Oracle Efficient Estimation of Structural Breaks in Cointegrating Regressions
From MaRDI portal
Publication:5030952
DOI10.1111/jtsa.12593zbMath1493.62073arXiv2001.07949OpenAlexW3159329005MaRDI QIDQ5030952
Publication date: 18 February 2022
Published in: Journal of Time Series Analysis (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2001.07949
Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Ridge regression; shrinkage estimators (Lasso) (62J07) Asymptotic distribution theory in statistics (62E20) Economic time series analysis (91B84)
Related Items
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Penalized methods for bi-level variable selection
- The Adaptive Lasso and Its Oracle Properties
- A Simple Estimator of Cointegrating Vectors in Higher Order Integrated Systems
- The limit distribution of the estimates in cointegrated regression models with multiple structural changes
- Consistent group selection in high-dimensional linear regression
- Model selection by LASSO methods in a change-point model
- A novel and fast methodology for simultaneous multiple structural break estimation and variable selection for nonstationary time series models
- Consistencies and rates of convergence of jump-penalized least squares estimators
- A note on adaptive group Lasso
- On stepwise pattern recovery of the fused Lasso
- Testing for common breaks in a multiple equations system
- Multiple change-point detection: a selective overview
- Residual-based tests for cointegration in models with regime shifts
- Cointegration tests in the presence of structural breaks
- Testing for structural breaks in cointegrated relationships
- Does modeling a structural break improve forecast accuracy?
- Simultaneous analysis of Lasso and Dantzig selector
- Tests for cointegration with structural breaks based on subsamples
- High-dimensional graphs and variable selection with the Lasso
- Testing for cointegration with threshold adjustment in the presence of structural breaks
- CONSISTENT AND CONSERVATIVE MODEL SELECTION WITH THE ADAPTIVE LASSO IN STATIONARY AND NONSTATIONARY AUTOREGRESSIONS
- Inflation and Welfare
- Structural breaks in time series
- Shrinkage Tuning Parameter Selection with a Diverging number of Parameters
- SHRINKAGE ESTIMATION OF REGRESSION MODELS WITH MULTIPLE STRUCTURAL CHANGES
- Testing for Multiple Structural Changes in Cointegrated Regression Models
- Tests for Parameter Instability and Structural Change With Unknown Change Point
- New Improved Tests for Cointegration with Structural Breaks
- A group bridge approach for variable selection
- Testing For and Dating Common Breaks in Multivariate Time Series
- Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
- Estimating and Testing Linear Models with Multiple Structural Changes
- Penalized estimation of high-dimensional models under a generalized sparsity cindition
- Group LASSO for Structural Break Time Series
- Multiple Change-Point Estimation With a Total Variation Penalty
- A mixture‐distribution factor model for multivariate outliers
- Model Selection and Estimation in Regression with Grouped Variables
- Testing for the Null Hypothesis of Cointegration with a Structural Break
- Estimating and Testing Structural Changes in Multivariate Regressions
- Consistent two‐stage multiple change‐point detection in linear models
- Structural Break Estimation for Nonstationary Time Series Models
- Inference on locally ordered breaks in multiple regressions