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The least-squares criteria of the random coefficient dynamic regression model

Author(s)
Araveeporn, Autcha
Date Issued
June 1, 2012
Type
Article
DOI
10.1080/15598608.2012.673891
Abstract
The random coefficient dynamic regression (RCDR) model develops from random coefficient autoregressive (RCA) model and autoregressive (AR) model. The RCDR model is considered by adding exogenous variables. In this article, the concept of the least-squares (LS) criterion is used to estimate the parameter on the RCDR model. Simulation results have shown that the proposed coefficient of the AR model provided asymptotically unbiased estimates nearly for most of the six data-generating models. The RCDR model is then applied to a series of daily observations of the exchange rate of Baht/GBP and Baht/EUR to illustrate the methodology. The predictions of LS criteria are used with those obtained on 20 hold-out future values of withheld observations. Copyright © Grace Scientific Publishing, LLC.
Citation
Journal of Statistical Theory and Practice, 6(2), 315-333, 2012
Subjects

Autoregressive

Least-squares criteri...

Random coefficient dy...

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