This paper investigates convergence and dynamic effects of human and physical capital on growth, in WAEMU countries. Using recently developed models for panel data and a growth accounting model, the study finds that growth is largely explained by changes in literacy rates and factor...

This paper studies asymptotically the bias of the fixed effect (FE) estimator induced by cross-section heterogeneity in the slope parameters of stationary vector autoregressions (VARs). The paper also compares the FE, the mean group estimator (MG), and a simple instrumental variable alternative...

We propose using a Bayesian time-varying coefficient model estimated with Markov chain-Monte Carlo methods to measure contagion empirically. The proposed measure works in the joint presence of heteroskedasticity and omitted variables and does not require knowledge of the timing of the crisis. It...

“Program numbers” from a sample of IMF-supported programs are studied as if they were forecasts, through statistical analyses of the relationship between projections and outcomes for growth, inflation, and three balance of payments concepts. Statistical bias is found only for projections of...

Trade theories covering Preferential Trade Agreements (PTAs) are as diverse as the literature in search of their empirical support. To account for the model uncertainty that surrounds the validity of the competing PTA theories, we introduce Bayesian Model Averaging (BMA) to the PTA literature....

This paper empirically investigates the relationship between privatization and measures of fiscal and macroeconomic performance. One of the main findings is that privatization proceeds transferred to the budget tend to be saved. Specifically, they are largely used to reduce domestic financing,...

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...