There is an immense body of literature on the relationship of money and output, with result-integrity depending on the aggregates used. This paper proposes an alternative two-step approach, based on the reality that: (1) money creation is just the outcome of new bank loans extended, and (2) the...

Over the last two decades the intensity of credit standards' tightening during economic contractions has exceeded their easing during expansions among euro area banks. This mechanism is fed by the boom-bust cycle of credit that, as much research has shown, is linked to financial instability with...

Starting in the mid 1980s, the level and volatility of inflation decreased across industrial countries. The inflation stabilization can be explained by a shift in monetary policy or by a lucky period of low volatility in business cycle shocks. To test the "good luck hypothesis", we examine the...

Forecasting banking system liquidity is crucial for the effective monetary policy implementation. This study investigates the effectiveness of various econometric and machine learning models in predicting the autonomous factors of banking system liquidity. The research compares widely used...

The inference for hidden Markov chain models in which the structure is a multiple-equation macroeconomic model raises a number of difficulties that are not as likely to appear in smaller models. One is likely to want to allow for many states in the Markov chain without allowing the number of...

When impulse responses in dynamic multivariate models such as identified VARs are given economic interpretations, it is important that reliable statistical inferences be provided. Before probability assessments are provided, however, the model must be normalized. Contrary to the conventional...

Multivariate dynamic time series models are widely encountered in practical studies, e.g., modelling policy transmission mechanism and measuring connectedness between economic agents. To better capture the dynamics, this paper proposes a wide class of multivariate dynamic models with time —...

We propose a statistical identification procedure for structural vector autoregressive (VAR) models that present a nonlinear dependence (at least) at the contemporaneous level. By applying and adapting results from the literature on causal discovery with continuous additive noise models to...

We propose a methodology for producing forecast densities for economic aggregates based on disaggregate evidence. Our ensemble predictive methodology utilizes a linear mixture of experts framework to combine the forecast densities from potentially many component models. Each component represents...

We propose a methodology for producing forecast densities for economic aggregates based on disaggregate evidence. Our ensemble predictive methodology utilizes a linear mixture of experts framework to combine the forecast densities from potentially many component models. Each component represents...