애스크로AIPublic Preview
← 학술논문 검색
학술논문기업경영리뷰2025.02 발행

An Empirical Study on the Relationship among Ownership·Governance Structure, Capital Structure and Firm Value

An Empirical Study on the Relationship among Ownership·Governance Structure, Capital Structure and Firm Value

조수혜(닝보 금융경제대학교); 정강원(국립공주대학교)

16권 1호, 133~160쪽

초록

This study focuses on the manufacturing industry listed on the KOSPI and analyzes the relationship between governance structure, capital structure, and firm value. While existing research has extensively examined governance structure and capital structure individually, there is a lack of empirical analysis that comprehensively links governance structure, capital structure, and corporate value. Therefore, this study aims to bridge this gap by integrating the governance structure equation and the capital structure equation, employing structural equation modeling (SEM) to analyze the manufacturing industry listed on the Korean securities market from 2010 to 2020. Building on prior research and considering the cashflow right and control right deviation characteristics of Korean corporate groups, the entire sample was categorized into two groups for empirical analysis: group firms and general firms. The empirical analysis yields the following results. Firstly, it was confirmed that the foreign shareholder ratio, outside director ratio, and board size have a negative impact on leverage and a positive impact on corporate value. This can be interpreted as a supervisory mechanism for corporate operations, such as the board size, the proportion of independent directors, and the foreign shareholder ratios. By restraining, supervising, and monitoring management, it reduces agent costs, mitigates information asymmetry, and thus increases firm value. Secondly, the concentration of ownership in firm groups has a significant positive impact on leverage, while also exerting a negative impact on firm value. The concentration of ownership in general firms has a negative impact on leverage and a positive impact on firm value at the 1% level.

Abstract

This study focuses on the manufacturing industry listed on the KOSPI and analyzes the relationship between governance structure, capital structure, and firm value. While existing research has extensively examined governance structure and capital structure individually, there is a lack of empirical analysis that comprehensively links governance structure, capital structure, and corporate value. Therefore, this study aims to bridge this gap by integrating the governance structure equation and the capital structure equation, employing structural equation modeling (SEM) to analyze the manufacturing industry listed on the Korean securities market from 2010 to 2020. Building on prior research and considering the cashflow right and control right deviation characteristics of Korean corporate groups, the entire sample was categorized into two groups for empirical analysis: group firms and general firms. The empirical analysis yields the following results. Firstly, it was confirmed that the foreign shareholder ratio, outside director ratio, and board size have a negative impact on leverage and a positive impact on corporate value. This can be interpreted as a supervisory mechanism for corporate operations, such as the board size, the proportion of independent directors, and the foreign shareholder ratios. By restraining, supervising, and monitoring management, it reduces agent costs, mitigates information asymmetry, and thus increases firm value. Secondly, the concentration of ownership in firm groups has a significant positive impact on leverage, while also exerting a negative impact on firm value. The concentration of ownership in general firms has a negative impact on leverage and a positive impact on firm value at the 1% level.

발행기관:
KNU 기업경영연구소
분류:
경영학일반

AI 법률 상담

이 논문의 주제에 대해 더 알고 싶으신가요?

460만+ 법률 자료에서 관련 판례·법령·해석례를 찾아 답변합니다

AI 상담 시작
An Empirical Study on the Relationship among Ownership·Governance Structure, Capital Structure and Firm Value | 기업경영리뷰 2025 | AskLaw | 애스크로 AI