Should we go one step further? An accurate comparison of one-step and two-step procedures in a generalized method of moments framework
DOI10.1016/J.JECONOM.2018.07.006zbMath1452.62649OpenAlexW1668294501WikidataQ129211263 ScholiaQ129211263MaRDI QIDQ1739594
Publication date: 26 April 2019
Published in: Journal of Econometrics (Search for Journal in Brave)
Full work available at URL: https://escholarship.org/uc/item/58r2z98m
nonstandard asymptoticsfixed-smoothing asymptoticsasymptotic mixed normalityheteroskedasticity and autocorrelationtwo-step GMM estimation
Applications of statistics to economics (62P20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic properties of nonparametric inference (62G20)
Related Items (5)
Cites Work
- Large Sample Properties of Generalized Method of Moments Estimators
- Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation
- Fixed-smoothing asymptotics in the generalized empirical likelihood estimation framework
- A theory of robust long-run variance estimation
- Fixed-smoothing asymptotics for time series
- A fixed-bandwidth view of the pre-asymptotic inference for kernel smoothing with time series data
- Robustifying multivariate trend tests to nonstationary volatility
- Inference with dependent data using cluster covariance estimators
- Heteroskedasticity, autocorrelation, and spatial correlation robust inference in linear panel models with fixed-effects
- Should we go one step further? An accurate comparison of one-step and two-step procedures in a generalized method of moments framework
- Finite sample properties of tests based on prewhitened nonparametric covariance estimators
- Heteroskedasticity and spatiotemporal dependence robust inference for linear panel models with fixed effects
- Sieve inference on possibly misspecified semi-nonparametric time series models
- Let's fix it: fixed-\(b\) asymptotics versus small-\(b\) asymptotics in heteroskedasticity and autocorrelation robust inference
- FIXED-b ASYMPTOTICS FOR SPATIALLY DEPENDENT ROBUST NONPARAMETRIC COVARIANCE MATRIX ESTIMATORS
- ON SIZE AND POWER OF HETEROSKEDASTICITY AND AUTOCORRELATION ROBUST TESTS
- t-Statistic Based Correlation and Heterogeneity Robust Inference
- THE MOVING BLOCKS BOOTSTRAP FOR PANEL LINEAR REGRESSION MODELS WITH INDIVIDUAL FIXED EFFECTS
- A NEW ASYMPTOTIC THEORY FOR HETEROSKEDASTICITY-AUTOCORRELATION ROBUST TESTS
- OPTIMAL BANDWIDTH SELECTION FOR ROBUST GENERALIZED METHOD OF MOMENTS ESTIMATION
- A Simple, Positive Semi-Definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix
- Simple Robust Testing of Regression Hypotheses
- Fixed-Smoothing Asymptotics in a Two-Step Generalized Method of Moments Framework
- A Self-Normalized Approach to Confidence Interval Construction in Time Series
- HETEROSKEDASTICITY-AUTOCORRELATION ROBUST TESTING USING BANDWIDTH EQUAL TO SAMPLE SIZE
- A heteroskedasticity and autocorrelation robustFtest using an orthonormal series variance estimator
- BLOCK BOOTSTRAP HAC ROBUST TESTS: THE SOPHISTICATION OF THE NAIVE BOOTSTRAP
- Optimal Bandwidth Selection in Heteroskedasticity–Autocorrelation Robust Testing
- The Error in Rejection Probability of Simple Autocorrelation Robust Tests
- Heteroskedasticity-Autocorrelation Robust Standard Errors Using The Bartlett Kernel Without Truncation
- HAC ESTIMATION BY AUTOMATED REGRESSION
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