15 datasets found
  1. T

    United States Core Personal Consumption Expenditure Price Index

    • tradingeconomics.com
    • fa.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Aug 15, 2025
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    TRADING ECONOMICS (2025). United States Core Personal Consumption Expenditure Price Index [Dataset]. https://tradingeconomics.com/united-states/core-pce-price-index
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    csv, excel, json, xmlAvailable download formats
    Dataset updated
    Aug 15, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 31, 1959 - Aug 31, 2025
    Area covered
    United States
    Description

    Core PCE Price Index in the United States increased to 126.71 points in August from 126.42 points in July of 2025. This dataset provides - United States Core Pce Price Index - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  2. T

    United States Personal Consumption Expenditure Price Index

    • tradingeconomics.com
    • es.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Aug 15, 2025
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    TRADING ECONOMICS (2025). United States Personal Consumption Expenditure Price Index [Dataset]. https://tradingeconomics.com/united-states/pce-price-index
    Explore at:
    excel, json, csv, xmlAvailable download formats
    Dataset updated
    Aug 15, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 31, 1959 - Aug 31, 2025
    Area covered
    United States
    Description

    PCE Price Index in the United States increased to 127.29 points in August from 126.95 points in July of 2025. This dataset provides the latest reported value for - United States Personal Consumption Expenditure Price Index - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

  3. M

    Core PCE Price Index y/y - economic news from the United States

    • mql5.com
    csv
    Updated Nov 20, 2025
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    MQL5 Community (2025). Core PCE Price Index y/y - economic news from the United States [Dataset]. https://www.mql5.com/en/economic-calendar/united-states/core-pce-price-index-yy
    Explore at:
    csvAvailable download formats
    Dataset updated
    Nov 20, 2025
    Dataset authored and provided by
    MQL5 Community
    Time period covered
    Oct 27, 2023 - Sep 26, 2025
    Area covered
    United States
    Description

    Overview with Chart & Report: Core PCE Price Index y/y reflects price changes on durable and non-durable goods and services in the reporting month compared to the same month of the previous year. Food and energy prices are

  4. T

    United States PCE Price Index Annual Change

    • tradingeconomics.com
    • zh.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Sep 26, 2025
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    TRADING ECONOMICS (2025). United States PCE Price Index Annual Change [Dataset]. https://tradingeconomics.com/united-states/pce-price-index-annual-change
    Explore at:
    json, csv, excel, xmlAvailable download formats
    Dataset updated
    Sep 26, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 31, 1960 - Aug 31, 2025
    Area covered
    United States
    Description

    PCE Price Index Annual Change in the United States increased to 2.74 percent in August from 2.60 percent in July of 2025. This dataset includes a chart with historical data for the United States PCE Price Index Annual Change.

  5. T

    United States Core PCE Price Index Annual Change

    • tradingeconomics.com
    • pl.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Sep 26, 2025
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    TRADING ECONOMICS (2025). United States Core PCE Price Index Annual Change [Dataset]. https://tradingeconomics.com/united-states/core-pce-price-index-annual-change
    Explore at:
    json, csv, excel, xmlAvailable download formats
    Dataset updated
    Sep 26, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 31, 1960 - Aug 31, 2025
    Area covered
    United States
    Description

    Core PCE Price Index Annual Change in the United States increased to 2.91 percent in August from 2.85 percent in July of 2025. This dataset includes a chart with historical data for the United States Core Pce Price Index Annual Change.

  6. T

    United States PCE Price Index Monthly Change

    • tradingeconomics.com
    • zh.tradingeconomics.com
    • +12more
    csv, excel, json, xml
    Updated Sep 26, 2025
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    TRADING ECONOMICS (2025). United States PCE Price Index Monthly Change [Dataset]. https://tradingeconomics.com/united-states/pce-price-index-monthly-change
    Explore at:
    excel, xml, csv, jsonAvailable download formats
    Dataset updated
    Sep 26, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Feb 28, 1959 - Aug 31, 2025
    Area covered
    United States
    Description

    PCE Price Index Monthly Change in the United States increased to 0.30 percent in August from 0.20 percent in July of 2025. This dataset includes a chart with historical data for the United States PCE Price Index Monthly Change.

  7. T

    United States Personal Spending

    • tradingeconomics.com
    • es.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Sep 26, 2025
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    TRADING ECONOMICS (2025). United States Personal Spending [Dataset]. https://tradingeconomics.com/united-states/personal-spending
    Explore at:
    xml, excel, json, csvAvailable download formats
    Dataset updated
    Sep 26, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Feb 28, 1959 - Aug 31, 2025
    Area covered
    United States
    Description

    Personal Spending in the United States increased 0.60 percent in August of 2025 over the previous month. This dataset provides the latest reported value for - United States Personal Spending - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

  8. B

    Brazil FIPE: CPI: MoM: Personal Expenses: Recreation and Culture: Culture:...

    • ceicdata.com
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    CEICdata.com, Brazil FIPE: CPI: MoM: Personal Expenses: Recreation and Culture: Culture: Newspaper [Dataset]. https://www.ceicdata.com/en/brazil/consumer-price-index-june1994100-so-paulo-so-paulo-monthonmonth-fipe/fipe-cpi-mom-personal-expenses-recreation-and-culture-culture-newspaper
    Explore at:
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Mar 1, 2024 - Feb 1, 2025
    Area covered
    Brazil
    Variables measured
    Consumer Prices
    Description

    FIPE: Consumer Price Index (CPI): MoM: Personal Expenses: Recreation and Culture: Culture: Newspaper data was reported at 0.000 % in Mar 2025. This records a decrease from the previous number of 1.044 % for Feb 2025. FIPE: Consumer Price Index (CPI): MoM: Personal Expenses: Recreation and Culture: Culture: Newspaper data is updated monthly, averaging 0.000 % from Jan 2000 (Median) to Mar 2025, with 303 observations. The data reached an all-time high of 11.199 % in Sep 2000 and a record low of -9.459 % in Aug 2010. FIPE: Consumer Price Index (CPI): MoM: Personal Expenses: Recreation and Culture: Culture: Newspaper data remains active status in CEIC and is reported by Institute of Economic Research Foundation. The data is categorized under Brazil Premium Database’s Inflation – Table BR.IB006: Consumer Price Index: June1994=100: São Paulo: São Paulo: Month-on-Month: FIPE.

  9. Consumer Expenditure Diary Survey 2006 - United States

    • datacatalog.ihsn.org
    • catalog.ihsn.org
    Updated Mar 29, 2019
    + more versions
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    United State Census Bureau (2019). Consumer Expenditure Diary Survey 2006 - United States [Dataset]. https://datacatalog.ihsn.org/catalog/6803
    Explore at:
    Dataset updated
    Mar 29, 2019
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    United State Census Bureau
    Time period covered
    2006
    Area covered
    United States
    Description

    Abstract

    The Consumer Expenditure Survey (CE) program provides a continuous and comprehensive flow of data on the buying habits of American consumers. These data are used widely in economic research and analysis, and in support of revisions of the Consumer Price Index. To meet the needs of users, the Bureau of Labor Statistics (BLS) produces population estimates (for consumer units or CUs) of average expenditures in news releases, reports, and articles in the Monthly Labor Review. Tabulated CE data are also available on the Internet and by facsimile transmission (see Section XVI. Appendix 5). The microdata are available on CD-ROM as SAS data sets or ASCII text files.

    These microdata files present detailed expenditure and income data for the Diary component of the CE for 2006. They include weekly expenditure (EXPN), annual income (DTAB) files, and imputed income files (DTAB_IMPUTE). The data in EXPN, DTAB, and DTAB_IMPUTE files are categorized by a Universal Classification Code (UCC). The advantage of the EXPN and DTAB files is that with the data classified in a standardized format, the user may perform comparative expenditure (income) analysis with relative ease. The FMLY and MEMB files present data on the characteristics and demographics of CUs and CU members. The summary level expenditure and income information on the FMLY files permits the data user to link consumer spending, by general expenditure category, and household characteristics and demographics on one set of files.

    Estimates of average expenditures in 2006 from the Diary survey, integrated with data from the Interview survey, are published in Consumer Expenditures in 2006. A list of recent publications containing data from the CE appears at the end of this documentation. The microdata files are in the public domain and, with appropriate credit, may be reproduced without permission. A suggested citation is: “U.S. Department of Labor, Bureau of Labor Statistics, Consumer Expenditure Survey, Diary Survey, 2006”.

    The Diary survey PUMD are organized into five major data files for each quarter: 1. FMLD - a file with characteristics, income, and summary level expenditures for the household 2. MEMD - a file with characteristics and income for each member in the household
    3. EXPD - a detailed weekly expenditure file categorized by UCC 4. DTBD - a detailed annual income file categorized by UCC
    5. DTID - a household imputed income file categorized by UCC

    Analysis unit

    Consumer Unit

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    A. SURVEY SAMPLE DESIGN

    Samples for the CE are national probability samples of households designed to be representative of the total U. S. civilian population. Eligible population includes all civilian noninstitutional persons.

    The first step in sampling is the selection of primary sampling units (PSUs), which consist of counties (or parts thereof) or groups of counties. The set of sample PSUs used for the 2006 sample is composed of 91 areas. The design classifies the PSUs into four categories:

    • 21 "A" certainty PSUs are Metropolitan Statistical Areas (MSA's) with a population greater than 1.5 million. • 38 "X" PSUs, are medium-sized MSAs. • 16 "Y" PSUs are nonmetropolitan areas that are included in the CPI. • 16 "Z" PSUs are nonmetropolitan areas where only the urban population data will be included in the CPI.

    The sampling frame (that is, the list from which housing units were chosen) for the 2006 survey is generated from the 2000 Population Census file. The sampling frame is augmented by new construction permits and by techniques used to eliminate recognized deficiencies in census coverage. All Enumeration Districts (EDs) from the Census that fail to meet the criterion for good addresses for new construction, and all EDs in nonpermit-issuing areas are grouped into the area segment frame.

    To the extent possible, an unclustered sample of units is selected within each PSU. This lack of clustering is desirable because the sample size of the Diary Survey is small relative to other surveys, while the intraclass correlations for expenditure characteristics are relatively large. This suggests that any clustering of the sample units could result in an unacceptable increase in the within-PSU variance and, as a result, the total variance. Each selected sample unit is requested to keep two 1-week diaries of expenditures over consecutive weeks. The earliest possible day for placing a diary with a household is predesignated with each day of the week having an equal chance to be the first of the reference week. The diaries are evenly spaced throughout the year.

    B. COOPERATION LEVELS

    The annual target sample size at the United States level for the Diary Survey is 7,200 participating sample units. To achieve this target the total estimated work load is 12,200 sample units. This allows for refusals, vacancies, or nonexistent sample unit addresses.

    Each participating sample unit selected is asked to keep two 1-week diaries. Each diary is treated independently, so response rates are based on twice the number of housing units sampled.

    Mode of data collection

    Computer Assisted Personal Interview [capi]

    Response rate

    The response rate for the 2006 Diary Survey is 74.2%. This response rate refers to all diaries in the year.

  10. Consumer Expenditure Survey, 2007: Diary Survey

    • archive.ciser.cornell.edu
    Updated Oct 16, 2025
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    Department of Labor (2025). Consumer Expenditure Survey, 2007: Diary Survey [Dataset]. http://doi.org/10.6077/j5/b14kfj
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    Dataset updated
    Oct 16, 2025
    Dataset provided by
    United States Department of Laborhttp://www.dol.gov/
    Authors
    Department of Labor
    Variables measured
    Group
    Description

    The CE provides a continuous and comprehensive flow of data on the buying habits of American consumers. These data are used widely in economic research and analysis, and in support of revisions of the Consumer Price Index. To meet the needs of users, the Bureau of Labor Statistics (BLS) produces population estimates for consumer units (CUs) of average expenditures in news releases, reports, quarterly web articles, Monthly Labor Review articles, and annual tabulated CE data. The Diary survey collects data on weekly expenditures of frequently purchased items such as food at home, food away from home, alcoholic beverages, smoking supplies, personal care products and services, and nonprescription drugs, as well as income and characteristics data. The Diary survey PUMD are organized into five major data files for each quarter: 1. FMLD - a file with characteristics, income, and summary level expenditures for the household 2. MEMD - a file with characteristics and income for each member in the household 3. EXPD - a detailed weekly expenditure file categorized by UCC 4. DTBD - a detailed annual income file categorized by UCC 5. DTID - a household imputed income file categorized by UCC2 The population estimates used in the reports and tables mentioned above were derived using CE microdata. CE microdata are at the CU level. To produce the public-use version of CE microdata, the CE undertakes a yearly process that strips the data of any potential respondent identifying information.

  11. Consumer Expenditure Diary Survey 2003 - United States

    • catalog.ihsn.org
    Updated Mar 29, 2019
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    United States Census Bureau (2019). Consumer Expenditure Diary Survey 2003 - United States [Dataset]. https://catalog.ihsn.org/index.php/catalog/6805
    Explore at:
    Dataset updated
    Mar 29, 2019
    Dataset authored and provided by
    United States Census Bureauhttp://census.gov/
    Time period covered
    2003
    Area covered
    United States
    Description

    Abstract

    The Consumer Expenditure Survey (CE) program provides a continuous and comprehensive flow of data on the buying habits of American consumers. These data are used widely in economic research and analysis, and in support of revisions of the Consumer Price Index. To meet the needs of users, the Bureau of Labor Statistics (BLS) produces population estimates for consumer units (CUs) of average expenditures in news releases, reports, issues, and articles in the Monthly Labor Review. Tabulated CE data are also available on the Internet and by facsimile transmission (See Section XV. APPENDIX 4). The microdata are available online at http://www/bls.gov/cex/pumdhome.htm.

    These microdata files present detailed expenditure and income data for the Diary component of the CE for 2003. They include weekly expenditure (EXPD) and annual income (DTBD) files. The data in EXPD and DTBD files are categorized by a Universal Classification Code (UCC). The advantage of the EXPD and DTBD files is that with the data classified in a standardized format, the user may perform comparative expenditure (or income) analysis with relative ease. The FMLD and MEMD files present data on the characteristics and demographics of CUs and CU members. The summary level expenditure and income information on the FMLD files permits the data user to link consumer spending, by general expenditure category, and household characteristics and demographics on one set of files.

    Estimates of average expenditures in 2003 from the Diary survey, integrated with data from the Interview survey, are published in Consumer Expenditures in 2003. A list of recent publications containing data from the CE appears at the end of this documentation.

    The microdata files are in the public domain and with appropriate credit, may be reproduced without permission. A suggested citation is: "U.S. Department of Labor, Bureau of Labor Statistics, Consumer Expenditure Survey, Diary Survey, 2003".

    STATE IDENTIFIER

    Since the CE is not designed to produce state-level estimates, summing the consumer unit weights by state will not yield state population totals. A CU's basic weight reflects its probability of selection among a group of primary sampling units of similar characteristics. For example, sample units in an urban nonmetropolitan area in California may represent similar areas in Wyoming and Nevada. Among other adjustments, CUs are post-stratified nationally by sex-age-race. For example, the weights of consumer units containing a black male, age 16-24 in Alabama, Colorado, or New York, are all adjusted equivalently. Therefore, weighted population state totals will not match population totals calculated from other surveys that are designed to represent state data.

    To summarize, the CE sample was not designed to produce precise estimates for individual states. Although state-level estimates that are unbiased in a repeated sampling sense can be calculated for various statistical measures, such as means and aggregates, their estimates will generally be subject to large variances. Additionally, a particular state-population estimate from the CE sample may be far from the true state-population estimate.

    INTERPRETING THE DATA

    Several factors should be considered when interpreting the expenditure data. The average expenditure for an item may be considerably lower than the expenditure by those CUs that purchased the item. The less frequently an item is purchased, the greater the difference between the average for all consumer units and the average of those purchasing. (See Section V.B. for ESTIMATION OF TOTAL AND MEAN EXPENDITURES). Also, an individual CU may spend more or less than the average, depending on its particular characteristics. Factors such as income, age of family members, geographic location, taste and personal preference also influence expenditures. Furthermore, even within groups with similar characteristics, the distribution of expenditures varies substantially.

    Expenditures reported are the direct out-of-pocket expenditures. Indirect expenditures, which may be significant, may be reflected elsewhere. For example, rental contracts often include utilities. Renters with such contracts would record no direct expense for utilities, and therefore, appear to have no utility expenses. Employers or insurance companies frequently pay other costs. CUs with members whose employers pay for all or part of their health insurance or life insurance would have lower direct expenses for these items than those who pay the entire amount themselves. These points should be considered when relating reported averages to individual circumstances.

    The Diary survey PUMD are organized into five major data files for each quarter: 1. FMLD - a file with characteristics, income, and summary level expenditures for the household 2. MEMD - a file with characteristics and income for each member in the household
    3. EXPD - a detailed weekly expenditure file categorized by UCC 4. DTBD - a detailed annual income file categorized by UCC
    5. DTID - a household imputed income file categorized by UCC

    Analysis unit

    Consumer Unit

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    A. SURVEY SAMPLE DESIGN

    Samples for the CE are national probability samples of households designed to be representative of the total U. S. civilian population. Eligible population includes all civilian noninstitutional persons.

    The first step in sampling is the selection of primary sampling units (PSUs), which consist of counties (or parts thereof) or groups of counties. The set of sample PSUs used for the 2003 sample is composed of 105 areas. The design classifies the PSUs into four categories:

    • 31 "A" certainty PSUs are Metropolitan Statistical Areas (MSA's) with a population greater than 1.5 million. • 46 "B" PSUs, are medium-sized MSA's. • 10 "C" PSUs are nonmetropolitan areas that are included in the CPI. • 18 "D" PSUs are nonmetropolitan areas where only the urban population data will be included in the CPI.

    The sampling frame (that is, the list from which housing units were chosen) for the 2003 survey is generated from the 1990 Population Census 100-percent-detail file. The sampling frame is augmented by new construction permits and by techniques used to eliminate recognized deficiencies in census coverage. All Enumeration Districts (ED's) from the Census that fail to meet the criterion for good addresses for new construction, and all ED's in nonpermit-issuing areas are grouped into the area segment frame.

    To the extent possible, an unclustered sample of units is selected within each PSU. This lack of clustering is desirable because the sample size of the Diary Survey is small relative to other surveys, while the intraclass correlations for expenditure characteristics are relatively large. This suggests that any clustering of the sample units could result in an unacceptable increase in the within-PSU variance and, as a result, the total variance.

    Each selected sample unit is requested to keep two 1-week diaries of expenditures over consecutive weeks. The earliest possible day for placing a diary with a household is predesignated with each day of the week having an equal chance to be the first of the reference week. The diaries are evenly spaced throughout the year. During the last 6 weeks of the year, however, the Diary Survey sample is supplemented to twice its normal size to increase the reporting of types of expenditures unique to the holidays.

    B. COOPERATION LEVELS

    The annual target sample size at the United States level for the Diary Survey is 7,800 participating sample units. To achieve this target the total estimated work load is 11,275 sample units. This allows for refusals, vacancies, or nonexistent sample unit addresses.

    Each participating sample unit selected is asked to keep two 1-week diaries. Each diary is treated independently, so response rates are based on twice the number of housing units sampled.

    Mode of data collection

    Computer Assisted Personal Interview [capi]

    Response rate

    The response rate for the 2003 Diary Survey is 73.4%. This response rate refers to all diaries in the year.

  12. Consumer Expenditure Diary Survey 2005 - United States

    • catalog.ihsn.org
    • datacatalog.ihsn.org
    Updated Mar 29, 2019
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    United State Census Bureau (2019). Consumer Expenditure Diary Survey 2005 - United States [Dataset]. https://catalog.ihsn.org/index.php/catalog/6804
    Explore at:
    Dataset updated
    Mar 29, 2019
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    United State Census Bureau
    Time period covered
    2005
    Area covered
    United States
    Description

    Abstract

    The Consumer Expenditure Survey (CE) program provides a continuous and comprehensive flow of data on the buying habits of American consumers. These data are used widely in economic research and analysis, and in support of revisions of the Consumer Price Index. To meet the needs of users, the Bureau of Labor Statistics (BLS) produces population estimates (for consumer units or CUs) of average expenditures in news releases, reports, and articles in the Monthly Labor Review. Tabulated CE data are also available on the Internet and by facsimile transmission (see Section XVI. Appendix 5). These microdata files present detailed expenditure and income data for the Diary component of the CE for 2005. They include weekly expenditure (EXPD), annual income (DTBD) files, and imputed income files (DTID). The data in EXPD, DTBD, and DTID files are categorized by a Universal Classification Code (UCC). The advantage of the EXPD and DTBD files is that with the data classified in a standardized format, the user may perform comparative expenditure (income) analysis with relative ease. The FMLD and MEMD files present data on the characteristics and demographics of CUs and CU members. The summary level expenditure and income information on the FMLD files permits the data user to link consumer spending, by general expenditure category, and household characteristics and demographics on one set of files. Estimates of average expenditures in 2005 from the Diary survey, integrated with data from the Interview survey, are published in Consumer Expenditures in 2005. A list of recent publications containing data from the CE appears at the end of this documentation.

    The microdata files are in the public domain and, with appropriate credit, may be reproduced without permission. A suggested citation is: “U.S. Department of Labor, Bureau of Labor Statistics, Consumer Expenditure Survey, Diary Survey, 2005”.

    State Identifier Since the CE is not designed to produce state-level estimates, summing the consumer unit weights by state will not yield state population totals. A CU's basic weight reflects its probability of selection among a group of primary sampling units of similar characteristics. For example, sample units in an urban nonmetropolitan area in California may represent similar areas in Wyoming and Nevada. Among other adjustments, CUs are post-stratified nationally by sex-age-race. For example, the weights of consumer units containing a black male, age 16-24 in Alabama, Colorado, or New York, are all adjusted equivalently. Therefore, weighted population state totals will not match population totals calculated from other surveys that are designed to represent state data.

    To summarize, the CE sample was not designed to produce precise estimates for individual states. Although state-level estimates that are unbiased in a repeated sampling sense can be calculated for various statistical measures, such as means and aggregates, their estimates will generally be subject to large variances. Additionally, a particular state-population estimate from the CE sample may be far from the true state-population estimate.

    Interpreting the data Several factors should be considered when interpreting the expenditure data. The average expenditure for an item may be considerably lower than the expenditure by those CUs that purchased the item. The less frequently an item is purchased, the greater the difference between the average for all consumer units and the average of those purchasing. (See Section V.B. for ESTIMATION OF TOTAL AND MEAN EXPENDITURES). Also, an individual CU may spend more or less than the average, depending on its particular characteristics. Factors such as income, age of family Members, geographic location, taste and personal preference also influence expenditures. Furthermore, even within groups with similar characteristics, the distribution of expenditures varies substantially.

    Expenditures reported are the direct out-of-pocket expenditures. Indirect expenditures, which may be significant, may be reflected elsewhere. For example, rental contracts often include utilities. Renters with such contracts would record no direct expense for utilities, and therefore, appear to have no utility expenses. Employers or insurance companies frequently pay other costs.CUs with Members whose employers pay for all or part of their health insurance or life insurance would have lower direct expenses for these items than those who pay the entire amount themselves. These points should be considered when relating reported averages to individual circumstances.

    The Diary survey PUMD are organized into five major data files for each quarter: 1. FMLD - a file with characteristics, income, and summary level expenditures for the household 2. MEMD - a file with characteristics and income for each member in the household
    3. EXPD - a detailed weekly expenditure file categorized by UCC 4. DTBD - a detailed annual income file categorized by UCC
    5. DTID - a household imputed income file categorized by UCC

    Analysis unit

    Consumer Unit

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    A. SURVEY SAMPLE DESIGN

    Samples for the CE are national probability samples of households designed to be representative of the total U. S. civilian population. Eligible population includes all civilian noninstitutional persons.

    The first step in sampling is the selection of primary sampling units (PSUs), which consist of counties (or parts thereof) or groups of counties. The set of sample PSUs used for the 2005 sample is composed of 102 areas. The design classifies the PSUs into four categories:

    • 28 "A" certainty PSUs are Metropolitan Statistical Areas (MSA's) with a population greater than 1.5 million. • 42 "B" PSUs, are medium-sized MSAs. • 16 "C" PSUs are nonmetropolitan areas that are included in the CPI. • 16 "D" PSUs are nonmetropolitan areas where only the urban population data will be included in the CPI.

    The sampling frame (that is, the list from which housing units were chosen) for the 2005 survey is generated from the 2000 Population Census file. The sampling frame is augmented by new construction permits and by techniques used to eliminate recognized deficiencies in census coverage. All Enumeration Districts (EDs) from the Census that fail to meet the criterion for good addresses for new construction, and all EDs in nonpermit-issuing areas are grouped into the area segment frame.

    To the extent possible, an unclustered sample of units is selected within each PSU. This lack of clustering is desirable because the sample size of the Diary Survey is small relative to other surveys, while the intraclass correlations for expenditure characteristics are relatively large. This suggests that any clustering of the sample units could result in an unacceptable increase in the within-PSU variance and, as a result, the total variance.

    Each selected sample unit is requested to keep two 1-week diaries of expenditures over consecutive weeks. The earliest possible day for placing a diary with a household is predesignated with each day of the week having an equal chance to be the first of the reference week. The diaries are evenly spaced throughout the year.

    B. COOPERATION LEVELS

    The annual target sample size at the United States level for the Diary Survey is 7,800 participating sample units. To achieve this target the total estimated work load is 11,275 sample units. This allows for refusals, vacancies, or nonexistent sample unit addresses.

    Each participating sample unit selected is asked to keep two 1-week diaries. Each diary is treated independently, so response rates are based on twice the number of housing units sampled.

    Mode of data collection

    Computer Assisted Personal Interview [capi]

    Response rate

    The response rate for the 2005 Diary Survey is 68.9%. This response rate refers to all diaries in the year.

  13. Consumer Expenditure Diary Survey 2002 - United States

    • catalog.ihsn.org
    • datacatalog.ihsn.org
    Updated Mar 29, 2019
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    United States Census Bureau (2019). Consumer Expenditure Diary Survey 2002 - United States [Dataset]. https://catalog.ihsn.org/index.php/catalog/6806/study-description
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    Dataset updated
    Mar 29, 2019
    Dataset authored and provided by
    United States Census Bureauhttp://census.gov/
    Time period covered
    2002
    Area covered
    United States
    Description

    Abstract

    The Consumer Expenditure Survey (CE) program provides a continuous and comprehensive flow of data on the buying habits of American consumers. These data are used widely in economic research and analysis, and in support of revisions of the Consumer Price Index. To meet the needs of users, the Bureau of Labor Statistics (BLS) produces population estimates for consumer units (CUs) of average expenditures in news releases, reports, issues, and articles in the Monthly Labor Review. Tabulated CE data are also available on the Internet and by facsimile transmission (See Section XV. APPENDIX 4). The microdata are available online at http://www/bls.gov/cex/pumdhome.htm.

    These microdata files present detailed expenditure and income data for the Diary component of the CE for 2002. They include weekly expenditure (EXPD) and annual income (DTBD) files. The data in EXPD and DTBD files are categorized by a Universal Classification Code (UCC). The advantage of the EXPD and DTBD files is that with the data classified in a standardized format, the user may perform comparative expenditure (income) analysis with relative ease. The FMLD and MEMD files present data on the characteristics and demographics of CUs and CU members. The summary level expenditure and income information on the FMLD files permits the data user to link consumer spending, by general expenditure category, and household characteristics and demographics on one set of files.

    Estimates of average expenditures in 2002 from the Diary survey, integrated with data from the Interview survey, are published in Consumer Expenditures in 2002. A list of recent publications containing data from the CE appears at the end of this documentation.

    The microdata files are in the public domain and with appropriate credit, may be reproduced without permission. A suggested citation is: "U.S. Department of Labor, Bureau of Labor Statistics, Consumer Expenditure Survey, Diary Survey, 2002".

    STATE IDENTIFIER Since the CE is not designed to produce state-level estimates, summing the consumer unit weights by state will not yield state population totals. A CU's basic weight reflects its probability of selection among a group of primary sampling units of similar characteristics. For example, sample units in an urban nonmetropolitan area in California may represent similar areas in Wyoming and Nevada. Among other adjustments, CUs are post-stratified nationally by sex-age-race. For example, the weights of consumer units containing a black male, age 16-24 in Alabama, Colorado, or New York, are all adjusted equivalently. Therefore, weighted population state totals will not match population totals calculated from other surveys that are designed to represent state data. To summarize, the CE sample was not designed to produce precise estimates for individual states. Although state-level estimates that are unbiased in a repeated sampling sense can be calculated for various statistical measures, such as means and aggregates, their estimates will generally be subject to large variances. Additionally, a particular state-population estimate from the CE sample may be far from the true state-population estimate.

    INTERPRETING THE DATA

    Several factors should be considered when interpreting the expenditure data. The average expenditure for an item may be considerably lower than the expenditure by those CUs that purchased the item. The less frequently an item is purchased, the greater the difference between the average for all consumer units and the average of those purchasing. (See Section V.B. for ESTIMATION OF TOTAL AND MEAN EXPENDITURES). Also, an individual CU may spend more or less than the average, depending on its particular characteristics. Factors such as income, age of family members, geographic location, taste and personal preference also influence expenditures. Furthermore, even within groups with similar characteristics, the distribution of expenditures varies substantially.

    Expenditures reported are the direct out-of-pocket expenditures. Indirect expenditures, which may be significant, may be reflected elsewhere. For example, rental contracts often include utilities. Renters with such contracts would record no direct expense for utilities, and therefore, appear to have no utility expenses. Employers or insurance companies frequently pay other costs. CUs with members whose employers pay for all or part of their health insurance or life insurance would have lower direct expenses for these items than those who pay the entire amount themselves. These points should be considered when relating reported averages to individual circumstances.

    Analysis unit

    Consumer Unit

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    A. SURVEY SAMPLE DESIGN

    Samples for the CE are national probability samples of households designed to be representative of the total U. S. civilian population. Eligible population includes all civilian noninstitutional persons.

    The first step in sampling is the selection of primary sampling units (PSUs), which consist of counties (or parts thereof) or groups of counties. The set of sample PSUs used for the 2002 sample is composed of 105 areas. The design classifies the PSUs into four categories:

    • 31 "A" certainty PSUs are Metropolitan Statistical Areas (MSA's) with a population greater than 1.5 million. • 46 "B" PSUs, are medium-sized MSA's. • 10 "C" PSUs are nonmetropolitan areas that are included in the CPI. • 18 "D" PSUs are nonmetropolitan areas where only the urban population data will be included in the CPI.

    The sampling frame (that is, the list from which housing units were chosen) for the 2002 survey is generated from the 1990 Population Census 100-percent-detail file. The sampling frame is augmented by new construction permits and by techniques used to eliminate recognized deficiencies in census coverage. All Enumeration Districts (ED's) from the Census that fail to meet the criterion for good addresses for new construction, and all ED's in nonpermit-issuing areas are grouped into the area segment frame.

    To the extent possible, an unclustered sample of units is selected within each PSU. This lack of clustering is desirable because the sample size of the Diary Survey is small relative to other surveys, while the intraclass correlations for expenditure characteristics are relatively large. This suggests that any clustering of the sample units could result in an unacceptable increase in the within-PSU variance and, as a result, the total variance.

    Each selected sample unit is requested to keep two 1-week diaries of expenditures over consecutive weeks. The earliest possible day for placing a diary with a household is predesignated with each day of the week having an equal chance to be the first of the reference week. The diaries are evenly spaced throughout the year. During the last 6 weeks of the year, however, the Diary Survey sample is supplemented to twice its normal size to increase the reporting of types of expenditures unique to the holidays.

    B. COOPERATION LEVELS

    The annual target sample size at the United States level for the Diary Survey is 7,800 participating sample units. To achieve this target the total estimated work load is 11,275 sample units. This allows for refusals, vacancies, or nonexistent sample unit addresses.

    Each participating sample unit selected is asked to keep two 1-week diaries. Each diary is treated independently, so response rates are based on twice the number of housing units sampled.

    Mode of data collection

    Computer Assisted Personal Interview [capi]

    Response rate

    The response rate for the 2002 Diary Survey is 74.2%. This response rate refers to all diaries in the year.

  14. Consumer Expenditure Interview Survey 2003 - United States

    • datacatalog.ihsn.org
    • catalog.ihsn.org
    • +1more
    Updated Mar 29, 2019
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    United States Census Bureau (2019). Consumer Expenditure Interview Survey 2003 - United States [Dataset]. https://datacatalog.ihsn.org/catalog/6801
    Explore at:
    Dataset updated
    Mar 29, 2019
    Dataset authored and provided by
    United States Census Bureauhttp://census.gov/
    Time period covered
    2003
    Area covered
    United States
    Description

    Abstract

    The Consumer Expenditure Survey (CE) program provides a continuous and comprehensive flow of data on the buying habits of American consumers. These data are used widely in economic research and analysis, and in support of revisions of the Consumer Price Index. To meet the needs of users, the Bureau of Labor Statistics (BLS) produces population estimates for consumer units (CUs) of average expenditures in news releases, reports, issues, and articles in the Monthly Labor Review. Tabulated CE data are also available on the Internet and by facsimile transmission (See Section XV. APPENDIX 4). The microdata are available online at http://www/bls.gov/cex/pumdhome.htm.

    These microdata files present detailed expenditure and income data from the Interview component of the CE for 2003 and the first quarter of 2004. The Interview survey collects data on up to 95 percent of total household expenditures. In addition to the FMLI, MEMI, MTBI, and ITBI files, the microdata include files created directly from the expenditure sections of the Interview survey (EXPN files). The EXPN files contain expenditure data and ancillary descriptive information, often not available on the FMLI or MTBI files, in a format similar to the Interview questionnaire. In addition to the extra information available on the EXPN files, users can identify distinct spending categories easily and reduce processing time due to the organization of the files by type of expenditure.

    Estimates of average expenditures in 2003 from the Interview Survey, integrated with data from the Diary Survey, will be published in the report Consumer Expenditures in 2003. A list of recent publications containing data from the CE appears at the end of this documentation.

    The microdata files are in the public domain and, with appropriate credit, may be reproduced without permission. A suggested citation is: "U.S. Department of Labor, Bureau of Labor Statistics, Consumer Expenditure Survey, Interview Survey, 2003."

    Analysis unit

    Consumer Units

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    Samples for the CE are national probability samples of households designed to be representative of the total U. S. civilian population. Eligible population includes all civilian non-institutionalized persons. The first step in sampling is the selection of primary sampling units (PSUs), which consist of counties (or parts thereof) or groups of counties. The set of sample PSUs used for the 2003 and 2004 samples is composed of 105 areas. The design classifies the PSUs into four categories: • 31 "A" certainty PSUs are Metropolitan Statistical Areas (MSA's) with a population greater than 1.5 million. • 46 "B" PSUs, are medium-sized MSA's. • 10 "C" PSUs are nonmetropolitan areas that are included in the CPI. • 18 "D" PSUs are nonmetropolitan areas where only the urban population data will be included in the CPI.

    The sampling frame (that is, the list from which housing units were chosen) for the 2003 and 2004 surveys is generated from the 1990 Census of Population 100-percent-detail file. The sampling frame is augmented by new construction permits and by techniques used to eliminate recognized deficiencies in census coverage. All Enumeration Districts (EDs) from the Census that fail to meet the criterion for good addresses for new construction, and all EDs in non-permit-issuing areas are grouped into the area segment frame. Interviewers are then assigned to list these areas before a sample is drawn. To the extent possible, an unclustered sample of units is selected within each PSU. This lack of clustering is desirable because the sample size of the Diary Survey is small relative to other surveys, while the intraclass correlations for expenditure characteristics are relatively large. This suggests that any clustering of the sample units could result in an unacceptable increase in the within-PSU variance and, as a result, the total variance. The Interview Survey is a panel rotation survey. Each panel is interviewed for five consecutive quarters and then dropped from the survey. As one panel leaves the survey, a new panel is introduced. Approximately 20 percent of the addresses are new to the survey each month.

    WEIGHTING Each CU included in the CE represents a given number of CUs in the U.S. population, which is considered to be the universe. The translation of sample families into the universe of families is known as weighting. However, since the unit of analysis for the CE is a CU, the weighting is performed at the CU level. Several factors are involved in determining the weight for each CU for which an interview is obtained. There are four steps in the weighting procedure: 1) The basic weight is assigned to an address and is the inverse of the probability of selection of the housing unit. 2) A weight control factor is applied to each interview if subsampling is performed in the field. 3) A noninterview adjustment is made for units where data could not be collected from occupied housing units. The adjustment is performed as a function of region, housing tenure, family size and race. 4) A final adjustment is performed to adjust the sample estimates to national population controls derived from the Current Population Survey. The adjustments are made based on both the CU's Member composition and the CU as a whole. The weight for the CU is adjusted for individuals within the CU to meet the controls for 14 age/race categories, 4 regions, and 4 region/urban categories. The CU weight is also adjusted to meet the control for total number of CUs and total number of CUs who own their living quarters. The weighting procedure uses an iterative process to ensure that the sample estimates meet all the population controls.

    NOTE: The weight for a consumer unit (CU) can be different for each quarter in which the CU participates in the survey, as the CU may represent a different number of CUs with similar characteristics.

    Mode of data collection

    Computer Assisted Personal Interview [capi]

  15. T

    United States Core Inflation Rate

    • tradingeconomics.com
    • id.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Oct 24, 2025
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    TRADING ECONOMICS (2025). United States Core Inflation Rate [Dataset]. https://tradingeconomics.com/united-states/core-inflation-rate
    Explore at:
    excel, csv, json, xmlAvailable download formats
    Dataset updated
    Oct 24, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Feb 28, 1957 - Sep 30, 2025
    Area covered
    United States
    Description

    Core consumer prices in the United States increased 3 percent in September of 2025 over the same month in the previous year. This dataset provides - United States Core Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

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TRADING ECONOMICS (2025). United States Core Personal Consumption Expenditure Price Index [Dataset]. https://tradingeconomics.com/united-states/core-pce-price-index

United States Core Personal Consumption Expenditure Price Index

United States Core Personal Consumption Expenditure Price Index - Historical Dataset (1959-01-31/2025-08-31)

Explore at:
csv, excel, json, xmlAvailable download formats
Dataset updated
Aug 15, 2025
Dataset authored and provided by
TRADING ECONOMICS
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Time period covered
Jan 31, 1959 - Aug 31, 2025
Area covered
United States
Description

Core PCE Price Index in the United States increased to 126.71 points in August from 126.42 points in July of 2025. This dataset provides - United States Core Pce Price Index - actual values, historical data, forecast, chart, statistics, economic calendar and news.

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