In this study, we develop a framework, based on a global vector autoregression (GVAR) model, to unite two perspectives on commodity markets, the commodity-specific, single-market-centered approach, investigating the micro- and macroeconomic drivers of commodity prices, and the market...

We propose a dynamic factor state-space model for the prediction of high-dimensional realized covariance matrices of asset returns. Using a block LDL decomposition of the joint covariance matrix of assets and factors, we express the realized covariance matrix of the individual assets similar to...

This paper introduces an extended multivariate EGARCH model that overcomes the zero-return problem and allows for negative news and volatility spillover effects, making it an attractive tool for multivariate volatility modeling. Despite limitations, such as noninvertibility and unclear...

This paper introduces a novel model to analyse the impact of macroeconomic shocks on volatility spillovers within key financial markets, such as Stock, Bond, Gold and Crude Oil. By treating macroeconomic variables as external factors to financial market volatility, our study distinguishes...

This study measures congestion in major container ports and investigates how port characteristics and regional factors influence congestion during the COVID-19 periods. We develop port congestion indicators, including vessel arrivals, vessels staying in a period, waiting time, and service time....

This paper provides evidence that oil price fluctuations have been an important driver of petroleum investment in Norway. To show this, I utilize a Bayesian vector autoregressive (BVAR) model combined with local projections, using various investment data from national accounts and firms' survey...

This paper presents a framework for empirical analysis of dynamic macroeconomic models using Bayesian Öltering, with a speciÖc focus on the state-space formulation of Dynamic Stochastic General Equilibrium (DSGE) models with multiple regimes. We outline the theoretical foundations of model...

We estimate a time-varying parameter vector autoregression to examine the evolution of international spillovers of U.S. monetary policy in light of increasing globalization in real and financial markets. We find that the adverse international effects of a U.S. tightening have substantially...

This paper examines the forecast accuracy of cointegrated vector autoregressive models when confronted with extreme observations at the end of the sample period. It focuses on comparing two outlier correction methods, additive outliers and innovational outliers, within a forecasting framework...

What drives the recent inflation surge? To answer this question, one must decompose inflation fluctuations into the contribution of structural shocks. We document how whimsical such a historical shock decomposition can be in standard vector autoregressive (VAR) models. We show that the...