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Max H Farrell

Personal Details

First Name:Max
Middle Name:H
Last Name:Farrell
Suffix:
RePEc Short-ID:pfa702
[This author has chosen not to make the email address public]

Affiliation

Department of Economics
University of California-Santa Barbara (UCSB)

Santa Barbara, California (United States)
http://www.econ.ucsb.edu/
RePEc:edi:educsus (more details at EDIRC)

Research output

as
Jump to: Working papers Articles Software Chapters

Working papers

  1. Matias D. Cattaneo & Richard K. Crump & Max H. Farrell & Yingjie Feng, 2024. "Nonlinear Binscatter Methods," Papers 2407.15276, arXiv.org.
  2. Matias D. Cattaneo & Max H. Farrell & Michael Jansson & Ricardo Masini, 2022. "Higher-order Refinements of Small Bandwidth Asymptotics for Density-Weighted Average Derivative Estimators," Papers 2301.00277, arXiv.org, revised Feb 2024.
  3. Max H. Farrell & Tengyuan Liang & Sanjog Misra, 2020. "Deep Learning for Individual Heterogeneity: An Automatic Inference Framework," Papers 2010.14694, arXiv.org, revised Jul 2021.
  4. Matias D. Cattaneo & Richard K. Crump & Max H. Farrell & Yingjie Feng, 2019. "On Binscatter," Papers 1902.09608, arXiv.org, revised Apr 2024.
    • Matias D. Cattaneo & Richard K. Crump & Max H. Farrell & Yingjie Feng, 2024. "On Binscatter," American Economic Review, American Economic Association, vol. 114(5), pages 1488-1514, May.
  5. Matias D. Cattaneo & Max H. Farrell & Yingjie Feng, 2019. "lspartition: Partitioning-Based Least Squares Regression," Papers 1906.00202, arXiv.org, revised Aug 2019.
  6. Matias D. Cattaneo & Richard K. Crump & Max H. Farrell & Yingjie Feng, 2019. "Binscatter Regressions," Papers 1902.09615, arXiv.org, revised Jul 2024.
  7. Sebastian Calonico & Matias D. Cattaneo & Max H. Farrell, 2019. "nprobust: Nonparametric Kernel-Based Estimation and Robust Bias-Corrected Inference," Papers 1906.00198, arXiv.org.
  8. Sebastian Calonico & Matias D. Cattaneo & Max H. Farrell, 2018. "Optimal Bandwidth Choice for Robust Bias Corrected Inference in Regression Discontinuity Designs," Papers 1809.00236, arXiv.org, revised Jan 2020.
  9. Matias D. Cattaneo & Richard K. Crump & Max H. Farrell & Ernst Schaumburg, 2018. "Characteristic-Sorted Portfolios: Estimation and Inference," Papers 1809.03584, arXiv.org, revised Oct 2019.
  10. Max H. Farrell & Tengyuan Liang & Sanjog Misra, 2018. "Deep Neural Networks for Estimation and Inference," Papers 1809.09953, arXiv.org, revised Sep 2019.
  11. Sebastian Calonico & Matias D. Cattaneo & Max H. Farrell, 2018. "Coverage Error Optimal Confidence Intervals for Local Polynomial Regression," Papers 1808.01398, arXiv.org, revised Jul 2021.
  12. Matias D. Cattaneo & Max H. Farrell & Yingjie Feng, 2018. "Large Sample Properties of Partitioning-Based Series Estimators," Papers 1804.04916, arXiv.org, revised Jun 2019.
  13. Sebastian Calonico & Matias D. Cattaneo & Max H. Farrell & Rocio Titiunik, 2018. "Regression Discontinuity Designs Using Covariates," Papers 1809.03904, arXiv.org.
  14. Sebastian Calonico & Matias D. Cattaneo & Max H. Farrell, 2015. "On the Effect of Bias Estimation on Coverage Accuracy in Nonparametric Inference," Papers 1508.02973, arXiv.org, revised Mar 2018.
  15. Max H. Farrell, 2013. "Robust Inference on Average Treatment Effects with Possibly More Covariates than Observations," Papers 1309.4686, arXiv.org, revised Feb 2018.

Articles

  1. Matias D. Cattaneo & Richard K. Crump & Max H. Farrell & Yingjie Feng, 2024. "On Binscatter," American Economic Review, American Economic Association, vol. 114(5), pages 1488-1514, May.
  2. Max H. Farrell & Tengyuan Liang & Sanjog Misra, 2021. "Deep Neural Networks for Estimation and Inference," Econometrica, Econometric Society, vol. 89(1), pages 181-213, January.
  3. Matias D. Cattaneo & Richard K. Crump & Max H. Farrell & Ernst Schaumburg, 2020. "Characteristic-Sorted Portfolios: Estimation and Inference," The Review of Economics and Statistics, MIT Press, vol. 102(3), pages 531-551, July.
  4. Sebastian Calonico & Matias D Cattaneo & Max H Farrell, 2020. "Optimal bandwidth choice for robust bias-corrected inference in regression discontinuity designs," The Econometrics Journal, Royal Economic Society, vol. 23(2), pages 192-210.
  5. Sebastian Calonico & Matias D. Cattaneo & Max H. Farrell & Rocío Titiunik, 2019. "Regression Discontinuity Designs Using Covariates," The Review of Economics and Statistics, MIT Press, vol. 101(3), pages 442-451, July.
  6. Sebastian Calonico & Matias D. Cattaneo & Max H. Farrell, 2018. "On the Effect of Bias Estimation on Coverage Accuracy in Nonparametric Inference," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 113(522), pages 767-779, April.
  7. Sebastian Calonico & Matias D. Cattaneo & Max H. Farrell & Roc ́ıo Titiunik, 2017. "rdrobust: Software for regression-discontinuity designs," Stata Journal, StataCorp LP, vol. 17(2), pages 372-404, June.
  8. Farrell, Max H., 2015. "Robust inference on average treatment effects with possibly more covariates than observations," Journal of Econometrics, Elsevier, vol. 189(1), pages 1-23.
  9. Cattaneo, Matias D. & Farrell, Max H., 2013. "Optimal convergence rates, Bahadur representation, and asymptotic normality of partitioning estimators," Journal of Econometrics, Elsevier, vol. 174(2), pages 127-143.

Software components

  1. Sebastian Calonico & Matias D. Cattaneo & Max H. Farrell & Rocio Titiunik, 2018. "RDROBUST: Stata module to provide robust data-driven inference in the regression-discontinuity design," Statistical Software Components S458483, Boston College Department of Economics, revised 30 Sep 2022.

Chapters

  1. Matias D. Cattaneo & Max H. Farrell, 2011. "Efficient Estimation of the Dose–Response Function Under Ignorability Using Subclassification on the Covariates," Advances in Econometrics, in: Missing Data Methods: Cross-sectional Methods and Applications, pages 93-127, Emerald Group Publishing Limited.

More information

Research fields, statistics, top rankings, if available.

Statistics

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Rankings

This author is among the top 5% authors according to these criteria:
  1. Number of Citations, Discounted by Citation Age
  2. Number of Citations, Weighted by Simple Impact Factor, Discounted by Citation Age
  3. Number of Citations, Weighted by Recursive Impact Factor, Discounted by Citation Age
  4. Number of Citations, Weighted by Number of Authors, Discounted by Citation Age
  5. Number of Citations, Weighted by Number of Authors and Simple Impact Factors, Discounted by Citation Age
  6. Number of Citations, Weighted by Number of Authors and Recursive Impact Factors, Discounted by Citation Age
  7. Number of Abstract Views in RePEc Services over the past 12 months
  8. Euclidian citation score
  9. Breadth of citations across fields
  10. Wu-Index

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 11 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-ECM: Econometrics (10) 2016-08-21 2018-04-23 2018-08-20 2018-09-24 2018-10-01 2018-10-08 2019-03-04 2020-11-16 2023-02-06 2024-08-26. Author is listed
  2. NEP-BIG: Big Data (3) 2018-10-08 2019-03-11 2020-11-16
  3. NEP-CMP: Computational Economics (1) 2020-11-16
  4. NEP-DCM: Discrete Choice Models (1) 2020-11-16
  5. NEP-NET: Network Economics (1) 2020-11-16

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