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On the Performance of RESET and Durbin Watson Tests in Detecting Specification Error

Babatunde, O. S. and Oguntunde, P.E. and Ogunmola, A.O and Balogun, O. S. (2014) On the Performance of RESET and Durbin Watson Tests in Detecting Specification Error. Copyright © 2014 by Modern Scientific Press Company, Florida, USA International Journal of Modern Mathematical Sciences,, 11 (3). pp. 144-151. ISSN 2166-286X

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When a model is created which correctly leaves out one or more important variables, one rarely know which test has the highest power for detecting the associated specification error. This research adopts the use of bootstrapping experiment. The models investigated consist of three omitted variables which have a coefficient that varies from 0.1 through 1 and 2. A bootstrap simulation approach was used to generate data for each of the models at different sample sizes (n) 20, 30, 50, and 80 respectively, each with 100 replications(r). For the models considered, the experiment reveals that the Ramsey Regression Equation Specification Error Test (RESET test) is more efficient than that of Durbin-Watson test in detecting the error of omitted variable in specification error.

Item Type: Article
Uncontrolled Keywords: Bootstrap, Error, Regression, Simulation, Specification, RESET
Subjects: Q Science > Q Science (General)
Q Science > QA Mathematics
Divisions: Faculty of Engineering, Science and Mathematics > School of Mathematics
Depositing User: Mrs Hannah Akinwumi
Date Deposited: 01 Mar 2016 10:56
Last Modified: 01 Mar 2016 10:56

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