Max H Farrell
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Farrell |
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Contact
Affiliations
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University of California-Santa Barbara (UCSB)
/ Department of Economics
Research profile
author of:
- On Binscatter
American Economic Review, American Economic Association (2024)
by Matias D. Cattaneo & Richard K. Crump & Max H. Farrell & Yingjie Feng
(ReDIF-article, aea:aecrev:v:114:y:2024:i:5:p:1488-1514) - Robust Inference on Average Treatment Effects with Possibly More Covariates than Observations
Papers, arXiv.org (2013)
by Max H. Farrell
(ReDIF-paper, arx:papers:1309.4686) - On the Effect of Bias Estimation on Coverage Accuracy in Nonparametric Inference
Papers, arXiv.org (2015)
by Sebastian Calonico & Matias D. Cattaneo & Max H. Farrell
(ReDIF-paper, arx:papers:1508.02973) - Large Sample Properties of Partitioning-Based Series Estimators
Papers, arXiv.org (2018)
by Matias D. Cattaneo & Max H. Farrell & Yingjie Feng
(ReDIF-paper, arx:papers:1804.04916) - Coverage Error Optimal Confidence Intervals for Local Polynomial Regression
Papers, arXiv.org (2018)
by Sebastian Calonico & Matias D. Cattaneo & Max H. Farrell
(ReDIF-paper, arx:papers:1808.01398) - Optimal Bandwidth Choice for Robust Bias Corrected Inference in Regression Discontinuity Designs
Papers, arXiv.org (2018)
by Sebastian Calonico & Matias D. Cattaneo & Max H. Farrell
(ReDIF-paper, arx:papers:1809.00236) - Characteristic-Sorted Portfolios: Estimation and Inference
Papers, arXiv.org (2018)
by Matias D. Cattaneo & Richard K. Crump & Max H. Farrell & Ernst Schaumburg
(ReDIF-paper, arx:papers:1809.03584) - Regression Discontinuity Designs Using Covariates
Papers, arXiv.org (2018)
by Sebastian Calonico & Matias D. Cattaneo & Max H. Farrell & Rocio Titiunik
(ReDIF-paper, arx:papers:1809.03904) - Deep Neural Networks for Estimation and Inference
Papers, arXiv.org (2018)
by Max H. Farrell & Tengyuan Liang & Sanjog Misra
(ReDIF-paper, arx:papers:1809.09953) - On Binscatter
Papers, arXiv.org (2019)
by Matias D. Cattaneo & Richard K. Crump & Max H. Farrell & Yingjie Feng
(ReDIF-paper, arx:papers:1902.09608) - Binscatter Regressions
Papers, arXiv.org (2019)
by Matias D. Cattaneo & Richard K. Crump & Max H. Farrell & Yingjie Feng
(ReDIF-paper, arx:papers:1902.09615) - nprobust: Nonparametric Kernel-Based Estimation and Robust Bias-Corrected Inference
Papers, arXiv.org (2019)
by Sebastian Calonico & Matias D. Cattaneo & Max H. Farrell
(ReDIF-paper, arx:papers:1906.00198) - lspartition: Partitioning-Based Least Squares Regression
Papers, arXiv.org (2019)
by Matias D. Cattaneo & Max H. Farrell & Yingjie Feng
(ReDIF-paper, arx:papers:1906.00202) - Deep Learning for Individual Heterogeneity: An Automatic Inference Framework
Papers, arXiv.org (2020)
by Max H. Farrell & Tengyuan Liang & Sanjog Misra
(ReDIF-paper, arx:papers:2010.14694) - Higher-order Refinements of Small Bandwidth Asymptotics for Density-Weighted Average Derivative Estimators
Papers, arXiv.org (2022)
by Matias D. Cattaneo & Max H. Farrell & Michael Jansson & Ricardo Masini
(ReDIF-paper, arx:papers:2301.00277) - Nonlinear Binscatter Methods
Papers, arXiv.org (2024)
by Matias D. Cattaneo & Richard K. Crump & Max H. Farrell & Yingjie Feng
(ReDIF-paper, arx:papers:2407.15276) - RDROBUST: Stata module to provide robust data-driven inference in the regression-discontinuity design
Statistical Software Components, Boston College Department of Economics (2018)
by Sebastian Calonico & Matias D. Cattaneo & Max H. Farrell & Rocio Titiunik
(ReDIF-software, boc:bocode:s458483) - Optimal convergence rates, Bahadur representation, and asymptotic normality of partitioning estimators
Journal of Econometrics, Elsevier (2013)
by Cattaneo, Matias D. & Farrell, Max H.
(ReDIF-article, eee:econom:v:174:y:2013:i:2:p:127-143) - Robust inference on average treatment effects with possibly more covariates than observations
Journal of Econometrics, Elsevier (2015)
by Farrell, Max H.
(ReDIF-article, eee:econom:v:189:y:2015:i:1:p:1-23) - Efficient Estimation of the Dose–Response Function Under Ignorability Using Subclassification on the Covariates
Advances in Econometrics, Emerald Group Publishing Limited (2011)
by Matias D. Cattaneo & Max H. Farrell
(ReDIF-chapter, eme:aecozz:s0731-9053(2011)000027a007) - Characteristic-Sorted Portfolios: Estimation and Inference
Staff Reports, Federal Reserve Bank of New York (2016)
by Matias D. Cattaneo & Richard K. Crump & Max H. Farrell & Ernst Schaumburg
(ReDIF-paper, fip:fednsr:788) - On binscatter
Staff Reports, Federal Reserve Bank of New York (2019)
by Matias D. Cattaneo & Richard K. Crump & Max H. Farrell & Yingjie Feng
(ReDIF-paper, fip:fednsr:881) - Nonlinear Binscatter Methods
Staff Reports, Federal Reserve Bank of New York (2024)
by Matias D. Cattaneo & Richard K. Crump & Max H. Farrell & Yingjie Feng
(ReDIF-paper, fip:fednsr:98622) - Optimal bandwidth choice for robust bias-corrected inference in regression discontinuity designs
The Econometrics Journal, Royal Economic Society (2020)
by Sebastian Calonico & Matias D Cattaneo & Max H Farrell
(ReDIF-article, oup:emjrnl:v:23:y:2020:i:2:p:192-210.) - On the Effect of Bias Estimation on Coverage Accuracy in Nonparametric Inference
Journal of the American Statistical Association, Taylor & Francis Journals (2018)
by Sebastian Calonico & Matias D. Cattaneo & Max H. Farrell
(ReDIF-article, taf:jnlasa:v:113:y:2018:i:522:p:767-779) - Regression Discontinuity Designs Using Covariates
The Review of Economics and Statistics, MIT Press (2019)
by Sebastian Calonico & Matias D. Cattaneo & Max H. Farrell & Rocío Titiunik
(ReDIF-article, tpr:restat:v:101:y:2019:i:3:p:442-451) - Characteristic-Sorted Portfolios: Estimation and Inference
The Review of Economics and Statistics, MIT Press (2020)
by Matias D. Cattaneo & Richard K. Crump & Max H. Farrell & Ernst Schaumburg
(ReDIF-article, tpr:restat:v:102:y:2020:i:3:p:531-551) - rdrobust: Software for regression-discontinuity designs
Stata Journal, StataCorp LLC (2017)
by Sebastian Calonico & Matias D. Cattaneo & Max H. Farrell & Roc ́ıo Titiunik
(ReDIF-article, tsj:stataj:v:17:y:2017:i:2:p:372-404) - Binscatter regressions
Stata Journal, StataCorp LLC (2025)
by Matias D. Cattaneo & Richard K. Crump & Max H. Farrell & Yingjie Feng
(ReDIF-article, tsj:stataj:v:25:y:2025:i:1:p:3-50) - Deep Neural Networks for Estimation and Inference
Econometrica, Econometric Society (2021)
by Max H. Farrell & Tengyuan Liang & Sanjog Misra
(ReDIF-article, wly:emetrp:v:89:y:2021:i:1:p:181-213)