Financial Reporting Quality Influence on Corporate Cost of Financing

Abstract

This research investigates the nuanced relationship between financial reporting
quality and corporate cost of financing through a novel methodological lens that integrates computational linguistics, network theory, and historical financial data analysis.
Departing from traditional regression-based approaches that dominate the literature,
we develop a multi-dimensional quality index derived from textual analysis of annual reports, semantic coherence metrics, and disclosure network centrality. Our methodology
treats financial reports as complex information systems rather than mere compliance
documents, allowing us to capture qualitative dimensions of reporting that quantitative accruals models typically overlook. We construct a unique dataset spanning
1995-2004, comprising 2,500 U.S. public companies, and employ a hybrid analytical
framework combining natural language processing for narrative sections, graph theory
for footnote interconnections, and traditional financial ratio analysis. Our findings
reveal three distinctive contributions: first, we identify a non-linear threshold effect
where reporting quality improvements significantly reduce financing costs only beyond
a certain coherence threshold; second, we demonstrate that semantic consistency between management discussion and financial footnotes matters more for debt financing
costs than for equity; third, we uncover a network effect where companies with centrally
positioned reporting practices within industry clusters enjoy financing advantages independent of their absolute reporting quality. These insights challenge conventional
linear models of the reporting-quality relationship and suggest that strategic positioning within disclosure ecosystems may be as important as intrinsic reporting quality.
Our approach offers financial managers and regulators a more granular understanding
of how specific reporting dimensions differentially influence various financing channels, while providing scholars with a methodological framework for analyzing financial
documents as complex, interconnected information networks rather than isolated data
sources.