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Year of publication
Subject
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Neyman 2 Orthogonalization 2 boosted trees 2 cross-fit 2 debiased machine learning 2 deep learning 2 double machine learning 2 efficiency 2 efficient score 2 lasso 2 neural nets 2 optimality 2 orthogonal score 2 post-machine-learning and post-regularization inference 2 random forest 2 Arbeitsbedingungen 1 Arbeitsbeziehungen 1 Arbeitsplatz 1 Arbeitszufriedenheit 1 Artificial intelligence 1 Betriebliches Gesundheitsmanagement 1 Causality analysis 1 Corporate culture 1 Econometrics 1 Employment relations 1 Forecasting model 1 Gesundheitsvorsorge 1 Job satisfaction 1 Kausalanalyse 1 Künstliche Intelligenz 1 Learning 1 Learning process 1 Lernen 1 Lernprozess 1 Neural networks 1 Neuronale Netze 1 Occupational health 1 Personality psychology 1 Persönlichkeitspsychologie 1 Preventive care 1
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Online availability
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Free 2 Undetermined 1
Type of publication
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Book / Working Paper 2 Article 1
Type of publication (narrower categories)
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Working Paper 2 Arbeitspapier 1 Article in journal 1 Aufsatz in Zeitschrift 1 Graue Literatur 1 Non-commercial literature 1
Language
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English 3
Author
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Chernozhukov, Victor 2 Chetverikov, Denis 2 Demirer, Mert 2 Duflo, Esther 2 Newey, Whitney K. 2 Damon, Zack 1 Hansen, Christian 1 Hansen, Christian Bailey 1 James, Eric P. 1 Zanin, Alaina C. 1
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Published in...
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CEMMAP working papers / Centre for Microdata Methods and Practice 1 Management communication quarterly : an international journal 1 cemmap working paper 1
Source
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ECONIS (ZBW) 2 EconStor 1
Showing 1 - 3 of 3
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Double machine learning for treatment and causal parameters
Chernozhukov, Victor; Chetverikov, Denis; Demirer, Mert; … - 2016
Most modern supervised statistical/machine learning (ML) methods are explicitly designed to solve prediction problems very well. Achieving this goal does not imply that these methods automatically deliver good estimators of causal parameters. Examples of such parameters include individual...
Persistent link: https://www.econbiz.de/10011594359
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Cover Image
Double machine learning for treatment and causal parameters
Chernozhukov, Victor; Chetverikov, Denis; Demirer, Mert; … - 2016
Most modern supervised statistical/machine learning (ML) methods are explicitly designed to solve prediction problems very well. Achieving this goal does not imply that these methods automatically deliver good estimators of causal parameters. Examples of such parameters include individual...
Persistent link: https://www.econbiz.de/10011538313
Saved in:
Cover Image
Blue-collar and healthy worker identities : how parallel ideal worker identities sustain unobtrusive control on the shop-floor
James, Eric P.; Zanin, Alaina C.; Damon, Zack - In: Management communication quarterly : an international … 37 (2023) 3, pp. 542-571
Persistent link: https://www.econbiz.de/10014312928
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