PANLWT for labor market gross flow caclulation by age?

I think you will find the CPS Technical Paper 77 very useful in answering your questions.

PANLWT is a composite weight, and is created by raking, not with single ages, but with age groups. Sample person weights are raked to force their sums to equal the control totals. The control totals are groups defined by age, sex, race, and ethnicity. You can see the exact groups used on page 74-75 of the linked document. When it comes to comparing estimates obtained using PANLWT and WTFINL, I want to note that PANLWT is created to add up to decennial census estimates of the employed, unemployed, and NILF population estimates, while WTFINL is created to add up to total population estimates. Another important difference between the two is that, according to CPS Technical Paper 66, “composite-age detail [used to create PANLWT] is coarser than the second-stage age detail [used to create WTFINL]. For example, the composite procedure controls for White alone, male, ages 60−64; the second stage has more age detail (60−62 and 63−64). Summations of final (composite) weights for all White alone males by age will not match the corresponding second-stage population control for either the 60−62 or the 63−64 age group. However, the summed final weights for White alone, males, ages 60−64 will match the sum of the two second-stage population controls.” So, it is possible to estimate gross flows using single age groups, but you will see discrepancies between estimates that use PANLWT and those that use WTFINL because of the differences in how the two weights are constructed. Also, because neither weight is constructed using single ages, your estimates will not have the level of accuracy that they would if you were able to use a weight constructed using single ages.

To estimate gross flows, it is recommended that you use PANLWT rather than WTFINL, since only PANLWT accounts for linking across panels.

It seems possible to try to recreate PANLWT yourself using a raking method that uses single age groups as your control population groups. I would recommend consulting the literature in your field to determine if others have done something similar as a starting point, or revisiting this discussion you had with Matt a couple years ago.

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