Description: Reducing Uncertainty – Reducing the Margin of Error in the American Community Survey
data (5130) maps (2027) acs (266) census (186) margin of error (2)
The American Community Survey (ACS) is the largest survey of US households (3.5 million homes contacted each year) and is the principal source for neighborhood scale information about the US population. The ACS is used to allocate billions in federal spending and is a critical input to social scientific research in the US. However, estimates from the ACS can be highly unreliable. For example, in over 72% of census tracts, the estimated number of children under 5 in poverty has a margin of error greater than
Our project presents a way to reduce the margins of error in survey data via the creation of new geographies, a process called regionalization. Technical details of this paper and example implementations are described in this PLOSOne Paper . This website presents the data from 388 metropolitan statistical areas, before and after the regionalization process, in order to explain, demonstrate, and circulate our results and the data .
Each ACS estimate has a corresponding margin of error (MOE). The MOE measures how much the estimate might vary relative to the population value, given a certain confidence level. The ACS uses a confidence level of 90%. For example, if the estimate of median household income for a particular census tract is $50,000 with an MOE of $10,000, then we are 90% confident that the actual median household income for that tract is between $40,000 and $60,000. If the MOE was $40,000, than that range would balloon to $1