arXiv 5 Apr 2022 · Econometrics
arXiv:2204.02073 · PDF · DOI · OpenAlex · Extracted main text
We establish the asymptotic theory in quantile autoregression when the model parameter is specified with respect to moderate deviations from the unit boundary of the form (1 + c / k) with a convergence sequence that diverges at a rate slower than the sample size n. Then, extending the framework proposed by Phillips and Magdalinos (2007), we consider the limit theory for the near-stationary and the near-explosive cases when the model is estimated with a conditional quantile specification function and model parameters are quantile-dependent. Additionally, a Bahadur-type representation and limiting distributions based on the M-estimators of the model parameters are derived. Specifically, we show that the serial correlation coefficient converges in distribution to a ratio of two independent random variables. Monte Carlo simulations illustrate the finite-sample performance of the estimation procedure under investigation.
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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 | Phillips, P. C. B. and Magdalinos, T (2007) Limit theory for moderate deviations from a unit root | 0.969 | 11 | 5 | 91% |
| 2 | Wang, X., Tang, X., and Song, Y (2022) Asymptotics of m-estimators for moderate deviations from a unit root model with possibly infinite variance | 0.843 | 4 | 3 | 75% |
| 3 | Chan, N. H., Peng, L., and Qi, Y (2006) Quantile inference for near-integrated autoregressive time series with infinite variance | 0.811 | 4 | 2 | 100% |
| 4 | Buchmann, B. and Chan, N. H (2007) Asymptotic theory of least squares estimators for nearly unstable processes under strong dependence | 0.737 | 3 | 2 | 100% |
| 5 | Hui, J., Yilong, W., and Guangyu, Y (2022) Deviation inequalities and cramer-type moderate deviations for the explosive autoregressive process | 0.737 | 3 | 2 | 100% |
| 6 | Magdalinos, T. and Petrova, K (2022) Uniform and distribution-free inference with general autoregressive processes | 0.737 | 3 | 2 | 100% |
| 7 | Phillips, P. C. B. and Magdalinos, T (2009) Econometric inference in the vicinity of unity | 0.737 | 3 | 2 | 100% |
| 8 | Aue, A. and Horváth, L (2007) A limit theorem for mildly explosive autoregression with stable errors | 0.737 | 3 | 2 | 100% |
| 9 | Dickey, D. A. and Fuller, W. A (1979) Distribution of the estimators for autoregressive time series with a unit root | 0.737 | 3 | 2 | 100% |
| 10 | Kostakis, A., Magdalinos, T., and Stamatogiannis, M. P (2015) Robust econometric inference for stock return predictability | 0.737 | 3 | 2 | 100% |
Showing the top 10 of 95 scored citations.