The authors use first differenced logged quarterly series for the GDP of 29 countries and the euro area to assess the need to use nonlinear models to describe business cycle dynamic behaviour. Their approach is model (estimation)-free, based on testing only. The authors aim to maximize power to...

The authors use first differenced logged quarterly series for the GDP of 29 countries and the euro area to assess the need to use nonlinear models to describe business cycle dynamic behaviour. Their approach is model (estimation)-free, based on testing only. The authors aim to maximize power to...

In this paper we contrast a number of univariate models of Canadian GDP. We find that non-linear models are prefered to linear models, and that the most recent recession in Canada was unique in both its length and in the slow speed of recovery. We also briefly explore the link between stages of...

We address the question of whether asymmetry in the business cycle and asymmetry in the persistence of negative versus positive shocks characteries Australian output growth. Using nonlinear time series models we provide evidence that suggests Australian output growth is characterised by three...

We propose an event-study research design to identify the nature and propagation of large unusual shocks in DSGE models and apply it to study the macroeconomic effects of the Covid shock. The initial outbreak is represented as the onset of a new shock process where the shock loads on wedges...

This paper estimates a medium-scale DSGE model with search unemployment by matching model and data spectra. Price mark-up shocks emerge as the main source of business-cycle fluctuations in the euro area. Key factors in the propagation of these disturbances are a high degree of inflation...

We characterise the behaviour of Norwegian output, the real exchange rate and real money balances over a period of almost two centuries. The empirical analysis is based on a new annual data set that has recently been compiled and covers the period 1830-2003. We apply multivariate linear and...

Machine Learning models are often considered to be "black boxes" that provide only little room for the incorporation of theory (cf. e.g. Mukherjee, 2017; Veltri, 2017). This article proposes so-called Dynamic Factor Trees (DFT) and Dynamic Factor Forests (DFF) for macroeconomic forecasting, which...

This paper estimates a medium-scale DSGE model with search unemployment by matching model and data spectra. Price mark-up shocks emerge as the main source of business-cycle fluctuations in the euro area. Key factors in the propagation of these disturbances are a high degree of inflation...