Li, S., Hoque, H. and Thijssen, J. (2021) Firm financial behaviour dynamics and interactions: a structural vector autoregression approach. Journal of Corporate Finance, 69. 102028. ISSN 0929-1199
Abstract
This paper investigates the dynamic interactions of firms' financial behaviours using a five-variable structural vector autoregression (SVAR) framework. We provide empirical evidence that firms' financial behaviours are jointly determined. We demonstrate that a single-equation analysis on one financial behaviour generates biased estimates. We find that firms deviate from the desired level of each financial characteristic to absorb shocks to the other financial characteristics. Following such deviations, the characteristics revert in subsequent periods. Among these inter-related financial behaviours, equity decisions are the most independent, followed by dividend target, investment, and leverage target. Although firms prioritize financial behaviours differently, it appears that there is neither one financial behaviour that firms use only to absorb shocks nor one that never responds to the others.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2021 Elsevier. This is an author produced version of a paper subsequently published in Journal of Corporate Finance. Uploaded in accordance with the publisher's self-archiving policy. Article available under the terms of the CC-BY-NC-ND licence (https://creativecommons.org/licenses/by-nc-nd/4.0/). |
Keywords: | Firm financial behaviours; Interactions; Structural vector autoregression; Priority; Impulse response |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Social Sciences (Sheffield) > Management School (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 19 Oct 2023 14:35 |
Last Modified: | 19 Oct 2023 14:35 |
Status: | Published |
Publisher: | Elsevier BV |
Refereed: | Yes |
Identification Number: | 10.1016/j.jcorpfin.2021.102028 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:204416 |