ASYMPTOTIC INFERENCES FOR AN AR(1) MODEL WITH A CHANGE POINT: STATIONARY AND NEARLY NON-STATIONARY CASES

ASYMPTOTIC INFERENCES FOR AN AR(1) MODEL WITH A CHANGE POINT: STATIONARY AND NEARLY NON-STATIONARY CASES

This article examines the asymptotic inference for AR(1) models with a possible structural break in the AR parameter β near the unity at an unknown time k0. Consider the model yt = β1yt − 1I{t ≤ k0} + β2yt − 1I{t > k0} + ϵt, t = 1,2, … ,T, where I{ ⋅ } denotes the indicator function. We examine t...

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Veröffentlicht in:Journal of time series analysis 2014-03, Vol.35 (2), p.133-150
Hauptverfasser: Pang, Tianxiao, Zhang, Danna, Chong, Terence Tai-Leung
Format: Artikel
Sprache:eng
Schlagworte:
AR model
change point
domain of attraction of the normal law
Estimation
Indicators
least squares estimator
limiting distribution
Mathematical models
Mathematics
Monte Carlo simulation
Random variables
Samples
Statistical analysis
Studies
Time series
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Zusammenfassung:This article examines the asymptotic inference for AR(1) models with a possible structural break in the AR parameter β near the unity at an unknown time k0. Consider the model yt = β1yt − 1I{t ≤ k0} + β2yt − 1I{t > k0} + ϵt, t = 1,2, … ,T, where I{ ⋅ } denotes the indicator function. We examine two cases: case I | β1 | 
ISSN:0143-9782
1467-9892
DOI:10.1111/jtsa.12055