This paper proposes a large Bayesian Vector Autoregressive (BVAR) model with common stochastic volatility to forecast global equity indices. Using a dataset consisting of monthly data on global stock indices the BVAR model inherently incorporates co-movements in the stock markets. The...

This paper aims to identify the contribution of knowledge capital and its determinant - human capital - to total factor productivity differences among regions within a regression framework in general and the impact of their spillovers on regional total factor productivity in particular. The...

The speed of income convergence in Europe remains one of the hot topics in regional economics. Recently Bayesian Model Averaging (BMA) applied to spatial autoregressive models seems to have gained more popularity. BMA averages over some predetermined number of so called top models, ranked by the...

This paper considers the problem of model uncertainty associated with variable selection and specification of the spatial weight matrix in spatial growth regression models in general and growth regression models based on the matrix exponential spatial specification in particular. A natural...

We present evidence that global vectorautoregressive (GVAR) models produce significantly more accurate recession forecasts than country-specific time-series models in a Bayesian framework. This result holds for most countries and forecast horizons as well as for several country groups.

We analyze how modeling international dependencies improves forecasts for the global economy based on a Bayesian GVAR with SSVS prior and stochastic volatility. To analyze the source of performance gains, we decompose the predictive joint density into its marginals and a copula term capturing...

We analyze how modeling international dependencies improves forecasts for the global economy based on a Bayesian GVAR with SSVS prior and stochastic volatility. To analyze the source of performance gains, we decompose the predictive joint density into its marginals and a copula term capturing...

This paper exploits the information collected from an ad hoc survey conducted on a sample of Macedonian firms to study the extent of nominal price and wage rigidities in the Republic of Macedonia. The research was motivated by the observation that sticky prices influence the responsiveness of...

This paper puts forward a Bayesian Global Vector Autoregressive Model with Common Stochastic Volatility (B-GVAR-CSV). We assume that country specific volatility is driven by a single latent stochastic process, which simplifies the analysis and implies significant computational gains. Apart from...

In this paper we assess the predictive abilities of a Bayesian threshold vector autoregression (B-TVAR) to forecast the EUR/USD exchange rate. By introducing stochastic search variable selection priors (SSVS), we account for the inherent model uncertainty when it comes to modeling exchange...