What Drives Corporate Savings

SSRN Electronic Journal · 2026-01-01

What Drives Corporate Savings

National Bureau of Economic Research · 2026-01-01

We study the determinants of corporate cash holdings by extending the standard q theory of investment with financing frictions and productivity shocks.While existing models predict a low propensity to hold cash, we show that realistic cash holdings arise only when three ingredients are combined: 1.) costly external financing, 2.) persistent productivity shocks, and 3.) contemporaneous productivity shocks.With costly external financing, persistent productivity shocks generate predictable cash flows and investment opportunities, but yield little need for savings since the internally generated cash flows are aligned with the investment needs.Contemporaneous shocks make internally generated cash flows random, inducing firms to hold cash at levels consistent with those observed empirically.

Corporate Hierarchy

2025-08-14

We introduce a novel measure of corporate hierarchies for over 3,100 U.S. public firms. This measure is obtained from online resumes of 7 million employees and a network estimation technique that allows us to identify hierarchical layers. Equipped with this measure, we document several facts about corporate hierarchies. Firms have on average ten hierarchical layers and a pyramidal organizational structure. More hierarchical firms have a more educated workforce, higher internal promotion rates, and longer employee tenure. Their operating performance is higher, but they face higher administrative costs. They are more active acquirers and produce more patents, but not higher-quality patents. They exhibit lower stock return volatility and operating asset volatility. We also examine how companies adjust their hierarchies in response to demand and knowledge shocks. We find that pharmaceutical companies increased their number of layers following the Covid-19 pandemic, while companies flattened their hierarchies following the adoption of artificial intelligence (AI) technologies. These findings are consistent with the theoretical predictions of existing models of corporate hierarchies.

Corporate Hierarchy

SSRN Electronic Journal · 2025-01-01

Corporate Hierarchy

National Bureau of Economic Research · 2025-08-01 · 1 citations

Corporate Hierarchy

SSRN Electronic Journal · 2025-01-01

What Drives Corporate Savings

SSRN Electronic Journal · 2025-01-01

Corporate Hierarchy

2025-10-12

We introduce a novel measure of corporate hierarchies for over 3,100 U.S. public firms. This measure is obtained from online resumes of 7 million employees and a network estimation technique that allows us to identify hierarchical layers. Equipped with this measure, we document several facts about corporate hierarchies. Firms have on average ten hierarchical layers and a pyramidal organizational structure. More hierarchical firms have a more educated workforce, higher internal promotion rates, and longer employee tenure. Their operating performance is higher, but they face higher administrative costs.They are more active acquirers and produce more patents, but not higher-quality patents. They exhibit lower stock return volatility and operating asset volatility. We also examine how companies adjust their hierarchies in response to demand and knowledge shocks. We find that pharmaceutical companies increased their number of layers following the Covid-19 pandemic, while companies flattened their hierarchies following the adoption of artificial intelligence (AI) technologies. These findings are consistent with the theoretical predictions of existing models of corporate hierarchies.

Propagation and Amplification of Local Productivity Spillovers

Econometrica · 2024-01-01 · 34 citations

The gains from agglomeration economies are believed to be highly localized. Using confidential Census plant‐level data, we show that large industrial plant openings raise the productivity not only of local plants but also of distant plants hundreds of miles away, which belong to large multi‐plant, multi‐region firms that are exposed to the local productivity spillover through one of their plants. This “global” productivity spillover does not decay with distance and is stronger if plants are in industries that share knowledge with each other. To quantify the significance of firms' plant‐level networks for the propagation and amplification of local productivity shocks, we estimate a quantitative spatial model in which plants of multi‐region firms are linked through shared knowledge. Counterfactual exercises show that while large industrial plant openings have a greater local impact in less developed regions, the aggregate gains are greatest when the plants locate in well‐developed regions, which are connected to other regions through firms' plant‐level (knowledge‐sharing) networks.

Innovation Spillovers across U.S. Tech Clusters

SSRN Electronic Journal · 2024-01-01