H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Economics and Finance D-index 47 Citations 15,526 72 World Ranking 787 National Ranking 507

Research.com Recognitions

Awards & Achievements

2012 - Member of the National Academy of Sciences

2008 - Fellow of the American Academy of Arts and Sciences

2007 - John Bates Clark Medal, the American Economic Association

2004 - Fellows of the Econometric Society

2000 - Fellow of Alfred P. Sloan Foundation

Overview

What is she best known for?

The fields of study she is best known for:

  • Statistics
  • Law
  • Microeconomics

Susan Athey mostly deals with Econometrics, Common value auction, Microeconomics, Statistics and Bidding. Susan Athey interconnects Inference, External validity, Economic model and Identification in the investigation of issues within Econometrics. Her biological study spans a wide range of topics, including Random forest and Asymptotic distribution.

Her Common value auction research includes themes of Mathematical economics, Game theory, Nash equilibrium and Complete information. Her study explores the link between Microeconomics and topics such as Private information retrieval that cross with problems in Discretion, Social welfare function and Mechanism design. Her work deals with themes such as Best response, Strategy, Service and Revenue, which intersect with Bidding.

Her most cited work include:

  • Estimation and Inference of Heterogeneous Treatment Effects using Random Forests (577 citations)
  • Identification and Inference in Nonlinear Difference-in-Differences Models (524 citations)
  • Single Crossing Properties and the Existence of Pure Strategy Equilibria in Games of Incomplete Information (415 citations)

What are the main themes of her work throughout her whole career to date?

Susan Athey focuses on Econometrics, Microeconomics, Inference, Estimator and Common value auction. Her Econometrics study integrates concerns from other disciplines, such as Random assignment and Identification. Her study in the field of Collusion, Incentive and Shock is also linked to topics like Value.

Her Inference study combines topics in areas such as Counterfactual thinking and Contrast, Regression, Statistics, Sample. Susan Athey has included themes like Mathematical optimization and Applied mathematics in her Estimator study. Her Common value auction study combines topics in areas such as Bidding, Mathematical economics and Revenue.

She most often published in these fields:

  • Econometrics (20.13%)
  • Microeconomics (14.09%)
  • Inference (15.10%)

What were the highlights of her more recent work (between 2018-2021)?

  • Estimator (13.76%)
  • Artificial intelligence (13.76%)
  • Machine learning (12.42%)

In recent papers she was focusing on the following fields of study:

Her primary areas of study are Estimator, Artificial intelligence, Machine learning, Econometrics and Regression. Her Estimator study combines topics from a wide range of disciplines, such as Mathematical optimization and Robustness. Her Machine learning research focuses on subjects like Causal inference, which are linked to Relevance.

Her specific area of interest is Econometrics, where she studies Panel data. The concepts of her Regression study are interwoven with issues in Random forest, Inference and Factor analysis. The Inference study combines topics in areas such as Counterfactual thinking and Consumer choice.

Between 2018 and 2021, her most popular works were:

  • Generalized random forests (287 citations)
  • Machine Learning Methods That Economists Should Know About (88 citations)
  • Machine Learning Methods That Economists Should Know About (88 citations)

In her most recent research, the most cited papers focused on:

  • Statistics
  • Law
  • Microeconomics

Her primary areas of investigation include Machine learning, Artificial intelligence, Estimator, Inference and Causal inference. She combines subjects such as Effective method, Counterfactual thinking and Consumer choice with her study of Machine learning. Her Estimator research incorporates elements of Decision tree, Observational study, Instrumental variable and Leverage.

Her Inference research includes elements of Outcome and Regression. Unsupervised learning is closely connected to Relevance in her research, which is encompassed under the umbrella topic of Causal inference. Her Econometrics research extends to the thematically linked field of Average treatment effect.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Identification and Inference in Nonlinear Difference-in-Differences Models

Susan Athey;Guido W. Imbens.
Econometrica (2006)

1167 Citations

Estimation and Inference of Heterogeneous Treatment Effects using Random Forests

Stefan Wager;Susan Athey.
Journal of the American Statistical Association (2018)

1059 Citations

Single Crossing Properties and the Existence of Pure Strategy Equilibria in Games of Incomplete Information

Susan Carleton Athey.
Econometrica (2001)

711 Citations

An Empirical Framework for Testing Theories About Complimentarity in Organizational Design

Susan Athey;Scott Stern.
National Bureau of Economic Research (1998)

668 Citations

The State of Applied Econometrics: Causality and Policy Evaluation

Susan Athey;Guido W. Imbens.
Journal of Economic Perspectives (2017)

633 Citations

Identification of standard auction models

Susan Athey;Philip A. Haile.
Econometrica (2002)

545 Citations

Position Auctions with Consumer Search

Susan Athey;Glenn Ellison.
Quarterly Journal of Economics (2011)

531 Citations

Optimal collusion with private information

Susan Athey;Kyle Bagwell.
The RAND Journal of Economics (2001)

528 Citations

Generalized random forests

Susan Athey;Julie Tibshirani;Stefan Wager.
Annals of Statistics (2019)

521 Citations

Recursive partitioning for heterogeneous causal effects

Susan Athey;Guido Imbens.
Proceedings of the National Academy of Sciences of the United States of America (2016)

498 Citations

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