This paper attempts to identify robust patterns of cross-country growth behavior in the world as a whole and Africa. It employs a novel methodology that incorporates a dynamic panel estimator, and Bayesian Model Averaging to explicitly account for model uncertainty. The findings indicate that:...

This paper develops the theoretical background for the Limited Information Bayesian Model Averaging (LIBMA). The proposed approach accounts for model uncertainty by averaging over all possible combinations of predictors when making inferences about the variables of interest, and it...

We study a model where an employer, trying to fill a vacancy, engages in optimal sequential search by drawing from two subpopulations of candidates who differ in their "discourse systems": during an interview, a minority candidate with a discourse system not shared with the employer conveys a...

Time series on economic activity in developing countries, in particular real GDP, are reported with important lags. Therefore, it is useful to construct indicators that coincide or lead the actual direction and level of economic activity. A general methodology to construct these indicators is...

This paper revisits the cross-country growth empirics debate using a novel Limited Information Bayesian Model Averaging framework to address model uncertainty in the context of a dynamic growth model in panel data with endogenous regressors. Our empirical findings suggest that once model...

This paper presents an integrated framework for assessing systemic risk. The framework models banks’ capital asset ratios as a function of future losses and credit growth using a generalized method of moments to calibrate shocks to credit quality and credit growth. The analysis is...