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The Difference Between Hedonic Imputation Indexes and Time Dummy Hedonic Indexes

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  • Saeed Heravi
  • Mick Silver

Abstract

Statistical 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 Törnqvist "superlative" index. It shows why the results may differ and discusses the issue of choice between these approaches.

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Bibliographic Info

Paper provided by International Monetary Fund in its series IMF Working Papers with number 06/181.

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Length: 20
Date of creation: 01 Jul 2006
Date of revision:
Handle: RePEc:imf:imfwpa:06/181

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Keywords: Consumer price indexes; Consumer prices; equation; paper; statistics; equations; dummy variable; arithmetic; regression equation; functional form; samples; number theory; parameter change; dummy variables; econometrics; covariance; sampling; sample selection; functional forms; survey;

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References

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  1. 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.
  2. 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.).
  3. 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.
  4. Silver, Mick & Heravi, Saeed, 2001. "Scanner Data and the Measurement of Inflation," Economic Journal, Royal Economic Society, vol. 111(472), pages F383-404, June.
  5. 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..
  6. 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.
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Cited by:
  1. Raquel Arévalo Tomé & José María Chamorro Rivas, . "Geographic Heterogeneity in Housing. Evidence from Spain," Studies on the Spanish Economy 203, FEDEA.
  2. Robert J. Hill & Michael Scholz, 2014. "Incorporating Geospatial Data in House Price Indexes: A Hedonic Imputation Approach with Splines," Graz Economics Papers 2014-05, University of Graz, Department of Economics.
  3. 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.

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