We propose a multicountry quantile factor augmeneted vector autoregression (QFAVAR) to model heterogeneities both across countries and across characteristics of the distributions of macroeconomic time series. The presence of quantile factors allows for summarizing these two heterogeneities in a...

Predictability is time and frequency dependent. We propose a new forecasting method - forecast combination in the frequency domain - that takes this fact into account. With this method we forecast the equity premium and real GDP growth rate. Combining forecasts in the frequency domain produces...

While corporate credit losses have been low since the start of the Covid-19 pandemic, their future evolution is quite uncertain. Using a forecasting model with a solid track record, we find that the baseline scenario ("expected losses") is benign up to 2024. This is due to policy support...

The main contribution of this paper is the construction of a cyclical systemic risk indicator from early warning indicators of banking crises (EWIs) used in Finland. Previous research has shown that combining EWIs can enhance their early warning properties. This study evaluates the indicator's...

We investigate whether European banks adjust their loan prices and volumes of new lending in the months running up to major national elections. Using a unique dataset that draws on data covering some 250 banksin 19 Eurozone countries from 2010 to 2020 at monthly frequency, and that includes...

In this study, we employ the pairwise stochastic convergence approach to identify the pairs of NUTS2 regions for all 28 EU Member States that exhibit co-movement in their growth dynamics, over the period 1980-2018. We then use the observed stochastic convergence trajectories to assess the role...

We propose a novel copula approach to producing density forecasts of economic aggregates combining models using disaggregate data. Our copula approach is more flexible compared to existing techniques, because it is applicable to any econometric model that produces density forecasts. We construct...

We test for state-dependent bias in the European Central Bank's inflation projections. We show that the ECB tends to underpredict when the observed inflation rate at the time of forecasting is higher than an estimated threshold of 1.8%. The bias is most pronounced at intermediate forecasting...

This paper presents a framework for quantifying uncertainty around point forecasts for GDP, inflation and house prices in Norway. The framework combines quantile regressions using a broad set of uncertainty indicators with a skewed t-distribution, allowing for time-variation and asymmetry in the...