The Annual Social and Economic (ASEC) 2017 Supplement is part of the Current Population Survey (CPS) Series. The CPS is a source of the official Government statistics on employment and unemployment. The Census Bureau conducts the ASEC (known as the Annual Demographic File prior to 2003) over a three-month period, in February, March, and April, with most of the data collected in the month of March. The ASEC uses two sets of survey questions, the basic CPS and a set of supplemental questions. The CPS, administered monthly, is a labor force survey providing current estimates of the economic status and activities of the population of the United States. Specifically, the CPS provides estimates of total employment (both farm and nonfarm), nonfarm self-employed persons, domestics, and unpaid helpers in nonfarm family enterprises, wage, and salaried employees, and estimates of total unemployment. In addition to the basic CPS questions, respondents were asked questions from the ASEC, which provides supplemental data on poverty, geographic mobility/migration, and work experience. Comprehensive work experience information was given on the employment status, occupation, and industry of persons aged 15 and over. Additional data for persons aged 15 and older were available concerning weeks worked and hours per week worked, reason not working full-time, total income and supplemental income components. Demographic variables include age, sex, race, Hispanic origin, marital status, veteran status, educational attainment, occupation, and income. Data on employment and income refer to the previous calendar year, although demographic data refer to the time of the survey. The occupation and industry information variables in this data collection can help the data users identify individuals who worked in arts and culture related fields. The occupations are listed in a category entitled "Arts, Design, Entertainment, Sports, and Media Occupations," which includes professions such as artists, designers, actors, musicians, and writers (see Appendix B of the User Guide for further category details). Industries related to the arts and culture are in the "Arts, Entertainment, and Recreation" category (see Appendix C of the User Guide for further category details). For example, using the occupation and industry information variables from the ASEC help data users to obtain statistics about people in artists occupations that receive supplemental income, live public housing, or are full-time students. The ASEC data provided by the Census Bureau are distributed in a hierarchical file structure, with three record types present: Household, Family, and Person. The ASEC is designed to be a multistage stratified sample of housing units, where the hierarchical file structure can be thought of as a person within a family within a household unit. Here the main unit of analysis is the household unit.

Abstract (en): This data collection is comprised of data from the 2007 Annual Social and Economic Supplement (ASEC), and is a part of the Current Population Survey (CPS) Series. The Census Bureau conducts the ASEC (known as the Annual Demographic File prior to 2003) over a three-month period, in February, March, and April, with most of the data collected in the month of March. The ASEC uses two sets of survey questions, the basic CPS and a set of supplemental questions.The CPS, administered monthly, is a labor force survey providing current estimates of the economic status and activities of the population of the United States. Specifically, the CPS provides estimates of total employment (both farm and nonfarm), nonfarm self-employed persons, domestics, and unpaid helpers in nonfarm family enterprises, wage and salaried employees, and estimates of total unemployment.In addition to the basic CPS questions, respondents were asked questions from the ASEC, which provides supplemental data on poverty, geographic mobility/migration, and work experience. Comprehensive work experience information was given on the employment status, occupation, and industry of persons aged 15 and over. Additional data for persons aged 15 and older were available concerning weeks worked and hours per week worked, reason not working full time, total income and supplemental income components. Additional data are included that cover training and assistance received under welfare reform programs such as job readiness training, child care services, or job skill training. Data covering nine noncash income sources: food stamps, school lunch program, employer-provided group health insurance plan, employer-provided pension plan, personal health insurance, Medicaid, Medicare, CHAMPUS or military health care, and energy assistance are also included.Demographic variables include age, sex, race, Hispanic origin, marital status, veteran status, educational attainment, occupation, and income. Data on employment and income refer to the previous calendar year, although demographic data refer to the time of the survey.The original ASEC data provided by the Census Bureau are distributed in a hierarchical file structure, with three record types present: Household, Family, and Person. The ASEC is designed to be a multistage stratified sample of housing units, where the hierarchical file structure can be thought of as a person within a family within a household unit. Here the main unit of analysis is the household unit. For ease of analysis at the person-level, ICPSR created a rectangular file structure that contains a record for every person with the respective Household and Family variables prepended to the Person variables. Part 1 contains the rectangular data file and Part 2 contains the original hierarchical data file. The data contain five weight variables: Basic CPS earnings weight, A_ERNLWT; Basic CPS final weight, A_FNLWGT; March supplement Household weight, HSUP_WGT; March supplement Family weight, FSUP_WGT; ASEC supplement Person weight, MARSUPWT; Users are strongly encouraged to refer to the User Guide for detailed information on how to use the weights, as well as how they were derived. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Standardized missing values.; Created online analysis version with question text.; Checked for undocumented or out-of-range codes.. The civilian noninstitutional population of the United States living in housing units, and members of the Armed Forces living in civilian housing units on a military base or in a household not on a military base. A multistage probability sample was used for the housing unit. The sample was based on the results of the decennial Census, with coverage in all 50 states and the District of Columbia. More detailed information about the sampling frame can be found in the User Guide. computer-assisted personal interview (CAPI), computer-assisted telephone interview (CATI)ICPSR used syntax created by Jean Roth and the National Bureau of Economic Research (NBER) to read in the data for Part 1.The data in Part 2 are distributed exactly as they arrived from the data depositor. ICPSR...

analyze the current population survey (cps) annual social and economic supplement (asec) with r the annual march cps-asec has been supplying the statistics for the census bureau's report on income, poverty, and health insurance coverage since 1948. wow. the us census bureau and the bureau of labor statistics ( bls) tag-team on this one. until the american community survey (acs) hit the scene in the early aughts (2000s), the current population survey had the largest sample size of all the annual general demographic data sets outside of the decennial census - about two hundred thousand respondents. this provides enough sample to conduct state- and a few large metro area-level analyses. your sample size will vanish if you start investigating subgroups b y state - consider pooling multiple years. county-level is a no-no. despite the american community survey's larger size, the cps-asec contains many more variables related to employment, sources of income, and insurance - and can be trended back to harry truman's presidency. aside from questions specifically asked about an annual experience (like income), many of the questions in this march data set should be t reated as point-in-time statistics. cps-asec generalizes to the united states non-institutional, non-active duty military population. the national bureau of economic research (nber) provides sas, spss, and stata importation scripts to create a rectangular file (rectangular data means only person-level records; household- and family-level information gets attached to each person). to import these files into r, the parse.SAScii function uses nber's sas code to determine how to import the fixed-width file, then RSQLite to put everything into a schnazzy database. you can try reading through the nber march 2012 sas importation code yourself, but it's a bit of a proc freak show. this new github repository contains three scripts: 2005-2012 asec - download all microdata.R down load the fixed-width file containing household, family, and person records import by separating this file into three tables, then merge 'em together at the person-level download the fixed-width file containing the person-level replicate weights merge the rectangular person-level file with the replicate weights, then store it in a sql database create a new variable - one - in the data table 2012 asec - analysis examples.R connect to the sql database created by the 'download all microdata' progr am create the complex sample survey object, using the replicate weights perform a boatload of analysis examples replicate census estimates - 2011.R connect to the sql database created by the 'download all microdata' program create the complex sample survey object, using the replicate weights match the sas output shown in the png file below 2011 asec replicate weight sas output.png statistic and standard error generated from the replicate-weighted example sas script contained in this census-provided person replicate weights usage instructions document. click here to view these three scripts for more detail about the current population survey - annual social and economic supplement (cps-asec), visit: the census bureau's current population survey page the bureau of labor statistics' current population survey page the current population survey's wikipedia article notes: interviews are conducted in march about experiences during the previous year. the file labeled 2012 includes information (income, work experience, health insurance) pertaining to 2011. when you use the current populat ion survey to talk about america, subract a year from the data file name. as of the 2010 file (the interview focusing on america during 2009), the cps-asec contains exciting new medical out-of-pocket spending variables most useful for supplemental (medical spending-adjusted) poverty research. confidential to sas, spss, stata, sudaan users: why are you still rubbing two sticks together after we've invented the butane lighter? time to transition to r. :D

The URL says 2019-2023 but the data now covers 2020-2024 and will be updated annually.

I'm an independent contractor providing flexible end-to-end analytics support for startups and small teams. I offer low introductory rates, free consultation and estimates, and no minimums, so contact me today and let's chat about how I can help!

https://www.techbybryce.com

The Annual Social and Economic Supplement to the Current Population Survey (CPS-ASEC) is a fascinating, valuable, and comprehensive data set shared by the Census. There are about 700 fields at the person, family, and household levels, including age, income, health insurance coverage, health status, federal and state income tax, housing, and more.

Unfortunately, it isn't straightforward to use. Values are coded and must be found in PDFs. Years are split into different files. It can take a lot of work to discover the data you want.

This project makes this data readily available to anyone! I've combined the last five years into one file, parsed the PDFs, mapped hundreds of millions of values, and created an R Shiny app to help you search the fields and download your desired data.

You can also use my app to select and download just the fields you need from https://asec.brycechamberlainllc.com, and the code and details are at https://github.com/superchordate/ASEC-census-helper.

I haven't had as much time to work with this data as I'd like, so please let me know if there are issues, and I'll do my best to resolve them.

To provide estimates of employment, unemployment, and other characteristics of the general labor force, of the population as a whole, and of various subgroups of the population. Monthly labor force data for the country are used by the Bureau of Labor Statistics (BLS) to determine the distribution of funds under the Job Training Partnership Act. These data are collected through combined computer-assisted personal interviewing (CAPI) and computer-assisted telephone interviewing (CATI). In addition to the labor force data, the CPS basic funding provides annual data on work experience, income, health insurance, and migration data from the Annual Social and Economic Supplement (ASEC), and on school enrollment of the population from the October Supplement. Other supplements, some of which are sponsored by other agencies, are conducted biennially or intermittently.

This dataset reflects the final cleaned CPS-ASEC dataset for years 1963-2022 for replication of Autor et al. (2008). This dataset does not adjust for top-coded income variables in the CPS, and is used in Figure 1 of Autor et al. (2008).

This data set is built based on the ASEC Reports provided by the United States Census Buraeu. I have included with this dataset two JSON files which can be used to extract insight from the data. The Column Definitions JSON file containing a description of the column names with the values within the column placed in a list based on whether the column is categorical in nature or not. The Value Translation JSON file is a more detailed version of the Column Definitions file. This file separates the values by creating a dictionary with keys that point to its corresponding meaning (please view the example below)

The column named "H_TYPEBC" contains values ranging from 00 to 19 and have the following for its values: "10":string"Other" "11":string"Demolished" "12":string"House or trailer moved" "13":string"Outside segment" "14":string"Converted to perm business or storage" "15":string"Merged" "16":string"Condemned" "17":string"Built after April 1, 1980" "18":string"Unused line of listing sheet" "19":string"Other" "00":string"Interviewed or Type A" "01":string"Vacant -regular" "02":string"Vacant -storage of HHLD furniture" "03":string"Temp occ by persons with URE" "04":string"Unfit or to be demolished" "05":string"Under construction, not ready" "06":string"Converted to temp business or storage" "07":string"Occ by AF members or persons under 15" "08":string"Unocc tent or trailer site" "09":string"Permit granted, construction not started"

This was done to allow others to quickly transform the dataset from ASEC into other types of data and to understand the meaning behind the numbers and its columns.

All credit goes to the United States Census Bureau. The transformation of its pdf file containing the definitions and explanations for its values to JSON files were done to allow others to use the data set and develop projects based on US income, Household wage, family wage, and individual wage.

Context

For my final project for my Data Science Principle course at University of Texas at Austin, our team decided to do income prediction using census data. However, we had a hard time finding any data set that was not from the 1994 "Adult Data Set". We wanted a more updated version of the data set that we can use alongside the 1994 data set to do various comparisons and data analysis. So, we found data from the ASEC survey from 2020 on the US Census Bureau's website and preprocessed the data to look like the 1994 data set. This data set is derived from: https://www.census.gov/data/datasets/time-series/demo/cps/cps-asec.html.

Content

Data was extracted using the same conditions as the 1994 data set: ((AAGE>16) && (AGI>100) && (AFNLWGT>1)&& (HRSWK>0)).

Columns are almost exactly the same as the 1994 data set with a few changes: - We are missing a "capital-loss" column in the newer 2020 data set because we could not find such feature in the original ASEC data. - "income-90k-threshold" added, because 50k (which is the threshold used in the "Adult Data Set") in 1994 adjusted for inflation is 90k. - "coded-income" added. This contains more specific income brackets. -"native-country" and "occupation" may have countries and occupations not existing in the 1994 data set, and some countries and occupations existing in 1994 data set may not be in the 2020 data set.

https://www2.census.gov/programs-surveys/cps/datasets/2020/march/ASEC2020ddl_pub_full.pdf A_AGE = age A_FNLWGT = fnlwgt A_SEX = gender A_MARITL = marital-status A_PFREL = relationship A_HGA = education PRDTRACE = race PTOT_R (income recode)= income A_CLSWKR = class of worker A_MJOCC = occupation HRSWK = hours per week PENATVTY(coded) = native-country CAP_VAL = capital gain

"coded-income" means: 0 = NO INCOME 1 = UNDER $2,500 OR LOSS 2 = $2,500 TO $4,999 3 = $5,000 TO $7,499 4 = $7,500 TO $9,999 5 = $10,000 TO $12,499 6 = $12,500 TO $14,999 7 = $15,000 TO $17,499 8 = $17,500 TO $19,999 9 = $20,000 TO $22,499 10 = $22,500 to $24,999 11 = $25,000 to $27,499 12 = $27,500 to $29,999 13 = $30,000 to $32,499 14 = $32,500 to $34,999 15 = $35,000 to $37,499 16 = $37,500 to $39,999 17 = $40,000 to $42,499 18 = $42,500 to $44,999 19 = $45,000 to $47,499 20 = $47,500 to $49,999 21 = $50,000 to $52,499 22 = $52,500 to $54,999 23 = $55,000 to $57,499 24 = $57,500 to $59,999 25 = $60,000 to $62,499 26 = $62,500 to $64,999 27 = $65,000 to $67,499 28 = $67,500 to $69,999 29 = $70,000 to $72,499 30 = $72,500 to $74,999 31 = $75,000 to $77,499 32 = $77,500 to $79,999 33 = $80,000 to $82,499 34 = $82,500 to $84,999 35 = $85,000 to $87,499 36 = $87,500 to $89,999 37 = $90,000 to $92,499 38 = $92,500 to $94,999 39 = $95,000 to $97,499 40 = $97,500 to $99,999 41 = $100,000 and over

Acknowledgements

We wouldn't be here without the help of others. Special thanks to my team members: Julian Fritz, Chris Karouta, and Samuel Rizzo.

This data collection is comprised of data from the 2009 Annual Social and Economic Supplement (ASEC), and is a part of the Current Population Survey (CPS) Series. The Census Bureau conducts the ASEC (known as the Annual Demographic File prior to 2003) over a three-month period, in February, March, and April, with most of the data collected in the month of March. The ASEC uses two sets of survey questions, the basic CPS and a set of supplemental questions. The CPS, administered monthly, is a labor force survey providing current estimates of the economic status and activities of the population of the United States. Specifically, the CPS provides estimates of total employment (both farm and nonfarm), nonfarm self-employed persons, domestics, and unpaid helpers in nonfarm family enterprises, wage and salaried employees, and estimates of total unemployment. In addition to the basic CPS questions, respondents were asked questions from the ASEC, which provides supplemental data on poverty, geographic mobility/migration, and work experience. Comprehensive work experience information was given on the employment status, occupation, and industry of persons aged 15 and over. Additional data for persons aged 15 and older were available concerning weeks worked and hours per week worked, reason not working full time, total income and supplemental income components. Additional data are included that cover training and assistance received under welfare reform programs such as job readiness training, child care services, or job skill training. Data covering nine noncash income sources: food stamps, school lunch program, employer-provided group health insurance plan, employer-provided pension plan, personal health insurance, Medicaid, Medicare, CHAMPUS or military health care, and energy assistance are also included. Demographic variables include age, sex, race, Hispanic origin, marital status, veteran status, educational attainment, occupation, and income. Data on employment and income refer to the previous calendar year, although demographic data refer to the time of the survey. The original ASEC data provided by the Census Bureau are distributed in a hierarchical file structure, with three record types present: Household, Family, and Person. The ASEC is designed to be a multistage stratified sample of housing units, where the hierarchical file structure can be thought of as a person within a family within a household unit. Here the main unit of analysis is the household unit. (Source: ICPSR, 06/23/2011)

Content

Household is an occupied housing unit. Householder is a person in whose name the housing unit is rented or owned. This person must be at least 15 years old. Family household is a household in which there is at least 1 person present who is related to the householder by birth, marriage or adoption. Family is used to refer to a family household. In general, family consists of those related to each other by birth, marriage or adoption.

This data uses the householder's person weight to describe characteristics of people living in households. As a result, estimates of the number of households do not match estimates of housing units from the Housing Vacancy Survey (HVS). The HVS is weighted to housing units, rather than the population, in order to more accurately estimate the number of occupied and vacant housing units. For more information about the source and accuracy statement of the Annual Social and Economic Supplement (ASEC) of the Current Population Survey (CPS) see the technical documentation accessible at: http://www.census.gov/programs-surveys/cps/technical-documentation/complete.html

Context

This is a dataset from the U.S. Census Bureau hosted by the Federal Reserve Economic Database (FRED). FRED has a data platform found here and they update their information according the amount of data that is brought in. Explore the U.S. Census Bureau using Kaggle and all of the data sources available through the U.S. Census Bureau organization page!

• Update Frequency: This dataset is updated daily.

• Observation Start: 1940-01-01

• Observation End : 2019-01-01

Acknowledgements

This dataset is maintained using FRED's API and Kaggle's API.

Content

Household is an occupied housing unit. Householder is a person in whose name the housing unit is rented or owned. This person must be at least 15 years old. Family household is a household in which there is at least 1 person present who is related to the householder by birth, marriage or adoption. Family is used to refer to a family household. In general, family consists of those related to each other by birth, marriage or adoption.

This data uses the householder's person weight to describe characteristics of people living in households. As a result, estimates of the number of households do not match estimates of households from the Housing Vacancy Survey (HVS). The HVS is weighted to housing units, rather than the population, in order to more accurately estimate the number of occupied and vacant housing units. For more information about the source and accuracy statement of the Annual Social and Economic Supplement (ASEC) of the Current Population Survey (CPS) see the technical documentation accessible at: http://www.census.gov/programs-surveys/cps/technical-documentation/complete.html

Context

This is a dataset from the U.S. Census Bureau hosted by the Federal Reserve Economic Database (FRED). FRED has a data platform found here and they update their information according the amount of data that is brought in. Explore the U.S. Census Bureau using Kaggle and all of the data sources available through the U.S. Census Bureau organization page!

• Update Frequency: This dataset is updated daily.

• Observation Start: 1950-01-01

• Observation End : 2019-01-01

Acknowledgements

This dataset is maintained using FRED's API and Kaggle's API.

To provide estimates of employment, unemployment, and other characteristics of the general labor force, of the population as a whole, and of various subgroups of the population. Monthly labor force data for the country are used by the Bureau of Labor Statistics (BLS) to determine the distribution of funds under the Job Training Partnership Act. These data are collected through combined computer-assisted personal interviewing (CAPI) and computer-assisted telephone interviewing (CATI). In addition to the labor force data, the CPS basic funding provides annual data on work experience, income, health insurance, and migration data from the Annual Social and Economic Supplement (ASEC), and on school enrollment of the population from the October Supplement. Other supplements, some of which are sponsored by other agencies, are conducted biennially or intermittently.

Content

Household is an occupied housing unit. Householder is a person in whose name the housing unit is rented or owned. This person must be at least 15 years old. Family household is a household in which there is at least 1 person present who is related to the householder by birth, marriage or adoption. Family is used to refer to a family household. In general, family consists of those related to each other by birth, marriage or adoption.

This data uses the householder's person weight to describe characteristics of people living in households. As a result, estimates of the number of households do not match estimates of households from the Housing Vacancy Survey (HVS). The HVS is weighted to housing units, rather than the population, in order to more accurately estimate the number of occupied and vacant housing units. For more information about the source and accuracy statement of the Annual Social and Economic Supplement (ASEC) of the Current Population Survey (CPS) see the technical documentation accessible at: http://www.census.gov/programs-surveys/cps/technical-documentation/complete.html

Context

This is a dataset from the U.S. Census Bureau hosted by the Federal Reserve Economic Database (FRED). FRED has a data platform found here and they update their information according the amount of data that is brought in. Explore the U.S. Census Bureau using Kaggle and all of the data sources available through the U.S. Census Bureau organization page!

• Update Frequency: This dataset is updated daily.

• Observation Start: 1940-01-01

• Observation End : 2019-01-01

Acknowledgements

This dataset is maintained using FRED's API and Kaggle's API.

+Due to rounding, some categories do not sum to 100 percent.a percentage is based on population age 18, not total population.b refers to percentage of households with members under age 18c refers to percentage of foreign-born individualsSources for US data: 1–2012 CPS ASEC; 2–2014 CPS ASEC; 3–2013 CPS ASEC.[24–26]Respondent Demographics, Unweighted+.

This data collection is comprised of responses from the March and April installments of the 2006 Current Population Survey (CPS). Both the March and April surveys used two sets of questions, the basic CPS and a separate supplement for each month.The CPS, administered monthly, is a labor force survey providing current estimates of the economic status and activities of the population of the United States. Specifically, the CPS provides estimates of total employment (both farm and nonfarm), nonfarm self-employed persons, domestics, and unpaid helpers in nonfarm family enterprises, wage and salaried employees, and estimates of total unemployment.In addition to the basic CPS questions, respondents were asked questions from the March supplement, known as the Annual Social and Economic (ASEC) supplement. The ASEC provides supplemental data on work experience, income, noncash benefits, and migration. Comprehensive work experience information was given on the employment status, occupation, and industry of persons 15 years old and older. Additional data for persons 15 years old and older are available concerning weeks worked and hours per week worked, reason not working full time, total income and income components, and place of residence on March 1, 2005. The March supplement also contains data covering nine noncash income sources: food stamps, school lunch program, employer-provided group health insurance plan, employer-provided pension plan, personal health insurance, Medicaid, Medicare, CHAMPUS or military health care, and energy assistance. Questions covering training and assistance received under welfare reform programs, such as job readiness training, child care services, or job skill training were also asked in the March supplement.Respondents were asked supplemental questions in April about the economic situation of persons and families for the previous year. All household members 15 years of age and older that are a biological parent of children in the household from an absent parent were asked detailed questions about child support and alimony. Information regarding child support was collected to determine the size and distribution of the population with children affected by divorce or separation, or other relationship status change. Moreover, the data were collected to better understand the characteristics of persons requiring child support, and to help develop and maintain programs designed to assist in obtaining child support. These data highlight alimony and child support arrangements made at the time of separation or divorce, amount of payments actually received, and value and type of any property settlement.The April supplement data were matched to March supplement data for households that were in the sample in both March and April 2006. In March 2006, there were 4,635 household members eligible, of which 1,453 required imputation of child support data. When matching the March 2006 and April 2006 data sets, there were 190 eligible people on the March file that did not match to people on the April file. Child support data for these 190 people were imputed. The remaining 1,263 imputed cases were due to nonresponse to the child support questions. Demographic variables include age, sex, race, Hispanic origin, marital status, veteran status, educational attainment, occupation, and income. Data on employment and income refer to the preceding year, although other demographic data refer to the time at which the survey was administered.

To provide estimates of employment, unemployment, and other characteristics of the general labor force, of the population as a whole, and of various subgroups of the population. Monthly labor force data for the country are used by the to determine the distribution of funds under the Job Training Partnership Act. These data are collected through combined computer-assisted personal interviewing (CAPI) and computer-assisted telephone interviewing (CATI). In addition to the labor force data, the CPS basic funding provides annual data on work experience, income, health insurance, and migration data from the Annual Social and Economic Supplement (ASEC), and on school enrollment of the population from the October Supplement. Other supplements, some of which are sponsored by other agencies, are conducted biennially or intermittently

To provide estimates of employment, unemployment, and other characteristics of the general labor force, of the population as a whole, and of various subgroups of the population. Monthly labor force data for the country are used by the to determine the distribution of funds under the Job Training Partnership Act. These data are collected through combined computer-assisted personal interviewing (CAPI) and computer-assisted telephone interviewing (CATI). In addition to the labor force data, the CPS basic funding provides annual data on work experience, income, health insurance, and migration data from the Annual Social and Economic Supplement (ASEC), and on school enrollment of the population from the October Supplement. Other supplements, some of which are sponsored by other agencies, are conducted biennially or intermittently

To provide estimates of employment, unemployment, and other characteristics of the general labor force, of the population as a whole, and of various subgroups of the population. Monthly labor force data for the country are used by the to determine the distribution of funds under the Job Training Partnership Act. These data are collected through combined computer-assisted personal interviewing (CAPI) and computer-assisted telephone interviewing (CATI). In addition to the labor force data, the CPS basic funding provides annual data on work experience, income, health insurance, and migration data from the Annual Social and Economic Supplement (ASEC), and on school enrollment of the population from the October Supplement. Other supplements, some of which are sponsored by other agencies, are conducted biennially or intermittently

We document trends in earnings volatility separately by gender using unique linked survey data from the CPS ASEC and Social Security earnings records for the tax years spanning 1995–2015. The exact data link permits us to focus on differences in measured volatility from earnings nonresponse, survey attrition, and measurement between survey and administrative earnings data reports, while holding constant the sampling frame. Our results for both men and women suggest that the level and trend in volatility is similar in the survey and administrative data, showing substantial business-cycle sensitivity among men but no overall trend among continuous workers, while women demonstrate no change in earnings volatility over the business cycle but a declining trend. A substantive difference emerges with the inclusion of imputed earnings among survey nonrespondents, suggesting that users of the ASEC drop earnings nonrespondents.

Poverty In Utah, extracted from the Annual Social and Economic Supplement (ASEC) to the Current Population Survey (CPS)