Semiparametric Estimation in Time Series Regression with Long Range Dependence
We consider semiparametric estimation in time series regression in the presence of long range dependence in both the errors and the stochastic regressors. A central limit theorem is established for a class of semiparametric frequency domain weighted least squares estimates, which includes both narrow band ordinary least squares and narrow band generalized least squares as special cases. The estimates are semiparametric in the sense that focus is on the neighborhood of the origin, and only periodogram ordinates in a degenerating band around the origin are used. This setting differs from earlier work on time series regression with long range dependence where a fully parametric approach has been employed. The generalized least squares estimate is infeasible when the degree of long range dependence is unknown and must be estimated in an initial step. In that case, we show that a feasible estimate exists, which has the same asymptotic properties as the infeasible estimate. By Monte Carlo simulation, we evaluate the finite-sample performance of the generalized least squares estimate and the feasible estimate.
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- Carlos Velasco, 2003. "Gaussian Semi-parametric Estimation of Fractional Cointegration," Journal of Time Series Analysis, Wiley Blackwell, vol. 24(3), pages 345-378, 05.
- Hassler, Uwe & Marmol, Francesc & Velasco, Carlos, 2002.
"Residual Log-Periodogram Inference for Long-Run Relationships,"
Darmstadt Discussion Papers in Economics
115, Darmstadt University of Technology, Department of Law and Economics.
- Hassler, U. & Marmol, F. & Velasco, C., 2006. "Residual log-periodogram inference for long-run relationships," Journal of Econometrics, Elsevier, vol. 130(1), pages 165-207, January.
- Lobato, Ignacio N., 1999. "A semiparametric two-step estimator in a multivariate long memory model," Journal of Econometrics, Elsevier, vol. 90(1), pages 129-153, May.
- Lobato, I. & Robinson, P. M., 1996. "Averaged periodogram estimation of long memory," Journal of Econometrics, Elsevier, vol. 73(1), pages 303-324, July.
- Hannan, E. J., 1979. "The central limit theorem for time series regression," Stochastic Processes and their Applications, Elsevier, vol. 9(3), pages 281-289, December.
- Phillips, P.C.B., 1986.
"Understanding spurious regressions in econometrics,"
Journal of Econometrics,
Elsevier, vol. 33(3), pages 311-340, December.
- Peter C.B. Phillips, 1985. "Understanding Spurious Regressions in Econometrics," Cowles Foundation Discussion Papers 757, Cowles Foundation for Research in Economics, Yale University.
- Tsay, Wen-Jen & Chung, Ching-Fan, 2000. "The spurious regression of fractionally integrated processes," Journal of Econometrics, Elsevier, vol. 96(1), pages 155-182, May.
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