Max H. Farrell

Associate Professor of Economics
Mellichamp Chair of Mind and Machine Intelligence
University of California, Santa Barbara

Curriculum Vitae (PDF)

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Working Papers

  1. Higher-order Refinements of Small Bandwidth Asymptotics for Density-Weighted Average Derivative Estimators | arXiv
  2. Deep Learning for Individual Heterogeneity: An Automatic Inference Framework | arXiv | cemmap
  3. On Binscatter | arXiv | Replication


  1. Coverage Error Optimal Confidence Intervals for Local Polynomial Regression | arXiv | Published PDF | Replication
  2. Deep Neural Networks for Estimation and Inference | arXiv | Published PDF | Replication
  3. Large Sample Properties of Partitioning-Based Series Estimators | arXiv | Published PDF | Replication
  4. Optimal Bandwidth Choice for Robust Bias Corrected Inference in Regression Discontinuity Designs | arXiv | Published PDF | Replication
  5. Characteristic-Sorted Portfolios: Estimation and Inference | arXiv | Published PDF | Replication
  6. Regression Discontinuity Designs Using Covariates | arXiv | Published PDF | Supplement PDF | Replication
  7. On the Effect of Bias Estimation on Coverage Accuracy in Nonparametric Inference | arXiv | Published PDF | Replication
  8. Robust Inference on Average Treatment Effects with Possibly More Covariates than Observations | arXiv | Published PDF | Replication
  9. Optimal Convergence Rates, Bahadur Representation, and Asymptotic Normality of Partitioning Estimators | Published PDF | Supplement PDF
  10. Efficient Estimation of the Dose Response Function under Ignorability using Subclassification on the Covariates | PDF

Last updated October 2022