The COVID-19 pandemic is hitting rural and tribal communities hard. Although media and stakeholders share important stories about these hardships, we lack high-quality, systematic data to tell us what the pandemic’s lasting effects will be on rural businesses, industries, and workers.
Our recent research partnership with the Housing Assistance Council and the Aspen Institute’s Community Strategies Group uncovered how inadequate existing data sources are for shaping economic development and investment in rural communities. We scanned more than 20 data sources on rural prosperity and spoke with a range of rural researchers and practitioners. Here is what we learned about how rural data fall short:
- Defining “rural” as “not urban” perpetuates perceptions of rural decline. As rural counties near urban centers grow in population and wealth, they frequently are absorbed into cities’ metropolitan or micropolitan statistical areas, even when much of the counties’ lands and economies remain rural. This systematically excludes many of the most prosperous rural areas from national measures of rural economic health. Meanwhile, county-level data can hide unique assets of individual rural communities within them.
- Common datasets have well-known issues, but because there’s a lack of alternatives, they are still used for making decisions and conducting research. For example, the US Census Bureau’s annual American Community Survey includes small sample sizes in sparsely populated areas, which produces high margins of error and makes measures for individual communities unreliable. Yet it is relied upon to set federal program eligibility and analyze rural needs and strengths.
- Rural data collection and reporting is difficult, contributing to accuracy issues. Small communities are known to have lower response rates to national surveys, in part caused by internet access challenges. For tribal areas (PDF), challenges compound. Privacy concerns can also keep public- and private-sector data owners from releasing useful data, particularly in geographies smaller than counties.
How can we improve rural data?
Accessing better data on rural communities is necessary to inform policymakers and ensure rural communities are not left behind after the pandemic. These three steps could lead to better rural data and improve rural policy, practice, and research.
- Explore new methods of increasing data usefulness. Data providers can apply new data synthesis and privacy methods to allow the release of more data on rural communities while maintaining privacy.
- Improve data integration. Local and federal government data providers can consolidate administrative data from a variety of programs they administer to create richer datasets on social service utilization, taxation, and local investment levels.
- Seek out alternate data sources. Once privacy and rural coverages are improved, private companies’ datasets can be a helpful source of economic measures, such as real estate and credit card transactions.
We may never know the true impacts of COVID-19 on rural workers and economies, but better data, and better data practices, are essential to ensuring rural people and places are equipped to recover and prosper.
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The Urban Institute podcast, Evidence in Action, inspires changemakers to lead with evidence and act with equity. Co-hosted by Urban President Sarah Rosen Wartell and Executive Vice President Kimberlyn Leary, every episode features in-depth discussions with experts and leaders on topics ranging from how to advance equity, to designing innovative solutions that achieve community impact, to what it means to practice evidence-based leadership.