A Monte Carlo comparison of Bayesian testing for cointegration rank

被引:0
|
作者
Sugita, Katsuhiro [1 ]
机构
[1] Univ Ryukyus, Fac Law & Letters, Nishihara, Okinawa, Japan
来源
ECONOMICS BULLETIN | 2009年 / 29卷 / 03期
关键词
D O I
暂无
中图分类号
F [经济];
学科分类号
02 ;
摘要
This article considers a Bayesian testing for cointegration rank, using an approach developed by Strachan and van Dijk (2007), that is based on Koop, Leon-Gonzalez, and Strachan (2006). The Bayes factors are calculated for selecting cointegrating rank. We calculate the Bayes factors using two methods - the Schwarz BIC approximation and Chib's (1995) algorithm for calculating the marginal likelihood. We run Monte Carlo simulations to compare the two methods.
引用
收藏
页码:2145 / 2151
页数:7
相关论文
共 50 条
  • [21] Bayesian Evaluation for Uncertainty of Indirect Measurements in Comparison with GUM and Monte Carlo
    Molina-Muñoz, Juan Daniel
    Giraldo-Jaramillo, Luis Fernando
    Delgado-Trejos, Edilson
    Ingenieria y Universidad, 2022, 26
  • [22] A commentary on 'A comparison of Bayesian and Monte Carlo sensitivity analysis for unmeasured confounding'
    Greenland, Sander
    STATISTICS IN MEDICINE, 2017, 36 (20) : 3278 - 3280
  • [23] A comparison of Bayesian Markov chain Monte Carlo methods in a multilevel scenario
    Karunarasan, Darshika
    Sooriyarachchi, Roshini
    Pinto, Vimukthini
    COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION, 2023, 52 (10) : 4756 - 4772
  • [24] Bayesian statistics and the Monte Carlo method
    Herzog, TN
    PROCEEDINGS OF THE 2002 WINTER SIMULATION CONFERENCE, VOLS 1 AND 2, 2002, : 136 - 146
  • [25] The effect of spillover on the Johansen tests for cointegration: a Monte Carlo analysis
    Mantalos, Panagiotis
    Mansson, Kristofer
    Shukur, Ghazi
    INTERNATIONAL JOURNAL OF COMPUTATIONAL ECONOMICS AND ECONOMETRICS, 2010, 1 (3-4) : 327 - 342
  • [26] Bayesian statistics and Monte Carlo methods
    Koch, K. R.
    JOURNAL OF GEODETIC SCIENCE, 2018, 8 (01) : 18 - 29
  • [27] Bayesian Optimized Monte Carlo Planning
    Mern, John
    Yildiz, Anil
    Sunberg, Zachary
    Mukerji, Tapan
    Kochenderfer, Mykel J.
    THIRTY-FIFTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, THIRTY-THIRD CONFERENCE ON INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE AND THE ELEVENTH SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE, 2021, 35 : 11880 - 11887
  • [28] Temporal aggregation and the power of cointegration tests: A Monte Carlo study
    Haug, AA
    OXFORD BULLETIN OF ECONOMICS AND STATISTICS, 2002, 64 (04) : 399 - 412
  • [29] On Monte Carlo methods for Bayesian inference
    Qian, SS
    Stow, CA
    Borsuk, ME
    ECOLOGICAL MODELLING, 2003, 159 (2-3) : 269 - 277
  • [30] BAYESIAN MODEL COMPARISON VIA PATH-SAMPLING SEQUENTIAL MONTE CARLO
    Zhou, Yan
    Johansen, Adam M.
    Aston, John A. D.
    2012 IEEE STATISTICAL SIGNAL PROCESSING WORKSHOP (SSP), 2012, : 245 - 248