Program evaluation and causal inference with high-dimensional data
by A. Belloni, V. Chernozhukov, I. Fernández-Val and C. Hansen
| Year of publication: |
January 2017
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| Authors: | Belloni, Alexandre ; Chernozhukov, Victor ; Fernández-Val, Iván ; Hansen, Christian Bailey |
| Published in: |
Econometrica : journal of the Econometric Society, an international society for the advancement of economic theory in its relation to statistics and mathematics. - [Wechselnde Erscheinungsorte] : [Wechselnde Verlage], ISSN 0012-9682, ZDB-ID 1798-X. - Vol. 85.2017, 1, p. 233-298
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| Subject: | Machine learning | causality | Neyman orthogonality | heterogenous treatment effects | endogeneity | local average and quantile treatment effects | instruments | local effects of treatment on the treated | propensity score | Lasso | inference after model selection | moment-condition models | moment-condition models with a continuum of target parameters | Lasso and Post-Lasso with functional response data | randomized control trials | high-dimensional data | Kausalanalyse | Causality analysis | Künstliche Intelligenz | Artificial intelligence |
| Type of publication: | Article |
|---|---|
| Type of publication (narrower categories): | Aufsatz in Zeitschrift ; Article in journal |
| Language: | English |
| Other identifiers: | 10.3982/ECTA12723 [DOI] |
| Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10011738490