At the same time, demand for some products soared: pandemic-era stimulus programs left shoppers with extra cash to spend, and everyone wanted to buy the same types of things. More recently, inflation has been driven mostly by the cost of buying or renting a home. This is due to entirely different reasons, mainly that new homebuilding has been slow and older Americans are not moving out of their homes as frequently. Inflation has slowed since its peak, but that only means prices aren’t rising as quickly as before. The chance that prices actually fall are very slim, although we have seen price declines in products likes eggs and used cars. Still, the U.S. has made great progress. Reining in inflation has not led to a recession and widespread job loss.   Cooling inflation, while keeping unemployment at historically low levels, has been the ideal scenario, or what economists like to call a “soft landing.”

Brookings

The Fed has targeted an average inflation rate of 2% and will use the tools necessary to get the economy to that place

There’s no single culprit.  Early in the pandemic, there were fewer workers and disruptions in the availability of goods due to snarled shipping routes and shuttered childcare centers, among other factors.

Inflation

Inflation, the change in price of goods and services over time, is often confused with the cost of things.

Ben Harris Ben Harris Vice President and Director - Economic Studies

In response to economic inflation, 43% of participants reported inflation had “no effect” on their health, 11% reported concerns about personal finances, and only small proportions reported other negative psychosocial impacts. Collectively, these findings suggest many low-income veterans are resilient during major events. Further research is needed on long-term health effects of inflation on this population.

Home Journal of Community Health Article Self-reported Impacts of the COVID-19 Pandemic and Economic Inflation on the Well-being of Low-income U.S. Veterans Original Paper Published: 21 August 2023

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In response to the COVID-19 pandemic, 59% of participants reported the pandemic had “no effect” on their health, 7% reported increased social isolation, and small proportions of participants reported negative effects on physical and mental health.

rapid assessment procedures

psychosocial impacts

This study examined written self-reported impacts of the Coronavirus Disease-2019 (COVID-19) pandemic and the economic inflationary period on health from a national sample of 854 low-income U.S. veterans

Jack Tsai  ORCID: orcid.org/0000-0002-0329-648X1,2,3, Rachel Hird3 & Asha Collier2

Table 1. Summary of household respondents, fourth quarter 2021SurveyNumber of households in urban populationPercent in urban populationWage earnersAmericans 62 years of age and olderUnweightedWeightedUnweightedWeightedInterview Survey4,51522.424.137.534.1Diary Survey2,69423.825.539.533.5Source: U.S. Bureau of Labor Statistics.

U.S. Bureau of Labor Statistics

Notes 1 Joshua Klick and Anya Stockburger, “Experimental CPI for lower and higher income households,” Working Paper 537 (U.S. Bureau of Labor Statistics, March 8, 2021), https://www.bls.gov/osmr/research-papers/2021/pdf/ec210030.pdf; and Klick and Stockburger, “Inflation experiences for lower and higher income households,” Spotlight on Statistics (U.S. Bureau of Labor Statistics, December 2022), https://www.bls.gov/spotlight/2022/inflation-experiences-for-lower-and-higher-income-households/home.htm.2 All references to income in this article refer to equivalized income, unless otherwise noted.3 For more information on these research indexes, see “R-CPI-I and R-C-CPI-I homepage,” Consumer Price Index (U.S. Bureau of Labor Statistics), https://www.bls.gov/cpi/research-series/r-cpi-i.htm.4 Much of the literature also considers differences in household composition, often assuming, for instance, that children “need” less than adults. See, for example, OECD Handbook on the Compilation of Household Distributional Results on Income, Consumption and Saving in Line with National Accounts Totals (Paris: Organisation for Economic Co-operation and Development, 2020), https://www.oecd.org/sdd/na/EG-DNA-Handbook.pdf. In contrast, other work equivalizes income by using a single parameter, such as the square root of household size. See, for example, Dennis Fixler, Marina Gindelsky, and David Johnson, “Measuring inequality in the national accounts,” Working Paper 2020-3 (U.S. Bureau of Economic Analysis, December 2020), https://www.bea.gov/system/files/papers/measuring-inequality-in-the-national-accounts_0.pdf; and “Distribution of Personal Consumption Expenditures,” Consumer Expenditure Surveys (U.S. Bureau of Labor Statistics), https://www.bls.gov/cex/pce-ce-distributions.htm.5 Index results are not seasonally adjusted.6 Thesia I. Garner, David S. Johnson, and Mary F. Kokoski, “An experimental Consumer Price Index for the poor,” Monthly Labor Review, September 1996, https://www.bls.gov/opub/mlr/1996/09/art5full.pdf.7 Klick and Stockburger, “Experimental CPI for lower and higher income households.”8 Technical Recommendations for the Consumer Inflation Measure Best Suited for Conducting Annual Adjustments to the Official Poverty Measure (Office of Management and Budget, June 16, 2021), https://www.bls.gov/evaluation/technical-recommendations-for-the-consumer-inflation-measure-best-suited-for-conducting-annual-adjustments-to-the-official-poverty-measure.pdf.9 Daniel E. Sichel and Christopher Mackie, eds., Modernizing the Consumer Price Index for the 21st Century (Washington, DC: The National Academies Press, 2022), https://doi.org/10.17226/26485.10 Examples include Greg Kaplan and Sam Schulhofer-Wohl, “Inflation at the household level,” Working Paper 2017-13 (Federal Reserve Bank of Chicago, 2017), https://www.chicagofed.org/publications/working-papers/2017/wp2017-13; Xavier Jaravel, “The unequal gains from product innovations: evidence from the U.S. retail sector,” The Quarterly Journal of Economics, vol. 134, no. 2, May 2019, pp. 715–783; and Georg Strasser, Teresa Messner, Fabio Rumler, and Miguel Ampudia, “Inflation heterogeneity at the household level,” Occasional Paper 325 (European Central Bank, 2023), https://www.ecb.europa.eu/pub/pdf/scpops/ecb.op325~7422ebe3c1.en.pdf?63924885a8f1c0e86c5e55ca344811c7.11 Because the U.S. Bureau of Labor Statistics (BLS) began imputing missing income values in 2004, income data from 2003 are not comparable. For this research, we used 2004 expenditures to calculate the spending shares used in index calculations for 2006 and 2007. The remaining spending shares are based on 2 years of expenditures (through index period 2022), consistent with Consumer Price Index (CPI) methodology. Since 2023, CPI weights have been revised annually, with index calculation using a reference-year lag of 2 years. For example, the 2023 CPI for All Urban Consumers (CPI-U) uses expenditure weights for reference year 2021.12 Nearly half of income values are imputed for the urban population in the Diary and Interview surveys. For more information on income imputation, see “CE income imputation explanatory note,” Consumer Expenditure Surveys (U.S. Bureau of Labor Statistics), https://www.bls.gov/cex/csximpute.htm. For comparison, 45 percent of income values are imputed in the Current Population Survey (CPS) Annual Social and Economic Supplement; see Charles Hokayem, Trivellore Raghunathan, and Jonathan Rothbaum, “Match bias or nonignorable nonresponse? Improved imputation and administrative data in the CPS ASEC,” Journal of Survey Statistics and Methodology, vol. 10, no. 1, February 2022, https://academic.oup.com/jssam/article-abstract/10/1/81/5943180?redirectedFrom=fulltext.13 There is a large body of literature using equivalence scales to adjust household income in order to account for different characteristics across households. See, for example, Angela Daley, Thesia I. Garner, Shelley Phipps, and Eva Sierminska, “Differences across place and time in household expenditure patterns: implications for the estimation of equivalence scales,” Working Paper 520 (U.S. Bureau of Labor Statistics, November 2019), https://www.bls.gov/osmr/research-papers/2020/pdf/ec200010.pdf; and Richard V. Reeves and Christopher Pulliam, “Tipping the balance: why equivalence scales matter more than you think” (Washington, DC: The Brookings Institution, April 17, 2019), https://www.brookings.edu/blog/up-front/2019/04/17/whats-in-an-equivalence-scale.14 See Klick and Stockburger, “Experimental CPI for lower and higher income households;” and Klick and Stockburger, “Inflation experiences for lower and higher income households.”15 BLS calibrates Consumer Expenditure Surveys (CE) sample weights to the CPS in order to control for demographic characteristics such as age, race, owner or renter, geography, and Hispanic ethnicity; see section on calculation methodology in “Consumer expenditures and income: calculation,” Handbook of Methods (U.S. Bureau of Labor Statistics, last modified September 12, 2022), https://www.bls.gov/opub/hom/cex/calculation.htm#calculation-methodology. Weighting methods also control for subsampling, geography, household size, number of contacts, and average gross income for a household’s ZIP Code. The use of sample weights reflects known urban population totals and is particularly relevant in comparisons of owners and renters, ensuring that weights are equivalent across quintiles and comparable to CE’s weighted ranking of the total population. See “Table 1101. Quintiles of income before taxes: annual expenditure means, shares, standard errors, and coefficients of variation, Consumer Expenditure Surveys, 2021” (U.S. Bureau of Labor Statistics, 2022), https://www.bls.gov/cex/tables/calendar-year/mean-item-share-average-standard-error/cu-income-quintiles-before-taxes-2021.pdf.For information on the CE income-distribution methodology, see Geoffrey Paulin, Sally Reyes-Morales, and Jonathan Fisher, “User’s guide to income imputation in the CE” (U.S. Bureau of Labor Statistics, July 31, 2018), https://www.bls.gov/cex/csxguide.pdf. The CE program creates an income-ranking variable based on before-tax income as a distribution over the interval (0,1], so that weights are relatively equally distributed across defined quantiles. The income-ranking variable is created by sorting by income and a random number (used to break ties for consumer units reporting the same income) in ascending order for each collection quarter and survey source.16 The CPI income-distribution methodology includes sorting by consumer-unit identification number prior to random number assignment.17 For details, see David C. Swanson, Sharon K. Hauge, and Mary Lynn Schmidt, “Evaluation of composite estimation methods for cost weights in the CPI” (U.S. Bureau of Labor Statistics, 1999), https://www.bls.gov/osmr/research-papers/1999/pdf/st990050.pdf.18 For details, see Robert Cage, John Greenlees, and Patrick Jackman, “Introducing the Chained Consumer Price Index” (U.S. Bureau of Labor Statistics, May 2003), https://www.bls.gov/cpi/additional-resources/chained-cpi-introduction.pdf.19 For a description of nonsampled items, see “Changing the item structure of the Consumer Price Index,” Consumer Price Index (U.S. Bureau of Labor Statistics), https://www.bls.gov/cpi/additional-resources/revision-1998-item-structure.htm.20 See “Measuring price change in the CPI: medical care,” Consumer Price Index (U.S. Bureau of Labor Statistics), https://www.bls.gov/cpi/factsheets/medical-care.htm.21 Weight calculation is described in greater detail in “Consumer Price Index: calculation,” Handbook of Methods (U.S. Bureau of Labor Statistics, last modified September 6, 2023), https://www.bls.gov/opub/hom/cpi/calculation.htm.22 See, for example, “Worries about affording essentials in a high-inflation environment” (Paris: Organisation for Economic Co-operation and Development, July 2023), https://www.oecd.org/social/soc/OECD2023-RTM2022-PolicyBrief-Inflation.pdf.23 For more information on these broad classifications, see “CPI item aggregation,” Consumer Price Index (U.S. Bureau of Labor Statistics), https://www.bls.gov/cpi/additional-resources/cpi-item-aggregation.htm.24 See footnote 1 in “Table 7. Consumer Price Index for All Urban Consumers (CPI-U): U.S. city average, by expenditure category, 12-month analysis table,” Economic News Release (U.S. Bureau of Labor Statistics), https://www.bls.gov/news.release/cpi.t07.htm.25 For item definitions, see “Appendix 7. Consumer Price Index items by publication level,” Consumer Price Index (U.S. Bureau of Labor Statistics), https://www.bls.gov/cpi/additional-resources/index-publication-level.htm.26 The gap effects are evaluated as the difference between the first-quintile effect and the fifth-quintile effect at the item level. Then, the gap effects are renormalized to determine the corresponding proportional contribution to the all-items gap.27 See Cage, Greenlees, and Jackman, “Introducing the Chained Consumer Price Index.”28 To minimize variance across basic item-area monthly expenditures, we smooth monthly weights by using a ratio allocation of the 12-month moving average of item shares. To reflect the average weight for the current and previous periods, we use monthly weights as a 2-month moving-average shares.29 Because CE data are available with a lag, we could not calculate 2023 indexes at the time of our analysis.30 Index revisions based on the constant-elasticity-of-substitution formula were processed as update weights revised in January of even years. However, chaining was processed annually (to the final Chained CPI for December of the prior year) instead of quarterly (as occurs in production).31 See, for example, Kaplan and Schulhofer-Wohl, “Inflation at the household level;” and Jaravel, “The unequal gains from product innovations: evidence from the U.S. retail sector.”32 See Daryl Larsen and Raven Molloy, “Differences in rent growth by income 1985–2019 and implications for real income inequality,” FEDS Notes (Board of Governors of the Federal Reserve System, November 5, 2021), https://www.federalreserve.gov/econres/notes/feds-notes/differences-in-rent-growth-by-income-1985-2019-and-implications-for-real-income-inequality-20211105.html.33 See Fixler, Gindelsky, and Johnson, “Measuring inequality in the national accounts.” See also “Distribution of Personal Consumption Expenditures,” Consumer Expenditure Surveys (U.S. Bureau of Labor Statistics), https://www.bls.gov/cex/pce-ce-distributions.htm. About the Author Joshua Klick cpi_info@bls.gov Joshua Klick is a senior economist in the Office of Prices and Living Conditions, U.S. Bureau of Labor Statistics. Anya Stockburger cpi_info@bls.gov Anya Stockburger is a supervisory economist in the Office of Prices and Living Conditions, U.S. Bureau of Labor Statistics. Related Content Related Articles Measuring total-premium inflation for health insurance in the Consumer Price Index, Monthly Labor Review, April 2024. Two plus two really does equal four: simulating official BLS gasoline price measures, Monthly Labor Review, June 2023. Automotive dealerships 2019–22: dealer markup increases drive new-vehicle consumer inflation, Monthly Labor Review, April 2023. The impact of changing consumer expenditure patters at the onset of the COVID-19 pandemic on measures of consumer inflation, Monthly Labor Review, April 2022. An experimental Consumer Price Index for the poor, Monthly Labor Review, September 1996. Related Subjects Income Consumer price index Consumer expenditures Statistical programs and methods Prices Inflation Family issues Article Citations Crossref0 Article Citations × $(document).ready(function(){ $.get("/opub/mlr/content/doi/mlr.2024.12.txt",handleDoi) function handleDoi(data){ if(data!=""){ var ctx=JSON.parse(data).crossref_result.query_result.body; $("#cited-by").show() if(ctx.hasOwnProperty("forward_link")){ if(ctx.forward_link.length==undefined){ readFL(ctx.forward_link) $(".citation-number a").html(1) }else{ for(k in ctx.forward_link){ readFL(ctx.forward_link[k]) } $(".citation-number a").html(ctx.forward_link.length) } $(".citation-number a").click(function(e){ e.preventDefault(); $('#mlrModal').modal('show') return false; }) }else{ $(".citation-number a").replaceTagName('span'); } } } function readFL(flo){ let ctx = flo[Object.keys(flo)[0]]; if(ctx){ $('#mlrModal .modal-body').append('<p><a target="_blank" href="https://doi.org/'+ctx.doi.content+'">'+(ctx.article_title || ctx.chapter_title || ctx.paper_title)+'</a>, <em>'+(ctx.journal_title || ctx.volume_title)+'</em>, '+ctx.year+'.</p>'); } } }) top Back to Top $(document).ready(function(){ var back_to_top_location = $("#page-top-link").position().top; var footerHeight = $(document).height() - $(".footerNav").position().top + 20; $(window).scroll(function(){ if($(window).scrollTop() > back_to_top_location && $(document).height() - ($(window).scrollTop() + $(window).height()) > footerHeight){ $("#page-top-link").css("position","fixed").css("bottom","10px"); }else if($(document).height() - ($(window).scrollTop() + $(window).height()) < footerHeight ){ var back_to_top_bottom = footerHeight + ($(window).scrollTop() + $(window).height()) - $(document).height(); $("#page-top-link").css("position","fixed").css("bottom",back_to_top_bottom+"px") ; }else if($(window).scrollTop() <= back_to_top_location){ $("#page-top-link").css("position","relative").css("bottom",""); } }); }); #exposeMask{z-index:9999 !important; } .bls-chartdata-overlay{display:none;} $(document).ready(function(){ $("a[name^='_edn']").css("text-decoration","none"); $("#mlr-main-article a[href]").each(function(){ if(!$(this).parents("#errata").size()){ if($(this).attr("href").match("/opub/mlr/.*?/(highcharts/data|images/data|tables)/.*\.stm")){ var that = $(this); $(this).attr("rel","#custom-overlay"); $(this).mouseover(function(){ $(".contentWrap").load(that.attr("href")); }); $(this).overlay({ mask: 'black', fixed: false, left: "center", fixed: true, onBeforeLoad: function() { this.getOverlay().find(".contentWrap").load(this.getTrigger().attr("href")); }, onLoad:function(){ $(".contentWrap").css("height",($(window).height()/2) +'px') setTimeout(function(){createFixedHeader($("#custom-overlay table"),".contentWrap");},500) if($.fn.jquery > "1.4.2"){ $(".bls-chartdata-overlay .bls-overlay-heading a").on("click", function(){ that.data("overlay").close(); }); }else{ $(".bls-chartdata-overlay .bls-overlay-heading a").click(function(){ that.data("overlay").close(); }); } }, onClose:function(){ $("#mlr-main-article table.fixed-headers").each(function(){ createFixedHeader($(this)); }) } }); }} }); }); $("#mlr-main-article table").addClass("fixed-headers") close or Esc Key Recommend this page using: Facebook Twitter LinkedIn

This article extends our previous research on producing price indexes for households in different income groups.1

equivalized income

BLS publishes CPIs for subgroups of a target urban population

Joshua Klick cpi_info@bls.gov Joshua Klick is a senior economist in the Office of Prices and Living Conditions, U.S. Bureau of Labor Statistics. Anya Stockburger cpi_info@bls.gov Anya Stockburger is a supervisory economist in the Office of Prices and Living Conditions, U.S. Bureau of Labor Statistics.