1930/31 Time Diary Data from College Educated Women in the United States

IPUMS Time Use, in partnership with Dr. Teresa Harms of the Centre for Time Use Research, is proud to announce the public release of the 1930-31 USDA College Women Time Use study. These data provide researchers a unique look into the lives of married, college-educated women at the beginning of the Great Depression. The respondents were asked to complete a detailed record of their time use for seven consecutive 24-hour periods (see a sample daily diary below; borrowed with permission from Teresa Harms, CTUR). The women described activities in their own words, listing them consecutively as they occurred throughout the day, with a minimum interval of five minutes. They also recorded the time devoted to various homemaking tasks by other household members and paid help as well as demographic and work status data and information about the household. The data also include the verbatim activity reports and the occupations the women reported at the time of data collection. All data are available via the IPUMS American Heritage Time Use Study (AHTUS) extract system.

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2021 IPUMSI New Data Release Highlights

Map depicting where IPUMSI has dataIPUMS International has added 19 new census samples and new labor force surveys.  First-time data release countries include four new countries from four different continents—Finland, Mauritius, Myanmar, and Suriname. Other newly added samples extend pre-existing series. Another first is the addition of labor force surveys from Spain and Italy. See a summary of the full IPUMS collection on the IPUMSI samples page.

In addition to the new data, check out the usage-enhancing highlights that are part of this recent release.

  • Spatially-harmonized migration variables
  • New work variables that maximize the utility of newly-harmonized labor force surveys
  • New disability variables per The Washington Group recommendations
  • Access to harmonization tables and code for registered IPUMS data users
  • Population density variables for all samples with the requisite geography- POPDENSGEO1 and POPDENSGEO2 capture the population density in persons per square kilometer of the first and second administrative units of the household, respectively.
  • Variables AREAMOLLWGEO1 and AREAMOLLWGEO2 provided for additional convenience
  • New lower level single-sample variables for select countries, as well as regionalized variables and shapefiles at the 3rd administrative level for Senegal 2013 and 2002, South Africa 2016, 2011, and 2007, and Uganda 2014, and Myanmar 2014

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Locating Dimensions of Women’s Empowerment in Family Planning in Burkina Faso

By Tayler Nelson

Women’s “empowerment,” defined by Naila Kabeer[1] as “the expansion of people’s ability to make strategic life choices in a context where this ability was previously denied to them,” has been shown[2] to be associated with greater birth spacing, lower fertility, and lower rates of unplanned pregnancy. Yet scholars disagree[3] on how to measure women’s empowerment, and meanings of empowerment can shift across geographic and cultural contexts.

IPUMS PMA’s family planning surveys include variables that can help researchers investigate dimensions of women’s empowerment in family planning. All samples include indicators of women’s knowledge about family planning methods. Many survey rounds dig deeper, collecting data that can be used by researchers and policymakers.

The Burkina Faso 2018 Round 6 survey includes a range of variables measuring family planning attitudes, beliefs, and decision-making dynamics that relate to women’s empowerment. I used a weighted polychoric factor analysis[4] to investigate women’s empowerment in family planning in Burkina Faso. Factor analysis can help researchers reduce a large number of observed variables by identifying similar response patterns among observed variables and grouping them into a smaller set of underlying variables, or factors. Through analyzing how variables are grouped and the strength and signs of coefficients within these groups, researchers can glean insight into which sets of observed variables might be best at measuring an unobserved construct such as women’s empowerment.

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