I use Bayesian VARs to forecast global temperatures anomalies until the end of the XXI century by exploiting their cointegration with the Joint Radiative Forcing (JRF) of the drivers of climate change. Under a ‘no change’ scenario, the most favorable median forecast predicts the land...

This paper puts forward a Bayesian version of the global vector autoregressive model (B-GVAR) that accommodates international linkages across countries in a system of vec-tor autoregressions. We compare the predictive performance of B-GVAR models for the one- and four-quarter ahead forecast...

This chapter reviews Bayesian methods for inference and forecasting with VAR models. Bayesian inference and, by extension, forecasting depends on numerical methods for simulating from the posterior distribution of the parameters and special attention is given to the implementation of the...

This study examined the causal relationship between inflation and economic growth as well as estimating threshold and forecasting of inflation in Nigeria for the period of 1961 { 2016. The study employed Granger causality test, Au- toregressive Distributed Lag (ARDL), Autoregressive Integrated...