Improved Tests for Forecast Comparisons in the Presence of Instabilities

DOI10.1111/JTSA.12179zbMath1396.62213OpenAlexW2505943376MaRDI QIDQ2817311

Pierre Perron, Luis F. Martins

Publication date: 30 August 2016

Published in: Journal of Time Series Analysis (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/10071/12874

zbMATH Keywords

structural changelong-run varianceforecastsnon-monotonic power

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Economic time series analysis (91B84) Markov processes: hypothesis testing (62M02)

Related Items (5)

GENERALIZED LAPLACE INFERENCE IN MULTIPLE CHANGE-POINTS MODELS ⋮ Theory of evolutionary spectra for heteroskedasticity and autocorrelation robust inference in possibly misspecified and nonstationary models ⋮ Simultaneous bandwidths determination for DK-HAC estimators and long-run variance estimation in nonparametric settings ⋮ Continuous record Laplace-based inference about the break date in structural change models ⋮ Moderate deviations for quantile regression processes

Cites Work

• Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation
• Assessing the relative power of structural break tests using a framework based on the approximate Bahadur slope
• Tests for Parameter Instability and Structural Change With Unknown Change Point
• Estimating and Testing Linear Models with Multiple Structural Changes
• The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis
• Asymptotic Inference about Predictive Ability
• Tests of Conditional Predictive Ability
• Tests of equal forecast accuracy and encompassing for nested models

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