By using a unique data set of single-family house transactions, we examine theaccuracy of the cost and sales comparison approach over different forecast horizons. We find that sales comparison values provide better long-term forecaststhan cost values if the economic loss function is symmetric. A...

Two main hypotheses are usually put forward to explain the productivity advantages of larger cities: agglomeration economies and firm selection. Combes et al. (2012) propose an empirical approach to disentangle these two effects and fail to find any impact of selection on local productivity...

This paper proposes the use of Bayesian model averaging (BMA) as a tool to select the predictors' set for bridge models. BMA is a computationally feasible method that allows us to explore the model space even in the presence of a large set of candidate predictors. We test the performance of BMA...

Dimension reduction techniques for functional data analysis model and approximate smooth random functions by lower dimensional objects. In many applications the focus of interest lies not only in dimension reduction but also in the dynamic behaviour of the lower dimensional objects. The most...

Over recent years, study on risk management has been prompted by the Basel committee for regular banking supervisory. There are however limitations of some widely-used risk management methods that either calculate risk measures under the Gaussian distributional assumption or involve numerical...

Risk management technology applied to high dimensional portfolios needs simple and fast methods for calculation of Value-at-Risk (VaR). The multivariate normal framework provides a simple off-the-shelf methodology but lacks the heavy tailed distributional properties that are observed in data. A...

The aim of the paper is to understand the interaction between market and credit risk. Using a comprehensive set of Italian data, we apply a factor model to identify the common sources of risk driving fluctuations in the real and financial sectors. The common latent factors are then inserted in a...

We estimate a Bayesian VAR with a detailed characterization of the banking sector for Italy since the 1990s. We use conditional forecasting techniques to retrieve bank capital shocks related to regulatory and supervisory initiatives and quantify their impact on credit supply and economic...

Forecasting inflation is an important and challenging task. In this paper we assume that the core inflation components evolve as a multivariate local level process. This model, which is theoretically attractive for modelling inflation dynamics, has been used only to a limited extent to date...