In this paper, we develop a Bayesian approach to counterfactual analysis of structural change. Contrary to previous analysis based on classical point estimates, this approach provides a straightforward measure of estimation uncertainty for the counterfactual quantity of interest. We apply the...

We investigate the issue of model uncertainty in cross-country growth regressions using Bayesian model averaging (BMA). We find that the posterior probability is distributed among many models, suggesting the superiority of BMA over any single model. Out-of-sample predictive results support that...

This study constructs a Bayesian nonparametric model to investigate whether stock market returns predict real economic growth. Unlike earlier studies, our use of an infinite hidden Markov model enables parameters to be time-varying across an infinite number of Markov-switching states estimated...

We use Bayesian Model Averaging (BMA) to evaluate the robustness of determinants of economic growth in a new dataset of 255 European regions in the 1995-2005 period. We use three different specifications based on (1) the cross-section of regions, (2) the cross-section of regions with country...

We examine the dynamic impact of liquidity shocks resonating in stock and housing markets on real GDP growth. We fit a Bayesian time-varying parameter VAR model with stochastic volatility to US data from 1970 to 2014. GDP becomes highly sensitive to house market liquidity shocks as disruptions...

In this paper, we analyse Okun's law - a relation between the change in the unemployment rate and GDP growth - using data from Australia, the euro area, the United Kingdom and the United States. More specifically, we assess the relevance of non-Gaussianity when modelling the relation. This is...

This article examines the growth performance of Africa and the Middle East for the period 1990-2005. It employs a Bayesian Model Averaging method that constructs estimates as a weighted average of Spatial Autoregressive estimates for every possible combination of included variables. One of the...

This paper estimates the distribution-led regime of the US economy for the period 1947-2019. We use a time varying parameter model, which allows for changes in the regime over time. To the best of our knowledge this is the first paper that has attempted to do this. This innovation is important,...

This study develops a framework to forecast India's gross domestic product growth on a quarterly frequency from 2004 to 2018. The models, which are based on real and monetary sector descriptions of the Indian economy, are estimated using Bayesian vector autoregression (BVAR) techniques. The real...