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American Time Use Survey (ATUS): Arts Activities, [United States], 2003-2018

Version
v4
Resource Type
Dataset : survey data
Creator
  • United States. Bureau of Labor Statistics
Other Title
  • ATUS: Arts Activities, 2003-2018 (Alternative Title)
  • Version 4 (Subtitle)
Collective Title
  • American Time Use Survey (ATUS) Series
Publication Date
2015-09-08
Publication Place
Ann Arbor, Michigan
Publisher
  • Inter-University Consortium for Political and Social Research
Language
English
Free Keywords
Schema: ICPSR
arts; arts participation; caregivers; civic engagement; consumer expenditures; education; entertainment; households; leisure; personal care; recreation; religious behavior; sports; travel; volunteers; work
Description
  • Abstract

    The American Time Use Survey (ATUS) is the Nation's first federally administered, continuous survey on time use in the United States. This multi-year data collection contains information on the amount of time (in minutes) that people spent doing various activities in the years 2003 through 2018, and asks about a much broader range of topics covered than just what is in this study, which focuses on arts activities. But this particular study focuses solely upon the time spent on a given day in all types of activity. For this data collection, 201,151 respondents were randomly selected from a subset of households that completed their eighth and final month of interviews for the Current Population Survey (CPS). Only one respondent per household, aged 15 or older, was randomly selected to participate. Respondents were interviewed one time about how they spent their time on the previous day starting at 4:00 a.m. and ending at 4:00 a.m. on the interview day. The ATUS classifies activities into 18 Tier 1 categories. Each Tier 1 category contains multiple Tier 2 categories providing a second level of classification. Overall there are 96 Tier 2 categories with the average being 5 sub-classifications per Tier 1 category. In total, the ATUS contains 424 unique activity codes designated by a six digit classification code. Additionally, the study provides demographic information--including sex, age, ethnicity, race, education, employment, and children in the household.
  • Abstract

    The primary purpose of this data collection is to develop nationally representative estimates (in minutes) of how people spend their time on any given day.
  • Methods

    Between the years 2003-2018 201,151 respondents completed the ATUS survey. The survey results are based on computer-assisted telephone interviews (CATI) with a representative sample of residents living in households in the United States that are at least 15 years of age, with the exception of active military personnel and people residing in institutions such as nursing homes and prisons. For additional details on the study design please refer to chapter 3 within the User Guide sub-section portion of the larger ATUS 2003-2018 User Guide document.
  • Methods

    Variables for this data collection provide information about the amount of time (in minutes) people spend doing various activities for any given 24-hour period. The period in question is from 4:00 am the day preceding the interview up through 4:00 am the day of the interview. Activities are classified into 18 Tier 1 categories which include: Personal care; Household activities; Caring for and helping household members; Caring for and helping non-household members; Work and work related activites; Education; Consumer purchases; Professional and personal care services; Household services; Government services and civic obligations; Eating and drinking; Socializing, relaxing, and leisure; Sports, exercise, and recreation; Religious and spiritual activities; Volunteer activities; Telephone calls; Traveling; Unable to classify; There are a total of 424 unique activity codes in Dataset 1 and listed in the ATUS Activity Lexicon 2003-2018 portion of the User Guide document. Dataset 1 also contains additional demographic variables such as age, gender, race, ethnicity, education, employment, and children in the household. Additionally, there are two variables that designate what day of the week the interview took place on and whether or not that day was a holiday or not.
  • Methods

    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: Created variable labels and/or value labels.; Created online analysis version with question text.; Checked for undocumented or out-of-range codes..
  • Methods

    Response Rates: The average response rate to the ATUS from 2003-2018 was 53.1 percent. The response rate for each year from 2003 through 2018 are as follows: 2003: 57.8 percent; 2004: 57.3 percent; 2005: 56.6 percent; 2006: 55.1 percent; 2007: 52.5 percent; 2008: 54.6 percent; 2009: 56.6 percent; 2010: 56.9 percent; 2011: 54.6 percent; 2012: 53.2 percent; 2013: 49.9 percent; 2014: 51.0 percent; 2015: 48.5 percent; 2016: 46.8 percent; 2017: 45.6 percent; 2018: 43.3 percent; For additional information on how response rates were calculated please refer to section 3.6 within the User Guide sub-section portion of the larger ATUS 2003-2018 User Guide document.
  • Abstract

    Datasets:

    • DS0: Study-Level Files
    • DS1: Activity Summary Data
    • DS2: Replicate Weights Data
Temporal Coverage
  • Time period: 2003--2018
  • 2003 / 2018
  • Collection date: 2003--2018
  • 2003 / 2018
Geographic Coverage
  • United States
Sampled Universe
All residents living in households in the United States that are at least 15 years of age, with the exception of active military personnel and people residing in institutions such as nursing homes and prisons.
Sampling
The sample for this data collection was drawn from households that had completed their final month of interviews for the Current Population Survey (CPS). The ATUS utilizes a stratified three-stage sampling approach. The first stage is at the state level so that the sample is in the same proportion as to the proportion of the population of that state compared to the population of the country. The second stage of the sample is selection at the household level stratified by key demographics. The third stage is selection of the respondent within the household.
Collection Mode
  • computer-assisted telephone interview (CATI)
Note
2020-05-20 Updated to include 2018 data, as well as adding online analysis.2019-05-01 Data through 2017 were added to the data collection.2016-11-28 An infographic on TV watching for 2015 was added. The 2010-2014 summary tables file was updated to create two files that include state-level summary tables. One file includes summary tables that provide percentages of time that the population spent doing selected activities and percentages of the population that did them. The second 2010-2014 summary tables file covers numbers of persons and average hours per day spent on each activity. 2016-10-20 Data for 2015 and unpublished ATUS summary tables for 2011-2015 (produced by the BLS) were added to the data collection.2016-03-10 Unpublished ATUS summary tables produced by the United States Bureau of Labor Statistics have been added to the data collection.
Availability
Download
This version of the study is no longer available on the web. If you need to acquire this version of the data, you have to contact ICPSR User Support (ICPSR-help@umich.edu).
Alternative Identifiers
  • 36268 (Type: ICPSR Study Number)
Relations
  • Is previous version of
    DOI: 10.3886/ICPSR36268.v5
  • Is new version of
    DOI: 10.3886/ICPSR36268.v3
Publications
  • Augustine, Jennifer March, Prickett, Kate C., Negraia, Daniela V.. Doing it all? Mothers' college enrollment, time use, and affective well-being. Journal of Marriage and Family.80, 963-974.2018.
    • ID: 10.1111/jomf.12477 (DOI)
  • Cardon, James H., Eide, Eric R., Phillips, Kerk L., Showalter, Mark H.. A model of sleep, leisure and work over the business cycle. Journal of Economic Dynamics and Control.95, 19-26.2018.
    • ID: 10.1016/j.jedc.2018.08.003 (DOI)
  • Gimenez-Nadal, J.I., Molina, Jose A., Velilla, Jorge. The commuting behavior of workers in the United States: Differences between the employed and the self-employed. Journal of Transport Geography.66, 19-29.2018.
    • ID: 10.1016/j.jtrangeo.2017.10.011 (DOI)
  • Gobbi, Paula E.. Childcare and commitment within households. Economic Theory.176, 503-551.2018.
    • ID: 10.1016/j.jet.2018.04.010 (DOI)
  • Greiman, Lillie, Fleming, S.P., Ward, Bryce, Myers, Andrew, Ravesloot, Craig. Life starts at home: Bathing,exertion and participation for people with mobility impairment. Archives of Physical Medicine and Rehabilitation.99, (7), 1289-1294.2018.
    • ID: 10.1016/j.apmr.2017.11.015 (DOI)
  • Kaushal, Neeraj, Muchomba, Felix M.. Missing time with parents: Son preference among Asians in the USA. Journal of Population Economics.31, (2), 397-427.2018.
    • ID: 10.1007/s00148-017-0668-6 (DOI)
  • Kimbrough, Gray. Xboxes and Ex-workers? Gaming and Labor Supply of Young Adults in the U.S. MPRA Paper No. 87311.Munich, Germany: Munich Personal RePEc Archive. 2018.
    • ID: https://mpra.ub.uni-muenchen.de/87311/1/MPRA_paper_87311.pdf (URL)
  • Kydland, Finn, Pretnar, Nicholas. The Costs and Benefits of Caring: Aggregate Burdens of an Aging Population. Society for Economic Dynamics Annual Meeting 2018.Mexico City, Mexico. 2018.
    • ID: https://economicdynamics.org/meetpapers/2018/paper_271.pdf (URL)
  • McConnell, Kenneth E., Siikamaki, Juha V.. Seeking external evidence to assess benefit transfers for environmental policy. Environmental and Resource Economics.69, (3), 555-573.2018.
    • ID: 10.1007/s10640-017-0212-x (DOI)
  • Ogilvie, Rachel P., Patel, Sanjay R.. Changing national trends in sleep duration: Did we make America sleep again?. Sleep.41, (4), 1-3.2018.
    • ID: 10.1093/sleep/zsy055 (DOI)
  • Pepin, Joanna R., Sayer, Liana C., Casper, Lynne M.. Marital status and mothers' time use: Childcare, housework, leisure, and sleep. Demography.55, (1), 107-133.2018.
    • ID: 10.1007/s13524-018-0647-x (DOI)
  • Robbins, Rebecca, Jean-Louis, Girardin. Sleep at work: The economic and societal argument for workplace-based health promotion tailored to shift workers. American Journal of Health Promotion.32, (7), 1641-1644.2018.
    • ID: 10.1177/0890117118790621d (DOI)
  • Song, Chen, Wei, Chao. Travel time use over five decades. Transportation Research, Part A: Policy and Practice.116, 73-96.2018.
    • ID: 10.1016/j.tra.2018.05.021 (DOI)
  • Stone, Arthur A., Schneider, Stefan, Krueger, Alan, Schwartz, Joseph E., Deaton, Angus. Experiential wellbeing data from the American Time Use Survey: Comparisons with other methods and analytic illustrations with age and income. Social Indicators Research.136, (1), 359-378.2018.
    • ID: 10.1007/s11205-016-1532-x (DOI)
  • Wan, He, Weingartner, Rose M., Sayer, Liana C.. Subjective Well-Being of Eldercare Providers: 2012-2013. Current Population Survey Reports.Washington, DC: U.S Census Bureau; U.S. Government Printing Office. 2018.
    • ID: https://www.census.gov/content/dam/Census/library/publications/2018/demo/P23-215.pdf (URL)
  • Ward, Michael R.. Cutting class to play video games. Information Economics and Policy.42, 11-19.2018.
    • ID: 10.1016/j.infoecopol.2017.10.001 (DOI)
  • Gimenez-Nadal, Jose Ignacio, Molina, Jose Alberto, Velilla, Jorge. Spatial distribution of U.S employment in an urban efficiency wage setting. Journal of Regional Science.58, 141-158.2017.
    • ID: 10.1111/jors.12351 (DOI)
  • Yamashita, Takashi, Bardo, Anthony R., Liu, Darren. Time spent on beneficial leisure activities among elder caregivers in their third age. Leisure Sciences.40, (5), 356-373.2017.
    • ID: 10.1080/01490400.2016.1256798 (DOI)
  • Rife, Mary Lou, King, Damaris, Thomas, Samuel, Li, Rose. Measuring Cultural Engagement: A Quest for New Terms, Tools, and Techniques. Summary of a Joint Research Symposium titled “Measuring Cultural Engagement amid Confounding Variables: A Reality Check,” held at the Gallup headquarters in Washington, DC, June 2–3, 2014.Washington, DC: National Endowment for the Arts. 2014.
    • ID: https://www.arts.gov/sites/default/files/measuring-cultural-engagement.pdf (URL)
  • National Endowment for the Arts. An Average Day in the Arts: State Participation Patterns from the American Time Use Survey for 2006-2010. NEA Research Note #106.Washington, DC: National Endowment for the Arts. 2012.
    • ID: http://arts.gov/sites/default/files/106.pdf (URL)
  • National Endowment for the Arts. Time and Money: Using Federal Data to Measure the Value of Performing Arts Activities. NEA Research Note #102.Washington, DC: National Endowment for the Arts. 2011.
    • ID: http://arts.gov/sites/default/files/102.pdf (URL)
  • Robinson, John P.. IT use and leisure time displacement: Convergent evidence over the last 15 years. Information, Communication and Society.14, (4), 495-509.2011.
    • ID: 10.1080/1369118X.2011.562223 (DOI)
  • Vernon, Margaret K.. Time use as a way of examining contexts of adolescent development in the United States. Society and Leisure.28, (2), 549-570.2005.
    • ID: 10.1080/07053436.2005.10707695 (DOI)

Update Metadata: 2020-05-20 | Issue Number: 2 | Registration Date: 2019-05-01

United States. Bureau of Labor Statistics (2015): American Time Use Survey (ATUS): Arts Activities, [United States], 2003-2018. Version 4. American Time Use Survey (ATUS) Series. Version: v4. ICPSR - Interuniversity Consortium for Political and Social Research. Dataset. https://doi.org/10.3886/ICPSR36268.v4