Variational Bayes Estimation of Time Series Copulas for Multivariate Ordinal and Mixed Data

2017 ◽  
Author(s):  
Rubbn Albeiro Loaiza Maya ◽  
Michael S. Smith
Keyword(s):  
Time Series ◽  
Variational Bayes ◽  
Bayes Estimation ◽  
Mixed Data ◽  
Estimation Of Time

scholarly journals What To Do (and Not to Do) with Time-Series Cross-Section Data

1995 ◽  
Vol 89 (3) ◽  
pp. 634-647 ◽  
Author(s):  
Nathaniel Beck ◽  
Jonathan N. Katz
Keyword(s):  
Time Series ◽  
Cross Section ◽  
Generalized Least Squares ◽  
Monte Carlo Analysis ◽  
Standard Errors ◽  
Comparative Political Economy ◽  
Section Data ◽  
Alternative Estimator ◽  
Estimation Of Time ◽  
Least Squares Approach

We examine some issues in the estimation of time-series cross-section models, calling into question the conclusions of many published studies, particularly in the field of comparative political economy. We show that the generalized least squares approach of Parks produces standard errors that lead to extreme overconfidence, often underestimating variability by 50% or more. We also provide an alternative estimator of the standard errors that is correct when the error structures show complications found in this type of model. Monte Carlo analysis shows that these “panel-corrected standard errors” perform well. The utility of our approach is demonstrated via a reanalysis of one “social democratic corporatist” model.

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