Estimating multiple breaks in nonstationary autoregressive models
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Publication:2225018
DOI10.1016/j.jeconom.2020.06.005zbMath1464.62390OpenAlexW2914030703MaRDI QIDQ2225018
Lingjie Du, Terence Tai-Leung Chong, Tian-Xiao Pang
Publication date: 4 February 2021
Published in: Journal of Econometrics (Search for Journal in Brave)
Full work available at URL: https://mpra.ub.uni-muenchen.de/92074/1/MPRA_paper_92074.pdf
Applications of statistics to economics (62P20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to actuarial sciences and financial mathematics (62P05)
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Uses Software
Cites Work
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- Modified tests for a change in persistence
- Limit theory for moderate deviations from a unit root
- Ratio-based estimators for a change point in persistence
- Asymptotic inference for nearly nonstationary AR(1) processes
- Partial parameter consistency in a misspecified structural change model
- High-dimensional change-point detection under sparse alternatives
- STRUCTURAL CHANGE IN AR(1) MODELS
- WALD TESTS FOR DETECTING MULTIPLE STRUCTURAL CHANGES IN PERSISTENCE
- Dating the timeline of financial bubbles during the subprime crisis
- On Asymptotic Distributions of Estimates of Parameters of Stochastic Difference Equations
- Towards a unified asymptotic theory for autoregression
- Estimating and Testing Linear Models with Multiple Structural Changes
- FINANCIAL BUBBLE IMPLOSION AND REVERSE REGRESSION
- STRUCTURAL CHANGE IN NONSTATIONARY AR(1) MODELS
- High Dimensional Change Point Estimation via Sparse Projection
- Change Point Estimation in High Dimensional Markov Random-Field Models
- Multiple-Change-Point Detection for High Dimensional Time Series via Sparsified Binary Segmentation
- The Lasso for High Dimensional Regression with a Possible Change Point
- Multiple-Change-Point Detection for Auto-Regressive Conditional Heteroscedastic Processes
- TESTING FOR MULTIPLE BUBBLES: HISTORICAL EPISODES OF EXUBERANCE AND COLLAPSE IN THE S&P 500
- TESTING FOR MULTIPLE BUBBLES: LIMIT THEORY OF REAL‐TIME DETECTORS
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