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 independencebased approach, additive noise models, and non-algorithmic inferen...
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Universidad Nacional de Colombia
2018-12-01
|
| Series: | Cuadernos de Economía |
| Subjects: | |
| Online Access: | https://revistas.unal.edu.co/index.php/ceconomia/article/view/69832 |