Staff Voices: Small Towns and the American Community Survey

Kelly Asche is the Program Coordinator at CST
I’ve been following the debate about U.S. Census Bureau’s transition of the long form census to the American Community Survey and its impacts on rural communities over the last few years. The debate on whether the estimates produced by the survey is too unreliable for small towns delves into the complicated details of the methodology behind each of these surveys, navigating the various government agencies and philanthropics that rely on this information to determine grant and loan eligibility, and how a community depends on these funds for important economic and community development projects. I believe a real-life story can cut through these complexities. So, here is a brief story on a small town in West Central Minnesota.


We love to use acronyms in rural community development. So, before we get started, lets define a few.
 
  • MHI – Median Household Income: Take an area. Measure each household’s income within that area. Rank all the incomes you collected from lowest to highest. And then, pick the very middle income. That is your median household income.
  • SNMHI – State, non-metropolitan median household income: this is the median household income of a state excluding all households within a census designated urban area.
  • ACS – American Community Survey.
  • USDA – United States Department of Agriculture.


Over the past year, this city has been working on funding opportunities to assist in installing a municipal sewer system to alleviate environmental and home value issues arising within the community. With a population of ~100 (2010 census) and the high cost of installing a basic system, it is not possible for the community to pay for it alone. The community has been working with a great organization, Midwest Assistance Program (MAP), to navigate the various resources available to communities.They are currently seeking funds from the USDA Rural Development, however, funds are allocated based on “need”. Essentially, communities that have the poorest households get higher priority. The data used to assess a community’s wealth is the median household income supplied by the American Community Survey.


Since the year 2000, the U.S. Census Bureau has transitioned away from the long-form decennial census to the American Community Survey.  One of the main benefits of the ACS is that it surveys households every year, supplying updated information every year instead of every ten years. However, the methodology of the ACS are problematic in rural areas. For an excellent overview of the methodology and these problems, check out the 2012 Rural Minnesota Journal article, “Who Lives in Minnesota?”, written by Ben Winchester.


There are a couple of key points everyone should know when using ACS data.
  1. The estimates produced for areas with less than 20,000 residents are a “rolling average” over a five year period. This is why you see ACS reported in rural areas as; 2005-2007 ACS, 2006-2010 ACS, 2007-2011 ACS, and 2008-2012 ACS.
  2. The estimates come with a margin of error that are, many times, very large in our small communities.


So how does this impact this particular community? Well, in 2000 the median household income was $29,688. This was an accurate representation of the community and was the last MHI with the long form census. The most recent ACS, 2008-2012 5 year, shows the community’s MHI at $54,375. But, that estimate comes with a margin of error; in fact, the margin of error is +/- $21,816. This means that the estimate is likely somewhere between $32,559 and $76,191.



This chart shows the margin of error along with the estimate given for the last four ACS, 5 yr average, surveys and the 2013 State Non-Metropolitan MHI.


The USDA Rural Development compares a community’s MHI with the state, non-metropolitan median household income (SNMHI) to determine the level of priority. There are various guidelines regarding funding. For example, if a community falls below 80% of the SNMHI and have a public health and safety issue/concern, it would qualify for a grant paying up to 75% of the costs. Most of the guidelines give communities access to more dollars and an increasing chance of receiving dollars, the closer or farther below a community is to the SNMHI. The state of Minnesota’s, non-metropolitan MHI is currently $43,036. The margin of error for this community’s MHI is so large that the SNMHI is clearly within that range, making it unclear if it has greater access to funds.


The USDA Rural Development have been great at acknowledging ACS’s limitations and allows communities to hire an outside, objective partner to collect household incomes and determine a more accurate estimate of the MHI. However, the decision to go this route isn’t as easy as it seems. Not only does it cost a community money to hire someone to do this, which can be a lot depending on the size of the community, but the community runs the risk of having their MHI actually be higher, thus reducing their access to funds.


This story is not meant to call-out the Census Bureau or the USDA Rural Development. In fact, much of the data produced by the American Community Survey is accurate and very helpful. The USDA Rural development have been instrumental in assisting and funding projects in many communities.  However, this story does highlight some of the difficulties and complexities associated with community data and the issues our small towns have to face solely related to the size of their population.

Written by Kelly Asche, who coordinates programming development at the Center for Small Towns

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