嘉宾评论:贝叶斯计量经济学方法研讨会

IF 0.7 Q3 ECONOMICS Review of Economic Analysis Pub Date : 2010-08-04 DOI:10.15353/rea.v2i2.1467
Rodney W. Strachan
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引用次数: 0

摘要

第三届RCEA贝叶斯研讨会于2009年7月在里米尼举行。研讨会以一场辩论拉开序幕,由盖尔·马丁主持,主要的贝叶斯计量经济学家克里斯蒂安·罗伯特和主要的古典计量经济学家拉塞尔·戴维森就贝叶斯方法和古典(或频率论)方法的相对优点进行了辩论。这场愉快的民间辩论的主题是“21世纪属于贝叶斯”。讲习班还汇集了各种古典和贝叶斯计量经济学家和统计学家,以便与会者就其具体研究领域的发展交流信息。本卷的两篇论文,一篇是经典方法,一篇是贝叶斯方法,对经典方法的见解部分反映了这一目的,还有更多的论文在研讨会上发表。在他的论文中,Russell Davidson以自回归移动平均(ARMA)(1,1)过程中的单位根测试为例,研究了自举测试中的问题。他关注的是MA多项式的根接近于- 1的情况。在这种情况下测试时,由于单位AR根与MA根几乎相消,导致引导测试中的大小扭曲。Davidson提出了基于非线性最小二乘的估计器,计算速度比最大似然估计器快,但效率不如最大似然估计器。这些估计器的计算速度比Galbraith和zind - walsh(1994)和(1997)提出的估计器慢,但比Galbraith和zind - walsh估计器有效得多。此外,Davidson提出了一种新的自举过程,它比Beran(1988)的双自举过程在计算上要求更低。戴维森得出了他所有的结果,而没有求助于渐近理论或渐近改进的测试程序。Polasek, Sellner和Llano考虑了在不同聚集程度上进行数据测量以及在一个或多个聚集水平上缺失一些观测值时空间模型中的估计和预测问题。他们采用了Chow和Lin(1971)的程序,该程序是针对具有观测值的时间序列数据开发的
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Guest Editorial: Workshop on Bayesian Econometric Methods
The 3rd RCEA Bayesian workshop was held in Rimini in July, 2009. The workshop opened with a debate, chaired by Gael Martin, between a leading Bayesian econometrician, Christian Robert, and a leading classical econometrician, Russell Davidson, on the relative virtues of the Bayesian and classical (or frequentist) approaches. The pleasantly civil debate was conducted under the topic "The 21st Century Belongs to Bayes". The workshop also brought together a variety of both classical and Bayesian econometricians and statisticians, with a view to participants exchanging information on developments in their specific fields of research. The two papers of this volume one classical in approach and one Bayesian, with insights into classical approaches partially reflect this purpose, with many more papers having been presented at the workshop itself. In his paper, Russell Davidson investigates issues in bootstrap testing using, as an example, testing for a unit root in an autoregressive moving average (ARMA) (1,1) process. He focuses on the situation when the root of the MA polynomial is close to minus one. Size distortions in the bootstrap tests result when testing in this situation, due to the near cancellation of the unit AR root with the MA root. Davidson proposes estimators based on nonlinear least squares that are faster to compute than, but not quite as efficient as, the maximum likelihood estimator. These estimators are slower to compute than those proposed by Galbraith and Zinde-Walsh (1994) and (1997), but far more efficient than the Galbraith and Zinde-Walsh estimators. Further, Davidson proposes a new bootstrap procedure that is computationally less demanding than the double bootstrap of Beran (1988). Davidson produces all of his results without recourse to asymptotic theory or asymptotic refinements of the testing procedure. Polasek, Sellner and Llano consider the problem of estimation and prediction in spatial models when data measurements are taken at different degrees of aggregation and where some observations are missing at one or more levels of aggregation. They adapt the procedure of Chow and Lin (1971), which was developed for time series data with observations on
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发文量
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审稿时长
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