Analytical Bias Reduction for Small Samples in the U.S. Consumer Price Index (original) (raw)
Related papers
2008
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%.
The treatment of substitution bias in consumer price index: An alternative approach
Statistical Methods & Applications, 2002
Substitution bias is a well-known problem in fixed-basket price indices. When a new product substitutes an old one, the most of statistical agencies adopt an ad hoc strategy, using the ratio between prices of the two goods (in a previous period) as a measure of quality change. In the present work we propose an alternative way to manage substitution that can be easily included in the computation process of the index. Price survey is a pure panel survey, and then substitution may be considered as an attrition problem and faced using the estimator for panels with partial overlap. After a brief description of the problem and of the suggested formula, an experimental application is presented. The application is based on about 771 elementary prices collected in Milano in March 1997. Main results are that in each category of consumption the two approaches show significant differences in the micro-indices, at the aggregated level, that is when weights are used to combine micro-indices, the differences agree with the conclusions of Boskin's report.
On curing the CPI's substitution and new goods bias
The basic idea developed in this paper is that a modified (two level) CES utility or cost function accounts for substitution caused by price changes as well as by changes in the range of available commodities. The theory of the associated cost of living index is provided, as well as a practical recipe for calculating this index in real time.
The Consumer Price Index the actual published value only approximates. The true value of the CPI is considered to be the true cost-of-living index, and so we begin with a discussion of the theory of the cost of living index. We progress to the construction of the actual CPI as it is reported every month, following the description of methodology in the Bureau of Labor Statistics' (BLS) Handbook of Methods. In the remainder of the article, we consider how well the CPI approximates the true cost-of-living index, paying particular attention to the problems of substitution, quality change, and the introduction of new goods, which are generally considered to cause the CPI to overstate the rate of increase in the cost of living or, alternatively, overstate the rate of inflation. 2 Some analysts have suggested that these measurement errors are so large that
The Impact of the Price Index Formula on the Consumer Price Index Measurement
Statistika: Statistics and Economy Journal, 2019
The Consumer Price Index (CPI) is a common measure of inflation. Similarly to the Harmonised Index of Consumer Prices (HICP), it is determined using the Laspeyres index, thus data on the consumption of the basket of goods do not have to be current. The Laspeyres index, using weights only from the base period, may not reflect changes in consumer preferences that occurred in the studied year. In the ideal case, the CPI should be measured by one of the so called superlative price indices, such as the Fisher, Törnqvist or Walsh index formulas. The main problem with such indices is that they need expenditure data from the current period. The aim of the article is to assess the impact of the choice of the price index formula on the CPI measurement. We verify differences among known index formulas at the lowest and some higher data aggregation levels. We use known bilateral unweighted and weighted formulas together with their chained versions.
The Lowe Consumer Price Index and its Substitution Bias
This note considers the Lowe consumer price index as an approxi- mation to a true cost of living index. A simple example, based on systematic long run trends in prices, is used to obtain some idea of the magnitude of the substitution bias. Corresponding author. The views expressed in this paper are those of the author and do not necessarily reflect the policies of Statistics Netherlands. Tel.: 31 70 337 4704; fax: 31 70 387 7429.