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Simulation Evidence on Theory‐based and Statistical Identification under Volatility Breaks
Author(s) -
Herwartz Helmut,
Plödt Martin
Publication year - 2016
Publication title -
oxford bulletin of economics and statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.131
H-Index - 73
eISSN - 1468-0084
pISSN - 0305-9049
DOI - 10.1111/obes.12098
Subject(s) - econometrics , autoregressive model , a priori and a posteriori , identification (biology) , volatility (finance) , monte carlo method , sign (mathematics) , heteroscedasticity , statistical theory , series (stratigraphy) , economics , monetary policy , computer science , mathematics , statistics , macroeconomics , mathematical analysis , paleontology , philosophy , botany , epistemology , biology
Abstract Beside a priori theoretical assumptions on instantaneous or long‐run effects of structural shocks, sign restrictions have become a prominent means for structural vector autoregressive (SVAR) analysis. Moreover, changes in second order moments of systems of time series can be fruitfully exploited for identification purposes in SVARs. By means of Monte Carlo studies, we examine to what degree theory‐based and statistical identification approaches offer an accurate quantification of the true structural relations in a standard model for monetary policy analysis. Subsequently, we discuss how identifying information from theory‐based and statistical approaches can be combined on the basis of a low‐dimensional empirical model of US monetary policy.