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A causal approach to test empirical capital structure regularities

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Title: A causal approach to test empirical capital structure regularities
Authors: Cenci, S
Kealhofer, S
Item Type: Journal Article
Abstract: Capital structure theories are often formulated as causal narratives to explain which factors drive financing choices. These narratives are usually examined by estimating cross–sectional relations between leverage and its determinants. However, the limitations of causal inference from observational data are often overlooked. To address this issue, we use structural causal modeling to identify how classic determinants of leverage are causally linked to capital structure and how this causal structure influences the effect-estimation process. The results provide support for the causal role of variables that measure the potential for information asymmetry concerning firms’ market values. Overall, our work provide a crucial step to connect capital structure theories with their empirical tests beyond simple correlations.
Issue Date: Nov-2022
Date of Acceptance: 9-Sep-2022
URI: http://hdl.handle.net/10044/1/105293
DOI: 10.1016/j.jfds.2022.09.002
ISSN: 2405-9188
Publisher: Elsevier BV
Start Page: 214
End Page: 232
Journal / Book Title: The Journal of Finance and Data Science
Volume: 8
Copyright Statement: © 2022 The Authors. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Publication Status: Published
Online Publication Date: 2022-09-16
Appears in Collections:Imperial College Business School



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