期刊
ECONOMETRIC THEORY
卷 32, 期 4, 页码 793-826出版社
CAMBRIDGE UNIV PRESS
DOI: 10.1017/S0266466615000043
关键词
-
类别
资金
- FWF (Austrian Science Fund) [P20833/N18, P24198/N18]
- ARC (Australian Research Council) [DP1092571]
- NICTA
- Australian Government
- ARC through the ICT Centre of Excellence program
- Austrian Science Fund (FWF) [P 24198] Funding Source: researchfish
- Austrian Science Fund (FWF) [P24198] Funding Source: Austrian Science Fund (FWF)
- Australian Research Council [DP1092571] Funding Source: Australian Research Council
This paper is concerned with the problem of identifiability of the parameters of a high frequency multivariate autoregressive model from mixed frequency time series data. We demonstrate identifiability for generic parameter values using the population second moments of the observations. In addition we display a constructive algorithm for the parameter values and establish the continuity of the mapping attaching the high frequency parameters to these population second moments. These structural results are obtained using two alternative tools viz. extended Yule Walker equations and blocking of the output process. The cases of stock and flow variables, as well as of general linear transformations of high frequency data, are treated. Finally, we briefly discuss how our constructive identifiability results can be used for parameter estimation based on the sample second moments.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据