Author:
Cuestas Juan Carlos,Gil-Alana Luis Alberiko
Abstract
AbstractThis paper examines the interaction between non-linear deterministic trends and long run dependence by means of employing Chebyshev time polynomials and assuming that the detrended series displays long memory with the pole or singularity in the spectrum occurring at one or more possibly non-zero frequencies. The combination of the non-linear structure with the long memory framework produces a model which is linear in parameters and therefore it permits the estimation of the deterministic terms by standard OLS-GLS methods. Moreover, the orthogonality property of Chebyshev’s polynomials makes them especially attractive to approximate non-linear structures of data. We present a procedure which allows us to test (possibly fractional) orders of integration at various frequencies in the presence of the Chebyshev trends with no effect on the standard limit distribution of the method. Several Monte Carlo experiments are conducted and the results indicate that the method performs well. An empirical application, using data of real exchange rates is also carried out at the end of the article.
Subject
Economics and Econometrics,Social Sciences (miscellaneous),Analysis,Economics and Econometrics,Social Sciences (miscellaneous),Analysis
Reference122 articles.
1. An Introduction to Long Memory Time Series and Fractional Differencing of;Granger;Journal Econometrics,1980
2. Seasonal Periodic Long Memory Model for Monthly River Flows Environmental Modelling and Software;Ooms,2001
3. Additional Evidence of Long - run Purchasing Power Parity with Restricted Structural Change of and;Papell;Journal Money Credit Banking,2006
4. Occasional Structural Breaks and Long Memory with an Application to the Absolute Stock Returns of Empirical;Granger;Journal Finance,2004
5. Testing for Higher Order Serial Correlation in Regression Equations when the Regressors Include Lagged Dependent Variables;Godfrey;Econometrica,1978
Cited by
52 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献