IHGIS Research Example: Fertilizer Use from Agricultural Census Data

By Chris M. Boyd

The IPUMS International Historical Geographic Information System (IHGIS) provides subnational data from agricultural and population and housing censuses from around the world. The agricultural census data cover a wide range of information on agricultural inputs, labor, production, and more, which can be used to explore a variety of research questions. IHGIS data can help understand, for instance, which factors contribute to better crop productivity, including the role of fertilizer use. Researchers have used agricultural census data at the subnational level to analyze the negative relationship between farm size and fertilizer overuse in China1; the relationship between maize yield, farm size and fertilizer and irrigation use in Mexico2; the use of chemical fertilizers in direct market farms in the U.S.3; and the environmental sustainability of using fertilizers, insecticides and pesticides in Pakistan4.

To date, IHGIS has released Agricultural Census tables for ten countries (see https://ihgis.ipums.org/dataset-descriptions), including seven developing countries in Africa and the Pacific Islands. These seven datasets include information about fertilizer use, though each measures it in a different way (see Table 1). Despite the differences, these data can reveal broad patterns in the use of fertilizer by farmers among these countries.

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Conceptualizing Structural Racism with IPUMS Time Use Data

By Solvejg Wastvedt and Yash Singh

A major challenge for researchers studying racism is measuring the consequences of this macro-level phenomenon in people’s everyday lives. For the purposes of this post we define structural racism as a system of racialized advantage and disadvantage underlying and structuring multiple domains of life, including housing, interactions with government, education, the criminal legal system, and more. 5 6 7 8 9 Structural racism does not refer to individual prejudices or discriminatory beliefs. Rather, it is a macro-level phenomenon: a principle upon which structures in our society are built. When researchers study racism as a structural force, its impacts in any one area affect and reinforce impacts in every other area.

The consequences of structural racism for individuals are well-documented; for example, research shows structural racism produces poorer health outcomes for racialized groups. 10 However, research often focuses on a single aspect of structural racism, such as police brutality, and struggles to capture the full impact of this multidimensional phenomenon. Measures used to assess impacts of structural racism typically differ by domain, and while robust research documents these impacts, it can also be difficult to capture the mechanisms through which they occur.

Time — specifically time use — is a type of data that can unite studies of structural racism across domains and offer a glimpse into how this macro-level force acts on individuals.

Time is a form of capital: we only have so much of it, and time spent in one place is not spent elsewhere. For example, an individual living in a segregated neighborhood because of residential discrimination may be required to drive long distances for work or health care. This reduces time available for all other activities, including exercise. The resulting lack of time may lead, in turn, to negative health outcomes. While simply an illustration of one possible pathway linking the macro and micro levels, this example shows how time use data can capture impacts across multiple domains and, ultimately, on daily life.

IPUMS Time Use provides data from the American Time Use Survey (ATUS), a nationally representative U.S. time diary survey. In this post, we highlight measures from the ATUS corresponding to two aspects of structural racism: residential segregation and discrimination in government services. Researchers interested in other aspects can create and select variables from IPUMS ATUS data to match their areas of interest.

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An Age-Based Approach to Disability

By Solvejg Wastvedt and Yash Singh

Disability is dynamic: it evolves over time and interacts with environmental and societal factors. Due to the complex nature of disability, researchers conceptualize and measure disability differently depending on their research question and available data. For instance, an identical condition might evolve differently for a child facing food insecurity compared to one that has stable access to food. Similarly, a physical limitation for a worker in New York City may have a vastly different impact compared to a similar worker in rural Iowa. Disability can be viewed as the relational concept between individuals with physical or mental impairment and the environment.11 12 This complexity makes measuring disability a challenging task. The following post aims to help researchers understand and use disability measurements available in IPUMS data collections.

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Things to Consider when Using the 2020 American Time Use Survey

By Kelsey J. Drotning

Curious about how COVID-19 has affected time in leisure, sleep, work, and family activities in the United States? The 2020 ATUS will provide some clues. Data from the 2020 American Time Use Survey (ATUS) were released by the Bureau of Labor Statistics on July 22, 2021. The data have been harmonized with previous ATUS surveys by the IPUMS team, released on July 30, 2021. The 2020 ATUS provides a window into how daily lives shifted in response to COVID-19 pandemic conditions and the corresponding economic recession via 24-hour time diaries. Potential research topics include, but are not limited to:

• What, where, and with whom people spent their time post-onset compared to pre-onset of the pandemic
• Differences in daily activities by gender, race, ethnicity, nativity, age, parental and marital status, household composition, employment status, education.
• How daily activities, such as work, time with children, school, commuting, socializing and sleep changed as social distancing restrictions were enacted, lifted or maintained across U.S. states

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Visualizing IPUMS Global Health with Storymaps

By Matt Gunther

IPUMS data are a great research resource; they are also widely used by faculty for teaching students about using data to tell stories. This blog post, adapted from the IPUMS PMA Data Analysis Hub blog series, highlights work from students using IPUMS Global Health data.

This semester, students in the Global Health Survey Analysis course at the University of Minnesota used an amazing tool called StoryMaps to develop interactive narratives exploring different topics related to family planning. StoryMaps have been used in both the undergraduate and graduate curriculum throughout the College of Liberal Arts and beyond – we encourage you to check out the full gallery of student projects here!

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Online Analysis Tool Now Exports CSV Output

By Matthew Sobek

IPUMS is pleased to announce a major usability upgrade to our online analysis tool: the ability to download tabular output as a CSV file. No more cleaning up html!

The IPUMS online analysis tool has been a big hit with our users, and we’ve made it available for most of the IPUMS data collections. If you haven’t tried it, you should. We even have a tutorial.

Despite its popularity with users, the SDA (Survey Documentation and Analysis) software that drives the system has always had a significant limitation: it produces tables in html format, which is fine for web display but highly inconvenient for cutting and pasting into documents.

In spring 2020 the SDA folks at the Institute for Scientific Analysis were looking for a new project and thoughtfully asked what change we thought users would most appreciate. We responded immediately “CSV downloads,” and within a few months, they had produced a working version of the software that incorporates the new feature. We have now upgraded all the IPUMS sites that offer online analysis to the new version of SDA.

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IPUMS Announces 2020 Research Award Recipients

IPUMS research awardsIPUMS is excited to announce the winners of its annual IPUMS Research Awards. These awards honor the best-published research and nominated graduate student papers from 2020 that used IPUMS data to advance or deepen our understanding of social and demographic processes.

IPUMS, developed by and housed at the University of Minnesota, is the world’s largest individual-level population database, providing harmonized data on people in the U.S. and around the world to researchers at no cost.

There are six award categories, and each is tied to the following IPUMS projects:

  • IPUMS USA, providing data from the U.S. decennial censuses, the American Community Survey, and IPUMS CPS from 1850 to the present.
  • IPUMS International, providing harmonized data contributed by more than 100 international statistical office partners; it currently includes information on 500 million people in more than 200 censuses from around the world, from 1960 forward.
  • IPUMS Health Surveys, which makes available the U.S. National Health Interview Survey (NHIS) and the Medical Expenditure Panel Survey (MEPS).
  • IPUMS Spatial, covering IPUMS NHGIS and IPUMS Terra. NHGIS includes GIS boundary files from 1790 to the present; Terra provides data on population and the environment from 1960 to the present.
  • IPUMS Global Health: providing harmonized data from the Demographic and Health Surveys and the Performance Monitoring and Accountability surveys, for low and middle-income countries from the 1980s to the present.
  • IPUMS Time Use, providing time diary data from the U.S. and around the world from 1965 to the present.

Over 2,500 publications based on IPUMS data appeared in journals, magazines, and newspapers worldwide last year. From these publications and from nominated graduate student papers, the award committees selected the 2020 honorees.

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