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Home | Events Archive | 12th Tinbergen Institute Conference: Inference Issues in Econometrics
TI Annual Conference

12th Tinbergen Institute Conference: Inference Issues in Econometrics

  • Speaker(s)
    Don Andrews (Yale University, United States), Isaiah Andrews (MIT, United States), Bertille Antoine (Simon Fraser University, Canada), Federico Bugni (Duke University, United States), Matias Cattaneo (University of Michigan, United States), et al.
  • Field
  • Location
    De Burcht, Henri Polaklaan 9, Amsterdam
  • Date and time

    May 19 2017, 09:00 until May 20 2017, 18:15

Statistical inference on the parameters of interest in a vast number of econometric models is plagued by its dependence on the settings of secondary nuisance parameters. Examples of such models are wide spread and include:

  1. Linear instrumental variables regression
  2. Inference in linear regression models after model selection
  3. Generalized method of moments
  4. Dynamic stochastic general equilibrium models
  5. Inference on parameters of large scale models with sparsity estimated by Lasso
  6. Dynamic panel data models
  7. Vector autoregressions with cointegration

These models are widely used by applied researchers. Inference on their parameters can be hampered by the value of underlying/secondary nuisance parameters. It was long thought that such settings of the nuisance parameters are unrealistic so they can basically be ignored for applied purposes. The empirical relevance of so-called weak instruments shows, however, that this is not the case. Weak instruments are a commonality in applied work so it is important to have inference methods that are robust to them. The same argument also applies to the other models stated above.

The conference brings together the leading researchers on inference issues in econometric models. During the two day meeting they present around twenty research papers on a variety of the above stated models.


In alphabetical order:

Name Affiliation Abstract
Don Andrews Yale University, United States A Note on Optimal Inference in the Linear IV Model
Isaiah Andrews MIT, United States Identification of and Correction for Publication Bias. Joint with Max Kasy
Bertille Antoine Simon Fraser University, Canada Identification-Robust Nonparametric Inference in a Linear IV Model
Otilia Boldea Tilburg University Bootstrapping Structural Change Tests
Federico Bugni Duke University, United States Regression-based Inference for Covariate-Adaptive Randomization with Multiple Treatments
Matias Cattaneo University of Michigan, United States Coverage Error Optimal Confidence Intervals for Regression Discontinuity Designs
Gregory Cox Yale University, United States Weak Identification in a Class of Generically Identified Models with an Application to Factor Models
Geert Dhaene University of Leuven, Belgium Second-order corrected Likelihood for Nonlinear Panel Models with Fixed Effects
Prosper Dovonon Concordia University, Canada Inference in Second-Order Identified Models
Jean-Marie Dufour McGill University, Canada Wald Tests of Nonlinear Hypotheses when Restrictions are Singular
Patrik Guggenberger The Pennsylvania State University, United States On the Subvector Anderson Rubin test in Linear IV Regression with conditional heteroskedasticity
Grant Hillier University of Southampton Nonparametric testing for exogeneity with discrete regressors and instruments
Michael Jansson University of California, Berkeley, United States Bootstrap-Based Inference for Cube Root Consistent Estimators
Philipp Ketz Paris School of Economics, France A Simple Solution to Invalid Inference in the Random Coeffcients Logit Model
Toru Kitagawa University College London, United Kingdom Uncertain Identification
Sophocles Mavroeidis Oxford University, United Kingdom
Adam McCloskey Brown University, United States Estimation and Inference with a (Nearly) Singular Jacobian
Marcelo Moreira Getúlio Vargas Foundation, Brazil Invariant Tests in the Instrumental Variable Model
Alexei Onatskiy Campbridge University, United Kingdom Alternative Asymptotics for Cointegration Tests in Large VARs
Anders Rahbek University of Copenhagen, Denmark Bootstrapping non-causal autoregressions: with applications to explosive bubble modelling
Kees Jan van Garderen University of Amsterdam Confidence Regions for Spatial Autoregressive Models
Tiemen Woutersen University of Arizona, United States Increasing the Power of Specification Tests

Organizing committee of the 12th Tinbergen Institute Conference: Inference Issues in Econometrics was:

TI fellows Peter Boswijk (University of Amsterdam) and Frank Kleibergen (University of Amsterdam).