New Data for Understanding Rural America: The American Community Survey

by Kathy Miller, RUPRI Program Director

As most Americans know, 2010 was a “Census Year.” The requirement to count the population every decade is outlined in the U.S. Constitution, which states that members in the House of Representatives shall be apportioned based on the population of their states. The decennial Census has undergone significant changes since the first Census was taken door-to-door by U.S Marshals in 1790.

One of the most significant changes was in 1940, when detailed questions regarding social and economic conditions were asked of a sample of the population. This detailed questionnaire became known as the “long form,” and over time became the prominent source of detailed data such as educational attainment, poverty and income, occupations and employment, as well as housing conditions. This became the key source of data for rural conditions and trends, since so few other data sources covered rural geographies.

While the long form did indeed provide researchers and policymakers with significant data about conditions and trends at very small geographic levels, the data becomes less and less useful and representative as the decade progresses. This is problematic particularly for the allocation of federal funding – in 2009, did we want to be allocating federal funding based on data that was nearly a decade old?

Responding to this challenge, the Census Bureau designed a new data collection system, The American Community Survey, which was fully implemented in 2005 (for detailed information regarding the ACS, visit https://www.census.gov/acs/). The 2010 Decennial Census, recently taken, only included the constitutionally required short form, which counted the population as of April 1, 2010. No long form survey was conducted. The American Community Survey, rather than a one-time sample survey, is an ongoing survey of households taken throughout every year of the decade. Data is continuously collected, with households surveyed every month throughout the year. Then, data is averaged over time to create a large enough sample size for estimates at various geographic levels. The result is a dataset that is more frequently released, with more up-to-date information about social and economic conditions.

While this is indeed a goldmine for users of data, particularly for small-area geographies for which there are few alternatives, it is important to understand some caveats when seeking to analyze data for rural areas.

For smaller population areas, data is collected over a number of years in order to obtain a large enough sample to provide reliable estimates. For areas with a population of 65,000 or more, data can be released on an annual basis. For areas with a population of 20,000 or more, data is collected and averaged over three years. Finally, for areas with populations under 20,000, data is collected and averaged over five years. A map below shows how this affects the release of county data through the American Community Survey. For much of rural America, data is available only at the five-year average.

Map, Population EstimateThe reality of the American Community Survey is that there is more timely data for areas with larger populations. Rural data is averaged over time. This is a particular problem in big counties (primarily in the West), in which the large geographic size also creates an averaging over vast geographic space. Consider the recent economic downturn. For data that is averaged from 2005-2009 (as most data for rural counties is), this period contained some really good and really bad years – it will be difficult to understand the timing and severity of the recession with these statistics. For example, large population counties will see annual estimates reflecting the impacts of the recession, such as poverty rates, income levels, and usage of public assistance benefits such as food stamps. More rural counties, on the other hand, only see these data averaged over a five-year period. This may result in rural areas appearing to fare better or worse than in reality. However, these realities of the American Community Survey should not overshadow the potential for using its data for a deeper understanding of rural America. In December 2010, the Census Bureau released the first five-year estimates from the American Community Survey. For the 40 percent of counties with populations under 20,000, this represents the very first look at conditions since the 2000 Decennial Census was released.

RUPRI and the Rural Human Services Panel has conducted a study, utilizing the American Community Survey data, on human services indicators and how they compare in rural and urban areas. This analysis, The Geography of Need (forthcoming from RUPRI),documents how human services needs differ significantly, both in the degree of need as well as the types of needs, in metropolitan and nonmetropolitan areas, as well as across different geographic areas of the country. A future issue of the Rural Monitor will offer highlights of this study.


Types of Data Collected in the American Community Survey:
  • Age, Sex, Race, Ethnicity
  • Family and Relationships
  • Income and Benefits
  • Health Insurance
  • Education
  • Veteran Status
  • Disabilities
  • Where you work and how you get there
  • Where you live and how much you pay for some essentials

Kathleen Miller joined the Rural Policy Research Institute in January 2000 as Program Director. Ms. Miller is responsible for assisting the coordination of the RUPRI program of work, which encompasses researchers and practitioners across the country analyzing the rural impacts of public policies and programs in health care, human services, entrepreneurship, regional and community development. Ms. Miller’s research interests include understanding how the definitions of rural geographies impact policy outcomes, and she has published several RUPRI policy briefs on this topic. Ms. Miller received a Master of Science degree in Agricultural Economics from Penn State University, where she also received her Bachelor of Science Degree in Agricultural Economics and Rural Sociology.

Opinions expressed in this column are those of the author and do not necessarily reflect the views of the Rural Health Information Hub.


Back to: Spring 2011 Issue