Experts may have domain-specific knowledge that is not included in a statistical model and that can improve forecasts. While one-step-ahead forecasts address the conditional mean of the variable, model-based forecasts for longer horizons have a tendency to convert to the unconditional mean of a...

Using a standard 4-variable linear vector error correction model (VECM), we first show that the null hypothesis of linearity can be strongly rejected against the alternative of smooth transition autoregressive nonlinearity. An important result from this stage of the analysis is that the...

This paper proposes a methodology to jointly generate optimal forecasts from an autoregression of order p for 1 to h steps ahead. The relevant model is a Partial Least Squares Autoregression, which is positioned in between a single AR(p) model for all forecast horizons and different AR models...

In this paper we put forward a new time series model, which describes nonlinearity and seasonality simultaneously. We discuss its representation, estimation of the parameters and inference. This seasonal STAR (SEASTAR) model is examined for its practical usefulness by applying it to 18 quarterly...

We propose a simulation-based technique to calculate impulse-response functions and their confidence intervals in a market share attraction model [MCI]. As an MCI model implies a reduced form model for the logs of relative market shares, simulation techniques have to be used to obtain the...

This paper surveys recent developments related to the smooth transition autoregressive [STAR] time series model and several of its variants. We put emphasis on new methods for testing for STAR nonlinearity, model evaluation, and forecasting. Several useful extensions of the basic STAR model,...

Collectible postage stamp prices in the Netherlands witnessed a bubble in the late 1970’s, while prices rapidly floored in the mid 1980’s. We analyze 500 individual stamps prices (instead of a single index) to examine if the bubble could somehow have been predicted and whether there were...

This paper presents the results of a survey held amongst all editorial board members of six journals. These journals in part focus on the development of models and methods for forecasting. The key question was whether one believes that the forecasting discipline has made progress in the last...

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 business and in macroeconomics it is common practice to use econo- metric models to generate forecasts. These models can take any degree of sophistication. Sometimes it is felt by an expert that the model-based fore- cast needs adjustment. This paper makes a plea for a formal approach to such...