A Bayesian dynamic compositional model is introduced that can deal with combining a large set of predictive densities. It extends the mixture of experts and the smoothly mixing regression models by allowing for combination weight dependence across models and time. A compositional model with...

This paper investigated the macroeconomic effects of fiscal policy shocks in Ethiopiausing a Bayesian Vector Auto Regression model. We examined the dynamic responsesof output, inflation, interest rate and exchange rate to fiscal policy shocks employingquarterly data from 2000/01Q1 to 2015/16Q4....

A Bayesian typically uses data and a prior to produce a posterior. In practice, the data and the posterior are often observed but not the prior. We shall follow the opposite route, using data and the posterior information to reveal the prior. We then apply this theory to (equilibrium) climate...

Average hours worked in the US recovers much faster than the unemployment rate following financial crises. Using an identified vector autoregression framework with nine quarterly US time series from 1984 to 2014, I find that an adverse financial shock leads to a fall in economic activity with a...

This paper examines the robustness of explanatory variables in cross-country economic growth regressions. It employs a novel approach, Bayesian Averaging of Classical Estimates (BACE), which constructs estimates as a weighted average of OLS estimates for every possible combination of included...

We study a self-reflexive DSGE model with heterogeneous households, aimed at characterising the impact of economic recessions on the different strata of the society. Our framework allows to analyse the combined effect of income inequalities and confidence feedback mediated by heterogeneous...

We explore the consequences of weakening the notion of incentive compatibility from strategy-proofness to ordinal Bayesian incentive compatibility (OBIC) in the random assignment model. If the common prior of the agents is a uniform prior, then a large class of random mechanisms are OBIC with...

This paper investigated the macroeconomic effects of government spending shocks in Ethiopia using a Bayesian Vector Auto Regression model. We examined the dynamic responses of output, inflation, interest rate and exchange rate to Government Spending shocks employing quarterly data from 2000/01Q1...

This tutorial provides an introduction to Bayesian modeling and Markov Chain Monte-Carlo (MCMC) algorithms including the Metropolis-Hastings and Gibbs Sampling algorithms. We discuss some of the challenges associated with running MCMC including the important question of determining when...