96 citations · 339 across the 17 of their papers we have counts for
19 papers
Adapting to Misspecification
Timothy B. Armstrong, Patrick Kline, Liyang Sun
Empirical research typically involves a robustness-efficiency tradeoff. A researcher seeking to estimate a scalar parameter can invoke strong assumptions to motivate a restricted e…
Robust Estimation and Inference in Panels with Interactive Fixed Effects
Timothy B. Armstrong, Martin Weidner, Andrei Zeleneev
We consider estimation and inference for a regression coefficient in panels with interactive fixed effects (i.e., with a factor structure). We demonstrate that existing estimators…
False Discovery Rate Adjustments for Average Significance Level Controlling Tests
Timothy B. Armstrong
Multiple testing adjustments, such as the Benjamini & Hochberg (1995) step-up procedure for controlling the false discovery rate (FDR), are typically applied to families of tests t…
Asymptotic Efficiency Bounds for a Class of Experimental Designs
Timothy B. Armstrong
We consider an experimental design setting in which units are assigned to treatment after being sampled sequentially from an infinite population. We derive asymptotic efficiency bo…
Bias-Aware Inference in Regularized Regression Models
Timothy B. Armstrong, Michal Kolesár, Soonwoo Kwon
We consider inference on a scalar regression coefficient under a constraint on the magnitude of the control coefficients. A class of estimators based on a regularized propensity sc…
Robust Empirical Bayes Confidence Intervals
Timothy B. Armstrong, Michal Kolesár, Mikkel Plagborg-Møller
We construct robust empirical Bayes confidence intervals (EBCIs) in a normal means problem. The intervals are centered at the usual linear empirical Bayes estimator, but use a crit…
Adaptation Bounds for Confidence Bands under Self-Similarity
Timothy B. Armstrong
We derive bounds on the scope for a confidence band to adapt to the unknown regularity of a nonparametric function that is observed with noise, such as a regression function or den…
Sensitivity Analysis using Approximate Moment Condition Models
Timothy B. Armstrong, Michal Kolesár
We consider inference in models defined by approximate moment conditions. We show that near-optimal confidence intervals (CIs) can be formed by taking a generalized method of momen…
Finite-Sample Optimal Estimation and Inference on Average Treatment Effects Under Unconfoundedness
Timothy B. Armstrong, Michal Kolesár
We consider estimation and inference on average treatment effects under unconfoundedness conditional on the realizations of the treatment variable and covariates. Given nonparametr…
Simple and Honest Confidence Intervals in Nonparametric Regression
Timothy B. Armstrong, Michal Kolesár
We consider the problem of constructing honest confidence intervals (CIs) for a scalar parameter of interest, such as the regression discontinuity parameter, in nonparametric regre…
Optimal inference in a class of regression models
Timothy B. Armstrong, Michal Kolesár
We consider the problem of constructing confidence intervals (CIs) for a linear functional of a regression function, such as its value at a point, the regression discontinuity para…
Unbiased Instrumental Variables Estimation Under Known First-Stage Sign
Isaiah Andrews, Timothy B. Armstrong
We derive mean-unbiased estimators for the structural parameter in instrumental variables models with a single endogenous regressor where the sign of one or more first stage coeffi…
A Note on Minimax Testing and Confidence Intervals in Moment Inequality Models
Timothy B. Armstrong
This note uses a simple example to show how moment inequality models used in the empirical economics literature lead to general minimax relative efficiency comparisons. The main po…
A Simple Adjustment for Bandwidth Snooping
Timothy B. Armstrong, Michal Kolesár
Kernel-based estimators such as local polynomial estimators in regression discontinuity designs are often evaluated at multiple bandwidths as a form of sensitivity analysis. Howeve…
On the Choice of Test Statistic for Conditional Moment Inequalities
Timothy B. Armstrong
This paper derives asymptotic approximations to the power of Cramer-von Mises (CvM) style tests for inference on a finite dimensional parameter defined by conditional moment inequa…
Adaptive testing on a regression function at a point
Timothy Armstrong
We consider the problem of inference on a regression function at a point when the entire function satisfies a sign or shape restriction under the null. We propose a test that achie…
On the Asymptotic Distribution of Variance Weighted KS Statistics
Timothy B. Armstrong
This paper derives the asymptotic distribution of variance weighted Kolmogorov-Smirnov statistics for conditional moment inequality models for the case of a one dimensional covaria…
Asymptotically Exact Inference in Conditional Moment Inequality Models
Timothy B. Armstrong
This paper derives the rate of convergence and asymptotic distribution for a class of Kolmogorov-Smirnov style test statistics for conditional moment inequality models for paramete…
Weighted KS Statistics for Inference on Conditional Moment Inequalities
Timothy B. Armstrong
This paper proposes confidence regions for the identified set in conditional moment inequality models using Kolmogorov-Smirnov statistics with a truncated inverse variance weightin…