How Important Is Internal Information Asymmetry for Firm-Level Productivity?

Theoretical research suggests internal information asymmetry (IIA) between top managers and divisional managers can reduce productivity by distorting internal resource allocation. The net effect, however, is unclear because IIA also reflects valuable private information within divisions, and empirical evidence is limited because of the unobservability of managers’ private information sets. Using a measure of IIA that exploits differences in returns to insider trading by top and divisional managers, we find that higher IIA is associated with lower total factor productivity. A one standard deviation increase in IIA corresponds to a 2.6% decrease in productivity relative to industry peers. This effect is comparable in magnitude to other important internal informational frictions, such as internal control weaknesses, and is distinct from internal information quality. Cross-sectional analyses indicate that the negative association is stronger when curative measures are limited and when agency conflicts between top managers and shareholders are greater. Mechanism tests indicate that IIA reduces internal capital market efficiency and increases underinvestment. Finally, using brokerage mergers and closures as a plausibly exogenous shock, we find that increases in IIA lead to declines in productivity. Overall, we provide empirical evidence that IIA is an economically important determinant of firm-level productivity. This paper was accepted by Jan Bouwens, accounting. Supplemental Material: The code and data files are available at https://doi.org/10.1287/mnsc.2024.08526 .

Authors

Institutions

Publication Details

Journal
Management Science
Published
2026-08-18
DOI
https://doi.org/10.1287/mnsc.2024.08526
Primary Topic
Corporate Finance and Governance
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

How Important Is Internal Information Asymmetry for Firm-Level Productivity?

Vishal P. Baloria, David P. Weber, Trent Krupa
Management Science
Corporate Finance and Governance
article

How Important Is Internal Information Asymmetry for Firm-Level Productivity?

Vishal P. Baloria, David P. Weber, Trent Krupa
article en

Abstract

Theoretical research suggests internal information asymmetry (IIA) between top managers and divisional managers can reduce productivity by distorting internal resource allocation. The net effect, however, is unclear because IIA also reflects valuable private information within divisions, and empirical evidence is limited because of the unobservability of managers’ private information sets. Using a measure of IIA that exploits differences in returns to insider trading by top and divisional managers, we find that higher IIA is associated with lower total factor productivity. A one standard deviation increase in IIA corresponds to a 2.6% decrease in productivity relative to industry peers. This effect is comparable in magnitude to other important internal informational frictions, such as internal control weaknesses, and is distinct from internal information quality. Cross-sectional analyses indicate that the negative association is stronger when curative measures are limited and when agency conflicts between top managers and shareholders are greater. Mechanism tests indicate that IIA reduces internal capital market efficiency and increases underinvestment. Finally, using brokerage mergers and closures as a plausibly exogenous shock, we find that increases in IIA lead to declines in productivity. Overall, we provide empirical evidence that IIA is an economically important determinant of firm-level productivity. This paper was accepted by Jan Bouwens, accounting. Supplemental Material: The code and data files are available at https://doi.org/10.1287/mnsc.2024.08526 .

Management Science
Pennsylvania State University (US), University of Connecticut (US)
Decent work and economic growth
Openalex Percentile: Top 14%
Corporate Finance and Governance
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.