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 - GrĂ¼n, Bettina AU - Hofmarcher, Paul AU - Humer, Stefan AU - Moser, Mathias ER -