A Vector Autoregressive Moving Average Model for Interval-Valued Time Series Data
Yongmiao Hong (),
Shouyang Wang and
A chapter in Essays in Honor of Aman Ullah, 2016, vol. 36, pp 417-460 from Emerald Publishing Ltd
Abstract Modelling and forecasting interval-valued time series (ITS) have received increasing attention in statistics and econometrics. An interval-valued observation contains more information than a point-valued observation in the same time period. The previous literature has mainly considered modelling and forecasting a univariate ITS. However, few works attempt to model a vector process of ITS. In this paper, we propose an interval-valued vector autoregressive moving average (IVARMA) model to capture the cross-dependence dynamics within an ITS vector system. A minimum-distance estimation method is developed to estimate the parameters of an IVARMA model, and consistency, asymptotic normality and asymptotic efficiency of the proposed estimator are established. A two-stage minimum-distance estimator is shown to be asymptotically most efficient among the class of minimum-distance estimators. Simulation studies show that the two-stage estimator indeed outperforms other minimum-distance estimators for various data-generating processes considered.
Keywords: Asymptotic efficiency; interval vector-valued time series; interval-valued data; minimum-distance estimation; vector autoregressive moving average interval models; C3; C32 (search for similar items in EconPapers)
References: Add references at CitEc
Citations: View citations in EconPapers (2) Track citations by RSS feed
Downloads: (external link)
http://www.emeraldinsight.com/10.1108/S0731-905320 ... RePEc&WT.mc_id=RePEc (text/html)
Access to full text is restricted to subscribers
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:eme:aecozz:s0731-905320160000036021
Ordering information: This item can be ordered from
Emerald Group Publishing, Howard House, Wagon Lane, Bingley, BD16 1WA, UK
http://www.emeraldgr ... ies.htm?id=0731-9053
Access Statistics for this chapter
More chapters in Advances in Econometrics from Emerald Publishing Ltd
Bibliographic data for series maintained by Charlotte Maiorana ().