I'm seeking to create a map which overlays 2022 MIGPUMAs onto 2018-2021 and provides weighting for overlapping boundaries. In preparing this, I've noticed that both the total population and number of employed persons in 2022 is lower than previous years. Ideally, my weighting would be the sum of 'PWGTP' for 2022 divided by the sum of 'PWGTP' for all years, but those values are surprising:Calculation for figures below: sum('PWGTP') * 5 for each yearpop_2018 = 330,392,650pop_2019 = 330,778,030pop_2020 = 335,532,750pop_2021 = 335,754,690pop_2022 = 323,029,850
same calculation but with employed persons:
2018: 159,018,4502019: 160,511,7252020: 157,185,1402021: 158,912,1852022: 157,184,160
My gut tells me to use the sum of 'PWGTP' for each year for weighting, since those will be how my variables are weighted, but it feels odd given 2022 certainly had a higher population and labor force than previous years.
Does anyone have advice? My goal is to create a 5-year average, just like the data prescribes. It will be one one map though, and I'm not sure how much to weight my averages for 2022.
Why not use the 2018-2022 PUMS instead of those single-year sources?
I am using the 5-year PUMS, but I'm creating a map. The MIGPUMA/POWPUMA boundaries changed in 2022, so to visualize data requires some sort of map manipulation.
The blue lines are 2022-2031 boundaries. The dashed red lines are 2012-2021
So, I've looked at the values of 'ADJINC' (you could also look at the serial number) to determine year from the 5-year data.