Experts often add domain knowledge to model-based forecasts while aiming to reduce forecast errors. Indeed, there is some empirical evidence that expert-adjusted forecasts improve forecast quality. However, surprisingly little is known about what experts actually do. Based on a large and...

This paper conjectures that the behaviour of experts who adjust statistical-model-based forecasts obeys the Law of Small Numbers [LSN]. To put this hypothesis to an empirical test, I propose a simple but effective methodology. It is applied to a database containing information on many experts...

This paper builds on De Groot and Franses (2005) (Econometric Institute Report 2005-01). It modifies the EICIE, the Econometric Institute Current Indicator of the Economy, by allowing for two regimes. These regimes are marked by positive or negative annual growth in the staffing services data....

We develop a method which measures the effect of the major international conventions in the area of safety, pollution, search and rescue and work related measures. We further distinguish between the effect of entry into force and the status of ratification of a convention by its parties. We use...

Two important empirical features of monthly US unemployment are that shocks to the series seem rather persistent and that unemployment seems to rise faster in recessions than that it falls during expansions. To jointly capture these features of long memory and nonlinearity, respectively, we put...

This paper develops a return forecasting methodology that allows for instabil ity in the relationship between stock returns and predictor variables, for model uncertainty, and for parameter estimation uncertainty. The predictive regres sion speci¯cation that is put forward allows for...

We develop a parsimonious panel model for quarterly regional house prices, for which both the cross-section and the time series dimension is large. The model allows for stochastic trends, cointegration, cross-equation correlations and, most importantly, latent-class clustering of regions. Class...

We consider the problem of testing for seasonal unit roots in monthly panel data. To this aim, we generalize the quarterly CHEGY test to the monthly case. This parametric test is contrasted with a new nonparametric test, which is the panel counterpart to the univariate RURS test that relies on...

In this chapter we use a simulation experiment to examine whether the seasonal adjustment methods Census X12-ARIMA and TRAMO/SEATS effectively remove seasonality properties from time series data, while preserving other features like the stochastic trend. As data generating processes we use a...

In this paper we develop a new semi-parametric model for conditional correlations, which combines parametric univariate GARCH-type specifications for the individual conditional volatilities with nonparametric kernel regression for the conditional correlations. This approach not only avoids the...