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...

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...

This article provides a comprehensive econometric analysis of factors driving aggregate mortality rates over time. It differs from previous studies in this field by simultaneously considering an extensive set of macroeconomic, socio-economic and ecological factors as explanatory variables....

We use a Bayesian dynamic factor model to measure Germanys pre WorldWar I economic activity. The procedure makes better use of existing time seriesdata than historical national accounting. To investigate industrializationwe propose to look at comovement between sectors. We find that...

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...

This paper discusses the paper "The Source of Historical Economic Fluctuations: An Analysis using Long-Run Restrictions" by Neville Francis and Valerie A. Ramey. It argues that these authors have made great progress both in the precise measurement of labor input as well as determining the effect...

The paper develops a non-parametric, non-stationary framework for business-cycle dating based on an innovative statistical methodology known as Adaptive Weights Smoothing (AWS). The methodology is used both for the study of the individual macroeconomic time series relevant to the dating of the...

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...