Improved forecasting of autoregressive series by weighted least squares approximate REML estimation

Rohit S. Deo

International Journal of Forecasting, 2012, vol. 28, issue 1, 39-43

Abstract: Restricted maximum likelihood (REML) estimation has recently been shown to provide less biased estimates in autoregressive series. A simple weighted least squares approximate REML procedure has been developed that is particularly useful for vector autoregressive processes. Here, we compare the forecasts of such processes using both the standard ordinary least squares (OLS) estimates and the new approximate REML estimates. Forecasts based on the approximate REML estimates are found to provide a significant improvement over those obtained using the standard OLS estimates.

Keywords: Forecast error; Autoregressive; REML; OLS (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:intfor:v:28:y:2012:i:1:p:39-43

DOI: 10.1016/j.ijforecast.2011.02.014

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