Bootstrapping GMM estimators for time series

DOI10.1016/j.jeconom.2005.06.004zbMath1345.62124OpenAlexW2090021211MaRDI QIDQ275250

Mototsugu Shintani, Atsushi Inoue

Publication date: 25 April 2016

Published in: Journal of Econometrics (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/1803/15690

zbMATH Keywords

Edgeworth expansionsinstrumental variablesdependent datablock bootstrapasymptotic refinements

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Bootstrap, jackknife and other resampling methods (62F40) Non-Markovian processes: hypothesis testing (62M07)

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Uses Software

• nlmdl

Cites Work

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• Large Sample Properties of Generalized Method of Moments Estimators
• Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation
• Maximum likelihood and the bootstrap for nonlinear dynamic models
• The use of subseries values for estimating the variance of a general statistic from a stationary sequence
• Second-order correctness of the blockwise bootstrap for stationary observations
• The jackknife and the bootstrap for general stationary observations
• On Edgeworth expansion and moving block bootstrap for Studentized \(M\)-estimators in multiple linear regression models
• A Simple, Positive Semi-Definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix
• Asymptotic expansions for sums of weakly dependent random vectors
• An Improved Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimator
• ON STUDENTIZING AND BLOCKING METHODS FOR IMPLEMENTING THE BOOTSTRAP WITH DEPENDENT DATA
• Automatic Lag Selection in Covariance Matrix Estimation
• BIAS-CORRECTED NONPARAMETRIC SPECTRAL ESTIMATION
• Monetary Policy Rules and Macroeconomic Stability: Evidence and Some Theory*
• EQUIVALENCE OF THE HIGHER ORDER ASYMPTOTIC EFFICIENCY OF k-STEP AND EXTREMUM STATISTICS
• Unit Root Tests in ARMA Models with Data-Dependent Methods for the Selection of the Truncation Lag
• Bootstrap Critical Values for Tests Based on Generalized-Method-of-Moments Estimators
• Higher-Order Improvements of a Computationally Attractive k-Step Bootstrap for Extremum Estimators
• The bootstrap and Edgeworth expansion

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