Can a net migration rateby age be calculated for a PUMA county using your variables? Thank you.

Hi! Can you provide additional guidance on how to use the combination of migpuma1, migplac1, and migrate1d in the Analyze Online tool to get net migration (into city/county of San francisco and out of it)? Then also disaggregate by age categories?

  1. In-migration: Would the following filter to migration into SF using filters for (1) migrate1d for movers who change pumas, states, or came from abroad, and (2) city for now live in SF?
    Row: year (2012-2020)
    Column: blank
    Control: blank or city(6290)
    Filter: migrate1d(24,30,40), city (6290)

  2. Would age categories go in row, column, or control (I’ve tried to create age categories, but they don’t group, each age is row or column, like this: age(1-15, 16-24, 25-39, 40-54, 55-64, 65-99)?

  3. Out: Would the following filter to moving out of SF by filtering (1) migrate1d movers, and then (2) migplac1 for living in CA one year ago and migpuma1 for living in SF county one year ago?
    Row: year(2012-2020)
    Column: blank
    Control: blank
    Filter: migrate1d(24, 30, 40), migplac1(06), migpuma(7500)

The above two produced tables, but past posts mention using the migplac1 and migpuma1 together by creating a new variable in Analyze Online. Is that necessary and is it the recode or create new expression option? This post was similar and this post and this post also had some hints.