http://repub.eur.nl/res/aut/10552/ List of Publications en http://repub.eur.nl/static-eur/img/logo.png http://repub.eur.nl http://repub.eur.nl/res/pub/18164/ 2009-04-01T00:00:00Z This Special Issue brings together a selection of the papers presented at the third conference in the Economic and Social Research Council (ESRC) Seminar series “Nonlinear Economics and Finance Research Community”, as well as a number of other related contributions. This Conference took place at Keele University (UK) on the 1st of February 2008, and was hosted by Christopher Martin (Brunel University), Costas Milas (Keele University) and Theodore Panagiotidis (University of Macedonia), with funding from the ESRC under grant RES-451-25-4260. The aim of the seminar series is to bring together researchers working on nonlinear topics in economics and finance http://repub.eur.nl/res/pub/2169/ 2004-04-01T00:00:00Z In this paper we discuss the current state-of-the-art in estimating, evaluating, and selecting among non-linear forecasting models for economic and financial time series. We review theoretical and empirical issues, including predictive density, interval and point evaluation and model selection, loss functions, data-mining, and aggregation. In addition, we argue that although the evidence in favor of constructing forecasts using non-linear models is rather sparse, there is reason to be optimistic. However, much remains to be done. Finally, we outline a variety of topics for future research, and discuss a number of areas which have received considerable attention in the recent literature, but where many questions remain. http://repub.eur.nl/res/pub/11145/ 2003-08-01T00:00:00Z We compare linear autoregressive (AR) models and self-exciting threshold autoregressive (SETAR) models in terms of their point forecast performance, and their ability to characterize the uncertainty surrounding those forecasts, i.e. interval or density forecasts. A two-regime SETAR process is used as the data-generating process in an extensive set of Monte Carlo simulations, and we consider the discriminatory power of recently developed methods of forecast evaluation for different degrees of non-linearity. We find that the interval and density evaluation methods are unlikely to show the linear model to be deficient on samples of the size typical for macroeconomic data. http://repub.eur.nl/res/pub/1567/ 1999-03-12T00:00:00Z We consider the usefulness of the two-regime SETAR model for out-of-sample forecasting, and compare it with a linear AR model. A range of newly-developed forecast evaluation techniques are employed. Our simulation results show that time-series data need to exhibit a substantial degree of non-linearity before the SETAR model is favoured on some of these criteria. We find only weak evidence that a SETAR model of US GNP provides more accurate forecasts than a linear AR model.