2022/04/05 by Christis Katsouris, Katsouris, Christis
Mathematics · #Econometrics (econ.EM) #FOS: Economics and business #Statistical Methods and Inference
paper · pdf · doi:10.48550/arxiv.2204.02073
openalex publication_date 2022/04/05 · openalex created_date 2022/05/05 · openalex updated_date 2026/07/28
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.