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Abstract Details
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Activity Number:
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417
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Type:
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Contributed
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Date/Time:
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Tuesday, August 2, 2011 : 2:00 PM to 3:50 PM
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Sponsor:
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Business and Economic Statistics Section
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| Abstract - #302105 |
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Title:
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Bayesian Multivariate Ordinal Probit Analysis of China's Consumer Confidence Index Data
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Author(s):
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Junni Zhang*+ and Wei Lan
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Companies:
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Peking University and Peking University
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Address:
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, , ,
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Keywords:
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Multivariate Ordinal Probit Regression ;
Parameter Expansion ;
Inverse Wishart Distribution
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Abstract:
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We build a Bayesian multivariate ordinal probit model, using the parameter expansion approach to expand the correlation matrix into a covariance matrix, and then adopting a specific conjugate prior that can help shrink the off-diagonal elements of the inverse covariance matrix (therefore those of the inverse correlation matrix) toward zero. Gibbs sampling is then used to sample the parameters. We apply this model to analyze China's consumer confidence index data for year 2009, in which consumers' judgements about seven aspects of the economy were quarterly collected for the present status and the status three months later.
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