Research: Center for Econometrics
Featured Research
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Past working Papers
2022
- Optimal Paternalism in a Population with Bounded Rationality (Charles Manski and Eytan Sheshinski)
- Decomposition and Interpretation of Treatment Effects in Settings with Delayed Outcomes (Federico Bugni, Ivan Canay, and Steve McBride)
- Recovering Network Structure from Aggregated Relational Data using Penalized Regression
(Eric Auerbach, Hossein Alidaee, and Michael Leung) - Testing Homogeneity in Dynamic Discrete Games in Finite Samples (Federico Bugni, Jackson Bunting, and Takuya Ura)
- A User’s Guide for Inference in Models Defined by Moment Inequalities (Ivan Canay, Gaston Illanes, and Amilcar Velez)
- Inference for Cluster Randomized Experiments with Non-ignorable Cluster Sizes (Federico Bugni, Ivan Canay, Azeem Shaikh, and Max Tabord-Meehan)
- Subvector Inference in Partially Identified Moment Inequality Models with Many Moment Inequalities (Federico Bugni, Alexandre Belloni, and Victor Chernozhukov)
- The Local Approach to Causal Inference under Network Interference (Eric Auerbach and Max Tabord-Meehan)
- Identifying Socially Disruptive Policies (Eric Auerbach and Yong Cai)
- Digitization and Employment in the Pandemic: Evidence from Seventy Billion Emails ( Eric Auerbach, Sida Peng, Peichun Wang, Hongwei Liang, and Andy Wu)
- Using Limited Trial Evidence to Choose Treatment Dosage when Efficacy and Toxicity Weakly Increase with Dose (Charles Manski)
- Using Measures of Race to Make Clinical Predictions: Decision Making, Patient Health, and Fairness (Charles Manski, John Mullahy, and Atheendar Venkataramani)
- Inference with Imputed Data: The Allure of Making Stuff Up (Charles Manski)
- Identification and Statistical Decision Theory (Charles Manski)
2021
- Misguided Use of Observed Covariates to Impute Missing Covariates in Conditional Prediction: A Shrinkage Problem (Charles Manski, M. Gmeiner, and A. Tambur)
- A User’s Guide to Approximate Randomization Tests in Regressions with a Small Number of Clusters (Ivan Canay, Young Cai, Deborah Kim, and Azeem Shaikh)
2020
- On the Use of Outcome Tests for Detecting Bias in Decision Making (Ivan Canay, Magne Mogstad, and Jack Mountjoy)
- Estimating the COVID-19 Infection Rate: Anatomy of an Inference Problem (Charles Manski and Francesca Molinari)
- Bounding the Difference between True and Nominal Rejection Probabilities in Tests of Hypotheses about Instrumental Variables Models (Joel Horowitz)
- Adaptive Diversification of COVID-19 Policy (Charles Manski)
- Statistical Decision Properties of Imprecise Trials Assessing COVID-19 Drugs (Charles Manski and Aleksey Tetenov)
- Identification and Estimation of a Partially Linear Regression Model using Network Data(Eric Auerbach)
- Testing for Differences in Stochastic Network Structure (Eric Auerbach)
2019
- Bootstrap Methods in Econometrics (revised) (Joel Horowitz)
- Testing Exogeneity in Nonparametric Instrumental Variables Models Identified by Conditional Quantile Restrictions (Joel Horowitz, Jia-Young Michael Fu, and Matthias Parey)
- Permutation Tests for Equality of Distributions of Functional Data (Federico Bugni and Joel Horowitz)
- Estimation of a Heterogeneous Demand Function with Berkson Errors (revised) (Joel Horowitz, Richard Blundell, and Matthias Parey)
- Using Penalized Likelihood to Select Parameters in a Random Coefficients Multinomial Logit Model (Joel Horowitz and Lars Nesheim)
2018
- The Wild Bootstrap with a “Small” Number of “Large” Clusters, (Ivan Canay, Andres Santos, and Azeem M. Shaikh)
- Tail and Center Rounding of Probabilistic Expectations in the Health and Retirement Study (Charles Manski, Pamela Giustinelli, and Francesca Molinari)
- Minimax-Regret Sample Design in Anticipation of Missing Data, With Application to Panel Data (Charles Manski and Jeff Dominitz)
- Testing Continuity of a Density via g-order statistics in the Regression Discontinuity Design (Federico Bugni and Ivan Canay)
- Non-Asymptotic Inference in Instrumental Variables Estimation (Joel Horowitz)
- Bootstrap Methods in Econometrics (Joel Horowitz)
- Estimation of a Nonseparable Heterogeneous Demand Function with Shape Restrictions and Berkson Errors (Joel Horowitz, Richard Blundell, and Matthias Parey)
2017
- Inference under Covariate Adaptive Randomization with Multiple Treatments(Federico Bugni, Ivan Canay, and Azeem Shaikh)
- A Bootstrap Method for Constructing Pointwise and Uniform Confidence Bands for Conditional Quantile Functions (Joel Horowitz and Anand Kirshamurthy)
- Permutation Tests for Equality of Distributions of Functional Data (Federico Bugni and Joel Horowitz)
- Non-asymptotic inference in instrumental variables estimation (Joel Horowitz)
2016
- Nonparametric estimation and inference under shape restrictions,
Joel Horowitz and Sokbae Lee - Bias-corrected confidence intervals in a class of linear inverse problems (Joel Horowitz, Jean-Pierre Florens, and Ingrid Van Keilegom)
- Testing exogeneity in nonparametric instrumental variables identified by conditional quantile restrictions (Joel Horowitz, Jia-Young Fu, and Matthias Parey)
- Practical and Theoretical Advances in Inference for Partially Identified Models (Ivan Canay and Azeem Shaikh)
2015
- Clinical Trial Design enabling e-optimal treatment rules (Charles Manski and Aleksey Tetenov)
- Variable Selection and Estimation in High Dimensional Models (Joel Horowitz)
- Inference under Covariate Adaptive Randomization (Federico Bugni, Ivan Canay, and Azeem Shaikh)
- Approximate Permutation Tests and Induced Order Statistics in the Regression Discontinuity Design (Ivan Canay and Vishal Kamat)
- Partial Identification by Extending Subdistributions (Alex Torgovitsky)
- Partial Identification of State Dependence (Alex Torgovitsky)
2014
- The Quantile Performance of Statistical Treatment Rules Using Hypothesis Tests to Allocate a Population to Two Treatments (Charles Manski and Aleksey Tetenov)
- Randomization Tests Under an Approximate Symmetry Assumption (Joe P. Romano, Ivan Canay, and Azeem Shaikh)
- Communicating Uncertainty in Official Economic Statistics (Charles Manski)
- Inference for functions of partially identified parameters in moment inequality models (Federico Bugni, Ivan Canay, and Xiaoxia Shi)
- Instrumental variables estimation of a generalized correlated random coefficients model (Alex Torgovitsky and Matthew Masten)
- Ill-Posed inverse problems in Economics (Joel Horowitz)
2013
- Default Bayesian Inference in a Class of Partially Identified Models (Elie Tamer and Brendan Kline)
- Using Elicited Choice Probabilities in Hypothetical Elections to Study Decisions to Vote (Charles Manski and Adeline Delavande)
- Useful Variation in Clinical Practice under Uncertainty: Diversification and Learning (Charles Manski)
- Sensitivity Analysis In Semiparametric Likelihood Models (Elie Tamer, Alex Torgovitsky, and Xiaohong Chen)
- Specification Tests in Partially Identified Models defined by Moment Inequalities (Federico Bugni, Ivan Canay, and Xiaoxia Shi)
- Identification and Shape Restrictions in Nonparametric Instrumental Variables Estimation (Joachim Freyberger and Joel Horowitz)
- Nonparametric Estimation of a Heterogeneous Demand Function Under the Slutsky Inequality Restriction (Joel Horowitz, Richard Blundell, and Matthias Parey)
- A Simple Bootstrap Method for Constructing Confidence Bands for Functions (Joel Horowitz and Peter Hall)
- Identification of Nonseparable Models with General Instruments (Alex Torgovitsky)