Murhadi Managerial Overconfident 2017

MANAGERIAL OVERCONFIDENT AND

FIRMFINANCING DECISION: AN INDONESIAN CASE Werner R. Murhadi

Abstract

Purpose – This research aims to determine the effect of managerial overconfidence and firm characteristics on financing decision of a firm.

Design/methodology/approach – This research uses panel data to follow the panel model testing by using Common Effect (CE), Fixed Effect Model (FEM), and Random Effect Model (REM), to test the effect of managerial overconfidence and firm characteristic onfinancing decision of firms listed in Bursa Efek Indonesia in the period of 2006 – 2015.

Findings – Researcher founds: First, the higher the confidence of an executive, judged by the profile photo, the smaller the debt used by the firm; Second, the higher the past performance of a ratio, measured from the cash flow on operational activity to total asset, the debt used by the firm tends to decrease. Third, a higher education level of the executive tends to increase the usage of debt by the firm; Fourth, the past working experience ofa CEO will make him able to face many situationsby using the available information and likely to be unbiased. These abilities will formhis confidence, resulting in less usage of debt by the firm. Finally, gender does not have a significant effect on the size of debt in a firm.

Practical Implications – the finding indicates that behavioral factor, such as managerial overconfidence, can explain the reason of the usage of debt in a firm.

Originality/Value – the research that uses behavioral finance aspect to explain the financing decision in a firm is still relatively rare conducted in Indonesia.

Keywords: Financing decision, behavioral finance, managerial overconfidence, firm characteristics.

Paper Type – Research Paper

1. Introduction

Financing decision is one of the most important parts in a firm. Improper financing decision will result in an expensive cost of capital, followed by disapproval ofpotential projects that would have been beneficial to the firm. Current theories like Trade-Off theory (Miller,1977), Pecking Order theory (Myers, 1984; and Myers and Majluf, 1984), and Agency theory (Jensen and Meckling, 1976) are more focusing on the relationship between financing options and market instruments, industry

and the firm’s internal, such as tax, bankruptcy cost, and asymmetric information level in the firm. This research is done through a different perspective, which is through behavioral finance, specifically intertwined with management characteristics. Behavioral finance combines neoclassical economic theory with psychology insight and neuroscience to describe the explanation behind the deviation of the previous basic assumption, that is rational/efficient (Scheinert, 2014),done by individuals, firms, and markets. Individuals are no longer seen to always think rationally, but they are also affected by emotional factors and cognitive bias in taking decisions.

Malmendier, Tate, and Yan (2007) stated that characteristics of a firm’s management can be an explanatory factor in a firm’s decision to choose between financing alternatives. A firm,which is operated by management team with higher confidence (overconfident CEOs)believes that its management team will be able to generate cash flow and increase the firm’s value. An overconfident management, when having to use external financing, is most likely to utilize debt than issuing shares. Another research done by Fedyk (2014) defines that in the trade-off theory, rational CEOs would prefer debt financing or share issuance after considering the cost and benefit from each alternative. In the trade-off theory, management would choose an optimized financing, by taking tax saving and bankruptcy expense into consideration. However, this theory fails to explain the practical findings, which proves that firms often choose financing alternative that passes the optimal point. Kiong Ting et al (2016) then do a similar research,stating that there is an assumption of managers and financial industry subjects who tend to act rationally (Barros and da Silveira, 2009). On the other hand, psychology experts believe that human beings do not always think rationally. When human beings do not think rationally, their acts in taking decision are most likely to be overestimating or underestimating. Overestimation is highly relevant to a personal act

that is related to overconfidence (Wei et al., 2011). Li et al (2009) in Kiong Ting et al. (2016) explains that overconfidence is a miscalibration ofconfidence. Overconfidence people tend to overestimate their self-confidences, or underestimate variety of risks. Nofsinger (2003) stated that overconfidence will encourage managers to invest using more debts than doing many acquisitions.

There are different views on the effect of managerial overconfidence towards firm’s debt financing decision.Rechner and Dalton (1991) explained that overconfident managers tend to use more debts. Hambrick and Cannella (2004) made few decisions related to the implication of decision making by overconfident managers: (1) managers tend to invest more; (2) The investment is done by using debt; (3) Firm has bigger default risk. While Almeida et al. (2005) interviewed CFO and found that overconfident CFO tends to use more debts, particularly long term debt.

Malmendier and Tate (2005) showed different result, whereas overconfident managers choose to use internal funding first, then debt, and stock. This happens because managers overestimate their abilities to increase the firm’s value, therefore they also tend to overestimate the future cash inflow of a project. Abor (2007) supported the result from Malmendier and Tate (2005), that optimistic managers show a strong relevancy between debt utilization and deficit financing, compared to non-optimistic managers.

According to many references, an alternative is needed to explain phenomenon in financing election using management characteristics related to managerial confidence. This research will examine the effect of managerial overconfidence on firm’s financing decision. This research will use control variables from the research of Ernawati and Murhadi (2013), such as firm profitability, firm size, asset tangibility, and firm growth, which according to previous studies, they showed significant effect on the financing decision.

This researchfocuseson discussing the effect of management behaviors, particularly managerial overconfidence that will affect firm’s financing decision making. A confident management will believe in their abilities to generate cash and value to the firm, therefore, it tends to be bolder in taking risk by utilizing more debts. Control variables such as firm profitability, firm size, asset tangibility, and firm growth, will be taken into this research as these variables have been used in many studies as an influential factors to a firm’s financing decision. Based on the identification, a major research questionhas been developed: is managerial overconfidence affecting firm’s debt positive significance. From the major research question, minor research question using proxy from Managerial Overconfidence proxies, such as CEO profile photo in annual report, CEO level of education, CEO level of experience, CEO gender, and CEO past working performance have been developed. Furthermore, these are the detail of minor research questions:

1. Does Managerial Overconfidence that uses CEO profile photo as proxy have a positive effect on a firm debt financing policy? 2. Does Managerial Overconfidence that uses CEO level of

education have a positive effect on a firm debt financing policy? 3. Does Managerial Overconfidence that uses CEO level of

experience have a positive effect on a firm debt financing policy?

4. Does Managerial Overconfidence, that uses CEO gender, particularly man, have a positive effect on a firm debt financing policy?

5. Does Managerial Overconfidence, that uses CEO past working performance, have a positive effect on a firm debt financing policy?

2. Theories Discussion and Literature Review

Behavioral finance is a study that combining Financial Management and Psychology. Shefrin (2002) in Prasetyo (2009) explained that behavioral finance is an interaction from psychology with financial act and performance from all types of investor/decision maker categories. Shefrin suggested that investor/decision maker must be cautious in making mistake during the investment, for example, making judgment. Shefrin (2000) in Prasetyo (2009) stated that the mistake made by investor/decision maker might be advantageous to another investor/decision maker. Behavioral finance enriches the comprehension on economy by integrating human natural aspect into financial model.

Wendy (2012) stated that rationality assumption has begun taking critics despite the fact that it has been the main streamin explaining individual decision making. More economists interpret literature; conclude that market phenomenon is consistent with irrationality, which is the characteristic of individuals who take complicated decision. Several empirical studies also prove that not only the factor of ratio is taken into account while taking decision, but also the factor of emotion and behavior (KahnemanadTversky, 1979; Kahneman, 1992; Shefrin, 1985; Statman, 1999; Hirshleifer, 2001; and Ritter, 2003 in Wendy, 2012). The results of the studies show that besides of responding rationally/cognitively, individual is also able to respond emotionally while taking financial decision. This situation emerges 2 perspectives in financial theory, particularly in analyzing capital market phenomenon, such as rational and irrational perspectives.

Kiong Ting et al. (2016) did research on the effect of managerial overconfidence to the financing decision with the government ownership moderation. The research used 793 samples of companies listed on the main board of Kuala Lumpur Stock Exchange (KLSE) in 2002-2011 and

used OLS regression, FEM, and Tobit method. The dependent variable usedto measure debt is debt ratio (total asset divided by total asset) and as replacement to debt ratio, debt-to-equity ratio is used to test the robustness. As for the proxy of managerial overconfidence measurement, it is done using personal characteristics of the management, such as CEO’s profile photo in annual report, CEO’s education level, CEO’s level of experience, CEO’s gender, CEO’s business network, and CEO’s past working experience. The moderation variable in the paper is the government ownership percentage, while the control variable is the concentrated 5 biggest shareholders ownership, profitability, firm size, asset tangibility, investment in research and development, and firm growth. In the early model, a test without moderation is done by dividing into 2 subsets, they are government linked companies (GLC) and non-government linked companies (NGLC), while the second model was involving moderation. In the GLC sample, the result generated was a CEO managerial overconfidence is contributing a significant role in the financing decision-making. Besides that, the result also states that the higher the managerial overconfidence of a CEO, the lower is the debt utilized in the firm. As for the NGLC sample, it showsa contrary results to the GLC sample; a managerial overconfidence is proved not to significantly affect to the debt utilized by the firm. Therefore, the conclusion is managerial overconfidence encourages lower debt utilization, and this relation depends on the government ownership.

Fedyk (2014) did research on the effect of managerial characteristic, specifically managerial overconfidence, to a firm financing decision. The research is using Fortune 500 USA companies in one-decade period as the sample. The approach to this managerial overconfidence measurement research isusingthe situation when a CEO does a press conference or known as “CEO overconfidence through optimistic press coverage”. Managerial overconfidence is reflected from the managerial act

that prefers to raise debt financing to fund its investment. The purpose of this act is to allow management to have complete control to the firm and its financing decision, and is also supported by Ben-David et al. (2007) research; argued that overconfident managerialrecommends using debt to repurchase stock. For the dependent variable of financing decision, the research uses the percentage change in the number of shares outstanding measurement. Fedyk (2014) also used “strictly firm specific optimistic press percentage” as the control variable. The result of the research shows that Fedyk (2014) could not make a certain conclusion on the effect of an overconfident CEO to a firm financing decision.

The next research comes from Ben-David et al. (2007), studied the effect of managerial overconfidence to firm policy. The study is done using survey method with more than 6.500 CFO or Financial Vice President in USA for the sample. The control variables in the research are past market condition and financial performance. As for theconcernedfirm policies are investment policy, financing/capital structure policy, dividend policy, market timing activity, and executive compensation. The result shows that firm with overconfident CFO will have more investments and acquisitions, and the market reacts negatively to the acquisition activities. Ben David et al. (2007) also find a positive impact of managerial overconfidence and financing structure, in which a firm with overconfident CFO tends to have more debts, depends on long-term debt and low dividend payment. Finally, Ben-David et al. (2007) also found that compensation payment to executives in a firm with overconfident CFO is based on the performance.

A dissertation by Scheinert (2014) explained the effect of managerial optimism to a firm financing decision. The result generated is that managerial traits have a significant impact on various financing decision by the management. Since manager is the decision maker in a firm, naturally, manager individual characteristicswill affect the firm decision. In the classic financial literatures, they only focus on

fundamentals and rationality to explain financing decision, while behavioral traits show a significant contribution to understand many decision aspects in finance and accounting field. Therefore, behavioral bias must not, in general, be negatively viewed, but can be considered as a context that will affect decision-making process. Managerial optimism encourages taking a decision exposed to risk-taking, which might affect stakeholders negatively, but also might positively affect stakeholders on the other hand.

Fairchild (2007) studied the effect of managerial overconfidence on financing decision and firm value when investor is faced to hazard moral of a management team. The research is divided to 2 groups. The first group is for the manager who operates the firm in a low efficiency (managerial shrinking), in which he will use debt to motivate the business. Overconfident management is likely to overestimate its ability and underestimate the expense of financial distress. Therefore, in this condition, Fairchild (2007) predicted a positive effect of managerial overconfidence to debt. In the next group, manager has incentive to use free cash flow to invest in new projects that might decrease firm value (the free cash flow problem). In the second group, managerial confidence has a negative effect on debt. The results are that the first group (managerial shrinking) is able to prove managerial overconfidence positive affect on debt; meanwhile, the second group (the free cash flow problem) is proven to have a negative effect on debt. However, the effect of managerial overconfident to the firm value is still ambiguous.

3. Data and Methodology

Data source used in this research is secondary data generated from annual report published by firm and listed in Indonesia Stock Exchange (BEI). This research uses entire companies listed in Indonesia Stock Exchange (BEI), except financial industry due to different financing

structure. Research period is taken from 2006-2015. The sample characteristics are: (1) the firm is listed in Indonesia Stock Exchange (BEI) for the entire period, (2) does not have negative equity because a negative equity will result in an undefined debt to equity ratio.

As for the dependent variable, this research uses debt measured by long-term debt to total asset, and long-term debt to total equity for the robustness test.

Independent variables tested are managerial overconfidence, as employed in Kiong Ting et al. (2016), using personal characteristics of management, such as CEO profile photo in annual report, CEO level of education, CEO level of experience, CEO gender, and CEO past working performance. CEO profile photo uses nominal scale by 4 points if the CEO profile photo is presented in the annual report, at least, half of the whole page, 3 points if it is less than half of the page, 2 points if there is another profile photo aside the CEO in one page, and 1 point if there is no profile photo of the CEO (Schrand and Zechman, 2012). For the level of education, as stated by Rakhmayil and Yuce (2013), a higher level of education and working experience will positively affect debt usage. Level of education uses nominal scale by: 1 point if CEO is below bachelor graduate, 2 points if CEO is a bachelor graduate, 3 points if CEO is a master graduate and 4 points if CEO is a doctoral graduate. CEO’s experience will make CEO is capable in encountering many situations using existing information and tends to be unbiased, and will shape its confidence. This research applies dummy variable by 1 point if previously the CEO had once held position as chief officer (CEO, CFO, COO, CIO, and other equivalent positions) whether in current or different firm, and 0 if the other way around. In terms of gender, Huang and Kisgen (2012) explained that male executive tends to be more overconfident than woman. In relation to that finding, gender variable in this research will use 1 dummy variable for male CEO and 0 for female CEO (Abor, 2007). The next measurement for the independent

variable is CEO past working performance. A CEO good working performance encourages CEO confidence. This research measures CEO past working performance based on operational performance in the past. Past working performance proxy is measuring operating cash flow to total asset ratio (Balafas, and Florackis, 2014).

Control variables in this research are firm profitability, firm size, asset tangibility, and firm growth. Firm profitability will employ return on asset (R0A) ratio. Firm size will be measured by natural logarithm of total sales. Asset tangibility will be generated from fixed asset to total asset ratio. Finally, firm growth will be measured through the current year sales growth compared to the previous year.

As for the model to be tested is:

Where: PP is the profile photo for firmiat time t, pend stands for the level of education for firmi at time t, Gend is gender for firmIattime t, peng is the experience for firmi at time t, prof is the profitability for firmiat time t, KML is past working performance for firmi at time t, Tan is for tangibility of firmi at time t, Uk is the firm size for firmi at time t, and Gr stands for growth of firmi at time t.

Next, for the robustness test, we undertake by using second model as shown below:

This research undertakes data panel, followed by a series of panel model test, such as Common Effect (CE), Fixed Effect model (FEM), and

Random Effect Model (REM). Out of these 3 models, Chow and Haussman test will be used to choose one best method.

4. Empirical Results and Analysis

Sample used in this research that has met the criteria is 470 years of observation. On the first phase, we will do multicollinearity test between variables by undertaking Pearson correlation analysis as shown in table 1.

Table 1.Correlation Analysis Result

GENDER GROWTH PAST

WORKING EXPERIENCE

PEND. PENG. PROFIL

FOTO

PROFIT TAN. UK.

GENDER 1.000 0.032 0.065 0.016 0.024 (0.076) 0.036 0.158 0.162

GROWTH 0.032 1.000 0.054 0.151 (0.034) (0.055) 0.129 0.003 0.038

PAST_WORKING_ EXPERIENCE

0.065 0.054 1.000 0.232 0.180 0.112 0.573 0.064 0.434

EDUCATION 0.016 0.151 0.232 1.000 0.073 (0.051) 0.211 0.071 0.129

EXPERIENCE 0.024 (0.034) 0.180 0.073 1.000 0.017 0.202 0.021 0.111

PROFILE_PHOTO (0.076) (0.055) 0.112 (0.051) 0.017 1.000 (0.000) 0.090 0.180

PROFITABILITY 0.036 0.129 0.573 0.211 0.202 (0.000) 1.000 (0.170) 0.372

TANGIBILITY 0.158 0.003 0.064 0.071 0.021 0.090 (0.170) 1.000 (0.013

SIZE 0.162 0.038 0.434 0.129 0.111 0.180 0.372 (0.013) 1.000

As shown in table 1, it uses all variables with correlation coefficient less than 0.6 by making the correlation value to absolute, except for past working experience and profile photo. The next test is the variance test for inflation factor with the result of all variables are below cut-off 5, such as: Gender with VIF value of 1.074; growth with VIF value of 1.056; past working performance with VIF value of 1.730; education with VIF value of 1.102; experience with VIF value of 1.056; profile photo with VIF value of 1.078; profitability with VIF value of 1.711; tangibility with VIF value of 1.122; and size with VIF value of 1.344. Due to this result, it can be concluded that there is no linkage between independent variables, and no variable need to be removed from the research.

After seeing the correlation between independent variables, the result of the data processed must be analyzed through descriptive statistic as shown in table 2. From table 2, it is seen that the average debt to totalasset is less than 20%, and the firm debt to equity ratio is reaching the average of 60%.

Table 2 Descriptive Statistic

Means (Modus) Min. Max.

LTD_TA 0.1898 0.0001 0.8056

LTD_TE 0.5935 0.0002 16.9192

PROFILE_PHOTO (2) 1 4

EDUCATION (2) 1 4

EXPERIENCE (1) 0 1

GENDER (1) 0 1

PAST_WORKING_ EXPERIENCE

0.0824 -0.5392 0.7423

PROFITABILITY 0.0618 -0.7557 0.9660

SIZE 28.0635 21.1949 32.9378

TANGIBILITY 0.57911 0.1223 0.9945

GROWTH 0.1428 -1.4918 2.3491

The financial report shows that managerial overconfident reflected from the profile photo in financial report, therefore most of the executive profile photos are 2, which means there is another party beside the executive that also has his profile photo in the financial report. The other party is identified to be the commissioner. As from the education, most executives are bachelor graduates. While from the experience, most executives have been officiated as chief officers (CEO, CFO, COO, CIO, and other equivalents position) either at current firm or at previous companies. In terms of gender, most executives are male. The next managerial overconfident factor is related to CEO past working

performance. The average of past working performance, which is shown by the ability to generate cash flow from operational activity, is reaching the range of 8% to the total asset.

Furthermore, further discussion to the main model will be made. After applying Chow and Hausmann test to 3 models of data panel, such as CE, FEM, and REM, the Chow test generates significant result, where FEM gives more estimation than CE. After that, Haussman test is done to choose either REM or FEM is the best model. The chosen model to be interpreted is FEM.

Table 3

Inferential Statistic Result for Model 1

Variable CE FEM-1.1 FEM-1.2. REM

Beta t beta t Beta t beta t

PROFILE_PHOTO 0.0002 0.02 -0.0200 -2.86* -0.0199 -2.86* -0.0190 -2.78* EDUCATION -0.0122 -1.17 0.0220 1.84** 0.0220 1.84** 0.0155 1.39 EXPERIENCE -0.0321 -2.34* 0.0363 2.49* 0.0359 2.49* 0.0270 1.96** GENDER -0.0459 -1.46 -0.0091 -0.19 -0.0036 -0.08 PAST_WORKING_

PERFORMANCE

-0.1238 -1.77** -0.1668 -3.32* -0.1670 -3.33* -0.1664 -3.37*

PROFITABILITY -0.0682 -0.86 0.0866 1.54 0.0871 1.55 0.0803 1.45 SIZE 0.0162 4.30* -0.0129 -1.70** -0.0128 -1.69** -0.0004 -0.07 TANGIBILITY 0.2946 8.68* 0.0624 1.51 0.0621 1.50 0.1200 3.20* GROWTH 0.0289 1.41 0.0198 1.44 0.0198 1.44 0.0173 1.28

R Squared 0.1916 0.7573 0.7573 0.0767

Adjusted R Squared 0.1758 0.7251 0.7257 0.0587 F Statistics 12.1190* 23.4971* 23.9872* 4.2505*

Information: * Significance on α = 5%; ** significance onα = 10%

From the F test, we can see that FEM model 1 is significant, which means that altogether the independent variable is affecting the firm financing decision. In table 3, especially model 1 that uses FEM as seen from 5 measurements of managerial overconfidence, 4 proxies are found to be significant, such as profile photo, education, experience, and past working performance. This result implies that managerial overconfidence variables in the executive will determine a firm financing decision. Two of 5 managerial overconfidence approaches, such as profile photo and past working performance appear to be negative significance, while education and experience are positive significance, and gender appears to give no significance effect.

Table 3 shows that the result of profile photo is different from the hypotheses, where apparently, the higher the confidence of an executive, the lower the debt used. This result is consistence to the research done by Kiong-Ting et al. (2016), which means that the more confident the executive, the less is the debt used by the firm. Therefore, this result explains that overconfident executive chooses to utilize internal funding for its new projects in expectation to give additional value for the shareholders.

Meanwhile, education variable is found to be positive significance, which means that the higher the level of education, the higher the confidence of the executive will likely to raise the usage of debt. The confident executive will have high assurance that the new project invested is a right choice, which is why the executive is certain on its ability to pay-off the debt. Likewise to the working experience, it also shows a positive significance result. It appears that by having a working experience, a CEO will be able to encounter many situations by using existing information and tends to be unbiased, and this will form its confidence. CEO experience at its previous specific position (CEO, CFO, COO, CIO, and other equivalent positions) either at the current firm or the previous firm, will be useful in overcoming problems that might appear at new projects, so CEO tends to use debt financing. From table 3, we can see that gender has no effect on the firm financing decision. With the education and experience owned by CEO, and by focusing on the past working experience, the firm will be the main factor in shaping CEO confidence when it comes to choose whether to use debt or not. It is also presented in table 3, the second FEM model by removing gender variable that is not significant. By removing insignificant factor like gender, the result of the test showsconsistency on both sides; direction and significance.

This research also does robustness test by using long term debt to total equity as dependent variable. The result of this test can be seen on table 4. FEM 2.1 model is a model that uses all independent variables as used in FEM 1 on table 3. The generated result from the test is education, experience, and past working experience are proven to be affecting, while gender is consistently showing insignificant effect to a firm debt usage decision. However, there has

been a shift, where profile photo that is previously significant, has now become insignificant. The test is said to be robust because 3 out of 5 managerial overconfidence measurements, have direction and significance that suit the main model.

Table4

Inferential Statistic Result for Model 2

Variable FEM 2.1. FEM 2.2. FEM2.3

beta T beta t beta t

PROFIL_PHOTO -0.1322 -1.54 -0.1317 -1.53

EDUCATION 0.3311 2.26* 0.3313 2.26* 0.3387 2.31*

EXPERIENCE 0.4542 2.53* 0.4474 2.52* 0.4622 2.61*

GENDER -0.1606 -0.27

PAST_WORKING_ EXPERIENCE

-2.6065 -4.23* -2.6101 -4.24* -2.6445 -4.29* PROFITABILITY 2.0150 2.93* 2.0235 2.95* 2.0790 3.03* SIZE -0.2914 -3.12* -0.2898 -3.11* -0.3129 -3.40* TANGIBILITY -0.7761 -1.53 -0.7817 -1.54 -0.8169 -1.61

GROWTH 0.2773 1.64 0.2762 1.64 0.2835 1.68**

R Squared 0.3777 0.3776 0.3741

Adjusted R Squared 0.2951 0.2967 0.2944

F Statistics 4.5704* 4.6640* 4.6921*

Information: * Significant on α = 5%; ** significant onα = 10%

In table 4, a test is also done to remove insignificant factors and those are gender in model FEM 2.2.; also, gender and profile photo in model FEM 2.3. The result shows consistency in direction and significance of 3 variables, such as education, experience, and past working experience to financing policy in a firm. As for the control variable in model FEM 1 and model 2, the result is that firm size has a negative significant result to financing. This result means that the bigger the firm size, it tends to not use much debt. It is because a big size firm tends to dominate market, both service or product market, so the firm earns higher profit. Firm with a high profit like Unilever Indonesia tends to avoid the option of using debt in its financing policy. For the other control variables, those are tangibility and growth, a consistent result of being insignificant either on the first and second model is found. Meanwhile, for profitability, there has been a significant change, which on the

first model, it is proven to be insignificant, yet on the second model, it turns out to be negative significant.

5. Conclusion

The result generated from this research shows 4 proxies out of 5 managerial overconfidence measurements whichare proven to be significant, they are profile photos, education, experience, and past working performance. This result means that managerial overconfidence variable in an executive characteristic will determine firm financing decision. Out of 5 managerial confidence approaches, 2 variables, profile photo and past working performance, are showing negative significant results, while education and experience show positive significant results, and gender does not have significant impact. Managerial overconfidence in this research only based on the data presented in the firm annual report. In the future, a better questionnaire method or interview is expected to generate a better result to reflect managerial overconfidence.

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Wei, J., Min, X. dan Jiaxing, Y., 2011, Managerial overconfidence and debt maturity structure of firms: analysis based on China’s listed companies,

Wendy, 2012, Pembentukan Perilaku Rasional Dan Irasional Dalam Pengambilan Keputusan Investasi Berisiko: Implikasi Teori Coping Dalam Model Adaptasi Pemodal Pada Eksperimen Laboratori, Disertasi, Universitas Gadjah Mada.

performance. The average of past working performance, which is shown by the ability to generate cash flow from operational activity, is reaching the range of 8% to the total asset.

Furthermore, further discussion to the main model will be made. After applying Chow and Hausmann test to 3 models of data panel, such as CE, FEM, and REM, the Chow test generates significant result, where FEM gives more estimation than CE. After that, Haussman test is done to choose either REM or FEM is the best model. The chosen model to be interpreted is FEM.

Table 3

Inferential Statistic Result for Model 1

Variable CE FEM-1.1 FEM-1.2. REM

Beta t beta t Beta t beta t

PROFILE_PHOTO 0.0002 0.02 -0.0200 -2.86* -0.0199 -2.86* -0.0190 -2.78*

EDUCATION -0.0122 -1.17 0.0220 1.84** 0.0220 1.84** 0.0155 1.39

EXPERIENCE -0.0321 -2.34* 0.0363 2.49* 0.0359 2.49* 0.0270 1.96**

GENDER -0.0459 -1.46 -0.0091 -0.19 -0.0036 -0.08

PAST_WORKING_ PERFORMANCE

-0.1238 -1.77** -0.1668 -3.32* -0.1670 -3.33* -0.1664 -3.37*

PROFITABILITY -0.0682 -0.86 0.0866 1.54 0.0871 1.55 0.0803 1.45

SIZE 0.0162 4.30* -0.0129 -1.70** -0.0128 -1.69** -0.0004 -0.07

TANGIBILITY 0.2946 8.68* 0.0624 1.51 0.0621 1.50 0.1200 3.20*

GROWTH 0.0289 1.41 0.0198 1.44 0.0198 1.44 0.0173 1.28

R Squared 0.1916 0.7573 0.7573 0.0767

Adjusted R Squared 0.1758 0.7251 0.7257 0.0587

F Statistics 12.1190* 23.4971* 23.9872* 4.2505*

Information: * Significance on α = 5%; ** significance onα = 10%

From the F test, we can see that FEM model 1 is significant, which means that altogether the independent variable is affecting the firm financing decision. In table 3, especially model 1 that uses FEM as seen from 5 measurements of managerial overconfidence, 4 proxies are found to be significant, such as profile photo, education, experience, and past working performance. This result implies that managerial overconfidence variables in the executive will determine a firm financing decision. Two of 5 managerial overconfidence approaches, such as profile photo and past working performance appear to be negative significance, while education and experience are positive significance, and gender appears to give no significance effect.

Table 3 shows that the result of profile photo is different from the hypotheses, where apparently, the higher the confidence of an executive, the lower the debt used. This result is consistence to the research done by Kiong-Ting et al. (2016), which means that the more confident the executive, the less is the debt used by the firm. Therefore, this result explains that overconfident executive chooses to utilize internal funding for its new projects in expectation to give additional value for the shareholders.

Meanwhile, education variable is found to be positive significance, which means that the higher the level of education, the higher the confidence of the executive will likely to raise the usage of debt. The confident executive will have high assurance that the new project invested is a right choice, which is why the executive is certain on its ability to pay-off the debt. Likewise to the working experience, it also shows a positive significance result. It appears that by having a working experience, a CEO will be able to encounter many situations by using existing information and tends to be unbiased, and this will form its confidence. CEO experience at its previous specific position (CEO, CFO, COO, CIO, and other equivalent positions) either at the current firm or the previous firm, will be useful in overcoming problems that might appear at new projects, so CEO tends to use debt financing. From table 3, we can see that gender has no effect on the firm financing decision. With the education and experience owned by CEO, and by focusing on the past working experience, the firm will be the main factor in shaping CEO confidence when it comes to choose whether to use debt or not. It is also presented in table 3, the second FEM model by removing gender variable that is not significant. By removing insignificant factor like gender, the result of the test showsconsistency on both sides; direction and significance.

This research also does robustness test by using long term debt to total equity as dependent variable. The result of this test can be seen on table 4. FEM 2.1 model is a model that uses all independent variables as used in FEM 1 on table 3. The generated result from the test is education, experience, and past working experience are proven to be affecting, while gender is consistently showing insignificant effect to a firm debt usage decision. However, there has

been a shift, where profile photo that is previously significant, has now become insignificant. The test is said to be robust because 3 out of 5 managerial overconfidence measurements, have direction and significance that suit the main model.

Table4

Inferential Statistic Result for Model 2

Variable FEM 2.1. FEM 2.2. FEM2.3

beta T beta t beta t

PROFIL_PHOTO -0.1322 -1.54 -0.1317 -1.53

EDUCATION 0.3311 2.26* 0.3313 2.26* 0.3387 2.31*

EXPERIENCE 0.4542 2.53* 0.4474 2.52* 0.4622 2.61*

GENDER -0.1606 -0.27

PAST_WORKING_ EXPERIENCE

-2.6065 -4.23* -2.6101 -4.24* -2.6445 -4.29*

PROFITABILITY 2.0150 2.93* 2.0235 2.95* 2.0790 3.03*

SIZE -0.2914 -3.12* -0.2898 -3.11* -0.3129 -3.40*

TANGIBILITY -0.7761 -1.53 -0.7817 -1.54 -0.8169 -1.61

GROWTH 0.2773 1.64 0.2762 1.64 0.2835 1.68**

R Squared 0.3777 0.3776 0.3741

Adjusted R Squared 0.2951 0.2967 0.2944

F Statistics 4.5704* 4.6640* 4.6921*

Information: * Significant on α = 5%; ** significant onα = 10%

In table 4, a test is also done to remove insignificant factors and those are gender in model FEM 2.2.; also, gender and profile photo in model FEM 2.3. The result shows consistency in direction and significance of 3 variables, such as education, experience, and past working experience to financing policy in a firm. As for the control variable in model FEM 1 and model 2, the result is that firm size has a negative significant result to financing. This result means that the bigger the firm size, it tends to not use much debt. It is because a big size firm tends to dominate market, both service or product market, so the firm earns higher profit. Firm with a high profit like Unilever Indonesia tends to avoid the option of using debt in its financing policy. For the other control variables, those are tangibility and growth, a consistent result of being insignificant either on the first and second model is found. Meanwhile, for profitability, there has been a significant change, which on the

first model, it is proven to be insignificant, yet on the second model, it turns out to be negative significant.

5. Conclusion

The result generated from this research shows 4 proxies out of 5 managerial overconfidence measurements whichare proven to be significant, they are profile photos, education, experience, and past working performance. This result means that managerial overconfidence variable in an executive characteristic will determine firm financing decision. Out of 5 managerial confidence approaches, 2 variables, profile photo and past working performance, are showing negative significant results, while education and experience show positive significant results, and gender does not have significant impact. Managerial overconfidence in this research only based on the data presented in the firm annual report. In the future, a better questionnaire method or interview is expected to generate a better result to reflect managerial overconfidence.

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