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...

In the current study, we analyze the effect of having a Roma background on women's wages. By utilizing the Athens Area Study random sample (2007-08) drawn from 16 multiethnic municipalities in which Roma live, we estimate that 66.1% of the wage differential between Roma and non-Roma female...

In a previous paper (J. Non-Newtonian Fluid Mech. 76 (1998) 5), the analogy between the methodology typical of the dynamics of polymeric liquids and those used in granular flow theory was investigated. It was shown that such a methodology could be successfully extended to granular flow, and then...