Template-Type: ReDIF-Paper 1.0
Author-Name: Kaashoek, J.F.
Author-Name-Last: Kaashoek
Author-Name-First: Johan
Author-Name: van Dijk, H.K.
Author-Name-Last: van Dijk
Author-Name-First: Herman
Author-Person: pva325
Title: Neural networks as econometric tool
Abstract: The flexibility of neural networks to handle complex data patterns of economic variables is well known. In this survey we present a brief introduction to a neural network and focus on two aspects of its flexibility . First, a neural network is used to recover the dynamic properties of a nonlinear system, in particular, its stability by making use of the Lyapunov exponent. Second, a two-stage network is introduced where the usual nonlinear model is combined with time transitions, which may be handled by neural networks. The connection with time-varying smooth transition models is indicated. The procedures are illustrated using three examples: a structurally unstable chaotic model, nonlinear trends in real exchange rates and a time-varying Phillips curve using US data from 1960-1997.
Creation-Date: 2001-02-19
File-URL: https://repub.eur.nl/pub/1670/feweco20010219155055.pdf
File-Format: application/pdf
Series: RePEc:ems:eureir
Number: EI 2001-05
Keywords: Exchange rates, Neural networks, Nonlinear dynamics, Phillips curve
Handle: RePEc:ems:eureir:1670