The New Palgrave Dictionary of Economics Online Causality in Economics and Econometrics

By Kevin D. Hoover, Steven N. Durlauf, L. Blume

Subfields: Causal Inference & Discovery, Economics & Operations Research

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Causal Inference & Discovery

1. Bernhard Schölkopf
2. Kun Zhang
3. Jan Peters
4. Dominik Janzing
5. Stefan Bauer
6. Yoshua Bengio
7. Anirudh Goyal
8. Peter Spirtes

In Economics & Operations Research

1. Peter Spirtes
2. Jan Peters
3. Stefan Bauer
4. Bernhard Schölkopf
5. Yoshua Bengio
6. Miguel D. Mahecha
7. Kun Zhang

Citations in the corpus

• Toward Causal Representation Learning (2021, background): “The notion of invariant, autonomous, and independent mechanisms has appeared in various guises throughout the history of causality research [72], [100], [111], [124], [183], [188], [240].”
• Towards Causal Representation Learning (2021, background): “The notion of invariant, autonomous, and independent mechanisms has appeared in various guises throughout the history of causality research [99, 71, 111, 183, 120, 240, 188].”
• Causality for Machine Learning (2019, background): “Hoover (2008) attributes to Herb Simon the invariance criterion: the true causal order is the one that is invariant under the right sort of intervention.”
• Inferring causation from time series in Earth system sciences (2019, background): “Next to Granger ’ s seminal works in economics 9,29 , observational causal inference methods have mostly been applied in neuroscience 30,31 and bioinformatics 32,33 where observational causal inference can also be combined with interventional experiments.”