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  • 标题:Formula I(1) and I(2): Race Tracks for Likelihood Maximization Algorithms of I(1) and I(2) Cointegrated VAR Models
  • 本地全文:下载
  • 作者:Doornik, Jurgen A. ; Mosconi, Rocco ; Paruolo, Paolo
  • 期刊名称:Econometrics
  • 印刷版ISSN:2225-1146
  • 出版年度:2017
  • 卷号:5
  • 期号:4
  • 页码:1-30
  • 出版社:MDPI, Open Access Journal
  • 摘要:This paper provides some test cases, called circuits, for the evaluation of Gaussian likelihood maximization algorithms of the cointegrated vector autoregressive model. Both I(1) and I(2) models are considered. The performance of algorithms is compared first in terms of effectiveness , defined as the ability to find the overall maximum. The next step is to compare their efficiency and reliability across experiments. The aim of the paper is to commence a collective learning project by the profession on the actual properties of algorithms for cointegrated vector autoregressive model estimation, in order to improve their quality and, as a consequence, also the reliability of empirical research.
  • 关键词:maximum likelihood; Monte Carlo; VAR; cointegration; I(1); I(2)
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