Hybrid and Size-Corrected Subsample Methods
87 Pages Posted: 6 Mar 2007
Date Written: March 2007
Abstract
This paper considers the problem of constructing tests and confidence intervals (CIs) that have correct asymptotic size in a broad class of non-regular models. The models considered are non-regular in the sense that standard test statistics have asymptotic distributions that are discontinuous in some parameters. It is shown in Andrews and Guggenberger (2005a) that standard fixed critical value, subsample, and b < n bootstrap methods often have incorrect size in such models. This paper introduces general methods of constructing tests and CIs that have correct size. First, procedures are introduced that are a hybrid of subsample and fixed critical value methods. The resulting hybrid procedures are easy to compute and have correct size asymptotically in many, but not all, cases of interest. Second, the paper introduces size-correction and plug-in size-correction methods for fixed critical value, subsample, and hybrid tests. The paper also introduces finite-sample adjustments to the asymptotic results of Andrews and Guggenberger (2005a) for subsample and hybrid methods and employs these adjustments in size-correction.
The paper discusses several examples in detail. The examples are: (i) tests when a nuisance parameter may be near a boundary, (ii) CIs in an autoregressive model with a root that may be close to unity, and (iii) tests and CIs based on a post-conservative model selection estimator.
Keywords: Asymptotic size, Autoregressive model, b < n bootstrap, Finite-sample size, Hybrid test, Model selection, Over-rejection, Parameter near boundary, Size correction, Subsample confidence interval, Subsample test
JEL Classification: C12, C15
Suggested Citation: Suggested Citation
Do you have a job opening that you would like to promote on SSRN?
Recommended Papers
-
Inference in Incomplete Models
By Alfred Galichon and Marc Henry
-
Asymptotic Properties for a Class of Partially Identified Models
-
Inference for Parameters Defined by Moment Inequalities Using Generalized Moment Selection
-
Applications of Subsampling, Hybrid, and Size-Correction Methods
-
Set Identification in Models with Multiple Equilibria
By Alfred Galichon and Marc Henry
-
The Limit of Finite-Sample Size and a Problem With Subsampling
-
Bayesian and Frequentist Inference in Partially Identified Models
-
A Test of Non-Identifying Restrictions and Confidence Regions for Partially Identified Parameters
By Alfred Galichon and Marc Henry
-
Boosting Your Instruments: Estimation with Overidentifying Inequality Moment Conditions