This paper estimates and tests a new Keynesian small open economy model in the tradition of Christiano, Eichenbaum, and Evans (2005) and Smets and Wouters (2003) using Bayesian estimation techniques on Swedish data. To account for the switch to an inflation targeting regime in 1993 we allow for...

In this paper we develop a dynamic stochastic general equilibrium (DSGE) model for an open economy, and estimate it on Euro area data using Bayesian estimation techniques. The model incorporates several open economy features, as well as a number of nominal and real frictions that have proven to...

We show how to construct optimal policy projections in Ramses, the Riksbank's open economy medium-sized DSGE model for forecasting and policy analysis. Bayesian estimation of the parameters of the model indicates that they are relatively invariant to alternative policy assumptions and supports...

There are many indications that formal methods are not used to their full potential by central banks today. In this paper we demonstrate how BVAR and DSGE models can be used to shed light on questions that policy makers deal with in practice using data from Sweden. We compare the forecast...

We evaluate forecasts made in real time to support monetary policy decisions at Sveriges Riksbank (the central bank of Sweden) from 2007 to 2013. We compare forecasts made with a DSGE model and a BVAR model with judgemental forecasts published by the Riksbank, and we evaluate the usefulness of...

We introduce time-varying systemic risk (à la He and Krishnamurthy, 2014) in an otherwise standard New-Keynesian model to study whether simple leaning-against-the-wind interest rate rules can reduce systemic risk and improve welfare. We find that while financial sector leverage contains...

This paper specifies a new convenient algorithm to construct policy projections conditional on alternative anticipated policy-rate paths in linearized dynamic stochastic general equilibrium (DSGE) models, such as Ramses, the Riksbank's main DSGE model. Such projections with anticipated...

We demonstrate improvements in predictive power when introducing spline functions to take account of highly non-linear relationships between firm failure and earnings, leverage, and liquidity in a logistic bankruptcy model. Our results show that modeling excessive non-linearities yields...

We model a regression density nonparametrically so that at each value of the covariates the density is a mixture of normals with the means, variances and mixture probabilities of the components changing smoothly as a function of the covariates. The model extends existing models in two important...

The degree of empirical support of a priori plausible structures on the cointegration vectors has a central role in the analysis of cointegration. Villani (2000) and Strachan and van Dijk (2003) have recently proposed finite sample Bayesian procedures to calculate the posterior probability of...