TY  - JOUR
TI  - Unveiling Covariate Inclusion Structures In Economic Growth Regressions Using Latent Class Analysis
AB  - We propose the use of Latent Class Analysis methods to analyze the covariate inclusion patterns across specifications resulting from Bayesian model averaging exercises. Using Dirichlet Process clustering, we are able to identify and describe dependency structures among variables in terms of inclusion in the specifications that compose the model space. We apply the method to two datasets of potential determinants of economic growth. Clustering the posterior covariate inclusion structure of the model space formed by linear regression models reveals interesting patterns of complementarity and substitutability across economic growth determinants.
DO  - http://dx.doi.org/10.1016/j.euroecorev.2015.03.009
SP  - 189
EP  - 202
UR  - http://www.sciencedirect.com/science/article/pii/S0014292115000458
PY  - 2016-01-01
JO  - European Economic Review
AU  - Crespo Cuaresma, Jesus 
AU  - Grün, Bettina 
AU  - Hofmarcher, Paul 
AU  - Humer, Stefan 
AU  - Moser, Mathias 
ER -