This paper analyzes the stochastic inventory control problem when the demand distribution is not known. In contrast to previous Bayesian inventory models, this paper adopts a non-parametric Bayesian approach in which the firm’s prior information is characterized by a Dirichlet process prior....

This paper develops a panel unobserved components model of the monetary transmission mechanism in the world economy, disaggregated into twenty national economies along the lines of the Group of Twenty. This structural macroeconometric model features extensive linkages between the real and...

This paper reviews recent advances in the specification and estimation of Bayesian Vector Autoregressive models (BVARs). After describing the Bayesian principle of estimation, we first present the methodology originally developed by Litterman (1986) and Doan et al. (1984) and review alternative...

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...

This paper estimates a New Keynesian DSGE model with an explicit financial intermediary sector. Having measures of financial stress, such as the spread between lending and borrowing, enables the model to capture the impact of the financial crisis in a more direct and efficient way. The model...

Emerging markets are more volatile and face different types of shocks, in size and nature, compared to their developed counterparts. Accurate identification of the stochastic properties of shocks is difficult. We show evidence suggesting that uncertainty about the underlying stochastic process...

Do growth spells in Africa end because of bad realizations of the same factors that influence growth spells in the rest of the world, or because of different factors altogether? To answer this question, we examine determinants of growth spells in Africa and the rest of the world using Bayesian...