arXiv 14 Feb 2018 · Econometrics · publishedEconometric Theory (2018) · 2 citations (OpenAlex)
arXiv:1802.05333 · PDF · DOI · OpenAlex · Extracted main text
In unit root testing, a piecewise locally stationary process is adopted to accommodate nonstationary errors that can have both smooth and abrupt changes in second- or higher-order properties. Under this framework, the limiting null distributions of the conventional unit root test statistics are derived and shown to contain a number of unknown parameters. To circumvent the difficulty of direct consistent estimation, we propose to use the dependent wild bootstrap to approximate the non-pivotal limiting null distributions and provide a rigorous theoretical justification for bootstrap consistency. The proposed method is compared through finite sample simulations with the recolored wild bootstrap procedure, which was developed for errors that follow a heteroscedastic linear process. Further, a combination of autoregressive sieve recoloring with the dependent wild bootstrap is shown to perform well. The validity of the dependent wild bootstrap in a nonstationary setting is demonstrated for the first time, showing the possibility of extensions to other inference problems associated with locally stationary processes.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Cavaliere, G. and A. M. R. Taylor (2009) Bootstrap M unit root tests | 1.000 | 7 | 3 | 100% |
| 2 | Cavaliere, G. and A. M. R. Taylor (2008) Bootstrap unit root tests for time series with nonstationary volatility | 1.000 | 5 | 3 | 100% |
| 3 | Paparoditis, E. and D. N. Politis (2003) Residual-based block bootstrap for unit root testing | 1.000 | 5 | 3 | 100% |
| 4 | Zhou, Z (2013) Heteroscedasticity and autocorrelation robust structural change detection | 0.874 | 6 | 2 | 100% |
| 5 | Zhou, Z. and W. B. Wu (2009) Local linear quantile estimation for nonstationary time series | 0.874 | 6 | 2 | 100% |
| 6 | Phillips, P. C. B (1987) Time series regression with a unit root | 0.874 | 5 | 2 | 100% |
| 7 | Shao, X (2010) The dependent wild bootstrap self | 0.737 | 3 | 2 | 100% |
| 8 | Smeekes, S. and J.-P. Urbain (2014) A multivariate invariance principle for modified wild bootstrap methods with an application to unit root testing | 0.737 | 3 | 2 | 100% |
| 9 | Wu, W. B (2005) Nonlinear system theory: Another look at dependence | 0.737 | 3 | 2 | 100% |
| 10 | Cavaliere, G. and A. M. R. Taylor (2007) Testing for unit roots in time series models with non-stationary volatility | 0.644 | 2 | 2 | 100% |
Showing the top 10 of 59 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Testing for Nonlinear Cointegration under Heteroskedasticity | 0.511 | 2 | 1 |
| 2 | High-Dimensional Forecasting in the Presence of Unit Roots and Cointegration | 0.405 | 1 | 1 |
| 3 | A Bootstrap-Assisted Self-Normalization Approach to Inference in Cointegrating Regressions | 0.405 | 1 | 1 |