|Title:||Quantile Regression on Quantile Ranges - A Threshold Approach||Authors:||CHUNG-MING KUAN
|Keywords:||Quantile regression; threshold model; serial correlation; bahadur representation; confidence intervals for threshold parameter||Issue Date:||2017||Publisher:||WILEY-BLACKWELL||Journal Volume:||38||Journal Issue:||1||Start page/Pages:||99||Source:||JOURNAL OF TIME SERIES ANALYSIS||Abstract:||
Copyright © 2016 John Wiley & Sons Ltd We study, via quantile regression, time series models whose conditional distribution may change over different quantile range of a threshold variable. We derive the limiting distribution of the estimated threshold parameter under the frameworks of asymptotically shrinking and fixed regime change magnitude. We construct confidence intervals for the estimated threshold parameter via a likelihood-ratio-type statistic and tabulate critical values, and by extensive simulation, we investigate their coverage probabilities. We also derive the Bahadur representation allowing for serially correlated errors and discuss related inference problems on threshold effects. Our asymptotic and simulation results complement the existing literature of Caner (2002), Galvao et al (2011, 2014) on threshold regression models.
|Appears in Collections:||財務金融學系|
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