Artikel
On the interpretation of instrumental variables in the presence of specification errors: A causal comment
- Language
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Englisch
- Bibliographic citation
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Journal: Econometrics ; ISSN: 2225-1146 ; Volume: 5 ; Year: 2017 ; Issue: 3 ; Pages: 1-6 ; Basel: MDPI
- Classification
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Wirtschaft
Methodological Issues: General
Single Equation Models: Single Variables: Instrumental Variables (IV) Estimation
- Subject
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causal inference
instrumental variable
omitted variable
structural model
- Event
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Geistige Schöpfung
- (who)
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Raunig, Burkhard
- Event
-
Veröffentlichung
- (who)
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MDPI
- (where)
-
Basel
- (when)
-
2017
- DOI
-
doi:10.3390/econometrics5030031
- Handle
- Last update
-
10.03.2025, 11:42 AM CET
Data provider
This object is provided by:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Artikel
Associated
- Raunig, Burkhard
- MDPI
Time of origin
- 2017
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Specification testing in nonparametric instrumental quantile regression
Specification Testing in Nonparametric Instrumental Quantile Regression
Causal random forests model using instrumental variable quantile regression
Spotlight on researcher decisions: Infrastructure evaluation, instrumental variables, and specification screening
Spotlight on Researcher Decisions – Infrastructure Evaluation, Instrumental Variables, and Specification Screening
Spotlight on Researcher Decisions – Infrastructure Evaluation, Instrumental Variables, and Specification Screening
Removing specification errors from the usual formulation of binary choice models
The neural encoding of information prediction errors during non-instrumental information seeking
Some comments on specification tests in nonparametric absolutely regular processes
On the interpretation of instrumental variables in the presence of specification errors
On the interpretation of instrumental variables in the presence of specification errors: A Reply
Causal inference with imperfect instrumental variables
Specification testing in nonparametric instrumental quantile regression
Specification Testing in Nonparametric Instrumental Quantile Regression
Causal random forests model using instrumental variable quantile regression
Spotlight on researcher decisions: Infrastructure evaluation, instrumental variables, and specification screening
Spotlight on Researcher Decisions – Infrastructure Evaluation, Instrumental Variables, and Specification Screening
Spotlight on Researcher Decisions – Infrastructure Evaluation, Instrumental Variables, and Specification Screening
Removing specification errors from the usual formulation of binary choice models
The neural encoding of information prediction errors during non-instrumental information seeking