Omitted variable bias of Lasso-based inference methods : a finite sample analysis
Kaspar Wüthrich, Ying Zhu
| Year of publication: |
[2022] ; This version: September 14, 2021
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| Authors: | Wüthrich, Kaspar ; Zhu, Ying |
| Institutions: | University of California, San Diego / Department of Economics (issuing body) |
| Publisher: |
San Diego : Department of Economics, UC San Diego [Ithaca, New York] : Cornell University |
| Subject: | Lasso | post double Lasso | debiased Lasso | OLS | omitted variablebias | size distortions | nite sample analysis | Theorie | Theory | Stichprobenerhebung | Sampling | Systematischer Fehler | Bias | Induktive Statistik | Statistical inference | Regressionsanalyse | Regression analysis |
| Extent: | 1 Online-Ressource (circa 87 Seiten) Illustrationen |
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| Series: | |
| Type of publication: | Book / Working Paper |
| Type of publication (narrower categories): | Graue Literatur ; Non-commercial literature |
| Language: | English |
| Notes: | Auch erschienen in: The review of economics and statistics https://doi.org/10.1162/rest_a_01128 |
| Other identifiers: | 10.48550/arXiv.1903.08704 [DOI] |
| Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://ebvufind01.dmz1.zbw.eu/10013387539