Generalized Forecast Error Variance Decomposition for Linear and Nonlinear Multivariate Models

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What drives carbon dioxide emissions in the long-run? Evidence from selected South Asian Countries (2016, methodology): “The IAA provides prominent method of explaining the estimated linear and non-linear multivariate time series models (Ahmed et al., 2016d; Alves and Moutinho, 2013; Lanne and Nyberg, 2014; Shahbaz, 2015).”
Estimating the Real Effects of Uncertainty Shocks at the Zero Lower Bound (2017, unknown): “This way of modeling uncertainty is common in the literature (see, e.g., Bloom (2009), Caggiano, Castelnuovo, and Groshenny (2014), Leduc and Liu (2016)).”
Economic Policy Uncertainty Spillovers in Booms and Busts (2019, unknown): “We conduct the forecast error variance decomposition analysis by implementing the al-gorithm by Lanne and Nyberg (2016), who propose a generalized version of the forecast error variance decomposition for multivariate nonlinear models. o r Table 3 collects the ﬁgures related to the forecast error…”
How do normalization schemes affect net spillovers? A replication of the Diebold and Yilmaz (2012) study (2019, unknown): “…of each market is obtained as the difference between the directional spillovers TO others and FROM others: 𝑁𝐸𝑇𝑔(ℎ) = 𝐷𝑆 → 𝑔 (ℎ) − 𝐷𝑆→ 𝑔 (ℎ) (8) In this way, in line with Diebold and Yilmaz (2009, 2012, 2014) we are able to identify the markets that are net donors and those that are net…”