Introduces random smoothing to produce asymptotically normal estimators and Wald confidence regions for linear regression with jointly stationary-ergodic errors without long-run variance estimation.
and West, Kenneth D
2 Pith papers cite this work. Polarity classification is still indexing.
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Self-normalized CUSUM-based tests for multistep conditional predictive ability avoid HAC estimation, deliver pivotal asymptotics, and show improved finite-sample size control in simulations.
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New Confidence Regions for Linear Regression Parameters with Stationary-Ergodic Dependent Errors
Introduces random smoothing to produce asymptotically normal estimators and Wald confidence regions for linear regression with jointly stationary-ergodic errors without long-run variance estimation.
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Self-normalized tests for multistep conditional predictive ability
Self-normalized CUSUM-based tests for multistep conditional predictive ability avoid HAC estimation, deliver pivotal asymptotics, and show improved finite-sample size control in simulations.