Block-recursive non-Gaussian structural vector autoregressions

Autor:	Keweloh, Sascha Alexander, Hetzenecker, Stephan, Seepe, Andre
Jazyk:	angličtina
Rok vydání:	2021
Předmět:	SVAR non-Gaussianity monetary policy block-recursive identification stock market
Popis:	This study combines block-recursive restrictions with higher-order moment conditions to identify and estimate non-Gaussian structural vector autoregressions. The estimator allows to impose a block-recursive structure on the SVAR and for a given block-recursive structure we derive a conservative set of assumptions on the dependence and Gaussianity of the shocks to ensure identification. We use a Monte Carlo simulation to illustrate the advantages of the proposed blockrecursive estimator compared to unrestricted, purely data driven estimators in small samples. The block-recursive estimator is used to analyze the interdependence of monetary policy and the stock market. We find that a positive stock market shock contemporaneously increases the nominal interest rate, while contractionary monetary policy shocks lead to lower stock returns on impact. Discussion Paper / SFB823;23/2021
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b4d65f7e95d887fbb08f782da4036ff9 http://hdl.handle.net/2003/40548 Zobrazit plný text záznamu