Pre-election polls can suffer from survey effects. For example, surveyed individuals can become more aware of the upcoming election so that they become more inclined to vote. These effects may depend on factors like political orientation and prior intention to vote, and this may cause biases in...

Pre-election polls can suffer from survey effects. For instance, individuals taking part in the poll may become more aware of the upcoming election so that they become more inclined to vote. Such effects cause biases in forecasted outcomes of elections. We propose a simple methodology that takes...

Direct extrapolation of survey results on purchase intentions may give a biased view on actual consumer behavior. This is because the purchase intentions of consumers may be affected by the survey itself. On the positive side, such effects can be incorporated in econometric models to get...

We propose to estimate the parameters of the Market Share Attraction Model (Cooper & Nakanishi, 1988; Fok & Franses, 2004) in a novel way by using a non-parametric technique for function estimation called Support Vector Regressions (SVR) (Vapnik, 1995; Smola, 1996). Traditionally, the parameters of the...

Regime-switching models, like the smooth transition autoregressive (STAR) model are typically applied to time series of moderate length. Hence, the nonlinear features which these models intend to describe may be reflected in only a few observations. Conversely, neglected outliers in a linear...

The accuracy of real-time forecasts of macroeconomic variables that are subject to revisions may crucially depend on the choice of data used to compare the forecasts against. We put forward a flexible time-varying parameter regression framework to obtain early estimates of the final value of...

A key feature of many nonlinear time series models is that they allow for the possibility that the model structure experiences changes, depending on for example the state of the economy or of the financial market. A common property of these models is that it generally is not possible to fully...

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...

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...