Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/23167
Authors: 
Clements, Michael P.
Franses, Philip Hans
Swanson, Norman R.
Year of Publication: 
2003
Series/Report no.: 
Working papers / Rutgers University, Department of Economics 2003,09
Abstract: 
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.
Document Type: 
Working Paper

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