Generalised partially linear regression with misclassified data and an application to labour market transitions


Dlugosz, Stephan ; Mammen, Enno ; Wilke, Ralf A.


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URL: https://ub-madoc.bib.uni-mannheim.de/39488
URN: urn:nbn:de:bsz:180-madoc-394880
Document Type: Working paper
Year of publication: 2015
The title of a journal, publication series: ZEW Discussion Papers
Volume: 15-043
Place of publication: Mannheim
Publication language: English
Institution: Sonstige Einrichtungen > ZEW - Leibniz-Zentrum für Europäische Wirtschaftsforschung
MADOC publication series: Veröffentlichungen des ZEW (Leibniz-Zentrum für Europäische Wirtschaftsforschung) > ZEW Discussion Papers
Subject: 330 Economics
Keywords (English): Semiparametric regression , measurement error , side information
Abstract: We consider the semiparametric generalised linear regression model which has mainstream empirical models such as the (partially) linear mean regression, logistic and multinomial regression as special cases. As an extension to related literature we allow a misclassified covariate to be interacted with a nonparametric function of a continuous covariate. This model is tailormade to address known data quality issues of administrative labour market data. Using a sample of 20m observations from Germany we estimate the determinants of labour market transitions and illustrate the role of considerable misclassification in the educational status on estimated transition probabilities and marginal effects.

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Dlugosz, Stephan ; Mammen, Enno ; Wilke, Ralf A. (2015) Generalised partially linear regression with misclassified data and an application to labour market transitions. Open Access ZEW Discussion Papers Mannheim 15-043 [Working paper]
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