LeBeau: Analyzing the American Community Survey for Rural Research

In A Guide to the American Community Survey (ACS) for the Rural Researcher: Unpacking the Conceptual and Technical Aspects of Using Secondary Data for Rural Research, author Kristie LeBeau (Developmental Sociology, Cornell) identifies and demonstrates how scholars can best use the American Community Survey (ACS) to address rural research questions.

The ACS is operated by the Federal Census Bureau, which collects data every month and year, including on rural populations and small towns. While the ACS is a commonly used and widely available source of community-level data, results for small rural communities often contain a high level of statistical error because it relies on samples to produce population-wide estimates.

With the ACS’s limitations in mind, LeBeau offers an example of how ACS data can best be used by rural researchers by conducting a case study of the relationship between school presence and community income level in the state of Indiana. The article offers a general overview of the methodology and considers how methodological obstacles LeBeau encountered might be overcome. For example, as the margin of error is more prevalent when the community population sampled is smaller, LeBeau recommends future researchers follow these guidelines: (1) report the margin of error with descriptive statistics, (2) explore the variation in data quality, (3) reduce uncertainty by combining estimates, and (4) run the model with and without high margin of error estimates.

LeBeau concludes that with care and transparency, rural researchers can draw upon ACS data as a useful resource that can offer avenues for further exploration into why certain patterns and trends emerge in their findings. Ultimately, the ACS can act as an important tool in efforts to develop more nuanced, community-aware policies that benefit rural communities.