An Experimental Component Index for the CPI: From Annual Computer Data to Monthly Data on Other Goods
Until recently the Consumer Price Index consisted solely of "matched model" component indexes. The latter are constructed by BLS personnel who visit stores and compare prices of goods with the same set of characteristics over successive periods. This procedure is subject to a selection bias. Goods that were not on the shelves in the second period were discarded and hence never contributed price comparisons. The discarded goods were disproportionately goods which were being obsoleted and had falling prices. Pakes (2003) provided an analytic framework for analyzing this selection effect and showed both that it could be partially corrected using a particular hedonic technique and that the correction for his personal computer example was substantial. The BLS staff has recently increased the rate at which they incorporate techniques to correct for selection effects in their component indexes. However recent work shows very little difference between hedonic and matched model indices for non computer components of the CPI. This paper explores why. We look carefully at the data on the component index for TVs and show that differences between the TV and computer markets imply that to obtain an effective selection correction we need to use a more general hedonic procedure than has been used to date. The computer market is special in having well defined cardinal measures of the major product characteristics. In markets where such measures are absent we may need to allow for selection on unmeasured, as well as measured, characteristics. We develop a hedonic selection correction that accounts for unmeasured characteristics, apply it to TVs, and show that it yields a much larger selection correction than the standard hedonic. In particular we find that matched model techniques underestimate the rate of price decline by over 20%.
|Date of creation:||Sep 2008|
|Date of revision:|
|Publication status:||published as Pakes A, Erickson T. An Experimental Component Index for the CPI: From Annual Computer Data to Monthly Data on Other Goods. American Economic Review. 2011;101(5):1707-1738.|
|Contact details of provider:|| Postal: National Bureau of Economic Research, 1050 Massachusetts Avenue Cambridge, MA 02138, U.S.A.|
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- Newey, W.K., 1991.
"The Asymptotic Variance of Semiparametric Estimators,"
583, Massachusetts Institute of Technology (MIT), Department of Economics.
- Newey, Whitney K, 1994. "The Asymptotic Variance of Semiparametric Estimators," Econometrica, Econometric Society, vol. 62(6), pages 1349-82, November.
- Newey, W.K., 1989. "The Asymptotic Variance Of Semiparametric Estimotors," Papers 346, Princeton, Department of Economics - Econometric Research Program.
- G. Steven Olley & Ariel Pakes, 1992.
"The Dynamics of Productivity in the Telecommunications Equipment Industry,"
NBER Working Papers
3977, National Bureau of Economic Research, Inc.
- Olley, G Steven & Pakes, Ariel, 1996. "The Dynamics of Productivity in the Telecommunications Equipment Industry," Econometrica, Econometric Society, vol. 64(6), pages 1263-97, November.
- George S Olley & Ariel Pakes, 1992. "The Dynamics Of Productivity In The Telecommunications Equipment Industry," Working Papers 92-2, Center for Economic Studies, U.S. Census Bureau.
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