A synthesized distribution model: Asymmetric information, agency problem, and intertemporal optimization

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Abstract

A firm’s policy of distribution over current and future time periods influences the capital structure of the firm and its profitability. Managers decide on the amount of effort input in such a context of financial structure to maximize their utility. Nevertheless, shareholders’ preferred distribution of income is determined by the goal of corporate value maximization. The study aims to reach an optimal level of income distribution and reinvestment over current and future periods in which both the manager’s utility and shareholders’ corporate value have been maximized. The study adopts Lagrange’s multipliers method and the discounted cash flow valuation model of corporate value maximization. By processing a method of mathematical deduction and optimization, the study aims to reach an optimal equilibrium level of the dividend distribution model and explore key factors in the model for the determination of the distribution of income. As a result, the study concluded an optimal dividend distribution model, in which six factors jointly determine a theoretical equilibrium of optimization. These factors consist of the capital structure of the firm, the tax shield from debt financing, the growth rate of the dividend, dividend tax, the investment strategy of the principal, and the cost of capital.

Keywords: Company Finance, Corporate Governance, Agency Problem, Dividend Policy

Authors’ individual contribution: The Author is responsible for all the contributions to the paper according to CRediT (Contributor Roles Taxonomy) standards.

Declaration of conflicting interests: The Author declares that there is no conflict of interest.

JEL Classification: G35

Received: 22.12.2022
Accepted: 23.10.2023
Published online: 26.10.2023

How to cite this paper: Jiang, J. (2023). A synthesized distribution model: Asymmetric information, agency problem, and intertemporal optimization. Corporate Governance and Organizational Behavior Review, 7(4), 152–160. https://doi.org/10.22495/cgobrv7i4p13