Non-stationary log-periodogram regression

Journal of Econometrics

Volumn 91, Issue 2, 1999, Pages 325-371

  Velasco, Carlos ^a  

^a UNIVERSIDAD CARLOS III DE MADRID   (Spain)

Author keywords

Log periodogram regression; Non stationary time series; Semiparametric inference; Tapering

Indexed keywords

EID: 0012713113     PISSN: 03044076     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0304-4076(98)00080-3     Document Type: Article

References (22)

1. Agiakloglou, C., Newbold, P., Wohar, M., 1993. Bias in an estimator of the fractional difference parameter. Journal of Time Series Analysis 14, 235-246.
2. Alekseev, V.G., 1996. Jackson- and Jackson-Vallée Poussin-type kernels and their probability applications. Theory of Probability and its Applications 41, 137-143.
3. Bloomfield, P., 1976. Fourier Analysis of Time Series: an Introduction. Wiley, New York.
4. Bloomfield P., 1991. Time series methods. In: Hinkley, D.V., Reid, N., Snell, E.J. (Eds.), Statistical Theory and Modeling. Chapman & Hall, London, pp. 152-176.
5. Dahlhaus, R., 1988. Small sample effects in time series analysis: a new asymptotic theory and a new estimate. Annals of Statistics 16, 808-841.
6. Durlauf, S., Phillips, P.C.B., 1988. Trends versus random walks in time series analysis. Econometrica 56, 1333-1354.
7. Geweke, J., Porter-Hudak, S., 1983. The estimation and application of long memory time series models. Journal of Time Series Analysis 4, 221-238.
8. Giraitis, L., Robinson, P.M., Samarov, A., 1997. Rate optimal semiparametric estimation of the memory parameter of the Gaussian time series with long range dependence. Journal of Time Series Analysis 18, 49-60.
9. Granger, C.W.J., 1966. The typical spectral shape of an economic variable. Econometrica 34, 150-161.
10. Hannan, E.J., 1970. Multiple Time Series. Wiley, New York.
11. Hassler, U., 1992. Unit root test: the autoregressive approach in comparison with the periodogram regression. Statistical Papers 34, 67-82.
12. Hurvich, C.M., Ray, B.K., 1995. Estimation of the memory parameter for nonstationary or noninvertible fractionally integrated processes. Journal of Time Series Analysis 16, 17-42.
13. Percival, D.B., Walden, A.T., 1993. Spectral Analysis for Physical Applications. Cambridge University Press, Cambridge.
14. Robinson, P.M., 1986. On the errors-in-variables problem for time series. Journal of Multivariate Analysis 19, 240-250.
15. Robinson P.M., 1992. Log-periodogram regression of time series with long range dependence. Preprint London School of Economics.
16. Robinson, P.M., 1994a. Rates of convergence and optimal spectral bandwidth for long range dependence. Probability Theory and Related Fields 99, 443-473.
17. Robinson, P.M., 1994b. Efficient tests of nonstationary hypotheses. Journal of the American Statistical Association 89, 1420-1437.
18. Robinson, P.M., 1995. Log-periodogram regression of time series with long range dependence. Annals of Statistics 23, 1048-1072.
19. Velasco, C., 1997. Non-Gaussian log-periodogram regression. Preprint.
20. Zhurbenko, I.G., 1979. On the efficiency of estimates of a spectral density. Scandinavian Journal of Statistics 6, 49-56.
21. Zhurbenko, I.G., 1980. On the efficiency of spectral estimates density estimators of a stationary process I. Theory of Probability and its Applications 6, 466-480.
22. Zhurbenko, I.G., 1982. On the efficiency of spectral estimates density estimators of a stationary process II. Theory of Probability and its Applications 8, 409-419.