Microdata Adjustment by the Minimum Information Loss Principle
AbstractMicrodata 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.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 7231.
Date of creation: Jul 1994
Date of revision:
Microdata Adjustment; Microanalyses; Microsimulation; Minimum Information Loss; Modified Newton- Raphson Algorithm; PC program package ADJUST;
Other versions of this item:
- Joachim Merz, 1994. "Microdata Adjustment by the Minimum Information Loss Principle," FFB-Discussionpaper 10, Research Institute on Professions (Forschungsinstitut Freie Berufe (FFB)), LEUPHANA University Lüneburg.
- C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
- C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Merz, Joachim, 1993.
"Microsimulation as an Instrument to Evaluate Economic and Social Programmes,"
7236, University Library of Munich, Germany.
- Joachim Merz, 1993. "Microsimulation as an Instrument to Evaluate Economic and Social Programmes," FFB-Discussionpaper 05, Research Institute on Professions (Forschungsinstitut Freie Berufe (FFB)), LEUPHANA University Lüneburg.
- Joachim Merz, 1994.
"Microsimulation - A Survey of Methods and Applications for Analyzing Economic and Social Policy,"
09, Research Institute on Professions (Forschungsinstitut Freie Berufe (FFB)), LEUPHANA University Lüneburg.
- Merz, Joachim, 1994. "Microsimulation - A Survey of Methods and Applications for Analyzing Economic and Social Policy," MPRA Paper 7232, University Library of Munich, Germany.
- Merz, Joachim & Wolff, Klaus G, 1993. "The Shadow Economy: Illicit Work and Household Production: A Microanalysis of West Germany," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 39(2), pages 177-94, June.
- Finke, Renate & Theil, Henri, 1984. "An extended version of minimum information estimation of allocation models," Economics Letters, Elsevier, vol. 15(3-4), pages 229-233.
- Theil, Henri & Finke, Renate & Flood, Lennart R., 1984. "Minimum information estimation of allocation models," Economics Letters, Elsevier, vol. 15(3-4), pages 251-256.
- Merz, Joachim, 1991. "Microsimulation -- A survey of principles, developments and applications," International Journal of Forecasting, Elsevier, vol. 7(1), pages 77-104, May.
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