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Microdata adjustment by the minimum information loss principle
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 analysis on explaining factors of successful firms in the German engineering industry. ; Mikrodaten sind von zunehmender Bedeutung für wirtschafts- und sozialpolitische Analysen. Ein besonderes Problem für fast alle praktischen Analysen mit Mikrodaten überhaupt, seien es zu analysierende Mikrodaten als singuläre Querschnitts- oder Längsschnitt-Stichproben oder im Bereich der statischen Mikrosimulation zur Aktualisierung und Fortschreibung der Situation sozioökonomischer Gruppen, ist es, repräsentative Ergebnisse zu erhalten.In dieser Studie ...
Microdata adjustment by the minimum information loss principle
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 analysis on explaining factors of successful firms in the German engineering industry. ; Mikrodaten sind von zunehmender Bedeutung für wirtschafts- und sozialpolitische Analysen. Ein besonderes Problem für fast alle praktischen Analysen mit Mikrodaten überhaupt, seien es zu analysierende Mikrodaten als singuläre Querschnitts- oder Längsschnitt-Stichproben oder im Bereich der statischen Mikrosimulation zur Aktualisierung und Fortschreibung der Situation sozioökonomischer Gruppen, ist es, repräsentative Ergebnisse zu erhalten.In dieser Studie ...
Microdata adjustment by the minimum information loss principle
Merz, Joachim (author)
1994-01-01
Paper
Electronic Resource
English
Theorie , Minimaler Informationsverlust , Mikroanalysen , Microanalyses , Schätztheorie , Hochrechnung von Mikrodaten , Microdata Adjustment , Minimum Information Loss , ddc:330 , C80 , Statische Mikrosimulation , Mikrozensus , C81 , Modifizierter Newton-Raphson Algorithmus , PC program package ADJUST , Modified Newton-Raphson Algorithm , Information , PC-Programmpaket ADJUST , Microsimulation
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