Designing an investment strategy in transition economies is a difficult task, because stock markets opened through time, time series are short, and there is little guidance how to obtain expected returns and covariance matrices necessary for mean-variance asset allocation. Moments of market...

When supervisors have imperfect information about the soundness of banks, they may be unaware of insolvency problems that develop in the interval between on-site examinations. Supervising banks more often will alleviate this problem but will increase the costs of supervision. This paper analyzes...

In this paper, we attempt to analyse the relationship between house price developments and the business cycle. Employing a time-varying transition probability Markov switching framework, we provide empirical evidence that house price growth may prove a useful leading indicator for turning point...

This paper quantifies the effects on welfare of misspecified monetary policy objectives in a stylized DSGE model. We show that using inappropriate objectives generates relatively large welfare costs. When expressed in terms of ‘consumption equivalent’ units, these costs correspond to...

In this paper we provide a unified methodology for conducting likelihood-based inference on the unknown parameters of a general class of discrete-time stochastic volatility (SV) models, characterized by both a leverage effect and jumps in returns. Given the nonlinear/non-Gaussian state-space...

In this paper we argue that banks anticipate short-term market rates when setting interest rates on loans and deposits. In order to include anticipated rates in an empirical model, we use two methods to forecast market rates - a level, slope, curvature model and a principal components model -...

Standard practice for the estimation of dynamic stochastic general equilibrium (DSGE) models maintains the assumption that economic variables are properly measured by a single indicator, and that all relevant information for the estimation is summarized by a small number of data series. However,...

We propose a new filtering and smoothing technique for non-linear state-space models. Observed variables are quadratic functions of latent factors following a Gaussian VAR. Stacking the vector of factors with its vectorized outer-product, we form an augmented state vector whose first two...