Arbeitspapier

Instrumental variables estimation with partially missing instruments

We examine instrumental variables estimation in situations where the instrument is only observed for a sub-sample, which is fairly common in empirical research. Typically, researchers simply limit the analysis to the sub-sample where the instrument is non-missing. We show that when the instrument is non-randomly missing, standard IV estimators require strong, auxiliary assumptions to be consistent. In many (quasi)natural experiments, the auxiliary assumptions are unlikely to hold. We therefore introduce alternative IV estimators that are robust to non-randomly missing instruments without auxiliary assumptions. A Monte-Carlo study illustrates our results.

Sprache
Englisch

Erschienen in
Series: IZA Discussion Papers ; No. 4689

Klassifikation
Wirtschaft
Multiple or Simultaneous Equation Models: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
Multiple or Simultaneous Equation Models: Truncated and Censored Models; Switching Regression Models
Thema
Instrumental variables
partially missing instruments
sample selection
sub-sample estimation
Schätztheorie
Kausalanalyse
Stichprobenverfahren
Theorie

Ereignis
Geistige Schöpfung
(wer)
Mogstad, Magne
Wiswall, Matthew
Ereignis
Veröffentlichung
(wer)
Institute for the Study of Labor (IZA)
(wo)
Bonn
(wann)
2010

Handle
Letzte Aktualisierung
20.09.2024, 08:22 MESZ

Datenpartner

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Objekttyp

  • Arbeitspapier

Beteiligte

  • Mogstad, Magne
  • Wiswall, Matthew
  • Institute for the Study of Labor (IZA)

Entstanden

  • 2010

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