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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| 出版年: | Cuadernos de Economía |
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| 主要な著者: | , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Universidad Nacional de Colombia
2018
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| 主題: | |
| オンライン･アクセス: | 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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