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Seasonal smooth transition autoregression

Franses, Ph.H.B.F.; Bruin, P. de; Dijk, D.J.C. van - Erasmus University Rotterdam, Econometric Institute - 2000

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 …

Persistent link: https://www.econbiz.de/10008465404

The forecasting performance of various models for seasonality and nonlinearity for quarterly industrial production

Franses, Ph.H.B.F.; Dijk, D.J.C. van - Erasmus University Rotterdam, Econometric Institute - 2001

. In addition, business cycle nonlinearity is a prominent feature of many such series too. A forecaster can nowadays … we examine the forecasting performance of various models for seasonality and nonlinearity using quarterly industrial …

Persistent link: https://www.econbiz.de/10008570605

Nonlinearities and outliers: robust specification of STAR models

Escribano, A.; Franses, Ph.H.B.F.; Dijk, D.J.C. van - Erasmus University Rotterdam, Econometric Institute - 1998

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

Persistent link: https://www.econbiz.de/10008584751

Neural networks as econometric tool

Kaashoek, J.F.; Dijk, H.K. van - Erasmus University Rotterdam, Econometric Institute - 2000

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...

Persistent link: https://www.econbiz.de/10008584789