At What Price? Conceptualizing and Measuring Cost-of-Living and Price Indexes (2002) / Chapter Skim
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9 Data Collection for CPI Construction
9 Data Collection for CPI Construction
Pages 252-282
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From page 252... ...
For example, the current data system does not allow for production of non-urban-area indexes or regional price-level comparisons; nor does it support accurate price indexes for subpopulations such as the elderly, minorities, or the poor, particularly at subnational levels. Also, in order to reduce respondent burden, households are only asked about a portion of CPI item categories, which also inhibits the construction of some potentially useful, alternatively weighted (e.g., democratic)
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From page 253... ...
THE CURRENT DATA COLLECTION PROCESS The Consumer Expenditure Survey The CEX is the primary tool for establishing CPI weights at the basic (218) item level.
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From page 254... ...
that the total expenditure of households implied by CEX and PCE weights is drifting further apart, perhaps by as much as 1 percent a year. One should not jump to the conclusion that these differentials imply an accurate PCE and an inaccurate CEX, but the wide discrepancies clearly warrant further investigation since both sets of expenditure weights cannot be correct.
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From page 255... ...
A major advantage of the CEX weights is that they are derived directly from reported household expenditures. One benefit of this direct reporting is that it allows household characteristics to be linked to expenditure information and, in turn, subpopulation indexes such as the CPI-E and CPI-W to be calculated.
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From page 256... ...
The CPI has traditionally determined these quantities from a 3-year span of CEX data; current weights reflect expenditure shares calculated from the 1993-1995 surveys, with immediately prior weights based on the 1982-1984 surveys. In 1998 BLS announced that it would update and apply 1999-2000 expenditure weights effective January 2002 and revise these weights every 2 years, instead of roughly every 10, as has been its prior practice (see the "Technical Notes" at the end of the chapter for additional details about the CEX)
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From page 257... ...
The decision to update CPI-U and CPI-W expenditure weights every 2 years beginning in 2002 was based on a tradeoff between timeliness and concern about "chain drift," which can occur when the price indexes of non-identical items must be linked.3 BLS agreed with critics (such as Boskin et al., 1996) that the weights should be updated more often than every decade or so as in the past, but little theory or empirical evidence existed to provide guidance on the optimal frequency of updates.
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From page 258... ...
One can infer though that the 30,000 figure refers to the desired sample size to be used by BLS when it uses 2 years of CEX data to establish expenditure-base quantities; if so, the Conference Board is really recommending an increase from the current annual effective CEX sample size of 5,870 to double that of the proposed 7,500, to 15,000 per year.
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From page 259... ...
For the superlative measures, you use two years' worth of data, so with a 50 percent increase in sample size, we would have about the same precision in the weights." But there is no reference to the targeted level of accuracy, nor of the impact of the increase in sample size on the precision of the current CPI computation. The commissioner's statement merely says that the increase in sample size will enable BLS to estimate a CPI with the similar variance characteristics as those of the current CPI computation.
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From page 260... ...
To see the impact of an increase in the sample size of the CEX, consider an extreme case in 1998 the 12-month price change in the apparel CPI had a conditional standard error of 0.00811844 and an unconditional standard error of 0.00997372 for a ratio of 1.22853. Doubling the CEX sample size would have reduced this ratio to 1.120107.
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From page 261... ...
Many of the issues have already been addressed to varying degrees by the BLS and others. Improving the CEX will involve continued assessment of the effectiveness of the interview and diary survey approaches, what methodologies minimize underreporting of purchases or attrition from a diary panel, the appropriate universe of households and goods and services to be covered, and the role of incentives programs in increasing survey accuracy and reducing nonresponse.
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From page 262... ...
Assuming different expenditure weights apply to each, a much larger CEX sample will be required. The Point of Purchase Survey A seconc' major survey input to the CPI is the POPS, which is used to determine which outlets BLS data collectors will visit in the C&S survey to record actual prices.6 The POPS produces outlet-specific expenditure information for item categories so that a sample of those outlets can be selected with a probability proportional to consumer use.
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From page 263... ...
BLS continues to explore methods for improving the quality of price data. The most visible experimental activities involve expanding the use of electronic data, which may offer such advantages as larger samples, reduced variances, more accurate determination of in-store sales shares, more timely publication of superlative indexes, and the potential to use unit pricing.
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From page 264... ...
combining POPS and CEX into an integrated survey that contains expenditure and outlet-use data at detailed product levels, along with household demographic information needed for subgroup indexes; and (2) moving toward scanner-based collection systems, which could be used to improve the existing surveys or as a component of an alternative.
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From page 265... ...
The CEX sample may be more representative of the population since it is based on samples drawn from census household files, not on random digital telephone sampling as is the POPS. Each CEX household also reports on a larger share of total household expenditures than does a POPS respondent.
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From page 266... ...
Yet the real advantage of a survey that links prices paid for specific items to the purchasing households is that, in principle, from such data one could calculate average prices paid for specific items by different household types. The big question is what size household sample would be required to support such an index or, more realistically, how big a sample would be needed to make an experimental pilot project work.
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From page 267... ...
, whereas the current quote sampling method only records prices for a small fraction of items on store shelves. CPI price quotes are drawn from items at outlets made eligible by selection in the most recent POPS sample.
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From page 268... ...
For cereal in New York, the sample size of price quotes is more than 1,400 times the number in the traditional CPI data. However this translates into a reduction of standard errors, such an increase should create greater index precision.
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From page 269... ...
cite marketing literature indicating that there is substantial consumer substitution across weeks in response to price changes and advertising. Also, their own data on canned tuna show a high degree of price variation and substantial response of consumer demand to that variation (Feenstra and Shapiro, 2001~.
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From page 270... ...
Regarding quote timing, CPI and scanner data cover similar periods within the month; scanner data have the advantage of covering weekends and holidays, which CPI data do not. · For many cases, scanner data cover the entire domain of products within any given item strata and area cell, which is important for methodological consistency.
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From page 271... ...
Household-Based Scanner Technology Household scanner technology could be adopted in one of three ways: it could be used to improve the accuracy and coverage of the current household surveys, particularly the CEX; it could also be used in a combined CEX/POPS survey; or, more ambitiously, it could be the technical centerpiece of a household-based panel survey that produces both expenditure share and price information that would be used to produce household or subgroup indexes. Any plan to
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From page 272... ...
Potential to Enhance Accuracy of the CEX and POPS Even before considering price issues, household scanner devices could increase the quality of current surveys by improving the accuracy of households' documentation of purchases. It could produce more accurate and detailed weighting from the item strata to sub-ELI levels.
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From page 273... ...
273 . shows substantial pitfalls of mechanically applying price indexes to such data." The superlative index is intended to capture reductions in the cost of living as consumers substitute goods that have decreased in price for those that have increased.
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From page 274... ...
Research into the accuracy and sample size of the CEX should be a high priority among topic areas relating to the data collection process for the CPI. The panel concluded that it is likely that CEX estimates of consumer expenditure shares are biased, perhaps seriously.
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From page 275... ...
to test impact on statistical properties of price data. We note that in 2002 BLS will consider ScanData recommendations about solving geography issues and about funding requests needed to expand the project and incorporate scanner-based subindexes into the CPI.
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From page 276... ...
. Experimental development of subgroup indexes: performance of the household-based price data experiment, likely involving household scanner technology, to produce subgroup indexes that capture variation in both expenditure weights and prices paid.
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From page 277... ...
is multiplied by a dollar-weighted average of price relatives, with the dollar expenditure weights being those of the quantity-base period quantities priced at the previous period's prices and the price relative taken with respect to the price in the previous period. One should note that what is reported monthly by BLS is the period-to-period index, namely PLt/PLt-]
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From page 278... ...
Finally, the item strata are subdivided into entrylevel items (ELIs) ; as of 2000, there were 282 ELIs.l4 The following is an example of this hierarchy of goods (Bureau of Labor Statistics, 1997a)
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From page 279... ...
Until January 1999, BLS calculated Rthz—an estimate of the relative price change in basic area h, item stratum z, from period t- l to period t using the formula when the samples of items within the item strata are selected with each unit having a probability proportional to quantity, or the formula ~ WhiPhi Rat _ i£Z hiPh, i£z ~ WhiPhi IPhi Rt _ i£z hiPh, IPhi i£z when the samples of items within the item strata are selected with each unit having a probability proportional to expenditure. In both forms the weights W reflect the probability that item i in item stratum z is selected to be priced in basic area h in the first of these the weights Whi are essentially qahi /~c; in the second the weights Whi are essentially pahi qahi /~hi, where Phi iS the probability that item i in item stratum z is selected to be priced in basic area h.
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From page 280... ...
Consumer Expenditure Survey The CEX, sponsored by BLS and conducted by the Bureau of the Census, is a national probability sample of household units. It is comprised of two parts, a Quarterly Interview Panel Survey and a Diary Survey.
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From page 281... ...
POPS category 129, hardware items, hand tools, and other materials for minor home repairs, contains the other four ELIs of item stratum 2401 24011, 24012, 24015, and 24016; it also contains ELI 24041, miscellaneous supplies and equipment; ELI 32043, other hardware; and ELI 32044, nonpowered hand tools. For the purpose of outlet selection, the BLS has aggregated the POPS categories into eight categories and the PSUs into ten groups (see Bureau of Labor Statistics, 1997a:~.
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From page 282... ...
To give readers a sense of the number of outlets selected, the largest number is nine, in the POPS foods and beverages category, PSU group Philadelphia. At a selected outlet a BLS field representative uses a multistage probability selection procedure for selecting the specific item to be priced among those that the outlet sells that fall within the designated-for-pricing ELI definition.
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