ON THE ALTERNATIVE LONG-RUN VARIANCE RATIO TEST FOR A UNIT ROOT

DOI10.1017/S026646660606018XzbMath1125.62096OpenAlexW2161387031MaRDI QIDQ3409058

Mototsugu Shintani, Ye Cai

Publication date: 7 November 2006

Published in: Econometric Theory (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1017/s026646660606018x

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic properties of nonparametric inference (62G20) Monte Carlo methods (65C05)

Related Items (5)

A bootstrap bias correction of long run fourth order moment estimation in the CUSUM of squares test ⋮ Portmanteau-type tests for unit-root and cointegration ⋮ UNIT ROOT TESTS WITH WAVELETS ⋮ Portmanteau-type test for unit root with heavy-tailed noise ⋮ Testing for strict stationarity in a random coefficient autoregressive model

Cites Work

• Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation
• Size and power of tests of stationarity in highly autocorrelated time series
• Limiting power of unit-root tests in time-series regression
• Nonparametric tests for unit roots and cointegration.
• Determination of cointegrating rank in partially non‐stationary processes via a generalised von‐Neumann criterion
• Asymptotic Properties of Residual Based Tests for Cointegration
• Testing Residuals from Least Squares Regression for Being Generated by the Gaussian Random Walk
• On the Theory of Testing for Unit Roots in Observed Time Series
• A Simple, Positive Semi-Definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix
• Simple Robust Testing of Regression Hypotheses
• Time Series Regression with a Unit Root
• Useful Modifications to some Unit Root Tests with Dependent Errors and their Local Asymptotic Properties
• Efficient Tests for an Autoregressive Unit Root
• The Error in Rejection Probability of Simple Autocorrelation Robust Tests
• Heteroskedasticity-Autocorrelation Robust Standard Errors Using The Bartlett Kernel Without Truncation
• A simple cointegrating rank test without vector autoregression

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