Biotech Firms' Financing and the Capitalism Model: A Historical Baseline (1997–2008) and an Updated Reading for the Post-Crisis Era[Le financement des entreprises biotechnologiques et le modèle de capitalisme : référence historique (1997-2008) et lecture actualisée pour l'ère post-crise]

This paper investigates whether the structural features of national capitalism — captured by the dichotomy between market-oriented (MOM) and bank-oriented (BOM) models — shape the financing decisions of innovative firms. Using an international panel of 1,064 listed biotechnology firms from 16 developed economies over the 1997–2008 period, drawn from Datastream / Thomson Financial, I estimate the determinants of stock issues (SI/TA) and of financial leverage (TD/TA) and contrast them across capitalism models. Three results stand out. First, operating cash flow and R&D intensity are positive and highly significant determinants of stock issues in both market-oriented sub-samples, while the same cash-flow effect is far weaker in bank-oriented economies — a contrast consistent with deeper equity-market support for high-burn biotech R&D in MOM systems. Second, several other determinants — the non-debt tax shield, sales intensity, historical risk and the financing deficit — enter with signs and significance levels that differ across MOM and BOM economies, consistent with a persistent institutional segmentation. Third, the determinants of financial leverage are themselves institutionally patterned, with asset tangibility and firm size playing markedly stronger roles in bank-oriented economies. The empirical estimates are drawn from a fixed-effects panel specification, selected on Fisher, Breusch-Pagan and Hausman tests. The paper closes with an extended discussion of what has changed since 2008 — the post-crisis monetary regime, the 2013–2021 biotech IPO boom, SPACs and direct listings, the rise of Asian biotech, and AI-driven drug discovery — and argues that the convergence-versus-segmentation debate remains open. The 1997–2008 results are best read as a historical baseline against which post-crisis empirical work should now be calibrated.