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  Alternative approaches to testing non-nested models with autocorrelated disturbances
 
 
Title: Alternative approaches to testing non-nested models with autocorrelated disturbances
Author: McAleer, Michael
Pesaran, M. Hashem
Bera, Anil K.
Appeared in: Communications in statistics
Paging: Volume 19 (1990) nr. 10 pages 3619-3644
Year: 1990
Contents: 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.
Publisher: Taylor & Francis
Source file: Elektronische Wetenschappelijke Tijdschriften
 
 

                             Details for article 2 of 29 found articles
 
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