IPUMS has an exciting new data collection to announce: IPUMS MICS!
IPUMS MICS is the integrated version of UNICEF MICS (Multiple Indicator Cluster Surveys), the largest and most robust source of data on women and children’s well-being across the globe, including countries in Africa, Eastern Europe, Asia, and Latin America. Separate datasets cover women of childbearing age, children aged 0 to 4, children aged 5 to 17, respondent’s birth history, men, household members, and household characteristics.
Currently, IPUMS MICS includes harmonization of data from 202 MICS samples, which represent 88 countries, and cover surveys conducted between 2005-forward. There are over 800 integrated variables currently available on our website. Future releases will expand the sample and variable coverage of IPUMS MICS.
R users have a powerful new way to access IPUMS NHGIS!
The July 2023 release of ipumsr 0.6.0 includes a fully-featured set of client tools enabling R users to get NHGIS data and metadata via the IPUMS API. Without leaving their R environment, users can find, request, download and read in U.S. census summary tables, geographic time series, and GIS mapping files for years from 1790 through the present. This blog post gives an overview of the possibilities and describes how to get started.
What you can do with ipumsr
Request and download NHGIS data
You can use ipumsr to specify the parameters of an NHGIS data extract request and submit that request for processing by the IPUMS servers. You can request any of the data products that are available through the NHGIS Data Finder: summary tables, time series tables, and shapefiles. You can also specify general formatting parameters (e.g., file format or time series table layout) to customize the structure of your data extract.
Once you have specified a data extract, you can use a series of ipumsr functions to:
submit the extract request to the IPUMS servers for processing
check on the extract status
wait for the extract to complete
download the extract as soon as it’s ready
load the data into R with detailed data field descriptions.
This workflow allows you to go from a set of abstract NHGIS data specifications to analyzable data, all without having to leave your R session!
A new exhibit, “Going Global: IPUMS International,” is now on display at IPUMS headquarters, housed at the University of Minnesota. The exhibit features pieces that tell the history and scope of IPUMS International.
Beginning in 1999 with a social science infrastructure grant from the National Science Foundation, IPUMS International had a simple yet audaciously ambitious goal: preserve the world’s microdata resources and democratize access to those resources. Twenty-four years later, the goals are: collecting and preserving census and survey data and documentation; harmonizing those data; and disseminating the harmonized data free of charge. The data series includes information on an impressive range of population characteristics, including fertility, nuptiality, life-course transitions, migration, labor-force participation, occupational structure, education, ethnicity, and household composition.
Dr. Bob McCaa
Source data for IPUMS International are generously provided by participating national statistical offices. Our staff develop and nurture relationships with representatives of NSOs from around the world. As IPUMS International got underway, co-principal investigator Dr. Bob McCaa, University of Minnesota Department of History, “proved to have formidable persuasive powers and managed to convince . . . agency directors of the benefits of preservation and access to scientific information.” Over time, IPUMS International developed a team of research scientists articulating to a broad international audience the significance of the IPUMS data collection, harmonization, and preservation work. Today, an NSF advisory committee, senior personnel including research scientists and data analysts, an external advisory panel, and graduate and undergraduate research assistants all support the work of IPUMS International.
Time diary data offer researchers an opportunity to visualize daily life in a way that just isn’t possible with other data and demonstrating how people spend time. Respondents report every activity that they engage in (along with where and who they were with) over the course of the day, which means that time diaries can indicate how much time was spent in various activities as well as when activities occur during the day (e.g., timing) and the order in which they occur (i.e., sequencing) . This blog post will describe how to transform IPUMS ATUS data to perform these types of analyses, illustrate how to create a tempogram (including sample code), and link to additional resources for creating tempograms and performing sequence analysis.
While there are several ways to leverage the unique properties of time diary data, analysts are increasingly interested in creating tempograms and conducting sequence analyses, both of which capitalize on the temporal specificity of time diary data. These techniques allow researchers to explore the timing and order of activities over the course of a day. Both creating tempograms and conducting sequence analysis require time units that are consistent across respondents. Most time diary data are not natively in this format.
As part of the IPUMS mission to democratize data, our User Support team strives to answer your questions about the data. Over time, some questions are repeated. This blog post is an extension of an earlier series addressing frequently asked questions. Maybe you’ll learn something. Perhaps you’ll just find the information interesting. Regardless, we hope you enjoy it!
Here’s one of those questions:
How can I use IPUMS CPS to calculate the Alternative Measures of Unemployment published by the BLS?
Every month the Bureau of Labor Statistics (BLS) publishes a set of Alternative Measures of Labor Underutilization as part of its well-known Employment Situation News Release. A common question we are asked at IPUMS is how to calculate these rates using IPUMS CPS data. The “headline” unemployment figure is known as U-3 and is a straightforward calculation using only the main employment status variable, EMPSTAT. However, the other measures are not quite as simple. Nonetheless, these can be calculated using IPUMS CPS! Using the table below, you can calculate these rates using the public use microdata.
We attend the Population Association of America (PAA) annual meeting every year and we are always inspired by the outstanding research being shared. We love having conversations with users at our booth, at poster sessions, at presentations, or even just in the lobby. This year was a little extra special because we also gathered to celebrate 30 years of IPUMS.
IPUMS Director Steve Ruggles shares a few words at the IPUMS 30 Celebration
We also were thrilled to celebrate with Elizabeth Heger Boyle. She was honored with the Harriet B. Presser Award for her record of sustained research contributions to the study of gender and demography. Dr. Boyle pioneered IPUMS Global Health, democratizing access to women and children’s health data and unleashing innovative new streams of cross-national comparative research.
If you are an avid IPUMS user who reads every email update, you have probably noticed that we pepper you with requests to complete our annual user survey. Perhaps you have asked yourself, “why bother?” or assumed we don’t really want YOUR feedback–that the survey is meant for a different type of IPUMS data user. We conduct an annual survey of data users for three reasons: 1) we value your input, 2) we want to invest in areas that benefit users, and 3) we reference your feedback when reporting to funders on current work and in applying for support to expand IPUMS. Let me assure you, we want to hear from YOU and we hope you take a few minutes to complete the survey.
Feedback is an important part of the IPUMS lifecycle. Our mission is to democratize access to the world’s social and economic data; data users are central to the success of this mission. We can learn a lot from registration numbers for each IPUMS data collection, the number and timing of online analysis or custom data extract requests, #poweredbyIPUMS publications, or questions and comments submitted to our User Support team. However, none of these is a substitute for directly asking users what they like most about IPUMS and what we can do better.
If you are an avid IPUMS user who reads every email update, you have probably noticed that we pepper you with requests to