Bootstrap prediction intervals for autoregression using asymptotically mean-unbiased estimators
Article Abstract:
Extensive Monte Carlo experiments are conducted by using a number of stationery and near unit-root autoaggressive (AR) models. It was found that bias-correction based on asymptotically mean-unbiased estimation substantially improves small sample properties of bootstrap prediction intervals.
Publication Name: International Journal of Forecasting
Subject: Economics
ISSN: 0169-2070
Year: 2004
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Forecasting using the trend model with autoregressive errors
Article Abstract:
A method for forecasting time series generated by the linear trend model with autoregressive errors, allowing a possible unit root (UR), is presented.
Publication Name: International Journal of Forecasting
Subject: Economics
ISSN: 0169-2070
Year: 2005
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Forecasting autoregressive time series with bas-corrected parameter estimators
Article Abstract:
While all the bias-removing techniques examined offer improvement to forecasts, bootstrapping is found to deliver the best results.
Publication Name: International Journal of Forecasting
Subject: Economics
ISSN: 0169-2070
Year: 2003
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