A Random Invitation: The American Community Survey

By Karen Sternheimer

Earlier this week I opened my mail to find an invitation--not to a party but to be a participant in the American Community Survey (ACS). As a sociologist, this was exciting since I have used ACS data in my research and teaching for many years. I will now get to be a part of the process from the inside.

The ACS is a survey conducted by the U.S. Census Bureau each year to learn more about the American population between the census collection, which takes place every ten years. Not only does the survey provide data on population changes, it also provides us with data annually on marital status, housing, education, and income.

While by law the census studies the entire population—or at least attempts to include the entire population—the ACS is a smaller sample of approximately 3.5 million Americans, randomly selected by home address. According to the Census’s population clock site, the U.S. population is just over 314 million, making the ACS survey a sample of just over 1 percent of the overall population.

 

 This might sound miniscule, but using random sampling methods (where everyone in a population theoretically has the same chance at being selected to participate) even a small sample can give us a great deal of useful information. Social scientists who analyze the data also use weighting techniques to match the sample to some of the demographic characteristics of the population to ensure that the sample best reflects the country’s racial/ethnic composition.

Of course, people who have no home address get left out of a survey like this, so there is a built in selection bias preventing us from learning more about individuals who are homeless. And those that are included may choose not to participate, although technically the law requires those selected to participate. People who are very busy or those who do not understand the instructions may simply fail to complete the survey. If one group or type of respondent is more prone to skip the survey, this too could skew the results.

There is a big difference between a less-than-perfect sample and a useless sample. Just because the ACS has limitations it does not mean it lacks value.

Earlier this year, the House of Representatives voted to eliminate the ACS, arguing that it costs too much money (an estimated $240 million per year out of a budget of about $3.6 trillion) and that the questions about race, age, and income are intrusive. It has not passed in the Senate so far, and a petition has been drafted to save the ACS.

Without the ACS, we would lose valuable updates about poverty, about who has health insurance, and population and transportation shifts that contribute to where the federal government spends money on infrastructure like roads and bridges. Economists expressed concern that businesses would lose valuable customer data as well. (The ACS does not provide individual names, addresses or responses. Disclosure of any individual’s personal information could lead to five years in prison and/or a $250,000 fine).

One of the nice things about federally collected data is that we all have access to the results, which tell us quite a bit about large scale patterns (and again, no personal information). I encourage all sociology students—and voters—to actually go to the ACS website and see what kind of data are created from the survey before congress eliminates it altogether.

Why wouldn’t we want to know how many people live in poverty or lack health care coverage, or be able to track migration patterns? I’ll be filling out my survey when it arrives.

Comments

[Keith Appleby]

Love the ACS. Incredibly rich data source.

[Curtis Jones]

Karen, excellent post. I hope you and other social scientists and the general public fight hard to save this survey. Unfortunately we in Canada have lost that battle and we are going to have much worse data as a result.

http://www.thestar.com/news/canada/census/article/830206--tories-eliminate-compulsory-long-census-form

[home energy programs]

I think they are not seeing the big picture. they do not see that the information from research and surveys are tools for improvement. Improvement starts with knowledge without these surveys then how can we know what areas need attention?