Alternative approaches to testing non-nested models with autocorrelated disturbances

Abstract
Since departures from the classical assumptions regarding the disturbances in a linear tegression model arise frequently in empirical application, deveral computationally Straightforward procedutes are presented in this paper for testiog non-nested models when the disturbances of these models follow first- or higher-order autoregressive processes. Anempirical example is used to illustrate how the procedures may be used to test competing Keynesian and New Classical non-nested models of unemployment for the U.S using annual time series data for 1955-85.