In the Industrial Production Index the main source of non-linearity is given by the asymmetric nature of the business cycle. Evidence of conditional heteroskedasticity in the Industrial Production Index series has been found by some authors (e.g. Byers and Peel, 1995). The approach we propose in this paper allows having asymmetric effects present not only in the level but also in the conditional variance component. The main intuition behind this is that a negative shock, corresponding to a decrease in the industrial production level, is expected to have an effect on the volatility of the series which is greater than that due to a positive shock, corresponding to an increase in the industrial production level, of the same magnitude. In particular we combine a threshold model for the conditional mean with a Constrained Changing Parameters Volatility (CPV-C) model, recently proposed by Storti (1999). The predictive performance of the model is assessed by means of some measures of goodness of fit. The results are compared by those obtained by a model including a simple linear autoregressive component for the conditional mean together with a CPV model for the conditional variance of the series.

Non-linear Dynamics in the Industrial Production Index

AMENDOLA, Alessandra;STORTI, Giuseppe
2004

Abstract

In the Industrial Production Index the main source of non-linearity is given by the asymmetric nature of the business cycle. Evidence of conditional heteroskedasticity in the Industrial Production Index series has been found by some authors (e.g. Byers and Peel, 1995). The approach we propose in this paper allows having asymmetric effects present not only in the level but also in the conditional variance component. The main intuition behind this is that a negative shock, corresponding to a decrease in the industrial production level, is expected to have an effect on the volatility of the series which is greater than that due to a positive shock, corresponding to an increase in the industrial production level, of the same magnitude. In particular we combine a threshold model for the conditional mean with a Constrained Changing Parameters Volatility (CPV-C) model, recently proposed by Storti (1999). The predictive performance of the model is assessed by means of some measures of goodness of fit. The results are compared by those obtained by a model including a simple linear autoregressive component for the conditional mean together with a CPV model for the conditional variance of the series.
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11386/1062329
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? 0
social impact