A Structural Model of a Firm's Operating Cash Flow with Applications.

This article focuses on developing and empirically estimating a structural vector autoregressive (SVAR) model to analyze the endogenous and dynamic relationships among a firm's operating cash flow (OCF) and key operational variables—sales, inventory, accounts payable, and selling, general, and administrative expenses—while incorporating exogenous macroeconomic indicators such as GDP, consumer confidence, and CEO confidence indices. Using quarterly data from 575 U.S. public firms across retail, wholesale, and manufacturing sectors from 1990 to 2020, the model identifies causal impacts of structural shocks on these variables, enabling the evaluation of managerial policies and forecasting improvements. Applications include assessing the effects of economic shocks like recessions on firm performance, illustrating compensating managerial actions to mitigate adverse impacts, and demonstrating that joint forecasting of operational variables significantly improves cash flow prediction accuracy compared to traditional univariate models. The study provides a generalizable tool for managers to better understand and manage cash flow dynamics in the context of operational and macroeconomic fluctuations.