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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Official URL: 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 |
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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: | Divisions > Division of Human and Social Sciences > School of Economics |
Depositing User: | Mehdi Hamidi Sahneh |
Date Deposited: | 02 Nov 2017 15:10 UTC |
Last Modified: | 05 Nov 2024 11:00 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/64222 (The current URI for this page, for reference purposes) |
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