The Transmission Mechanism of Monetary Expansion to Corporate Distress: A Case Study of Carvana Co. Under the Post-Pandemic Inflationary Regime

Abstract

This academic research paper constructs a mathematically rigorous, structurally integrated micro-macro econometric framework designed to isolate and quantify the exact transmission mechanisms through which systemic macroeconomic monetary shocks propagate into corporate capital structures, balance sheet constraints, and subsequent financial distress. Focusing empirically on the turbulent post-pandemic business cycle spanning from January 2020 through December 2024, this study utilizes Carvana Co. (NYSE: CVNA) as a representative high-growth, asset-heavy, digitally native corporate vehicle that experienced extreme financial distress. In the wake of the exogenous economic freeze induced by the COVID-19 pandemic, the Federal Reserve implemented unprecedented open-ended quantitative easing (QE) alongside a zero-interest-rate policy (ZIRP). This structural regime shift engineered a historic, non-linear expansion in the United States M2 monetary aggregate. By operationalizing the classical Friedmanite Quantity Theory of Money (QTM) alongside sector-specific supply-demand microeconomic equilibrium frameworks, we map how this hyper-liquidity altered asset pricing dynamics in the used-vehicle marketplace, inducing Carvana into aggressive, debt-financed inventory and infrastructure expansion. Conversely, we analyse the subsequent contractionary policy turnaround executed to tame secular inflation, mathematically demonstrating that sudden, aggressive interest rate shocks propagate corporate distress via two primary empirical vectors: The Long-Run Average Cost (LRAC) scale compression channel and the structural Merton-model financial refinancing channel. The empirical results, verified via quantitative asset volatility modelling and a dynamic multi-variable financial distress proxy, demonstrate that macroeconomic policy regimes dictate microeconomic survival boundaries, proving the critical necessity of integrating macro-regime vectors into modern financial engineering risk architecture.