This paper develops methods for automatic selection of variables in forecasting Bayesian vector autoregressions (VARs) using the Gibbs sampler. In particular, I provide computationally efficient algorithms for stochastic variable selection in generic (linear and nonlinear) VARs. The performance...

This paper proposes a Bayesian nowcasting approach that utilizes information coming both from large real-time data sets and from priors constructed using internet search popularity measures. Exploiting rich information sets has been shown to deliver significant gains in nowcasting contexts,...

This paper develops and estimates a dynamic stochastic general equilibrium model of a closed economy which approximately accounts for the empirical evidence concerning the monetary transmission mechanism, as summarized by impulse response functions derived from an estimated structural vector...

This paper develops and estimates a dynamic stochastic general equilibrium model of a closed economy which provides a quantitative description of the monetary transmission mechanism, yields a mutually consistent set of indicators of inflationary pressure together with confidence intervals, and...

Using quarterly data from 2006q3 to 2017q4, this paper employed sign restrictions with rejection method in a Vector Autoregression to estimate the pass-through of exchange rate dynamics to domestic prices in Ghana. The priors of the model belongs to the flat Normal inverted-Wishart family....

This paper analyzes the performance of central banks in 27 inflation targeting countries by examining their success in achieving their explicit inflation targets. For this purpose, we decompose the inflation gap, the difference between actual inflation and inflation target, into predictable and...

In this paper I assess the ability of Bayesian vector autoregressions (BVARs) and dynamic stochastic general equilibrium (DSGE) models of different size to forecast comovements of major macroeconomic series in the euro area. Both approaches are compared to unrestricted VARs in terms of...

This paper proposes a simple technical approach for the derivation of future (forward) point-in-time PD forecasts, with minimal data requirements. The inputs required are the current and future through-the-cycle PDs of the obligors, their last known default rates, and a measure for the...

In order to explain clearly inflation forecasting and the dynamic of Tunisian prices, this paper uses two econometric approaches, the Standard VAR and Bayesian VAR (BVAR), to assess three models for predicting inflation, the mark-up model, the monetary model and Phillips curve over the period...

This paper investigates the use of DMA approach for identifying good inflation predictors and forecasting inflation in Mongolia, one of the most commodity dependent economies, using dynamic model averaging (DMA). The DMA approach allows for both set of predictors for inflation and marginal...