@article{eprints6284,
          number = {3},
         journal = {Copyright {\copyright} 2014 by Modern Scientific Press Company, Florida, USA International Journal of Modern Mathematical Sciences,},
           pages = {144--151},
            year = {2014},
          volume = {11},
           title = {On the Performance of RESET and Durbin Watson Tests in
Detecting Specification Error},
       publisher = {Modern Scientific Press Company},
          author = {O. S. Babatunde and P.E. Oguntunde and A.O Ogunmola and O. S. Balogun},
        abstract = {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.},
        keywords = {Bootstrap, Error, Regression, Simulation, Specification, RESET},
             url = {http://eprints.covenantuniversity.edu.ng/6284/}
}