Linking ASEC short-panels to ATUS

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Hi Ivan & IPUMS Team,

Thanks so much for your thorough response! I’ve given more thought on how to identify individuals moving into households, but I’m still unclear on the best approach – how do I know, or at least approximate, who’s a new entrant to the household?

Currently, I’m using the Basic Monthly CPS (2021-2023) to observe household compositional changes over time. I’ve been using the first observed year-month in my extract (regardless of MISH) to flag potential move-ins by comparing each person’s first observed date (pers_first_date ) to their household’s first observed date (hh_first_date ).

Based on the following, I flag the individual as a potential mover-in with their parents:

  1. pers_first_date > hh_first_date
  2. MOMLOC or POPLOC is non-zero or non-missing (coreside_flag==1)
  3. AGE>=25 (to avoid college kids, since my target sample are adult kids)

However, I’ve noticed:

  • In each HH, PERNUM == 1 will never have pers_first_date > hh_first_date since hh_first_date is based on the first person’s survey info (usually PERNUM == 1).
  • Since PERNUM == 1 is typically the household head, I’ve assumed an adult child moving in with a parent typically wouldn’t assume headship immediately, so this might be a minimal source of bias, but I plan to check this systematically.

Alternatively, I have also considered:

  • Identifying movers-in by simply restricting each individual to MISH 2+, but because some people only appear in MISH 5-8 in my extract (their MISH 1-4 occurred before my 2021 start date), but they weren’t necessarily move-ins. I got this idea from an IPUMS Forum post: “I would expect anyone who joins (or replaces) a household in MISH 2 or later to have moved in the past year.”
  • Would checking the first 6 digits of CPSID vs CPSIDP, as suggested in this IPUMS Forum post, help identify movers-in?
  • Checking for changes in METAREA or the most granular geography as a proxy for moves, but this won’t work because the CPS surveys residences and doesn’t follow households/individuals as they move.

Long story short, initially, I chose the BMS for its 16-month panel with monthly detail, but now I see that migration variables (MIGRATE1, WHYMOVE) come from the ASEC. I could merge these into the BMS, but that limits me to the ASEC subset, and only a certain proportion of BMS respondents have matched ASEC data.

Given these tradeoffs, is it better to continue using the BMS to observe household compositional changes for detecting movers-in, or is manually linking cross-sectional ASEC files to utilize migration variables a cleaner approach for identifying movers-in in this context?

Apologies for the long-winded reply and thanks in advance for any help!