Generalised Partially Linear Regression with Misclassified Data and an Application to Labour Market Transitions

Stephan Dlugosz, Enno Mammen, Ralf Wilke

Research output: Working paperResearch

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.
Original languageEnglish
Place of PublicationMannheim
PublisherZEW
Number of pages27
Publication statusPublished - 2015
SeriesZEW Discussion Papers
Number15-043

Keywords

  • Semiparametric regression
  • Measurement error
  • Side information

Cite this

Dlugosz, Stephan ; Mammen, Enno ; Wilke, Ralf. / Generalised Partially Linear Regression with Misclassified Data and an Application to Labour Market Transitions. Mannheim : ZEW, 2015. (ZEW Discussion Papers; No. 15-043).
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Generalised Partially Linear Regression with Misclassified Data and an Application to Labour Market Transitions. / Dlugosz, Stephan; Mammen, Enno; Wilke, Ralf.

Mannheim : ZEW, 2015.

Research output: Working paperResearch

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KW - Side information

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