Consumer price index

A consumer price index (CPI) is an index number measuring the average price of consumer goods and services purchased by households. It is one of several price indices calculated by national statistical agencies. The percent change in the CPI is a measure of inflation. The CPI can be used to index (i.e., adjust for the effects of inflation) wages, salaries, pensions, or regulated or contracted prices. The CPI is, along with the population census and the National Income and Product Accounts, one of the most closely watched national economic statistics.

Introduction
Two basic types of data are required to construct the CPI: price data and weighting data. The price data are collected for a sample of goods and services from a sample of sales outlets in a sample of locations for a sample of times. The weighting data are estimates of the shares of the different types of expenditure as fractions of the total expenditure covered by the index. These weights are usually based upon expenditure data obtained for sampled periods from a sample of households. Although some of the sampling is done using a sampling frame and probabilistic sampling methods, much is done in a commonsense way (purposive sampling) that does not permit estimation of confidence intervals. Therefore, the sampling variance is normally ignored, since a single estimate is required in most of the purposes for which the index is used. Stocks greatly affect this cause.

The index is usually computed monthly, or quarterly in some countries, as a weighted average of sub-indices for different components of consumer expenditure, such as food, housing, clothing, each of which is in turn a weighted average of sub-sub-indices. At the most detailed level, the elementary aggregate level, (for example, men's trousers sold in department stores in the Northwest), detailed weighting information is unavailable, so elementary aggregate indices are computed using an unweighted arithmetic or geometric mean of the prices of the sampled product offers. (However, the growing use of scanner data is gradually making weighting information available even at the most detailed level.) These indices compare prices each month with prices in the price-reference month. The weights used to combine them into the higher-level aggregates, and then into the overall index, relate to the estimated expenditures during a preceding whole year of the consumers covered by the index on the products within its scope in the area covered. Thus the index is a fixed-weight index, but rarely a Laspeyres index, since the weight-reference period of a year and the price-reference period, usually a more recent single month, do not coincide. It takes time to assemble and process the information used for weighting which, in addition to household expenditure surveys, may include trade and tax data.

Ideally, the weights would relate to the composition of expenditure during the time between the price-reference month and the current month. There is a large technical economics literature on index formulae which would approximate this and which can be shown to approximate what economic theorists call a true cost of living index. Such an index would show how consumer expenditure would have to move to compensate for price changes so as to allow consumers to maintain a constant standard of living. Approximations can only be computed retrospectively, whereas the index has to appear monthly and, preferably, quite soon. Nevertheless, in some countries, notably in North America and Sweden,the philosophy of the index is that it is inspired by and approximates the notion of a true cost of living (constant utility) index, whereas in most of Europe it is regarded more pragmatically. The coverage of the index may be limited. Consumers' expenditure abroad is usually excluded; visitors' expenditure within the country may be excluded in principle if not in practice; the rural population may or may not be included; certain groups such as the very rich or the very poor may be excluded. Black market expenditure and expenditure on illegal drugs and prostitution are often excluded for practical reasons, although the professional ethics of the statistician require objective description free of moral judgments. Saving and investment are always excluded, though the prices paid for financial services provided by financial intermediaries may be included along with insurance.

The index reference period, usually called the base year, often differs both from the weight-reference period and the price reference period. This is just a matter of rescaling the whole time-series to make the value for the index reference-period equal to 100. Annually revised weights are a desirable but expensive feature of an index, for the older the weights the greater is the divergence between the current expenditure pattern and that of the weight reference-period.

Weights and sub-indices
Weights can be expressed as fractions summing to unity, as percentages summing to 100 or as per mille numbers summing to 1000.

In the European Union's Harmonised Index of Consumer Prices, for example, each country computes some 80 prescribed sub-indices, their weighted average constituting the national Harmonised Index. The weights for these sub-indices will consist of the sum of the weights of a number of component lower level indexes. The classification is according to use, developed in a national accounting context. This is not necessarily the kind of classification that is most appropriate for a Consumer Price Index. Grouping together of substitutes or of products whose prices tend to move in parallel might be more suitable.

For some of these lower level indexes detailed weights within them may be available, allowing computations where the individual price observations can all be weighted. This may be the case, for example, where all selling is in the hands of a single national organisation which makes its data available to the index compilers. For most lower level indexes, however, the weight will consist of the sum of the weights of a number of elementary aggregate indexes, each weight corresponding to its fraction of the total annual expenditure covered by the index. An 'elementary aggregate' is a lowest-level component of expenditure, one which has a weight but within which, weights of its sub-components are usually lacking Thus, for example: Weighted averages of elementary aggregate indexes (e.g. for men’s shirts, raincoats, women’s dresses etc.) make up low level indexes (e.g. Outer garments),

Weighted averages of these in turn provide sub-indices at a higher, more aggregated level,(e.g. Clothing) and Weighted averages of the latter provide yet more aggregated sub-indices (e.g. Clothing and Footwear).

Some of the elementary aggregate indexes, and some of the sub-indexes can be defined simply in terms of the types of goods and/or services they cover, as in the case of such products as newspapers in some countries and postal services, which have nationally uniform prices. But where price movements do differ or might differ between regions or between outlet types, separate regional and/or outlet-type elementary aggregates are ideally required for each detailed category of goods and services, each with its own weight. An example might be an elementary aggregate for sliced bread sold in supermarkets in the Northern region.

Most elementary aggregate indexes are necessarily 'unweighted' averages for the sample of products within the sampled outlets. However in cases where it is possible to select the sample of outlets from which prices are collected so as to reflect the shares of sales to consumers of the different outlet types covered, self-weighted elementary aggregate indexes may be computed. Similarly, if the market shares of the different types of product represented by product types are known, even only approximately, the number of observed products to be priced for each of them can be made proportional to those shares.

Estimating weights
The outlet and regional dimensions noted above mean that the estimation of weights involves a lot more than just the breakdown of expenditure by types of goods and services, and the number of separately weighted indexes composing the overall index depends upon two factors:
 * 1) The degree of detail to which available data permit breakdown of total consumption expenditure in the weight reference-period by type of expenditure, region and outlet type.
 * 2) Whether there is reason to believe that price movements vary between these most detailed categories.

How the weights are calculated, and in how much detail, depends upon the availability of information and upon the scope of the index. In the UK the RPI does not relate to the whole of consumption, for the reference population is all private households with the exception of a) pensioner households that derive at least three-quarters of their total income from state pensions and benefits and b) “high income households” whose total household income lies within the top four per cent of all households. The result is that it is difficult to use data sources relating to total consumption by all population groups.

For products whose price movements can differ between regions and between different types of outlet:
 * The ideal, rarely realisable in practice, would consist of estimates of expenditure for each detailed consumption category, for each type of outlet, for each region.
 * At the opposite extreme, with no regional data on expenditure totals but only on population (e.g. 24% in the Northern region) and only national estimates for the shares of different outlet types for broad categories of consumption (e.g. 70% of food sold in supermarkets) the weight for sliced bread sold in supermarkets in the Northern region has to be estimated as the share of sliced bread in total consumption × 0.24 × 0.7.

The situation in most countries comes somewhere between these two extremes. The point is to make the best use of whatever data are available.

The nature of the data used for weighting
No firm rules can be suggested on this issue for the simple reason that the available statistical sources differ between countries. However, all countries conduct periodical Household Expenditure surveys and all produce breakdowns of Consumption Expenditure in their National Accounts. The expenditure classifications used there may however be different. In particular: Even with the necessary adjustments, the National Account estimates and Household Expenditure Surveys usually diverge.
 * Household Expenditure surveys do not cover the expenditures of foreign visitors, though these may be within the scope of a Consumer Price Index.
 * National Accounts include imputed rents for owner-occupied dwellings which may not be within the scope of a Consumer Price Index

The statistical sources required for regional and outlet-type breakdowns are usually weaker. Only a large-sample Household Expenditure survey can provide a regional breakdown. Regional population data are sometimes used for this purpose, but need adjustment to allow for regional differences in living standards and consumption patterns. Statistics of retail sales and market research reports can provide information for estimating outlet-type breakdowns, but the classifications they use rarely correspond to COICOP categories.

The increasingly widespread use of bar codes and scanners in shops has meant that detailed cash register printed receipts are provided by shops for an increasing share of retail purchases. This development makes possible improved Household Expenditure surveys, as Statistics Iceland has demonstrated. Survey respondents keeping a diary of their purchases need to record only the total of purchases when itemised receipts were given to them and keep these receipts in a special pocket in the diary. These receipts provide not only a detailed breakdown of purchases but also the name of the outlet. Thus response burden is markedly reduced, accuracy is increased, product description is more specific and point of purchase data are obtained, facilitating the estimation of outlet-type weights.

There are only two general principles for the estimation of weights: use all the available information and accept that rough estimates are better than no estimates.

Reweighting
Ideally, in computing an index, the weights would represent current annual expenditure patterns. In practice they necessarily reflect past expenditure patterns, using the most recent data available or, if they are not of high quality, some average of the data for more than one previous year. Some countries have used a three-year average in recognition of the fact that household survey estimates are of poor quality. In some cases some of the data sources used may not be available annually, in which case some of the weights for lower level aggregates within higher level aggregates are based on older data than the higher level weights.

Infrequent reweighting saves costs for the national statistical office but delays the introduction into the index of new types of expenditure. For example, subscriptions for Internet Service entered index compilation with a considerable time lag in some countries, and account could be taken of digital camera prices between reweightings only by including some digital cameras in the same elementary aggregate as film cameras.

United States


In the USA, CPI figures are prepared monthly by the Bureau of Labor Statistics of the United States Department of Labor.

The CPI-U includes expenditures by all urban consumers. The CPI-W includes expenditures by consumer units with clerical workers, sales workers, craft workers, operative, service workers, or laborers. Recently, the Chained Consumer Price Index C-CPI-U, a chained index, was introduced. The C-CPI-U tries to mitigate the substitution bias that is encountered in CPI-W and CPI-U by employing a Tornqvist formula and utilizing expenditure data in adjacent time periods in order to reflect the effect of any substitution that consumers make across item categories in response to changes in relative prices. The new measure, called a "superlative" index, is designed to be a closer approximation to a "cost-of- living" index than the other measures. The use of expenditure data for both a base period and the current period in order to average price change across item categories distinguishes the C-CPI-U from the existing CPI measures, which use only a single expenditure base period to compute the price change over time. In 1999, the BLS introduced a geometric mean estimator for averaging prices within most of the index’s item categories in order to approximate the effect of consumers’ responses to changes in relative prices within these item categories. The geometric mean estimator is used in the C-CPI-U in the same item categories in which it is now used in the CPI-U and CPI-W.

Sources of data
Prices for the goods and services used to calculate the CPI are collected in 87 urban areas throughout the country and from approximately 23,000 retail and service establishments. Data on rents are collected from about 50,000 landlords and tenants.

The weight for an item is derived from reported expenditures on that item as estimated by the Consumer Expenditure Survey. Prices are taken throughout the month.

The BLS numbers are available through:
 * Monthly news release. Consumer Price Index. Electronic access available.
 * Historical data in Handbook of Labor Statistics. Electronic access available.
 * Diskettes
 * "LABSTAT" database.

Major research in progress

 * Continuing research on technical improvements in the calculation of the CPI.
 * Continuing work on the next major weight revision of the CPI.

In 1996, the Boskin Commission found the CPI to be a biased measure, and gave a quantitative analysis of the bias. The Boskin critique helped to spur some changes in the U.S. CPI, although it was partially disputed by the BLS. Many of the changes were aimed at moving the CPI to a cost of living model which takes consumer substitutions into account and typically reduces the reported level of inflation.

Canada
Statistics Canada looks at all the payments and taxes paid by consumers in Canada and then eventually publishes the CPI figures and the data used in the calculation.

Colombia
The IPC, which stands for Indice de Precios al Consumidor (Consumer Price Index), is calculated and published on a monthly basis by Banco de la República de Colombia, the National Central Bank.

Eurozone
The European Central Bank publishes the Monetary Union Index of Consumer Prices (MUICP). It is a weighted average of price indices of member states. The method is a HICP or "Harmonized Index of Consumer Prices", where goods are split by final consumption; it is a seasonally adjusted chained index.

United Kingdom
The traditional measure of inflation in the UK for many years was the Retail Price Index, which was first calculated in the early 20th Century to evaluate the extent to which workers were affected by price changes during the first world war. An explicit inflation target was first set in October 1992 by then-Chancellor of the Exchequer Norman Lamont following the departure of the UK from the Exchange Rate Mechanism. Initially, the target was based on the RPIX, which is the RPI calculated excluding mortgage interest payments. This was felt to be a better measure of the effectiveness of macroeconomic policy. It was argued that if interest rates are used to curb inflation, then including mortgage payments in the inflation measure would be misleading. Until 1997, interest rates were set by the Treasury.

On winning power in May 1997, the New Labour government handed control over interest rates to the Bank of England, whose Monetary Policy Committee now sets rates on the basis of an inflation target set by the Chancellor. If in any month inflation is more than one percentage point off its target, the Governor of the Bank of England is required to write to the Chancellor explaining why. Mervyn King became the first Governor to do so in April 2007, when inflation ran at 3.1% against a target 2%.

Since 1996 the United Kingdom has also tracked a Consumer Price Index figure, and in December 2003 its inflation target was changed to one based on the CPI. The CPI target is currently 2%. Both the CPI and the RPI are published monthly by the Office for National Statistics.

Belgium
In Belgium, wages, pensions, house rent, insurance premiums, unemployment benefits, health insurance payments, etc. are by law tied to a consumer price index.

Mexico
The INPC, which stands for Indice Nacional de Precios al Consumidor (National Consumer Price Index in English), is calculated and published on a monthly basis by Banco de México, the Central Bank.

Sweden
The index is calculated and published by Statistics Sweden

Switzerland
Switzerland issues a monthly CPI calculation by the Swiss Federal Statistical Office.

Australia
The CPI is calculated and posted quarterly by the Australian Bureau of Statistics. Historical figures are available at the Reserve Bank of Australia website.

China
China's CPI is published by National Bureau of Statistics of China.

Israel
The Israeli CPI (Hebrew: מדד המחירים לצרכן Madad HaMechirim Latsarchan) is calculated and published by the Central Bureau of Statistics.

Ireland
Ireland's CPI is published by the Central Statistics Office Ireland.

Hong Kong
Hong Kong's CPI is published by the Census and Statistics Department.

New Zealand
New Zealands CPI is calculated and published quarterly by Statistics New Zealand from prices gathered in a range of surveys at 15 urban areas.