Working Papers

These are some of the recent working papers by members of the Center for Econometrics.

2022-23

  1. Optimal Paternalism in a Population with Bounded Rationality,
    Charles F. Manski, and Eytan Sheshinski
  2. Decomposition and Interpretation of Treatment Effects in Settings with Delayed Outcomes,
    Federico A. Bugni, Ivan A. Canay, and Steve McBride
  3. Recovering Network Structure from Aggregated Relational Data using Penalized Regression,
    Hossein Alidaee, Eric Auerbach, and Michael Leung
  4. Testing Homogeneity in Dynamic Discrete Games in Finite Samples,
    Federico A. Bugni, Jackson Bunting, and Takuya Ura
  5. A User’s Guide for Inference in Models Defined by Moment Inequalities,
    Ivan A. Canay, Gaston Illanes, and Amilcar Velez
  6. Inference for Cluster Randomized Experiments with Non-ignorable Cluster Sizes,
    Federico Bugni, Ivan Canay, Azeem Shaikh, and Max Tabord-Meehan
  7. Subvector Inference in Partially Identified Moment Inequality Models with Many Moment Inequalities,
    Alexandre Belloni, Federico A. Bugni, and Victor Chernozhukov
  8. The Local Approach to Causal Inference under Network Interference,
    Eric Auerbach and Max Tabord-Meehan
  9. Identifying Socially Disruptive Policies,
    Eric Auerbach and Yong Cai
  10. Digitization and Employment in the Pandemic: Evidence from Seventy Billion Emails,
    Sida Peng, Peichun Wang, Eric Auerbach, Hongwei Liang, and Andy Wu
  11. Using Limited Trial Evidence to Choose Treatment Dosage when Efficacy and Toxicity Weakly Increase with Dose,
    Charles F. Manski
  12. Using Measures of Race to Make Clinical Predictions: Decision Making, Patient Health, and Fairness,
    Charles F. Manski, John Mullahy, and Atheendar Venkataramani
  13. Inference with Imputed Data: The Allure of Making Stuff Up,
    Charles F. Manski
  14. Identification and Statistical Decision Theory,
    Charles F. Manski

2021

  1. Misguided Use of Observed Covariates to Impute Missing Covariates in Conditional Prediction: A Shrinkage Problem,
    M. Gmeiner, Charles F. Manski, and A. Tambur
  2. A User’s Guide to Approximate Randomization Tests in Regressions with a Small Number of Clusters,
    Young Cai, Ivan A. Canay, Deborah Kim, and Azeem Shaikh

2020

  1. On the Use of Outcome Tests for Detecting Bias in Decision Making,
    Ivan A. Canay,  Magne Mogstad, and Jack Mountjoy
  2. Estimating the COVID-19 Infection Rate: Anatomy of an Inference Problem,
    Charles F. Manski and Francesca Molinari
  3. Bounding the Difference between True and Nominal Rejection Probabilities in Tests of Hypotheses about Instrumental Variables Models
    Joel L. Horowitz
  4. Adaptive Diversification of COVID-19 Policy,
    Charles F. Manski
  5. Statistical Decision Properties of Imprecise Trials Assessing COVID-19 Drugs,
    Charles F. Manski and Aleksey Tetenov
  6. Identification and Estimation of a Partially Linear Regression Model using Network Data,
    Eric Auerbach
  7. Testing for Differences in Stochastic Network Structure,
    Eric Auerbach

2019

  1. Bootstrap Methods in Econometrics (revised)
    Joel L. Horowitz
  2. Testing Exogeneity in Nonparametric Instrumental Variables Models Identified by Conditional Quantile Restrictions
    Jia-Young Michael Fu, Joel L. Horowitz, and Matthias Parey
  3. Permutation Tests for Equality of Distributions of Functional Data
    Federico A. Bugni and Joel L. Horowitz
  4. Estimation of a Heterogeneous Demand Function with Berkson Errors (revised)
    Richard Blundell, Joel L. Horowitz, and Matthias Parey
  5. Using Penalized Likelihood to Select Parameters in a Random Coefficients Multinomial Logit Model
    Joel L. Horowitz and Lars Nesheim

2018

  1. The Wild Bootstrap with a “Small” Number of “Large” Clusters,
    Ivan A. Canay,  Andres Santos, and Azeem M. Shaikh
  2. Tail and Center Rounding of Probabilistic Expectations in the Health and Retirement Study,
    Pamela Giustinelli, Charles F. Manski, and Francesca Molinari
  3. Minimax-Regret Sample Design in Anticipation of Missing Data, With Application to Panel Data,
    Jeff Dominitz and Charles F. Manski
  4. Testing Continuity of a Density via g-order statistics in the Regression Discontinuity Design,
    Federico A. Bugni and Ivan A. Canay
  5. Non-Asymptotic Inference in Instrumental Variables Estimation,
    Joel Horowitz
  6. Bootstrap Methods in Econometrics,
    Joel L. Horowitz
  7. Estimation of a Nonseparable Heterogeneous Demand Function with Shape Restrictions and Berkson Errors,
    Richard Blundell, Joel L. Horowitz, and Matthias Parey

2017

  1. Inference under Covariate Adaptive Randomization with Multiple Treatments
    Federico A. Bugni, Ivan A. Canay,  and Azeem Shaikh
  2. A Bootstrap Method for Constructing Pointwise and Uniform Confidence Bands for Conditional Quantile Functions,
    Joel L. Horowitz, and Anand Kirshamurthy
  3. Permutation Tests for Equality of Distributions of Functional Data,
    Federico Bugni and Joel Horowitz
  4. Non-asymptotic inference in instrumental variables estimation,
    Joel L. Horowitz

2016

  1. Nonparametric estimation and inference under shape restrictions,
    Joel L. Horowitz and Sokbae Lee
  2. Bias-corrected confidence intervals in a class of linear inverse problems,
    Jean-Pierre Florens, Joel L. Horowitz, and Ingrid Van Keilegom
  3. Testing exogeneity in nonparametric instrumental variables identified by conditional quantile restrictions,
    Jia-Young Fu, Joel L. Horowitz, and Matthias Parey
  4. Practical and Theoretical Advances in Inference for Partially Identified Models,
    Ivan A. Canay and Azeem Shaikh

2015

  1. Clinical Trial Design enabling e-optimal treatment rules
    Charles F. Manski and Aleksey Tetenov
  2. Variable Selection and Estimation in High Dimensional Models,
    Joel L. Horowitz
  3. Inference under Covariate Adaptive Randomization,
    Federico Bugni, Ivan A. Canay, and Azeem Shaikh
  4. Approximate Permutation Tests and Induced Order Statistics in the Regression Discontinuity Design,
    Ivan A. Canay and Vishal Kamat
  5. Partial Identification by Extending Subdistributions,
    Alex Torgovitsky
  6. Partial Identification of State Dependence,
    Alex Torgovitsky

2014

  1. The Quantile Performance of Statistical Treatment Rules Using Hypothesis Tests to Allocate a Population to Two Treatments,
    Charles F. Manski and Aleksey Tetenov
  2. Randomization Tests Under an Approximate Symmetry Assumption,
    Joe P. Romano, Ivan A. Canay and Azeem Shaikh
  3. Communicating Uncertainty in Official Economic Statistics,
    Charles F. Manski
  4. Inference for functions of partially identified parameters in moment inequality models,
    Federico Bugni, Ivan A. Canay and Xiaoxia Shi
  5. Instrumental variables estimation of a generalized correlated random coefficients model,
    Matthew Masten and Alex Torgovitsky
  6. Ill-Posed inverse problems in Economics,
    Joel L. Horowitz

2013

  1. Default Bayesian Inference in a Class of Partially Identified Models,
    Brendan Kline and Elie Tamer
  2. Using Elicited Choice Probabilities in Hypothetical Elections to Study Decisions to Vote,
    Adeline Delavande and Charles F. Manski
  3. Useful Variation in Clinical Practice under Uncertainty: Diversification and Learning
    Charles F. Manski
  4. Sensitivity Analysis In Semiparametric Likelihood Models
    Xiaohong Chen, Elie Tamer, and Alex Torgovitsky
  5. Specification Tests in Partially Identified Models defined by Moment Inequalities,
    Federico Bugni, Ivan A. Canay and Xiaoxia Shi
  6. Identification and Shape Restrictions in Nonparametric Instrumental Variables Estimation
    Joachim Freyberger and Joel L. Horowitz
  7. Nonparametric estimation of a heterogeneous demand function under the Slutsky inequality restriction,
    Richard Blundell, Joel L. Horowitz, and Matthias Parey
  8. A Simple Bootstrap Method for Constructing Confidence Bands for Functions,
    Peter Hall and Joel L. Horowitz
  9. Identification of Nonseparable Models with General Instruments
    Alex Torgovitsky