Arbeitspapier
Proxy variables and nonparametric identification of causal effects
Proxy variables are often used in linear regression models with the aim of removing potential confounding bias. In this paper we formalise proxy variables within the potential outcome framework, giving conditions under which it can be shown that causal effects are nonparametrically identified. We characterise two types of proxy variables and give concrete examples where the proxy conditions introduced may hold by design.
- Sprache
-
Englisch
- Erschienen in
-
Series: Working Paper ; No. 2016:12
- Klassifikation
-
Wirtschaft
Semiparametric and Nonparametric Methods: General
- Thema
-
average treatment effect
observational studies
potential outcomes
unobserved confounders
- Ereignis
-
Geistige Schöpfung
- (wer)
-
DeLuna, Xavier
Fowler, Philip
Johansson, Per-Olov
- Ereignis
-
Veröffentlichung
- (wer)
-
Institute for Evaluation of Labour Market and Education Policy (IFAU)
- (wo)
-
Uppsala
- (wann)
-
2016
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:43 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- DeLuna, Xavier
- Fowler, Philip
- Johansson, Per-Olov
- Institute for Evaluation of Labour Market and Education Policy (IFAU)
Entstanden
- 2016
Ähnliche Objekte (12)
Proxy Variables and Nonparametric Identification of Causal Effects
Nonparametric identification with discrete endogenous variables
Nonparametric identification using instrumental variables: Sufficient conditions for completeness
Nonparametric identification using instrumental variables: Sufficient conditions for completeness
Nonparametric identification of dynamic models with unobserved state variables
Identification and shape restrictions in nonparametric instrumental variables estimation
Nonparametric identification of dynamic models with unobserved state variables
Identification and shape restrictions in nonparametric instrumental variables estimation
On causal networks of financial firms: Structural identification via non-parametric heteroskedasticity
Testing for nonparametric identification of causal effects in the presence of a quasi-instrument
Testing for nonparametric identification of causal effects in the presence of a quasi-instrument
Nonparametric instrumental variable estimation
Proxy Variables and Nonparametric Identification of Causal Effects
Nonparametric identification with discrete endogenous variables
Nonparametric identification using instrumental variables: Sufficient conditions for completeness
Nonparametric identification using instrumental variables: Sufficient conditions for completeness
Nonparametric identification of dynamic models with unobserved state variables
Identification and shape restrictions in nonparametric instrumental variables estimation
Nonparametric identification of dynamic models with unobserved state variables
Identification and shape restrictions in nonparametric instrumental variables estimation
On causal networks of financial firms: Structural identification via non-parametric heteroskedasticity
Testing for nonparametric identification of causal effects in the presence of a quasi-instrument
Testing for nonparametric identification of causal effects in the presence of a quasi-instrument
Nonparametric instrumental variable estimation
Proxy Variables and Nonparametric Identification of Causal Effects
Nonparametric identification with discrete endogenous variables
Nonparametric identification using instrumental variables: Sufficient conditions for completeness
Nonparametric identification using instrumental variables: Sufficient conditions for completeness
Nonparametric identification of dynamic models with unobserved state variables
Identification and shape restrictions in nonparametric instrumental variables estimation
Nonparametric identification of dynamic models with unobserved state variables
Identification and shape restrictions in nonparametric instrumental variables estimation
On causal networks of financial firms: Structural identification via non-parametric heteroskedasticity
Testing for nonparametric identification of causal effects in the presence of a quasi-instrument
Testing for nonparametric identification of causal effects in the presence of a quasi-instrument