INTRODUCTION
Introduction and Background
Investment is crucial for companies aiming to achieve specific economic and financial objectives, with investment efficiency significantly influencing project evaluations, company growth, future cash flow, and overall value Various factors affecting this efficiency have been extensively studied, revealing issues such as information asymmetry between management and financial institutions, and agency conflicts among controlling shareholders, minority investors, and management These challenges notably impact investment decisions and are particularly prevalent in emerging markets Vietnam, characterized by its emerging economy status, weak market efficiency, limited capital and equity markets, and poor corporate governance, serves as an ideal case study for examining investment efficiency amid financial constraints and agency problems, which can lead to suboptimal investment choices detrimental to the nation's companies.
Investment inefficiency can lead to significant growth losses for firms, manifesting as under-investment, where positive NPV projects are overlooked, or over-investment, where resources are wasted on negative NPV projects This phenomenon, termed abnormal investment, has been observed in various countries, including the U.S., China, Brazil, and Singapore Research indicates that abnormal investment negatively impacts company performance and stakeholder relationships, prompting studies into its influencing factors Notably, free cash flow has been found to have a significant positive correlation with abnormal investment Additionally, the sensitivity of abnormal investment to free cash flow tends to increase in over-investing firms due to agency problems, while under-investing firms experience heightened sensitivity due to financial constraints.
Research indicates that firms experiencing financial constraints and those facing agency problems demonstrate higher positive investment-cash flow sensitivities compared to other companies This suggests that underinvesting firms and overinvesting firms react more strongly to changes in cash flow, highlighting the impact of financial conditions on investment decisions (Guariglia & Yang, 2016; Hovakimian & Hovakimian, 2009).
Numerous studies have explored solutions to the issue of over-investment, which occurs when a company invests excessively beyond its anticipated needs, potentially engaging in projects with negative Net Present Value (NPV) This misallocation of resources can significantly hinder a company's operational efficiency and effectiveness, as highlighted by researchers such as López-de-Foronda et al (2019) and Wei et al (2019).
Research indicates that paying dividends compels managers to make efficient investments to boost profitability and meet shareholder expectations Consequently, dividends serve a disciplinary function within firms, as dividend policies can help mitigate the risks associated with overinvestment This concept has been validated by various studies across multiple countries, including those by Rozeff (1982), Moin, Guney, and El Kalak (2019), Wei et al (2019), and Crisóstomo, de Freitas Brandão, and López-Iturriaga (2020).
Vietnam's rapidly growing economy has revealed issues of abnormal investment, including both under- and over-investment in listed firms, as identified by Le Ha Diem Chi and Chau (2019) and other studies Their research highlights a positive correlation between free cash flow and overinvestment, aligning with agency theory Additionally, Trong and Nguyen (2020) found that dividend policy can mitigate the adverse effects of overinvestment on firm performance Despite these findings, there remains a lack of comprehensive studies addressing the causes, solutions, and determinants of abnormal investment, particularly within the context of Vietnam's market This gap in research has motivated the author to explore this critical topic further.
The study examines the factors influencing abnormal investment among listed firms on the Ho Chi Minh Stock Exchange, with a specific emphasis on the roles of free cash flow and dividends It aims to understand how these financial elements affect investment decisions, potentially leading to abnormal investment patterns By analyzing the relationship between free cash flow, dividend distribution, and investment behavior, the research seeks to provide insights into the financial dynamics within the Vietnamese stock market.
Research gap identification and new contributions
Building on prior research findings, the author identifies significant gaps in ideas and methodologies concerning abnormal investment that warrant further investigation Consequently, this thesis makes four key contributions aimed at addressing these deficiencies in the current literature.
The thesis explores the coexistence of under- and over-investment in Vietnam, attributing this phenomenon to the country's inadequate corporate governance and underdeveloped financial market, characterized by weak institutional quality and significant information asymmetry (Van Tuan & Tuan, 2016; Trong & Nguyen, 2020) This perspective contrasts with various official and unofficial studies conducted in Vietnam, such as those by Le Ha Diem Chi and Chau.
Research conducted in 2019, along with studies by Richardson (2006), Franzoni (2009), Cai (2013), and S Fazzari et al (1987), focused exclusively on a specific type of abnormal investment This approach allows the thesis to draw comprehensive conclusions regarding various aspects of investment inefficiency issues.
The thesis will demonstrate a comprehensive research process utilizing innovative methodologies such as Random Effects Model (REM), Fixed Effects Model (FEM) with clustered standard errors, and System Generalized Method of Moments (GMM) for future studies on this topic in Vietnam Previous Vietnamese studies, both official and unofficial, have primarily relied on Ordinary Least Squares (OLS) regressions, categorized by size for analysis, along with two-step GMM, logistic polynomial regression, and Euler equation regression (Le Ha Diem Chi & Chau, 2019; Trong & Nguyen, 2020).
The thesis uniquely examines the relationship between dividends and overinvestment by directly regressing overinvestment value on the dividend payout ratio This approach contrasts with previous studies, such as Trong & Nguyen (2020), which analyzed the marginal effect of dividends on overinvestment, and Rozeff (1982), who focused on the relationship between the dividend payout ratio and agency costs through average growth rates Additionally, Moin et al (2019) regressed the dividend payout ratio on overinvestment, while Crisóstomo et al explored the impact of growth opportunities, represented by the market-to-book assets ratio, on dividend policy.
In 2020, research indicated that analyzing the direct relationship between dividends and investment efficiency could reveal whether dividends serve as a tool to mitigate overinvestment and enhance investment effectiveness.
This thesis presents a comprehensive analysis of the overinvestment issue related to agency theory in Vietnam, utilizing a robust dataset comprising 3,672 firm-year observations from 306 non-financial companies listed on the Ho Chi Minh Stock Exchange (HOSE) between 2008 and 2019.
Research objectives
This study aimed to explore the influence of free cash flow and cash dividends on abnormal investment across various business scenarios, focusing on Vietnamese non-financial firms listed on the Ho Chi Minh Stock Exchange from 2008 to 2019.
This study investigates the relationship between abnormal investment, including both under- and over-investment, and free cash flow among Vietnamese listed firms Utilizing the framework established by Richardson (2006) and further developed by Guariglia and Yang (2016), the research constructs measures for abnormal investment and free cash flow The findings aim to clarify whether investment inefficiencies in Vietnam can be attributed to financial constraints and agency problems Specifically, the study seeks to determine if firms experiencing financial constraints or agency issues exhibit greater sensitivities and positive correlations between under-investment and free cash flow when below their optimal levels, and over-investment when above these levels.
The second objective is to investigate the role of cash dividends as a potential constraint on overinvestment by analyzing their impact The findings from this research will inform the development of policies aimed at enhancing business investment decision-making and operational efficiency.
Research questions
In order to achieve the research objectives, the thesis seeks to address the following three main research questions:
Research question 1.1: What is the impact of negative free cash flow on underinvestment in listed firm in HOSE? Can this effect be considered as a consequence of financial constraints?
Research question 1.2: What is the impact of positive free cash flow on overinvestment in listed firm in HOSE? Can this effect be considered as a consequence of agency problems?
Research question 2: What is the influence of cash dividends on over investment caused by free cash flow in listed firm in HOSE?
The scope of the study
This research will investigate in 306 non-financial firms in manufacturing, services industries in Ho Chi Minh Stock Exchange during the period 12 years from 2008 to
In 2019, the author chose the 12-year period starting from 2008 as it marks a significant benchmark when Vietnam's stock market encountered challenges due to the global financial crisis, subsequently beginning a remarkable recovery and growth in the years that followed.
The increasing number of companies listed on the Stock Exchange, along with the growth in firm sizes and market dynamics, creates an ideal environment for this study Furthermore, the accessibility and ease of data collection enhance the research process This study focuses exclusively on non-financial firms to avoid potential biases, as the characteristics and implications of high leverage differ significantly between financial and non-financial entities.
Research data and Methodology
This thesis will use the secondary data collected from financial statements of 306 firms’ annually audited Consolidated Financial Statements from the year 2008 to
In 2019, the analysis included key financial metrics such as net cash flow from investment activities, depreciation and amortization, net cash flow from operating activities, dividends, and various firm characteristics like age, other receivables, and payables After excluding financial firms and certain inappropriate entities from the Ho Chi Minh Stock Exchange, the study comprised 3,672 firm-year observations, with the exact numbers varying by analysis model This sample represented 89.21% of the companies and approximately 70% of the total market capitalization on the HOSE.
Various methodologies, including Ordinary Least Squares (OLS) regression, Fixed Effect Models (FEM) with or without Huber-White robust standard errors, clustered techniques, and Generalized Method of Moments (GMM), are frequently employed in research to investigate abnormal investment, as demonstrated in studies by Richardson (2006), Guariglia and Yang (2016), Franzoni (2009), and Pellicani and Kalatzis (2019).
S Fazzari et al (1987) and are employed to investigate the relationship or sensitivity between free cash flow and investment by researches of Richardson (2006); Guariglia and Yang (2016); Ding et al (2010); X Chen, Sun, and Xu (2016); S Fazzari et al (1987); Mulier et al (2016) Also, such frequent methods are adopted to test the relationship between cash dividends and over – investment by some studies of Trong and Nguyen (2020), Moin et al (2019), Farooq, Gilbert, and Tourani-Rad , Crisóstomo et al (2020), then the robustness tests are carried out for checking the consistency of those approaches Although OLS regression is simply to use and understand, the main disadvantages of it are limitations in the shapes that linear models can assume over long ranges, possibly poor extrapolation properties, and sensitivity to outliers, which could make unreliable results Therefore, the author will inherit and develop the methodology from previous research by applying Fixed and Random-Effects Models (FEM and REM) for all the research models with panel data because a major advantage of these models is provide a way to control for all time- invariant unmeasured or latent variables that influence the dependent variable whether these variables are known or unknown to the researcher (Bollen & Brand,
The Random Effects Model (REM) assumes that omitted time-invariant variables are uncorrelated with included time-varying covariates, while the Fixed Effects Model (FEM) allows for correlation between these variables The REM offers greater efficiency compared to the FEM, resulting in smaller standard errors and higher statistical power for detecting effects A Hausman test will be conducted to determine the most consistent model between FEM and REM, enabling the author to identify the best fit for the thesis Subsequent diagnostic tests will address any model issues Ultimately, either the System-Generalized Method of Moments (System-GMM) or FEM/REM with clustered standard errors will be employed based on the specific research model challenges, leading to the final conclusions of the study.
Research structure
The thesis has been organized in the following way
Chapter 1 (Introduction) provides the overall background, brief description about research gap and the reasons lead to this dissertation Then, it shows the research objectives and questions, research data and methodology
Chapter 2 (Literature review) shows the framework theory, literature review, definitions about the term which are used throughout the dissertation and some previous researches Then, it indicates about the hypotheses of each research models Chapter 3 (Research methodologies) first shows the information about data, sample and variables of the research Next, it presents the models for the three research questions Then, it describes the research methods and process, which would be applied throughout this thesis
Chapter 4 (Empirical results) depicts the results of models through each method and gives the analysis, evaluation and make conclusions
Chapter 5 (Conclusion and Policy implications) gives the findings, recommendations and limitations of the study.
LITERATURE REVIEW
Theoretical Framework
Pecking order theory, proposed by Myers and Majluf (1984), highlights that managers possess superior knowledge about their company's internal information, including prospects, risks, and value, compared to outside investors This theory posits that firms prefer to finance their operations in a specific order, prioritizing internal funds first, followed by debt, and finally new equity.
(2010), Myers (2001) argues that due to the information asymmetries between the firm and potential investors, firms have a preferred hierarchy for financing decisions, hereinafter:
(Source: Kaplan Financial Knowledge Bank (2013), authors’ own illustration)
The selection of sources of financing depends on the preference order: retained earnings to debt, short-term debt over long-term debt and debt over equity (Li, Chen,
Internal funds, including retained earnings and free cash flow, are prioritized for financing as they originate directly from the firm, resulting in minimal information asymmetry costs This makes internal financing the most cost-effective and convenient option for businesses.
External financing, including debt and equity, incurs higher costs for firms due to information asymmetry (Luigi & Sorin, 2009) Unlike internal financing, debt financing typically requires lower returns for debt holders compared to stockholders, as debt holders have a superior claim to assets in bankruptcy situations.
Financial constraints theory, as defined by Kaplan and Zingales (1995), posits that a firm is financially constrained when the cost of accessing external funds prevents it from pursuing investments that would be viable with available internal funds Asymmetric information, highlighted by Kadapakkam, Kumar, and Riddick (1998), indicates that not all market participants have equal access to information Berk and DeMarzo (2007) further assert that managers possess more internal financial insights than outside investors, particularly regarding the firm's financial health Researchers such as Harbula (2001) and Myers and Majluf (1984) argue that market imperfections, exemplified by asymmetric information between borrowers and lenders, lead firms to favor internal financing Consequently, the greater the availability of internal funds, the higher the investment capacity of firms, as these funds are the most cost-effective and accessible (S M Fazzari & Athey, 1987; Harbula, 2001).
Firms often rely on internal funds due to information asymmetry, which limits their access to external financing and increases costs associated with obtaining such funds In extreme cases, credit rationing can occur, leading to a situation where firms face financial constraints and cannot secure necessary loans, resulting in underinvestment Even in less severe scenarios, lenders may impose a cost premium due to capital market imperfections, preventing firms from funding all viable investment opportunities Research by Guariglia and Yang (2016) indicates that firms with insufficient internal resources may forgo positive net present value (NPV) projects to avoid high external financing costs This underinvestment problem can hinder future economic growth and development potential.
2.1.3 Agency problems theory – Free cash flow theory
The agency problems theory, also known as the free cash flow theory, posits that firms with significant free cash flow—defined as cash exceeding the amount needed for positive net present value (NPV) projects—may encounter issues where managers make decisions that do not maximize value This occurs when managers invest in negative NPV projects for personal gain, despite the availability of positive NPV opportunities (Jensen, 1986) The theory highlights conflicts of interest arising from the separation of ownership and control, leading to information asymmetry between shareholders and management (Berle & Means, 1932; Jensen, 1986) Shareholders, the principals, aim to maximize firm value, while managers, the agents, often prioritize firm growth or sales (Murphy, 1985) This information asymmetry, combined with the lack of a dividend obligation, incentivizes managers to pursue growth beyond optimal levels, resulting in decisions that may not align with shareholders' interests (Jensen, 1986; Kadapakkam et al., 1998; Shleifer & Vishny, 1997).
Managers can leverage a firm's positive free cash flow to pursue investments that align with their performance goals, as noted by Richardson (2006) In contrast, firms with negative free cash flow struggle to secure financing and face increased scrutiny from external markets (DeAngelo, DeAngelo, & Stulz, 2004; Jensen, 1986) This can lead to managers making reckless investments or funding unprofitable projects using free cash flow, allowing them to avoid the accountability that comes with paying dividends to shareholders, thereby exacerbating the agency problem (Yilei Zhang, 2009) Such behavior incurs agency costs, which arise from the risk of managerial misuse of internal resources and the necessary monitoring efforts to mitigate this risk through financial statements audited by external parties (Blair; Hillier et al., 2010) Consequently, agency costs tend to rise in tandem with free cash flow levels (Jensen).
If shareholders are unable to effectively monitor managerial behaviors, it can lead to significant issues, as highlighted by Brealey, Myers, and Allen (2008) and Myers and Majluf (1984) This lack of oversight may result in overinvestment in projects with negative net present value (NPV), ultimately harming the firm's overall value (Badavar Nahandi & Taghizadeh Khanqah, 2018; Ding, Knight, & Zhang, 2019; Fu, 2010; N Liu & Bredin, 2010; Titman, Wei, & Xie, 2003; Yang, 2005).
Free cash flow
Free cash flow (FCF) is a crucial financial performance metric that serves as a vital source for firm investments, defined by various researchers as prior period net investment spending Bilicic and Connor (2004) described FCF as operating income before depreciation, minus interest expenses, income taxes, and dividends, although this definition lacks accounting precision (G Y Wang, 2010) Richardson (2006) refined this measurement, defining FCF as the cash flow beyond what is necessary to maintain existing assets and finance new investments Building on this, Guariglia and Yang (2016) calculated FCF by subtracting the optimal cash flow level from net cash flow from operating activities Additionally, FCF represents the current cash flow sufficient to cover future investment expenditures (Hirshleifer, Hou, & Teoh, 2007), and it reflects the impact of investments in operating assets (Subramanyam, Muralidhararao, & Devanna, 2009) Consequently, firms' investment decisions heavily rely on FCF, making a stable and positive FCF critical for effective decision-making processes (Ferreira & Vilela, 2004; Khurana, Martin, & Pereira, 2006).
Dividends
According to Clause 3, Article 4 and Clause 2, Article 132 of the Enterprises Law
In 2014, dividends refer to the distribution of a company's net profit to its shareholders, either in cash or other assets, after meeting financial obligations such as taxes, debt payments, and previous losses While paying dividends is not mandatory, they serve as rewards for shareholders, determined by the company's board of directors and requiring shareholder approval The dividend payout ratio is the measure of total dividends paid relative to the company's net income.
Abnormal investment and measurement framework
Vietnam has emerged as a significant development market with a GDP growth rate of approximately 6.51% per year from 2000 to 2020 Despite this growth, it remains a less developed market characterized by a bank-based economy The financial landscape in Vietnam comprises equity markets, capital markets, and a banking system, with over 80% of firms relying on the banking sector for funding Individual investors dominate the equity market, representing about 99.42% of the investor base, but their contributions are typically short to medium-term due to limited capital and long-term strategies The capital market, including corporate bonds and bills, remains small and largely inactive, with banks and securities firms controlling the corporate bond market This heavy reliance on the banking sector places significant pressure on banks, which may struggle to meet the financing needs of all firms Research indicates that small and medium enterprises (SMEs) face discrimination in loan approvals compared to larger firms, limiting their access to resources and hindering their growth Although SMEs constitute the majority of businesses in Vietnam, only about 36% had access to bank capital by the end of 2019, as commercial banks tend to favor larger, state-owned enterprises due to perceived risks associated with SMEs Consequently, banks impose stricter collateral and lending requirements on SMEs, further complicating their financial access.
In 2009, Vietnam's financial markets struggled to efficiently allocate resources and alleviate financial constraints, posing significant challenges for numerous firms This inefficiency can result in underinvestment, hindering overall economic growth.
Vietnam, like many emerging markets, faces challenges with enforcement of disclosure regulations, leading to significant transparency issues According to Transparency International, the country ranks 96 out of 180 nations in terms of transparency, highlighting the need for improved regulatory practices.
Despite regulatory efforts to enhance transparency in Vietnam's financial environment, the quality of information disclosure in financial reports of listed firms remains poor, with significant discrepancies before and after audits The corporate governance framework in Vietnam has historically failed to meet the standards of effective governance due to deficiencies in flexibility, accountability, and efficiency However, recent amendments to the Enterprises Law in 2014 reflect the government's commitment to improving corporate governance, resulting in better protection for investors and shareholders, although some governance aspects remain ambiguous, which can lead to issues like expropriation or tunneling Research indicates that weak corporate governance contributes to tunneling problems in Asia, exacerbated by a lack of transparency and a weak legal system, creating information asymmetry between shareholders and management, thus leading to agency problems Managers often exploit internal funds to pursue investments, including those with negative net present values, primarily for personal gain, resulting in overinvestment that adversely affects minority shareholders This phenomenon of overinvestment in listed firms has been documented and aligns with agency theory.
In Vietnam's financial market, two types of abnormal investment coexist, prompting an examination of their presence based on empirical findings from other studies This thesis utilizes a framework model from Richardson (2006) and Guariglia and Yang (2016) to analyze abnormal investments among listed firms on the HOSE It measures abnormal investment by subtracting expected expenditures for new positive NPV projects and necessary maintenance costs from total investment expenditures Consequently, abnormal investment is defined as unexpected expenditures on new projects, which can manifest as underinvestment (negative values) or overinvestment (positive values).
Underinvestment, as highlighted by financial constraints theory (S Fazzari et al., 1987; Kaplan & Zingales, 1995), refers to the inability of firms to pursue investment opportunities with positive net present value (NPV) or high profitability due to market imperfections This situation arises when necessary investment expenditures are either postponed or forgone, preventing firms from achieving their optimal investment levels (Guariglia & Yang, 2016; Le Ha Diem Chi & Chau, 2019).
The concept of overinvestment, rooted in agency problems and free cash flow theory as proposed by Jensen (1986), refers to the scenario where investment expenditures exceed the necessary level to maintain existing assets and fund new positive NPV projects (Richardson, 2006) Yilei Zhang (2009) further characterizes overinvestment as the tendency of top managers to prioritize personal benefits over shareholder value by directing internal free cash flow towards negative NPV projects.
2.4.1 Financial constraints with free cash flow-underinvestment relationship
Financial constraints refer to the challenges firms face in accessing external funds, primarily due to the costs associated with asymmetric information Kaplan and Zingales (1995) defined a financially constrained firm as one unable to secure available external financing for investments that could be pursued with adequate internal funds They further elaborated in 1997, stating that a firm becomes increasingly financially constrained as the disparity between its internal and external funding costs widens.
The investment-cash flow sensitivity, introduced by S Fazzari et al in 1987, serves as a key empirical measure of financial constraints This research indicates that financially unconstrained firms can readily access external financing, resulting in no significant relationship between investment and cash flow Conversely, financially constrained firms exhibit a positive investment-cash flow sensitivity, relying on internal funds for their investments Supporting this notion, Guariglia (2008) demonstrated the sensitivity of abnormal investment to free cash flow as evidence of financial constraints Numerous studies, including those by Almeida & Campello (2007), Audretsch & Elston (2002), Benito (2005), Guariglia (2008), Myers & Majluf (1984), and Silva & Carreira (2012), have corroborated that this sensitivity effectively measures financial constraints.
According to financial constraints theory, information asymmetries should also take a great responsibility for underinvestment of enterprises Modigliani and Miller
Investment decisions are influenced by a firm's free cash flow, as highlighted in 1958, indicating that when cash flows are insufficient, companies may seek debt or equity financing Firms often favor high internal cash flow for investments due to the lower costs compared to sourcing external funds (S M Fazzari & Athey, 1987; Harbula).
2001) With respect to debt sources or issuing new shares, Covitz and Harrison
Debt issuance can signal a negative trend in debt rating migration, as highlighted in 1999 To mitigate the risks associated with this, external investors—lacking access to internal information about promising project growth—tend to demand higher returns This phenomenon has been supported by various studies, including those by Brennan & Subrahmanyam (1996), Easley & O'Hara (2004), Harbula (2001), Le Ha Diem Chi & Chau (2019), and Myers (1984).
Myers and Majluf (1984) introduced a model of asymmetric information, highlighting that uninformed investors demand discounts on stocks or bonds to mitigate the risk of overvalued securities, ultimately leading to reduced stock prices and increased equity financing costs Research indicates that both debt and equity financing negatively impact a firm's market value and incur higher capital raising costs from external sources compared to internal financing, such as retained earnings Consequently, when firms face financial constraints or insufficient internal capital, they may forgo positive Net Present Value (NPV) projects to avoid the high premiums associated with external financing, resulting in underinvestment This underinvestment is particularly pronounced in firms with limited free cash flow, as financial constraints exacerbate the challenges of funding investment opportunities.
2.4.2 Agency problems with free cash flow-overinvestment relationship
The agency problem, a longstanding issue since the advent of joint stock companies, highlights the conflict between shareholders and managers arising from the separation of ownership and control This conflict leads to agency costs, which reflect the measures shareholders must take to monitor managers due to their lack of direct oversight Jensen's (1986) hypothesis on agency costs of free cash flow suggests that increased free cash flow exacerbates agency problems, a finding supported by various studies, including those by Harford (1999) and Opler et al (1999).
Recent studies highlight the significant relationship between a firm's free cash flow and its capital spending Research by Gentry and Hubbard (1998), Opler et al (1999), and others indicates that firms with excess free cash flow tend to increase their investment expenses, even in the presence of limited investment opportunities Ferreira and Vilela (2004) and Khurana et al (2006) found that firms' investment decisions are heavily influenced by internal cash flow Additionally, a positive correlation between overinvestment and free cash flow has been identified, largely attributed to agency conflict issues (Harford, 1999; Hovakimian & Hovakimian, 2009; Jensen & Meckling, 1976; Richardson, 2006; Rubin, 1990; Stulz, 1990).
Managers in firms with high free cash flow often prefer to invest in projects that may be profitable from their perspective but unprofitable for shareholders, as highlighted by research from Rubin (1990) and Stulz (1990) According to agency cost theory, such managers can misuse free cash flow primarily when it is abundant, as firms with negative free cash flow are compelled to seek external financing and face greater scrutiny (DeAngelo et al., 2004; Jensen, 1986) Internal funds, like free cash flow, are favored for financing investments due to their lower costs compared to external options (Cummins et al., 2006; Myers & Majluf, 1984) This allows managers to bypass shareholder approval and avoid dividend payments, motivating them to invest even in projects with negative net present values (NPV) (Drobetz et al., 2010) Consequently, they may prioritize their interests over those of shareholders, leading to over-investment and increased agency costs (Yilei Zhang, 2009) Ultimately, the agency problem is a significant factor driving overinvestment in firms with excess free cash flow.
2.4.3 The relationship between dividends and overinvestment
The previous researches
In recent years, there has been an increasing amount of literature on abnormal investment, which is referred as under- and over- investment (Guariglia & Yang,
Numerous studies have employed various methods to investigate abnormal investment patterns across different countries A notable research by S Fazzari et al (1987) utilized a fixed effect model to analyze U.S manufacturing firms from the Value Line database between 1969 and 1984, revealing that underinvestment driven by financial constraints was evident in the U.S market.
(2006) documented that overinvestment concentratedly exists in U.S firms have the highest free cash flow levels while analysing 58,053 U.S firm-year observations obtained from Compustat annual database and excluded financial institutions from
1988 to 2002 This research was done by using Pooled regression model with Huber
Research indicates that investment inefficiencies, characterized by overinvestment and underinvestment, are prevalent across various countries and firm sizes Franzoni (2009) found that overinvestment is mainly observed in large firms, while underinvestment is more common among a broader sample of listed companies, based on an analysis of 1,522 U.S firms from 1990 to 2001 Similarly, Ding et al (2010) demonstrated evidence of overinvestment in all types of Chinese enterprises by analyzing 100,112 firms from 2000 to 2007 using the System GMM approach Cai (2013) further confirmed this trend among non-financial companies listed on the Shanghai and Shenzhen stock exchanges from 2003 to 2010 through multivariate regression analysis Guariglia and Yang (2016) expanded on these findings, documenting significant investment inefficiencies among 2,113 A-share listed firms in China from 1998 to 2014, attributing these issues to financing constraints and agency problems In Singapore, Farooq et al (2015) reported that 52% of firms engaged in appropriate investments, while 29% overinvested and 19% underinvested, based on a study of 360 non-financial companies from 2005 to 2011 Additionally, Pellicani and Kalatzis (2019) identified similar patterns of over- and under-investment among 485 Brazilian firms from 1997 to 2007 These findings highlight the widespread nature of abnormal investment across both developing and developed markets, posing risks to firms' capital-raising capabilities and future profitability.
Numerous studies have explored the relationship between free cash flow and investment, often through the lens of financial constraints theory A seminal empirical study by S Fazzari et al (1987) utilized OLS regression and a fixed effect model to analyze 442 U.S manufacturing firms from 1970 to 1984 This research revealed that firms with cash flow below their optimal level exhibited a greater sensitivity to underinvestment, indicating a higher likelihood of facing financing constraints Subsequent studies, such as those by Almeida and Campello (2007), further support these findings.
Research has consistently shown a significant positive relationship between investment and cash flow in financially constrained firms across various countries Denis and Sibilkov (2010) identified higher investment-cash flow sensitivities in constrained U.S firms using advanced econometric methods Similarly, Carpenter and Guariglia (2008) revealed a significant association between cash flow and investment in 693 UK firms from 1983 to 2000, highlighting the impact of financing constraints Mulier et al (2016) confirmed this trend in six European countries, including Belgium and France, from 1996 to 2008, where constrained firms exhibited the strongest relationship Furthermore, Bassetto and Kalatzis (2011) applied a Bayesian econometric model to 367 large Brazilian firms between 1997 and 2004, finding that firms with higher investment-cash flow sensitivity are more financially constrained In Pakistan, Riaz et al (2016) corroborated these findings in a study of 288 listed companies, utilizing first-difference GMM analysis from the State Bank of Pakistan and the Karachi Stock Exchange.
Research has explored the relationship between free cash flow and investment, highlighting the influence of agency problems Pawlina and Renneboog (2005) found that investment is significantly sensitive to cash flow, primarily due to agency costs, through a study of 985 UK firms from 1992 to 1998 Subsequent studies by Richardson (2006) and Moez and Amina (2018) revealed that firms with high free cash flow often overinvest, a trend attributed to agency issues in U.S companies Ding et al (2010) and Cai (2013) further established a positive correlation between overinvestment and free cash flow among non-financial firms listed in China, reinforcing agency theory X Chen et al (2016) corroborated these findings, noting that Chinese firms with elevated free cash flow exhibit higher levels of overinvestment Francis et al (2013) expanded this understanding across 362 companies in 14 countries, confirming that investment sensitivity to free cash flow increases with poor corporate governance Additionally, studies by Hovakimian and Hovakimian (2009) and Guariglia and Yang (2016) indicated that both financial constraints and agency problems contribute to investment-cash flow sensitivity Overall, the relationship between cash flow and investment is evident globally, explained by financial constraints, agency costs, or a combination of both theories, with detailed findings summarized in Appendix 2.
Recent studies have explored the link between cash dividends and overinvestment, revealing that higher dividends can reduce agency costs, as suggested by Rozeff (1982) An analysis of 200 firms across 64 industries from 1974 to 1980 employed a multiple regression model to support this claim Lang and Litzenberger (1989) found that a decrease in dividends indicates a tendency to undertake negative net present value projects, aligning with the overinvestment hypothesis Their research, which analyzed common stock prices and returns from 1979 to 1984, was corroborated by subsequent studies, including Moin et al (2019), who noted lower dividends in overinvesting non-financial firms in Indonesia, and Farooq et al., who found that higher dividends correlate with lower overinvestment in Australian firms from 2005 to 2014 Wei et al (2019) highlighted that the 30% Rule's effectiveness in curbing overinvestment among Chinese firms diminishes in the presence of agency problems, while Iturriaga and Crisóstomo (2010) confirmed dividends' role in mitigating free cash flow issues in Brazilian firms However, some researchers, like Kato, Loewenstein, and Tsay (2002), argue that Japanese firms do not use dividend policy to address overinvestment Various methodologies, including OLS regression and propensity score matching, were employed across these studies, which generally suggest a negative relationship between dividends and overinvestment A summary of these findings can be found in Appendix 3.
A study by Le Ha Diem Chi and Chau (2019) analyzed 511 non-financial institutions listed on the Hanoi (HNX) and Ho Chi Minh City Stock Exchanges (HOSE) from 2008 to 2015, revealing a significant prevalence of overinvestment among Vietnamese enterprises Their findings indicate a positive correlation between overinvestment and free cash flow, aligning with agency theory To address overinvestment, Trong and Nguyen (2020) suggested that dividend policy can mitigate its adverse effects on firm performance, based on their analysis of all companies listed on HNX and HOSE from 2008 to 2018 using System GMM Despite existing research on the relationship between free cash flow, dividends, and abnormal investment, gaps remain for further exploration These insights pave the way for the forthcoming research topic, which will be thoroughly examined in this thesis.
Hypotheses for models
S Fazzari et al (1987) pioneering paper investigated about the sensitivity results of investment to internal finance as the first empirical measure for financial constraints Due to capital market imperfections and asymmetric information between corporate insiders, which are the borrowers, and outside creditors, which are the lenders, the usage of external finance such as bank loans, debt and equity lead to a cost premium to compensate for higher risk creditors that surpasses the costs of internal finance (Brennan & Subrahmanyam, 1996; Carpenter & Guariglia, 2008; Easley & O'hara, 2004; S Fazzari et al., 1987; Harbula, 2001; Le Ha Diem Chi & Chau, 2019; Myers, 1984; Myers & Majluf, 1984) This premium cost and the available of external funding force firms to use and prefer internal sources such as free cash flow, retain earnings to invest In the circumstance where firms faced insufficient funds, firms may have to forego good investment projects to avoid the excessively high cost premiums associated with applying for external finance In addition, when firms encounter financial constraints, negative cash flow shocks could lead to underinvestment Many studies such as Bond, Harhoff, and Van Reenen (1999); Carpenter, Fazzari, Petersen, Kashyap, and Friedman (1994) and Nickell and Nicolitsas (1999) researched and supported to this theory Therefore, a high positive sensitivity of underinvestment to negative free cash flow can be considered as evidence of financial constraints This leads to the financing constraints hypothesis as below:
H1.1 Financing Constraints Hypothesis: Firms which are more likely to face financing constraints exhibit positive impact and higher sensitivities of negative free cash flow on underinvestment
Vietnam is an emerging market characterized by a developing legal system and inadequate corporate governance, resulting in a lack of transparency This environment exacerbates agency problems between managers (agents) and shareholders (principals), primarily due to information asymmetry that creates conflicts of interest between the two parties (Guariglia & Yang, 2016; Jensen, 1986).
Managers often leverage their superior internal information compared to shareholders to make investment decisions that prioritize their own interests, including pursuing growth projects with negative NPV, supported by ample internal funds (Jensen, 1986; Kadapakkam et al., 1998; Shleifer & Vishny, 1997) Internal financing sources, such as free cash flow and retained earnings, allow managers to avoid market scrutiny, leading to potential overinvestment instead of distributing dividends to shareholders (Yilei Zhang, 2009) Consequently, firms with higher free cash flow are more likely to overinvest, indicating a positive correlation between overinvestment and free cash flow, which serves as evidence of agency problems This observation supports the agency problems hypothesis.
H1.2 Agency Cost Hypothesis: Firms which are more likely to face agency problems exhibit positive impact and higher sensitivities of positive free cash flow on overinvestment
Overinvestment occurs when managers exploit free cash flow for their own benefit, often by investing in negative NPV projects, particularly when free cash flow is positive, as explained by agency problems (Richardson, 2006) To address this issue, Mizuno (2007) suggests that firms should prioritize distributing cash as dividends to shareholders rather than engaging in unprofitable investments Research by Amidu (2007), Jensen (1986), and Jensen and Meckling (1976) indicates that cash dividend payouts can effectively reduce excessive managerial investments in unprofitable projects by limiting the availability of internal cash flow This finding is further supported by studies from Rozeff (1982), Easterbrook (1984), Jensen (1986), Alli, Khan, and Ramirez (1993), Biddle et al (2009), Al-Najjar and Kilincarslan (2019), and Cho et al (2019) A robust cash dividend policy enhances external monitoring, prompting managers to make more prudent investment decisions, thereby decreasing inefficient overinvestment In Vietnam, Trong and Nguyen (2020) also found that dividend policies can mitigate overinvestment levels and improve firm performance Consequently, it can be concluded that issuing cash dividends reduces free cash flow in publicly listed companies and curtails overinvestment issues, suggesting a negative relationship between dividend payout ratios and overinvestment.
H2 Cash dividend affects negatively to overinvestments caused by free cash flow.
RESEARCH METHODOLOGIES
Data, Sample and Variables
Our study analyzes a sample of 306 non-financial Vietnamese companies listed on the Ho Chi Minh Stock Exchange (HOSE) from 2008 to 2019 This sample represents 89.21% of the companies on the exchange and accounts for approximately 70% of the total market capitalization in HOSE.
We utilize secondary data gathered from the Ho Chi Minh Stock Exchange (HOSE) database, focusing on investment spending, growth opportunities, and key financial ratios such as leverage and dividend payout ratios This financial information is sourced from the financial statements of various companies.
This research analyzes a total of 3,672 firm-year observations, excluding financial firms, with variations in the number of observations due to data availability Utilizing the yearly Audited Consolidated Financial Statements, which align with the Vietnamese firms' fiscal reporting calendar, the study aims for consistent and unbiased results To achieve this, firms with fewer than three consecutive years of observations are excluded, and all variables, except for Age, are deflated to a value of 100% in 2010 using the Consumer Price Index (CPI).
Our research focuses on the factors influencing abnormal investment, specifically examining how free cash flow and dividend payout ratios affect investment behaviors We aim to shed light on whether financial constraints and agency problems contribute to underinvestment or overinvestment Additionally, this study highlights that cash dividends serve as a limiting factor against inefficient investment, particularly by analyzing their impact on overinvestment driven by free cash flow.
The author employs the accounting-based framework established by Richardson (2006) and Guariglia and Yang (2016) to measure investment expenditure Total investment (I_totali,t) is calculated as capital expenditure minus revenue from the sale of property, plant, and equipment, adjusted by total assets Following Guariglia and Yang's methodology, the author opts for a simpler proxy by excluding acquisitions and Research and Development (R&D) expenditures, as capital expenditure is widely recognized as a proxy for investment in finance and economics literature (Gentry & Hubbard, 1998), and R&D data is not available in Vietnam's financial records Total investment is categorized into two segments: new investment expenditure (I_newi,t) and maintenance investment expenditure (I_maini,t), which is derived from the sum of amortization and depreciation All financial figures are sourced from the annual financial statements of individual firms.
New investment expenditure (I_newi,t) comprises two key components: the expected investment in new positive NPV projects (Ie_newi,t), derived from the investment expectation model, and unexpected investment or abnormal investment expenditure (Iu_newi,t), which represents the residual from this model Abnormal investment levels can be categorized into overinvestment (Over_investmenti,t), indicated by a positive residual, and underinvestment (Under_investmenti,t), indicated by a negative residual All investment expenditure variables are normalized by total assets to ensure comparability.
The study on free cash flow, based on the research of Guariglia and Yang (2016), defines a firm's optimal cash flow level as the total of maintenance investment (I_maini,t) and anticipated investment expenditure (Ie_newi,t) Free cash flow (FCF) is determined by deducting this optimal cash flow (I_maini,t + Ie_newi,t) from the cash flow generated from operating activities (CFO).
Guariglia and Yang (2016) found that using expected investment expenditure (Ie_newi,t) is a more effective measure of free cash flow than traditional CAPEX, as actual CAPEX may be affected by financial constraints or agency costs, leading to inconsistent results Free cash flow can vary, being either positive or negative, depending on whether cash flow from operating activities (CFO) exceeds the optimal level of cash flow.
The frameworks for the construction of abnormal investment and free cash flow are illustrated as below
Figure 3.1 Framework for the construction of under- and over- investment
Figure 3.2 Framework for Free Cash Flow
This thesis examines cash dividend payout using the dividend payout ratio, defined as dividend per share divided by earnings per share, following the methodology of Yulian Zhang and Guo (2018) To assess growth opportunities, the research employs the Tobin Q ratio, as established in studies by Guariglia and Yang (2016) and others, which is calculated by summing market capitalization and the liquidating value of the firm's outstanding preferred stock, referencing foundational works by Brainard & Tobin (1968) and Tobin (1969, 1978).
Expected investment expenditure (Ie_new i,t ) Fitted value
Abnormal investment expenditure (Iu_new i,t ) Residuals
Investment expenditure necessary to maintain assets in place (I_main i,t )
Cash flow from operating activities (CFO)
Free Cash Flow (FCF) Positive Free Cash Flow
Investment expenditure necessary to maintain assets in place (I_main i,t )
Expected investment expenditure (Ie_new i,t) is determined by the fitted values of stock and market value of debt, scaled by total assets Market capitalization is calculated as a firm's share price multiplied by the number of outstanding common stock shares, while the market value of debt is derived from short-term liabilities minus short-term assets, plus the book value of long-term debt (Chung & Pruitt, 1994) Research by Y Wang, Wu, and Yang (2009) indicates that firms in less developed markets may not rely solely on market valuation for investment decisions Given that the Vietnamese stock market is an emerging and inefficient market with slow information transmission (Gupta, Yang), this finding is particularly relevant.
This thesis builds upon the research of Guariglia and Yang (2016) and Yeo (2018) by incorporating firm performance metrics, specifically Return on Assets (ROA), as a measure of firm performance Previous studies have established the significance of ROA in evaluating corporate effectiveness (Chari, Chen, & Dominguez, 2012; Y Chen & Hammes, 2004; Gleason, Mathur, & Mathur, 2000; Karaca & Eksi, 2012; Uwuigbe).
& Olusanmi, 2012), instead of stock returns in Richardson (2006)’s dynamic investment model
The author incorporates firm characteristics in the analysis by utilizing various variables, including cash level (the ratio of total cash and cash equivalents to total assets), firm size (the logarithm of total assets), leverage (total liabilities divided by total assets), firm age (the number of years since the firm was listed on HOSE), and tunneling (the sum of short-term and long-term other receivables scaled by total assets) Additionally, industry sectors are classified numerically from 1 to 12 based on Vietnam's listed industry sector classification from HOSE Dummy variables represent regional distinctions, assigning a value of one if the firm's headquarters are located in one of Vietnam's three main regions—North, Central, or South—and zero otherwise.
Definitions of all these variables are listed in appendix 4.
Research Models
3.2.1 Expectation model for firm investment expenditure decision level
This research aims to estimate the optimal level of investment expenditure in new positive NPV projects by regressing new investment spending on factors influencing investment decisions Building on the dynamic investment expectation model developed by Richardson (2006) and further explored by Guariglia and Yang (2016) and Yulian Zhang and Guo (2018), the study utilizes accounting-based measurements of new investment spending as the dependent variable, collected in year t.
This article analyzes various explanatory variables that may influence investment decisions, including new investment spending levels, cash reserves, growth opportunities, firm size, return on assets (ROA), leverage, and firm age Data for these factors is collected from the previous year (t-1), while firm age is assessed in the current year (t) The study posits a positive correlation between prior new investment spending (independent variable) and its future value (dependent variable), supported by empirical findings from several researchers, including Hubbard (1997), Lamont (2000), Barro (1990), Bates (2005), Richardson (2006), Guariglia and Yang (2016), and Yulian Zhang and Guo (2018) The research employs the Tobin Q ratio as a key metric, referencing works by Chung & Pruitt (1994) and Tobin (1969, 1978).
1977) as a proxy for investment opportunities followed studies by Guariglia and Yang (2016); Yulian Zhang and Guo (2018); Blose and Shieh (1997); Ang and Beck
The Tobin Q theory, as articulated by Tobin in 1969 and further developed in 1978 and 1977 with Brainard, posits that when the Tobin Q ratio exceeds 1, firms are incentivized to invest in additional capital by selling equity at elevated share prices This scenario arises because the value of capital surpasses the cost of acquisition, leading to increased investment activities Conversely, a Tobin Q ratio below 1 discourages firm investment Consequently, a higher Tobin Q ratio correlates with greater levels of new investment spending.
(2016) also found the predicted positive relation between new investment spending and Tobin Q, so the assumed sign for the relationship between them in the model is positive
A study by Y Wang et al (2009) indicates that firms in less developed markets, such as Vietnam, do not solely rely on market valuation for investment decisions due to the slow development of the stock market and insufficient financial and legal institutions (ANDO & SCHEELA, 2005) This thesis builds upon the research of Guariglia and Yang (2016) and Yulian Zhang and Guo (2018) by examining additional factors influencing new investment levels, particularly Return on Assets (ROA) as a measure of firm performance (Y Chen & Hammes, 2004; Gleason et al., 2000; Karaca & Eksi, 2012; Sheng et al., 2012; Uwuigbe & Olusanmi, 2012), rather than stock returns as suggested in Richardson's (2006) dynamic investment model Kim, Xiang, and Lee (2009) found a significant correlation between heavy investment and strong firm performance, while Guariglia and Yang (2016) and Yulian Zhang and Guo (2018) also identified a positive relationship between ROA and new investment spending, leading to the assumption of a positive correlation in this model.
Previous research indicates a negative relationship between leverage and investment, highlighting that increased leverage diminishes a firm's capacity to finance growth-oriented investments due to liquidity constraints High levels of debt can undermine management and shareholder incentives, compelling managers to prioritize debt repayment over new investment opportunities Consequently, it is anticipated that leverage adversely affects the level of new investment spending.
For control variables such as Cash level, Firm Size and Firm Age, several studies has documented a sensitivity of firm level investment to these measures (Barro, 1990;
Research indicates a positive relationship between firm size and cash reserves with new investment levels, as larger firms typically find it easier to secure additional financing (Adelino, Ma, & Robinson, 2017; Fazzari et al., 1987; Hubbard, 1997) However, many small, older firms show little interest in growth or seizing investment opportunities (Hurst & Pugsley, 2011) In contrast, younger firms often possess better investment prospects and experience higher sales growth, making their investment spending more responsive to cash flow (Chaddad & Heckelei, 2003; Schaller, 1993) Consequently, empirical studies suggest a negative correlation between firm age and new investment spending (Richardson, 2006; Guariglia & Yang, 2016; Yulian Zhang & Guo, 2018).
The model incorporates various indicator variables, including firm-specific, time-specific, industry-specific, and province-specific effects, within the error term to account for additional variation in new investment expenditure that existing variables do not explain The indexing system uses i for firms, t for years (from 2008 to 2019), j for industries, and p for provinces The error term is composed of five components: vi represents firm-specific effects, vt captures time-specific effects through year dummy variables to reflect business cycle influences, and vj denotes industry-specific effects, which are represented by a numerical classification of industries from 1 to 12 based on Vietnam's listed sectors from HOSE Additionally, vp accounts for province-specific effects by incorporating province dummy variables to address disparities across regions, while vj,t considers industry-specific business cycles through the interaction of industry classifications with time dummies Lastly, εi,t signifies the idiosyncratic component of the model.
The fitted value from the regression estimates the expected new investment expenditure for positive NPV projects, while the residual represents abnormal investment expenditure Utilizing a dynamic model based on studies by Richardson (2006), Guariglia and Yang (2016), and Yulian Zhang and Guo (2018), this thesis incorporates a partial adjustment mechanism and addresses unobserved factors among the regressors Additionally, all independent variables, except age, are lagged to mitigate simultaneity issues, as suggested by Duchin, Ozbas, & Sensoy (2010) and Polk & Sapienza (2008) These methodologies enhance the consistency and unbiased nature of the empirical results, with variable definitions and predicted relationships detailed in Appendix 5.
3.2.2 The relationship between free cash flow and abnormal investment level
The author examines the influence of free cash flow on abnormal investment levels by building on the research of Richardson (2006) and Guariglia and Yang (2016) This analysis involves regressing abnormal investment against free cash flow using two distinct models (model 2.1 and model 2.2) that categorize firm-year observations into under-investing and over-investing firms These categories are determined based on the abnormal investment expenditure (Iu_newi,t), derived from the residuals of model 1.
Model 2.1 analyzes firm-year observations of underinvesting firms, characterized by negative abnormal investment levels (Iu_newi,t0) Both models incorporate negative and positive free cash flow as explanatory variables, defined through the interaction of free cash flow (FCFi,t) and a dummy variable (DumFCF0 for positive) Free cash flow is calculated by deducting the optimal cash flow level (I_maini,t + Ie_newi,t) from cash flow from operating activities (CFO) The dummy variable equals 1 for firms with negative or positive free cash flow and 0 otherwise, as supported by previous research (Almeida & Campello, 2007; Audretsch & Elston, 2002; Benito, 2005; Guariglia, 2008; Myers).
The financing constraints hypothesis suggests a positive relationship between negative free cash flow and underinvestment, indicating that financially constrained firms are likely to underinvest Supporting this, research by Richardson (2006), Guariglia and Yang (2016), Le Ha Diem Chi and Chau (2019), Carpenter and Guariglia (2008), S Fazzari et al (1987), and Myers and Majluf (1984) aligns with the agency problems hypothesis, which posits that positive free cash flow significantly influences overinvestment, demonstrating that firms facing agency issues tend to overinvest.
In the two models, indicator variables like firm-specific effects (vi) and time-specific effects (vt) are utilized for control purposes However, industry-specific business cycle effects (vj,t), as well as industry-specific (vj) and province-specific effects (vp), are excluded from these equations due to the application of fixed effects models (FEM), which inherently eliminate these effects through the differencing process For detailed definitions of the variables and their predicted relationships, please refer to Appendix 6.
3.2.3 The relationship between dividends and overinvestment
The study investigates the impact of cash dividends on over-investment to address the third research question Following the methodology of Yulian Zhang and Guo (2018), the author regresses over-investment—defined as the residual values from model 1 exceeding zero—against cash dividends, measured by the dividend payout ratio, free cash flow, and other control variables for the same year The regression analysis focuses on firm-year observations that exhibit over-investment.
The dividend pay-out ratio (DPR) serves as a crucial explanatory variable in understanding investment behaviors Research indicates that a well-structured dividend pay-out policy can act as a constraint on over-investment by alleviating agency problems, enhancing external monitoring, and encouraging managers to carefully consider their investment choices Consequently, this leads to a reduction in inefficient investments, such as over-investment, as supported by various studies (Al-Najjar & Kilincarslan, 2019; Alli et al., 1993; Amidu, 2007; Biddle et al., 2009; Cho et al., 2019; Easterbrook, 1984; Jensen, 1986).
& Meckling, 1976; Rozeff, 1982) Therefore, the influence of dividend pay – out ratio is assumed to have a negative correlation on over – investment
The independent variables analyzed include investment opportunities (Tobin Q), leverage, free cash flow, firm age, firm size, and tunneling, all measured in year t The Tobin Q ratio, which serves as a proxy for investment opportunities, is supported by research from Brainard & Tobin (1968), Chung & Pruitt (1994), and others This model follows the investment theory established by Tobin in 1969 and 1978, as well as Tobin and Brainard in 1977, highlighting the significance of Tobin Q in evaluating firm performance and investment potential.
Research methods
Descriptive statistics, as noted by Abebe, Daniels, McKean, and Kapenga (2001a), serve as concise coefficients that summarize data sets, representing either an entire population or a sample These statistics are categorized into measures of central tendency—such as mean, median, and mode—and measures of variability, which include standard deviation, variance, minimum, and maximum values By utilizing descriptive statistics, researchers can effectively summarize statistical data for each variable, facilitating easier analysis and investigation of their research problems.
This research employs panel data estimations utilizing the fixed effects model (FEM), random effects model (REM) with clustered standard errors, and the System-Generalized Method of Moments (system-GMM) Building on the foundational studies of Richardson (2006) and Guariglia and Yang (2016), these methods are applied to accurately estimate parameters in the analysis The common panel data regression model serves as the framework for these estimations.
𝑦 𝑖𝑡 = 𝑎 + 𝑏𝑥 𝑖𝑡 + 𝜀 𝑖𝑡 (Equation 3.1) Where y is the dependent variable, x is the independent variable, a and b are coefficients, i and t are indices for individuals and time, and ɛit is the error term
As for random effects model (REM), it is one of the most popular models for panel data The usual REM is:
In the model, "a" denotes the unique intercept for each entity, resulting in n entity-specific intercepts The dependent variable, represented as "yit," varies by entity (i) and time (t) Meanwhile, "xit" signifies an independent variable, with "b" as its corresponding coefficient The term "uit" captures the between-entity error, while "εit" reflects the within-entity error.
The random-effects model (REM) is recommended when differences among entities impact the dependent variable, as it enables generalization of inferences beyond the sample used (Torres-Reyna, 2007) Some researchers argue that REM is more efficient than the fixed-effects model (FEM) because it estimates fewer parameters Additionally, REM is suitable when the intercept for each cross-sectional unit is uncorrelated with the regressors, and it allows the entity's error term to remain uncorrelated with the predictors, thereby enabling time-invariant variables to serve as explanatory factors (Abebe et al., 2001b).
About fixed effects model (FEM), it is used to control for omitted variables that differ between cases but are constant over time The model may be formulated as:
The fixed-effects model (FEM) is utilized to examine the effects of time-varying variables on a dependent variable, denoted as yit, where i represents the entity and t indicates time In this model, a signifies the unknown intercept for each entity, while xit denotes an independent variable with b as its corresponding coefficient, and uit is the error term According to Torres-Reyna (2007), FEM investigates the relationship between predictor and outcome variables within unique entities that possess distinct characteristics that may influence these variables The model assumes that inherent individual factors can affect or bias the predictor and outcome variables, necessitating control for these influences Furthermore, FEM posits that time-invariant characteristics are specific to each individual and should not correlate with other individual traits (Borenstein et al.).
2009) In order to get the results consistent and unbiased, Hausman test would be applied to select the best fit model between FEM and REM (Durbin, 1954)
In the presence of both heteroskedasticity and autocorrelation within a fixed effect model, it is advisable to utilize clustered heteroskedasticity and autocorrelation-consistent (HAC) standard errors These clustered standard errors account for heteroskedastic and autocorrelated errors within individual entities while maintaining independence across different entities This approach enhances the nuance, accuracy, and informativeness of the results without altering the fixed effects estimator, as supported by research from Driscoll & Kraay (1998), Nichols & Schaffer (2007), Rogers (1994), and Stock & Watson (2006).
The System-Generalized Method of Moments (System-GMM) is utilized when errors in models cannot be addressed through Fixed Effects Models (FEM) or Random Effects Models (REM), even with clustered standard errors For example, when a lagged dependent variable (yi,t-1) is included as an independent variable in panel data estimation, it can exacerbate measurement errors and inflate standard errors This results in biased estimates of the coefficient for the lagged dependent variable, a bias that cannot be corrected by simply increasing the sample size or employing FEM or REM (Nickell).
The System-Generalized Method of Moments (System-GMM) is a widely used solution for addressing endogeneity issues, correlation, heteroskedasticity, and serial correlation in panel data, as highlighted by Hall and Inoue (2003) and Arellano and Bond (1991) This estimator relies on a set of instruments to correct for errors and assumes these instruments are exogenous (Thanh, 2014) It is particularly effective for datasets characterized by a "small T, large N" structure, meaning few time periods and many individuals (Roodman, 2009) The identification of equations can be classified as under-identified, exactly identified, or over-identified based on the relationship between the number of instruments and regressors While System-GMM is generally effective in resolving model errors, the reliability of results must be validated through diagnostic tests Specifically, valid outcomes are indicated when the first autocorrelation test shows a significant p-value, the second autocorrelation test shows a non-significant p-value, the Hansen test yields a p-value greater than 0.1 but less than 0.25, and the number of instruments is fewer than the number of groups (Roodman, 2009).
This study investigates the determinants of abnormal investment, focusing on factors like free cash flow and cash dividend pay-out The author addresses three key research questions sequentially, employing appropriate methodologies such as Fixed Effects Model (FEM), Random Effects Model (REM), and System Generalized Method of Moments (System-GMM) using STATA 14.0 software This rigorous approach ensures the development of robust and consistent models for drawing conclusions.
This thesis is conducted with the following main steps and these stages would be illustrated through the process diagram below
Figure 3.3 Steps in research process
Choose FEM/REM Exclude Endogeneity Include Endogeneity
FEM/REM with clustering standard errors
Hansen test’s result is valid p-value AR(1) is significant p-value AR(2) is insignificant