Modelling causality in nonstationary variances with an application to carbon markets

Susana Campos-Martins () and Cristina Amado ()
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Susana Campos-Martins: NIPE/Centre for Research in Economics and Management, University of Minho; and Católica Lisbon School of Business & Economics
Cristina Amado: NIPE/Centre for Research in Economics and Management, University of Minho, Portugal

No 13/2023, NIPE Working Papers from NIPE - Universidade do Minho

Abstract: In this paper we propose a multivariate generalisation of the multiplicative decomposition of the volatility within the class of conditional correlation GARCH models. The GARCH variance equations are multiplicatively decomposed into a deterministic nonstationary component describing the long-run movements in volatility and a short-run dynamic component allowing for volatility spillover effects across markets or assets. The conditional correlations are assumed to be time-invariant in its simplest form or generalised into a flexible dynamic parameterisation. Parameters of the model are estimated equation-by-equation by maximum likelihood applying the maximisation by parts algorithm to the variance equations, and thereafter to the structure of conditional correlations. An empirical application using carbon markets data illustrates the usefulness of the model. Our results suggest that, after modelling the variance equations accordingly, we find evidence that the transmission mechanism of shocks persists which is supported by the presence of variance interactions robust to nonstationarity.

Keywords: Variance interactions; Nonstationarity; Short- and long-term volatility; Lagrange multiplier test. (search for similar items in EconPapers)
JEL-codes: C12 C13 C32 C51 (search for similar items in EconPapers)
Date: 2023
New Economics Papers: this item is included in nep-ecm and nep-ets
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