Consistent estimation and orthogonality

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Scopus citations

Abstract

Observations in a dataset are rarely missing at random. One can control for this non-random selection of the data by introducing fixed effects or other nuisance parameters. This chapter deals with consistent estimation the presence of many nuisance parameters. It derives a new orthogonality concept that gives sufficient conditions for consistent estimation of the parameters of interest. It also shows how this orthogonality concept can be used to derive and compare estimators. The chapter then shows how to use the orthogonality concept to derive estimators for unbalanced panels and incomplete data sets (missing data).

Original languageEnglish (US)
Title of host publicationMissing Data Methods
Subtitle of host publicationCross-Sectional Methods and Applications
EditorsWilliam Greene, David Drukker
Pages155-178
Number of pages24
DOIs
StatePublished - Dec 1 2011
Externally publishedYes

Publication series

NameAdvances in Econometrics
Volume27 A
ISSN (Print)0731-9053

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Keywords

  • Causal inference
  • Information orthogonality
  • Missing data
  • Panel data

ASJC Scopus subject areas

  • Economics and Econometrics

Cite this

Woutersen, T. (2011). Consistent estimation and orthogonality. In W. Greene, & D. Drukker (Eds.), Missing Data Methods: Cross-Sectional Methods and Applications (pp. 155-178). [17004567] (Advances in Econometrics; Vol. 27 A). https://doi.org/10.1108/S0731-9053(2011)000027A009