Analyzing the Quality of 2020 Census Data

Accurate decennial census data are critical to making effective decisions at the national, state, and local levels. The Census Bureau’s population counts affect congressional redistricting, social program funding, school planning, and more.

But the 2020 Census faced a series of challenges that could affect its quality, including the COVID-19 pandemic and related stay-at-home orders, new household dynamics, displacement of college students, and natural disasters. The Census Bureau also delayed its operations and shortened fieldwork during the pandemic, and it implemented a new privacy definition for protecting publicly released data. These factors delayed the release of the 2020 Census data products and have led to increased scrutiny of those data by policymakers and data users, who may question whether the data are fit to use.

To help state and local decisionmakers and data users determine the quality of 2020 Census data, we developed a dashboard that analyzes whether the data look reasonable relative to expectations. We compiled data from other public and administrative sources to create benchmark expectations for population counts at the county level.

We will continue to update the dashboard as the Census Bureau releases new 2020 data products, and we will publish the dashboard’s underlying data. We encourage users to email AnalyzingCensus@Urban.org to let us know how the data in the dashboard align with their expectations and how we could improve the tool.

Through this project, we hope to assist local decisionmakers and data users as they assess whether the 2020 Census data are fit for their use, and we hope to give additional context for determining the best possible statistical data to in turn inform the best possible decisions.

For more information about this project, contact AnalyzingCensus@Urban.org.

New resources through this project

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About

This project was funded by the Tableau Foundation. We are grateful to them and to all our funders, who make it possible for Urban to advance its mission. The views expressed are those of the authors and should not be attributed to the Urban Institute, its trustees, or its funders. Funders do not determine research findings or the insights and recommendations of Urban experts.

Project team

  • Claire Bowen, Lead Data Scientist for Privacy and Data Security at the Urban Institute
  • Amy O’Hara, Research Professor at the Georgetown University Massive Data Institute and Director of the Federal Statistical Research Data Center at the Georgetown University McCourt School of Public Policy
  • Ronald Prevost, Research Professor at the Georgetown University McCourt School of Public Policy
  • Izzy Youngs, Research Specialist at the Georgetown University Massive Data Institute
  • Lahy Amman, Project Manager at the Georgetown University Massive Data Institute
  • Sang Doan, Research Assistant at the Georgetown University Massive Data Institute
  • Gabriel Morrison, Data Science Intern at the Urban Institute