A structured comparison of causal machine learning methods to assess heterogeneous treatment effects in spatial data
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DOI: 10.1007/s10109-023-00413-0
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More about this item
Keywords
Causal forest; Heterogeneous treatment effects; Machine learning; Causal inference; Spatial; CO2 emissions; Transit;All these keywords.
JEL classification:
- C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
- C54 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Quantitative Policy Modeling
- C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
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