Weights Whats delivered with the original data and
Weights Whats delivered with the original data and what to do about weighting linked data CPS Weights There are several Choice of which weight to use depends on which data you are using With one exception, all weights provided by CPS are cross-sectional weights Weights IPUMS
name WTFINL COMPWT EARNWT PANLWT Original name PWSSWGT Purpose Use for most analyses of basic monthly data
PWCMPWGT Use to replicate published BLS labor force estimates PWORWGT Use for outgoing rotation group analyses PWLGWWT Use for gross flows analysis Supplement Weights Many supplements have a weight that you should use if you are using data from that supplement Noted on sample notes pages Not every supplement universe is All Persons and there is supplement nonresponse
IPUMS supplement weight naming convention [SUPP STEM]SUPPWT (e.g., VOSUPPWT for voting) Exception: ASECWT Weights for Linked Data PANLWT is the closest Used for gross flows analysis of adjacent months of data Weight on month X applies to flows between month X-1 and month X Reference: Estimating gross flows consistent with stocks in the CPS by Harley J. Frazis, Edwin L. Robison, Thomas D. Evans and Martha A. Duff (Monthly Labor Review, September 2005, pp. 3-9.) IPUMS CPS has constructed a set of test weights for use with
linked data NOTE: these are BETA Why Care about Weights? Panel attrition and sample representativeness Panel attrition is more severe as more time passes between observations January - February 2009 (month to month) 96% retention; 95% match on AGE, SEX, RACE March 2009 - March 2010 (one year apart) 79% retention; 75% match on AGE, SEX, RACE All 8 months for cohort beginning in January 2009
68% retention; 65% match on AGE, SEX, RACE Options We Considered Doing nothing Normalizing the weights Generating regression-based adjustment factors predicted probability of being observed in following month(s) and multiple T1 weight by 1/predicted probability Iterative Proportional Fitting Construction of IPUMS Weights Iterative Proportional Fitting (IPF) or Raking in Python (validate in Stata)
Builds on what CPS does Anchored to the month for which they are available and (currently) for forward linkages Idea is for subset of individuals who actually link to be representative of the subset of who should link Eligible Subset MIS (January) 1 2 3 4 5
6 7 8 Eligible Subset MIS (February) 2 3 4 OUT 6 7 8
OUT Construction of IPUMS Weights Sum of WTFINL for eligible subset Create cross-categories of: AGE, SEX, RACE AGE, SEX, HISPAN AGE, SEX, STATE Essentially sum of WTFINL at each category of every
intersection Rake WTFINL for the eligible subset who actually link, for example, to the next month IPUMS Weights for Linked Data Not comprehensive of all linking possibilities Based on types of linkages that we think people might use Based on forward linking Currently available from 1989 to present IPUMS Weights for Linked Data IPUMS name
Purpose LNKFW1MWT Use for one month forward linkages LNKFW1YWT Use for one year forward linkages LNKFW8WT Use for a full 8 observation panel linked forward
LNKFWMIS14WT Use for full MIS 1-4 observations linked forward LNKFWMIS45WT Use for MIS 4 linked forward to MIS 5 LNKFWMIS58WT Use for full MIS 5-8 observations linked forward Some Caveats
Idea is for subset of individuals who actually link to be representative of the subset of who should link Actual linkages = mechanical linkages Current IPUMS panel weights are For forward in time linkages Created based on adjustments to WTFINL, not supplement weights So What to do about Weights? Do something IPUMS recommends using weights for analysis of CPS data Lots of sensitivity analyses
Help us test our new weights for linked data and give us feedback! We are planning to conduct analyses with original and new weights to better understand the extent to which weight adjustment methods (or not) matter for estimates Creating Weights for Linked Data Stata ipfraking program written by Stanislav Kolenikov Documented in https:// www.stata-journal.com/sjpdf.html?articlenum=st0 323
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