Identifying Structural Vector Autoregressions Via Non-Gaussianity of Potentially Dependent Structural Shocks

Tutkimustuotos: Työpaperi › Tieteellinen

Alkuperäiskieli	englanti
Kustantaja	Social Sciences Research Network (SSRN)
DOI - pysyväislinkit	https://doi.org/10.2139/ssrn.4564713
Tila	Julkaistu - 2023
OKM-julkaisutyyppi	D4 Julkaistu kehittämis- tai tutkimusraportti taikka -selvitys

Tieteenalat

@techreport{a03930bfcb614d6a84d8c622ee213ff9,

title = "Identifying Structural Vector Autoregressions Via Non-Gaussianity of Potentially Dependent Structural Shocks",

keywords = "511 Economics",

author = "Markku Lanne and Keyan Liu and Jani Luoto",

year = "2023",

doi = "10.2139/ssrn.4564713",

language = "English",

publisher = "Social Sciences Research Network (SSRN)",

address = "United States",

type = "WorkingPaper",

institution = "Social Sciences Research Network (SSRN)",

}

TY - UNPB

T1 - Identifying Structural Vector Autoregressions Via Non-Gaussianity of Potentially Dependent Structural Shocks

AU - Lanne, Markku

AU - Liu, Keyan

AU - Luoto, Jani

PY - 2023

Y1 - 2023

KW - 511 Economics

U2 - 10.2139/ssrn.4564713

DO - 10.2139/ssrn.4564713

M3 - Working paper

BT - Identifying Structural Vector Autoregressions Via Non-Gaussianity of Potentially Dependent Structural Shocks

PB - Social Sciences Research Network (SSRN)

ER -