This study examines the effect of political connections on firms' ability to attract institutional equity capital in Malaysia.
Based on a dataset of 865 Malaysian publicly listed firms comprising 16,190 firm-year observations from 2000 to 2022, we employ an ordinary least squares (OLS) model to examine the relationships between political connections and institutional ownership, including domestic institutional ownership, long-term institutional ownership and blockholding ownership.
Politically connected firms (PCFs) attract significantly higher levels of institutional ownership, particularly from domestic and long-term institutional investors as well as blockholders who prioritise growth prospects and sustained performance. Furthermore, these effects are largely driven by government-linked companies (GLCs). The evidence indicates that institutional investors do not respond uniformly to all forms of political connections.
The findings provide important guidance for firm managers in understanding how political ties influence access to external equity capital. They also offer insights for institutional investors in evaluating the trade-offs between potential benefits and governance risks associated with PCFs.
The results provide policymakers with evidence on how political connections shape capital allocation in the Malaysian market. This may support policy reforms aimed at improving transparency, reducing political favouritism and strengthening investor protection mechanisms.
This study advances the literature by examining how institutional investors interpret political connections through the lens of political economy and corporate governance. By resolving the tension between political protection and agency risk, it shows that political connections function as both strategic resources and informative signals in investment decisions. The focus on ownership heterogeneity further deepens understanding of institutional investment in emerging markets. Despite the costs associated with elite political ties, institutional investors systematically incorporate political considerations into their capital allocation decisions.
1. Introduction
Political connections remain a central factor shaping firm performance and governance in emerging economies, where governments play a significant role in allocating resources and regulating markets (Alshirah et al., 2022; Anggraini and Widarjo, 2020; Chen et al., 2017; Nguyen et al., 2025; Sun and Ai, 2020; Wong and Hooy, 2018, 2024). In these contexts, business leaders often cultivate ties with political actors to secure preferential access to government financing, procurement contracts and regulatory advantages (Wong, 2025; Yu et al., 2020). Such connections are not incidental but are embedded institutional mechanisms that influence organisational outcomes, especially in economies characterised by crony capitalism. While political affiliations can generate substantial benefits, they also introduce governance risks, including agency conflicts, political interference and reputational concerns, which may undermine a firm's ability to attract high-quality external capital (Peranginangin et al., 2021; Ren et al., 2025).
This duality reflects a fundamental theoretical tension in the literature. On the one hand, political connections may serve as a protection mechanism by providing access to resources, regulatory support and resilience during adverse conditions (Alam and Houston, 2025; Wong, 2025). On the other hand, they may exacerbate agency problems, increase opacity and facilitate rent-seeking behaviour (Tee et al., 2021a). Whether political connections are ultimately viewed as valuable strategic resources or sources of agency risk remain an important question, particularly from the perspective of institutional investors. This issue is especially salient in emerging markets, where firms often face constrained access to bank financing or high borrowing costs, making institutional equity a critical source of capital for growth (Lu et al., 2022; Tawfik et al., 2024).
Despite the growing literature on political connections and institutional ownership, several important issues remain unresolved. First, existing research provides evidence consistent with both theoretical perspectives, yielding competing predictions about how institutional investors respond to politically connected firms (PCFs). Accordingly, it remains unclear whether institutional investors view political connections as value-enhancing strategic assets or governance liabilities when allocating equity capital. Resolving this theoretical ambiguity is important because firms increasingly rely on external equity financing as they expand beyond their internal funding capacity. Understanding how political connections shape institutional investors' capital allocation decisions therefore provides important insights into firms' access to external equity capital.
Second, an empirical gap exists regarding institutional investor heterogeneity. Although institutional ownership has expanded rapidly in emerging markets, tripling since the early 1990s (Khorana et al., 2005), prior studies generally treat institutional investors as a homogeneous group. Consequently, little is known about whether domestic institutional investors, long-term institutional investors and blockholders respond differently to political connections. This limitation is particularly important because institutional ownership plays a critical role in organisational sustainability, especially in environments characterised by volatile cash flows and limited access to traditional financing (Motta, 2017). The issue is further amplified in capital-intensive sectors that depend on long-term funding commitments (Feng and Tseng, 2019), where investment decisions are shaped by broader institutional conditions such as legal protections, market structures and governance frameworks (Panicker et al., 2019).
Third, a contextual gap exists in emerging-market settings. While political connections are especially influential in economies characterised by concentrated ownership, government intervention and political patronage, evidence remains limited regarding how institutional investors evaluate political ties in such environments. Existing emerging-market studies, including Abdul Wahab et al. (2009), Benjamin et al. (2016) and Qasem et al. (2023), demonstrate that PCFs are associated with higher institutional ownership and improved governance outcomes. However, these studies primarily examine the governance consequences of institutional investor presence, such as audit quality, dividend policy and audit report timeliness, rather than whether institutional investors themselves interpret political connections as favourable or unfavourable signals when making investment decisions. As a result, our understanding of how political ties influence firms' ability to attract different forms of institutional equity capital remains incomplete.
To address these gaps, this study examines whether political connections influence firms' ability to attract institutional equity capital and whether these effects vary across different categories of institutional investors. Specifically, we investigate the association between political connections and overall institutional ownership, domestic institutional ownership, long-term institutional ownership and blockholding ownership. By shifting the analytical focus from the consequences of institutional ownership to the investment decisions of institutional investors themselves, we provide a theoretically grounded explanation of how political ties affect capital allocation decisions.
Our theoretical framework integrates two complementary perspectives. First, we draw on crony capitalism and political patronage theory, which suggest that political ties provide firms with access to government contracts, financing and regulatory advantages while simultaneously creating governance risks through agency conflicts and managerial entrenchment (Tan and Wong, 2024; Tee, 2020; Tee et al., 2021a). Second, we draw on prospect theory and research on institutional investor heterogeneity, which emphasise that investors differ in their horizons, strategic priorities and tolerance for risk (Reichenbach and Walther, 2025). Domestic investors leverage local knowledge, long-term investors prioritise stability and sustainable returns and blockholders actively monitor management. Behavioural finance research further suggests that institutional investors' assessments of PCFs are shaped not only by rational evaluation but also by cognitive biases and heuristics (Chen et al., 2007). Political ties may convey government backing and stability, yet they may also trigger concerns related to opacity, rent-seeking and political vulnerability, particularly in the presence of loss aversion, home bias and herding behaviour (Khwaja and Mian, 2005; Qasem et al., 2023). These behavioural dynamics imply that political connections function as ambiguous signals that may attract some investors while deterring others (Tee et al., 2022; Wong et al., 2025). Taken together, these perspectives enable us to examine how institutional investors resolve the tension between the benefits and risks associated with political connections.
Malaysia provides an ideal setting for examining this issue. The legacy of the New Economic Policy, introduced in 1969, cultivated extensive patronage networks and entrenched ties between ruling elites and private firms, particularly through government-linked companies (GLCs) under the Ministry of Finance (Gomez and Jomo, 1999; Johnson and Mitton, 2003). Although the policy formally ended in the 1990s, its influence persists and continues to shape contemporary ownership structures, governance practices and corporate behaviour (Gomez et al., 2017). Malaysia also exhibits one of the highest levels of ownership concentration in Southeast Asia. By the end of 2020, Bursa Malaysia recorded a market capitalisation of RM3.4 trillion, with institutional investors holding roughly 43% of the market (Securities Commission Malaysia, 2020; OECD, 2022). This ownership structure, together with the strategic role of institutional investors in monitoring firms, makes Malaysia an ideal setting for examining how political ties influence equity allocation. The country's consistently high position on the Crony Capitalism Index further highlights the relevance of political affiliations in shaping market outcomes (The Economist, 2023). Within this context, our hand-collected classification of PCFs allows for a precise assessment of heterogeneous political ties and their implications for institutional ownership.
Drawing on a comprehensive dataset of Malaysian publicly listed firms covering 2000 to 2022, our findings indicate that political connections exert a positive influence on institutional ownership, with the strongest effects observed among domestic institutional investors, long-term investors and blockholders who emphasise sustainability and long-term value creation. This evidence suggests that PCFs are more successful in attracting equity capital from investor groups that value stability and strategic horizons. The analysis extends prior research that examined the effects of political connections on stakeholders such as customers, employees and suppliers (Li et al., 2016, 2018; Yan and Lu, 2019) by focusing on institutional investors as critical external stakeholders in the financing landscape. Whereas earlier studies predominantly investigated the impact of political ties on firm performance and risk outcomes (Ding et al., 2015; Nguyen et al., 2023; Peranginangin et al., 2021; Shen et al., 2015; Wong and Hooy, 2018, 2024), our findings redirect attention to ownership structures and reveal how political affiliations shape the investment behaviour of institutional investors themselves.
Nevertheless, we find that not all PCFs are equally attractive to institutional investors. Institutional investors maintain significant holdings in GLCs to maximise long-term returns, whereas this pattern does not extend to non-GLCs connected through directors, ruling elites' family members, informal business networks or politically affiliated chief executive officers (CEOs). Domestic institutional investors, long-term institutional investors and blockholders exhibit a stronger preference for GLCs, reflecting an emphasis on sustainable value creation and governance quality. Overall, the evidence suggests that institutional investors, on average, interpret political connections as a protection mechanism rather than a source of agency risk, although this interpretation varies across investor types and forms of political ties.
This study makes several contributions to the literature. First, the theoretical contribution is to explain how institutional investors resolve the tension between the protection benefits and agency risks associated with political connections. By integrating crony capitalism and political patronage theory with prospect theory, we demonstrate that institutional investors do not interpret political connections uniformly but evaluate them according to their investment horizons, monitoring capabilities and tolerance for political risk.
Second, the empirical contribution is to provide evidence on the heterogeneous relationship between political connections and institutional ownership. We show that domestic investors, in contrast to foreign and US investors highlighted in Aggarwal et al. (2011), Ferreira and Matos (2008), and Yu and Wang (2025), are more willing to allocate capital to PCFs. This reflects their comparative advantage in monitoring due to geographic, linguistic and cultural proximity, consistent with the arguments of Tee (2017, 2018, 2019a, 2020) and Tee et al. (2018). We further show that PCFs attract long-term institutional investors who value stability and growth opportunities, supporting Kim et al.’s (2017, 2019) view of patient investors as stabilising forces. In addition, political connections enhance a firm's attractiveness to blockholders, whose involvement provides high-quality monitoring and reinforces the resource-based view of political ties as strategic assets.
Third, the contextual contribution is to extend understanding of political connections within Malaysia's unique institutional environment, which is characterised by crony capitalism, political patronage and extensive government-linked ownership structures. By disaggregating both political connections and investor categories, we show how differences in investment horizons, strategic priorities and tolerance for political risk shape institutional investors' interpretation of political signals. We further demonstrate how political ties operate as both material and reputational advantages in Malaysia's politically centralised environment, where political cycles and coalition dynamics influence firm strategies and investor behaviour. These findings provide novel empirical insights that advance theoretical understanding of how political connections shape investor behaviour in emerging-market settings.
2. Literature review and hypotheses development
Scholarly interest in the strategic value of political connections has long focused on their implications for firm performance, resource access and risk exposure risk (Petrou and Thanos, 2014; Wong and Hooy, 2025; Yu et al., 2020). A dominant stream rooted in crony capitalism and political patronage theory argues that political ties provide firms with preferential access to finance, regulatory discretion, government contracts and protection from competitive pressures (Faccio, 2006; Shefter, 1977; Shleifer and Vishny, 1994). Evidence from emerging markets further suggests that such advantages are particularly pronounced where institutional environments are weak and state intervention is pervasive (Gomez and Jomo, 1999; Khwaja and Mian, 2005; Goldman et al., 2009). Within this view, political connections are primarily interpreted as a source of stability and long-term value creation.
A competing stream of research, however, challenges this optimistic interpretation by emphasising the governance and efficiency costs of political ties. While political connections may provide short-term insulation during crises such as the Asian financial crisis, the TARP intervention period and the COVID-19 shock (Faccio et al., 2006; Acemoglu et al., 2016; Wong et al., 2025), they may simultaneously intensify agency problems, weaken monitoring and encourage rent-seeking behaviour (Peranginangin et al., 2021; Ren et al., 2025; Tan and Wong, 2024). High-profile governance failures, including Malaysia's 1MDB case, further illustrate how political embeddedness can undermine transparency and facilitate expropriation (Jones, 2020). Collectively, these contrasting findings reflect a fundamental theoretical divide between a political protection view and an agency risk view, leaving unresolved how external stakeholders evaluate PCFs under uncertainty.
Within this fragmented debate, institutional investor research provides an important but incomplete perspective. Institutional investors are widely characterised as sophisticated monitors that rely not only on financial fundamentals but also on credibility signals related to reputation and policy alignment (Bushee et al., 2003; Celiktas et al., 2025; Chen et al., 2007; Dossa et al., 2025; Kim et al., 2017, 2019; Qasem, 2025). In environments characterised by information asymmetry and weak enforcement, political connections may therefore serve as heuristic cues of regulatory access, policy support and operational resilience (Anggraini and Widarjo, 2020). Evidence from Tee and Hooy (2023) and Wong (2025) indicates that PCFs are perceived as more resilient and better positioned to manage policy uncertainty, while Liu et al. (2025) show that political alignment enhances market credibility. However, existing studies largely document these associations without explaining how investors resolve the inherent trade-off between perceived protection and governance risk.
Behavioural theory offers additional insight into this ambiguity. Prospect theory suggests that loss-averse investors disproportionately value signals that reduce uncertainty and downside risk (Kahneman and Tversky, 1979). Accordingly, political connections may function as psychological anchors that shape perceptions of stability. This effect is likely to be stronger in institutional environments characterised by concentrated political authority and state-influenced capital allocation, as described by elite theory (Savage and Williams, 2008). Malaysia provides a particularly relevant context, given the entrenched linkages between political elites, government-linked entities and corporate ownership structures (Apaydin, 2025; Gomez et al., 2017; Qasem et al., 2023; Wong and Hooy, 2021).
Building on these competing perspectives, this study integrates political patronage theory, crony capitalism theory and prospect theory to argue that political connections simultaneously represent both resource-based advantages and behavioural signals of stability. In the Malaysian setting, where state influence over capital markets is substantial, we contend that the protective interpretation is likely to dominate investor assessment. Accordingly, institutional investors are expected to view political connections more as a source of protection than as a source of agency risk, leading to more favourable allocation decisions towards firms with credible political ties. Therefore, the following hypothesis is developed:
PCFs are associated with higher levels of institutional ownership.
Understanding the Malaysian business environment requires attention to institutional and cultural features that shape investment behaviour. Relationship-based capitalism continues to structure corporate activity, and prior studies (Tee, 2017; Tee et al., 2018; Tee and Rasiah, 2020) demonstrate how political affiliations and local norms influence firm operations. While these works provide descriptive insight, the mechanisms through which domestic institutional investors interpret political ties in forming investment decisions remain underexplored.
Geographical proximity theory provides a robust framework for this context. Domestic institutional investors' closeness to firm headquarters reduces information asymmetry and facilitates monitoring through greater access to management and corporate activities (Ayers et al., 2011). These investors engage actively in shareholder meetings, emphasise governance quality and influence board appointments, which lowers the costs of evaluating PCFs. Chhaochharia et al. (2012) and Velte (2022) further show that domestic institutional investors guide managers towards profitable and sustainable strategies, suggesting that oversight is particularly meaningful when firms maintain political affiliations.
Behavioural finance perspectives further clarify investment choices. Home bias and familiarity effects lead investors to prefer firms with cultural or political proximity due to perceived informational advantages (Coval and Moskowitz, 1999; Huberman, 2001). In politically influenced markets such as Malaysia, domestic investors may also align with peers or government-supported priorities, reflecting herding behaviour (Ghazali, 2010; Ooi, 2025). The prominence of government-linked investment companies, including the Employee Provident Fund, Khazanah Nasional Berhad, Kumpulan Wang Amanah Pencen, Lembaga Tabung Angkatan Tentera, Lembaga Tabung Haji, Menteri Kewangan Diperbadankan and Permodalan Nasional Berhad, reinforces these tendencies. These institutions actively monitor their portfolio firms to enhance shareholder value and board transparency (Putrajaya Committee, 2015), and collectively account for 55–65% of institutional and domestic institutional investments in Malaysia (Tee, 2018).
Domestic institutional investors are likely to interpret political ties as signals of firm resilience, given their potential to reduce uncertainty and facilitate access to policy support, while remaining mindful of associated governance risks. In politically embedded environments such as Malaysia, the perceived benefits of stability and resource access are likely to outweigh these concerns. Accordingly, theory and prior evidence suggest that PCFs are more likely to attract domestic institutional investors. Based on this reasoning, the following hypothesis is proposed:
PCFs are associated with higher ownership by domestic institutional investors.
Varying investment horizons shape institutional behaviour in markedly different ways (Bushee, 1998; Gaspar et al., 2005). Short-term institutional investors tend to emphasise rapid financial outcomes and exert pressure on managers to prioritise immediate returns. In contrast, long-term institutional investors, characterised by lower portfolio turnover, undertake more comprehensive firm evaluations and support strategies that promote sustained value creation (Kim et al., 2017, 2019). Their focus on organisational durability and stable performance makes them particularly responsive to institutional environments that reduce uncertainty.
Political connections provide firms with continuity, protection and preferential access to resources, thereby reducing exposure to regulatory and economic uncertainty, which is particularly valuable for long-term investors. However, they may also entail governance risks and managerial entrenchment that could concern investors with extended investment horizons. In contexts where political institutions play a central role in shaping economic outcomes, the stability and resource advantages associated with political ties are likely to outweigh these governance concerns. From a behavioural finance perspective, long-term investors are inclined to favour firms that mitigate volatility as PCFs offer predictable access to government support (Tee et al., 2021a). This inclination is further reinforced by time horizon bias, whereby long-term investors prioritise sustained regulatory advantages and resource flows (Gamache et al., 2024). Prior studies also suggest that political affiliations enhance knowledge transfer, innovation capability and talent development, contributing to long-term value creation (Sun and Ai, 2020; Tee, 2018) and serving as strategic buffers against market, regulatory and macroeconomic shocks (Kubinec et al., 2021; Tee et al., 2022).
In Malaysia's corporate environment, where political influence shapes credit allocation, project approvals and access to government-linked opportunities, long-horizon investors place greater emphasis on firms that demonstrate political resilience and organisational continuity. Evidence suggests that such investors also incorporate governance quality and transparency when evaluating PCFs, aligning their attractiveness with long-term investment objectives (Wu et al., 2012). Accordingly, PCFs are likely to be viewed favourably by long-term institutional investors as they offer both stability and sustained performance potential. Collectively, the theoretical and contextual insights suggest that political connections enhance the appeal of firms to long-term institutional investors. Hence, the following hypothesis is proposed:
PCFs are associated with higher ownership by long-term institutional investors.
Blockholders face greater exposure to stock price volatility than widely diversified investors, which heightens their incentives to conduct rigorous firm evaluation and maintain ongoing monitoring efforts (Kim et al., 2019). Their substantial ownership positions compel careful consideration of factors that can strengthen firm resilience and future performance (Celiktas et al., 2025). In this regard, political connections can represent a strategically valuable asset. The resource-based view conceptualises political ties as intangible resources that facilitate preferential access to government support, regulatory accommodation and opportunities for long-term value creation (Gloßner, 2019; Khan et al., 2025; Tihanyi et al., 2019). These advantages can enhance a firm's competitive position and appeal to investors with concentrated holdings who seek stability and strategic returns.
Behavioural factors also shape blockholder decision-making. Overconfidence may lead blockholders to believe they can effectively manage governance challenges associated with political ties, while the endowment effect can strengthen their commitment to firms in which they already hold significant stakes (Crosby, 2018; Inghelbrecht and Tedde, 2024; Liu et al., 2016). Their heightened sensitivity to portfolio fluctuations further increases their attention to corporate governance and organisational reputation. To safeguard their investments, blockholders frequently engage in private dialogues with management, monitor executive performance and advocate for governance practices that support sustained firm performance (Aiken and Lee, 2020; Lyssimachou and Bilinski, 2023).
Existing studies emphasise the monitoring role of blockholders, yet relatively little attention has been paid to how politically embedded environments shape their assessment of firm prospects. In Malaysia, where political ties are closely intertwined with the corporate sector, PCFs may be particularly attractive to blockholders seeking stability and privileged access to strategic resources. These advantages are likely to reinforce the appeal of concentrated ownership, thereby increasing blockholder investment in such firms. Accordingly, political connections are expected to enhance firm attractiveness to blockholders by providing both strategic benefits and perceived stability. In accordance with this reasoning, the following hypothesis is proposed:
PCFs are associated with higher ownership by blockholders.
3. Research method
3.1 Sample and data
The study focuses on companies listed on the Bursa Malaysia Main Board from 2000 to 2022, with 2022 representing the most recent year for which complete data were available at the time of collection [1]. Financial data were obtained from the Refinitiv Eikon database, while information on institutional ownership and political connections was hand-collected from firms' annual and quarterly reports accessible via Bursa Malaysia and company websites. After excluding observations with missing data for any input variables, the final sample comprised 16,190 firm-year observations across 865 firms. To mitigate the influence of outliers, all continuous variables were winsorised at the 1% level on both tails.
3.2 Measures of institutional ownership
Institutional ownership is defined as the total value of all institutional holdings in a firm's stock divided by the firm's total market capitalisation at the end of each fiscal year. For analytical refinement, institutional ownership is further divided into specific categories. Domestic institutional ownership represents the total holdings of Malaysian-domiciled institutional funds divided by the firm's total market capitalisation.
Institutional ownership is also segmented according to the investment horizons of institutional investors. Investment strategies and holding periods are classified based on institutional investors' investment turnover, following Kilincarslan and Ozdemir (2018). To construct this measure, the quarterly churn rates for every institutional investor are estimated with Gaspar et al.’s (2005) model:
where is the set of firms owned by investor , while and denote the share price and the number of shares, respectively, of firm held by institutional investor at quarter . A higher churn rate indicates a shorter investment horizon, while a lower churn rate implies a longer investment horizon. The quarterly churn rates are subsequently aggregated to the firm level. Investor turnover is calculated with Equation (2):
where is the set of shareholders in firm , and implies the proportion of investor ’s ownership relative to the total institutional ownership in firm . Institutional investors are then classified into tertiles based on their turnover, following Attig et al. (2013) and Kim et al. (2019). Long-term institutional ownership refers to the combined holdings of investors in the lowest turnover tertile, divided by the firm's total market capitalisation.
Blockholding ownership captures the holdings of investors owning at least 5% of a firm's shares. is computed as the combined holdings of the top five blockholders divided by the firm's total market capitalisation (Lyssimachou and Bilinski, 2023).
3.3 Measure of political connections
Faccio (2006) classify a firm as politically connected if at least one of its controlling shareholders or top executives has ties to the government or politicians. In Malaysia, such connections often arise through immediate family members of ruling elites involved in business or businessmen with close personal or professional links to political figures. Our study accounts for changes in political connections over the study period, including resignations, deaths and changes in the Prime Minister.
Political connection data were meticulously hand-collected by reviewing the names of controlling shareholders and top executives listed in the sections on substantial shareholders, board of directors and profiles of key senior management in annual reports. To ensure consistency and comparability, our methodology follows established hand-collected datasets, including Fung et al. (2015), Wong and Hooy (2018), Peranginangin et al. (2021) and Tee et al. (2021b), which span the period from 2001 to 2018. The compiled list of PCFs was cross-validated against these prior studies and corroborated using reputable financial media sources (e.g. BERNAMA, New Straits Times, The Star, The Economist and The Edge) to ensure the continued relevance of individuals deemed politically connected. A binary variable, , is employed in this study.
3.4 Control variables
A set of variables previously associated with institutional ownership in prior studies (Attig et al., 2013; Kim et al., 2019; Lyssimachou and Bilinski, 2023), including market capitalisation , return on assets , price-to-sales ratio , book-to-market ratio , research and development spending , leverage and advertising spending , is included in the study models.
, measured as the natural logarithm of the firm's market capitalisation, is controlled given the institutional investors' preference for larger firms with more liquid stocks (Borochin and Yang, 2017; Dahlquist and Robertsson, 2001). Furthermore, (net income scaled by total assets) is included to proxy for organisational profitability. Profitable firms are more attractive to institutional investors, while low profitability ones often correlate with higher stock risk (Gompers et al., 2003; Hou et al., 2015). (market capitalisation-to-total revenue ratio), (book value of equity-to-market capitalisation ratio) and (research and development expenses scaled by total sales) are incorporated to capture firm risk and growth opportunities, given that institutional investors tend to favour companies with strong growth potential (Huang and Paul, 2017). As debt financing can serve as an alternative to equity financing (Jensen and Murphy, 1990), (total debt scaled by total assets) is taken into account. Finally, (advertising expenses scaled by total sales) is used to control market visibility effects (Lang et al., 2003). All the control variables are measured at the fiscal year-end to align with the timing of institutional holdings and minimise potential reverse causality.
3.5 Model specification
The following model, estimated via OLS, served to examine Hypotheses 1 through 4:
where the dependent variable is either , , or , while the independent variable of interest is . represents a set of control variables that account for firm-specific factors. Industry and year fixed effects control for variation across industries and time periods. denotes unspecified random factors. Standard errors are clustered at the firm level. Table 1 presents the descriptions of all variables used in the study.
Variable descriptions
| Abbreviation | Expected sign | Definition | Supporting literature | Source(s) |
|---|---|---|---|---|
| Panel A: The dependent variables | ||||
| N/A | Percentage institutional ownership is measured as the total value of all institutional holdings in a firm's stock divided by the firm's total market capitalisation at the end of each fiscal year | Tee (2018), Tee et al. (2018) | Authors' calculations based on hand-collected data from the annual reports | |
| N/A | Domestic institutional ownership is defined as the total holdings of Malaysian-domiciled institutional funds divided by the firm's total market capitalisation | Tee (2018), Tee et al. (2018) | Authors' calculations based on hand-collected data from the annual reports | |
| N/A | Long-term institutional ownership is measured as the combined holdings of investors in the lowest turnover tertile, divided by the firm's total market capitalisation | Attig et al. (2013), Kim et al. (2019) | Authors' calculations based on hand-collected data from the annual reports | |
| N/A | Blockholding ownership is defined as the combined holdings of the top five investors, each owning at least 5% of a firm's shares, divided by the firm's total market capitalisation | Lyssimachou and Bilinski (2023) | Authors' calculations based on hand-collected data from the annual reports | |
| Panel B: The dependent variable | ||||
| +/− | Political connections are defined as a binary variable equal to 1 if the firm is politically connected, and 0 otherwise | Faccio (2006) | Fung et al. (2015), Wong and Hooy (2018), Peranginangin et al. (2021), Tee et al. (2021b), and hand collected from annual reports | |
| Panel C: The control variables | ||||
| + | Market value is measured as the natural logarithm of the firm's market capitalisation | Borochin and Yang (2017), Dahlquist and Robertsson (2001) | Authors' calculations based on Refinitiv Eikon data | |
| +/− | Return on assets is measured as net income scaled by total assets | Gompers et al. (2003), Hou et al. (2015), Kim et al. (2019) | Authors' calculations based on Refinitiv Eikon data | |
| +/− | Price-to-sales is measured as the ratio of market capitalisation to total revenue | Lyssimachou and Bilinski (2023) | Authors' calculations based on Refinitiv Eikon data | |
| – | The book-to-market ratio is measured as the ratio of the book value of equity to market capitalisation | Attig et al. (2013) | Authors' calculations based on Refinitiv Eikon data | |
| +/− | R&D is measured as research and development expenses scaled by total sales | Kim et al. (2019) | Authors' calculations based on Refinitiv Eikon data | |
| +/− | Leverage is measured as total debt scaled by total assets | Lyssimachou and Bilinski (2023) | Authors' calculations based on Refinitiv Eikon data | |
| +/− | Advertising is measured as advertising expenses scaled by total sales | Lang et al. (2003) | Authors' calculations based on Refinitiv Eikon data | |
| Abbreviation | Expected sign | Definition | Supporting literature | Source(s) |
|---|---|---|---|---|
| Panel A: The dependent variables | ||||
| N/A | Percentage institutional ownership is measured as the total value of all institutional holdings in a firm's stock divided by the firm's total market capitalisation at the end of each fiscal year | Authors' calculations based on hand-collected data from the annual reports | ||
| N/A | Domestic institutional ownership is defined as the total holdings of Malaysian-domiciled institutional funds divided by the firm's total market capitalisation | Authors' calculations based on hand-collected data from the annual reports | ||
| N/A | Long-term institutional ownership is measured as the combined holdings of investors in the lowest turnover tertile, divided by the firm's total market capitalisation | Authors' calculations based on hand-collected data from the annual reports | ||
| N/A | Blockholding ownership is defined as the combined holdings of the top five investors, each owning at least 5% of a firm's shares, divided by the firm's total market capitalisation | Authors' calculations based on hand-collected data from the annual reports | ||
| Panel B: The dependent variable | ||||
| +/− | Political connections are defined as a binary variable equal to 1 if the firm is politically connected, and 0 otherwise | |||
| Panel C: The control variables | ||||
| + | Market value is measured as the natural logarithm of the firm's market capitalisation | Authors' calculations based on Refinitiv Eikon data | ||
| +/− | Return on assets is measured as net income scaled by total assets | Authors' calculations based on Refinitiv Eikon data | ||
| +/− | Price-to-sales is measured as the ratio of market capitalisation to total revenue | Authors' calculations based on Refinitiv Eikon data | ||
| – | The book-to-market ratio is measured as the ratio of the book value of equity to market capitalisation | Authors' calculations based on Refinitiv Eikon data | ||
| +/− | R&D is measured as research and development expenses scaled by total sales | Authors' calculations based on Refinitiv Eikon data | ||
| +/− | Leverage is measured as total debt scaled by total assets | Authors' calculations based on Refinitiv Eikon data | ||
| +/− | Advertising is measured as advertising expenses scaled by total sales | Authors' calculations based on Refinitiv Eikon data | ||
4. Empirical results
4.1 Descriptive statistics
The PCFs reflects significantly higher institutional ownership levels compared to non-PCFs (24.1% vs 14.8%) (see Table 2). This finding indicates the prominence of institutional investors as key shareholders in PCFs. Domestic institutional investors hold approximately 21.3% of equity, while long-term institutional investors constitute 21.9% of stock ownership. Collectively, the top five blockholders own approximately 19.9% of equity. Institutional investors favouring long-term value creation serve as primary shareholders in PCFs.
Descriptive statistics
| PCFs | Non-PCFs | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Obs | Mean | Median | Std dev | Min | Max | Obs | Mean | Median | Std dev | Min | Max | Mean diff. | |
| 6,319 | 0.241 | 0.208 | 0.198 | 0.000 | 0.876 | 9,871 | 0.148 | 0.104 | 0.142 | 0.000 | 0.477 | 0.093*** | |
| 6,319 | 0.213 | 0.175 | 0.177 | 0.000 | 0.874 | 9,871 | 0.128 | 0.085 | 0.135 | 0.000 | 0.415 | 0.085*** | |
| 6,319 | 0.219 | 0.187 | 0.189 | 0.000 | 0.852 | 9,871 | 0.101 | 0.069 | 0.124 | 0.000 | 0.384 | 0.118*** | |
| 6,319 | 0.199 | 0.149 | 0.137 | 0.000 | 0.827 | 9,871 | 0.097 | 0.066 | 0.127 | 0.000 | 0.342 | 0.102*** | |
| 6,319 | 2.500 | 2.372 | 0.749 | 0.802 | 4.762 | 9,871 | 2.150 | 2.080 | 0.600 | 0.610 | 4.450 | 0.350*** | |
| 6,319 | 0.049 | 0.048 | 0.098 | −0.723 | 0.652 | 9,871 | 0.047 | 0.048 | 0.105 | −0.798 | 0.599 | 0.002 | |
| 6,319 | 1.199 | 1.193 | 1.577 | 0.158 | 12.503 | 9,871 | 1.191 | 1.186 | 1.367 | 0.155 | 12.775 | 0.008 | |
| 6,319 | 0.667 | 0.519 | 0.888 | 0.006 | 3.883 | 9,871 | 0.419 | 0.396 | 0.676 | 0.003 | 2.738 | 0.248*** | |
| 6,319 | 0.010 | 0.011 | 0.123 | 0.000 | 0.454 | 9,871 | 0.005 | 0.010 | 0.117 | 0.000 | 0.340 | 0.005*** | |
| 6,319 | 0.406 | 0.398 | 0.219 | 0.008 | 1.734 | 9,871 | 0.379 | 0.359 | 0.222 | 0.005 | 1.656 | 0.027*** | |
| 6,319 | 0.008 | 0.009 | 0.113 | 0.000 | 0.313 | 9,871 | 0.005 | 0.006 | 0.099 | 0.000 | 0.206 | 0.003** | |
| PCFs | Non-PCFs | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Obs | Mean | Median | Std dev | Min | Max | Obs | Mean | Median | Std dev | Min | Max | Mean diff. | |
| 6,319 | 0.241 | 0.208 | 0.198 | 0.000 | 0.876 | 9,871 | 0.148 | 0.104 | 0.142 | 0.000 | 0.477 | 0.093*** | |
| 6,319 | 0.213 | 0.175 | 0.177 | 0.000 | 0.874 | 9,871 | 0.128 | 0.085 | 0.135 | 0.000 | 0.415 | 0.085*** | |
| 6,319 | 0.219 | 0.187 | 0.189 | 0.000 | 0.852 | 9,871 | 0.101 | 0.069 | 0.124 | 0.000 | 0.384 | 0.118*** | |
| 6,319 | 0.199 | 0.149 | 0.137 | 0.000 | 0.827 | 9,871 | 0.097 | 0.066 | 0.127 | 0.000 | 0.342 | 0.102*** | |
| 6,319 | 2.500 | 2.372 | 0.749 | 0.802 | 4.762 | 9,871 | 2.150 | 2.080 | 0.600 | 0.610 | 4.450 | 0.350*** | |
| 6,319 | 0.049 | 0.048 | 0.098 | −0.723 | 0.652 | 9,871 | 0.047 | 0.048 | 0.105 | −0.798 | 0.599 | 0.002 | |
| 6,319 | 1.199 | 1.193 | 1.577 | 0.158 | 12.503 | 9,871 | 1.191 | 1.186 | 1.367 | 0.155 | 12.775 | 0.008 | |
| 6,319 | 0.667 | 0.519 | 0.888 | 0.006 | 3.883 | 9,871 | 0.419 | 0.396 | 0.676 | 0.003 | 2.738 | 0.248*** | |
| 6,319 | 0.010 | 0.011 | 0.123 | 0.000 | 0.454 | 9,871 | 0.005 | 0.010 | 0.117 | 0.000 | 0.340 | 0.005*** | |
| 6,319 | 0.406 | 0.398 | 0.219 | 0.008 | 1.734 | 9,871 | 0.379 | 0.359 | 0.222 | 0.005 | 1.656 | 0.027*** | |
| 6,319 | 0.008 | 0.009 | 0.113 | 0.000 | 0.313 | 9,871 | 0.005 | 0.006 | 0.099 | 0.000 | 0.206 | 0.003** | |
Note(s): This table presents the descriptive statistics of all variables. The sample includes firm-year observations from fiscal years 2000–2022, where all control variables have non-missing values. The superscripts *, ** and *** denote significance at the confidence levels of 90%, 95% and 99%, respectively
Consistent with previous research (Tee, 2017; Yu et al., 2020), the sample PCFs demonstrate higher firm performance, investment expenditures and leverage, as well as larger market capitalisation relative to non-PCFs.
4.2 Correlations
Following Table 3, all four measures of institutional ownership are positively and significantly correlated with political connections. Most of the remaining correlation coefficients are significant, with magnitudes below 0.8. In computing the variance inflation factors (VIFs) for subsequent regression models, VIF values consistently fall below 10.0. Multicollinearity is not a significant issue in this study.
Correlations
| (1) | (2) | (3) | (4) | (5) | (6) | (7) | (8) | (9) | (10) | (11) | (12) | ||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| (1) | 1.000 | ||||||||||||
| (2) | 0.647*** | 1.000 | |||||||||||
| (3) | 0.461*** | 0.016** | 1.000 | ||||||||||
| (4) | 0.484*** | 0.281*** | 0.167*** | 1.000 | |||||||||
| (5) | 0.261*** | 0.147*** | 0.035*** | 0.129*** | 1.000 | ||||||||
| (6) | 0.216*** | 0.202*** | 0.021*** | 0.082*** | 0.245*** | 1.000 | |||||||
| (7) | −0.022** | −0.010** | −0.031*** | −0.018* | 0.003 | 0.335*** | 1.000 | ||||||
| (8) | 0.015 | 0.017 | 0.027*** | −0.026*** | −0.002 | 0.158*** | −0.063*** | 1.000 | |||||
| (9) | −0.087*** | −0.068*** | −0.005** | −0.037*** | 0.205*** | 0.351*** | 0.079*** | 0.049*** | 1.000 | ||||
| (10) | −0.004 | −0.009 | −0.000 | −0.002 | −0.014 | 0.087*** | 0.146*** | 0.005 | 0.030*** | 1.000 | |||
| (11) | 0.085*** | 0.103*** | 0.055*** | 0.089*** | 0.061*** | −0.004 | −0.186*** | −0.175*** | −0.190*** | −0.028*** | 1.000 | ||
| (12) | 0.048*** | 0.072*** | 0.039*** | 0.031*** | 0.062*** | 0.012 | −0.113*** | 0.216*** | 0.013 | −0.025*** | −0.048*** | 1.000 |
| (1) | (2) | (3) | (4) | (5) | (6) | (7) | (8) | (9) | (10) | (11) | (12) | ||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| (1) | 1.000 | ||||||||||||
| (2) | 0.647*** | 1.000 | |||||||||||
| (3) | 0.461*** | 0.016** | 1.000 | ||||||||||
| (4) | 0.484*** | 0.281*** | 0.167*** | 1.000 | |||||||||
| (5) | 0.261*** | 0.147*** | 0.035*** | 0.129*** | 1.000 | ||||||||
| (6) | 0.216*** | 0.202*** | 0.021*** | 0.082*** | 0.245*** | 1.000 | |||||||
| (7) | −0.022** | −0.010** | −0.031*** | −0.018* | 0.003 | 0.335*** | 1.000 | ||||||
| (8) | 0.015 | 0.017 | 0.027*** | −0.026*** | −0.002 | 0.158*** | −0.063*** | 1.000 | |||||
| (9) | −0.087*** | −0.068*** | −0.005** | −0.037*** | 0.205*** | 0.351*** | 0.079*** | 0.049*** | 1.000 | ||||
| (10) | −0.004 | −0.009 | −0.000 | −0.002 | −0.014 | 0.087*** | 0.146*** | 0.005 | 0.030*** | 1.000 | |||
| (11) | 0.085*** | 0.103*** | 0.055*** | 0.089*** | 0.061*** | −0.004 | −0.186*** | −0.175*** | −0.190*** | −0.028*** | 1.000 | ||
| (12) | 0.048*** | 0.072*** | 0.039*** | 0.031*** | 0.062*** | 0.012 | −0.113*** | 0.216*** | 0.013 | −0.025*** | −0.048*** | 1.000 |
Note(s): The superscripts *, ** and *** denote significance at the confidence levels of 90%, 95% and 99%, respectively
4.3 Regression results
Evidence from Table 4 reveals a statistically significant and positive association between political connections and institutional ownership. The results corroborate the findings by Tee and Hooy (2023) and Wong et al. (2025). Past studies (Abdul Wahab et al., 2009; Benjamin et al., 2016; Tee and Rasiah, 2020) suggest that PCFs attract a higher proportion of institutional investors because political ties enhance firm value by facilitating access to government contracts, preferential financing and favourable regulatory treatment, which is consistent with the predictions of crony capitalism and political patronage theory. Simultaneously, in Malaysia, where political influence permeates the institutional and corporate environment, these ties appear to function as a perceived safeguard for investors who must navigate opaque and politically shaped markets. This perceived protection elevates the value of political connections, contributes to higher market valuations and increases institutional investor demand. Cognitive heuristics such as availability bias may further reinforce the belief that political affiliations reduce downside risk, and in line with prospect theory, these signals of stability can prompt institutional investors to allocate more capital to PCFs. Therefore, the results support the prediction made in H1.
Political connections and institutional investors
| (1) | (2) | (3) | (4) | |
|---|---|---|---|---|
| 0.071*** (0.025) | 0.064*** (0.014) | 0.022* (0.012) | 0.041** (0.019) | |
| 0.049*** (0.018) | 0.033*** (0.011) | 0.017* (0.010) | 0.026* (0.014) | |
| −0.157*** (0.038) | −0.128*** (0.037) | −0.081* (0.048) | −0.094* (0.056) | |
| 0.073 (0.053) | −0.082 (0.051) | 0.042 (0.099) | −0.062 (0.069) | |
| −0.002** (0.000) | −0.001* (0.000) | −0.001* (0.000) | −0.001* (0.000) | |
| −0.003 (0.014) | −0.011 (0.014) | 0.007 (0.019) | 0.013 (0.019) | |
| 0.047* (0.026) | 0.050* (0.026) | 0.055* (0.028) | 0.055* (0.032) | |
| 0.026 (0.053) | 0.021 (0.050) | 0.013 (0.046) | 0.035 (0.068) | |
| Constant | 0.228*** (0.052) | 0.242*** (0.053) | 0.888*** (0.043) | 0.592*** (0.067) |
| Yes | Yes | Yes | Yes | |
| Yes | Yes | Yes | Yes | |
| Adjusted R2 | 0.124 | 0.121 | 0.119 | 0.152 |
| Obs | 16,190 | 16,190 | 16,190 | 16,190 |
| (1) | (2) | (3) | (4) | |
|---|---|---|---|---|
| 0.071*** (0.025) | 0.064*** (0.014) | 0.022* (0.012) | 0.041** (0.019) | |
| 0.049*** (0.018) | 0.033*** (0.011) | 0.017* (0.010) | 0.026* (0.014) | |
| −0.157*** (0.038) | −0.128*** (0.037) | −0.081* (0.048) | −0.094* (0.056) | |
| 0.073 (0.053) | −0.082 (0.051) | 0.042 (0.099) | −0.062 (0.069) | |
| −0.002** (0.000) | −0.001* (0.000) | −0.001* (0.000) | −0.001* (0.000) | |
| −0.003 (0.014) | −0.011 (0.014) | 0.007 (0.019) | 0.013 (0.019) | |
| 0.047* (0.026) | 0.050* (0.026) | 0.055* (0.028) | 0.055* (0.032) | |
| 0.026 (0.053) | 0.021 (0.050) | 0.013 (0.046) | 0.035 (0.068) | |
| Constant | 0.228*** (0.052) | 0.242*** (0.053) | 0.888*** (0.043) | 0.592*** (0.067) |
| Yes | Yes | Yes | Yes | |
| Yes | Yes | Yes | Yes | |
| Adjusted R2 | 0.124 | 0.121 | 0.119 | 0.152 |
| Obs | 16,190 | 16,190 | 16,190 | 16,190 |
Note(s): The superscripts *, ** and *** denote significance at the confidence levels of 90%, 95% and 99%, respectively
Columns 2 to 4 report regression results using domestic institutional ownership , long-term institutional ownership and blockholding ownership as dependent variables. The positive and significant coefficients on political connections across these specifications provide support for H2 through H4. The positive association with domestic institutional ownership is consistent with Tee et al. (2018) and Tee (2020), but contrasts with the findings of Aggarwal et al. (2011), Ferreira and Matos (2008) and Yu and Wang (2025). One explanation is that domestic institutional investors benefit from informational advantages related to informal networks, elite patronage structures and the persistence of political alliances, which is consistent with geographical proximity theory. These investors are better positioned to interpret political signals associated with government alignment and regulatory stability, suggesting that political connections are viewed as informative signals that reduce uncertainty rather than as sources of agency risk. Overall, the results indicate that the attractiveness of PCFs reflects not only firm-level characteristics but also institutional investors' strategic responses to a politically mediated market environment.
The positive relationship between political connections and long-term institutional ownership reflects similar underlying dynamics. Although long-term investors are typically associated with stronger monitoring and lower tolerance for rent extraction, prospect theory suggests that they may view political ties as a form of downside protection against regulatory disruption, administrative constraints and macroeconomic shocks. These considerations are particularly relevant in Malaysia, where political patronage shapes access to financing, investment approvals and government procurement. Accordingly, political connections appear to be incorporated into investment decisions as stabilising factors that support long-term value preservation rather than as sources of agency risk. This interpretation is consistent with prior evidence that political ties enhance firm resilience and long-term valuation (Boubakri et al., 2012; Tee et al., 2022; Wong, 2025), reinforcing the view that such connections function as strategic assets rather than vehicles for short-term opportunism.
Finally, the positive association between political connections and blockholding ownership further reinforces this interpretation. In Malaysia's politically embedded environment, political ties may allow blockholders to leverage networks, secure preferential treatment and exert coordinated influence. Behavioural biases such as overconfidence and representativeness may amplify this tendency by leading blockholders to overestimate their ability to extract value from PCFs. Consequently, political connections are more likely to be perceived as sources of strategic advantage and stability rather than as governance concerns. This interpretation aligns with the resource-based view, which treats political ties as intangible assets that confer competitive advantages through privileged access to government-controlled resources. It also contrasts with the conventional assumption that blockholders primarily act as governance discipliners (Gloßner, 2019; Helling et al., 2020; Qian and Tam, 2021), suggesting instead that, in the presence of political ties, blockholding institutions may function as strategic complements to political influence rather than as countervailing forces.
4.4 Further analysis
Recent evidence (Nguyen et al., 2023; Phan et al., 2020; Tee et al., 2021b; Wong and Hooy, 2025) suggests that the heterogeneity of political connections plays a significant role in shaping organisational outcomes. For example, GLCs reflect higher stock price crash risks than firms connected through personal and informal business ties (Tee et al., 2021a). Consistent with crony cronyism and political patronage theory, the strength and impact of political ties depend on the nature of the connections maintained by firms (Shefter, 1977; Shleifer and Vishny, 1994). In other words, different types of political connections can generate distinct firm outcomes and influence institutional investors' behaviour.
We perform an extended analysis to determine whether different political connection types affect a firm's ability to attract institutional equity capital in distinctive ways. We classify PCFs based on the nature of their connections: government-linked companies , connections through directors , informal business ties , immediate family members of ruling elites , and CEOs . These political connection types serve as binary variables. For example, equals one if the firm is a GLC. We re-estimate Equation (3) by substituting with this group of binary variables.
Column 1 of Table 5 reveals that GLCs exhibit the highest levels of institutional ownership, followed by firms connected through directors, informal business ties, and CEOs, all of which are positively associated with institutional holdings. In contrast, firms with family-based political ties display no significant relationship with institutional ownership. This pattern suggests that institutional investors differentiate across types of political connections based on their perceived ability to enhance stability and reduce risk. Family-based ties are often viewed as less effective in facilitating access to government resources or enhancing shareholder value and may introduce greater volatility due to personal dynamics (Wong and Hooy, 2018), thereby reducing their attractiveness to investors seeking predictability. By comparison, more institutionalised and structured connections, such as government-linked and business-related ties, are easier to evaluate and perceived as more reliable. Overall, the findings indicate that structured political connections attract greater institutional ownership than family-based ties, reflecting investors' preference for transparent and stability-enhancing affiliations.
Heterogeneous political connections and institutional investors
| (1) | (2) | (3) | (4) | |||||
|---|---|---|---|---|---|---|---|---|
| Estimate | STD estimate | Estimate | STD estimate | Estimate | STD estimate | Estimate | STD estimate | |
| 0.231*** (0.061) | 22.56% | 0.217*** (0.063) | 21.75% | 0.098** (0.042) | 7.70% | 0.179*** (0.065) | 12.96% | |
| 0.038*** (0.014) | 9.83% | 0.035** (0.013) | 6.06% | 0.022 (0.014) | 4.57% | 0.025 (0.021) | 4.80% | |
| 0.143** (0.065) | 13.22% | 0.145** (0.066) | 13.64% | −0.021 (0.030) | −1.56% | 0.020 (0.062) | 1.47% | |
| 0.029 (0.052) | 2.34% | 0.033 (0.054) | 2.71% | −0.027 (0.023) | −1.75% | 0.009 (0.057) | 0.54% | |
| 0.167*** (0.059) | 15.73% | 0.181*** (0.060) | 17.35% | 0.056 (0.044) | 4.24% | 0.029 (0.068) | 2.03% | |
| Constant | 0.181*** (0.048) | 0.190*** (0.048) | 0.875*** (0.045) | 0.622*** (0.066) | ||||
| Control variables | Yes | Yes | Yes | Yes | ||||
| Yes | Yes | Yes | Yes | |||||
| Yes | Yes | Yes | Yes | |||||
| Adjusted R2 | 0.163 | 0.174 | 0.144 | 0.186 | ||||
| Obs | 16,190 | 16,190 | 16,190 | 16,190 | ||||
| Estimate | STD estimate | Estimate | STD estimate | Estimate | STD estimate | Estimate | STD estimate | |
|---|---|---|---|---|---|---|---|---|
| 0.231*** (0.061) | 22.56% | 0.217*** (0.063) | 21.75% | 0.098** (0.042) | 7.70% | 0.179*** (0.065) | 12.96% | |
| 0.038*** (0.014) | 9.83% | 0.035** (0.013) | 6.06% | 0.022 (0.014) | 4.57% | 0.025 (0.021) | 4.80% | |
| 0.143** (0.065) | 13.22% | 0.145** (0.066) | 13.64% | −0.021 (0.030) | −1.56% | 0.020 (0.062) | 1.47% | |
| 0.029 (0.052) | 2.34% | 0.033 (0.054) | 2.71% | −0.027 (0.023) | −1.75% | 0.009 (0.057) | 0.54% | |
| 0.167*** (0.059) | 15.73% | 0.181*** (0.060) | 17.35% | 0.056 (0.044) | 4.24% | 0.029 (0.068) | 2.03% | |
| Constant | 0.181*** (0.048) | 0.190*** (0.048) | 0.875*** (0.045) | 0.622*** (0.066) | ||||
| Control variables | Yes | Yes | Yes | Yes | ||||
| Yes | Yes | Yes | Yes | |||||
| Yes | Yes | Yes | Yes | |||||
| Adjusted R2 | 0.163 | 0.174 | 0.144 | 0.186 | ||||
| Obs | 16,190 | 16,190 | 16,190 | 16,190 | ||||
Note(s): The superscripts *, ** and *** denote significance at the confidence levels of 90%, 95% and 99%, respectively
We further present standardised coefficients, with all variables standardised to a mean of zero and a standard deviation of one, to evaluate the economic significance of political connection heterogeneity. These coefficients capture the change in institutional ownership associated with a one-standard-deviation change in each political connection variable. Based on the “STD estimate” in column 1, exerts the strongest economic effect on institutional ownership: a one-standard-deviation increase in corresponds to a 22.56% standard-deviation increase in institutional ownership. Moreover, the adjusted R2 of the model that incorporates heterogeneous political connection variables is higher than that of the baseline model (0.163 versus 0.124). Accounting for political connection heterogeneity increases the model's explanatory power by 31.45%.
The findings in column 2, where the dependent variable is , corroborate those in column 1: firms with government ownership, politically-connected directors, businessmen and CEOs reflected higher domestic institutional ownership. Regardless, the results outlined in columns 3 and 4, where the dependent variables constituted and , indicate that only GLCs can attract more long-term institutional investors and blockholders. Compared to other PCFs, GLCs consistently attracted higher domestic and long-term institutional investors, as well as blockholders. The evidence is consistent with Luo et al. (2022) and Tee et al. (2018). This advantage could be attributed to the GLC Transformation Programme, which aims at increasing transparency and disclosure standards (Putrajaya Committee, 2015). In this vein, GLCs are more appealing to institutional investors. Domestic institutional investors were drawn to GLCs due to familiarity bias and in-group preferences, perceiving them as stable entities aligned with local socio-political norms. Guided by loss aversion and the desire for predictable returns, long-term institutional investors considered GLCs safer investments owing to their government backing and resilience to market or political fluctuations. Blockholders are similarly attracted to GLCs due to their established political ties and access to government resources. Meanwhile, the more volatile and less reliable non-GLCs tend to lower institutional interest. In summary, GLCs' institutionalised nature and perceived stability render them more ideal for domestic and long-term investors, as well as blockholders, than other PCFs.
4.5 Robustness tests
Several sensitivity tests are conducted in this study to reinforce the robustness of the results. First, observations from election years (2004, 2008, 2013 and 2018), the recession period (2007 and 2008) and the COVID-19 pandemic years (2020, 2021, and 2022) are excluded to ensure that the results are not driven by specific periods. Upon re-assessing the key analyses, the results in panel A of Table 6 remain significant and robust.
Robustness tests
| (1) | (2) | (3) | (4) | |
|---|---|---|---|---|
| Panel A: Exclusion of specific period | ||||
| 0.070*** (0.014) | 0.052** (0.021) | 0.029** (0.013) | 0.037** (0.019) | |
| Constant | 0.119** (0.056) | 0.133** (0.057) | 0.885*** (0.044) | 0.572*** (0.070) |
| Adjusted R2 | 0.132 | 0.127 | 0.126 | 0.155 |
| Obs | 9,947 | 9,947 | 9,947 | 9,947 |
| Panel B: Alternative measure of political connections | ||||
| 0.326*** (0.068) | 0.305*** (0.073) | 0.113** (0.053) | 0.231*** (0.065) | |
| Constant | 0.115** (0.047) | 0.132*** (0.046) | 0.849*** (0.045) | 0.651*** (0.066) |
| Adjusted R2 | 0.175 | 0.190 | 0.181 | 0.169 |
| Obs | 16,190 | 16,190 | 16,190 | 16,190 |
| Panel C: Propensity score matching | ||||
| 0.076*** (0.014) | 0.070*** (0.014) | 0.026* (0.013) | 0.048** (0.020) | |
| Constant | 0.102** (0.044) | 0.112** (0.045) | 0.684*** (0.051) | 0.157*** (0.058) |
| Adjusted R2 | 0.140 | 0.130 | 0.127 | 0.141 |
| Obs. | 6,664 | 6,664 | 6,664 | 6,664 |
| Panel D: System GMM | ||||
| 0.982*** (0.048) | ||||
| 0.897*** (0.053) | ||||
| 0.853*** (0.029) | ||||
| 0.910*** (0.048) | ||||
| 0.022*** (0.004) | 0.017** (0.008) | 0.006*** (0.002) | 0.015** (0.007) | |
| Constant | 0.005 (0.010) | 0.000 (0.010) | 0.096*** (0.021) | 0.016 (0.014) |
| Obs. | 16,190 | 16,190 | 16,190 | 16,190 |
| AR1 (p-value) | 0.000 | 0.000 | 0.000 | 0.000 |
| AR2 (p-value) | 0.385 | 0.415 | 0.995 | 0.242 |
| Hansen J (p-value) | 0.765 | 0.816 | 0.785 | 0.831 |
| (1) | (2) | (3) | (4) | |
|---|---|---|---|---|
| Panel A: Exclusion of specific period | ||||
| 0.070*** (0.014) | 0.052** (0.021) | 0.029** (0.013) | 0.037** (0.019) | |
| Constant | 0.119** (0.056) | 0.133** (0.057) | 0.885*** (0.044) | 0.572*** (0.070) |
| Adjusted R2 | 0.132 | 0.127 | 0.126 | 0.155 |
| Obs | 9,947 | 9,947 | 9,947 | 9,947 |
| Panel B: Alternative measure of political connections | ||||
| 0.326*** (0.068) | 0.305*** (0.073) | 0.113** (0.053) | 0.231*** (0.065) | |
| Constant | 0.115** (0.047) | 0.132*** (0.046) | 0.849*** (0.045) | 0.651*** (0.066) |
| Adjusted R2 | 0.175 | 0.190 | 0.181 | 0.169 |
| Obs | 16,190 | 16,190 | 16,190 | 16,190 |
| Panel C: Propensity score matching | ||||
| 0.076*** (0.014) | 0.070*** (0.014) | 0.026* (0.013) | 0.048** (0.020) | |
| Constant | 0.102** (0.044) | 0.112** (0.045) | 0.684*** (0.051) | 0.157*** (0.058) |
| Adjusted R2 | 0.140 | 0.130 | 0.127 | 0.141 |
| Obs. | 6,664 | 6,664 | 6,664 | 6,664 |
| Panel D: System GMM | ||||
| 0.982*** (0.048) | ||||
| 0.897*** (0.053) | ||||
| 0.853*** (0.029) | ||||
| 0.910*** (0.048) | ||||
| 0.022*** (0.004) | 0.017** (0.008) | 0.006*** (0.002) | 0.015** (0.007) | |
| Constant | 0.005 (0.010) | 0.000 (0.010) | 0.096*** (0.021) | 0.016 (0.014) |
| Obs. | 16,190 | 16,190 | 16,190 | 16,190 |
| AR1 (p-value) | 0.000 | 0.000 | 0.000 | 0.000 |
| AR2 (p-value) | 0.385 | 0.415 | 0.995 | 0.242 |
| Hansen J (p-value) | 0.765 | 0.816 | 0.785 | 0.831 |
Note(s): Control variables, industry and year fixed effects are included, but not reported for brevity. The superscripts *, ** and *** denote significance at the confidence levels of 90%, 95% and 99%, respectively
The tests reported in Table 4 are repeated using the percentage of shareholding held by alleged connected persons as an alternative measure of political connections [2]. The significant and positive coefficients of across columns 1 to 4 (see panel B in Table 6) consistently support the prediction of PCFs related to higher institutional ownership. Moreover, the coefficients are larger than those reported in Table 4. This indicates a more significant impact of political connections on institutional ownership.
The findings may be subject to self-selection and potential observable differences between PCFs and non-PCFs. To address this, propensity score matching is employed using nearest-neighbour techniques to match PCFs in the treated sample with non-PCFs in the control sample (Rosenbaum and Rubin, 1983). Following Tee (2017, 2019b) and Tee et al. (2018), the propensity score is computed based on a set of firm characteristics that capture a firm's likelihood of establishing political connections with ruling elites. In particular, firm size , return on assets , leverage and Big Four auditors serve as the chosen characteristics. is measured as the natural logarithm of total assets, while the binary variable of equals one if the firm is audited by one of the Big Four auditors (and zero otherwise) (see panel C in Table 6). The political connection-institutional ownership relationship remains positive. These findings align with the main results and minimise self-selection bias.
Finally, the two-step system GMM estimator (Arellano and Bover, 1995; Blundell and Bond, 1998) is employed to address endogeneity in a dynamic panel setting. Political connections and the lagged dependent variable are treated as endogenous, with instruments based on lagged values and a collapsed instrument matrix to avoid proliferation. The results in Table 6, Panel D remain robust.
5. Conclusions
This study provides new evidence on how political connections shape institutional equity ownership in an emerging market context. Using a comprehensive Malaysian dataset, we find that PCFs attract higher ownership from domestic institutional investors, long-term investors and blockholders, all of whom prioritise strategic horizons and sustained value creation. This effect is driven primarily by GLCs, whose institutionalised governance structures and embedded state oversight serve as credible signals of stability and stronger institutional quality. Our findings directly address the central research question by showing that institutional investors generally interpret political connections as mechanisms that enhance stability and reduce uncertainty rather than as sources of agency risk, whereas non-GLCs connected through directors, CEOs, elite families or informal networks exhibit significantly weaker appeal, highlighting the heterogeneous value of different types of political ties. Overall, these results underscore the strategic role of political affiliations in shaping capital allocation decisions and demonstrate how behavioural considerations, institutional familiarity and risk perceptions jointly influence investors' responses to political signals.
The findings have important practical implications for both managers and institutional investors. Not all political connections are valued equally, as government-linked structures are particularly effective in attracting a broad base of institutional investors, whereas connections through directors, CEOs and informal networks appeal mainly to domestic institutions and hold limited relevance for foreign or long-horizon investors, while family-based political ties attract virtually no institutional equity. These patterns suggest that institutional investors reward political connections when they signal stability and governance credibility but discount them when they increase perceived uncertainty or opacity. Accordingly, firms should align their political affiliations with investor expectations and avoid forms of engagement that introduce governance concerns without delivering tangible capital market benefits. Institutional investors may likewise use these insights to refine their strategies by evaluating the economic and behavioural trade-offs associated with PCFs, particularly in politically salient environments.
For policymakers, the findings suggest that political connections can support broader economic objectives by enhancing firms' ability to secure external equity capital, thereby reducing reliance on government financing and enabling resources to be redirected towards social and developmental priorities such as poverty alleviation. These insights may also inform the design of counter-cyclical investment strategies aimed at stabilising investment cycles and strengthening corporate resilience (Szarzec et al., 2021). However, the capital-attracting benefits of political ties must be carefully balanced against the well-documented risks of patronage, rent-seeking, and cronyism. While political connections can facilitate capital allocation, they require robust institutional safeguards to prevent the emergence of agency conflicts and rent extraction. Accordingly, policymakers should prioritise reforms that enhance transparency, strengthen governance mechanisms and limit discretionary political intervention to preserve investor confidence and maintain market discipline.
A number of important limitations warrant consideration. Although we document robust associations between political connections and institutional ownership, we cannot directly observe the mechanisms through which political ties shape investment decisions. As a result, the extent to which investors respond to informational advantages, expectations of regulatory protection or behavioural heuristics remains an open question. Moreover, despite extensive hand-collected data, the measurement of certain political connections, particularly informal networks or personalised elite relationships, is inherently imprecise and may introduce classification constraints. Finally, Malaysia's institutional environment, marked by longstanding political patronage and a large government-linked corporate sector, limits the generalisability of our findings to other emerging markets with different political institutions or investor protection regimes.
These limitations highlight the need for further research employing causal identification strategies, richer measures of political embeddedness and comparative designs across diverse political-economic contexts. In particular, future studies should disentangle the conditions under which political connections are perceived as sources of protection vs agency risk, thereby extending the central theoretical tension examined in this study. Advancing this agenda requires identifying the causal channels through which political ties influence investor behaviour, examining how institutional environments shape these relationships across countries and assessing whether stronger minority shareholder protections alter investor responses to PCFs. Such efforts will deepen our understanding of how political connections interact with capital markets and shape institutional investment behaviour in emerging economies.
Notes
A longer and recent sample period is deliberately employed given that the impact of political connections on the capital market can change over time. Hence, the findings remain relevant and timely.
We use a primary binary variable, , to capture all forms of political connections, including non-shareholding ties such as CEOs or directors with political links but no disclosed ownership. An alternative measure, , based solely on shareholding data, is employed in robustness tests to capture the extent of political ownership. Firms with non-shareholding political ties are included as PCFs in the binary measure but not under . This dual approach ensures comprehensive coverage of political connections and aligns with the methodology of Tee et al. (2021a), addressing potential classification concerns for firms with politically connected executives or directors without disclosed ownership.

