Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Henrika Langen"'
Autor:
Henrika Langen
Publikováno v:
PLoS ONE, Vol 19, Iss 5, p e0302827 (2024)
This study assesses the effect of the #MeToo movement on the language used in judicial opinions on sexual violence related cases from 51 U.S. state and federal appellate courts. The study introduces various indicators to quantify the extent to which
Externí odkaz:
https://doaj.org/article/6d361c8d19e54a3baaa8bf69df734b2d
Autor:
Henrika Langen, Martin Huber
Publikováno v:
PLoS ONE, Vol 18, Iss 1, p e0278937 (2023)
We apply causal machine learning algorithms to assess the causal effect of a marketing intervention, namely a coupon campaign, on the sales of a retailer. Besides assessing the average impacts of different types of coupons, we also investigate the he
Externí odkaz:
https://doaj.org/article/da7bd017c9a046738b8dbbe36543b31f
Autor:
Martin Huber, Henrika Langen
Publikováno v:
Swiss Journal of Economics and Statistics, Vol 156, Iss 1, Pp 1-19 (2020)
Abstract We assess the impact of the timing of lockdown measures implemented in Germany and Switzerland on cumulative COVID-19-related hospitalization and death rates. Our analysis exploits the fact that the epidemic was more advanced in some regions
Externí odkaz:
https://doaj.org/article/5b78df5dad854cb7b219774ebb7560a6
Publikováno v:
The Econometrics Journal. 25:277-300
This paper combines causal mediation analysis with double machine learning to control for observed confounders in a data-driven way under a selection-on-observables assumption in a high-dimensional setting. We consider the average indirect effect of
Autor:
Henrika Langen, Martin Huber
We apply causal machine learning algorithms to assess the causal effect of a marketing intervention, namely a coupon campaign, on the sales of a retailer. Besides assessing the average impacts of different types of coupons, we also investigate the he
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3586a430cff9d605dae424157573719e