A note on testing for nonstationarity in autoregressive processes with level dependent conditional heteroskedasticity

被引：0
作者：
Paulo M. M. Rodrigues
Antonio Rubia
机构：
[1] University of Algarve,Faculty of Economics
[2] University of Alicante,Department of Financial Economics
来源：
Statistical Papers | 2008年 / 49卷
关键词：
Maximum likelihood estimation; Nonstationarity; Volatility; Interest rates;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
In this paper, we investigate the empirical distribution and the statistical properties of maximum likelihood (ML) unit-root t-statistics computed from data sampled from a first-order autoregressive (AR) process with level-dependent conditional heteroskedasticity (LDCH). This issue is of particular importance for applications on interest rate time-series. Unfortunately, the extent of the technical complexity related associated to LDCH patterns does not offer a feasible theoretical analysis, and there is no formal knowledge about the finite-sample size and power behaviour or the ML test for this context. Our analysis provides valuable guidelines for applied work and directions for future work.
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页码：581 / 593
页数：12
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