This paper discusses identification, specification, estimation and forecasting for a general class of periodic unobserved components time series models with stochastic trend, seasonal and cycle components. Convenient state space formulations are introduced for exact maximum likelihood...

This paper investigates uncertainty around point estimates of the German NAIRU in a state space framework. The relative accuracy of alternative MSE approximations for the states is compared using Monte Carlo simulations. A bootstrap method yields confidence intervals with the highest coverage...

This paper reconciles two widely used trend-cycle decompositions of GDP that give markedly different estimates: the correlated unobserved components model yields output gaps that are small in amplitude, whereas the Hodrick-Prescott (HP) filter generates large and persistent cycles. By embedding...

A deep understanding of the drivers of credit risk is valuable for financial institutions as well as for regulators from multiple viewpoints. The systemic component of credit risk drives losses across portfolios and thus poses a threat to financial stability. Traditional approaches consider...

The term now-casting is a contraction for now and forecasting and has been used for a long-time in meteorology and recently also in economics. In this paper we survey recent developments in economic now-casting with special focus on those models that formalize key features of how market...

In this paper, the authors examine how well the Hodrick-Prescott (HP) and the band-pass filter recently proposed by Baxter and King (BK) extract the business-cycle component of macroeconomic time series. The authors assess these filters using two different definitions of the business-cycle...

We consider unobserved components time series models where the components are stochastically evolving over time and are subject to stochastic volatility. It enables the disentanglement of dynamic structures in both the mean and the variance of the observed time series. We develop a simulated...

This paper considers a sticky price model with a cash-in-advance constraint where agents forecast inflation rates with the help of econometric models. Agents use least squares learning to estimate two competing models of which one is consistent with rational expectations once learning is...

We describe and assess the usefulness of a newly-constructed database of electronic payments, comprised of debit and credit card transactions as well cheques that clear through the banking system, as indicators of current GDP growth. Apart from capturing a broad range of spending activity, these...

Forecasting economic activity during an invasion is a nontrivial exercise. The lack of timely statistical data and the expected nonlinear effect of military action challenge the use of established nowcasting and shortterm forecasting methodologies. In a recent study (Constantinescu (2023b)), I...