Many companies collect stated preference data (SP) like intentions and satisfaction as well as revealed preference data (RP) like actual purchasing behavior. It seems relevant to examine the predictive usefulness of this information for future revealed preferences, that is, customer behavior. In...

Macroeconomic time series such as total unemployment or total industrial production concern data which are aggregated across regions, sectors, or age categories. In this paper we examine if forecasts for these aggregates can be improved by considering panel models for the disaggregate series. As...

In this paper it is advocated to select a model only if it significantly contributes to the accuracy of a combined forecast. Using hold-out-data forecasts of individual models and of the combined forecast, a useful test for equal forecast accuracy can be designed. An illustration for real-time...

In this paper we consider empirical econometric models for nine brands of fast-moving nondurable consumer product using weekly observed scanning data on market share and distribution conditional on advertising, price, and promotion activities. Since the data show nonstationary characteristics,...

Seasonality often accounts for the major part of quarterly or monthly movements in detrended macro-economic time series. In addition, business cycle nonlinearity is a prominent feature of many such series too. A forecaster can nowadays consider a wide variety of time series models which describe...

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...

A key application of long memory time series models concerns inflation. Long memory implies that shocks have a long-lasting effect. It may however be that empirical evidence for long memory is caused by neglecting one or more level shifts. Since such level shifts are not unlikely for inflation,...

Earnings management to avoid earnings decreases and losses implies that the time series properties of the last quarter in the fiscal year differ from those of the other three quarters. We propose a simple parametric methodology to diagnose such differences. Application to a random sample of 390...

We propose a new and simple methodology to estimate the loss function associated with experts' forecasts. Under the assumption of conditional normality of the data and the forecast distribution, the asymmetry parameter of the lin-lin and linex loss function can easily be estimated using a linear...

We propose a multivariate nonlinear econometric time series model, which can be used to examine if there is common nonlinearity across economic variables. The model is a multivariate censored latent effects autoregression. The key feature of this model is that nonlinearity appears as separate...