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<\/a><\/p>\nThe index for all items less food and energy rose 0.5 percent in February
\nfollowing a 0.6-percent increase the prior month. The shelter index was by far
\nthe biggest factor in the increase, with a broad set of indexes also
\ncontributing, including those for recreation, household furnishings and
\noperations, motor vehicle insurance, personal care, and airline fares.<\/p>\n
The all items index rose 7.9 percent for the 12 months ending February. The
\n12-month increase has been steadily rising and is now the largest since the
\nperiod ending January 1982. The all items less food and energy index rose 6.4
\npercent, the largest 12-month change since the period ending August 1982. The
\nenergy index rose 25.6 percent over the last year, and the food index increased
\n7.9 percent, the largest 12-month increase since the period ending July 1981.<\/p>\n
Table A. Percent changes in CPI for All Urban Consumers (CPI-U): U.S. city
\naverage<\/p>\n
Seasonally adjusted changes from
\npreceding month
\nUn-
\nadjusted
\n12-mos.
\nAug. Sep. Oct. Nov. Dec. Jan. Feb. ended
\n2021 2021 2021 2021 2021 2022 2022 Feb.
\n2022<\/p>\n
All items……………… .3 .4 .9 .7 .6 .6 .8 7.9
\nFood…………………. .4 .9 .9 .8 .5 .9 1.0 7.9
\nFood at home…………. .4 1.2 .9 .9 .4 1.0 1.4 8.6
\nFood away from home (1).. .4 .5 .8 .6 .6 .7 .4 6.8
\nEnergy……………….. 1.9 1.2 3.7 2.4 .9 .9 3.5 25.6
\nEnergy commodities……. 2.5 1.2 4.7 4.2 1.3 -.6 6.7 37.9
\nGasoline (all types)…. 2.5 1.1 4.6 4.5 1.3 -.8 6.6 38.0
\nFuel oil (1)………… -2.1 3.9 12.3 3.5 -2.4 9.5 7.7 43.6
\nEnergy services………. 1.2 1.2 2.4 .2 .3 2.9 -.4 12.3
\nElectricity…………. 1.0 .6 1.4 .2 .5 4.2 -1.1 9.0
\nUtility (piped) gas
\nservice………….. 1.6 2.9 5.9 .3 -.3 -.5 1.5 23.8
\nAll items less food and
\nenergy…………….. .2 .3 .6 .5 .6 .6 .5 6.4
\nCommodities less food and
\nenergy commodities…. .4 .3 1.1 .9 1.2 1.0 .4 12.3
\nNew vehicles………… 1.2 1.3 1.3 1.2 1.2 .0 .3 12.4
\nUsed cars and trucks…. -1.2 -.5 2.5 2.4 3.3 1.5 -.2 41.2
\nApparel…………….. .3 -.7 .6 .7 1.1 1.1 .7 6.6
\nMedical care
\ncommodities (1)…… -.2 .3 .6 .1 .0 .9 .3 2.5
\nServices less energy
\nservices………….. .1 .2 .4 .4 .3 .4 .5 4.4
\nShelter…………….. .2 .4 .5 .5 .4 .3 .5 4.7
\nTransportation services -1.2 -1.0 .2 .7 .0 1.0 1.4 6.6
\nMedical care services… .2 .2 .4 .3 .3 .6 .1 2.4<\/p>\n
1 Not seasonally adjusted.<\/p>\n
Food<\/p>\n
The food index increased 1.0 percent in February as the food at home index increased
\n1.4 percent over the month. All six major grocery store food group indexes increased
\nin February. The index for fruits and vegetables had the largest increase, rising 2.3
\npercent, its largest monthly increase since March 2010. The index for fresh fruits
\nincreased 3.7 percent over the month, and the index for fresh vegetables rose 1.3
\npercent. The index for dairy and related products rose 1.9 percent, its largest
\nmonthly increase since April 2011. The index for nonalcoholic beverages increased
\n1.6 percent in February.<\/p>\n
The index for meats, poultry, fish, and eggs increased 1.2 percent in February as all
\nof its major component indexes increased. The index for cereals and bakery products
\nrose 1.1 percent and the index for other food at home increased 0.8 percent over the
\nmonth.<\/p>\n
The food away from home index rose 0.4 percent in February after increasing 0.7
\npercent in January. The index for full service meals rose 0.6 percent and the index
\nfor limited service meals increased 0.3 percent.<\/p>\n
The food at home index rose 8.6 percent over the last 12 months, the largest 12-month
\nincrease since the period ending April 1981. The index for meats, poultry, fish, and
\neggs increased 13.0 percent over the last year as the index for beef rose 16.2 percent.
\nThe other major grocery store food group indexes also rose over the past year, with
\nincreases ranging from 5.2 percent (dairy and related products) to 8.2 percent (other
\nfood at home).<\/p>\n
The index for food away from home rose 6.8 percent over the last year, the largest
\n12-month increase since December 1981. The index for limited service meals rose 8.0
\npercent over the last 12 months, and the index for full service meals rose 7.5 percent.
\nThe index for food at employee sites and schools, in contrast, declined 40.7 percent
\nover the past 12 months, reflecting widespread free lunch programs.<\/p>\n
Energy<\/p>\n
The energy index rose 3.5 percent in February following a 0.9-percent increase in
\nJanuary. The gasoline index rose sharply in February, increasing 6.6 percent after
\nfalling 0.8 percent in January. (Before seasonal adjustment, gasoline prices rose 5.4
\npercent in February.) The index for natural gas increased in February, rising 1.5
\npercent after declining 0.5 percent in January. In contrast, the electricity index,
\nwhich rose sharply in January, declined 1.1 percent in February.<\/p>\n
The energy index rose 25.6 percent over the past 12 months with all major energy
\ncomponent indexes increasing. The index for gasoline rose 38.0 percent over the last
\nyear and the index for natural gas rose 23.8 percent. The index for electricity rose
\n9.0 percent for the 12 months ending February.<\/p>\n
All items less food and energy<\/p>\n
The index for all items less food and energy rose 0.5 percent in February. The shelter
\nindex increased 0.5 percent in February and accounted for over 40 percent of the
\nmonthly increase in the all items less food and energy index. The rent index increased
\n0.6 percent in February and the owners\u2019 equivalent rent index rose 0.4 percent. The
\nindex for lodging away from home rose 2.2 percent over the month after declining in
\nJanuary.<\/p>\n
The recreation index increased 0.7 percent in February following a 0.9-percent increase
\nin January. The index for household furnishings and operations also continued to rise,
\nincreasing 0.6 percent in February following larger increases in recent months. The
\nindex for motor vehicle insurance rose 1.2 percent over the month after a 0.9-percent
\nadvance in January. The personal care index increased 1.2 percent in February, its
\nlargest ever monthly increase. The index for airline fares rose 5.2 percent in February,
\nand the index for apparel increased 0.7 percent.<\/p>\n
The medical care index rose 0.2 percent in February. The index for prescription drugs
\nrose 0.3 percent, but the indexes for hospital services and for physicians\u2019 services
\nboth declined 0.1 percent.<\/p>\n
The index for new vehicles increased 0.3 percent in February after being unchanged the
\nprior month. The index for used cars and trucks, which rose sharply in recent months,
\ndeclined in February, falling 0.2 percent, one of the very few indexes to show a
\ndecline in February.<\/p>\n
The index for all items less food and energy rose 6.4 percent over the past 12 months,
\nwith virtually all of its major component indexes rising over the span. The shelter
\nindex rose 4.7 percent over the last 12 months, its largest 12-month increase since May
\n1991. Several transportation indexes showed large increases over the past year,
\nincluding used cars and trucks (+41.2 percent), new vehicles (+12.4 percent), and
\nairline fares (+12.7 percent).<\/p>\n
Not seasonally adjusted CPI measures<\/p>\n
The Consumer Price Index for All Urban Consumers (CPI-U) increased 7.9 percent over the
\nlast 12 months to an index level of 283.716 (1982-84=100). For the month, the index
\nincreased 0.9 percent prior to seasonal adjustment.<\/p>\n
The Consumer Price Index for Urban Wage Earners and Clerical Workers (CPI-W) increased
\n8.6 percent over the last 12 months to an index level of 278.943 (1982-84=100). For the
\nmonth, the index rose 1.0 percent prior to seasonal adjustment.<\/p>\n
The Chained Consumer Price Index for All Urban Consumers (C-CPI-U) increased 7.5 percent
\nover the last 12 months. For the month, the index increased 0.9 percent on a not
\nseasonally adjusted basis. Please note that the indexes for the past 10 to 12 months are
\nsubject to
\nrevision.
\n_______________
\nThe Consumer Price Index for March 2022 is scheduled to be released on Tuesday, April 12,
\n2022 at 8:30 a.m. (ET).<\/p>\n
Technical Note<\/p>\n
Brief Explanation of the CPI
\nThe Consumer Price Index (CPI) measures the change in prices paid by consumers for goods
\nand services. The CPI reflects spending patterns for each of two population groups: all
\nurban consumers and urban wage earners and clerical workers. The all urban consumer group
\nrepresents about 93 percent of the total U.S. population. It is based on the expenditures
\nof almost all residents of urban or metropolitan areas, including professionals, the self
\n-employed, the poor, the unemployed, and retired people, as well as urban wage earners
\nand clerical workers. Not included in the CPI are the spending patterns of people living
\nin rural nonmetropolitan areas, farming families, people in the Armed Forces, and those
\nin institutions, such as prisons and mental hospitals. Consumer inflation for all urban
\nconsumers is measured by two indexes, namely, the Consumer Price Index for All Urban
\nConsumers (CPI-U) and the Chained Consumer Price Index for All Urban Consumers (C-CPI-U).
\nThe Consumer Price Index for Urban Wage Earners and Clerical Workers (CPI-W) is based on
\nthe expenditures of households included in the CPI-U definition that meet two requirements:
\nmore than one-half of the household’s income must come from clerical or wage occupations,
\nand at least one of the household’s earners must have been employed for at least 37 weeks
\nduring the previous 12 months. The CPI-W population represents about 29 percent of the
\ntotal U.S. population and is a subset of the CPI-U population.<\/p>\n
The CPIs are based on prices of food, clothing, shelter, fuels, transportation, doctors\u2019
\nand dentists\u2019 services, drugs, and other goods and services that people buy for day-to-day
\nliving. Prices are collected each month in 75 urban areas across the country from about
\n6,000 housing units and approximately 22,000 retail establishments (department stores,
\nsupermarkets, hospitals, filling stations, and other types of stores and service
\nestablishments). All taxes directly associated with the purchase and use of items are
\nincluded in the index. Prices of fuels and a few other items are obtained every month in
\nall 75 locations. Prices of most other commodities and services are collected every month
\nin the three largest geographic areas and every other month in other areas. Prices of most
\ngoods and services are obtained by personal visit, telephone call, or web collection by the
\nBureau\u2019s trained representatives.<\/p>\n
In calculating the index, price changes for the various items in each location are
\naggregated using weights, which represent their importance in the spending of the
\nappropriate population group. Local data are then combined to obtain a U.S. city average.
\nFor the CPI-U and CPI-W, separate indexes are also published by size of city, by region of
\nthe country, for cross-classifications of regions and population-size classes, and for 23
\nselected local areas. Area indexes do not measure differences in the level of prices among
\ncities; they only measure the average change in prices for each area since the base period.
\nFor the C-CPI-U, data are issued only at the national level. The CPI-U and CPI-W are
\nconsidered final when released, but the C-CPI-U is issued in preliminary form and subject
\nto three subsequent quarterly revisions.<\/p>\n
The index measures price change from a designed reference date. For most of the CPI-U and
\nthe CPI-W, the reference base is 1982-84 equals 100. The reference base for the C-CPI-U is
\nDecember 1999 equals 100. An increase of 7 percent from the reference base, for example,
\nis shown as 107.000. Alternatively, that relationship can also be expressed as the price
\nof a base period market basket of goods and services rising from $100 to $107.<\/p>\n
Sampling Error in the CPI<\/p>\n
The CPI is a statistical estimate that is subject to sampling error because it is based
\nupon a sample of retail prices and not the complete universe of all prices. BLS calculates
\nand publishes estimates of the 1-month, 2-month, 6-month, and 12-month percent change
\nstandard errors annually for the CPI-U. These standard error estimates can be used to
\nconstruct confidence intervals for hypothesis testing. For example, the estimated standard
\nerror of the 1-month percent change is 0.03 percent for the U.S. all items CPI. This means
\nthat if we repeatedly sample from the universe of all retail prices using the same
\nmethodology, and estimate a percentage change for each sample, then 95 percent of these
\nestimates will be within 0.06 percent of the 1-month percentage change based on all retail
\nprices. For example, for a 1-month change of 0.2 percent in the all items CPI-U, we are 95
\npercent confident that the actual percent change based on all retail prices would fall
\nbetween 0.14 and 0.26 percent. For the latest data, including information on how to use
\nthe estimates of standard error, see
\nhttps:\/\/www.bls.gov\/cpi\/tables\/variance-estimates\/home.htm.<\/p>\n
Calculating Index Changes<\/p>\n
Movements of the indexes from 1 month to another are usually expressed as percent changes
\nrather than changes in index points, because index point changes are affected by the level
\nof the index in relation to its base period, while percent changes are not. The following
\ntable shows an example of using index values to calculate percent changes:<\/p>\n
Item A Item B Item C
\nYear I 112.500 225.000 110.000
\nYear II 121.500 243.000 128.000
\nChange in index points 9.000 18.000 18.000
\nPercent change 9.0\/112.500 x 100 = 8.0 18.0\/225.000 x 100 = 8.0 18.0\/110.000 x 100 = 16.4
\nUse of Seasonally Adjusted and Unadjusted Data<\/p>\n
The Consumer Price Index (CPI) produces both unadjusted and seasonally adjusted data.
\nSeasonally adjusted data are computed using seasonal factors derived by the X-13ARIMA-SEATS
\nseasonal adjustment method. These factors are updated each February, and the new factors are
\nused to revise the previous 5 years of seasonally adjusted data. The factors are available
\nat www.bls.gov\/cpi\/tables\/seasonal-adjustment\/seasonal-factors-2022.xlsx. For more
\ninformation on data revision scheduling, please see the Factsheet on Seasonal Adjustment at
\nwww.bls.gov\/cpi\/seasonal-adjustment\/questions-and-answers.htm and the Timeline of Seasonal
\nAdjustment Methodological Changes at
\nwww.bls.gov\/cpi\/seasonal-adjustment\/timeline-seasonal-adjustment-methodology-changes.htm.<\/p>\n
For analyzing short-term price trends in the economy, seasonally adjusted changes are usually
\npreferred since they eliminate the effect of changes that normally occur at the same time and
\nin about the same magnitude every year\u2014such as price movements resulting from weather events,
\nproduction cycles, model changeovers, holidays, and sales. This allows data users to focus on
\nchanges that are not typical for the time of year. The unadjusted data are of primary interest
\nto consumers concerned about the prices they actually pay. Unadjusted data are also used
\nextensively for escalation purposes. Many collective bargaining contract agreements and pension
\nplans, for example, tie compensation changes to the Consumer Price Index before adjustment for
\nseasonal variation. BLS advises against the use of seasonally adjusted data in escalation
\nagreements because seasonally adjusted series are revised annually.<\/p>\n
Intervention Analysis<\/p>\n
The Bureau of Labor Statistics uses intervention analysis seasonal adjustment (IASA) for some
\nCPI series. Sometimes extreme values or sharp movements can distort the underlying seasonal
\npattern of price change. Intervention analysis seasonal adjustment is a process by which the
\ndistortions caused by such unusual events are estimated and removed from the data prior to
\ncalculation of seasonal factors. The resulting seasonal factors, which more accurately represent
\nthe seasonal pattern, are then applied to the unadjusted data.<\/p>\n
For example, this procedure was used for the motor fuel series to offset the effects of the 2009
\nreturn to normal pricing after the worldwide economic downturn in 2008. Retaining this outlier
\ndata during seasonal factor calculation would distort the computation of the seasonal portion
\nof the time series data for motor fuel, so it was estimated and removed from the data prior to
\nseasonal adjustment. Following that, seasonal factors were calculated based on this \u201cprior
\nadjusted\u201d data. These seasonal factors represent a clearer picture of the seasonal pattern in
\nthe data. The last step is for motor fuel seasonal factors to be applied to the unadjusted data.<\/p>\n
For the seasonal factors introduced for January 2022, BLS adjusted 72 series using intervention
\nanalysis seasonal adjustment, including selected food and beverage items, motor fuels, electricity,
\nand vehicles.<\/p>\n
Revision of Seasonally Adjusted Indexes<\/p>\n
Seasonally adjusted data, including the U.S. city average all items index levels, are subject to
\nrevision for up to 5 years after their original release. Every year, economists in the CPI
\ncalculate new seasonal factors for seasonally adjusted series and apply them to the last 5 years
\nof data. Seasonally adjusted indexes beyond the last 5 years of data are considered to be final
\nand not subject to revision. For January 2022, revised seasonal factors and seasonally adjusted
\nindexes for 2017 to 2021 were calculated and published. For series which are directly adjusted
\nusing the Census X-13ARIMA-SEATS seasonal adjustment software, the seasonal factors for 2021 will
\nbe applied to data for 2022 to produce the seasonally adjusted 2022 indexes. Series which are
\nindirectly seasonally adjusted by summing seasonally adjusted component series have seasonal
\nfactors which are derived and are therefore not available in advance.<\/p>\n
Determining Seasonal Status<\/p>\n
Each year the seasonal status of every series is reevaluated based upon certain statistical
\ncriteria. Using these criteria, BLS economists determine whether a series should change its
\nstatus from “not seasonally adjusted” to “seasonally adjusted”, or vice versa. If any of the 81
\ncomponents of the U.S. city average all items index change their seasonal adjustment status from
\nseasonally adjusted to not seasonally adjusted, not seasonally adjusted data will be used in the
\naggregation of the dependent series for the last 5 years, but the seasonally adjusted indexes
\nbefore that period will not be changed. For 2022, 22 of the 81 components of the U.S. city
\naverage all items index are seasonally adjusted.<\/p>\n","protected":false},"excerpt":{"rendered":"
Washington, DC…The Consumer Price Index for All Urban Consumers (CPI-U) increased 0.8 percent in February on a seasonally adjusted basis after rising 0.6 percent in January, the U.S. Bureau of Labor Statistics reported today. Over the last 12 months, the all items index increased 7.9 percent before seasonal adjustment. Increases in the indexes for gasoline, […]<\/p>\n","protected":false},"author":1,"featured_media":137382,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_cbd_carousel_blocks":"[]","jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[3,20,5,1],"tags":[],"class_list":["post-137381","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-business","category-featured","category-government","category-news","last_archivepost"],"jetpack_featured_media_url":"https:\/\/new.thepinetree.net\/wp-content\/uploads\/2022\/03\/12-month-percentage-chan.jpeg","jetpack_sharing_enabled":true,"jetpack-related-posts":[],"_links":{"self":[{"href":"https:\/\/new.thepinetree.net\/index.php?rest_route=\/wp\/v2\/posts\/137381","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/new.thepinetree.net\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/new.thepinetree.net\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/new.thepinetree.net\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/new.thepinetree.net\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=137381"}],"version-history":[{"count":1,"href":"https:\/\/new.thepinetree.net\/index.php?rest_route=\/wp\/v2\/posts\/137381\/revisions"}],"predecessor-version":[{"id":137383,"href":"https:\/\/new.thepinetree.net\/index.php?rest_route=\/wp\/v2\/posts\/137381\/revisions\/137383"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/new.thepinetree.net\/index.php?rest_route=\/wp\/v2\/media\/137382"}],"wp:attachment":[{"href":"https:\/\/new.thepinetree.net\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=137381"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/new.thepinetree.net\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=137381"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/new.thepinetree.net\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=137381"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}