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Are Small-Scale SVARs Useful for Business Cycle Analysis? Revisiting Nonfundamentalness

Canova, Fabio, Hamidi Sahneh, Mehdi (2018) Are Small-Scale SVARs Useful for Business Cycle Analysis? Revisiting Nonfundamentalness. Journal of the European Economic Association, 16 (4). pp. 1069-1093. ISSN 1542-4766. E-ISSN 1542-4774. (doi:10.1093/jeea/jvx032) (KAR id:64222)

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http://dx.doi.org/10.1093/jeea/jvx032

Abstract

Nonfundamentalness arises when current and past values of the observables do not contain enough information to recover structural vector autoregressive (SVAR) disturbances. Using Granger causality tests, the literature suggested that several small-scale SVAR models are nonfundamental and thus not necessarily useful for business cycle analysis. We show that causality tests are problematic when SVAR variables cross-sectionally aggregate the variables of the underlying economy or proxy for nonobservables. We provide an alternative testing procedure, illustrate its properties with Monte Carlo simulations, and re-examine a prototypical small-scale SVAR model.

Item Type: Article
DOI/Identification number: 10.1093/jeea/jvx032
Uncontrolled keywords: C32 - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space ModelsC5 - Econometric ModelingE5 - Monetary Policy, Central Banking, and the Supply of Money and Credit
Subjects: H Social Sciences
Divisions: Faculties > Social Sciences > School of Economics
Depositing User: Mehdi Hamidi Sahneh
Date Deposited: 02 Nov 2017 15:10 UTC
Last Modified: 06 May 2020 03:16 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/64222 (The current URI for this page, for reference purposes)
Hamidi Sahneh, Mehdi: https://orcid.org/0000-0003-3425-6824
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