Construct · 1 fields · 1 citations

double machine learning: a standalone construct

One name. One construct. A landmark on the map.

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Causal inference

estimating causal parameters with machine-learning nuisance models plus orthogonalization and cross-fitting to remove regularization bias.

In causal inference, double machine learning refers to estimating causal parameters with machine-learning nuisance models plus orthogonalization and cross-fitting to remove regularization bias. This meaning comes from Chernozhukov (2018) in The Econometrics Journal.[1]

Unit
Recovery means
Measured by

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Nearby constructs

bias6 fields · 8 citationsjingle · one name, six constructs causation6 fields · 15 citationsjingle · one name, six constructs inference3 fields · 5 citationsjingle · one word, three constructs

References

Chernozhukov, V., Chetverikov, D., Demirer, M., Duflo, E., Hansen, C., Newey, W., & Robins, J. (2018). Double/debiased machine learning for treatment and structural parameters. The Econometrics Journal, 21(1), C1-C68. https://doi.org/10.1111/ectj.12097

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