Towards Uniformly Efficient Trend Estimation Under Weak/Strong Correlation and Non-stationary Volatility

Ke-Li Xu and Jui-Chung Yang

Scandinavian Journal of Statistics, 2015, vol. 42, issue 1, 63-86

Abstract: type="main" xml:id="sjos12095-abs-0001"> In this paper, we consider the deterministic trend model where the error process is allowed to be weakly or strongly correlated and subject to non-stationary volatility. Extant estimators of the trend coefficient are analysed. We find that under heteroskedasticity, the Cochrane–Orcutt-type estimator (with some initial condition) could be less efficient than Ordinary Least Squares (OLS) when the process is highly persistent, whereas it is asymptotically equivalent to OLS when the process is less persistent. An efficient non-parametrically weighted Cochrane–Orcutt-type estimator is then proposed. The efficiency is uniform over weak or strong serial correlation and non-stationary volatility of unknown form. The feasible estimator relies on non-parametric estimation of the volatility function, and the asymptotic theory is provided. We use the data-dependent smoothing bandwidth that can automatically adjust for the strength of non-stationarity in volatilities. The implementation does not require pretesting persistence of the process or specification of non-stationary volatility. Finite-sample evaluation via simulations and an empirical application demonstrates the good performance of proposed estimators.

Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://hdl.handle.net/10.1111/sjos.12095 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bla:scjsta:v:42:y:2015:i:1:p:63-86

Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=0303-6898

Access Statistics for this article

Scandinavian Journal of Statistics is currently edited by ÿrnulf Borgan and Bo Lindqvist

More articles in Scandinavian Journal of Statistics from Danish Society for Theoretical Statistics, Finnish Statistical Society, Norwegian Statistical Association, Swedish Statistical Association
Bibliographic data for series maintained by Wiley Content Delivery ().