On the determinants of the 2008 financial crisis: a Bayesian approach to the selection of groups and variables

2017 ◽  
Vol 21 (5) ◽  
Author(s):  
Ray-Bing Chen ◽  
Yi-Chi Chen ◽  
Chi-Hsiang Chu ◽  
Kuo-Jung Lee

AbstractWe consider the determinants of the 2008 crisis and address two main forms of model uncertainty: the uncertainty in selecting theoretical groups and the uncertainty in selecting explanatory variables. We introduce Bayesian hierarchical formulation that allows for the joint treatment of group and variable selection using the Group-wise Gibbs sampler. Our group variable selection shows that pre-crisis financial policies and trade linkages play a particularly important role in explaining the severity of the crisis, alongside institutions, and within the selected groups we identify a broader set of variables correlated with the crisis, which in turn leads to an improvement in prediction performance. In the robustness analysis we also find that our results are not qualitatively changed on alternative measures of crisis intensity, different groupings of variables, or prior assumptions. We further argue that the established results in the literature may well be attributed to different prior choices used in the analysis.

2017 ◽  
Vol 171 ◽  
pp. 241-250 ◽  
Author(s):  
Guang-Hui Fu ◽  
Feng Xu ◽  
Bing-Yang Zhang ◽  
Lun-Zhao Yi

2017 ◽  
Vol 47 (6) ◽  
Author(s):  
Joel Donazzolo ◽  
Vanessa Padilha Salla ◽  
Simone Aparecida Zolet Sasso ◽  
Moeses Andrigo Danner ◽  
Idemir Citadin ◽  
...  

ABSTRACT: The objective of this paper was to identify the direct and indirect effects of feijoa fruits (Acca sellowiana) traitson pulp weight, in order to use these traits in indirect genotypes selection. Fruits of five feijoa plants were collected in Rio Grande do Sul, in the years of 2009, 2010 and 2011. Six traits were evaluated: diameter, length, total weight, pulp weight, peel thickness and number of seeds per fruit. In the path analysis, with or without ridge regression, pulp weight was considered as the basic variable, and the other traits were considered as explanatory variables. Total weight and fruit diameter had high direct effect, and are the main traits associated with pulp weight. These traits may serve as criteria for indirect selection to increase feijoa pulp weight, since they are easy to be measured.


Author(s):  
Chakkrit Tantithamthavorn ◽  
Shane McIntosh ◽  
Ahmed E Hassan ◽  
Kenichi Matsumoto

Shepperd et al. (2014) find that the reported performance of a defect prediction model shares a strong relationship with the group of researchers who construct the models. In this paper, we perform an alternative investigation of Shepperd et al. (2014)’s data. We observe that (a) researcher group shares a strong association with the dataset and metric families that are used to build a model; (b) the strong association among the explanatory variables introduces a large amount of interference when interpreting the impact of the researcher group on model performance; and (c) after mitigating the interference, we find that the researcher group has a smaller impact than the metric family. These observations lead us to conclude that the relationship between the researcher group and the performance of a defect prediction model may have more to do with the tendency of researchers to reuse experimental components (e.g., datasets and metrics). We recommend that researchers experiment with a broader selection of datasets and metrics to combat potential bias in their results.


Author(s):  
Mulagala Sandhya ◽  
Mulagala Dileep ◽  
Akurathi Narayana Murthy ◽  
Md. Misbahuddin

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