The Moderation Effect of Debt and Dividend on the Overinvestment-Performance Relationship

Nghĩa, Nguyễn Trọng; Khang, Tran Le; Thành, Nguyễn Công

doi:10.1007/978-3-030-04200-4_81

Cited by 4 publications

(5 citation statements)

References 27 publications

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“…Debt policies and dividend distribution can reduce the negative impact of overinvestment on company performance (Nghĩa, & Thành, 2018). The negative overinvestment effect, which is characterized by a negative coefficient, indicates that overinvestment has a detrimental influence on company performance (Cai, 2013).…”

Section: Discussionmentioning

confidence: 99%

Global Perspectives on Financial Policy Optimization: Addressing Overinvestment and its Impact on Corporate Profitability (Study on Indonesia Stock Exchange)

Saputra,

Fahdillah

et al. 2024

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The primary objective of this research is to investigate the impact of overinvestment on corporate performance. It also seeks to analyze the effectiveness of debt policy, dividend policy, and the combined use of debt and dividend policy in alleviating the adverse effects of overinvestment on corporate performance. The study utilizes data from a sample of 53 non-financial companies that carried debt and consistently distributed dividends from 2010 to 2022. Overinvestment is assessed through two methods: the residual value derived from the new investment equation and the Hodrick-Prescott (HP) filter. The data is then transformed into panel data, and various models such as fixed effect, random effect, and common effect are applied to identify the most suitable model. The findings indicate a negative correlation between overinvestment and corporate performance. Debt policy emerges as a mitigating factor, addressing agency conflicts and reducing the adverse impact of overinvestment on company performance. Similarly, dividend policy proves effective in mitigating the negative effects of overinvestment by constraining excess cash. The combination of debt and dividend policies is identified as a comprehensive strategy to mitigate overinvestment, as it aids in curbing excessive free cash flow. However, it is noted that this combination also lowers financing funds to their minimum level, potentially leading to a shortage of funds for future profitable projects. Consequently, careful calculations are emphasized to ensure companies strike a balance, avoiding neglect of profitable investments in the future.

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Section: Discussionmentioning

confidence: 99%

Global Perspectives on Financial Policy Optimization: Addressing Overinvestment and its Impact on Corporate Profitability (Study on Indonesia Stock Exchange)

Saputra,

Fahdillah

et al. 2024

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“…Previous studies on overinvestment have used various methods, such as degree of Richardson used free cash flow as a measure of overinvestment and found that overinvestment is negatively related to future profitability, Effect of debt and dividends on the relationship between investment overcapacity and performance, regression statistics 20,35,58 . However, none of these studies applied machine learning techniques, despite the increasing popularity of machine learning in financial research.…”

Section: Discussionmentioning

confidence: 99%

“…Hao et al, and Nghia et al, both employ a measure of overinvestment based on Richardson's model. 20,34,35 . Hao et al, practiced with 650 real estate companies listed in China between 2010 -2015, successfully proved that overinvestment is a common practice (33.54% of real estate companies) and debt structure has a limited effect on overinvestment thereby providing policy implications for mitigating this problem 34 .…”

Section: Previous Studiesmentioning

confidence: 99%

“…Hao et al, practiced with 650 real estate companies listed in China between 2010 -2015, successfully proved that overinvestment is a common practice (33.54% of real estate companies) and debt structure has a limited effect on overinvestment thereby providing policy implications for mitigating this problem 34 . Nghia et al, conduct a study that investigates the detrimental impact of overinvestment on firm performance and the moderating role of debt and dividend in mitigating agency costs resulting from overinvestment 35 . The research comprises all of Vietnam's non-financial companies that are listed on HSX and HNX from 2006 to 2016.…”

Section: Previous Studiesmentioning

confidence: 99%

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Application of machine learning in classification of overinvestment: Evidence from listed firms in Vietnam stock exchange market

Phan Huy,

Ngo Dinh Linh,

Nguyen Thi Ngoc

et al. 2023

Sci.Tech.Dev.J.-Eco.Law Manag.

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Studies have consistently demonstrated that both overinvestment and underinvestment exert adverse effects on the overall efficacy of business operations, showcasing the significance of understanding and addressing these phenomena in the realm of scholarly research. Therefore, in this study, we aim to develop an accurate machine-learning model to identify overinvestment in firms listed on the HSX and the HNX stock exchanges in Vietnam. We decided to conduct a comparison to identify the optimal model for classifying firms of overinvestment or not, including Logistic Regression, K-Nearest Neighbor (KNN), Naive Bayes (NB), Support Vector Machine (SVM), Decision Tree, and Random Forest. Using a sample of 658 non-financial listed companies in Vietnam between 2011 and 2021, our result shows that the most importance predictor variable is "FCF" (free cash flow), with an importance value of 0.14. Although both logistic regression and random forest (RD) algorithms demonstrate high accuracy in identifying firms with overinvestment, the Random Forest algorithm exhibits slightly higher precision and recall for class 1 (overinvestment firms) when compared to Logistic Regression. By contrast, the accuracy performance of the four models (NB, KNN, DT, and SVM) is low, ranging from 0.53 to 0.67. At the microeconomic level, this research can help businesses gain insights into their financial performance, identify areas for improvement, and take proactive measures to avoid financial distress and improve profitability by identifying potential cases of overinvestment. Overall, the study provides a valuable contribution to the field of financial analysis using machine learning techniques. We firmly believe that the findings of this research will serve as a significant scholarly reference for future investigations in the field and explore other importance predictors of overinvestment in Vietnam and other emerging markets.

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“…Various types of (industrial, agricultural, service) enterprises get over-invested through an irrational use of assets which is intended to increase company value or have a positive effect on financial performance, but is based on an excessively optimistic evaluation of market PLOS ONE conditions [56][57][58]. As a consequence, the expected return on investment projects is below the interest rate offered in capital markets [59,60]. According to another approach, overinvestment takes place when companies excessively invest in financial or tangible assets [58].…”

Section: Discussionmentioning

confidence: 99%

Overinvestment in selected Central and Eastern European countries: Production and economic effects

et al. 2021

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Farms need to invest in order to earn incomes and maintain their competitive edge. However, the scale and extent of investments must be aligned with resources of other productive inputs, primarily including land, because otherwise there is risk of overinvestment. Since 2004, Central and Eastern European countries have been provided with access to investment support programs; these are non-repayable aid funds which can potentially lead to overinvestment issues. Therefore, this paper attempts to answer the question on the scale of overinvestment in the countries covered. This is all the more important since that problem has rarely been addressed in economic and agricultural research. The study presented in this paper is unique in that the research tasks are based on unpublished Farm Accountancy Data Network (FADN) microdata for 5839 selected Central and Eastern European farms provided by the European Commission’s Directorate-General for Agriculture and Rural Development (DG AGRI). Based on variables relating to the amount of productive inputs and production volumes, the authors developed their own typology of farms which includes the following categories: optimum investment levels (the growth rate of labor productivity is greater than growth in the assets-to-land ratio); relative overinvestment (while labor productivity grows, it does so at a slower rate than the assets-to-land ratio); absolute overinvestment (labor productivity declines while the assets-to-land ratio grows); underinvestment (decline in both labor productivity and the assets-to-land ratio). The authors demonstrated that members of the ‘absolute overinvestment’ group made flagrant mistakes in investment planning and implementation, whereas members of the ‘relative overinvestment’ group did record an improvement in labor productivity which ultimately can be considered a positive outcome. Underinvested farms were a very small minority in each country. In addition to filling a gap in the methodology for determining agricultural overinvestment, this paper also indicates the scale of that issue in Central and Eastern European countries. This study may be of importance both to farms (as guidelines for investment planning) and to agricultural policymakers who develop investment support programs.

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The Moderation Effect of Debt and Dividend on the Overinvestment-Performance Relationship

Cited by 4 publications

References 27 publications

Global Perspectives on Financial Policy Optimization: Addressing Overinvestment and its Impact on Corporate Profitability (Study on Indonesia Stock Exchange)

Global Perspectives on Financial Policy Optimization: Addressing Overinvestment and its Impact on Corporate Profitability (Study on Indonesia Stock Exchange)

Application of machine learning in classification of overinvestment: Evidence from listed firms in Vietnam stock exchange market

Overinvestment in selected Central and Eastern European countries: Production and economic effects

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