Artikel
Causal random forests model using instrumental variable quantile regression
We propose an econometric procedure based mainly on the generalized random forests method. Not only does this process estimate the quantile treatment effect nonparametrically, but our procedure yields a measure of variable importance in terms of heterogeneity among control variables. We also apply the proposed procedure to reinvestigate the distributional effect of 401(k) participation on net financial assets, and the quantile earnings effect of participating in a job training program.
- Sprache
-
Englisch
- Erschienen in
-
Journal: Econometrics ; ISSN: 2225-1146 ; Volume: 7 ; Year: 2019 ; Issue: 4 ; Pages: 1-22 ; Basel: MDPI
- Klassifikation
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Wirtschaft
- Thema
-
causal machine learning
instrumental variable
quantile regression
quantile treatment effect
random forests
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Chen, Jau-er
Hsiang, Chen-Wei
- Ereignis
-
Veröffentlichung
- (wer)
-
MDPI
- (wo)
-
Basel
- (wann)
-
2019
- DOI
-
doi:10.3390/econometrics7040049
- 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
- Artikel
Beteiligte
- Chen, Jau-er
- Hsiang, Chen-Wei
- MDPI
Entstanden
- 2019
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