sense for households to underreport—show large weight differentials that might support this notion (Triplett, 1997). For other components, such as rent or auto purchases, for which reporting rates are known to be high, it is encouraging that the ratios of CEX to PCE weights are close to 1.
There are ways in which the PCE data system appears more developed. The PCE has the advantage that it is based on large surveys of businesses (the most prominent being the Census Bureau’s Retail Trade Surveys) that generally keep careful records and that rely less on respondent memory than does the CEX. Triplett (1997:16) does note a “birth bias” in the establishment surveys that arises because there is no mechanism for bringing new businesses into the sampling frame quickly. However, data from the censuses of manufacturers, retail trade, and service industries allow PCE component weights to be revised periodically and benchmarked every 5 years, which surely corrects some reporting and other biases. The benchmarking resets the allocation of purchases by commodity among business, government, and households and updates commodity lists. Furthermore, the BEA methodology for keeping track of inputs and outputs includes cross-checks that impose consistency on the data.
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. To produce the PCE weights, business and government spending must be subtracted out of sales data. Thus, the PCE is an indirect measure, calculated residually as final goods and services minus purchases made by nonconsumer sectors. Triplett (1997:16) notes that it is especially difficult to calculate consumption shares at more refined item levels because sales to consumers are not always distinguishable from sales to businesses and government: “The finer the level of detail, the more likely that the long chain of computations necessary to reach the CPE’s indirect estimate of consumer spending will have cumulative errors that affect the totals.” Even so, it seems implausible that estimates of business purchases of consumers goods could be off by enough to generate the kind of ratios between NIPA and CEX weights that are now produced.
Difficulties associated with separating business from consumer purchases are compounded by the fact that the PCE covers a wider scope of goods and services than does the CEX. For instance, PCE coverage includes elements of government consumption, such as Medicare and Medicaid, the employer-paid portion of medical insurance, financial services, expenditures by nonprofit institutions, and the value of certain goods and services received in kind by households (Clark, 1999). As discussed throughout this report, the CPI currently covers only out-of-pocket expenditures by urban households. All told, about 25 percent of PCE spending is not reflected in the CPI. This, in itself, redistributes expenditure shares substantially. For instance, the medical care category (since it is not limited to out-of-pocket expenditures) gets a much higher weight in the PCE—