we examine the forecasting performance of various models for seasonality and nonlinearity using quarterly industrial …. In addition, business cycle nonlinearity is a prominent feature of many such series too. A forecaster can nowadays … production series for 17 OECD countries. We find that forecasting performance varies widely across series, across forecast …

found to perform better in out-of-sample forecasting than a benchmark linear model. An empirical illustration for US GDP …

In this paper we put forward a new time series model, which describes nonlinearity and seasonality simultaneously. We …-transition nonlinearity and for time-varying seasonality. We find that the model fits the data well for 14 of the 18 series. We also consider … out-of-sample forecasting where we compare forecasts from the SEASTAR models with forecasts from nested models. It turns …

convenient framework for simultaneously handling nonlinearity, structural change and outliers in time series. Many popular …

We compare the forecasting performance of linear autoregressive models, autoregressive models with structural breaks … 2000. The results of point forecast evaluation tests support the established notion in the forecasting literature on the …

Outliers and nonlinearity may easily be mistaken. This paper uses Monte Carlo methods to examine and compare the …

nonlinearity. In this paper we propose outlier robust tests for STAR type nonlinearity. These tests are designed such that they … robust tests. An application to several quarterly industrial production indices illustrates that apparent nonlinearity in …