(untitled) (gjstudies, 2022)
This research investigates the nuanced relationship between financial reportingquality 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 methodologytreats financial reports as complex information systems rather than mere compliancedocuments, allowing us to capture qualitative dimensions of reporting that quantitative accruals models typically overlook. We construct a unique dataset spanning1995-2004, comprising 2,500 U.S. public companies, and employ a hybrid analyticalframework combining natural language processing for narrative sections, graph theoryfor footnote interconnections, and traditional financial ratio analysis. Our findingsreveal three distinctive contributions: first, we identify a non-linear threshold effectwhere reporting quality improvements significantly reduce financing costs only beyonda certain coherence threshold; second, we demonstrate that semantic consistency between management discussion and financial footnotes matters more for debt financingcosts than for equity; third, we uncover a network effect where companies with centrallypositioned reporting practices within industry clusters enjoy financing advantages independent of their absolute reporting quality. These insights challenge conventionallinear 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 understandingof how specific reporting dimensions differentially influence various financing channels, while providing scholars with a methodological framework for analyzing financialdocuments as complex, interconnected information networks rather than isolated datasources.