scispace - formally typeset
M

Michael Raith

Researcher at University of Rochester

Publications -  42
Citations -  2403

Michael Raith is an academic researcher from University of Rochester. The author has contributed to research in topics: Incentive & Duopoly. The author has an hindex of 18, co-authored 41 publications receiving 2209 citations. Previous affiliations of Michael Raith include Université libre de Bruxelles & University of Chicago.

Papers
More filters
Journal ArticleDOI

Competition, Risk and Managerial Incentives

TL;DR: In this paper, the authors examine how the degree of competition among firms in an industry affects the optimal incentives that firms provide to their managers and find that managers' incentives are positively correlated with firm-level risk, consistent with empirical evidence.
Journal ArticleDOI

A General Model of Information Sharing in Oligopoly

TL;DR: In this article, the authors present a general model which encompasses virtually all models of the existing literature on information sharing as special cases, and show that in contrast to the apparent inconclusiveness of previous results some simple principles determining the incentives to share information can be obtained.
Journal ArticleDOI

The U-Shaped Investment Curve: Theory and Evidence

TL;DR: This paper analyzed how the availability of internal funds affects a firm's investment and showed that under fairly standard assumptions, the relation is U-shaped: investment increases monotonically with internal funds if they are large but decreases if they were very low, and argued that models predicting an always increasing relation are based on restrictive assumptions.
Journal ArticleDOI

Competition, Risk and Managerial Incentives

TL;DR: In this article, the authors examine how the degree of competition among firms in an industry affects the optimal incentives that firms provide to their managers and find that managers' incentives are positively correlated with firm-level risk, consistent with empirical evidence.
Journal ArticleDOI

Specific knowledge and performance measurement

TL;DR: Examination of optimal incentives and performance measurement in a setting where an agent has specific knowledge about the consequences of their actions for the principal shows how the optimal choice of performance measures and incentives depends on the agent's knowledge, environmental risk, technological uncertainty, and job complexity.