JOURNAL BROWSE
Search
Advanced SearchSearch Tips
New Bootstrap Method for Autoregressive Models
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
New Bootstrap Method for Autoregressive Models
Hwang, Eunju; Shin, Dong Wan;
  PDF(new window)
 Abstract
A new bootstrap method combined with the stationary bootstrap of Politis and Romano (1994) and the classical residual-based bootstrap is applied to stationary autoregressive (AR) time series models. A stationary bootstrap procedure is implemented for the ordinary least squares estimator (OLSE), along with classical bootstrap residuals for estimated errors, and its large sample validity is proved. A finite sample study numerically compares the proposed bootstrap estimator with the estimator based on the classical residual-based bootstrapping. The study shows that the proposed bootstrapping is more effective in estimating the AR coefficients than the residual-based bootstrapping.
 Keywords
Autoregressive model;stationary bootstrap;residual-based bootstrap;asymptotic property;
 Language
English
 Cited by
 References
1.
Bose, A. (1988). Edgeworth correction by bootstrap in autoregressions, Annals of Statistics, 16, 1709-1722. crossref(new window)

2.
Clements, M. P. and Kim, J. H. (2007). Bootstrap prediction intervals for autoregressive time series, Computational Statistics and Data Analysis, 51, 3580-3594. crossref(new window)

3.
Freedman, D. A. (1981). Bootstrapping regression models, Annals of Statistics, 9, 1218-1228. crossref(new window)

4.
Freedman, D. A. (1984). On bootstrapping two-stage least squares estimates in stationary linear models, Annals of Statistics, 12, 827-842. crossref(new window)

5.
Goncalves, S. and Kilian, L. (2004). Bootstrapping autoregressions with conditional heteroskedasticity of unknown form, Journal of Econometrics, 123, 89-120. crossref(new window)

6.
Goncalves, S. and Kilian, L. (2007). Asymptotic and bootstrap inference for AR(${\infty}$) processes with conditional heteroskedasticity, Econometric Reviews, 26, 609-641. crossref(new window)

7.
Grigoletto, M. (1998). Bootstrap prediction intervals for autoregressions: Some alternatives, International Journal of Forecasting, 14, 447-456. crossref(new window)

8.
Hwang, E. and Shin, D.W. (2011). Stationary bootstrapping for non-parametric estimator of nonlinear autoregressive model, Journal of Time Series Analysis, 32, 292-303. crossref(new window)

9.
Hwang, E. and Shin, D. W. (2012a). Strong consistency of the stationary bootstrap under $\psi$-weak dependence, Statistics and Probability Letters, 82, 488-495. crossref(new window)

10.
Hwang, E. and Shin, D. W. (2012b). Stationary bootstrap for kernel density estimators under $\psi$-weak dependence, Computational Statistics and Data Analysis, 56, 1581-1593. crossref(new window)

11.
Kabaila, P. (1993). On bootstrap predictive inference for autoregressive processes, Journal of Time Series Analysis, 14, 473-484. crossref(new window)

12.
Kim, J. H. (2004). Bias-correcting bootstrap prediction regions for vector autoregression, Journal of Forecasting, 23, 141-154. crossref(new window)

13.
Lahiri, S. N. (1999). On second-order properties of the stationary bootstrap method for studentized statistics, In: Asymptotic, Nonparametrics, and Time Series, (Eds. Ghosh, S.), Marcel Dekker, New York, 683-711.

14.
Nordman, D. J. (2009). A note on the stationary bootstrap's variance, Annals of Statistics, 37, 359-370. crossref(new window)

15.
Paparoditis, E. and Politis, D. N. (2005). Bootstrapping unit root tests for autoregressive time series, Journal of the American Statistical Association, 100, 545-553. crossref(new window)

16.
Parker, C., Paparoditis, E. and Politis, D. N. (2006). Unit root testing via the stationary bootstrap, Journal of Econometrics, 133, 601-638. crossref(new window)

17.
Pascual, L., Romo, J. and Ruiz, E. (2004). Bootstrap predictive inference for ARIMA processes, Journal of Time Series Analysis, 25, 449-465. crossref(new window)

18.
Patton, A., Politis, D. N. and White, H. (2009). Correction to "Automatic block-length selection for the dependent bootstrap" by D. Politis and H. White, Econometric Reviews, 28, 372-375. crossref(new window)

19.
Politis, D. N. (2003). The Impact of bootstrap methods on time series analysis, Statistical Science, 18, 219-230 crossref(new window)

20.
Politis, D. N. and Romano, J. P. (1994). The stationary bootstrap, Journal of the American Statistical Association, 89, 1303-1313. crossref(new window)

21.
Politis, D. N. and White, H. (2004). Automatic block-length selection for the dependent bootstrap, Econometric Reviews, 23, 53-70. crossref(new window)

22.
Swensen, A. R. (2003). Bootstrapping unit root tests for integrated processes, Journal of Time Series Analysis, 24, 99-126. crossref(new window)

23.
Thombs, L. A. and Schucany,W. R. (1990). Bootstrap prediction intervals for autoregression, Journal of the American Statistical Association, 95, 486-492.