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Microdata Adjustment by the Minimum Information Loss Principle

FFB Discussion Paper No. 10

43 Pages Posted: 12 Jun 2009  

Joachim Merz

Research Institute on Professions; Leuphana University of Lueneburg; Institute for the Study of Labor (IZA)

Date Written: July 1994

Abstract

Microdata have become increasingly important for economic and social analyses. One striking problem with almost any practical analysis of microdata, microdata as a singular cross or longitudinal sample or within (static) microsimulation, is to achieve representative results.

In this study a consistent solution of the microdata adjustment problem - that is to achieve representative results by re-weighting microdata to fit aggregate control data - is presented based on the Minimum Information Loss (MIL) principle. 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.

Practical experiences for large microdata sets in a pension reform analysis with e.g. more than 60.000 households and 240 restrictions simultaneously to be achieved within the Sfb 3 microsimulation model show that this MN procedure was able to rather largely reduce the computional expenses by 75%. The available efficient PC-computer program ADJUST is also succesfully applied in a described microsimulation analyses of the recent 1990 German tax reform investigating the impacts on market and non-market labour supply within the formal and informal economy, and in a recent firm microsimulation analysion explaining factors of successful firms in the German engineering industry.

Keywords: Microdata Adjustment, Microanalyses, Microsimulation, Minimum Information Loss, Modified Newton- Raphson Algorithm, PC program package ADJUST

JEL Classification: C80, C81

Suggested Citation

Merz, Joachim, Microdata Adjustment by the Minimum Information Loss Principle (July 1994). FFB Discussion Paper No. 10. Available at SSRN: https://ssrn.com/abstract=1417310

Joachim Merz (Contact Author)

Research Institute on Professions ( email )

L√ľneburg
Germany

Leuphana University of Lueneburg

Scharnhorststrasse 1
L√ľneburg, 21314
Germany

Institute for the Study of Labor (IZA)

P.O. Box 7240
Bonn, D-53072
Germany

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