TOOLS FOR CAUSAL INFERENCE FROM CROSS-SECTIONAL INNOVATION SURVEYS WITH CONTINUOUS OR DISCRETE VARIABLES: THEORY AND APPLICATIONS

This paper presents a new statistical toolkit by applying three techniques for data-driven causal inference from the machine learning community that are little-known among economists and innovation scholars: a conditional independence-based approach, additive noise models, and non-algorithmic infere...

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Опубліковано в::	Cuadernos de Economía
Автори:	Alex Coad, Dominik Janzing, Paul Nightingale
Формат:	Artigo
Мова:	Inglês
Опубліковано:	Universidad Nacional de Colombia 2018
Предмети:	Economía y Finanzas
Онлайн доступ:	https://www.redalyc.org/articulo.oa?id=282161175006 https://www.redalyc.org/journal/2821/282161175006/ https://www.redalyc.org/journal/2821/282161175006/html/ https://www.redalyc.org/journal/2821/282161175006/282161175006.epub https://www.redalyc.org/journal/2821/282161175006/movil
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