Measuring Consumption Growth: The Impact of New and Better Products

This study describes how the U.S. government measures real consumption growth and how it tries to take account of a complicating factor: that the goods and services offered to consumers change over time; new products are introduced and old products are improved. The 1996 Boskin Commission critique of this government methodology is described, along with the changes made in response to that critique. Also described is recent research related to how real consumption growth should be measured in the presence of new and better products. The views expressed herein are those of the author and not necessarily those of the Federal Reserve Bank of Minneapolis or the Federal Reserve System. (BLS). To construct the CPIs, the BLS collects prices on about 80,000 goods every month (U.S. Department of Labor 1997). Prices for this basket of goods are collected from around 23,000 outlets (supermarkets, department stores, gasoline stations, hospitals, and so on), 50,000 landlords and tenants, and 20,000 owner-occupants across more than 80 urban areas. The outlets are sampled probabilistically based on household point-of-purchase surveys, and the items within each outlet are sampled according to estimates of their relative sales. The BLS periodically rotates its samples of outlets and items to try to keep pace with changing household buying patterns. Unfortunately, the BLS does not use sample rotation to try to measure the change in the number of distinct varieties of goods, %∆N. Combined with an estimate of the parameter λ, such data could be used to estimate the value of changing variety, a hard-to-measure and currently unmeasured piece of (2). . . . And in Quality The BLS aims to measure growth in prices with quality growth taken into account. That is, it tries to net out quality increases to arrive at growth in quality-adjusted prices. If the BLS succeeds, then the BEA measure of real consumption growth fully incorporates quality growth. To adjust for quality growth, the BLS uses both passive and active methods. Its passive matched-model and overlap methods attempt to measure price changes only for goods of unchanging quality. Its active methods—primarily hedonics, but also manufacturer cost estimates in the case of cars—try to measure differences in quality between new and old goods. Table 1 provides an overview of when and where the BLS currently applies these methods. The matched-model method strives to measure the price of the same item from month to month. When this method succeeds, only goods of identical quality are compared across time. To implement this method, field agents collecting price quotes use detailed checklists of item attributes to try to ensure that they are pricing the same items in consecutive months. To illustrate how the matched-model method works, suppose a particular Toyota Camry is included among the items in the CPI, along with a more expensive, higher quality Lexus car model. Suppose further that the attributes of these car models remain unchanged over a certain period, but that households become richer, so that the number of units sold rises for the Lexus relative to the Camry. The BLS matched-model method never compares the prices of the Camry and Lexus. It compares only the prices of Camrys to Camrys and the prices of Lexuses to Lexuses. Since the Lexus is more expensive than the Camry, the shift in market shares is associated with rising consumer spending on cars. Because the shift does not affect the BLS price index for cars, the higher spending contributes to higher BEA real consumption. No new varieties or greater quantities of cars are involved, so such growth represents measured quality growth rather than variety growth or quantity growth. As this example illustrates, the matchedmodel method is a passive way of allowing quality growth to flow into real consumption growth. To extend the example, suppose a new car model (say, a Saturn) arrives on the market and wins market share at the expense of less expensive, lower quality models. The new Saturn will not be immediately incorporated into the CPI basket. Still, in the matched-model method, the higher consumer spending from the switch to Saturns shows up as real consumption growth because the BLS keeps tracking the prices of the (now less popular) lower quality models. When the new Saturn model is later rotated into BLS samples at the expense of lesser selling models, the BLS does not register the difference in their prices as inflation. The BLS instead uses the overlap method, collecting prices on incoming and outgoing items for an overlapping month. In the overlap month the BLS registers inflation as that on the outgoing item. In subsequent months, it registers inflation as that on the incoming item. In using this overlap method, the BLS implicitly assumes that price differences equal quality differences for incoming versus outgoing items. The BLS is passively measuring quality growth as the price difference between the old and new items in the sample. Unfortunately, the matched-model and overlap methods are not always feasible because items are frequently discontinued by the outlets in between BLS sample rotations. Moulton and Moses (1997, p. 323) report that around 30 percent of items that are not scheduled for BLS sample rotation are discontinued by retailers in a typical year. For these items, the BLS is forced to compare distinct items and sift quality-adjusted price differences from raw price differences. When an outlet discontinues an item, field agents search for the closest substitute at the outlet. Table 2 presents monthly item substitution rates over 1995–97 for different categories of consumption, tabulated from unpublished BLS data. As Table 2 shows, forced item substitutions were more common for goods than for services during this period. They were also more common for apparel, as one might expect with changing styles. The BLS compares the attributes of the replacement item to those of the discontinued item and classifies the replacement as either comparable or noncomparable to the discontinued item. Table 2 provides noncomparable substitution rates alongside the overall substitution rates. Noncomparable substitutions were ten times more common for durables than for services. The BLS deemed 48 percent of substitutions (1.5 percent of monthly price quotes) noncomparable over 1995–97. As noted, forced substitutions occur for around 30 percent of items in a typical year. This is very close to what one would find if all items had an equal and constant 3 percent monthly probability of being replaced. If all items had a constant 1.5 percent monthly noncomparable substitution rate, then 17 percent of items would be replaced with products of dissimilar quality in a typical year.6 The price of a comparable substitute enters the CPI without adjustment because the BLS deems the new item as essentially the same as the old item. In contrast, a noncomparable substitute enters the CPI with quality adjustments. In some categories, the BLS makes active quality adjustments, for example, using hedonic estimates.7 Over 1995–97, direct quality adjustments were made for 19 percent of all item substitutions. They were most common for trucks, cars, and men’s and women’s suits. For other noncomparable substitutions (29 percent of all substitutions), the BLS adjusted for quality passively, scaling the replacement’s price so that the change in quality-adjusted price matched the inflation rate of items not substituted within the same category. This link method of quality adjustment usually involved scaling down the replacement item’s price, with the replacement item inferred to be of higher quality than the discontinued item. How large are BLS quality adjustments? For 1995, Moulton and Moses (1997, p. 341) report that quality adjustments amounted to 1.76 percentage points. CPI inflation was 2.16 percent in that year, so it would have been 3.92 percent without the quality adjustments. These are the active quality adjustments the BLS made for noncomparable item substitutions. In addition to these, the BLS madepassivequalityadjustmentsusing thematched-model method and, during sample rotations, the overlap method. To infer combined quality adjustments, at item substitutions and at other times, one needs to compare the average unit prices paid by consumers to the BLS price index. In Bils and Klenow 2001b, we estimate average unit prices paid for 66 durable goods over 1980–96 from the consumer expenditure survey (CES) conducted by the BLS. For these goods, which represented about 12 percent of the CPI, average unit prices rose 1.46 percentage points faster than BLS price indexes over 1980–96 (Bils and Klenow 2001b, p. 1020). This is smaller than the Moulton and Moses (1997) estimate of 1.76 percentage points of active quality adjustments alone in 1995, suggesting that 1995 may have been a year of unusually large active quality adjustments. Another possibility is that active quality adjustments were smaller for the 66 durable goods examined than for the average item in the CPI, but this seems unlikely given the high rate of product turnover for durables relative to other items. Although these estimates are sketchy, they underscore the possibility that most of the official 2.4 percent annual measured growth in real consumption per capita over 1960–2000 came from growth in quality. Critiquing U.S. Methodology . . . The Boskin Commission (U.S. Congress 1996) concluded that the CPI overstated inflation in the cost of living and recommended a number of changes to BLS procedures. The commission estimated the upward bias in CPI inflation at 1.1 percentage points per year, with a range of plausible values between 0.8 and 1.6 percentage points. Usefully, the commission subdivided its bias estimate into component sources, reproduced here in Table 3.