There are 100 counties j. There are many people in each county. People do not move across counties from Jan 1 to Dec 31. No time subscript is needed in this example. It's a long difference.
Y_{i} = 1 if person i got cancer by Dec 31, and 0 otherwise.

X_{j(i)} = Amount of pollutant that spilled into county j (in which person i lives) from Jan 1 to Dec 31
Before reading Abadie et al. (2017), I have been thinking I need to cluster at state because there are state-level health-related policies.

But Abadie et al. (2017) say
"The researcher should assess whether the sampling process is clustered or not, and whether the assignment mechanism is clustered. If the answer to both is no, one should not adjust the standard errors for clustering, irrespective of whether such an adjustment would change the standard errors."
In this example, in what situation would "sampling process" and "assignment mechanism" be considered to be clustered?

Is Abadie et al. (2017) basically saying that clustering at state is too conservative approach?

So in this example, Abadie et al. (2017) recommends clustering at county?