ASYMPTOTIC SIZE AND A PROBLEM WITH SUBSAMPLING AND WITH THE m OUT OF n BOOTSTRAP

By Donald W. K. Andrews, Patrik Guggenberger. Econometric Theory, 2009

167 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/25c54b76f056624f01f23605a97c2239d8fa489e

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Citations in the corpus

ON THE ASYMPTOTIC SIZE DISTORTION OF TESTS WHEN INSTRUMENTS LOCALLY VIOLATE THE EXOGENEITY ASSUMPTION (2011, methodology): “Andrews and Guggenberger (2010a) show that a t-test using subsampling critical values has “almost” correct asymptotic size and provide sizecorrected and hybrid critical values based on the theory developed in Andrews and Guggenberger (2009a).”
Incorrect asymptotic size of subsampling procedures based on post-consistent model selection estimators (2009, methodology): “Samworth (2003) provides simulation results and heuristics indicating that the m out of n bootstrap does not provide a good approximation to the distribution of a shrinkage estimator.”
Generic results for establishing the asymptotic size of confidence sets and tests (2020, background): “For example, this 29 is the case in all of the examples considered in Andrews and Guggenberger (2009a, 2010a, 2009b).”
On the uniform asymptotic validity of subsampling and the bootstrap (2012, background): “27 62 v2 [ m at h. ST ] 1 8 Fe b 20 13 The Annals of Statistics 2012, Vol. 40, No. 6, 2798–2822 DOI: 10.1214/12-AOS1051 c© Institute of Mathematical Statistics, 2012”
Bootstrap Methods in Econometrics (2018, unknown): “4 method consistently estimates this distribution. The nonreplacement subsampling method also - consistently estimates asymptotic critical values for T n and asymptotic confidence intervals for t n . Andrews and Guggenberger (2010) show that nonreplacement subsampling is not - uniformly consistent i”
Bonferroni-Based Size-Correction for Nonstandard Testing Problems (2017, unknown): “For example, Andrews and Guggenberger (2010b) illustrate that when examining lower one-sided tests, the limit of the test statistic Wh is stochastically decreasing (increasing) in h1 for h2 0 (h2 ≥ 0).”
The validity of instruments revisited (2012, methodology): “This is the same near exogeneity assumption used by Berkowitz et al. (2008) in which the covariance between the structural error and the instruments is ‘‘C/ √ n’’ and where C is a constant vector.”
Weak Identification in Fuzzy Regression Discontinuity Designs (2016, methodology): “This idea can be formalized using the results obtained in the recent literature on uniform size properties of tests and confidence sets: Andrews and Guggenberger (2010), Andrews and Cheng (2012), and Andrews, Cheng, and Guggenberger (2011).”
Inference Based on Conditional Moment Inequalities (2013, methodology): “The results of the paper for CS s imply that this test has asymptotic size less than or equal to (with the inequality possibly being strict), e.g., see Andrews and Guggenberger (2009) for details of the argument.”
Select the Valid and Relevant Moments: An Information-Based LASSO for GMM with Many Moments (2013, methodology): “This is related to the post model selection inference problem investigated by Leeb and Pötscher (2005, 2008), Andrews and Guggenberger (2009, 2010), Guggenberger (2010), Belloni, Chernozhukov, and Hansen (2011), and McCloskey (2012), among others.”
The impact of a Hausman pretest on the size of a hypothesis test: The panel data case (2010, methodology): “For example, Blonigen (1997) justies the use of random e¤ects inference based on a Hausman pretest while Hastings (2004) uses xed e¤ects inference as a result of the Hausman pretest rejecting the random e¤ects specication.”