Cointegrating rank selection in models with time-varying variance

DOI10.1016/J.JECONOM.2012.01.022zbMath1443.62246OpenAlexW3121292107MaRDI QIDQ527990

Xu Cheng, Peter C. B. Phillips

Publication date: 12 May 2017

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

Full work available at URL: https://ink.library.smu.edu.sg/soe_research/1833

zbMATH Keywords

model selectionheterogeneityinformation criteriacointegrating ranktime varying variances

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)

Related Items (11)

Forecasting cointegrated nonstationary time series with time-varying variance ⋮ ADAPTIVE LONG MEMORY TESTING UNDER HETEROSKEDASTICITY ⋮ Forecasting vector autoregressions with mixed roots in the vicinity of unity ⋮ DETERMINING THE COINTEGRATION RANK IN HETEROSKEDASTIC VAR MODELS OF UNKNOWN ORDER ⋮ Asymptotic theory for near integrated processes driven by tempered linear processes ⋮ Extreme canonical correlations and high-dimensional cointegration analysis ⋮ REPRESENTATION OF I(1) AND I(2) AUTOREGRESSIVE HILBERTIAN PROCESSES ⋮ Adaptive estimation of heteroskedastic functional-coefficient regressions with an application to fiscal policy evaluation on asset markets ⋮ On asymptotic risk of selecting models for possibly nonstationary time-series ⋮ Lag length selection in panel autoregression ⋮ Bootstrap score tests for fractional integration in heteroskedastic ARFIMA models, with an application to price dynamics in commodity spot and futures markets

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Residual log-periodogram inference for long-run relationships
• Determining the cointegrating rank in nonstationary fractional systems by the exact local Whittle approach
• Adaptive estimation of autoregressive models with time-varying variances
• Testing for unit roots in time series models with non-stationary volatility
• Statistical analysis of cointegration vectors
• Testing for a unit root in the presence of a variance shift
• Modeling by shortest data description
• On predictive least squares principles
• Asymptotics for linear processes
• Estimating the dimension of a model
• Model selection in partially nonstationary vector autoregressive processes with reduced rank structure
• Testing for covariance stationarity in stock market data
• Unit root tests with a break in innovation variance.
• Exact local Whittle estimation of fractional integration
• Unit Root Tests under Time-Varying Variances
• STATIONARITY TESTS UNDER TIME-VARYING SECOND MOMENTS
• Semiparametric cointegrating rank selection
• Inference in Autoregression under Heteroskedasticity
• Likelihood-Based Inference in Cointegrated Vector Autoregressive Models
• Time Series Regression with a Unit Root
• Fully Modified Least Squares and Vector Autoregression
• Econometric Model Determination
• An Asymtotic Theory of Bayesian Inference for Time Series

This page was built for publication: Cointegrating rank selection in models with time-varying variance