We bring together the spatial and global vector autoregressive (GVAR) classes of econometric models by providing a detailed methodological review of where they meet in terms of structure, interpretation, and estimation methods. We discuss the structure of cross-section connectivity (weight)...

We use tests for multiple breaks at unknown points in the sample, and the Stock-Watson (1996, 1998) time-varying parameters median-unbiased estimation methodology, to investigate changes in the equilibrium rate of growth of labor productivity - both per hour and per worker - in the United...

This paper develops a framework for assessing systemic risks and for predicting (out-of-sample) systemic events, i.e. periods of extreme financial instability with potential real costs. We test the ability of a wide range of “stand alone” and composite indicators in predicting systemic...

We define nowcasting as the prediction of the present, the very near future and the very recent past. Crucial in this process is to use timely monthly information in order to nowcast key economic variables, such as e.g. GDP, that are typically collected at low frequency and published with long...

This paper presents a parsimonious model for forecasting and analysing euro area house prices and their interrelations with the macroeconomy. A quarterly vector error correction model is estimated over 1970-2009 using supply and demand forces central to the determination of euro area house...

The paper focuses on the estimation of the euro area output gap. We construct model-averaged measures of the output gap in order to cope with both model uncertainty and parameter instability that are inherent to trend-cycle decomposition models of GDP. We first estimate nine models of...

The paper uses the Self-Organizing Map for mapping the state of financial stability and visualizing the sources of systemic risks as well as for predicting systemic financial crises. The Self-Organizing Financial Stability Map (SOFSM) enables a two-dimensional representation of a...

The issue of forecast aggregation is to determine whether it is better to forecast a series directly or instead construct forecasts of its components and then sum these component forecasts. Notwithstanding some underlying theoretical results, it is generally accepted that forecast aggregation is...

We propose a new method for medium-term forecasting using exogenous information. We first show how a shifting-mean autoregressive model can be used to describe characteristic features in inflation series. This implies that we decompose the inflation process into a slowly moving nonstationary...

This paper examines the out‐of‐sample forecast performance of sectoral stock market indicators for real GDP, private consumption and investment growth up to 4 quarters ahead in the US and the Euro Area. Our findings are that the predictive content of sectoral stock market indicators: i) is...