Debiasing Random Forests for Treatment Effect Estimation

Debiasing Random Forests for Treatment Effect Estimation

Simons Institute via YouTube Direct link

Summary

12 of 13

12 of 13

Summary

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Debiasing Random Forests for Treatment Effect Estimation

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  1. 1 Introduction
  2. 2 Treatment Effect Estimation
  3. 3 Resource Allocation Tradeoffs in Election Campaign Planning
  4. 4 Conditional Average Treatment Effect (CATE)
  5. 5 Estimators for the CATE
  6. 6 Random Forests for Causal Estimation
  7. 7 Bias in Random Forests
  8. 8 Empirical CATE Coverage Simulations
  9. 9 Data Inspired CATE Coverage Simulations
  10. 10 Resource Allocation Tradeoffs in GOTV Experiments
  11. 11 Theoretical Results
  12. 12 Summary
  13. 13 Software

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