The aim of this paper is to propose new normalization schemes for the values obtained from thegeneralized forecast error variance decomposition, in order to obtain more reliable net spillovermeasures. We provide a review of various matrix normalization schemes used in different applicationdomains. The intention is to contribute to the financial econometrics literature aimed at building abridge between different approaches able to detect spillover effects, such as spatial regressions andnetwork analyses. Considering DGPs characterized by different degrees of correlation and persistence,we show that the popular row normalization scheme proposed by Diebold and Yilmaz (2012), as wellas the alternative column normalization scheme, may lead to inaccurate measures of net contributions(NET spillovers) in terms of risk transmission. Results are based on simulations and show that thenumber of errors increases as the correlation between the variable increases. The normalizationschemes we suggest overcome these limits.
|Number of pages||23|
|Publication status||Published - 2016|