Date of Award

Spring 2020

Degree Type

Restricted to Claremont Colleges Dissertation

Degree Name

Philosophy, PhD

Program

School of Politics and Economics

Advisor/Supervisor/Committee Chair

Tom Kniesner

Dissertation or Thesis Committee Member

C. Mónica Capra

Dissertation or Thesis Committee Member

Darren Filson

Dissertation or Thesis Committee Member

Ying-ying Lee

Terms of Use & License Information

Creative Commons Attribution-Share Alike 4.0 License
This work is licensed under a Creative Commons Attribution-Share Alike 4.0 License.

Rights Information

© Copyright Xiaolong Wang, 2020. All rights reserved

Keywords

CEO compensation, Endogeneity, Firm performance, Incentive, Inverse probability-of-treatment weighting, Structural equations model

Abstract

Determinants of CEO Compensation and Firm Performance — A Survey

Reviewing a large set of literature on CEO compensation and firm performance, I find the following. First, institutional and macro-level factors tend to take the first order importance in determining CEO compensation and firm outcome as well as many other factors in corpo- rate finance and corporate governance. Second, relations among the factors that determine CEO compensation and firm outcome are complex and often the exact causal directions are ambiguous. Third, endogeneity is present and it’s likely many factors including CEO compensation and firm performance are jointly determined. Fourth, CEO compensation has been mainly characterized in a principal-agent framework and many factors are regarded as either constraining or exacerbating the agency problems.

Optimality of Dynamic CEO Compensation and the Endogeneity Problem

Optimal dynamic contract theory postulates that the CEO’s portfolio needs to be rebal- anced each year to maintain the optimal incentive that implements a targeted effort. Thus,

given previous year’s incentive, there exists an optimal adjustment that has to be made by the principal in order to maximize firm value. If contracts are optimally written and im- plemented, it’s expected that the derivative of firm value on changes in CEO incentive is zero. I test this hypothesis by estimating the treatment effect of changes in CEO incentive on firm value while controlling for a large set of lagged market, firm, board and CEO charac- teristics and using the inverse probability-of-treatment weighting method. I also use lagged firm policy variables as proxies for unobserved characteristics such as CEO risk aversion. Part of the results show that there is no significant effect of incentive adjustment on firm value, thus possibly confirming the optimality of CEO incentive contracts. However, there is also evidence that unobserved confoudning exists and the inherent endogeneity may bias the results.

Causal Inference in Corporate Finance

I advance a methodology for sound causal inference in corporate finance. I first review three applications of the quasi-experimental methods to study causal relations in corporate finance and argue that ensuring the validity of the quasi-experimental design ironically re- quires a good amount of knowledge about the underlying causal mechanisms which is so far lacking. Then I argue that the structural equations model provides a systematic framework for causal inference and the complexity and interconnected relations in corporate finance can be an advantage in learning causal relations by applying causal discovery techniques. I also present three methods to estimate causal effects once a better understanding of the under- lying causal structure in corporate finance is achieved. Lastly I apply one of the methods to study the marginal contribution of CEO incentive in explaining firm performance beyond a large set of market, firm, board and CEO characteristics as well as lagged firm perfor- mance. I find that change in CEO incentive, or the incentive adjustment, has persistent and strong predictive power over Tobin’s q, which lends some support to the dynamic contracting theory.

ISBN

9798557036412

Download

Share

COinS