Abstract
In this paper, we propose a hybrid bootstrap procedure for augmented Dickey-Fuller (ADF) tests for the presence of a unit root. This hybrid proposal combines a time domain parametric autoregressive fit to the data and a nonparametric correction applied in the frequency domain to capture features that are possibly not represented by the parametric model. It is known that considerable size and power problems can occur in small samples for unit root testing in the presence of an MA parameter using critical values of the asymptotic Dickey-Fuller distribution. The benefit of the sieve bootstrap in this situation has been investigated by Chang and Park (J Time Ser Anal 24:379–400, 2003). They showed asymptotic validity as well as substantial improvements for small sample sizes, but the actual sizes of their bootstrap tests were still quite far away from the nominal size. The finite sample performances of our procedure are extensively investigated through Monte Carlo simulations and compared to the sieve bootstrap approach. Regarding the size of the tests, our results show that the hybrid bootstrap remarkably outperforms the sieve bootstrap.
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References
Akaike, H (1973) Information theory and an extension of the maximum likelihood principle. In: Petrov BN, Csáki F (eds) Proceedings of the 2nd International Symposium on Information Theory, Akademiai Kaido, Budapest, pp 267–281
Beltrão KI, Bloomfield P (1987) Determining the bandwidth of a kernel spectrum estimate. J Time Ser Anal 8: 21–38
Bühlmann P (1997) Sieve bootstrap for time series. Bernoulli 3: 48–123
Bühlmann P (1998) Sieve bootstrap for smoothing in nonstationary time series. Ann Stat 26: 48–83
Chang Y, Park JY (2003) A sieve bootstrap for the test of a unit root. J Time Ser Anal 24: 379–400
Dahlhaus R, Janas D (1996) A frequency domain bootstrap for ratio statistics in time series analysis. Ann Stat 24: 1934–1963
Davidson R, MacKinnon JG (1998) Graphical methods for investigating the size and power of test statistics. Manch Sch 66: 1–26
Dickey DA, Fuller WA (1979) Distribution of estimators for autoregressive time series with a unit root. J Am Stat Assoc 74: 427–431
Dickey DA, Fuller WA (1981) Likelihood ratio statistics for autoregressive time series with a unit root. Econometrica 49: 1057–1072
Efron B (1979) Bootstrap methods: another look at the jackknife. Ann Stat 20(1): 121–145
Franke J, Härdle W (1992) On Bootstrapping kernel spectral estimates. Ann Stat 2: 121–145
Fuller WA (1996) Introduction to statistical time series, 2nd (edn). Wiley, New York
Hall P, Horowitz JL (1996) Bootstrap critical values for tests based on generalized method of moments estimators with dependent data. Econometrica 64: 891–916
Jentsch C, Kreiss J-P (2010) The multiple hybrid bootstrap—resampling multivariate linear processes. J Multivar Anal 101: 2320–2345
Kreiss J-P (1998) Assymptotical Inference for a Class of Stochastic Processes. Habilitationsschrift, Universität Hamburgm
Kreiss J-P (1992) Bootstrap procedures for AR(∞) processes. In: Jöckel KH, Rothe G, Senders W (eds) Bootstrapping and related techniques, lecture notes in economics and mathematical systems 376, Heidelberg, Springer
Kreiss J-P, Paparoditis E (2003) Autoregressive-aided periodogram bootstrap for time series. Ann Stat 31(6): 1923–1955
Künsch HR (1989) The jackknife and the bootstrap for general stationary observations. Ann Stat 17: 1217–1241
Paparoditis E (2002) Frequency domain bootstrap for time series. In: Dehling H, Mikosch T, Sorensen M (eds) Empirical process techniques for dependent data. Birkhäuser, Boston, pp 365–381
Paparoditis E, Politis DN (1999) The local bootstrap for the periodogram. J Time Ser Anal 20: 193–222
Paparoditis E, Politis DN (2001) Tapered block bootstrap. Biometrika 88: 19–1105
Paparoditis E, Politis DN (2001) The tapered block bootstrap for general statistics from stationary sequences. Econom J 5: 48–131
Paparoditis E, Politis DN (2003) Residual-based block bootstrap for unit root testing. Econometrica 71: 813–855
Psaradakis Z (2001) Bootstrap tests for an autoregressive unit root in the presence of weakly dependent errors. J Time Ser Anal 22: 577–594
Said SE, Dickey DA (1984) Testing for unit roots in autoregressive-moving average models of unknown order. Biometrika 71: 599–608
Schwert GW (1989) Tests for unit roots: a Monte Carlo investigation. J Bus Econ Stat 7: 5–17
Swensen AR (2003) Bootstrapping unit root tests for integrated processes. J Time Ser Anal 24: 99–126
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Jentsch, C., Kreiss, JP., Mantalos, P. et al. Hybrid bootstrap aided unit root testing. Comput Stat 27, 779–797 (2012). https://doi.org/10.1007/s00180-011-0290-0
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DOI: https://doi.org/10.1007/s00180-011-0290-0