# Re: st: Microdata Adjustment through re-weighting

 From Austin Nichols To statalist@hsphsun2.harvard.edu Subject Re: st: Microdata Adjustment through re-weighting Date Fri, 15 May 2009 16:26:09 -0400

```Andreas Peichl <peichl@iza.org> :
-findit minimum information loss- reports no hits as does -findit merz-.
You can certainly use Mata to solve a nonlinear system of equations g(x)=0
via Newton Raphson or by minimizing g(x)^2 but see
http://www.stata.com/statalist/archive/2009-01/msg01140.html

On Fri, May 15, 2009 at 1:52 PM, Andreas Peichl <peichl@iza.org> wrote:
> Dear statalister,
>
> I'm interested in re-weighting a microdata sample to fit aggregate control
> data based on the Minimum Information Loss (MIL) principle (see Merz 1994).
> Based on information theory this principle satisfies the desired positivity
> constraint on the weighting factors to be computed. For the consistent
> solution which simultaneously adjusts hierarchical microdata (e.g. household
> and personal information), a fast numerical solution by a specific modified
> Newton-Raphson (MN) procedure with a global exponential approximation is
> proposed by Merz (1994).
> This procedure involes numerically solving of a set of non-linear equations.
>
> I'm aware of
> http://www.stata.com/support/faqs/lang/nl.html.
> I was wondering if it were possible to solve a set of non-linear equations
> with Mata (So far, I have't used Mata but I'd like to invest the time to
> learn it if it helps me solving this problem)? If yes, any hints on how to
> tackle this problem are highly appreciated.
> Does somebody know any other programs for Stata/Mata that allow reweighting
> of microdata?
>
Merz, Joachim (1994): Microdata Adjustment by the Minimum Information Loss
Principle. Unpublished. http://mpra.ub.uni-muenchen.de/7231/
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```