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<\/p>\nWashington, DC…The Consumer Price Index for All Urban Consumers (CPI-U) increased 0.6 percent in January on a seasonally adjusted basis, the U.S. Bureau of Labor Statistics reported today. Over the last 12 months, the all items index increased 7.5 percent before seasonal adjustment. Increases in the indexes for food, electricity, and shelter were the largest contributors to the seasonally adjusted all items increase. The food index rose 0.9 percent in January following a 0.5-percent increase in December. The energy index also increased 0.9 percent over the month, with an increase in the electricity index being partially offset by declines in the gasoline index and the natural gas index.<\/p>\n
<\/p>\n
The index for all items less food and energy rose 0.6 percent in January, the
\nsame increase as in December. This was the seventh time in the last 10 months
\nit has increased at least 0.5 percent. Along with the index for shelter, the
\nindexes for household furnishings and operations, used cars and trucks, medical
\ncare, and apparel were among many indexes that increased over the month. <\/p>\n
The all items index rose 7.5 percent for the 12 months ending January, the
\nlargest 12-month increase since the period ending February 1982. The all items
\nless food and energy index rose 6.0 percent, the largest 12-month change since
\nthe period ending August 1982. The energy index rose 27.0 percent over the last
\nyear, and the food index increased 7.0 percent. <\/p>\n
Table A. Percent changes in CPI for All Urban Consumers (CPI-U): U.S. city
\n average<\/p>\n
Seasonally adjusted changes from
\n preceding month
\n Un-
\n adjusted
\n 12-mos.
\n July Aug. Sep. Oct. Nov. Dec. Jan. ended
\n 2021 2021 2021 2021 2021 2021 2022 Jan.
\n 2022<\/p>\n
All items……………… .5 .3 .4 .9 .7 .6 .6 7.5
\n Food…………………. .7 .4 .9 .9 .8 .5 .9 7.0
\n Food at home…………. .6 .4 1.2 .9 .9 .4 1.0 7.4
\n Food away from home (1).. .8 .4 .5 .8 .6 .6 .7 6.4
\n Energy……………….. 1.6 1.9 1.2 3.7 2.4 .9 .9 27.0
\n Energy commodities……. 2.4 2.5 1.2 4.7 4.2 1.3 -.6 39.9
\n Gasoline (all types)…. 2.5 2.5 1.1 4.6 4.5 1.3 -.8 40.0
\n Fuel oil (1)………… .6 -2.1 3.9 12.3 3.5 -2.4 9.5 46.5
\n Energy services………. .7 1.2 1.2 2.4 .2 .3 2.9 13.6
\n Electricity…………. .2 1.0 .6 1.4 .2 .5 4.2 10.7
\n Utility (piped) gas
\n service………….. 2.2 1.6 2.9 5.9 .3 -.3 -.5 23.9
\n All items less food and
\n energy…………….. .3 .2 .3 .6 .5 .6 .6 6.0
\n Commodities less food and
\n energy commodities…. .4 .4 .3 1.1 .9 1.2 1.0 11.7
\n New vehicles………… 1.5 1.2 1.3 1.3 1.2 1.2 .0 12.2
\n Used cars and trucks…. .0 -1.2 -.5 2.5 2.4 3.3 1.5 40.5
\n Apparel…………….. .1 .3 -.7 .6 .7 1.1 1.1 5.3
\n Medical care
\n commodities (1)…… .2 -.2 .3 .6 .1 .0 .9 1.4
\n Services less energy
\n services………….. .3 .1 .2 .4 .4 .3 .4 4.1
\n Shelter…………….. .4 .2 .4 .5 .5 .4 .3 4.4
\n Transportation services -.9 -1.2 -1.0 .2 .7 .0 1.0 5.6
\n Medical care services… .2 .2 .2 .4 .3 .3 .6 2.7<\/p>\n
1 Not seasonally adjusted.<\/p>\n
Food<\/p>\n
The food index increased 0.9 percent in January. The food at home index increased
\n1.0 percent over the month after rising 0.4 percent in December. Five of the six
\nmajor grocery store food group indexes increased in January. The index for cereals
\nand bakery products increased the most, rising 1.8 percent over the month. The
\nindex for other food at home increased 1.6 percent in January, while the index
\nfor dairy and related products rose 1.1 percent. The fruits and vegetables index
\nrose 0.9 percent over the month, and the meats, poultry, fish, and eggs index
\nincreased 0.3 percent. The only grocery store group index not to increase in
\nJanuary was the index for nonalcoholic beverages, which was unchanged.<\/p>\n
The food away from home index rose 0.7 percent in January following an increase
\nof 0.6 percent in December. The index for full service meals and the index for
\nlimited service meals both also rose 0.7 percent over the month.<\/p>\n
The food at home index rose 7.4 percent over the last 12 months. All of the six
\nmajor grocery store food group indexes increased over the period. By far the
\nlargest increase was that of the index for meats, poultry, fish, and eggs, which
\nrose 12.2 percent over the year. The index for dairy and related products
\nincreased 3.1 percent, the smallest 12-month increase among the groups. <\/p>\n
The index for food away from home rose 6.4 percent over the last year, the largest
\n12-month increase since January 1982. The index for limited service meals rose 8.0
\npercent over the last 12 months, and the index for full service meals rose 7.1
\npercent. The index for food at employee sites and schools, in contrast, declined
\n46.9 percent over the past 12 months, reflecting widespread free lunch programs.<\/p>\n
Energy<\/p>\n
The energy index increased 0.9 percent in January. The electricity index rose
\nsharply in January, increasing 4.2 percent. The gasoline index fell 0.8 percent
\nin January after rising rapidly in the autumn of 2021. (Before seasonal adjustment,
\ngasoline prices rose 0.1 percent in January.) The index for natural gas also
\ndeclined in January, falling 0.5 percent after declining 0.3 percent in December. <\/p>\n
The energy index rose 27.0 percent over the past 12 months with all major energy
\ncomponent indexes increasing. The gasoline index rose 40.0 percent over the last
\nyear, despite declining in January. The index for natural gas rose 23.9 percent
\nover the last 12 months, and the index for electricity rose 10.7 percent.<\/p>\n
All items less food and energy<\/p>\n
The index for all items less food and energy rose 0.6 percent in January, the
\nsame increase as December. The shelter index increased 0.3 percent in January as
\nthe rent index increased 0.5 percent and the owners\u2019 equivalent rent index rose
\n0.4 percent. The index for household furnishings and operations rose 1.3 percent
\nover the month following a 1.1-percent increase in December. The used cars and
\ntrucks index rose 1.5 percent in January, a deceleration from the 3.3-percent
\nincrease reported in December.<\/p>\n
The medical care index rose 0.7 percent in January. The index for hospital
\nservices increased 0.5 percent and the index for prescription drugs rose 1.3
\npercent, while the index for physicians\u2019 services declined 0.1 percent. Other
\nindexes that rose in January include recreation (+0.9 percent), apparel (+1.1
\npercent), personal care (+1.0 percent), airline fares (+2.3 percent), and
\neducation (+0.2 percent).<\/p>\n
Only a few indexes decreased in January; among those that did were lodging away
\nfrom home (-3.9 percent) and wireless telephone services (-0.1 percent). The
\nindex for new vehicles was unchanged over the month.<\/p>\n
The index for all items less food and energy rose 6.0 percent over the past 12
\nmonths. Major contributors to this increase include shelter (+4.4 percent) and
\nused cars and trucks (+40.5 percent). However, the increase is broad-based, with
\nvirtually all component indexes showing increases over the past 12 months. <\/p>\n
Not seasonally adjusted CPI measures<\/p>\n
The Consumer Price Index for All Urban Consumers (CPI-U) increased 7.5 percent
\nover the last 12 months to an index level of 281.148 (1982-84=100). For the month,
\nthe index increased 0.8 percent prior to seasonal adjustment. <\/p>\n
The Consumer Price Index for Urban Wage Earners and Clerical Workers (CPI-W)
\nincreased 8.2 percent over the last 12 months to an index level of 276.296
\n(1982-84=100). For the month, the index rose 0.9 percent prior to seasonal
\nadjustment. <\/p>\n
The Chained Consumer Price Index for All Urban Consumers (C-CPI-U) increased 7.1
\npercent over the last 12 months. For the month, the index increased 0.8 percent
\non a not seasonally adjusted basis. Please note that the indexes for the past 10
\nto 12 months are subject to revision.
\n_______________
\nThe Consumer Price Index for February 2022 is scheduled to be released on Thursday,
\nMarch 10, 2022 at 8:30 a.m. (ET).<\/p>\n
Technical Note<\/p>\n
Brief Explanation of the CPI<\/p>\n
The Consumer Price Index (CPI) measures the change in prices paid by consumers for
\ngoods and services. The CPI reflects spending patterns for each of two population
\ngroups: all urban consumers and urban wage earners and clerical workers. The all
\nurban consumer group represents about 93 percent of the total U.S. population. It
\nis based on the expenditures of almost all residents of urban or metropolitan
\nareas, including professionals, the self-employed, the poor, the unemployed, and
\nretired people, as well as urban wage earners and clerical workers. Not included
\nin the CPI are the spending patterns of people living in rural nonmetropolitan
\nareas, farming families, people in the Armed Forces, and those in institutions,
\nsuch as prisons and mental hospitals. Consumer inflation for all urban consumers
\nis measured by two indexes, namely, the Consumer Price Index for All Urban Consumers
\n(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
\nbased on the expenditures of households included in the CPI-U definition that meet
\ntwo requirements: more than one-half of the household’s income must come from
\nclerical or wage occupations, and at least one of the household’s earners must
\nhave been employed for at least 37 weeks during the previous 12 months. The CPI-W
\npopulation represents about 29 percent of the total U.S. population and is a subset
\nof the CPI-U population.<\/p>\n
The CPIs are based on prices of food, clothing, shelter, fuels, transportation,
\ndoctors\u2019 and dentists\u2019 services, drugs, and other goods and services that people
\nbuy for day-to-day living. Prices are collected each month in 75 urban areas across
\nthe country from about 6,000 housing units and approximately 22,000 retail
\nestablishments (department stores, supermarkets, hospitals, filling stations, and
\nother types of stores and service establishments). All taxes directly associated
\nwith the purchase and use of items are included in the index. Prices of fuels and
\na few other items are obtained every month in all 75 locations. Prices of most
\nother commodities and services are collected every month in the three largest
\ngeographic areas and every other month in other areas. Prices of most goods and
\nservices 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
\naverage. For the CPI-U and CPI-W, separate indexes are also published by size of
\ncity, by region of the country, for cross-classifications of regions and population-
\nsize classes, and for 23 selected local areas. Area indexes do not measure
\ndifferences in the level of prices among cities; they only measure the average change
\nin prices for each area since the base period. For the C-CPI-U, data are issued only
\nat the national level. The CPI-U and CPI-W are considered final when released, but the
\nC-CPI-U is issued in preliminary form and subject to three subsequent quarterly
\nrevisions. <\/p>\n
The index measures price change from a designed reference date. For most of the CPI-U
\nand the CPI-W, the reference base is 1982-84 equals 100. The reference base for the
\nC-CPI-U is December 1999 equals 100. An increase of 7 percent from the reference base,
\nfor example, is shown as 107.000. Alternatively, that relationship can also be
\nexpressed as the price of a base period market basket of goods and services rising
\nfrom $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
\nbased upon a sample of retail prices and not the complete universe of all prices.
\nBLS calculates and publishes estimates of the 1-month, 2-month, 6-month, and 12-month
\npercent change standard errors annually for the CPI-U. These standard error estimates
\ncan be used to construct confidence intervals for hypothesis testing. For example, the
\nestimated standard error of the 1-month percent change is 0.03 percent for the U.S.
\nall items CPI. This means that if we repeatedly sample from the universe of all retail
\nprices using the same methodology, and estimate a percentage change for each sample,
\nthen 95 percent of these estimates will be within 0.06 percent of the 1-month percentage
\nchange based on all retail prices. For example, for a 1-month change of 0.2 percent in
\nthe all items CPI-U, we are 95 percent confident that the actual percent change based
\non all retail prices would fall between 0.14 and 0.26 percent. For the latest data,
\nincluding information on how to use the 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
\nlevel of the index in relation to its base period, while percent changes are not. The
\nfollowing table shows an example of using index values to calculate percent changes:<\/p>\n
Item A Item B Item C
\n Year I 112.500 225.000 110.000
\n Year II 121.500 243.000 128.000
\n Change in index points 9.000 18.000 18.000
\n Percent 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<\/p>\n
Use 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
\nare used to revise the previous 5 years of seasonally adjusted data. The factors are
\navailable at www.bls.gov\/cpi\/tables\/seasonal-adjustment\/seasonal-factors-2022.xlsx. For
\nmore information on data revision scheduling, please see the Factsheet on Seasonal Adjustment
\nat www.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 of
\nthe 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 70 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 calculate
\nnew seasonal factors for seasonally adjusted series and apply them to the last 5 years of data.
\nSeasonally adjusted indexes beyond the last 5 years of data are considered to be final and not
\nsubject to revision. For January 2022, revised seasonal factors and seasonally adjusted indexes
\nfor 2017 to 2021 were calculated and published. For series which are directly adjusted using the
\nCensus X-13ARIMA-SEATS seasonal adjustment software, the seasonal factors for 2021 will be applied
\nto data for 2022 to produce the seasonally adjusted 2022 indexes. Series which are indirectly
\nseasonally adjusted by summing seasonally adjusted component series have seasonal factors which
\nare 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 criteria.
\nUsing these criteria, BLS economists determine whether a series should change its status from “not
\nseasonally adjusted” to “seasonally adjusted”, or vice versa. If any of the 81 components of the U.S.
\ncity average all items index change their seasonal adjustment status from seasonally adjusted to not
\nseasonally adjusted, not seasonally adjusted data will be used in the aggregation of the dependent
\nseries for the last 5 years, but the seasonally adjusted indexes before that period will not be
\nchanged. For 2022, 36 of the 81 components of the U.S. city average all items index are not seasonally
\nadjusted.<\/p>\n","protected":false},"excerpt":{"rendered":"
Washington, DC…The Consumer Price Index for All Urban Consumers (CPI-U) increased 0.6 percent in January on a seasonally adjusted basis, the U.S. Bureau of Labor Statistics reported today. Over the last 12 months, the all items index increased 7.5 percent before seasonal adjustment. Increases in the indexes for food, electricity, and shelter were the largest […]<\/p>\n","protected":false},"author":1,"featured_media":136004,"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":[3,20,149,5,1],"tags":[],"class_list":["post-136003","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-business","category-featured","category-financial","category-government","category-news","last_archivepost"],"jetpack_featured_media_url":"https:\/\/new.thepinetree.net\/wp-content\/uploads\/2022\/02\/Jan22CPI.jpg","jetpack_sharing_enabled":true,"jetpack-related-posts":[],"_links":{"self":[{"href":"https:\/\/new.thepinetree.net\/index.php?rest_route=\/wp\/v2\/posts\/136003","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=136003"}],"version-history":[{"count":1,"href":"https:\/\/new.thepinetree.net\/index.php?rest_route=\/wp\/v2\/posts\/136003\/revisions"}],"predecessor-version":[{"id":136005,"href":"https:\/\/new.thepinetree.net\/index.php?rest_route=\/wp\/v2\/posts\/136003\/revisions\/136005"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/new.thepinetree.net\/index.php?rest_route=\/wp\/v2\/media\/136004"}],"wp:attachment":[{"href":"https:\/\/new.thepinetree.net\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=136003"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/new.thepinetree.net\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=136003"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/new.thepinetree.net\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=136003"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}