IPUMS International

By Derek Burk

When you’re building an IPUMS International extract, you almost always have a central topic or question in mind: How is children’s educational attainment influenced by their parents’ education levels? How have migration patterns in Latin America changed in the past few decades? How do age and disability status interact to influence employment?

In other words, you almost always know the main variables you want in your extract. To study education, you’ll need EDATTAIN. To study lifetime international migration, you’ll need BPLCOUNTRY. To study disability and employment, you’ll need DISABLED and EMPSTAT.

Wouldn’t it be great if there was a magic wand that could add all the samples with your variable(s) of interest to your extract with just a flick of the wrist?

If you’re nodding your head in agreement right now, we think you’ll love our new feature: variable based sample selection! It doesn’t involve a wand, but it is a magical way to select samples based on the variables you need.

Enabling variable based sample selection

Variable based sample selection is not enabled by default, so to use it, you’ll first need to turn it on. From the top level Select Variables page on the IPUMS International website, click on the Display Options button:

This will call up the Display Options menu. The variable based sample selection feature is listed at the very top of the menu. To turn the feature on, click the radio button next to “Enabled”, then click the Apply Selections button at the bottom.

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By Rodrigo Lovaton Davila

IPUMS International recently added twenty-one new harmonized variables that expand the thematic coverage of the data collection and enable new possibilities for research. Most notably, the data release introduces harmonized variables representing sample level information, including selected characteristics of the statistical operation and the sampling design (accessible in technical household). This information was previously available in the sample descriptions section, but is now also accessible through variables that can be included in data extracts. Read on for more details on these new sample-level variables and a few new work and household amenity variables!

New variables about the statistical operation describe whether the data correspond to a census or a survey; whether enumeration was de jure or de facto; the type of form received by respondents in the sample; and the month of data collection. The IPUMS International data collection currently includes 395 census samples, 233 labor force surveys, and 27 population surveys.

FORMTYPE allows users to identify whether the data for each sample consist of responses to a single, standard questionnaire applied to the entire population; responses to a short or long form, in a census that gathered more information from a sample of the population; or records derived from administrative registers (with no questionnaire used in data collection.) Most datasets in the collection correspond to one standard questionnaire (79% of 395 census samples). For censuses where a short and a long form were applied, the samples in IPUMS typically correspond to the long questionnaire (78% of 78 samples), which includes additional questions and is richer for research purposes.

ENUMTYPE indicates whether the enumeration was de jure or de facto, an important distinction for understanding how the population was counted in the census operation. Some censuses enumerate combining both de jure (usual residents) and de facto (those present on the census reference date whether resident or visitor), which is reflected in this new variable. Importantly, users can work with the existing variable RESIDENT to eliminate double-counting of persons who were enumerated both at their permanent residence and at the residence they were visiting on census night. ENUMMO complements the variable YEAR to provide a more accurate indicator of the timing of data collection.

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By Derek Burk, Lara Cleveland, Jane Lee, Rodrigo Lovaton, and Sula Sarkar

Great news for IPUMS International (IPUMSI) users! Our ever-expanding census and survey data collection has just released new harmonized census samples from Honduras (2013), Kenya (2019), Malawi (2018), Mongolia (2010, 2020), and Mozambique (2017). We now have an average of 4.5 censuses per country. The Kenya census collection now spans 50 years!

This release also includes a large series of quarterly Labor Force Surveys from the Philippines (1997-2019). The 91 waves of the Philippines Labor Force Survey contain a total of 18 million person records.

Many thanks to the National Statistical Office partners in these countries for their ongoing contributions.

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By Lara Cleveland

IPUMS International regularly asks representatives of National Statistical Offices (NSOs) around the world to share their data with the research community. While IPUMS offers a license payment to countries for the right to redistribute microdata, NSO representatives are most interested in how sharing data with IPUMS will benefit the people of their countries. After 30 years of harmonizing data that NSOs have shared with us, IPUMS can indeed point to innovative research from data users all over the world, many at major universities in these partner countries. Directors of statistical offices, especially those with close ties to academia, are thrilled that the data are used for scholarly scientific production and for the purpose of educating the next generation. However, most of these leaders are much more interested in how data sharing leads to effective policy. And they want examples. They are essentially asking how the data have been “used for good,” as the original IPUMS tagline, “Use it for good!” implores.

In response, IPUMS has been following data-to-policy trails where we can find them. The United Nations’ efforts to establish and measure the Sustainable Development Goals (SDGs) have provided wins in this area. Early in the life of the SDGs, colleagues from the World Health Organization visited IPUMS to leverage detailed information in the occupational variables for locating the health workforce. Microdata from censuses helped them measure the density of a range of health worker classifications at subnational levels. The International Organization for Migration (IOM) did similar work to disaggregate census-based SDGs by migratory status. At the start of the pandemic, The United Nations Population Fund (UNFPA) used IPUMS census microdata to spin up a dashboard showing the living arrangements of older adults, again at subnational levels. Each of these applications of IPUMS International data resulted in policy recommendations, informed by additional data, additional policy research, and pilot projects.

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By Lara Cleveland and Jane Lee

IPUMS International has released new data! Eighteen new census samples have been added to the collection, including data from Côte d’Ivoire, which is new to IPUMS International. Newly released census samples include Cambodia (2019), Côte d’Ivoire (1988, 1998), Denmark (1845, 1880, 1885), Laos (1995, 2015), Mexico (2020), Peru (2017), Puerto Rico (2015, 2020), Switzerland (2011), United Kingdom (1961, 1971), United States (2015, 2020) and Vietnam (2019). As always, we gratefully acknowledge the national statistical offices of all the countries partnering with IPUMS International to make data available for research.

New geography variables are also now available with harmonized migration variables at the second-administrative level; the codes for the newly released migration variables match existing IPUMS International geography codes and labels. As an example, the geographic units in the migration variable for Mexico at the municipo level (place of residence 5 years ago, MIG2_5_MX) are reconciled to the boundaries for place of current residence (GEO2_MX).

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