Testing for Neglected Nonlinearity in Cointegrating Relationships
AbstractThis paper proposes pure significance tests for the absence of nonlinearity in cointegrating relationships. No assumption of the functional form of the nonlinearity is made. It is envisaged that the application of such tests could form the first step towards specifying a nonlinear cointegrating relationship for empirical modelling. The asymptotic and small sample properties of our tests are investigated, where special attention is paid to the role of nuisance parameters and a potential resolution using the bootstrap.
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Bibliographic InfoPaper provided by Queen Mary, University of London, School of Economics and Finance in its series Working Papers with number 508.
Date of creation: Feb 2004
Date of revision:
Cointegration; Nonlinearity; Neural networks; Bootstrap;
Find related papers by JEL classification:
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
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- Blake, Andrew P. & Kapetanios, George, 2000.
"A radial basis function artificial neural network test for ARCH,"
Elsevier, vol. 69(1), pages 15-23, October.
- Andrew P Blake & George Kapetanios, 1999. "A Radial Basis Function Artificial Neural Network Test for ARCH," NIESR Discussion Papers 154, National Institute of Economic and Social Research.
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