Higher‐Order Improvements of a Computationally Attractive k‐Step Bootstrap for Extremum Estimators

By Donald W. K. Andrews. 2002

221 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/5d64049ec92324e5374e42f51b3521ccae1ac9d4

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In Statistics and Probability

Citations in the corpus

Pseudo-likelihood estimation and bootstrap inference for structural discrete Markov decision models (2008, unknown): “ln( P,, f)(ai|xi). ( 8 ) Suppose that an initial consistent estimator of is available.8 The one-step NPL algorithm,”
Tests of Conditional Predictive Ability (2003, methodology): “, as in (1)), the use of out-of-sample testing involves an unnecessary loss of information, whereas the in-sample test of the same hypothesis utilizes all the information available and thus leads to power gains in finite samples.”
Nonparametric Bootstrap Procedures for Predictive Inference Based on Recursive Estimation Schemes (2007, background): “In fact, recentering is necessary, even for first-order validity, in the case of overidentified generalized method of moments (GMM) estimators (see e.g., Hall and Horowitz, 1996, Andrews, 2002, 2004, and Inoue and Shintani, 2006).”
Bootstrapping GMM estimators for time series (2003, methodology): “ Andrews (2002a) establishes the higher-order”
Bootstrap Hypothesis Testing (2007, methodology): “In theory, these methods frequently –18– offer higher-order accuracy than asymptotic methods, but the rate of improvement is generally quite small; see Hall, Horowitz, and Jing (1995) and Andrews (2002, 2004).”
BLOCK BOOTSTRAP HAC ROBUST TESTS: THE SOPHISTICATION OF THE NAIVE BOOTSTRAP (2011, background): “vide refinements have been established by G¨otze and K¨unsch (1996), Lahiri (1996), Andrews (2002)”
Information in the Revision Process of Real-Time Datasets (2008, unknown): “This is because for refinements it no longer suffices to merely mimic the first two sample moments when showing asymptotic validity, and the martingale difference assumption does not help for higher moments (see, e.g., Andrews 2002).”
Bootstrap Methods for Time Series (2003, methodology): “ Andrews (2002) gives the overlapping-blocks version of the statistic.”
Bootstrap Conditional Distribution Tests In the Presence of Dynamic Misspecification (2006, background): “For example, Hall and Horowitz (1996) and Andrews (2002) show that the block bootstrap provides improved critical values, in the sense of asymptotic refinement, for “studentized” GMM estimators and for tests of overidentifying restrictions, in the case where the covariance across moment conditions…”
A bootstrap procedure for panel data sets with many cross‐sectional units (2008, unknown): “We carry out cross sectional resampling, temporal resampling with a block structure where the block size is set to [T 1/4] as suggested by, e.g., Lahiri (2003) or Andrews (2002), and combined cross sectional and temporal resampling.”
Bootstrapping the Box–Pierce Q test: A robust test of uncorrelatedness (2006, methodology): “When a test statistic is asymptotically pivotal, the block bootstrap provides approximations that are more accurate than the approximations of first-order asymptotic theory under certain regularity conditions (Hall et al., 1995; Hall and Horowitz, 1996; Andrews, 2002).”
Predictive density and conditional confidence interval accuracy tests (2006, methodology): “For this reason, it is our objective in this paper to provide a conditional Kolmogorov test, in the spirit of Andrews (1997), that allows for the joint comparison of multiple misspecified conditional distribution models, for the case of dependent observations. In particular, assume that the object o”
Testing for Stochastic Dominance Efficiency (2010, background): “…the test statistic as discussed in Linton, Maasoumi, and Whang (2005) and the review paper of Härdle, Horowitz, and Kreiss (2003) (see also Hall and Horowitz 1996 and Andrews 2002 for a discussion of the need for recentering to avoid excessive bias in tests based on extremum estimators).”
Bootstrap Methods in Econometrics (2006, unknown): “However, the rate of improvement is generally quite small; see Hall et al. (1995) and Andrews (2002, 2004).”
Generalized Method of Moments and Macroeconomics (2002, methodology): “Optimal rates and plug-in rules for h were derived by Andrews (1991) and Newey and West (1994).”