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06/21/2022
A sufficient and necessary condition for identification of binary choice models with fixed effects
We study the identification of binary choice models with fixed effects. ...
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07/06/2021
Inference for Low-Rank Models
This paper studies inference in linear models whose parameter of interes...
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03/24/2021
Phase transition of the monotonicity assumption in learning local average treatment effects
We consider the setting in which a strong binary instrument is available...
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03/21/2021
Comments on Leo Breiman's paper 'Statistical Modeling: The Two Cultures' (Statistical Science, 2001, 16(3), 199-231)
Breiman challenged statisticians to think more broadly, to step into the...
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06/05/2020
Can Two Forecasts Have the Same Conditional Expected Accuracy?
The method for testing equal predictive accuracy for pairs of forecastin...
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12/27/2019
Minimax Semiparametric Learning With Approximate Sparsity
Many objects of interest can be expressed as a linear, mean square conti...
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10/23/2019
How well can we learn large factor models without assuming strong factors?
In this paper, we consider the problem of learning models with a latent ...
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09/17/2019
Distributional conformal prediction
We propose a robust method for constructing conditionally valid predicti...
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05/02/2019
Sparsity Double Robust Inference of Average Treatment Effects
Many popular methods for building confidence intervals on causal effects...
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12/19/2018
Inference For Heterogeneous Effects Using Low-Rank Estimations
We study a panel data model with general heterogeneous effects, where sl...
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05/17/2018
k-step correction for mixed integer linear programming: a new approach for instrumental variable quantile regressions and related problems
This paper proposes a new framework for estimating instrumental variable...
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05/17/2018
Mixed integer linear programming: a new approach for instrumental variable quantile regressions and related problems
This paper proposes a new framework for estimating instrumental variable...
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02/26/2018
Testability of high-dimensional linear models with non-sparse structures
This paper studies hypothesis testing and confidence interval constructi...
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02/17/2018
Exact and Robust Conformal Inference Methods for Predictive Machine Learning With Dependent Data
We extend conformal inference to general settings that allow for time se...
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12/25/2017
An Exact and Robust Conformal Inference Method for Counterfactual and Synthetic Controls
This paper introduces new inference methods for counterfactual and synth...
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08/01/2017
Breaking the curse of dimensionality in regression
Models with many signals, high-dimensional models, often impose structur...
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05/06/2017
Comments on `High-dimensional simultaneous inference with the bootstrap'
We provide comments on the article "High-dimensional simultaneous infere...
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05/02/2017
A projection pursuit framework for testing general high-dimensional hypothesis
This article develops a framework for testing general hypothesis in high...
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10/14/2016
Two-sample testing in non-sparse high-dimensional linear models
In analyzing high-dimensional models, sparsity of the model parameter is...
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10/10/2016
Linear Hypothesis Testing in Dense High-Dimensional Linear Models
We propose a methodology for testing linear hypothesis in high-dimension...
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10/07/2016
