The forecasting of government revenues is extremely important for an adequate budget execution, since a good accuracy in the estimation allows the stipulation of an expenditure level that meets the demands of the population. Using data released by the National Council of Treasury Policy, the...

This paper introduces a weekly GDP indicator to track real economic activity in Germany in real-time. We use a mixed-frequency dynamic factor model with quarterly, monthly, and weekly indicators and obtain the weekly GDP indicator as the weighted common component of the mixed-frequency dataset....

Wind power generation is essential to reduce the use of fossil resources and, consequently, the emission of greenhouse gases (GHG). Currently, the National Interconnected System (SIN) has about 9971 wind turbines in operation, the sixth largest network in the world ranking, and 80% of Brazilian...

We present a medium-scale dynamic factor model to estimate and forecast the rate of growth of the Spanish economy in the very short term. The intermediate size of the model overcomes the serious specification problems associated with large scale-models and the implicit loss of information of...

Modelling the dynamics of credit derivatives is a challenging task in finance and economics. The recent crisis has shown that the standard market models fail to measure and forecast financial risks and their characteristics. This work studies risk of collateralized debt obligations (CDOs) by...

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...

After decades of rising global economic integration, the world economy is now fragmenting. To measure this phenomenon, we introduce an index of geopolitical fragmentation derived from various empirical indicators. This index is developed using a flexible dynamic factor model with time-varying...

In this paper, we develop and apply Bayesian inference for an extended Nelson-Siegel (1987) term structure model capturing interest rate risk. The so-called Stochastic Volatility Nelson-Siegel (SVNS) model allows for stochastic volatility in the underlying yield factors. We propose a Markov...

This study utilizes the dynamic factor model of Giannone et al. (2008) in order to make now-/forecasts of GDP quarter-on-quarter growth rates in Switzerland. It also assesses the informational content of macroeconomic data releases for forecasting of the Swiss GDP. We find that the factor model...