Long run variance estimation and robust regression testing using sharp origin kernels with no truncation
DOI10.1016/j.jspi.2006.06.033zbMath1104.62099OpenAlexW2164622888MaRDI QIDQ866643
Peter C. B. Phillips, Sainan Jin, Yixiao Sun
Publication date: 14 February 2007
Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)
Full work available at URL: https://ink.library.smu.edu.sg/soe_research/318
tablespower parameterlong run variancedata-determined kernel estimationheteroscedasticity and autocorrelation consistent standard errorsharp origin kernel
Applications of statistics to economics (62P20) Estimation in multivariate analysis (62H12) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic properties of nonparametric inference (62G20) Linear regression; mixed models (62J05) Hypothesis testing in multivariate analysis (62H15) Robustness and adaptive procedures (parametric inference) (62F35) Inference from stochastic processes and spectral analysis (62M15)
Related Items (14)
Cites Work
- A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity
- Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation
- Asymptotics for linear processes
- Higher-order approximations for frequency domain time series regression
- Higher order approximations for Wald statistics in time series regressions with integrated processes.
- Gaussian semiparametric estimation of long range dependence
- On Consistent Estimates of the Spectrum of a Stationary Time Series
- A NEW ASYMPTOTIC THEORY FOR HETEROSKEDASTICITY-AUTOCORRELATION ROBUST TESTS
- Fixed-b asymptotic approximation of the sampling behaviour of nonparametric spectral density estimators
- A Simple, Positive Semi-Definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix
- An Improved Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimator
- Consistent Covariance Matrix Estimation for Dependent Heterogeneous Processes
- Automatic Lag Selection in Covariance Matrix Estimation
- Consistency of Kernel Estimators of Heteroscedastic and Autocorrelated Covariance Matrices
- Simple Robust Testing of Regression Hypotheses
- EDGEWORTH EXPANSIONS FOR SPECTRAL DENSITY ESTIMATES AND STUDENTIZED SAMPLE MEAN
- HETEROSKEDASTICITY-AUTOCORRELATION ROBUST TESTING USING BANDWIDTH EQUAL TO SAMPLE SIZE
- Second Order Approximation in the Partially Linear Regression Model
- The Error in Rejection Probability of Simple Autocorrelation Robust Tests
- Heteroskedasticity-Autocorrelation Robust Standard Errors Using The Bartlett Kernel Without Truncation
- A CONVERGENT t-STATISTIC IN SPURIOUS REGRESSIONS
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
This page was built for publication: Long run variance estimation and robust regression testing using sharp origin kernels with no truncation