Trade-Off Theory or Pecking Order Theory With a State-Ownership Structure- The Vietnam Case

7/25/2019 Trade-Off Theory or Pecking Order Theory With a State-Ownership Structure- The Vietnam Case

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International Review of Business Research Papers

Vol. 11. No. 1. March 2015 Issue. Pp. 114132

Trade-Off Theory or Pecking Order Theory with a State-Ownership Structure: The Vietnam Case

Sbastien. Dereeper1and Quoc Dat. Trinh2

The process firms use to choose their capital structures is explainedby different corporate finance theories in which trade-off and peckingorder are the two most popular hypotheses. Testing these twomodels will help to determine whether a target debt ratio exists, andif so, how rapidly firms adjust their current leverage levels to matchthis target level. The findings in this paper determined that thepecking order theory might not be applied in Vietnam when internalfunds and new equity issuance are independent with the leveragelevel. In contrast, our empirical results proved that the long-run targetdebt ratio does exist in the Vietnamese market. The partial-adjustment model has shown that both private firms and state-owned

firms rapidly adjust to their optimal levels of debt. However, the stateownership structure does not affect the amount of debt taken duringthe year by the firms.

Field of Research:capital structure, state-owned firms, private firms, speed adjustment.

1. Introduction

Although being published in stock exchange is an efficient way to raise middle and long-term funds, firms still continue borrowing from financial intermediaries such as banks orfinancial companies for many reasons. The conflicts among shareholders and managers of

the firms might be one of those reasons. When raising funds from the stock market, firmsmanagers need to report business activities to many other new shareholders. This meansthey are loosening their control to the firms and they need to disclose more insideinformation to public. This is not what managers want because Jensen and Meckling (1976),with the concept of separation of ownership and control, indicated that managers can bemore interested in transferring firms resources into their personal benefits instead ofspending efforts on leading the firms. The decisions made by managers will not totallymaximize firms value as it would be. In contrast, although shareholders do not directlycontrol and manage firms activities, they do own the firm and receive a fraction of the gain.Shareholders will need to pay some costs to the managers and establish appropriatemonitoring solutions with the hope that the managers will act for the best benefits of

shareholders.

However, raising funds from banking system also faces many difficulties. These might bethe costs of bankruptcy if firms are out of payment, or other accurate borrowing conditionsissued by the banks that firms must satisfy. Generally, banks approve firms loans based ontheir own appraisal processes. However, in emerging market, where the effect of the stateon financial market is quite obviously, the decisions of banking system on how to give loansto firms might be remarkably affected by the governments policy.

1 Dr. Sbastien. Dereeper, Professeur des Universits, Universit de Lille 2 - SKEMA Business school,

ECCCS research center,[email protected];2Quoc Dat, Trinh, Universit de Lille 2 - SKEMA Business school, ECCCS research center,[email protected];
mailto:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]


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La Porta et al. (2002), Dinc (2005) suggested that profit might not be considered as the toppriority concern rather than serving primarily for political purposes of state-owned banks. InChina, Liu et al (2011) found that the influence of government intervention to financingbehaviors is significant and they suggested that state-owned firms would have the chanceto borrow more while non-stated firms would meet difficulty in borrowing.

The economic reform (Doi Moi) policy, started from 1986, has created a great change overthe whole economy of Vietnam from the centrally planned economy into the market orientedeconomy. Along with the market mechanisms, applied since Doi Moi, an equitization ofstate-owned enterprises was implemented in 1990 and dramatically promoted from 1996. Inthe year of 2000, Ho Chi Minh stock exchange was established for the first time in Vietnam,and five years later, in 2005, Ha Noi stock exchange was established with slightly lowerrequirements on equity scale to listed firms. Those events were the steps that thegovernment executed to bring more efficient and transparent management mechanisms toall enterprises. However, not all the firms are fully equitized. Government still holdsownership control in different specific and important-to-nation industries such as energy,

exploitation of natural resources, agriculture and forestry. That leads to the existence ofpartly-equitized firms even in the stock market. Therefore, examining the intervention ofVietnamese government on how firms support their financial needs is necessary.

A study on the effect of state ownership to capital structure of small and medium unlistedenterprises in Vietnam was conducted by Nguyen (2006). By considering 558 small andmedium unlisted firms, from 1998 to 2001, Nguyen provided a consensus with Liu et al.(2011) for China case by showing that state-owned small and medium enterprises havemore advantages in accessing bank loans than non state-owned enterprises. Another study,two years later, in 2008, conducted by Nahum Biger et al., confirmed the relationshipbetween firms characteristics and capital structure in Vietnam. The leverage ratio is

positively related to firm size, growth opportunities and managerial ownership but it isnegatively correlated with non-debt tax shield, fixed assets and profitability. In 2012, Okudaand Nhung, investigated the opaque relationship between state-owned firms andgovernment banks through an empirical analysis of a panel data sample from 2006 to 2009.These two authors stated that agency cost theory clearly explains the mechanism of debtchoices for enterprises in Vietnam. Companies prefer to use more debt when managerialownership ratio is high, and vice versa, lower level of managerial ownership would comealong with lower level of debt. Okuda and Nhung also found similar result with Nguyen(2006) by suggesting that state-owned companies in average have higher debt ratio thanprivate companies in both Ho Chi Minh and Hanoi stock market.

Although the relationship between government control and leverage ratio of firms in Vietnamhas been studied by Nguyen (2006), Nahum Biger et al. (2008), Okuda and Nhung (2012),an empirical test for the application of the two classical models, tradeoff theory or peckingorder theory, the Vietnam case, has not been precisely conducted. In addition, theconfirmation of whether an optimal level of debt exists for Vietnamese firms is questionable.And if an optimal level of leverage exits, at which speed the firms will adjust current debtlevel toward target debt level is also to be concerned. Our study aims to provide a clearexplanation for these issues and together with other researches; we hope our paper willcontribute to clarify the effect of government ownership on firms choices of capital structurein Vietnam; and answer the question of at which speed firms will adjust their borrowingbehaviors toward the optimal choices to maximize the firm value.


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The paper is organized as follows. The first section is Introduction which aims to set up theidea of the paper and show how this study is important to Vietnam. The second section isLiterature Review. This section provides a brief summary of what other studies havesuggested about the capital structure theories, both in developed and developing countries.Section two also reviews the relationship between ownership and debt ratio. Moreover,

section two states three hypotheses which are going to be tested in the paper. The thirdsection specifies how regression model was built to conduct an empirical test for threehypotheses stated in section two. Section four explains the variables and shows how thedata were collected. Section five and section six provide our analysis results on theapplication of tradeoff theory and pecking order theory in Vietnam market, respectively.Final section is conclusion and areas for further research.

2. Literature Review

Since the study of Miller and Modigliani (MM) in June 1958, capital structure theory hasbeen continued studying properly. The trade-off theory, which rejects the irrelevance

preposition by considering imperfect and friction capital market, suggests that a firm shouldmaximize its value by balancing the costs and benefits of borrowing debts. While costs ofdebts are majored as the financial bankrupt cost or distress cost when firms usedextravagant debts and might not be able to meet the deadline of interest and principalpayments, the most significant gain of debt is identified by the debt-tax shield throughinterest deduction. The optimal debt level is considered as the intersection betweenmarginal costs and marginal benefits of using more debts (Myers, 1984). Therefore, statictrade-off theory recommends that a firm should substitute between equity and debt till itreaches the target ratio to maximize its value. However, in a dynamic world, firm itselfchanges overtime. The dynamic tradeoff theory states that optimal debt ratio of the firm isadjusted by the change of exogenous and endogenous factors.

In contrast, the pecking order theory, which considers the asymmetric informationassumption, predicts that no optimal leverage level is preferred. In fact, firms prefer to useinternal funds to finance for their capital demand before borrowing debts or issuing stock.The main assumption of the theory, asymmetric information, indicates the costs of adverseselection. This predicts that firms owners (insiders) normally have more information of the firms than investors (outsiders). Because of that, if firms issue equity to finance for newprojects, the market might consider those projects as ineffective or high risk projects.Consequently, equity would be underpriced. New projects are going to be rejected eventhey have positive NPV. Leland and Pyle (1977) stated that it could be a signal of low-returnbusiness results if firms decide to sell equity to the outside investors and vice versa. Inaddition, management purpose is also another reason that firms are not willing to issue newstock to call for capital. Kenny Bell and Ed Vos (2009), concluded if given theunconstrained choice between external debt and internal funds, SMEs will, in general,choose not to utilise debt due to the preference for independence, control and financialfreedom. Consequently, the pecking order, firstly, starts with internal finance (usingretained earnings and adapting target dividend payout ratio to investment opportunities),then continues with safe securities such as debt and convertible bonds if internal fundsprovide insufficiently. Equity is only chosen as the last resort.

Given the importance of these two theories in capital structure, several empirical tests have

been conducted to examine the application of these theories in practice. The authors whoare supported for perking order theory, such as Shyam-Sunder and Myers (1999), by testing


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a sample of 157 firms in US, has concluded that pecking order theory provides a good first-order approximation of firm financing behaviors. They concluded that within their sampleand model of testing, the basic pecking order theory explains actual debt ratio much betterin time-serial variance than static trade-off theory. Graham and Harvey (2001) figured outthat the marginal benefits of tax shield seem to be far bigger than the marginal costs of

bankruptcy for almost all the firms. In this case, firms should use more debts (increaseleverage) because they were under-leveraged. Both pecking order theory and trade-offtheory are supported at a given level but not really clear when little evidences are significantfor the choices of debts based on asset substitutions, asymmetric information, transactioncosts and personal taxes. However, J.Qiu and F.Smith (2007), predicted that pecking ordertheory might not be the first-order if sample difference and nonlinearity are taken intoaccount.

For the trade-off theory, the relation between firms features and leverage has been testedwidely among researchers. One of those features is ownership structure. Interestingrelations have been found. Brailsford et al. (2002) figured out that there exists a

demonstration of an association between capital structure and ownership structure.Particularly, they found a positive relationship between external block-holders andleverage, a curvilinear relationship between the level of managerial share ownership andleverage. Low level of managerial ownership will create a fall in agency conflicts, and thus,bring a higher level of debt in capital structure.

For emerging market such as China and Vietnam, the presence of government on firmsownership is remarkable. Liu, Tian and Wang (2011) examined a case study with thesample of over 1000 firms in both state-owned and non state-owned enterprises (SOEs andnon SOEs respectively) in China. They found that SOEs use more debts than non SOEsand financial behaviors of SOEs are influenced more by the government; whereas non

SOEs are more market-oriented. Jiang and Zeng (2010) also considered the role of stateintervention on debt level of all the listed firms in China from 2000 to 2006. They found thatregarding short-term loans, listed state-owned firms received a better policy of appraisalfrom the state-owned banks than private listed firms. In addition, as mentioned inIntroduction section, Nguyen (2006) and Okuda and Nhung (2012) suggested state-ownedcompanies in average have higher debt ratio than private companies in Vietnam. Therefore,the first hypothesis tested in the paper is: state-owned listed firms use more debt or havehigher leverage ratio than private listed firms.

In a different study, considering 79 listed firms, Fauzi (2012) tried to investigate theapplication of trade-off theory and pecking order theory in New Zealand. He found that

tradeoff theory is more appropriately explained for New Zealand listed firms. However, Qiuand La (2010) using unbalanced panel data of 367 firms for the period of 15 years,suggested that pecking order theory is applied for the Australia case. Bruslerie and Latrous(2007) conducted a detail empirical test on the relationship between ownership structureand debt leverage. With a sample of 112 listed firms on the French stock market, over theperiod from 1998 to 2009, they found a U-shape relationship between shareholdersownership and leverage. Controlling managers firstly at the low level of ownership prefer touse more debt to resist the attempted acquisition (takeovers) from outsiders. However,when the distress costs increases along with the higher level of debt and when the level ofownership reaches a certain point, controlling shareholders converge into using otherresources to support for business activities rather than debts. These studies bring us thesecond hypothesis to test: there exists an optimal level of debt for each firm in accordance


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with its characteristics. This hypothesis aims to prove the application of trade-off theory inVietnam.

Other authors used firms characteristics to determine target leverage and considered thespeed that a firm would adjust its leverage level toward the optimum. Leary and Roberts

(2004) concluded that firms, in the presence of adjustment costs, tend to partly adjust theirdebt ratios toward the optimal leverage level. Flannery and Rangan (2005), using a hugeUS dataset from 1965 to 2001, stated the existence of target debt level and firms partiallymoved toward the optimal debt level by the rate of 32% of the gap between current andtarget debt ratio each year. From that, we continue to test the third hypothesis: a firmcontinuously adjusts its leverage level toward the optimal level for both state-owned andprivate listed firm.

3. Regression Model Specification

The paper considers the market debt ratio as total interest-bearing borrowings to the sum of

interest-bearing debts and market value of outstanding common shares.

(1)

The market debt ratio (MDR) is conducted based on the ideas of Flannery and Rangan(2005) to consider the market capital capacity of the firm. In which, is defined asinterest-bearing debt of firm i at time t while S i,t indicates the number of common sharesoutstanding of firm i. Pi,t denotes the price per share of stock i at time t.

The tradeoff theory states that target leverage ratio might differ overtime and across firms

following firms characteristics. And there always exists an optimal level of debt ratio, whichis specified by the following form:

MDR*i,t+1= Xi,t (2)

Where MDR*i,t is the desired market debt ratio, is coefficient vector, and Xi,t is the vectorset of firms characteristics. The trade-off theory suggests that # 0 and the variation inMDR*i,t+1should be non zero.

Firms would shift their leverage ratios forward the target ratio immediately in perfect andfrictionless market (there are no costs of transaction and adjustment). However, in an

imperfect world, immediate movement of debt ratio toward the desired ratio might beprevented. Firms intend to adjust their leverages toward the optimal leverage level butpartially. Following the ideas of Rangan and Flannery, we construct a standard partialadjustment model as follows:

( ) (3)

In which, is the speed adjustment toward optimal leverage level of firm i at time t.Substitute equation (2) into equation (3) we have the standard model which is used to testthe speed adjustment toward optimal level mentioned by the tradeoff theory.

(4)


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Equation (4) will be used as the core specification for the paper. Because pecking ordertheory mainly refers to internal factors inside firms; hence, while using market debt ratio intesting trade-off theory, we are going to use book debt ratio (total of short term and longterm interest-bearing debt to total assets) in testing pecking order theory regression instead.Pecking order theory implies that firms financing deficit is one of the most important

explanatory variables to the choice of capital funding. Due to adverse selection, firms intendto balance the need of dividend payment, new investment and working capital by internalresources before borrowing debt.

Table 2, page 229, Frank and Goyal (2003) mentioned a firms financing deficit (FINDEF),which was defined as the ratio of sum of (dividend payments + investment +change inworking capitalinternal CASHFLOW)/total assets. We will use this definition of FINDEF inour regression model. Therefore, replacing the book debt ratio for market debt ratio andadding FINDEF (financing deficit) as an explanatory variable into equation (4), we have thepecking order behavior testing specification as follows:

(5)

The equation (5) implies that a firms financing deficit clearly explains current changes in itsbook debt ratio. Because BDRi,t+1 = BDRi,t+1 - BDRi,t, substitute into (5) we will have:

BDRi,t+1= Xi,t+ (1- ) BDRi,t+FINDEFi,t+1 + i,t+1 (6)

Running regression by equation (6), if financial deficits variable (FINDEF) is foundstatistically significant to book debt ratio, pecking order theory is suggested as applicable inVietnamese market. However, if FINDEF is significant but it makes no differences/changes

on the coefficient of the other explanatory variables used in equation (4), we can concludethat pecking order theory is just a subset of trade-off theory, or on the other hand, trade-offtheory is a generalized model of pecking order theory.

4. Data and Variable Explantations

Generally in Vietnam, only listed companies are forced to publish their audited financialreports, business performances and activities while unlisted firms are free to this obligation.In addition, contrary to the information transparency of listed companies, data collected fromunlisted companies might be manipulated for private purposes of companies owners.

Therefore, to entrust the empirical results, the paper only focused on the database fromcompanies listed in Vietnam stock exchange.

In addition, we tried to ensure the database used in the paper is sufficient in term of timeperiod and number of observations. Hence, we considered all the listed firms in Vietnamstock market that we could access their data within the period of at least four years.Consequently, from those reasons, data in this paper were collected from over 300 hundredlisted companies categorized by 15 industries (classified by Vietnam Standard IndustrialClassification 2007); in Hanoi and Ho Chi Minh stock exchange, from 2005 to 2011. Weeliminated all the firms which have been listed in the stock exchange after 2007. In addition,to guarantee our database is consistent in term of demand side only, we ignored all the

financial companies and banks listed in the stock exchange because they are normallyconsidered as debt suppliers.


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We re-defined industry variable down into 5 sectors to make the empirical analysis becomemore precise. Industry variable included: Agriculture, forestry and fishing; Energyexploitation and distribution; Manufacturing; Construction and Transportation; and Otherindustries. However, some variables contained missing observations and we decided not todrop any of those variables. Thus, an unbalanced panel dataset was observed and used for

the regression test with total of over 1600 firm-year observations.

Because, the paper aims to test three hypotheses mentioned in Section I, we divided ourdata into two subsets, state-owned firms and private firms. Based on the state proportion infirms ownership structure, we defined a state-owned firm as a firm with at least 36 percentof equity belonging to the government, and vice versa, a firm with less than 36% ofgovernment control was considered as non state-owned (or private) firm. We chose 36% ofequity ownership because this percentage was legally regulated as the minimumrequirement for shareholders to have the right of veto, i.e., the right or the power to rejectany business proposal given by other shareholders. Moreover, 36% of registered capitalowned by state normally guarantees that government will have two members in the Board of

Directors, which allows government increases its direct control over the firms regularactivities and strategies. We did not use the normal rate 50% of state ownership to split oursample because this percentage leads to a huge unequal subset of our data.

The determinants of capital structure were mainly selected as previous papers have done.Those factors appeared frequently in the literature review of Fama and French (2001),Hovakimian (2003) and Flannery and Ranga (2006). Two other factors added by us wereFIRM-AGE and FIRM-CASH at the fiscal year end. Proxies and expectations of thosefactors are as followsi:

MDR: This variable stands for market debt ratio. It is defined as total debt (short-term debts

plus long-term debts) to the sum of total debt and a multiple of outstanding shares and stockprice.

BDR: this variable stands for book debt ratio of the firm. It is defined as the ratio of totaldebts (short-term plus long-term interest bearing debts) to total assets. Generally, BDR issmaller than MDR in our study.

LN_TA: this is the logarithm of total assets. It shows firm size or business scale of firms.Blackwell and Kidwell, 1988, with the flotation-costs assumption, considered that largerfirms preferred to use more debts than smaller ones in order to make economies of scale. Inaddition, larger firms may have lower asset volatility and they might have more power to

access debt supply market.

EBIT_TA: Earning before interest and tax to total assets. This factor indicates the ability offirms on paying loans. EBIT_TA also shows how the profitability affects debt borrowingbehaviors. It is expected to be positively correlated to the leverage level. However, on theother hand, because of high retained earnings, firms might borrow less debt to reduce thebankruptcy risks and protect their profitabilitys proxy. Therefore, a firm with high EBIT couldprefer to operate with both higher and lower portion of interest-bearing debt.

MB:Market to book ratio of assets. Following the asymmetric information assumption, firmswith high market to book ratio (MB) are considered as having brightly prospective growth.Therefore, those firms will try to keep their debt ratio low and try to protect these


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advantages by limiting the leverage level. The market timing theory also predicts lower levelof debt for firms with high market value of stock price.

DEP_TA:This is the ratio of depreciation to total asset of the firm. High depreciation leadsto low accounting profit but high CASH capacity. Therefore, firms with high depreciation

may have more cash and need less debt from borrowing activities compared to firms withlow depreciation.

FIRM_AGE: Traditional and long historical firms might be well-known with financialintermediary system. They can borrow with ease, and consequently, firms with long historymight be able to remain high leverage ratio to receive the benefits of tax deduction.However, on the other hand, long traditional firms may also have advantages of using thenon-interest bearing debt from late payment policies from their suppliers, which lead to alow level of debt.

FA_TA:This stands for the ratio of fixed asset to total assets. Firms with high proportion of

fixed assets might refer to have high production capacity. As a result, those firms mightneed more debts to support for their activities. That means a positive relationship betweenFA_TA and leverage ratio is expected.

CASH:Is the beginning CASH in the balance sheet of financial report. This variable is onlyused when the paper tests the existence of pecking order theory. Because we believeCASH policies have a strong effect on the FINDEF, the main explanatory variable in theempirical test of pecking order theory, and the behavior of debts.

INDU:Is defined for Industry classification and we encoded 5 industries as from 1 to 5.

FINDEF:Denoted as financing deficit. This ratio is defined as the ratio of a sum of (dividendpayments + investment + change in working capital internal cash-flow) to total assets.This ratio is assumed to wipe out all other variables significant effect. If this ratio issignificant and creates remarkable changes in other variables in equation (5), it isconsidered as an obvious signal for the existence of the pecking order theory in Vietnamesemarket.

The following table briefly specifies statistic summary of our database used in the paper:


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Table 1: Summary Statistics of the data

Variable Obs Mean Std. Dev. Min Max

YEAR 1654 2008.710 1.671 2005 2011

INDU 1654 3.438 1.440 1.000 5.000

MDR 1654 0.299 0.283 0.000 0.900

BDR 1653 0.224 0.208 0.000 0.901

FINDEF 1574 -0.039 0.224 -1.181 1.834

CASH 1568 10.196 0.774 7.330 12.570

LNTA 1654 26.536 1.436 23.220 31.201

EBIT_TA 1654 0.066 0.102 -0.901 0.609

DEP_TA 1608 0.037 0.054 -0.650 0.750

FA_TA 1654 0.306 0.210 0.001 0.976

FIRM_AGE 1654 20.826 12.752 5.000 67.000

MB 1654 33.426 39.391 0.900 560.000

Noted: Variables are described in the description above.

In average, the market debt ratio differs from book debt ratio an amount of 0.07 and theyboth range from 0 to over 0.9 percent. This shows our data cover a wide range from non-leverage to heavy leverage-bearing firms. In fact, MDRs in some cases equaled to zero,because, some firms have recently joined the market and they had no demand (or hard toaccess) for long-term debt for some first years, whereas at some moments, MDRs of somecompanies in construction industry were close to the value of 1 because at that time, theprice of outstanding shares decreased dramatically and the number of outstanding shareswas small too. Particularly, the maximum MDR is approximated to 1. Book debt ratio alsofollows the trend of MDR. Values of BDR fluctuate from 0 to 0.9. The book debt ratio whichapproximates 90% reflects the fact that firm heavily depended on outside resources and itwas in danger of bankruptcy. Beside that, average debt levels for MDR and BDR are around0.29 and 0.22, respectively. This guarantees the sufficiency of our sample, a great range ofleverage ratio from different industries but with reasonable mean.

Data of other variables also present gaps among firms. We considered from very young firmwhich was lately established within 5 years to very traditional and long-lasted history firmwhich was operated over 60 years ago. With the wide set of data, we expected that ourempirical results could be applied to explain for financial behavior of all firm types. However,some observations were abnormally far away from most of other observations as runningfirm-level empirical analysis, outlier error was another issue that we considered. A paper

written by Ghosh and Vogt, in Joint Statistical Meeting of American Statistical Association,2012, questioned on how small of the tail probability is to declare a value of an outlier. Theyfigured that while the outliers might not be in the range of the model or a pattern, most of theobservations seem to follow the same principles or satisfy the model. In general, treatmentsfor outlier issues are often conducted by one of these three methods: 1) keeping outliers asnormal data. In this case, we will ignore the issue of outlier and conduct the empirical testwith the whole sample of our database; 2) wisorizing the outliers at a given level (e.g. at thelevel of 1% or 5%); and 3) eliminating/trimming outliers from database or the sample.

While wisorizing or eliminating outliers will create statically bias and undervalue the outliersbecause of the significance impact by decreasing standard errors, keeping them as normal

data in regression process might lead to overvalue the outliers and may create remarkableresults which vary remarkably from the true population value. However, our database was


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collected from HOSE and HNX which were quite standardized in the requirements of thefirms equity size, profitability and transparence. In addition, our database was slightly smallfor a panel regression; therefore, we decided to treat potential outliers as normal data in ourempirical test to ensure the variability of the sampleii.

In addition, our explanatory variables looks closely related because we have employedseveral internal characteristics of the firm in empirical analysis. Therefore, we conducted amulti-collinearity test followed by instruction of Philip B. Ender, from UCLA Office ofAcademic Computing, distributed on 23/11/2010, to isolate the effect of each controlvariable to dependent variable.

Table 2: Multi-collinearity Test

Variables VIF SQRT-VIF Tolerance R-Squared

CASH 1.10 1.05 0.9091 0.0909

LN_TA 1.17 1.08 0.8531 0.1469

EBIT_TA 1.23 1.11 0.8146 0.1854

DEP_TA 1.11 1.05 0.9005 0.0995

FA_TA 1.13 1.06 0.8832 0.1168

FIRM_AGE 1.02 1.01 0.9789 0.0211

MB 1.20 1.09 0.836 0.164

Mean VIF 1.14 Condition Number 1.6808

From table 2, VIFs, variance inflation factor, and Condition Number, index of the globalinstability of regression coefficients, were all less than 2. That means each independentvariable could be considered as non-linear combination with other independent variables inour model. Consequently, multi-collinearity is not a serious problem for our empirical

analysis.

Finally, to ensure the resulting standard errors are consistent with the panel autocorrelationand heteroskedasticity issues, we used robust standard errors in our regression analysis.

5. Trade-off Theory and Regression Test Results

The first step of this study was testing the existence of an optimal level of debt for each firmgiven its characteristics. The explained variable is MDR, and explanatory variables includedfirm size, profitability, market-to-book value of total assets, firm age, depreciation and fixedassets. Running unbalanced panel regression by OLS, random effects and fixed effects,with the results can explain over 44% of the sample test (R2=0.4). We found that the desiredmarket debt ratio does exist but significantly depends on plausible firm features. In thiscase, those features are firm size, profitability, fixed assets and prospective firm growth.However, depreciation and history of the firm do not statistically influence the debt choice.Industry groups and time-varying effects do not elicit changes, as we received the sameresults for the significance of control variables to the output when adding the dummyvariables in columns (4), (5) and (6), except for the variable of market-to-book ratio ofassets.


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Table 3: Testing optimal leverage and firms featuresiii

Equation 2: MDR*i,t+1= Xi,t

In which, Xi,t included:

- LN_TA: logarithm of total assetdenoted for firm size- EBIT_TA: Earning before interest and tax/total assetdenoted for profitability- DEP_TA: Depreciation/total assetdenoted for Depreciation- FA_TA: Fixed asset/total assetdenoted for Fixed asset- Firm_Age: total year since firm establisheddenoted for history of firm- MB: Market to book ratio of assetsdenoted for prospective growth in future

(1) (2) (3) (4) (5) (6)

ControlVariables

OLSRandomeffects

Fixedeffects

OLS(dummy)

Randomeffects

(dummy)

Fixedeffects

(dummy)

LN_TA .0583*** .0882*** .0881*** .0407*** .0544*** .1374***(15.44) (15.61) (15.61) (11.20) (9.85) (9.88)

EBIT_TA -1.179*** -.8922*** -.8922*** -1.116*** -.8392*** -.6361***

(-20.11) (-14.98) (-14.98) (-20.56) (-15.12) (-10.37)

DEP_TA -0.042 -.1389 -.1388 .09005 -.0377 -.0526

(-0.42) (-1.55) (-1.55) (0.93) (-0.44) (-0.60)

FA_TA 0.104*** .1301*** .1300*** .1662*** .1906*** .1784***

(3.97) (3.77) (3.77) (6.67) (6.00) (4.08)

FIRM_AGE 0.001* .0007 .0007 .0008* .0006 -.0024

(2.41) (1.05) (1.05) (2.29) (1.03) (-0.65)

MB -0.002*** -.0016*** -.0016*** -.0004** -.0001 .0001

(-11.96) (-13.17) (-13.17) (-2.73) (-1.27) (0.60)

N 1608 1608 1608 1608 1608 1608

R2 (with in) 0.4473 .4054 0.5540 0.4969

t statistics in parentheses - legend: * p


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We continued our analysis by determining the effects of government control on fund-raisingbehaviours by running an empirical test with 689 observations of state-owned firms. Asdenoted in equation (4), the lead MDRi,t+1(MDR of firm i at time t+1) is explained by a set ofa firms characteristics, Xi,t, and its current MDRi,t(MDR of firm i at time t). We continuouslyrun the OLS, random effects and fixed effects analysis for the both cases, with and without

dummy variables.

Based on the results of Table 4, we figured that OLS and random effects bring similarresults regardless of if time and industry group dummies are included in the regressionanalysis. Firms with very high leverage will decrease their leverage to match the target levelof debt and vice versa, since the adjustment speed is naturally bounded between zero andunit. Firms with more assets in a given year borrow more in the following year, even if theyare controlled by the government. State-owned firms also fit in our assumption that highprofitability will help to reduce the dependence of debt usage. MB remains negativelyrelated to the debt ratio. However, when running fixed-effects analysis, we found nosignificance between the leverage level at time t and the leverage level at time t+1. The

significance of the partial adjustment model moved slightly when dummy variables wereincluded in the regression test. Leverage levels were proven to adjust dramatically towardthe long-term debt target, even at the significance level of 5%.

Nevertheless, the dynamic model contained the lagged dependent variables that yieldinconsistent estimates because regressors and error terms (disturbances) are correlated;the strict exogeneity condition was not satisfied. Therefore, least-square and fixed effectsmodels might not be the proper techniques for running the regression analysis. To solvethese problems, we applied the ArellanoBond difference GMM estimator in Stata, writtenby Roodman (2006), and presented the results in column (7). The coefficient of leadMDRi,t+1on MDRi,timplies that state-owned firms rapidly amend their debt ratios to optimum

levels. In the ordinary least squares and random-effects models, state-owned firms adjustapproximate 37% within one year to reach the target debt ratio. This adjustment speedpredicts that one typical state-owned firm only needs approximately 32 months to close thegap between the current and the optimal leverage levels. In the GMM method, a more rapidadjustment speed was found at the rate of 66%. This means that if everything is constant,after 18 months, state-owned firms might reach the target leverage level. Therefore, we canconclude the cost of deviating from the optimal debt ratio outweighs other considerationssuch as internal funds and issuing equity, which are mentioned in the pecking order theory.


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Table 4: Testing the partial adjustment model state-owned firmsiv

MDRi,t+1= Xi,t+(1-) MDRi,t+ i,t+1(1) (2) (3) (4) (5) (6) (7)

ControlVariables

OLSRandomeffects

Fixedeffects

OLS(dummy)

Randomeffects

(dummy)

Fixedeffects

(dummy)GMM

MDR .6344*** .6268*** .0558 .6507*** .6087*** .1122* 0.438***(15.89) (15.62) (1.12) (16.61) (15.16) (2.21) (4.530)

LN_TA .0406*** .0413*** .2222*** .0365*** .0391*** .1141*** 0.0981***

(6.59) (6.63) (10.35) (6.31) (6.31) (4.12) (4.230)

EBIT_TA -.3514*** -.3503*** .0882 -.1982* -.1961* .1559 -0.333

-3.61) (-3.58) (0.69) (-2.06) (-2.00) (1.28) (-1.48)

DEP_TA -.0729 -.0760 -.1325 .0580 .0535 -.0379 -0.116

(-0.54) (-0.56) (-0.95) (0.46) (0.42) (-0.28 ) (-0.29)

FA_TA .0694 .0711 .1253 .0493 .0596 .1021 0.448**

(1.81) (1.84) (1.42) (1.37) (1.56) (1.23) (3.310)

FIRM_AGE .0007 .0007 .0781 .0004 .0005 .1564* 0.001

(.08) (1.10) (1.00) (0.78) (0.78) (2.10) (0.380)MB .0001*** .0001*** .0003 -.0007** -.0006* -.0001 0.00105**

(0.59) (0.60) (1.33) (-2.63) (-2.53) (-0.53) (2.800)

N 531 531 531 531 531 531 531R2 (with in) .5878 0.1691 0.2841 .6745 0.3842

t statistics in parentheses - legend: * p


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Table 5: Testing partial adjustment model private firms

( MDRi,t+1= Xi,t +(1-) MDRi,t+ i,t+1 )

ControlVariables

(1) (2) (3) (4) (5) (6) (7)

OLSRandomEffects

FixedEffects

OLS withdummy

RandomEffects withdummy

Fixed Effectswith dummy

GMM

MDR 0.745*** 0.734*** 0.0685 0.709*** 0.683*** 0.0972* 0.780***

(22.58) (22.03) (1.54) (21.74) (20.57) (2.29) (9.36)

LN_TA 0.0224*** 0.0232*** 0.199*** 0.0193*** 0.0200*** 0.0324 0.03

(4.38) (4.45) (11.15) (4.12) (4.10) (1.43) (1.81)

EBIT_TA -0.325*** -0.325*** -0.159 -0.243** -0.241** -0.0758 -0.38

(-4.04) (-4.01) (-1.67) (-3.28) (-3.21) (-0.88) (-1.88)

DEP_TA -0.249* -0.252* -0.0757 -0.172 -0.177 -0.104 1.53

(-1.98) (-2.00) (-0.58) (-1.47) (-1.50) (-0.84) (1.72)

FA_TA -0.0179 -0.0184 -0.025 0.0542 0.0578 0.149* -0.16

(-0.52) (-0.52) (-0.35) (1.66) (1.72) (2.27) (-1.28)

FIRM_AGE 0.000182 0.000188 -0.00098 0.000294 0.00032 -0.00317 0.00

(0.35) (0.35) (-0.22) (0.60) (0.63) (-0.85) (1.67)

MB 0.000161 0.000163 0.000295 -0.000196 -0.000182 0.000264 0.00111**

(0.98) (0.98) (1.70) (-1.16) (-1.06) (1.47) (3.01)

N 771 771 771 771 771 771 771

R2 0.5938 0.0967 0.2550 0.6894 0.3004 0.4328

t statistics in parentheses - Legend: * p


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6. Pecking Order Theory and the Empirical Implication

The pecking order theory implies that firms have no strong preferences on how much debtshould be used to support for their financial deficits. Therefore, firms might not consideradjusting their leverage level to reach the optimal level of debt as top priority when they

need to raise funds. We applied Frannery and Rangans (2006) concept to build theestimated model by adding the financing deficit into the model as another control variablewith the same variables used in the trade-off theory of capital structure, found in sectionfive. The testing model was described in section four.

Frank and Goyal (2003) stated that the pecking order theory implies that the financingdeficit ought to wipe out the effects of other variables. If the financing deficit is simply onefactor among many that firms trade off, then what is left is a generalized version of thetrade-off theory (p.219). Although, this conclusion might not perfectly explain the events inemerging markets such as Vietnam, we still used the ideas of those authors to conduct ourmodel specification and run the empirical test for the application of the pecking order theory

in Vietnam.

Running the pecking order theory test for state-owned firms with different techniques usedin section five, we figured that coefficients between BDRi,t and BDRi,t+1are all statisticallysignificant. In addition, we found that regardless of the amount of beginning surplus cash,firms would still borrow at a given level of debt. This is also moderately consistent whendepreciation is unrelated with the outcome. The application of the pecking order theoryseems evident when our results indicated that adding financing deficit substantiallyindicated the significance of other explanatory variables. Production capacity and growthopportunities were no longer statistically significant to the book debt ratio. This seemsunlikely to Flannery and Rangan, since pecking order forces do not appear to be part of

what was referred to as the generalized version of the trade-off theory (Frank and Goyal,2003, p. 219). However, we only found the coefficient of financing deficit to be statisticallysignificant at 5% when running the OLS and random effects without dummies. With N small(N=493), OLS and random effects analysis created the exact same outcomes in our paper.However, if we considered industry and the time-varying impact on book debt ratio in theOLS and random-effects analyses, we found that the FINDEF coefficient was insignificant,consistent with the results received when running a fixed effects and GMM regressionanalysis. Because of the limitations of OLS and random effects regression analyses, whichwas mentioned in previous section, results from these two analyses are considered biasedand inconsistent. Therefore, we can conclude as implied by GMM model that the peckingorder implication has failed to explain debt-increasing behaviors of state-owned firms inVietnam.


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Table 7: Pecking order testing state-owned firms

BDRi,t+1= Xi,t+(1-) BDRi,t+FINDEFi,t+1 + i,t+1

Control

Variables

(1) (2) (3) (4) (5) (6) (7)

OLSRandomEffects

FixedEffects

OLS withdummy

RandomEffects with

dummy

FixedEffects

with

dummy

GMM

BDR 0.625*** 0.625*** 0.140** 0.625*** 0.625*** 0.148** 0.545***

(17.83) (17.83) (2.82) (17.22) (17.22) (2.94) (6.60)

CASH -0.00191 -0.00191 0.00965 -0.00288 -0.00288 0.0110 -0.0135

(-0.26) (-0.26) (0.68) (-0.38) (-0.38) (0.77) (-0.47)

LN_TA 0.0248*** 0.0248*** 0.0609*** 0.0268*** 0.0268*** 0.0497* 0.0421***

(5.19) (5.19) (3.44) (5.33) (5.33) (1.99) (3.44)

EBIT_TA -0.154* -0.154* 0.154 -0.0771 -0.0771 0.186 -0.112

(-2.08) (-2.08) (1.49) (-0.96) (-0.96) (1.75) (-0.80)

DEP_TA 0.0813 0.0813 -0.0909 0.128 0.128 -0.0587 0.115

(0.69) (0.69) (-0.68) (1.08) (1.08) (-0.44) (0.49)FA_TA 0.0421 0.0421 0.0297 0.0474 0.0474 0.0264 0.157

(1.43) (1.43) (0.41) (1.57) (1.57) (0.36) (1.89)

FIRM_AGE 0.000272 0.000272 0.0341 0.000253 0.000253 0.0166 0.00127

(0.59) (0.59) (0.55) (0.54) (0.54) (0.26) (0.83)

MB -0.000255 -0.000255 -0.000263 -0.000555** -0.000555** -0.000274 0.0000264

(-1.46) (-1.46) (-1.38) (-2.59) (-2.59) (-1.11) (0.08)

FINDEF -0.0544* -0.0544* -0.0360 -0.0404 -0.0404 -0.0285 -0.0383

(-1.98) (-1.98) (-1.18) (-1.44) (-1.44) (-0.92) (-0.62)

N 493 493 493 493 493 493 493



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Table 8: Pecking order testing private firms

BDRi,t+1= Xi,t+(1-) BDRi,t+ FINDEFi,t+1 + i,t+1

Control

Variables

(1) (2) (3) (4) (5) (6) (7)

OLSRandomEffects

FixedEffects

OLS withdummy

RandomEffectswith

dummy

FixedEffectswith

dummy

GMM

BDR 0.656*** 0.608*** 0.0963* 0.650*** 0.593*** 0.0782* 0.434***

(22.86) (20.43) (2.45) (21.47) (18.85) (1.99) (6.29)

CASH -0.00267 -0.00342 -0.00512 -0.000707 -0.00139 -0.00482 -0.00334

(-0.39) (-0.48) (-0.55) (-0.10) (-0.19) (-0.54) (-0.14)

LN_TA 0.0177*** 0.0193*** 0.0462** 0.0186*** 0.0200*** -0.0134 0.0332**

(4.53) (4.60) (3.30) (4.64) (4.59) (-0.70) (2.65)

EBIT_TA -0.119* -0.120* 0.00794 -0.103 -0.103 0.0103 -0.342*

(-2.03) (-1.99) (0.11) (-1.74) (-1.69) (0.14) (-2.54)

DEP_TA -0.268* -0.275* -0.208 -0.314** -0.321** -0.217 0.0880

(-2.51) (-2.54) (-1.75) (-2.85) (-2.87) (-1.81) (0.16)FA_TA 0.0898*** 0.0941*** 0.0850 0.110*** 0.117*** 0.146** 0.216*

(3.42) (3.38) (1.54) (3.98) (4.00) (2.67) (2.47)

FIRM_AGE 0.000220 0.000238 -0.00126 0.000237 0.000265 -0.00126 -0.000271

(0.57) (0.56) (-0.42) (0.60) (0.60) (-0.43) (-0.19)

MB -0.000155 -0.000165 -0.000255* -0.000299* -0.000289* -0.0000751 -0.000362

(-1.35) (-1.42) (-1.99) (-2.19) (-2.08) (-0.50) (-1.31)

FINDEF -0.0101 -0.0116 -0.0155 0.00609 0.00468 -0.0180 -0.0168

(-0.48) (-0.55) (-0.70) (0.29) (0.22) (-0.81) (-0.27)

N 708 708 708 708 708 708 708



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firms and private firms seem to hold an equal ratio in long-term debt, and no evidence wasfound to prove which type of firm is using more debt.

This study only used a database of listed companies within the maximum time period ofseven years. Several state-owned and private companies still have not decided to

participate in the exchange market. Therefore, it might be a limit of our panel regressionanalysis when the data consists of T small and lagged variables. In addition, we onlyconsidered the pecking order theory and the static trade-off theory in this study. Othercapital structure theories, such as market timing theories, were not included. Moreover, wealso only considered internal factors of the firms. Other external parameters that could havebeen included are corporate tax policy, bank credit supply and macro-economic factors.Therefore, these issues can be addressed in future capital structure studies for the Vietnamcase.

Endnotes

i

We did not add R&D expenditures as a determinant of capital structure in our empirical analysis, becausemost of listed companies in Vietnam do not seriously spend their money on research and developmentactivities. Therefore, R&D expenditures generally equal to zero or omit in the database.ii In fact, we also conducted regression analysis by using wisorizing technique at a given 1% level as arobustness check for outliers. However, we found that the results remained unchanged, compared to theresults we have described in main part of the paper. Therefore, to make the paper short and simple, wedecided not to provide wisorizing empirical results in our paper.iii Dummy variables here are considered as industry group (INDU) and year (YEAR) dummies. However, due

to the aim of our test is proving coefficients of Xi are non zero, hence, we do not present the regressionresults of dummies variables in table 4 and other tables afterward.iv From Table 5 afterward, we will not report the description of Independent Variables Xi,t as they are all

described in table 4 and section three.

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Trade-Off Theory or Pecking Order Theory With a State-Ownership Structure- The Vietnam Case

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