Preprint

Multiple imputation in a complex household survey - the German Panel on Household Finances (PHF): challenges and solutions

In this paper, we present a case study of the imputation in a complex household survey - the first wave of the German Panel on Household Finances (PHF). A household wealth survey has to be built on a questionnaire with rather complex logical structure mainly because the probes of many wealth items have to be proceeded on both intensive and extensive margins. Hence the number of potential predictors for each imputation model grows and more non-compliance can confront standard modelling due to, e.g., irregular missing patterns, interdependent logical constraints, data anomalies etc. Our model selection procedure borrows the techniques for the out-of-sample prediction to handle the overfitting often associated with the introduction of a large number of predictors. We also take the measures to produce ex ante evaluation for modelling which can be more efficient than the common diagnosis done after imputation in practice. Solutions for the difficulties in the real data and questionnaire structures are also presented. On the other hand, we incorporate the rich flagging information in developing various measures of item-nonresponse to access this complication from logical structure. We find that information loss due to the contagion of item-nonresponse between variables is not serious in our imputed data.

Sprache
Englisch

Klassifikation
Wirtschaft
Statistical Simulation Methods: General
Model Evaluation, Validation, and Selection
Classification Discontinued 2008. See C83.
Thema
Multiple imputation
Model selection
Panel on household finance
item-nonresponse evaluation
Household account
Scientific modelling

Ereignis
Geistige Schöpfung
(wer)
Eisele, Martin
Zhu, Junyi
Ereignis
Veröffentlichung
(wer)
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften, Leibniz-Informationszentrum Wirtschaft
(wo)
Kiel und Hamburg
(wann)
2013-12

Handle
Letzte Aktualisierung
10.03.2025, 11:45 MEZ

Datenpartner

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Objekttyp

  • Preprint

Beteiligte

  • Eisele, Martin
  • Zhu, Junyi
  • ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften, Leibniz-Informationszentrum Wirtschaft

Entstanden

  • 2013-12

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