This paper examines whether the presence of parameter instabilities in dynamic stochastic general equilibrium (DSGE) models affects their forecasting performance. We apply this analysis to medium-scale DSGE models with and without financial frictions for the US economy. Over the forecast period...

Inflation has been persistently weak in the euro area despite the economic recovery since 2013. We investigate the sources behind this protracted low inflation by building a time-varying parameter model that jointly explains the dynamics of inflation and inflation expectations from the ECB's...

In the last two decades, advances in globalization have evolved remarkably and countries have become more integrated with the entire world. The implications of this process have attracted interest of researchers and monetary policy authorities. This paper provides an assessment of the impact of...

Economists typically make simplifying assumptions to make the solution and estimation of their highly complex models feasible. These simplifications include approximating the true nonlinear dynamics of the model, disregarding aggregate uncertainty or assuming that all agents are identical. While...

We propose a new Bayesian VAR model for forecasting household loan stocks in Finland. The model is designed to work as a satellite model of a larger DSGE model for the Finnish economy, the Aino 2.0 model. The forecasts produced with the BVAR model can be conditioned on projections of several...

Prediction markets for future events are increasingly common and they often trade several contracts for the same event. This paper considers the distribution of a normative risk-neutral trader who, given any portfolio of contracts traded on the event, would choose not to reallocate that...

Very often in actual macroeconomic time series there are causes that disrupt the underlying stochastic process and their treatment is known as «linearization». In addition, variance non-stationarity is in many cases also present in such series and is removed by proper data transformation. The...

This document provides an overview of the StMAR Toolbox, a MATLAB toolbox specifically designed for simulation, estimation, diagnostic, and forecasting of the Student's t mixture autoregressive (StMAR) model proposed by Meitz, Preve & Saikkonen (2018). The StMAR model is a new type of mixture...

This paper proposes an accurate, parsimonious and fast-to-estimate forecasting model for integer-valued time series with long memory and seasonality. The modelling is achieved through an autoregressive Poisson process with a predictable stochastic intensity that is determined by two factors: a...

One of the most important risks in the actuarial industry is the longevity risk. The accurate prediction of mortality rates plays a crucial role in the management of the aforementioned risk. Such predictions are performed by modelling the mortality rates using mortality models. Aiming at...