We propose a test for neglected nonlinearity that uses an artificial neural network. We use radial basis functions for the `hidden layer' with basis function centers and radii chosen from the sample data set and selected on the basis of information criteria. The procedure is straightforward to implement and out-performs the random network test proposed by Lee, White, and Granger (1993).
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Paper provided by National Institute of Economic and Social Research in its series NIESR Discussion Papers with number
153.