterogeneity in Housing. Evidence from Spain," Studies on the Spanish Economy 203, FEDEA.
- W. Diewert, 2011.
"Measuring productivity in the public sector: some conceptual problems,"
Journal of Productivity Analysis,
Springer, vol. 36(2), pages 177-191, October.
- 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.
- 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.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ().
If references are entirely missing, you can add them using this form.