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International Monetary Fund

defined within the consumption classification used in the CPI. Samples of prices are collected within each elementary aggregate, so that elementary aggregates serve as strata for sampling purposes. 20.2 Data on the expenditures, or quantities, of the different goods and services are typically not available within an elementary aggregate. As there are no quantity or expenditure weights, most of the index number theory outlined in Chapters 15 to 19 is not directly applicable. As was noted in Chapter 1 , an elementary price index is a more primitive concept that relies

Brian Graf

between and within the different CPI samples, since badly allocated samples may lead to unnecessarily high sampling errors. Dalén and Ohlsson (1995) show that the error resulting from item sampling is relatively high compared with the error resulting from outlet sampling. In this case, it is worthwhile increasing the sample size of items and reducing the sample size of outlets. Beisteiner (2008) stresses the importance of allocating resources to those areas where the effect on the quality of the all-items CPI is maximized, especially to goods and services with a

Brian Graf

: Geographic (locations) and outlet samples: all places and outlets where a product is sold Product samples: all goods and services available for purchase Time: the subperiods of the index 4.3 In practice, CPI sampling follows a multistage approach. The universe of products is structured by first selecting the items within the different categories of the expenditure classification. For each item of the CPI classification, one or more representative varieties can then be sampled. For the geographic and outlet samples, specific locations for price collection

Brian Graf

.32 Price analysts can compare the prices collected in the field to those calculated from the scanner data sets. This analysis provides insight into any biases introduced to the CPI from point-in-time pricing compared with unit values. An analysis of the variety’s revenue and quantities sold can be used by the NSO price analysts to highlight where CPI samples could be improved. Using Scanner Data Sets to Replace Field-Collected Prices 10.33 In most countries, the majority of the prices used to compile the CPI are collected by visits to sampled retail businesses

Brian Graf

stop responding. Including new outlets also tends to facilitate the inclusion of new products in the CPI. Sampled price The price collected for a sampled product in a specific outlet at a specific time, sometimes described as a price quote. Sample rotation Limiting the length of time that outlets and products are included in the price surveys by dropping a proportion of them, or possibly all of them, after a certain period of time and selecting a new sample of outlets and products. Rotation is designed to keep the sample up to date. Sampling

Brian Graf

in average prices paid. 7.76 The simple use of the overlap method creates a distinct bias in the CPI as it overstates price inflation in ignoring the switch to cheaper prices. The benefits of the digital economy, in this respect, would be absent from the official statistics. CPI compilers would point to the integration of such outlets into the CPI sample, but this would only conceal the defciency of the methodology; indeed, it might be argued that based on the CPI data the new online outlets have no impact on consumer prices. 7.77 The unit value’s assumption

Brian Graf

web scraping. The appearance and disappearance of products from a CPI sample has the potential to bias the index unless any corresponding changes in the quality of the sample are dealt with appropriately. This poses a problem for the calculation of indices incorporating all (or most) web-scraped prices due to a large number of prices these data sets contain, the high rate of product attrition, and the tendency for products to have unusual price movements near the start and end of their life cycles. One approach for dealing with this problem is to estimate the

Brian Graf

Abstract

1.1 Chapter 1 provides a self-contained overview of the uses and the basic steps for compiling the consumer price index (CPI). More than just a summary of the chapters to follow, Chapter 1 guides the reader through the compilation process and highlights best practices that are explained in greater detail in subsequent chapters. The flow of the chapter follows the different steps needed to develop and maintain a CPI program that better reflects the standards and best practices set out in the Manual.