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The Economic Research Institute, Stockholm School of Economics SSE/EFI Working Paper Series in Economics and Finance

No 386:
Diagnostic Checking in a Flexible Nonlinear Time Series Model

Marcelo Medeiros () and Alvaro Veiga ()

Abstract: This paper considers a sequence of misspecification tests for a flexible nonlinear time series model. The model is a generalization of both the Smooth Transition AutoRegressive (STAR) and the AutoRegressive Artificial Artificial Neural Network (AR-ANN) models. The tests are Lagrange multiplier (LM) type tests of parameter constancy against the alternative of smoothly changing ones, of serial independence, and constant variance of the error term against the hypothesis that the variance smoothly changes between regimes. The small sample behaviour of the proposed tests is evaluated throw a Monte-Carlo study and the results show that the tests have size close to the nominal one and a good power.

Keywords: Time series; nonlinear models; STAR models; neural networks; statistical inference; parameter constancy; serial independence; heteroscedasticity; misspecification; (follow links to similar papers)

JEL-Codes: C22; C51; (follow links to similar papers)

24 pages, June 6, 2000, Revised January 15, 2001

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This paper is published as:
Medeiros, Marcelo and Alvaro Veiga, (2003), 'Diagnostic Checking in a Flexible Nonlinear Time Series Model', Journal of Time Series Analysis, Vol. 24, July, No. 4, pages 461-482



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