I am wondering if there is an approximate timeline for releasing time series standardized to 2020, particularly for the urban/rural geography dataset. From my understanding the definition of rurality changed in 2020, and our research team would like to standardize previous decades of data (2000 and 2010) to the 2020 definition. If the updated time series isn’t coming soon, any other tips for best ways to approach this problem?
Forgot to mention, we need this dataset at the US county level.
We expect to release time series standardized to 2020 geography at some point, but we have no timeline for that yet.
You raise an important question about the new urban definition and its effects on urban/rural counts. Our approach to standardization wouldn’t directly provide what you’re looking for. That is, it sounds like you’re looking for county-level counts of 2000 & 2010 urban/rural populations using 2020 urban definitions. To produce that exactly, you’d need to apply the 2020 urban area criteria to 2010 & 2000 data. That’s technically feasible but rather involved, and I don’t know of anyone who’s done it or is planning to do it, unfortunately. We’ll keep this in mind for possible future work.
Our time series “standardized to 2020” (when they become available) wouldn’t achieve this exactly. Instead, we’ll allocate 2000 & 2010 block-level counts to 2020 urban area boundaries, providing estimates of 2000 & 2010 characteristics for 2020 urban areas. (You could achieve this yourself now by using our crosswalks to allocate data from 2010 blocks to 2020 blocks & then summing by 2020 urban area.) Note, though, that this approach allocates some population that would have been rural in 2000 & 2010 to 2020 urban areas (and conversely, it allocates some population that would have been urban in 2000 & 2010 to areas that are now rural).
You could use this style of standardization to measure urban/rural trends across time, but it wouldn’t capture cases where a population remained in place but changed status because the area later became urban / became rural.