consumer price index

An index of prices used to measure the change in the cost of basic goods and services in comparison with a fixed base period. Also called cost-of-living index.

A measure that examines the weighted average of prices of a basket of consumer goods and services, such as transportation, food and medical care. The CPI is calculated by taking price changes for each item in the predetermined basket of goods and averaging them; the goods are weighted according to their importance. Changes in CPI are used to assess price changes associated with the cost of living.

Sometimes referred to as "headline inflation".

Investopedia Says:
The U.S. Bureau of Labor Statistics measures two kinds of CPI statistics: CPI for urban wage earners and clerical workers (CPI-W), and the chained CPI for all urban consumers (C-CPI-U). Of the two types of CPI, the C-CPI-U is a better representation of the general public, because it accounts for about 87% of the population.

CPI is one of the most frequently used statistics for identifying periods of inflation or deflation. This is because large rises in CPI during a short period of time typically denote periods of inflation and large drops in CPI during a short period of time usually mark periods of deflation.

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Federal government measure of the cost of living, also called the cost-of-living index. The Consumer Price Index is used as an economic indicator, measuring the rate of inflation by monitoring monthly and yearly price changes for major groups of consumer expenditures (e.g., food and beverages, housing, apparel, transportation, medical services, recreation, education, communication). Changes are also reported for individual items within those groups. The CPI is broken out by all U.S. Consumers, all urban consumers, and some local areas. The CPI is also broken out by hourly paid urban wage earners and clerical workers (CPI-W) versus other urban consumers (CPI-U). The CPI is expressed as a measurement against a base period. In 1999, the base period was 1982-1984. The price index for all items sold in the base period is 100 and the CPI at the start of 1999 was 163.9. For example, if a family's average expenses for apparel were $100 in 1984, they would have to spend $163.90 in 1999 to get the equivalent value in goods. Many union contracts require wage increases according to increases in the CPI.

The most widely known of many such measures of price levels and inflation that are reported to the U.S. Government. It measures and compares, from month to month, the total cost of a statistically determined "typical market basket" of goods and services consumed by U.S. Households.
Example: The Consumer Price Index for 2002 stood at 179.9. Compared to the base period of 1982-1984, prices were 79.9% higher.

Measure of price level computed by the Bureau of Labor Statistics on a monthly basis. It is the ratio of the cost of specific consumer items in any one year to the cost of those items in the base period, 1982-1984 = 100. Because the CPI includes things consumers buy regularly, it is frequently called the cost of living index. The so-called market basket, covered by the index, includes items such as food, clothing, automobiles, homes, and fees to doctors.

The Consumer Price Index (CPI) provides a standardized method for comparing the average level of prices faced by the consumers and households of a nation over time. Price-level information is vital to a wide range of personal, government, and business decision makers. The CPI focuses solely on the prices faced by consumers and does not attempt to reflect prices faced by all buying entities in a country. Nevertheless, it is the most commonly used price-level indicator in a nation. It is the basis for the calculation of a country's inflation rate.

Computation

The Bureau of Labor Statistics (BLS) publishes CPI data monthly. BLS workers collect price data on a set market basket of goods and services in selected cities across the country each month. The market basket includes hundreds of goods and services typically purchased by consumers. The price data is then weighted to represent the mix of goods and services typically purchased by consumers. The mix of goods and services and the weights are based on the Consumer Expenditure Survey, a national survey of the spending habits of 29,000 families (BLS, "How BLS Measures"). The decennial census of the population is used for selection of the urban areas included in the monthly surveys.

The CPI is computed by dividing the weighted price of the market basket in a time period by the weighted price of the market basket in a designated base time period. The resulting ratio times 100 yields an index with a value of 100 for the base time period. CPI values above or below 100 indicate that the price level is higher or lower than it was during the base period. For example, an index value of 140 indicates that the average price level is 40 percent higher than it was in the base year.

The prices of hundreds of goods and services are surveyed each month. The goods and services are organized into eight main groups: food and beverage, housing, apparel, transportation, medical care, recreation, education and communication, and other goods and services.

Each month the BLS publishes numerous CPIs based on the data collected. The two main CPI series are the CPI-U (Consumer Price Index for All Urban Consumers) and the CPI-W (Consumer Price Index for Urban Wage Earners and Clerical Workers) Separate indices are published for twenty-six selected urban areas and four geographic regions of the country. There are also indices for three classes of cities (population of over 1.5 million, mid-sized to small metropolitan areas, and nonmetropolitan areas) and for categories of goods and services.

Measurement Issues

The CPI provides a general approximation of the price level faced by consumers in a given time period. It is not designed to measure the exact price level faced by any one consumer. The BLS collects data only in urban areas. Thus the CPI does not attempt to provide a measure of rural price levels. However, the CPI-U should be serviceable for approximately 87 percent of the U.S. population (BLS, "Guide to Available.") A two-week lag time exists between the completion of data collection and the publication of CPI data. The measure has limitations. The computational methodology has been gradually adjusted over time to allow for more accurate measurement of changing price levels. Measurement issues include index bias due to product innovation and quality changes that affect prices and consumption patterns, as well as uneven price changes across retail outlets and geographic areas.

Historically, the CPI has been calculated as a Laspeyres index, or an index based on a fixed market basket of goods and services. This has been criticized as an inaccurate approach because it does not allow for changing consumption patterns. Consumption patterns may change due to the availability of new products, changing features of current products, changing consumer preferences, or changes in the relative prices of goods and services. The impact of the availability of new products on purchasing patterns is exemplified by products such as videocassette recorders and microwave ovens, which were not available for consumer purchase until the late 1970s but became common household purchases in less than a decade. The emergence of audio CDs and CD players reduced purchases of audio-cassette tapes.

Price changes due to changes in product quality or features can be seen in the development of the manual typewriter, electric typewriter, and word processor. Adjustments are made in the computation of the CPI for the impact of quality changes on price. Also, periodic adjustments in the market basket have been made every eight to twelve years to allow for changing consumption patterns due to new products. This creates a situation in which price-level comparisons may be more accurate when made over relatively short periods of time rather than over many years or decades during which the nature and mix of goods and services in the market basket changed considerably. The base year is also changed periodically. For example, in January 1988 the CPI base year was changed from 1967 100 to 1982-1984 100.

Beginning with January 1999 data, the BLS changed to a geometric-mean-estimator method of indexing. This method does not employ the Laspeyres fixed market basket; rather, it allows consumers to adjust purchases within broad categories of goods and services due to changes in the relative prices of the goods or services within each category. The consensus of experts was that the Laspeyres method led to a CPI which systematically overestimated the price level actually paid by consumers, because consumers would substitute away from goods that increased in price in favor of similar goods with lower increases in price. The geometric-mean-estimator method was adopted to reduce this overestimation. As part of this change, the BLS reports that CPI expenditure weights are to be updated on a regular two-year schedule (BLS, "Future Schedule").

During a year the prices of many goods and services fluctuate because of seasonal factors, such as increases in supply affecting vegetable prices during harvest season. The BLS also publishes monthly seasonally adjusted CPI measures, which factor out the monthly variation due to the season of the year.

The CPI does not provide any explanation for price-level changes, nor does it forecast future price levels. However, historical CPI data are used extensively by analysts in research on these issues.

Historical Trend

The CPI tracks an ongoing trend of increasing prices in the United States. When making comparisons of the CPI over time, it is important to make sure that all data use the same base year.

Related Measures

The CPI is not the only measure of price level published by the government. Other common price indexes include a producer price index, which tracks the average prices producers pay for inputs, and the GDP deflator, which includes not only consumer prices but also the prices paid by other purchasers such as investors and the government.

Several other measures are based directly on the CPI. A country's inflation rate is the annual rate of change in its CPI. Also, purchasing power indices are based on CPI data. Typically a purchasing power index is the reciprocal of a price index. In essence, the price index relates how much it would cost to purchase the same group of goods and services compared to a base-time period. A purchasing power index reflects the percentage of the base-period group of goods and services that could be purchased at current prices if income were constant.

Uses

Households, businesses, and governments use price-level data in a variety of ways. One of the most common uses is to adjust other statistics for the changes in price level. The resulting price-adjusted measures go by several terms including: real, in constant dollars, in (list base year) dollars, or deflated. For example, if an individual received a 10 percent raise while the CPI rose 3 percent, the individual would have a 7 percent increase in real income. Data which are not adjusted for price-level changes go by the descriptive term nominal. Real measures are commonly used in media reports and by decision makers. Other examples of real measures are real gross domestic product, real interest rates, real exchange rates, and real government purchases.

Individuals and households rarely make direct use of the CPI, although they use CPI-based information frequently. Examples of this include comparisons of the cost of living in different cities, planning how much income will be needed to provide a comparable standard of living in retirement, negotiating with employers for raises, and determining the real return received on savings.

Businesses use the CPI extensively in forecasting future average price levels and consumer expenditures. The expected price level also becomes an important issue in negotiating escalator clauses in long-term contracts. Labor contracts and pension plans may include cost-of-living adjustment (COLA) clauses that tie wage or pension increases to CPI increases. International business decision makers closely monitor differences in the inflation rates of relevant countries.

Many branches of government use the CPI. A stable price level is one of the three main goals of economic stability, and the CPI is the main measuring tool to assess a nation's progress toward this goal. Thus both fiscal and monetary policy makers use this statistic. Levels of many government expenditures, such as transfer payment levels and government employee salaries, are tied to changes in the CPI. The legal system may integrate CPI adjustments into alimony or child-support agreements. In the 1980s the U.S. began to index progressive income tax brackets to the inflation rate. Under an indexed income tax system, an individual will end up in a higher marginal income tax bracket only if his or her income rises more rapidly than the CPI.

Bibliography

Bureau of Labor Statistics. "BLS to Maintain Current Reference Base of 1982-84 100 for Most CPI Index series." Public Briefings on the 1998 CPI Revision. http://stats.bls.gov/cpibase1.htm. 1999.

Bureau of Labor Statistics. "Consumer Price Indexes." http://stats.bls.gov/epi0698c.htm. 1999.

Bureau of Labor Statistics. "Future Schedule for Expenditure Weight Updates in the Consumer Price Index." http://stats.bls.gov/cpiupdt.htm. 1999.

Bureau of Labor Statistics. "Guide to Available CPI Data." http://stats.bls.gov/cpifact8.htm. 1999.

Bureau of Labor Statistics. "How BLS Measures Changes in Consumer Prices." http://stats.bls.gov/cpifact2.htm.1999.

Bureau of Labor Statistics. "Measurement Issues in the Consumer Price Index." JEC Report: Quality and New Products Bias. http://stats.bls.gov/cpigm697.htm. 1999.

Bureau of Labor Statistics. "Planned Change in the Consumer Price Index Formula April 16, 1998." http://stats.bls.gov/epigm02.htm. 1999.

"ESBR: Prices." Economic Statistics Briefing Room. http://www.whitehouse.gov/fsbr/prices.html. 1999.

[Article by: C. BETH HAYNES]

For more information on consumer price index, visit Britannica.com.

A computation made and issued monthly by the Bureau of Labor Statistics of the federal Labor Department that attempts to track the price level of designated goods and services purchased by the average consumer.

The consumer price index (CPI) is an indicator of the rate of inflation in the economy because it measures changes in the cost of maintaining a particular standard of living.

An index published by the government each month of prices for a representative sample of goods and services. The consumer price index was formerly known as the cost-of-living index.

"CPI" redirects here. For other uses, see CPI (disambiguation).

A consumer price index (CPI) is a measure estimating the average price of consumer goods and services purchased by households. A consumer price index measures a price change for a constant market basket of goods and services from one period to the next within the same area (city, region, or nation).^[1] It is a price index determined by measuring the price of a standard group of goods meant to represent the typical market basket of a typical urban consumer.^[2] Related, but different, terms are the United Kingdom's CPI, RPI, and RPIX. It is one of several price indices calculated by most national statistical agencies. The percent change in the CPI is a measure estimating inflation. The CPI can be used to index (i.e., adjust for the effect of inflation on the real value of money: the medium of exchange) wages, salaries, pensions, and 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.

Contents 1 Introduction 2 Weighting 2.1 Weights and sub-indices 2.2 Estimating weights 2.3 The nature of the data used for weighting 2.4 Reweighing 3 History 4 See also 5 References 6 External links

Introduction

Two basic types of data are needed 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 decades 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 yearly, 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 shirts sold in department stores in San Francisco), 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 true 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 the United States 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. 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.

Example: The prices of 95,000 items from 22,000 stores, and 35,000 rental units are added together and averaged. They are weighted this way: Housing: 41.4%, Food and Beverage: 17.4%, Transport: 17.0%, Medical Care: 6.9%, Other: 6.9%, Apparel: 6.0%, Entertainment: 4.4%. Taxes (43%) are not included in CPI computation. ^[3]

Weighting

Weights and sub-indices

Weights can be expressed as fractions or ratios summing to one, 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 reweighing to make them 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:

• 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.

Even with the necessary adjustments, the National Account estimates and Household Expenditure Surveys usually diverge.

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, 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.

Reweighing

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 reweighing 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 re-weightings only by including some digital cameras in the same elementary aggregate as film cameras.

History

Between 1971 and 1977, the United States CPI increased 47%.^[4]
In 2009 the Consumer Price Index fell for the first time since 1955. ^[5]

See also

• Consumer price index by country
• Core inflation
• Cost of living index
• FRED (Federal Reserve Economic Data)
• Harmonised Index of Consumer Prices (HICP)
• Hedonic regression
• Household final consumption expenditure (HFCE)
• GDP deflator
• Inflation adjustment
• List of economics topics
• Market basket (basket of goods)
• Personal consumption expenditures price index (PCEPI)
• Producer Price Index (PPI)
• Quality bias
• RPIX
• Substitution
• World inflation crisis

References

This article includes a list of references or external links, but its sources remain unclear because it has insufficient inline citations. Please help to improve this article by introducing more precise citations where appropriate. (October 2008)

This article needs additional citations for verification. Please help improve this article by adding reliable references. Unsourced material may be challenged and removed. (January 2009)

1. ^ "BLS Information". Glossary. U.S. Bureau of Labor Statistics Division of Information Services. February 28, 2008. http://www.bls.gov/bls/glossary.htm. Retrieved 2009-05-05. 
2. ^ Sullivan, Arthur; Steven M. Sheffrin (2003). Economics: Principles in action. Upper Saddle River, New Jersey: Pearson Prentice Hall. pp. 339. ISBN 0-13-063085-3. http://www.pearsonschool.com/index.cfm?locator=PSZ3R9&PMDbSiteId=2781&PMDbSolutionId=6724&PMDbCategoryId=&PMDbProgramId=12881&level=4. 
3. ^ Bloomberg Business News, Social Security Administration
4. ^ Frum, David (2000). How We Got Here: The '70s. New York, New York: Basic Books. p. 324. ISBN 0465041957. 
5. ^ Harper's Magazine http://harpers.org/archive/2009/04/WeeklyReview2009-04-21

External links

• ILO CPI manualThis large manual produced co-operatively by a number of international organizations is the standard work on the methods of compiling consumer price indexes and on the underlying economic and statistical theory.
• Is India Misleading on its Inflation figures? Read March Archives
• myCPI.info Project for establishing alternative CPI data based on users inputting and tracking their personal CPI.
• "The Consumer Price Index and index number purpose": A technical article by economist W.E. Diewert

Specific countries

• International:
  • Worldwide Consumer Price Index Per City User-Updated
  • User-updated International Price Index
• France:
  • Consumer Price Index, INSEE
  • A description of the French consumer price index (in French)
• Germany: Consumer prices, Federal Statistical Office of Germany
• Hong Kong: Hong Kong Consumer Price Index (CPI) - Census and Statistics Department
• Spain: Consumer Price Index, Instituto Nacional de Estadística
• New Zealand: Consumers price index from Statistics New Zealand
• Norway: Official statistics
• Sweden:
  • A Consumer Price Index for Sweden 1290-2006
  • A detailed account in English of the Swedish consumer price index
• United Kingdom:
  • National Statistics Online: Consumer Prices, UK Office for National Statistics
  • A detailed account of the UK index
• United States:
  • Consumer Price Index Home Page, U.S. Department of Labor, Bureau of Labor Statistics
  • A detailed account of the US index
  • Inflation Calculator
  • Historical US CPI chart, monthly data since 1947
  • Alternate non official CPI measures

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