Journal of Finance and Data Science (Nov 2022)

A causal approach to test empirical capital structure regularities

  • Simone Cenci,
  • Stephen Kealhofer

Journal volume & issue
Vol. 8
pp. 214 – 232

Abstract

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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.

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