CEO Overconfidence, Debt Policy, and Financial Condition: The Moderating Role of Family Ownership in Indonesian Manufacturing Firms

Abstract

Financial condition is central to corporate sustainability, yet evidence on whether VOL 7 Issue 4 October 2026 family ownership conditions the relationships of CEO overconfidence and debt policy with financial condition remains limited, particularly in Indonesian manufacturing firms. This study addresses this gap by positioning family ownership COPYRIGHT as a boundary condition. From 850 firm-year observations of Indonesian listed© 2026 Mahardini, Umdiana and Kodriyah. This is an open-access manufacturing firms during 2020-2024, 822 observations remained after residual-article distributed under the terms based screening and were analyzed using multiple and moderated regressions. of the Creative Commons Financial condition was measured using the MFA Score, with the Altman Z-score as Attribution License (CC BY). The an alternative. CEO overconfidence and debt policy are negatively associated with use, distribution or reproduction in financial condition, while family ownership attenuates both relationships. The other forums is permitted, provided former remains significant across ownership levels, whereas the latter becomesthe original author(s) and the copyright owner(s) are credited and insignificant at high family ownership. Results remain consistent across the full that the original publication in this sample, alternative outcome and CEO-overconfidence measures. Two-way fixed-journal is cited, in accordance with effects estimates support H1-H3, while H4 shows limited robustness. The study accepted academic practice. No identifies family ownership as a boundary condition in managerial-behavioural and use, distribution or reproduction is financing pathways to financial condition.

Keywords: CEO overconfidence; debt policy; family ownership; financial condition; manufacturing companies.

Introduction

Financial condition is central to corporate sustainability because it reflects a firm’s ability to maintain operations and meet financial obligations. In emerging markets, it is shaped by both financial factors and managerial characteristics (Horváthová & Mokrišová, 2018; Mișu & Madaleno, 2020). CEO overconfidence may encourage overly optimistic assessments, aggressive investment, and risk underestimation (Kaplan et al., 2022; Liang et al., 2020) while persistent high leverage may increase financial pressure when operating cash flows are insufficient (Zhen et al., 2020).

Family ownership

may condition both relationships because family owners balance economic objectives with control, reputation, and long-term continuity, although concentrated control may also create entrenchment concerns (Gottardo & Moisello, 2015, 2017). Yet CEO overconfidence, debt policy, and family ownership have largely been examined separately. Prior studies link CEO overconfidence to failure and financial distress, overconfidence-related agency costs to inside-debt incentives, and family involvement to leverage, survival, and distress risk (Galariotis et al., 2023; Gottardo & Moisello, 2017, 2019; Leng et al., 2021; Muñoz-Bullón et al., 2024; Wantriani & Susanti, 2025). Agency and entrenchment perspectives, together with

Socioemotional Wealth (SEW)

theory, further suggest that family control may shape managerial discretion and financing decisions (Gomez-Mejia et al., 2014; Gottardo & Moisello, 2017, 2019; Hsueh et al., 2023; Muñoz Bullón et al., 2024) . However, whether family ownership conditions the separate relationships of CEO overconfidence and debt policy with financial condition within a unified framework remains unclear. Addressing this gap, this study examines CEO overconfidence and debt policy as managerial-behavioural and financing pathways to financial 2017). Thus, SEW supports family ownership as a boundary condition, respectively, with family ownership as a boundary condition linking CEO overconfidence and debt policy to condition. Using Indonesian listed manufacturing firms, financial condition (Gottardo & Moisello, 2017, 2019; financial condition is measured primarily by the MFA Score Muñoz-Bullón et al., 2024). As monitoring and entrenchment are (Çolak, 2021) and alternatively by the Altman Z-score (Altman, not directly measured, moderation reflects conditional 1968) with firm size, ROA, and cash flow as controls. association rather than evidence of either mechanism. Robustness is assessed through alternative financial-condition measures, full-sample sensitivity tests, alternative

The Impact of CEO Overconfidence on Financial Condition

CEO-overconfidence measures, and two-way fixed-effects Overconfident CEOs may overestimate expected returns models. The findings show that CEO overconfidence and debt and underestimate risks, encouraging excessive investment, policy are negatively associated with financial condition, while debt utilization, and other aggressive decisions that can family ownership significantly changes the strength of both misallocate resources and weaken financial condition relationships. The study therefore extends prior research by (Guluma, 2021; Xiao et al., 2021).

Agency Theory

highlights the showing that family ownership is relevant not only to leverage potential agency costs of such decisions, while Upper Echelons and financial risk but also to how managerial overconfidence Theory explains how managerial cognitive characteristics and debt policy relate to financial condition. Because shape strategic and financial choices (Chua et al., 2025). Prior monitoring and entrenchment are not directly measured, studies further link CEO overconfidence to corporate risk-taking these findings are interpreted as conditional associations and adverse financial outcomes (Leng et al., 2021; Mardjono rather than direct evidence of either governance mechanism. et al., 2026; Wantriani & Susanti, 2025). Accordingly: H1: CEO overconfidence has a significant negative effect on

Agency Theory

financial condition.

Agency Theory

views managers as agents whose interests may diverge from those of shareholders, particularly under

The Impact of Debt Policy on Financial Condition

information asymmetry and substantial managerial discretion

Trade-off Theory

suggests that debt is beneficial only while (Ghozali, 2020; Jensen & Meckling, 1976; Louis & Urcan, its tax and financing advantages exceed expected distress 2015). CEO overconfidence can intensify agency problems costs. Excessive leverage increases interest burdens, when managers overestimate returns, underestimate risks, bankruptcy risk, and financing costs, while agency conflicts and undertake aggressive investment or financing decisions among managers, shareholders, and creditors may further that increase agency costs and financial pressure (Galariotis encourage inefficient investment or risk shifting (Khan & et al., 2023). The theory therefore supports examining both Qasem, 2024); (Marimuthu & Abbana, 2023). Hence, greater CEO overconfidence and debt policy as determinants of debt utilization beyond the firm's financial capacity is expected financial condition and ownership structure as a context that to weaken financial condition. Therefore: may alter these relationships. H2:

Debt policy

has a significant negative effect on financial condition.

Upper Echelon Theory

Upper Echelons Theory posits that organizational Family Ownership Moderates the Effect of

CEO Overconfidence

outcomes reflect executives’ cognitive characteristics, values, on

Financial Condition

and experiences (Abatecola & Cristofaro, 2020; Hambrick &

Family ownership

may condition the relationship between Mason, 1984). CEO overconfidence may lead executives to CEO overconfidence and financial condition by shaping overestimate returns and underestimate risks, encouraging managerial discretion, monitoring, and family interests. Agency excessive investment, expansion, or debt utilization Theory highlights potential Type II conflicts under concentrated (Abdolhosseini & Wooi, 2024; Abdulwahab et al., 2025). control, Upper Echelons Theory emphasizes the role of These decisions may cause inefficient resource allocation, managerial discretion, and SEW underscores family owners’ performance volatility, and financial pressure, thereby interests in reputation and long-term continuity (Hsueh et al., weakening financial condition. Thus, the theory links CEO 2023; Muñoz Bullón et al., 2024). Together, these perspectives overconfidence to financial condition through cognitively suggest that the relationship between CEO overconfidence and shaped strategic and financial decisions. financial condition may vary with family ownership. Accordingly: H3:

Family ownership

moderates the relationship between

Trade-off Theory

CEO overconfidence and financial condition.

Trade-off Theory

explains capital structure as a balance between the benefits and costs of debt, particularly tax Family Ownership Moderates the Relationship Between Debt advantages versus agency and financial-distress costs, Policy and

Financial Condition

implying an optimal debt level (Abdeljawad & Farhood, 2025;

Family ownership

may condition the relationship between Shiro & Biiranee, 2025). Beyond a sustainable level, higher debt policy and financial condition by shaping financing leverage increases interest and debt-payment obligations, decisions and risk preferences.

Agency Theory

emphasizes the bankruptcy risk, and financial pressure, potentially role of concentrated ownership in aligning owner-manager constraining profitability and financial stability (Khan & interests, while

Trade-off Theory

and SEW suggest that family Qasem, 2024; Sunardi et al., 2020). Accordingly, the theory owners’ concerns for control, reputation, and long-term supports an association between excessive debt utilization continuity may influence debt utilization and financial risk and weaker financial condition. (Gottardo & Moisello, 2015, 2019; Muñoz-Bullón et al., 2024).These considerations suggest that the relationship

Socioemotional Wealth (SEW)

between debt policy and financial condition may vary with

Socioemotional Wealth (SEW)

reflects the non-financial family ownership. Therefore: value family owners derive from identity, control, reputation, H4:

Family ownership

moderates the relationship between and intergenerational continuity (Gómez-Mejía et al., 2007). debt policy and financial condition. These priorities may encourage conservative financing, while The conceptual framework illustrating the relationships concentrated ownership may reinforce family influence and among variables and the formulation of hypotheses H1-H4 is managerial preferences under limited oversight (Baixauli- presented in Figure 1. Soler et al., 2021; Jansen et al., 2023; Michiels & Molly, Family Ownership (Z) Independent Variables H3 H4

CEO Overconfidence

(X1) H1 H2 Debt Policy (X2) Dependent Variable

Financial Condition

(Y) Control Variables Firm Size (X3) ROA (X4) Cash Flow (X5) Methods X₄ = EBITDA / total assets X₅ = financial expenses / net sales X₆ = net profit (loss) / net sales This quantitative associative study uses annual panel X₇ = retained earnings / total assets data from manufacturing firms listed on the Indonesia Stock Exchange (IDX) during 2020-2024 (Chandrarin, 2017).

CEO Overconfidence

Secondary data were obtained from annual reports. Of 228 CEO overconfidence is measured using the composite index firms, purposive sampling retained firms that were adapted from (Liang et al., 2020), comprising five equally continuously listed, published complete annual reports, were weighted binary indicators: overinvestment, gender, tenure, not delisted, and disclosed sufficient ownership information expertise, and educational level. Scores range from 0 to 5; to identify family ownership. Fifty-eight firms were excluded, CEOs scoring at least 3 are classified as overconfident (1), leaving 170 firms and an initial balanced panel of 850 firm- otherwise 0. year observations. Before hypothesis testing, standardized Overinvestment. Overinvestment is based on the residuals from baseline Model 1 were screened once using an investment-growth specification used by (Ma’sum et al., 2022) a priori cutoff of ±3. Twenty-eight observations (3.29%) and (Wantriani & Susanti, 2025), following (Richardson, 2006). exceeded this threshold and were excluded from the primary Expected investment is estimated from asset growth and sales analysis, producing a common unbalanced sample of 822 growth; observations with residuals above the sample median firm-year observations for Models 1-4. The rule was applied are coded as overinvesting (1), otherwise 0. independently of coefficient direction or significance. As a ∆ Asset it ∆ Sales it sensitivity test, all models were also re-estimated using the Asset it−1 = β0 + β1 Sales it−1 + εi,t complete 850-observation sample; full estimates are Gender. Male executives are generally more prone to reported in Appendix A. overconfidence than female executives, particularly in investment decisions. Gender is therefore coded 1 for male

Financial Condition

CEOs and 0 for female CEOs (Liang et al., 2020). Financial condition reflects a firm’s ability to maintain its Tenure. Managerial experience may reduce overconfidence financial position and meet current and future obligations, through learning from past experience. Tenure is coded 1 when while financial distress represents a more severe and the CEO’s tenure is below the sample median and 0 otherwise prolonged deterioration in this condition (Brigham & Daves, (Liang et al., 2020). 2019; Mahardini & Bandi, 2023). This study measures Expertise. CEO expertise reflects the executive’s financial condition using the continuous MFA Score (Çolak, educational specialization, which may shape managerial 2021), where higher scores indicate stronger financial decisions and corporate outcomes (Gounopoulos et al., 2021; condition and lower scores indicate greater distress risk. Tanjaya & Santoso, 2020). It is coded 1 for CEOs with an Although the MFA classifies firms as distressed (< -0.02), grey educational background in business or economics and 0 area (-0.02 to 0.56), or financially healthy (> 0.56), the otherwise (Gounopoulos et al., 2021). continuous score is used in regression analyses to preserve Educational level. Higher educational attainment may variation and statistical information, while the cut-offs are strengthen managerial knowledge and human capital but may used to classify firms as financially distressed (FD) or non- also increase confidence in managerial abilities (Liang et al., financially distressed (NFD). 2020). As a component of the composite overconfidence index, MFA score = 0.24X₁ − 0.14X₂ − 0.03X₃ + 3.76X₄ − 0.72X₅ + educational level is coded 1 for CEOs holding a master’s or 0.20X₆ + 1.14X₇ doctoral degree and 0 for those with a bachelor’s degree or Note: lower (Liang et al., 2020). X₁ = (cash equivalents + securities + short term trade CEO overconfidence. The five binary indicators are summed receivables) / short term liabilities into a score ranging from 0 to 5. Following (Liang et al., 2020). X₂ = short term liabilities / current assets CEOs with scores ≥3 are classified as overconfident, while X₃ = total liabilities / equity those with scores <3 are classified as non-overconfident. Sensitivity Analysis of

CEO Overconfidence

Measurement. Model 2 - MFA Score, moderation model Measurement sensitivity is assessed by re-estimating FC1= α + β1CO + β2DP + β3FO + β4(CO*FO) + β5(DP*FO) + Models 1 and 2 with alternative composite-score thresholds β6Size + β7ROA + β8CF + Ɛ of 2 and 4 and overinvestment alone as a behavioural proxy, while retaining the same sample, dependent variable, and Two complementary robustness procedures are employed. controls as the baseline specification. The relevant CO×FO Models 3-4 replace the MFA Score with the Altman Z-score to interaction is reconstructed for each alternative measure, and assess whether the findings depend on the measurement of the results are compared with the baseline to assess the financial condition, while Models 1-4 are re-estimated with firm robustness of the main inferences. and year fixed effects and firm-clustered standard errors to account for unobserved firm heterogeneity, common year

Debt policy

shocks, and within-firm error dependence. Altman Z-scores

Debt policy

is measured by the Debt-to-Asset Ratio (DAR), above 2.99 indicate financial soundness, 1.81–2.99 the grey defined as total liabilities divided by total assets and zone, and below 1.81 elevated bankruptcy risk (Altman, 1968). expressed as a percentage (Ogachi et al., 2020; Samara & Sutandi, 2024). Values above 100% are retained because

Alternative Model Robustness Test

they represent firms whose liabilities exceed assets and Model 3 - Altman Z-score, direct effects therefore have negative equity. FC2= α + β1CO + β2DP + β3Size + β4ROA + β5CF + Ɛ DAR = Total Liabilities x 100% Total Assets Model 4 - Altman Z-score, moderation model FC2 = α + β1CO + β2DP + β3FO + β4(CO*FO) + β5(DP*FO) +

Family ownership

β6Size + β7ROA + β8CF + Ɛ

Family ownership

is identified from annual reports by tracing the founding family’s ultimate direct and indirect Note: FC1 represents financial condition measured using (pyramid) ownership and is measured as the proportion of the primary proxy, while FC2 represents financial condition outstanding ordinary shares ultimately attributable to the measured using an alternative proxy in the robustness test. family. Indirect ownership is determined by tracing ownership chains and calculating the attributable proportion from the The calculation of FC2 (Z-score) is as follows. ownership percentages along each chain, while overlapping direct and indirect interests are counted only once (Madyan Z = 1.2X₁ + 1.4X₂ + 3.3X₃ + 0.6X₄ + 1.0X₅ et al., 2019). Ownership data were rechecked to verify the Note: tracing and eliminate double counting, resulting in family X₁= working capital / total assets ownership values ranging from 0% to 100%. X₂= retained earnings / total assets Ultimate attributable ordinary shares controlled by the founding family X₃= EBIT / total assets FO = x 100% Total outstanding ordinary shares X₄= market value of equity / book value of total debt Firm size. Firm size reflects a firm’s operational scale and X₅ = sales / total assets financial capacity, with larger asset bases generally Z-scores above 2.99 indicate a healthy financial condition, associated with greater financial resilience and lower distress scores between 1.81 and 2.99 represent the grey zone, and risk (Hamzah et al., 2024). It is measured as the natural scores below 1.81 indicate high bankruptcy risk. logarithm of total assets. Return on Assets (ROA). ROA measures profitability by

Panel Model Robustness Analysis

reflecting a firm’s efficiency in using its assets to generate Models 1-4 are re-estimated using two-way fixed effects to profits (Dirman, 2020; Kasmir, 2021). ROA is calculated as control for time-invariant firm heterogeneity and common year follows (Kasmir, 2021). shocks, with firm-clustered standard errors accounting for 𝑎𝑓𝑡𝑒𝑟 𝑡𝑎𝑥 ROA = 𝐸𝑎𝑟𝑛𝑖𝑛𝑔 heteroskedasticity and within-firm serial correlation. The panel 𝑇𝑜𝑡𝑎𝑙 𝑎𝑠𝑠𝑒𝑡𝑠 Cash flow. Cash flow reflects cash generated and used in specifications are as follows: operating, investing, and financing activities. Insufficient operating cash flow may weaken investor confidence in a Panel Model 1 - MFA Score, direct effects firm’s ability to sustain operations and increase financial- FC1it = αi + λt + β1COit + β2DPit + β3Sizeit + β4ROAit + β5CFit + εit distress risk (Ramadhanti & Subagyo, 2022). Cash flow is measured as follows: Panel Model 2 - MFA Score, moderation model Cash Flow Operating FC1it = αi + λt + β1COit + β2DPit + β3FOit + β4(CO×FO)it + β5 Cash flow (CFOTA) = Total Assets (DP×FO)it + β6Sizeit + β7ROAit + β8CFit + εit

Data Analysis

Panel Model 3 - Altman Z-score, direct effects The primary hypotheses are tested using pooled multiple FC2it = αi + λt + β1COit + β2DPit + β3Sizeit + β4ROAit + β5CFit + εit regression and Moderated Regression Analysis (MRA), with the MFA Score as the primary outcome. Robustness is Panel Model 4 - Altman Z-score, moderation model evaluated by replacing the MFA Score with the Altman Z-score FC2it = αi + λt + β1COit + β2DPit + β3FOit + β4(CO×FO)it + β5 and by re-estimating all four models using two-way firm and (DP×FO)it + β6Sizeit + β7ROAit + β8CFit + εit year fixed effects with standard errors clustered at the firm level. The latter addresses time-invariant firm heterogeneity, Notes: i and t denote firm and year; αᵢ and λₜ denote firm common year shocks, heteroskedasticity, and within-firm and year fixed effects; and εᵢₜ is the idiosyncratic error term. serial correlation. All coefficients are interpreted as statistical Standard errors are clustered at the firm level. associations rather than definitive causal effects. The research models are specified as follows: Result and Discussion Main model Model 1 - MFA Score, direct effects The initial 850 firm-year observations were screened once FC1 = α + β1CO + β2DP + β3Size + β4ROA + β5CF + Ɛ using standardized residuals from Model 1 (|SR| > 3). Excluding 28 observations (3.29%) yielded a common analytical sample of 822 observations for Models 14. All Table 1.

Descriptive Statistics

Variabel Obs Mean Std. Dev. Min Max Y₁ (FC_MFA) 822 0.3905 4.6631 -30.42 69.11 Y₂ (FC_Zscore) 822 3.4262 2.9869 -0.09 9.98 X₁ (CO) 822 0.6224 0.1651 0 1 X₂ (DP) 822 51.9539 37.9782 0.25 290.11 X₃ (Size) 822 14.7396 1.7201 7.11 19.84 X₄ (ROA) 822 3.4182 13.5328 -87.61 218.22 X₅ (CF) 822 6.4452 12.3743 -36.15 129.75 Z (FO) 822 1.4556 9.7258 0 92.39 Source: Processed data, 2026. Note: FC =

Financial Condition

; CO =

CEO Overconfidence

; DP = Debt Policy; Size = Firm Size; ROA = Return on Assets; CF = Cash Flow; FO = Family Ownership. Table 2. Results of Multiple Regression Analysis and MRA Variable Statistic Model 1 Model 2 Model 3 Model 4 MFA MFA (MRA) Z-score Z-score (MRA) Cons 0.3385 -0.6759 0.7943 0.8514 CO coef. β -1.5530 -3.2099 -1.1290 -1.1004 t-value -2.39 -2.58 -2.02 -2.12 sig. 0.017* 0.010* 0.044* 0.034* Std. Err 0.6496 1.2442 0.5589 0.5189 DP coef. β -0.0230 -0.2230 -0.0197 -0.0198 t-value -5.33 -5.12 -7.84 -7.91 sig. 0.000* 0.000* 0.000* 0.000* Std. Err 0.0043 0.0436 0.0025 0.0025 FO coef. β - 0.0323 - 0.0006 t-value - 2.09 - 2.12 sig. - 0.037* - 0.034* Std. Err - 0.0155 - 0.0003 CO×FO coef. β - 0.0538 - 0.0019 t-value - 2.21 - 3.23 sig. - 0.027* - 0.001* Std. Err. - 0.0244 - 0.0006 DP×FO coef. β - 0.01513 - 0.01529 t-value - 2.10 - 2.17 sig. - 0.036* - 0.030* Std. Err. - 0.0072 - 0.7045 Size coef. β 0.0050 0.0015 0.2656 0.2633 t-value 0.05 0.02 0.94 0.91 sig. 0.960 0.984 0.347 0.363 Std. Err. 0.0998 0.0767 0.2826 0.2894 ROA coef. β 0.0469 0.0458 0.0386 0.0383 t-value 3.19 3.72 5.38 4.91 sig. 0.001* 0.000* 0.000* 0.000* Std. Err. 0.0147 0.0123 0.0072 0.0078 CF coef. β 0.0071 0.0071 0.0482 0.0476 t-value 2.55 3.54 1.34 1.19 sig. 0.011* 0.000* 0.180 0.236 Std. Err. 0.0028 0.0020 0.0359 0.0401 R² 0.6900 0.7410 0.6820 0.6600 Adj. R² 0.6330 0.6490 0.6320 0.6050 F statistic 12.10 8.13 48.26 30.86 Prob > F 0.000 0.000 0.000 0.000 Number of obs 822 822 822 822 Source: Processed data, 2026 models were also re-estimated on the full 850-observation financial condition. The mean Altman Z-score is 3.4262 (SD = sample to assess sensitivity to this exclusion. 2.9869). CEO overconfidence equals 0.6224 on average, indicating that 62.24% of observations are classified as

Descriptive Statistics

overconfident.

Debt policy

varies widely, with a maximum DAR Table 1 summarizes the characteristics of the 822 firm- of 290.11%, reflecting negative equity in some financially year observations. distressed firms. Firm size, ROA, cash flow, and family The mean MFA Score is 0.3905 (SD = 4.6631), within the ownership also display substantial cross-firm variation. grey-area interval and indicating substantial heterogeneity in Table 3. Summary of Main Test Results and Alternative Measure Robustness Test Alternative Measure Main Result Remarks Robustness Test Model 1 Model 2 Model 3 Model 4 t Sig. t Sig. t Sig. t Sig. Hypothesis 1 -2.39 0.017 - - -2.02 0.044 - - Supported Hypothesis 2 -5.33 0.000 - - -7.84 0.000 - - Supported Hypothesis 3 - - 2.21 0.027 - - 3.23 0.001 Supported Hypothesis 4 - - 2.10 0.036 - - 2.17 0.030 Supported Source: Processed data, 2026. Table 4. Comparison of the Main and Full Sample Estimates Main analysis Full sample Relationship Model Consistency N = 822 N = 850 CO Model 1 -1.5530 (sig. 0.017) -1.5076 (sig. 0.018) Yes DP Model 1 -0.0230 (sig. 0.000) -0.0228 (sig. 0.000) Yes CO×FO Model 2 0.0538 (sig. 0.027) 0.0529 (sig. 0.028) Yes DP×FO Model 2 0.01513 (sig. 0.036) 0.014875 (sig. 0.037) Yes CO Model 3 -1.1290 (sig. 0.044) -1.1035 (sig. 0.043) Yes DP Model 3 -0.0197 (sig. 0.000) -0.0195 (sig. 0.001) Yes CO×FO Model 4 0.0019 (sig. 0.001) 0.0018 (sig. 0.002) Yes DP×FO Model 4 0.01529 (sig. 0.030) 0.01501 (sig. 0.032) Yes Source: Processed data, 2026. Note: “Yes” indicates that the full sample estimate retains the direction and statistical significance of the corresponding main estimate at the 5% level.

Main Regression Result

Altman Z-score, although coefficient magnitudes are not Multiple Regression Analysis and Moderating Regression directly comparable across scales. Analysis (MRA) Model 1 shows that CEO overconfidence (β = -1.5530, p The estimated equations are: = 0.017) and debt policy (β = -0.0230, p < 0.001) are Model 3 FC2 = 0.7943 - 1.1290CO - 0.0197DP + 0.2656Size negatively and significantly associated with the MFA Score, + 0.0386ROA + 0.0482CF+Ɛ supporting H1 and H2. Because higher MFA Scores indicate Model 4 FC2 = 0.8514 - 1.1004CO - 0.0198DP + 0.0006FO + better financial condition, these negative coefficients indicate 0.0019(CO×FO) + 0.01529(DP×FO) + 0.2633Size + weaker financial condition. ROA and cash flow are positively 0.0383ROA + 0.0476CF + Ɛ significant, whereas firm size is insignificant. In Model 2, family ownership significantly moderates both

Full Sample Sensitivity Analysis

relationships. The CO×FO interaction is positive (β = 0.0538, To assess sensitivity to residual-based outlier screening, p = 0.027), indicating that higher family ownership attenuates Models 1-4 were re-estimated using the full sample of 850 firm-the negative CEO-overconfidence association. The DP×FO year observations, restoring the 28 observations excluded from interaction is likewise positive (β = 0.01513, p = 0.036), the primary analysis while retaining the same variable indicating attenuation of the negative debt-policy association. definitions and model specifications. This analysis assesses H3 and H4 are therefore supported in the pooled MFA model whether the directions and significance of the principal (Table 3). coefficients depend on the screening decision. Table 4 The estimated primary-model specifications are: summarizes the hypothesis-related estimates, with complete Model 1 FC1 = 0.3385 - 1.5530CO - 0.0230DP + 0.0050Size results reported in Appendix A. + 0.0469ROA + 0.0071CF + Ɛ Restoring the 28 excluded observations produces only Model 2 FC1 = -0.6759 - 3.2099CO - 0.2230DP + 0.03236FO modest changes in coefficients and p-values: CEO + 0.0538(CO×FO) + 0.01513(DP×FO) + 0.0015Size + overconfidence and debt policy remain negative and 0.0458ROA + 0.0071CF + Ɛ significant, while CO×FO and DP×FO remain positive and significant. Thus, the conclusions for H1-H4 are unchanged and

Robustness and Sensitivity Analyses

do not depend on residual-based screening. The 822-Alternative

Financial Condition

Measure observation sample is retained for the primary analysis Using the Altman Z-score as an alternative measure of because the prespecified criterion (|standardized residual| > financial condition, Models 3 and 4 retain the explanatory 3) was applied only once to the baseline model, excluded only variables, controls, and interaction structure of the main 3.29% of observations with unusually large prediction errors, models. CEO overconfidence remains negative and significant and was used consistently across Models 1-4. The consistent in Models 3 and 4 (β = -1.1290, p = 0.044; β = -1.1004, p = full-sample results further indicate that the screening improves 0.034), as does debt policy (β = -0.0197 and -0.0198, both p estimation stability without determining the substantive < 0.001). In Model 4, CO×FO (β = 0.0019, p = 0.001) and conclusions. DP×FO (β = 0.01529, p = 0.030) are positive and significant, indicating that higher family ownership attenuates the

Two-Way Fixed-Effects Robustness

negative associations of CEO overconfidence and debt policy To account for unobserved time-invariant firm with financial condition. As higher Altman Z-scores indicate characteristics, year-specific shocks, and within-firm error stronger financial condition, these results confirm that the dependence, Models 1-4 were re-estimated using two-way fixed directions, significance, and moderating patterns of the effects with firm-clustered standard errors. CEO overconfidence principal variables are consistent across the MFA Score and Table 5. Panel Robustness Analysis Using Two-Way Fixed Effects and Firm-Clustered Standard Errors Model 1 Model 2 Model 3 Model 4 Variable MFA MFA (MRA) Z-score Z-score (MRA) Cons 0.4100 -0.5200 0.6900 0.7400 coef. β -1.3100 -2.6800 -0.9800 -0.9400 t-value -2.18 -2.09 -1.99 -2.00 CO sig. 0.031* 0.038* 0.048* 0.047* Firm-clustered Std Err. 0.6022 1.2815 0.4920 0.4698 coef. β -0.0165 -0.1510 -0.0168 -0.0164 t-value -2.64 -2.54 -2.92 -2.84 DP sig. 0.009* 0.012* 0.004* 0.005* Firm-clustered Std Err. 0.0062 0.0595 0.0058 0.0058 coef. β - 0.0270 - 0.0005 t-value - 2.01 - 1.82 FO sig. - 0.046* - 0.071** Firm-clustered Std Err. - 0.0134 - 0.0003 coef. β - 0.0450 - 0.0016 t-value - 2.06 - 2.22 CO×FO sig. - 0.041* - 0.028* Firm-clustered Std Err. - 0.0219 - 0.0007 coef. β - 0.0110 - 0.0118 t-value - 1.74 - 1.70 DP×FO sig. - 0.083** - 0.091** Firm-clustered Std Err. - 0.0063 - 0.0069 coef. β 0.0120 0.0090 0.2410 0.2360 t-value 0.12 0.10 1.60 1.57 Size sig. 0.902 0.918 0.112 0.119 Firm-clustered Std Err. 0.0973 0.0873 0.1509 0.1506 coef. β 0.0410 0.0400 0.0310 0.0300 t-value 2.78 2.73 3.01 2.92 ROA sig. 0.006* 0.007* 0.003* 0.004* Firm-clustered Std Err. 0.0147 0.0147 0.0103 0.0103 coef. β 0.0064 0.0062 0.0380 0.0370 t-value 2.29 2.20 1.46 1.42 CF sig. 0.023* 0.029* 0.146 0.158 Firm-clustered Std Err. 0.0028 0.0028 0.0260 0.0261 Observations 822 822 822 822 Firm clusters 170 170 170 170 Firm fixed effects Yes Yes Yes Yes Year fixed effects Yes Yes Yes Yes Std errors clustered by firm Yes Yes Yes Yes LSDV R² 0,7020 0,7380 0,7160 0,7290 Two-way within R² 0,1180 0,1340 0,1270 0,1420 Source: Processed data, 2026. Table 6. Comparison of Main and Panel Robustness Results Main pooled model Two-way fixed-effects model Hypothesis Assessment t-value Sig. t-value Sig. H₁: CO -2.39 0.017 -2.18 0.031 Robust H₂: DP -5.33 0.000 -2.64 0.009 Robust H₃: CO×FO 2.21 0.027 2.06 0.041 Robust H₄: DP×FO 2.10 0.036 1.74 0.083 Limited robustness Source: Processed data, 2026. Notes: Firm and year fixed effects; firm-clustered standard errors (170 clusters). “Robust” = same direction and 5% significance; “limited robustness” = same direction but 10% significance. Interactions refer to Models 2 and 4. Table 7. Sensitivity Analysis of

CEO Overconfidence

Measurement Alternative CO → FC, β (sig.) CO×FO → FC, β (sig.) Conclusion measurement Baseline: score ≥3 -1.5530 (0.017) 0.0538 (0.027) Supported Score ≥2 -1.4620 (0.020) 0.0471 (0.035) Robust Score ≥4 -1.6814 (0.012) 0.0589 (0.022) Robust Overinvestment-only -1.3285 (0.028) 0.0445 (0.041) Robust Source: Processed data, and debt policy remain negative and significant, while CO×FO remains positive and significant, firm size insignificant, and remains positive and significant, supporting the robustness of cash flow significant only in the MFA models. Complete 2026.H1-H3. DP×FO remains positive but is significant only at estimates are reported in Table 5. the 10% level, indicating limited robustness for H4. ROA Comparison of pooled and panel estimates (Table 6) shows Table 8. Conditional Effects of

CEO Overconfidence

on

Financial Condition

at Different Levels of Family Ownership Marginal 95% Confidence FO Level FO Value Std. Err Sig. effect Interval Low 0.000 -3.2099 1.2442 0.010 [-5.6523, -0.7675] Mean 1.4556 -3.1316 1.2211 0.011 [-5.5282, -0.7350] High 11.1814 -2.6083 1.0840 0.016 [-4.7356, -0.4810] Source: Processed data, 2026. Figure 2. Interaction between

CEO Overconfidence

and Family Ownership stable directions and 5% significance for H1-H3, indicating conditional associations at other ownership levels are robust findings across both specifications. H4 retains a addressed in the moderation analysis. The finding is consistent positive interaction but weakens from 5% to 10% significance with

Agency Theory

and Upper Echelons Theory: overconfident in the panel model, indicating directional consistency but CEOs may overestimate expected outcomes and limited robustness. underestimate risks, encouraging aggressive investment and financing decisions that increase risk, resource misallocation,

CEO Overconfidence

Measurement Sensitivity and financial pressure (Abdolhosseini & Wooi, 2024; Galariotis Alternative CEO-overconfidence thresholds (scores ≥2 et al., 2023). It also aligns with evidence linking CEO and ≥4) and the overinvestment-only proxy yield consistently characteristics to financial stability (Abdulwahab et al., 2025) negative and statistically significant CEO-overconfidence overconfidence to corporate risk (Liang et al., 2020), and coefficients and positive and significant CO×FO interactions. overconfident CEOs to greater corporate-failure risk (Leng et al., Thus, the conclusions for H1 and H3 remain unchanged, 2021) extending this evidence to Indonesian listed indicating that the main findings are robust to the baseline manufacturing firms. This negative association remains cutoff and composite-index construction (Table 7). significant using the Altman Z-score (Model 3: β = -1.1290, sig. = 0.044), the full sample, two-way fixed effects with firm-

Coefficient of Determination

clustered standard errors, and alternative CEO-overconfidence Table 2 presents the OLS estimates for all models using measures. The finding is therefore robust across samples, the same 822 firm-year observations. Model 1 is the baseline financial-condition measures, estimators, and CEO-specification, while Model 2 adds family ownership and its overconfidence specifications. However, it should be interactions with CEO overconfidence and debt policy. The interpreted as a robust association rather than a definitive adjusted R² increases from 0.6330 in Model 1 to 0.6490 in causal effect because reverse causality and omitted time-Model 2, indicating that the additional moderating terms varying factors cannot be fully excluded. improve explanatory power despite greater model complexity. Models 3 and 4 use the Altman Z-score as an alternative The Effect of Debt Policy on

Financial Condition

. measure of financial condition, with adjusted R² values of

Debt policy

is negatively and significantly associated with 0.6320 and 0.6050, respectively. Although explanatory financial condition in Model 1 (β = -0.0230, sig. = 0.000), power declines slightly in Model 4 after adding the moderating indicating that greater debt reliance is associated with weaker terms, it remains substantial. financial condition after controlling for CEO overconfidence, firm size, profitability, and cash flow; thus, H2 is supported. The The Effect of

CEO Overconfidence

on

Financial Condition

relationship remains negative and significant in Model 2 (β = - CEO overconfidence is negatively and significantly 0.2230, sig. = 0.000), although this coefficient represents the associated with financial condition. In Model 1, its coefficient association when family ownership equals zero because is negative and significant (β = -1.5530, sig. = 0.017), DP×FO is included. Greater debt obligations may reduce indicating that firms led by overconfident CEOs tend to have financial flexibility and increase refinancing and distress risk lower MFA Scores, and thus weaker financial condition, after when cash flows are insufficient, consistent with prior evidence controlling for debt policy, firm size, profitability, and cash linking high or persistent leverage to weaker financial flow. Accordingly, H1 is supported. The coefficient remains outcomes and greater financial vulnerability (Idarti & Hasanah, negative and significant in Model 2 (β = -3.2099, sig. = 2018; Khan & Qasem, 2024; Liu et al., 2025; Samara & 0.010), although, given the CO×FO interaction, it represents Sutandi, 2024, 2024; Sunardi et al., 2020; Zhen et al., 2020). the association when family ownership equals zero; The finding is consistent with

Trade-off Theory

, which holds Table 9. Conditional Effects of Debt Policy on

Financial Condition

at Different Levels of Family Ownership Marginal 95% Confidence FO Level FO Value Std. Err Sig. effect Interval Low 0.0000 -0.2230 0.0436 0.000 [-0.3086, -0.1374] Mean 1.4556 -0.2010 0.0378 0.000 [-0.2752, -0.1268] High 11.1814 -0.0538 0.0626 0.390 [-0.1767, 0.0690] Source: Processed data, 2026. Note:

Family ownership

is measured in percentage points (0-100). Marginal effects, standard errors, and 95% confidence intervals were calculated from Model 2. that debt benefits must be balanced against increasing decisions, potentially weakening financial condition (Galariotis interest, bankruptcy, and financial-distress costs as leverage et al., 2023). However, these consequences depend on the rises (Abdeljawad & Farhood, 2025; Marimuthu & Abbana, ownership context in which managerial discretion is exercised. 2023). This interpretation is particularly relevant given the Concentrated family ownership may strengthen incentives and sample’s maximum DAR of 290.11%, indicating liabilities the ability to constrain decisions that threaten family wealth substantially exceeding assets for some firms. Thus, the result and long-term continuity, consistent with evidence that the does not imply that all debt is detrimental, but that greater consequences of CEO overconfidence vary with governance debt reliance within the observed range is associated with conditions conditions (Leng et al., 2021; Park & Chung, 2017). weaker financial condition. This association remains negative This interpretation is also consistent with the SEW perspective, and significant using the Altman Z-score (Model 3: β = - as family owners seek to preserve control, identity, reputation, 0.0197, sig. = 0.001), the full 850 firm-year sample, and two- and intergenerational continuity (Gomez-Mejia et al., 2014; way fixed effects with firm-clustered standard errors, Hsueh et al., 2023; Muñoz Bullón et al., 2024) . Accordingly, indicating robustness across measures, samples, and the positive CO×FO coefficient indicates that greater family estimators. Nevertheless, the evidence remains associational ownership attenuates the adverse association between CEO rather than causal because reverse causality and time-varying overconfidence and financial condition. omitted factors cannot be excluded. Concentrated family ownership may nevertheless create Type II agency conflicts, entrenchment, or weaker external Family Ownership Moderates the Effect of CEO monitoring, potentially reinforcing managerial preferences or Overconfidence on

Financial Condition

. family interests (Hsueh et al., 2023; Muñoz Bullón et al., 2024)

Family ownership

significantly moderates the relationship . The observed positive interaction and conditional effects are between CEO overconfidence and financial condition. In more consistent with the alternative explanation that family Model 2, the CO×FO interaction is positive and significant (β ownership constrains risky managerial discretion: increasing = 0.0538, p = 0.027), indicating that higher family ownership family ownership reduces the magnitude, but not the direction, attenuates, rather than reverses, the negative association of the negative CEO overconfidence-financial condition between CEO overconfidence and the MFA Score. This association, which remains statistically significant at the low, moderating pattern is also observed in Model 4 using the mean, and high ownership levels (Table 8). Thus, extending Altman Z-score (β = 0.0019, p = 0.001), supporting H3 across prior evidence linking CEO overconfidence to corporate risk, both measures of financial condition. To further assess this failure, performance, and financial distress (Leng et al., 2021; moderation, the marginal effect of CEO overconfidence was Liang et al., 2020; Mardjono et al., 2026; Wantriani & Susanti, estimated at low (0%), mean (1.4556%), and high 2025, 2025), the findings identify family ownership as a (11.1814%) family ownership. The high level represents the boundary condition in the managerial-behavioural pathway to mean plus one standard deviation, while 0% was used as the financial condition rather than as having a uniformly low level because the mean minus one standard deviation fell strengthening or weakening role. below the feasible lower bound. As family ownership is measured in percentage points, the Model 2 marginal effect Family Ownership Moderates the Effect of Debt Policy on is calculated as -3.2099 + 0.0538(FO). Table 8 reports the

Financial Condition

. corresponding estimates, standard errors, significance levels,

Family ownership

significantly moderates the relationship and 95% confidence intervals. between debt policy and financial condition. In Model 2, the As shown in Table 8, the conditional association remains positive and significant DP×FO interaction (β = 0.01513, sig. = negative and significant at low (-3.2099, p = 0.010; 95% CI [- 0.036) indicates that the negative association between debt 5.6523, -0.7675]), mean (-3.1316, p = 0.011; 95% CI [- policy and the MFA Score weakens as family ownership 5.5282, -0.7350]), and high family ownership (-2.6083, p = increases. The interaction remains positive and significant with 0.016; 95% CI [-4.7356, -0.4810]). The progressively smaller the Altman Z-score in Model 4 (β = 0.01529, sig. = 0.030), negative magnitude indicates that family ownership supporting H4 across both financial-condition measures. attenuates the adverse association of CEO overconfidence Conditional effects were estimated at low (0.0000%), mean with financial condition, but does not eliminate or reverse it (1.4556%), and high (11.1814%) family ownership. The because all confidence intervals remain below zero. observed minimum was used as the low level because the Figure 2 confirms this pattern visually: the CEO- mean minus one standard deviation fell below zero, while the overconfidence slope remains negative but becomes high level represents the mean plus one standard deviation. progressively less negative as family ownership increases. Because family ownership is measured from 0 to 100, the The confidence intervals remain below zero at all evaluated conditional effect was calculated as -0.2230 + 0.01513(FO), ownership levels, confirming that the conditional association with standard errors and 95% confidence intervals derived remains statistically significant. Thus, the figure supports an from Model 2 (Table 9). attenuating moderating effect rather than the disappearance Table 9 shows that the negative association weakens as or reversal of the negative association. family ownership increases. The marginal effect is negative and The moderating pattern can be interpreted through significant at low family ownership (-0.2230, sig. = 0.000; 95% Agency and Upper Echelons theories. CEO overconfidence CI [-0.3086, -0.1374]) and at the mean (-0.2010, sig. = 0.000; may encourage excessive reliance on managerial judgment, 95% CI [-0.2752, -0.1268]), but becomes smaller and risk underestimation, and aggressive investment or financing insignificant at the selected high level (-0.0538, sig. = 0.390; Figure 3. Conditional Effect of Debt Policy on

Financial Condition

across Levels of Family Ownership 95% CI [-0.1767, 0.0690]). Thus, the evidence indicates condition across both outcome measures and estimators, attenuation rather than a statistically confirmed reversal. supporting the role of profitability in strengthening firms’ Figure 3 reinforces this interpretation: the 95% financial capacity ((Dirman, 2020); (Karas & Reznakova, confidence interval remains below zero at low and mean 2020). Cash flow is positive and significant in the MFA models family ownership but crosses zero at the selected high level. but insignificant with the Altman Z-score, indicating a measure-Although the point estimate reaches zero at approximately dependent association, whereas firm size remains insignificant 14.74% family ownership above the selected high level of across specifications, consistent with evidence that financial 11.1814% but within the observed sample range statistical difficulties may affect firms of different sizes ((Dirman, 2020) uncertainty emerges before this crossover. The figure (Isayas, 2021). Overall, these control-variable patterns do not therefore supports a weakening, rather than a statistically alter the principal findings: CEO overconfidence, debt policy, confirmed reversal, of the negative debt-policy association. and CO×FO remain consistent across the main and panel The finding is consistent with

Trade-off Theory

, which specifications, while DP×FO retains its direction but shows emphasizes balancing the benefits of debt against interest limited robustness in the panel analysis. obligations, refinancing exposure, bankruptcy risk, and financial-distress costs (Abdeljawad & Farhood, 2025;

Limitations and Cautions

Marimuthu & Abbana, 2023).

Agency Theory

and the SEW Several limitations qualify the findings. Although two-way perspective further suggest that family owners may scrutinize fixed effects address time-invariant firm heterogeneity, year debt-related risks to protect concentrated wealth, control, shocks, and within-firm error dependence, they do not reputation, and intergenerational continuity (Gomez-Mejia et eliminate endogeneity from reverse causality, simultaneity, or al., 2014; Michiels & Molly, 2017; Muñoz‑Bullón et al., 2024; time-varying omitted factors; thus, the results indicate Michiels & Molly, 2017; Baixauli-Soler et al., 2021; Jansen et associations rather than causal effects. H4 is also less robust al., 2023). Accordingly, the positive DP×FO interaction than H1-H3 because DP×FO is significant only at the 10% level indicates that family ownership attenuates the adverse in the panel models. Measurement limitations remain because association between debt utilization and financial condition, CEO overconfidence is indirectly proxied, family ownership does without implying that family firms necessarily use less debt. not capture family involvement or underlying governance Extending prior research on family ownership and leverage, H4 mechanisms, and the accounting-based financial-condition identifies family ownership as a boundary condition in this measures may not fully reflect market expectations, debt-financing pathway: the debt policy-financial condition service capacity, or actual default. Finally, the Indonesian listed association is negative and significant at low and mean family manufacturing sample during 2020-2024, including the COVID-ownership but weaker and insignificant at the selected high 19 disruption and recovery, limits generalizability. level. Supplementary analyses provide broadly consistent but

Recommendations for Future Research

not uniform support. DP×FO remains positive and significant Future research could strengthen causal identification using the Altman Z-score (β = 0.01529, p = 0.030) and the through lagged variables, instrumental variables, natural full sample (Model 2: β = 0.01488, p = 0.037; Model 4: β = experiments, or dynamic panels. It could also employ 0.01501, p = 0.032), indicating that the result is not driven alternative CEO-overconfidence measures, richer indicators of by the financial-condition measure or exclusion of 28 family involvement and governance, and complementary observations. Under two-way fixed effects with firm-clustered financial-condition outcomes, including default, debt-service, standard errors, however, the interaction remains positive but and market-based measures. Broader industries, private firms, is significant only at the 10% level for MFA (β = 0.0110, p = longer periods, and cross-country samples could further assess 0.083) and Altman Z-score (β = 0.0118, p = 0.091). Thus, H4 generalizability. is supported in the main and alternative specifications, although its statistical robustness weakens under the more Conclusion stringent panel specification. This study examines the relationships of CEO overconfidence

Control Variables Across Model Specifications

and debt policy with the financial condition of Indonesian listed Among the control variables, ROA shows the most manufacturing firms and the moderating role of family consistent positive and significant association with financial ownership. Using 822 firm-year observations from 2020-2024, the results show that CEO overconfidence and debt policy are Author contributions negatively associated with financial condition, while family ownership attenuates both relationships. The findings remain The first author developed the research concept, collected consistent across the full sample, the Altman Z-score, and and analyzed the data, interpreted the findings, and prepared alternative CEO-overconfidence measures. Fixed-effects results the manuscript. The second author contributed to the research support H1-H3, whereas H4 shows limited robustness. Overall, methodology, validation of the analytical results, and family ownership represents a boundary condition in both improvement of the manuscript. The third author conducted managerial-behavioural and financing pathways to financial the literature review, synthesized prior studies, assessed the condition. These findings should be interpreted as conditional findings, and contributed to manuscript editing and revision. All associations rather than causal effects or direct evidence of authors reviewed and approved the final manuscript and specific governance mechanisms. The study integrates Upper accepted responsibility for its content. Echelons, Agency, Trade-off, and Socioemotional Wealth perspectives and highlights the relevance of managerial biases, leverage discipline, and ownership context. Future research Acknowledgements could strengthen causal identification and employ richer measures of CEO overconfidence and family involvement. 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Methods

Result and Discussion

Main model Model 1 - MFA Score, direct effects The initial 850 firm-year observations were screened once FC1 = α + β1CO + β2DP + β3Size + β4ROA + β5CF + Ɛ using standardized residuals from Model 1 (|SR| > 3). Excluding 28 observations (3.29%) yielded a common analytical sample of 822 observations for Models 14. All models were also re-estimated on the full 850-observation financial condition. The mean Altman Z-score is 3.4262 (SD = sample to assess sensitivity to this exclusion. 2.9869). CEO overconfidence equals 0.6224 on average, indicating that 62.24% of observations are classified as

Descriptive Statistics

overconfident.

Debt policy

varies widely, with a maximum DAR Table 1 summarizes the characteristics of the 822 firm- of 290.11%, reflecting negative equity in some financially year observations. distressed firms. Firm size, ROA, cash flow, and family The mean MFA Score is 0.3905 (SD = 4.6631), within the ownership also display substantial cross-firm variation. grey-area interval and indicating substantial heterogeneity in

Main Regression Result

Altman Z-score, although coefficient magnitudes are not Multiple Regression Analysis and Moderating Regression directly comparable across scales. Analysis (MRA) Model 1 shows that CEO overconfidence (β = -1.5530, p The estimated equations are: = 0.017) and debt policy (β = -0.0230, p < 0.001) are Model 3 FC2 = 0.7943 - 1.1290CO - 0.0197DP + 0.2656Size negatively and significantly associated with the MFA Score, + 0.0386ROA + 0.0482CF+Ɛ supporting H1 and H2. Because higher MFA Scores indicate Model 4 FC2 = 0.8514 - 1.1004CO - 0.0198DP + 0.0006FO + better financial condition, these negative coefficients indicate 0.0019(CO×FO) + 0.01529(DP×FO) + 0.2633Size + weaker financial condition. ROA and cash flow are positively 0.0383ROA + 0.0476CF + Ɛ significant, whereas firm size is insignificant. In Model 2, family ownership significantly moderates both

Full Sample Sensitivity Analysis

relationships. The CO×FO interaction is positive (β = 0.0538, To assess sensitivity to residual-based outlier screening, p = 0.027), indicating that higher family ownership attenuates Models 1-4 were re-estimated using the full sample of 850 firm-the negative CEO-overconfidence association. The DP×FO year observations, restoring the 28 observations excluded from interaction is likewise positive (β = 0.01513, p = 0.036), the primary analysis while retaining the same variable indicating attenuation of the negative debt-policy association. definitions and model specifications. This analysis assesses H3 and H4 are therefore supported in the pooled MFA model whether the directions and significance of the principal (Table 3). coefficients depend on the screening decision. Table 4 The estimated primary-model specifications are: summarizes the hypothesis-related estimates, with complete Model 1 FC1 = 0.3385 - 1.5530CO - 0.0230DP + 0.0050Size results reported in Appendix A. + 0.0469ROA + 0.0071CF + Ɛ Restoring the 28 excluded observations produces only Model 2 FC1 = -0.6759 - 3.2099CO - 0.2230DP + 0.03236FO modest changes in coefficients and p-values: CEO + 0.0538(CO×FO) + 0.01513(DP×FO) + 0.0015Size + overconfidence and debt policy remain negative and 0.0458ROA + 0.0071CF + Ɛ significant, while CO×FO and DP×FO remain positive and significant. Thus, the conclusions for H1-H4 are unchanged and

Robustness and Sensitivity Analyses

do not depend on residual-based screening. The 822-Alternative

Financial Condition

Measure observation sample is retained for the primary analysis Using the Altman Z-score as an alternative measure of because the prespecified criterion (|standardized residual| > financial condition, Models 3 and 4 retain the explanatory 3) was applied only once to the baseline model, excluded only variables, controls, and interaction structure of the main 3.29% of observations with unusually large prediction errors, models. CEO overconfidence remains negative and significant and was used consistently across Models 1-4. The consistent in Models 3 and 4 (β = -1.1290, p = 0.044; β = -1.1004, p = full-sample results further indicate that the screening improves 0.034), as does debt policy (β = -0.0197 and -0.0198, both p estimation stability without determining the substantive < 0.001). In Model 4, CO×FO (β = 0.0019, p = 0.001) and conclusions. DP×FO (β = 0.01529, p = 0.030) are positive and significant, indicating that higher family ownership attenuates the

Two-Way Fixed-Effects Robustness

negative associations of CEO overconfidence and debt policy To account for unobserved time-invariant firm with financial condition. As higher Altman Z-scores indicate characteristics, year-specific shocks, and within-firm error stronger financial condition, these results confirm that the dependence, Models 1-4 were re-estimated using two-way fixed directions, significance, and moderating patterns of the effects with firm-clustered standard errors. CEO overconfidence principal variables are consistent across the MFA Score and and debt policy remain negative and significant, while CO×FO remains positive and significant, firm size insignificant, and remains positive and significant, supporting the robustness of cash flow significant only in the MFA models. Complete 2026.H1-H3. DP×FO remains positive but is significant only at estimates are reported in Table 5. the 10% level, indicating limited robustness for H4. ROA Comparison of pooled and panel estimates (Table 6) shows stable directions and 5% significance for H1-H3, indicating conditional associations at other ownership levels are robust findings across both specifications. H4 retains a addressed in the moderation analysis. The finding is consistent positive interaction but weakens from 5% to 10% significance with

Agency Theory

and Upper Echelons Theory: overconfident in the panel model, indicating directional consistency but CEOs may overestimate expected outcomes and limited robustness. underestimate risks, encouraging aggressive investment and financing decisions that increase risk, resource misallocation,

CEO Overconfidence

Measurement Sensitivity and financial pressure (Abdolhosseini & Wooi, 2024; Galariotis Alternative CEO-overconfidence thresholds (scores ≥2 et al., 2023). It also aligns with evidence linking CEO and ≥4) and the overinvestment-only proxy yield consistently characteristics to financial stability (Abdulwahab et al., 2025) negative and statistically significant CEO-overconfidence overconfidence to corporate risk (Liang et al., 2020), and coefficients and positive and significant CO×FO interactions. overconfident CEOs to greater corporate-failure risk (Leng et al., Thus, the conclusions for H1 and H3 remain unchanged, 2021) extending this evidence to Indonesian listed indicating that the main findings are robust to the baseline manufacturing firms. This negative association remains cutoff and composite-index construction (Table 7). significant using the Altman Z-score (Model 3: β = -1.1290, sig. = 0.044), the full sample, two-way fixed effects with firm-

Coefficient of Determination

clustered standard errors, and alternative CEO-overconfidence Table 2 presents the OLS estimates for all models using measures. The finding is therefore robust across samples, the same 822 firm-year observations. Model 1 is the baseline financial-condition measures, estimators, and CEO-specification, while Model 2 adds family ownership and its overconfidence specifications. However, it should be interactions with CEO overconfidence and debt policy. The interpreted as a robust association rather than a definitive adjusted R² increases from 0.6330 in Model 1 to 0.6490 in causal effect because reverse causality and omitted time-Model 2, indicating that the additional moderating terms varying factors cannot be fully excluded. improve explanatory power despite greater model complexity. Models 3 and 4 use the Altman Z-score as an alternative The Effect of Debt Policy on

Financial Condition

. measure of financial condition, with adjusted R² values of

Debt policy

is negatively and significantly associated with 0.6320 and 0.6050, respectively. Although explanatory financial condition in Model 1 (β = -0.0230, sig. = 0.000), power declines slightly in Model 4 after adding the moderating indicating that greater debt reliance is associated with weaker terms, it remains substantial. financial condition after controlling for CEO overconfidence, firm size, profitability, and cash flow; thus, H2 is supported. The The Effect of

CEO Overconfidence

on

Financial Condition

relationship remains negative and significant in Model 2 (β = - CEO overconfidence is negatively and significantly 0.2230, sig. = 0.000), although this coefficient represents the associated with financial condition. In Model 1, its coefficient association when family ownership equals zero because is negative and significant (β = -1.5530, sig. = 0.017), DP×FO is included. Greater debt obligations may reduce indicating that firms led by overconfident CEOs tend to have financial flexibility and increase refinancing and distress risk lower MFA Scores, and thus weaker financial condition, after when cash flows are insufficient, consistent with prior evidence controlling for debt policy, firm size, profitability, and cash linking high or persistent leverage to weaker financial flow. Accordingly, H1 is supported. The coefficient remains outcomes and greater financial vulnerability (Idarti & Hasanah, negative and significant in Model 2 (β = -3.2099, sig. = 2018; Khan & Qasem, 2024; Liu et al., 2025; Samara & 0.010), although, given the CO×FO interaction, it represents Sutandi, 2024, 2024; Sunardi et al., 2020; Zhen et al., 2020). the association when family ownership equals zero; The finding is consistent with

Trade-off Theory

, which holds Table 9. Conditional Effects of Debt Policy on

Financial Condition

at Different Levels of Family Ownership Marginal 95% Confidence FO Level FO Value Std. Err Sig. effect Interval Low 0.0000 -0.2230 0.0436 0.000 [-0.3086, -0.1374] Mean 1.4556 -0.2010 0.0378 0.000 [-0.2752, -0.1268] High 11.1814 -0.0538 0.0626 0.390 [-0.1767, 0.0690] Source: Processed data, 2026. Note:

Family ownership

is measured in percentage points (0-100). Marginal effects, standard errors, and 95% confidence intervals were calculated from Model 2. that debt benefits must be balanced against increasing decisions, potentially weakening financial condition (Galariotis interest, bankruptcy, and financial-distress costs as leverage et al., 2023). However, these consequences depend on the rises (Abdeljawad & Farhood, 2025; Marimuthu & Abbana, ownership context in which managerial discretion is exercised. 2023). This interpretation is particularly relevant given the Concentrated family ownership may strengthen incentives and sample’s maximum DAR of 290.11%, indicating liabilities the ability to constrain decisions that threaten family wealth substantially exceeding assets for some firms. Thus, the result and long-term continuity, consistent with evidence that the does not imply that all debt is detrimental, but that greater consequences of CEO overconfidence vary with governance debt reliance within the observed range is associated with conditions conditions (Leng et al., 2021; Park & Chung, 2017). weaker financial condition. This association remains negative This interpretation is also consistent with the SEW perspective, and significant using the Altman Z-score (Model 3: β = - as family owners seek to preserve control, identity, reputation, 0.0197, sig. = 0.001), the full 850 firm-year sample, and two- and intergenerational continuity (Gomez-Mejia et al., 2014; way fixed effects with firm-clustered standard errors, Hsueh et al., 2023; Muñoz Bullón et al., 2024) . Accordingly, indicating robustness across measures, samples, and the positive CO×FO coefficient indicates that greater family estimators. Nevertheless, the evidence remains associational ownership attenuates the adverse association between CEO rather than causal because reverse causality and time-varying overconfidence and financial condition. omitted factors cannot be excluded. Concentrated family ownership may nevertheless create Type II agency conflicts, entrenchment, or weaker external Family Ownership Moderates the Effect of CEO monitoring, potentially reinforcing managerial preferences or Overconfidence on

Financial Condition

. family interests (Hsueh et al., 2023; Muñoz Bullón et al., 2024)

Family ownership

significantly moderates the relationship . The observed positive interaction and conditional effects are between CEO overconfidence and financial condition. In more consistent with the alternative explanation that family Model 2, the CO×FO interaction is positive and significant (β ownership constrains risky managerial discretion: increasing = 0.0538, p = 0.027), indicating that higher family ownership family ownership reduces the magnitude, but not the direction, attenuates, rather than reverses, the negative association of the negative CEO overconfidence-financial condition between CEO overconfidence and the MFA Score. This association, which remains statistically significant at the low, moderating pattern is also observed in Model 4 using the mean, and high ownership levels (Table 8). Thus, extending Altman Z-score (β = 0.0019, p = 0.001), supporting H3 across prior evidence linking CEO overconfidence to corporate risk, both measures of financial condition. To further assess this failure, performance, and financial distress (Leng et al., 2021; moderation, the marginal effect of CEO overconfidence was Liang et al., 2020; Mardjono et al., 2026; Wantriani & Susanti, estimated at low (0%), mean (1.4556%), and high 2025, 2025), the findings identify family ownership as a (11.1814%) family ownership. The high level represents the boundary condition in the managerial-behavioural pathway to mean plus one standard deviation, while 0% was used as the financial condition rather than as having a uniformly low level because the mean minus one standard deviation fell strengthening or weakening role. below the feasible lower bound. As family ownership is measured in percentage points, the Model 2 marginal effect Family Ownership Moderates the Effect of Debt Policy on is calculated as -3.2099 + 0.0538(FO). Table 8 reports the

Financial Condition

. corresponding estimates, standard errors, significance levels,

Family ownership

significantly moderates the relationship and 95% confidence intervals. between debt policy and financial condition. In Model 2, the As shown in Table 8, the conditional association remains positive and significant DP×FO interaction (β = 0.01513, sig. = negative and significant at low (-3.2099, p = 0.010; 95% CI [- 0.036) indicates that the negative association between debt 5.6523, -0.7675]), mean (-3.1316, p = 0.011; 95% CI [- policy and the MFA Score weakens as family ownership 5.5282, -0.7350]), and high family ownership (-2.6083, p = increases. The interaction remains positive and significant with 0.016; 95% CI [-4.7356, -0.4810]). The progressively smaller the Altman Z-score in Model 4 (β = 0.01529, sig. = 0.030), negative magnitude indicates that family ownership supporting H4 across both financial-condition measures. attenuates the adverse association of CEO overconfidence Conditional effects were estimated at low (0.0000%), mean with financial condition, but does not eliminate or reverse it (1.4556%), and high (11.1814%) family ownership. The because all confidence intervals remain below zero. observed minimum was used as the low level because the Figure 2 confirms this pattern visually: the CEO- mean minus one standard deviation fell below zero, while the overconfidence slope remains negative but becomes high level represents the mean plus one standard deviation. progressively less negative as family ownership increases. Because family ownership is measured from 0 to 100, the The confidence intervals remain below zero at all evaluated conditional effect was calculated as -0.2230 + 0.01513(FO), ownership levels, confirming that the conditional association with standard errors and 95% confidence intervals derived remains statistically significant. Thus, the figure supports an from Model 2 (Table 9). attenuating moderating effect rather than the disappearance Table 9 shows that the negative association weakens as or reversal of the negative association. family ownership increases. The marginal effect is negative and The moderating pattern can be interpreted through significant at low family ownership (-0.2230, sig. = 0.000; 95% Agency and Upper Echelons theories. CEO overconfidence CI [-0.3086, -0.1374]) and at the mean (-0.2010, sig. = 0.000; may encourage excessive reliance on managerial judgment, 95% CI [-0.2752, -0.1268]), but becomes smaller and risk underestimation, and aggressive investment or financing insignificant at the selected high level (-0.0538, sig. = 0.390; 95% CI [-0.1767, 0.0690]). Thus, the evidence indicates condition across both outcome measures and estimators, attenuation rather than a statistically confirmed reversal. supporting the role of profitability in strengthening firms’ Figure 3 reinforces this interpretation: the 95% financial capacity ((Dirman, 2020); (Karas & Reznakova, confidence interval remains below zero at low and mean 2020). Cash flow is positive and significant in the MFA models family ownership but crosses zero at the selected high level. but insignificant with the Altman Z-score, indicating a measure-Although the point estimate reaches zero at approximately dependent association, whereas firm size remains insignificant 14.74% family ownership above the selected high level of across specifications, consistent with evidence that financial 11.1814% but within the observed sample range statistical difficulties may affect firms of different sizes ((Dirman, 2020) uncertainty emerges before this crossover. The figure (Isayas, 2021). Overall, these control-variable patterns do not therefore supports a weakening, rather than a statistically alter the principal findings: CEO overconfidence, debt policy, confirmed reversal, of the negative debt-policy association. and CO×FO remain consistent across the main and panel The finding is consistent with

Trade-off Theory

, which specifications, while DP×FO retains its direction but shows emphasizes balancing the benefits of debt against interest limited robustness in the panel analysis. obligations, refinancing exposure, bankruptcy risk, and financial-distress costs (Abdeljawad & Farhood, 2025;

Limitations and Cautions

Marimuthu & Abbana, 2023).

Agency Theory

and the SEW Several limitations qualify the findings. Although two-way perspective further suggest that family owners may scrutinize fixed effects address time-invariant firm heterogeneity, year debt-related risks to protect concentrated wealth, control, shocks, and within-firm error dependence, they do not reputation, and intergenerational continuity (Gomez-Mejia et eliminate endogeneity from reverse causality, simultaneity, or al., 2014; Michiels & Molly, 2017; Muñoz‑Bullón et al., 2024; time-varying omitted factors; thus, the results indicate Michiels & Molly, 2017; Baixauli-Soler et al., 2021; Jansen et associations rather than causal effects. H4 is also less robust al., 2023). Accordingly, the positive DP×FO interaction than H1-H3 because DP×FO is significant only at the 10% level indicates that family ownership attenuates the adverse in the panel models. Measurement limitations remain because association between debt utilization and financial condition, CEO overconfidence is indirectly proxied, family ownership does without implying that family firms necessarily use less debt. not capture family involvement or underlying governance Extending prior research on family ownership and leverage, H4 mechanisms, and the accounting-based financial-condition identifies family ownership as a boundary condition in this measures may not fully reflect market expectations, debt-financing pathway: the debt policy-financial condition service capacity, or actual default. Finally, the Indonesian listed association is negative and significant at low and mean family manufacturing sample during 2020-2024, including the COVID-ownership but weaker and insignificant at the selected high 19 disruption and recovery, limits generalizability. level. Supplementary analyses provide broadly consistent but

Recommendations for Future Research

not uniform support. DP×FO remains positive and significant Future research could strengthen causal identification using the Altman Z-score (β = 0.01529, p = 0.030) and the through lagged variables, instrumental variables, natural full sample (Model 2: β = 0.01488, p = 0.037; Model 4: β = experiments, or dynamic panels. It could also employ 0.01501, p = 0.032), indicating that the result is not driven alternative CEO-overconfidence measures, richer indicators of by the financial-condition measure or exclusion of 28 family involvement and governance, and complementary observations. Under two-way fixed effects with firm-clustered financial-condition outcomes, including default, debt-service, standard errors, however, the interaction remains positive but and market-based measures. Broader industries, private firms, is significant only at the 10% level for MFA (β = 0.0110, p = longer periods, and cross-country samples could further assess 0.083) and Altman Z-score (β = 0.0118, p = 0.091). Thus, H4 generalizability. is supported in the main and alternative specifications, although its statistical robustness weakens under the more Conclusion stringent panel specification. This study examines the relationships of CEO overconfidence

Control Variables Across Model Specifications

and debt policy with the financial condition of Indonesian listed Among the control variables, ROA shows the most manufacturing firms and the moderating role of family consistent positive and significant association with financial ownership. Using 822 firm-year observations from 2020-2024, the results show that CEO overconfidence and debt policy are Author contributions negatively associated with financial condition, while family ownership attenuates both relationships. The findings remain The first author developed the research concept, collected consistent across the full sample, the Altman Z-score, and and analyzed the data, interpreted the findings, and prepared alternative CEO-overconfidence measures. Fixed-effects results the manuscript. The second author contributed to the research support H1-H3, whereas H4 shows limited robustness. Overall, methodology, validation of the analytical results, and family ownership represents a boundary condition in both improvement of the manuscript. The third author conducted managerial-behavioural and financing pathways to financial the literature review, synthesized prior studies, assessed the condition. These findings should be interpreted as conditional findings, and contributed to manuscript editing and revision. All associations rather than causal effects or direct evidence of authors reviewed and approved the final manuscript and specific governance mechanisms. The study integrates Upper accepted responsibility for its content. Echelons, Agency, Trade-off, and Socioemotional Wealth perspectives and highlights the relevance of managerial biases, leverage discipline, and ownership context. Future research Acknowledgements could strengthen causal identification and employ richer measures of CEO overconfidence and family involvement. 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(1984). Upper Echelons: The Organization as a Abdolhosseini, M., & Wooi, H. C. (2024). CEO Age & Firm Risk-Taking: The Reflection of Its Top Managers. Academy of Management Review, 9(2), Moderating Role of Uncertainty in the Middle East Countries. 193–206. https://doi.org/10.5465/amr.1984.4277628 International Postgraduate Research Symposium (INPOS), 3, 74–84. Hamzah, Z. Z., Gursida, H., & Indrayono, Y. (2024). Determinants of Financial Abdulwahab, A. I., Bala, H., Abdullahi, M., & Daddau, H. (2025). Chief Executive Distress and the Role of Firm Size the Variables are CR, DAR, to FD and Officer Characteristics and Financial Distress of Listed Financial Service FS as Moderation. The Es Economics and Entrepreneurship, 3(1), 87–99. Firms in Nigeria : Moderating Role Of Whistle Blowing. POLAC https://doi.org/10.58812/esee.v3i01 ECONOMIC REVIEW, 5(1), 264–273. Horváthová, J., & Mokrišová, M. (2018). Risk of Bankruptcy, Its Determinants and Altman, E. I. (1968). Financial Ratios, Discriminant Analysis and The Prediction Models. Risks, 6(4), 1–22. https://doi.org/10.3390/risks6040117 of Corporate Bankruptcy. The Journal of Finance, XXIII(4), 589–609. Hsueh, J. W., Massis, A. De, & Gomez-mejia, L. (2023). Examining Heterogeneous Baixauli-Soler, J. S., Belda-Ruiz, M., & Sánchez-Marín, G. (2021). Configurations of Socioemotional Wealth in Family Firms Through the Socioemotional Wealth and Financial Decisions in Private Family SMEs. Formalization of Corporate Social Responsibility Strategy. Family Business Journal of Business Research, 123(June 2020), 657–668. Review, 36(2), 172–198. https://doi.org/10.1016/j.jbusres.2020.10.022 https://doi.org/10.1177/08944865221146350 Brigham, E. F., & Daves, P. R. (2019). Intermediate Financial Management Idarti, & Hasanah, A. (2018). Analisis Pengaruh Struktur Kepemilikan, Kebijakan (13rd ed.). Cengage Learning. Hutang dan Likuiditas terhadap Financial Distress (Studi Empiris pada Chandrarin, G. (2017). Metode Riset Akuntansi. Salemba Empat. Perusahaan Properti dan Real Estate yang terdaftar di Bursa Efek Chua, M.-S., Roslen, S. N. M., Nizar, N., Chin, H.-C. C., & Hen, K. W. (2025). CEO Indonesia Periode 2013 – 2017). Journal of Applied Managerial Education and Bank’s Performance In Malaysia : Evidence From Stem Accounting, 2(2), 160–178. CEO, Finance CEO, MBA CEO, and CEO Educationl Level. South East Asia Isayas, Y. N. (2021). Financial Distress and its Determinants : Evidence from Journal of Contemporary Business, Economics and Law, 34(Apr), 113– Insurance Companies in Ethiopia Financial Distress and its Determinants : 119. Evidence from insurance companies in Ethiopia. Cogent Business & Çolak, M. S. (2021). A New Multivariate Approach for Assessing Corporate Management, 8(1), 1–16. Financial Risk Using Balance Sheets. Borsa Istanbul Review, 21(3), https://doi.org/10.1080/23311975.2021.1951110 239–255. https://doi.org/https://doi.org/10.1016/j.bir.2020.10.007 Jansen, K., Michiels, A., Voordeckers, W., & Steijvers, T. (2023). Financing Dirman, A. (2020). Financial Distress: The Impacts of Profitability, Liquidity, Decisions in Private Family Firms: a Family Firm Pecking Order. Small Leverage, Firm Size, and Free Cash Flow. International Journal of Business Economics, 61(2), 495–515. Business, Economics and Law, 22(1), 17–25. https://doi.org/10.1007/s11187-022-00711-9 Galariotis, E., Louca, C., Petmezas, D., & Wang, S. (2023). Agency Cost of Debt Jensen, M. C., & Meckling, W. H. (1976). Theory of the Firm: Managerial Behavior, and Inside Debt: The Role of

CEO Overconfidence

. British Journal Agency Costs, and Ownership Structure. Journal of Financial Economics, OfManagement, 34, 1606–1631. https://doi.org/10.1111/1467- 3, 305–360. 8551.12661 Kaplan, S. N., Sørensen, M., & Zakolyukina, A. A. (2022). What is CEO Ghozali, I. (2020). 25 Teori Besar Ilmu Manajemen, Akuntansi, dan Bisnis. Yoga Overconfidence? Evidence from Executive Assessments. Journal of Pratama. Financial Economics, 145, 409–425. Gomez-Mejia, L. R., Campbell, J. T., Martin, G., Hoskisson, R. E., Makri, M., & https://doi.org/10.1016/j.jfineco.2021.09.023 Sirmon, D. G. (2014). Socioemotional Wealth as a Mixed Gamble: Karas, M., & Reznakova, M. (2020). Cash Flows Indicators in the Prediction of Revisiting Family Firm R&D Investments With the Behavioral Agency Financial Distress. Inzinerine Ekonomika-Engineering Economics, 31(5), Model. Entrepreneurship: Theory and Practice, 38(6), 1351–1374. 525–535. https://doi.org/10.1111/etap.12083 1351 https://doi.org/http://dx.doi.org/10.5755/j01.ee.31.5.25202 Gómez-Mejía, L. R., Haynes, K. T., Núñez-Nickel, M., Jacobson, K. J. L., & Kasmir. (2021). Analisis Laporan Keuangan (Edisi Revi). Raja Grafindo Persada. Moyano-Fuentes, J. (2007). Socioemotional Wealth and Business Risks Khan, S., & Qasem, A. (2024). Are the Firms ’ Capital Structure and Performance in Family-Controlled Firms: Evidence from Spanish Olive Oil Mills. Related? Evidence from GCC Economies. Cogent Business & Administrative Science Quarterly, 52(1), 106–137. Management, 11(1), 1–27. Gottardo, P., & Moisello, A. M. (2015). The Impact of Socioemotional Wealth on https://doi.org/10.1080/23311975.2024.2344749 Family Firms’ Financial Performance. Problems and Perspectives in Leng, J., Ozkan, A., Ozkan, N., & Trzeciakiewicz, A. (2021).

CEO Overconfidence

Management, 13(1), 67–77. and the Probability of Corporate Failure: Evidence from the United Gottardo, P., & Moisello, A. M. (2017). Family Firms, Risk-Taking and Financial Kingdom. European Journal of Finance, 27(12), 1210–1234. Distress. Problems and Perspectives in Management, 15(2), 168–177. https://doi.org/10.1080/1351847X.2021.1876131 https://doi.org/10.21511/ppm.15(2-1).2017.01 Liang, Q., Ling, L., Tang, J., Zeng, H., & Zhuang, M. (2020). Managerial Gottardo, P., & Moisello, A. M. (2019). Capital Structure, Earnings Overconfidence , Firm Transparency , and Stock Price Crash Risk Evidence Management, and Risk of Financial Distress: A Comparative Analysis of from an Emerging Market. China Finance Review International, 10(3), Family and Non-Family Firms (Springer Briefs in Business, Ed.). Springer. 271–296. https://doi.org/10.1108/CFRI-01-2019-0007 https://doi.org/https://doi.org./10.1007/978-3-030-00344-9 Liu, R., Li, J., & Wu, M. (2025). The Impact of Climate Change Risk on Corporate Gounopoulos, D., Loukopoulos, G., & Loukopoulos, P. (2021). CEO Education Debt Financing Capacity : A Moderating Perspective Based on Carbon Emissions. Sustainability, 17, 1–37. Journal of Risk and Financial Management, 13(3), 47. https://doi.org/https://doi.org/10.3390/su17146276 https://doi.org/10.3390/jrfm13030047 Louis, H., & Urcan, O. (2015). Agency Conflicts, Dividend Payout, and the Direct Park, J., & Chung, C. Y. (2017).

CEO Overconfidence

, Leadership Ethics , and Benefits of Conservative Financial Reporting to Equity-Holders. Institutional Investors. Sustainability Article, 9(14), 1–28. Contemporary Accounting Research, 32(2), 455–484. https://doi.org/10.3390/su9010014 https://doi.org/doi:10.1111/1911-3846.12085 Ramadhanti, N. C., & Subagyo. (2022). Pengaruh Corporate Governance, Cash Madyan, M., Meidiaswati, H., Sasikirono, N., & Herlambang, M. H. (2019). Flow dan Profit terhadap Financial Distress Perusahaan Manufaktur di Family Control, Institutional Ownership, dan Kebijakan Dividen Bursa Efek Indonesia. Trilogi Accounting and Business Research, 03(01), Perusahaan Manufaktur Yang Terdaftar Di Bursa Efek Indonesia. Jurnal 13–33. Reviu Akuntansi Dan Keuangan, 9(1), 97–106. Richardson, S. (2006). Over-Investment of Free Cash Flow. Review of Accounting https://doi.org/10.22219/jrak.v9i1.47 Studies, 11(2–3), 159–189. https://doi.org/10.1007/s11142-006-Mahardini, N. Y., & Bandi. (2023). Choosing Ratio in the Financial Distress 9012-1 Prediction Model. Journal of Namibian Studies, 34, 1213–1232. Samara, A., & Sutandi. (2024). Pengaruh Profitabilitas , Kebijakan Hutang dan Mardjono, A., Maupa, H., Setyawan, I. R., & Pelawi, R. Y. (2026). When Perputaran Aset terhadap Financial Distress (Studi Empiris Pada Confidence Becomes Risk : The Interplay of

CEO Overconfidence

, Perusahaan Sub Sektor Kimia Yang Terdaftar di BEI Tahun 2020 – 2022 Strategic Risk-Taking, and Financial Performance in Indonesian Digital ). Jurnal Ilmiah Akuntansi Dan Teknologi, 16(1), 1–12. Banks. Risk and Financial Management, 19(317), 1–30. Shiro, A., & Biiranee, K. (2025). Testing The Trade-Off Theory of Capital Structure https://doi.org/https://doi.org/10.3390/jrfm19050317 in Nigerian Firms. International Journal of Education and Social Science Marimuthu, F., & Abbana, S. (2023). Financing Of State-Owned Entities : Can Research, 8(3), 262–280. The Trade-Off Theory Explain the Debt Structure? International Journal https://doi.org/https://doi.org/10.37500/IJESSR.2025.8317 of Entrepreneurship and Sustainability Studies, 3(1). Sunardi, N., Husain, T., & Kadim, A. (2020). Determinants of Debt Policy a nd https://doi.org/https://doi.org/10.31098/ijeass.v3i1.1483 Company’s Performance. International Journal of Economics and Ma’sum, M. A., Badjuri, A., Bagana, B. D., & Arisani, M. D. (2022). Business Administration, VIII(4), 204–213. Conservatisme Akuntansi dan Overconfidence CEO. Jurnal Bisnis Dan https://doi.org/10.35808/ijeba/580 Ekonomi, 29(2), 138–147. Tanjaya, F. L., & Santoso, E. B. (2020). Asosiasi Karakteristik CEO terhadap Michiels, A., & Molly, V. (2017). Financing Decisions in Family Businesses: A Potensi Kesulitan Keuangan Perusahaan. Media Akuntansi Dan Review and Suggestions for Developing the Field. Family Business Perpajakan Indonesia, 1(2), 57–69. Review, 30(4), 369–399. Wantriani, R., & Susanti, N. (2025). Analisis

CEO Overconfidence

Terhadap https://doi.org/https://doi.org/10.1177/0894486517736958 Financial Distress pada Perusahaan Produsen Minyak dan Gas Yang Mișu, N. B., & Madaleno, M. (2020). Assessment of Bankruptcy Risk of Large Terdaftar di London Stock Exchange Group Periode 2018-2022. Journal Companies: European Countries Evolution Analysis. Journal of Risk and of Accounting and Finance Management, 6(5), 2512–2522. Financial Management, 13(3), 1–28. https://doi.org/https://doi.org/10.38035/jafm.v6i5 https://doi.org/doi:10.3390/jrfm13030058 Xiao, L., Bai, M., Xiong, L., & Yang, L. (2021). Financial Slack and Inefficient Muñoz-Bullón, F., Sanchez-Bueno, M. J., & Velasco, P. (2024). Exploring The Investment Decisions in China. Managerial and Decision Economics, Link Between Family Ownership and Leverage: A Mediating Pathway 42(4), 920–941. https://doi.org/10.1002/mde.3282 Through Socioemotional Wealth Objectives. Review of Managerial Zhen, H., Weiwei, G., & Liying, C. (2020). Does the External Environment Matter Science, 18, 3203–3252. for the Persistence of Firms Debt Policy? Finance Research Letters, https://doi.org/https://doi.org/10.1007/s11846-023-00713-1 32(127), 1–9. https://doi.org/10.1016/j.frl.2018.12.021 Ogachi, D., Ndege, R., Gaturu, P., & Zoltan, Z. (2020). Corporate Bankruptcy Prediction Model, a Special Focus on Listed Companies in Kenya.

Table 1. Descriptive Statistics

Source: Processed data, 2026. Note: FC = Financial Condition; CO = CEO Overconfidence; DP = Debt Policy; Size = Firm Size; ROA = Return on Assets; CF = Cash Flow; FO = Family Ownership.

Table 2. Results of Multiple Regression Analysis and MRA

Source: Processed data, 2026.

Table 3. Summary of Main Test Results and Alternative Measure Robustness Test

Source: Processed data, 2026.

Table 4. Comparison of the Main and Full Sample Estimates

Source: Processed data, 2026.

Table 5. Panel Robustness Analysis Using Two-Way Fixed Effects and Firm-Clustered Standard Errors

Source: Processed data, 2026.

Table 6. Comparison of Main and Panel Robustness Results

Source: Processed data, 2026.

Table 7. Sensitivity Analysis of CEO Overconfidence Measurement

Source: Processed data, 2026.

Table 8. Conditional Effects of CEO Overconfidence on Financial Condition at Different Levels of Family Ownership

Source: Processed data, 2026.

Conclusion

Author Contributions

Acknowledgements

References

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ECONOMIC REVIEW, 5(1), 264–273. Horváthová, J., & Mokrišová, M. (2018). Risk of Bankruptcy, Its Determinants and

Altman, E. I. (1968). Financial Ratios, Discriminant Analysis and The Prediction Models. Risks, 6(4), 1–22. https://doi.org/10.3390/risks6040117 of Corporate Bankruptcy. The Journal of Finance, XXIII(4), 589–609. Hsueh, J. W., Massis, A. De, & Gomez-mejia, L. (2023). Examining Heterogeneous

Baixauli-Soler, J. S., Belda-Ruiz, M., & Sánchez-Marín, G. (2021). Configurations of Socioemotional Wealth in Family Firms Through the Socioemotional Wealth and Financial Decisions in Private Family SMEs. Formalization of Corporate Social Responsibility Strategy. Family Business Journal of Business Research, 123(June 2020), 657–668. Review, 36(2), 172–198. https://doi.org/10.1016/j.jbusres.2020.10.022 https://doi.org/10.1177/08944865221146350

Brigham, E. F., & Daves, P. R. (2019). Intermediate Financial Management Idarti, & Hasanah, A. (2018). Analisis Pengaruh Struktur Kepemilikan, Kebijakan (13rd ed.). Cengage Learning. Hutang dan Likuiditas terhadap Financial Distress (Studi Empiris pada

Chandrarin, G. (2017). Metode Riset Akuntansi. Salemba Empat. Perusahaan Properti dan Real Estate yang terdaftar di Bursa Efek

Chua, M.-S., Roslen, S. N. M., Nizar, N., Chin, H.-C. C., & Hen, K. W. (2025). CEO Indonesia Periode 2013 – 2017). Journal of Applied Managerial Education and Bank’s Performance In Malaysia : Evidence From Stem Accounting, 2(2), 160–178.

CEO, Finance CEO, MBA CEO, and CEO Educationl Level. South East Asia Isayas, Y. N. (2021). Financial Distress and its Determinants : Evidence from Journal of Contemporary Business, Economics and Law, 34(Apr), 113– Insurance Companies in Ethiopia Financial Distress and its Determinants : 119. Evidence from insurance companies in Ethiopia. Cogent Business &

Çolak, M. S. (2021). A New Multivariate Approach for Assessing Corporate Management, 8(1), 1–16. Financial Risk Using Balance Sheets. Borsa Istanbul Review, 21(3), https://doi.org/10.1080/23311975.2021.1951110 239–255. https://doi.org/https://doi.org/10.1016/j.bir.2020.10.007 Jansen, K., Michiels, A., Voordeckers, W., & Steijvers, T. (2023). Financing

Dirman, A. (2020). Financial Distress: The Impacts of Profitability, Liquidity, Decisions in Private Family Firms: a Family Firm Pecking Order. Small Leverage, Firm Size, and Free Cash Flow. International Journal of Business Economics, 61(2), 495–515. Business, Economics and Law, 22(1), 17–25. https://doi.org/10.1007/s11187-022-00711-9

Galariotis, E., Louca, C., Petmezas, D., & Wang, S. (2023). Agency Cost of Debt Jensen, M. C., & Meckling, W. H. (1976). Theory of the Firm: Managerial Behavior, and Inside Debt: The Role of CEO Overconfidence. British Journal Agency Costs, and Ownership Structure. Journal of Financial Economics, OfManagement, 34, 1606–1631. https://doi.org/10.1111/1467- 3, 305–360. 8551.12661 Kaplan, S. N., Sørensen, M., & Zakolyukina, A. A. (2022). What is CEO

Ghozali, I. (2020). 25 Teori Besar Ilmu Manajemen, Akuntansi, dan Bisnis. Yoga Overconfidence? Evidence from Executive Assessments. Journal of Pratama. Financial Economics, 145, 409–425. Gomez-Mejia, L. R., Campbell, J. T., Martin, G., Hoskisson, R. E., Makri, M., & https://doi.org/10.1016/j.jfineco.2021.09.023

Sirmon, D. G. (2014). Socioemotional Wealth as a Mixed Gamble: Karas, M., & Reznakova, M. (2020). Cash Flows Indicators in the Prediction of Revisiting Family Firm R&D Investments With the Behavioral Agency Financial Distress. Inzinerine Ekonomika-Engineering Economics, 31(5), Model. Entrepreneurship: Theory and Practice, 38(6), 1351–1374. 525–535. https://doi.org/10.1111/etap.12083 1351 https://doi.org/http://dx.doi.org/10.5755/j01.ee.31.5.25202

Gómez-Mejía, L. R., Haynes, K. T., Núñez-Nickel, M., Jacobson, K. J. L., & Kasmir. (2021). Analisis Laporan Keuangan (Edisi Revi). Raja Grafindo Persada.

Moyano-Fuentes, J. (2007). Socioemotional Wealth and Business Risks Khan, S., & Qasem, A. (2024). Are the Firms ’ Capital Structure and Performance in Family-Controlled Firms: Evidence from Spanish Olive Oil Mills. Related? Evidence from GCC Economies. Cogent Business & Administrative Science Quarterly, 52(1), 106–137. Management, 11(1), 1–27.

Gottardo, P., & Moisello, A. M. (2015). The Impact of Socioemotional Wealth on https://doi.org/10.1080/23311975.2024.2344749

Family Firms’ Financial Performance. Problems and Perspectives in Leng, J., Ozkan, A., Ozkan, N., & Trzeciakiewicz, A. (2021). CEO Overconfidence Management, 13(1), 67–77. and the Probability of Corporate Failure: Evidence from the United

Gottardo, P., & Moisello, A. M. (2017). Family Firms, Risk-Taking and Financial Kingdom. European Journal of Finance, 27(12), 1210–1234. Distress. Problems and Perspectives in Management, 15(2), 168–177. https://doi.org/10.1080/1351847X.2021.1876131 https://doi.org/10.21511/ppm.15(2-1).2017.01 Liang, Q., Ling, L., Tang, J., Zeng, H., & Zhuang, M. (2020). Managerial

Gottardo, P., & Moisello, A. M. (2019). Capital Structure, Earnings Overconfidence , Firm Transparency , and Stock Price Crash Risk Evidence Management, and Risk of Financial Distress: A Comparative Analysis of from an Emerging Market. China Finance Review International, 10(3), Family and Non-Family Firms (Springer Briefs in Business, Ed.). Springer. 271–296. https://doi.org/10.1108/CFRI-01-2019-0007 https://doi.org/https://doi.org./10.1007/978-3-030-00344-9 Liu, R., Li, J., & Wu, M. (2025). The Impact of Climate Change Risk on Corporate

Gounopoulos, D., Loukopoulos, G., & Loukopoulos, P. (2021). CEO Education Debt Financing Capacity : A Moderating Perspective Based on Carbon Emissions. Sustainability, 17, 1–37. Journal of Risk and Financial Management, 13(3), 47. https://doi.org/https://doi.org/10.3390/su17146276 https://doi.org/10.3390/jrfm13030047

Louis, H., & Urcan, O. (2015). Agency Conflicts, Dividend Payout, and the Direct Park, J., & Chung, C. Y. (2017). CEO Overconfidence , Leadership Ethics , and Benefits of Conservative Financial Reporting to Equity-Holders. Institutional Investors. Sustainability Article, 9(14), 1–28. Contemporary Accounting Research, 32(2), 455–484. https://doi.org/10.3390/su9010014 https://doi.org/doi:10.1111/1911-3846.12085 Ramadhanti, N. C., & Subagyo. (2022). Pengaruh Corporate Governance, Cash

Madyan, M., Meidiaswati, H., Sasikirono, N., & Herlambang, M. H. (2019). Flow dan Profit terhadap Financial Distress Perusahaan Manufaktur di Family Control, Institutional Ownership, dan Kebijakan Dividen Bursa Efek Indonesia. Trilogi Accounting and Business Research, 03(01), Perusahaan Manufaktur Yang Terdaftar Di Bursa Efek Indonesia. Jurnal 13–33.

Reviu Akuntansi Dan Keuangan, 9(1), 97–106. Richardson, S. (2006). Over-Investment of Free Cash Flow. Review of Accounting https://doi.org/10.22219/jrak.v9i1.47 Studies, 11(2–3), 159–189. https://doi.org/10.1007/s11142-006-Mahardini, N. Y., & Bandi. (2023). Choosing Ratio in the Financial Distress 9012-1

Prediction Model. Journal of Namibian Studies, 34, 1213–1232. Samara, A., & Sutandi. (2024). Pengaruh Profitabilitas , Kebijakan Hutang dan

Mardjono, A., Maupa, H., Setyawan, I. R., & Pelawi, R. Y. (2026). When Perputaran Aset terhadap Financial Distress (Studi Empiris Pada Confidence Becomes Risk : The Interplay of CEO Overconfidence, Perusahaan Sub Sektor Kimia Yang Terdaftar di BEI Tahun 2020 – 2022 Strategic Risk-Taking, and Financial Performance in Indonesian Digital ). Jurnal Ilmiah Akuntansi Dan Teknologi, 16(1), 1–12.

Banks. Risk and Financial Management, 19(317), 1–30. Shiro, A., & Biiranee, K. (2025). Testing The Trade-Off Theory of Capital Structure https://doi.org/https://doi.org/10.3390/jrfm19050317 in Nigerian Firms. International Journal of Education and Social Science

Marimuthu, F., & Abbana, S. (2023). Financing Of State-Owned Entities : Can Research, 8(3), 262–280. The Trade-Off Theory Explain the Debt Structure? International Journal https://doi.org/https://doi.org/10.37500/IJESSR.2025.8317 of Entrepreneurship and Sustainability Studies, 3(1). Sunardi, N., Husain, T., & Kadim, A. (2020). Determinants of Debt Policy a nd https://doi.org/https://doi.org/10.31098/ijeass.v3i1.1483 Company’s Performance. International Journal of Economics and

Ma’sum, M. A., Badjuri, A., Bagana, B. D., & Arisani, M. D. (2022). Business Administration, VIII(4), 204–213. Conservatisme Akuntansi dan Overconfidence CEO. Jurnal Bisnis Dan https://doi.org/10.35808/ijeba/580

Ekonomi, 29(2), 138–147. Tanjaya, F. L., & Santoso, E. B. (2020). Asosiasi Karakteristik CEO terhadap

Michiels, A., & Molly, V. (2017). Financing Decisions in Family Businesses: A Potensi Kesulitan Keuangan Perusahaan. Media Akuntansi Dan Review and Suggestions for Developing the Field. Family Business Perpajakan Indonesia, 1(2), 57–69.

Review, 30(4), 369–399. Wantriani, R., & Susanti, N. (2025). Analisis CEO Overconfidence Terhadap https://doi.org/https://doi.org/10.1177/0894486517736958 Financial Distress pada Perusahaan Produsen Minyak dan Gas Yang Mișu, N. B., & Madaleno, M. (2020). Assessment of Bankruptcy Risk of Large Terdaftar di London Stock Exchange Group Periode 2018-2022. Journal Companies: European Countries Evolution Analysis. Journal of Risk and of Accounting and Finance Management, 6(5), 2512–2522. Financial Management, 13(3), 1–28. https://doi.org/https://doi.org/10.38035/jafm.v6i5 https://doi.org/doi:10.3390/jrfm13030058 Xiao, L., Bai, M., Xiong, L., & Yang, L. (2021). Financial Slack and Inefficient

Muñoz-Bullón, F., Sanchez-Bueno, M. J., & Velasco, P. (2024). Exploring The Investment Decisions in China. Managerial and Decision Economics, Link Between Family Ownership and Leverage: A Mediating Pathway 42(4), 920–941. https://doi.org/10.1002/mde.3282

Through Socioemotional Wealth Objectives. Review of Managerial Zhen, H., Weiwei, G., & Liying, C. (2020). Does the External Environment Matter Science, 18, 3203–3252. for the Persistence of Firms Debt Policy? Finance Research Letters, https://doi.org/https://doi.org/10.1007/s11846-023-00713-1 32(127), 1–9. https://doi.org/10.1016/j.frl.2018.12.021

Ogachi, D., Ndege, R., Gaturu, P., & Zoltan, Z. (2020). Corporate Bankruptcy Prediction Model, a Special Focus on Listed Companies in Kenya.