Reweighting ACS PUMS Data to fit two external control totals

Hi everyone!

We are using acs pums microdata to estimate the number of potential Temporary Protected Status (TPS) holders and their tax contributions. Since ACS does not directly identify TPS holders, we rely on reweighting methods using CRS (Congressional Research Service) reports, which provide TPS data by state OR by birthplace, but not both. However, the problem is that

  • If we reweight ACS by birthplace, we match CRS birthplace totals, but our state-level distributions are off.
  • If we reweight by state, we match CRS state totals, but birthplace distributions are distorted.
  • We are looking for a method to balance accuracy at both levels in Stata...

Does anyone know of a reweighting approach or some kind of constrained optimization or post-stratification method to force totals to match both levels as closely as possible?

Parents
  • If you want to use R (which is free) the mipfp package does this for a set of multidimensional marginal tables.  If you have a lot of variables or marginal tables,  I have an R program (function) with the same arguments as the mipfp package that calls a C routine to speed things up.  It also uses less memory than the R mipfp package.

    Dave Dorer

    dorerfoundation.org/.../

Reply
  • If you want to use R (which is free) the mipfp package does this for a set of multidimensional marginal tables.  If you have a lot of variables or marginal tables,  I have an R program (function) with the same arguments as the mipfp package that calls a C routine to speed things up.  It also uses less memory than the R mipfp package.

    Dave Dorer

    dorerfoundation.org/.../

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