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A machine learning approach for flagging incomplete bid-rigging cartels
Wallimann, Hannes
;
Imhof, David
;
Huber, Martin
- In:
Computational economics
62
(
2023
)
4
,
pp. 1669-1720
Persistent link: https://www.econbiz.de/10014437552
Saved in:
2
Machine learning with screens for detecting bid-rigging cartels
Huber, Martin
;
Imhof, David
- In:
International journal of industrial organization
65
(
2019
),
pp. 277-301
Persistent link: https://www.econbiz.de/10012321207
Saved in:
3
Transnational machine learning with screens for flagging bid-rigging cartels
Huber, Martin
;
Imhof, David
;
Ishii, Rieko
-
2020
Persistent link: https://www.econbiz.de/10012436078
Saved in:
4
A machine learning approach for flagging incomplete bid-rigging cartels
Wallimann, Hannes
;
Imhof, David
;
Huber, Martin
-
2020
Persistent link: https://www.econbiz.de/10012260215
Saved in:
5
Machine learning with screens for detecting bid-rigging cartels
Huber, Martin
;
Imhof, David
-
2018
Persistent link: https://www.econbiz.de/10011923342
Saved in:
6
Testing for covariate balance using quantile regression and resampling methods
Huber, Martin
-
2010
Persistent link: https://www.econbiz.de/10008668305
Saved in:
7
Identification of average treatment effects in social experiments under different forms of attrition
Huber, Martin
-
2010
Persistent link: https://www.econbiz.de/10009240319
Saved in:
8
Causal pitfalls in the decomposition of wage gaps
Huber, Martin
-
2014
Persistent link: https://www.econbiz.de/10010242781
Saved in:
9
A simple test for the ignorability of non-compliance in experiments
Huber, Martin
-
2013
Persistent link: https://www.econbiz.de/10010242982
Saved in:
10
Identifying causal mechanisms in experiments (primarily) based on inverse probability weighting
Huber, Martin
-
2012
Persistent link: https://www.econbiz.de/10009719896
Saved in:
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