How the nature of inequality reduction matters for CO2 emissions

Tobias Angel, Alexandre Berthe, Valeria Costantini and Mariagrazia D’Angeli
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Tobias Angel: Università degli Studi Roma Tre and Université Paris Cité
Alexandre Berthe: Université Rennes 2 and LiRIS
Mariagrazia D’Angeli: Università degli Studi Roma Tre and SEEDS

No 2024.14, Working Papers from Fondazione Eni Enrico Mattei

Abstract: This paper presents new results on the identification of heteroskedastic structural vector autoregressive (HSVAR) models. Point identification of HSVAR models fails when some shifts in the variances of the structural shocks are suspected to be statistically indistinguishable from each other. This paper presents a new strategy that allows researchers to continue using HSVAR models in this empirically relevant case. We show that a combination of heteroskedasticity and zero restrictions can recover point identification in HSVAR models even in the absence of heterogeneous variance shifts. We derive the identified sets for impulse responses and show how to compute them. We perform inference on the impulse response functions, building on the robust Bayesian approach developed for set-identified SVARs. To illustrate our proposal, we present an empirical example based on the literature on the global crude oil market, where standard identification is expected to fail under heteroskedasticity.

Keywords: Inequality; Redistribution; Emissions; Climate Change; Social Protection (search for similar items in EconPapers)
JEL-codes: C33 D63 H23 Q54 (search for similar items in EconPapers)
Date: 2024-06
New Economics Papers: this item is included in nep-ene and nep-env
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Working Paper: How the nature of inequality reduction matters for CO2 emissions (2024)
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