Policy implications of the Lucas Critique empirically tested along the global financial crisis
Amira Karimova,
Esra Simsek and
Mehmet Orhan
Journal of Policy Modeling, 2020, vol. 42, issue 1, 153-172
Abstract:
This study is the first attempt to facilitate the substantial change in post-crisis monetary policy of the Fed to test the validity of Lucas Critique toward exploring implications of such changes for policymaking. Global financial crisis, asking for fundamental regime alterations presented an invaluable opportunity to test the empirical validity of Lucas Critique. We make use of quarterly US data over 1990–2015 to test for superexogeneity, the rejection of which lends support to Lucas Critique. We define the marginal models for wealth, GDP and Treasury Bill rate to construct the conditional model of money demand following Hendry (1988). Our results reject superexogeneity of the policies and report the support for Lucas Critique. We discuss about the details and consequences of the monetary policy followed to suggest arguments to prolonging debates on policy discussions.
Keywords: Lucas Critique; Monetary policy; Superexogeneity; Invariance; Rational expectations (search for similar items in EconPapers)
JEL-codes: C22 C52 E41 E42 E52 E58 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0161893819300870
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:jpolmo:v:42:y:2020:i:1:p:153-172
DOI: 10.1016/j.jpolmod.2019.06.003
Access Statistics for this article
Journal of Policy Modeling is currently edited by A. M. Costa
More articles in Journal of Policy Modeling from Elsevier
Bibliographic data for series maintained by Catherine Liu ().