© John M. Abowd 2005, all rights reserved Multiple Imputation, II John M. Abowd March 2005.

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Presentation transcript:

© John M. Abowd 2005, all rights reserved Multiple Imputation, II John M. Abowd March 2005

© John M. Abowd 2005, all rights reserved Outline Computational formulas for MI data Examples of building Multiply-imputed data files

© John M. Abowd 2005, all rights reserved Computational Formulas Assume that you want to estimate something as a function of the data Q(Y) Formulas account for missing data contribution to variance

© John M. Abowd 2005, all rights reserved Examples Survey of consumer finances Quarterly workforce indicators

© John M. Abowd 2005, all rights reserved Survey of Consumer Finances Codebook description of missing data proceduresCodebook description of missing data procedures

© John M. Abowd 2005, all rights reserved How are the QWIs Built? Raw input files: –UI wage records –ES-202 EQUI report –Census Numident –Census Place of Residence –LEHD geo-coding system Processed data files: –Individual characteristics –Employer characteristics –Employment history with earnings

© John M. Abowd 2005, all rights reserved Flow Chart

© John M. Abowd 2005, all rights reserved Processing the Input Files Each quarter the complete history of every individual, every establishment, and every job is processed through the production system Missing data on the individual and employment history records are multiply imputed Missing data on the employer characteristics are singly-imputed (explanation to follow)

© John M. Abowd 2005, all rights reserved Garden Variety Problems Missing demographic data on the individual file (birth date, sex, education, place of residence) –Multiple imputations using information from the individual, establishment, and employment history files –Model estimation component updated every quarter

© John M. Abowd 2005, all rights reserved The Mother of all Missing Data Problems The employment history records only code employer to the UI account level Establishment characteristics (industry, geo-codes) are missing for multi-unit establishments The establishment (within UI account) is multiply imputed using a dynamic multi-stage probability model Estimation of the posterior predictive distribution depends on the existence of a state with establishments coded on the UI wage record (MN)

© John M. Abowd 2005, all rights reserved Can It Be Done? Every quarter the QWI processes over 500 million employment histories (unique person-employer pair) covering 1990 to 2003 Approximately 30% of these histories require multiple employer imputations So, the system does 1.5 billion full information imputations every quarter The information used for the imputations is current, it includes all of the historical information for the person and every establishment associated with that person’s UI account

© John M. Abowd 2005, all rights reserved Does It Work? Full assessment using the state that codes both Summary slide follows

© John M. Abowd 2005, all rights reserved