The Joint Determination of Leverage and Maturity: Empirical ...

Forum Bisnis Dan KewirausahaanJurnal Ilmiah STIE MDPThe Joint Determination of Leverage and Maturity:Empirical Evidence from MalaysiaRini ApriliaSTIE MDPrinie_aprilia@yahoo.co.idAbstract: This study empirically investigates the simultaneity between leverage and debt maturity policies and thefactors that influences them by using a simultaneous equation framework in which leverage and debt maturity areendogenous variables. Based on a panel data of 788 non-financial firms listed on Bursa Malaysia from 1999 until2010. The simultaneity between leverage and debt maturity is tested by utilizing a two-stage least squares (2SLS)regression model. The results of this study show that leverage and debt maturity policies have a negativesimultaneous relationship which indicates that there are strategic complementarities between leverage and maturity.This study also documents different results among the exogenous variables in both equations, in which growthopportunities, regulation, firm size, profitability and tangibility lend considerable support to the proposedhypotheses on the leverage equation. Meanwhile, firm size, regulation, abnormal earnings and tangibility are foundto have significant effects on the debt maturity equation.Keywords: simultaneity, capital structure, debt maturity.Abstrak : Penelitian ini secara empiris menyelidiki simultanitas antara leverage dan maturitas hutang serta faktor –faktor yang mempengaruhinya dengan menggunakan kerangka persamaan simultan yang mana leverage danmaturitas hutang adalah variabel endogen. Berdasarkan data panel terdapat 788 perusahaan terdaftar di BursaMalaysia dari tahun 1999 sampai dengan 2010, tidak termasuk perusahaan yang bergerak di industri keuangan.Simultanitas antara leverage dan maturitas hutang diuji dengan menggunakan regresi model two stage least squares(2SLS). Hasil dari penelitian ini menunjukkan bahwa leverage dan maturitas hutang memiliki hubungan simultanitasnegatif yang menunjukkan bahwa terdapat hubungan yang komplementer anatara leverage dan maturitas hutang.Penelitian ini juga menunjukkan hasil yang berbeda antara variable eksogen dalam kedua persamaan tersebut, yangmana growth opportunities, regulation, firm size, profitability, dan tangibility memberikan dukungan yang penuhterhadap hipotesis yang diajukkan pada persamaan leverage. Disisi lain pula, firm size, regulation, abnormal return,dan tangibility ditemukan memiliki pengaruh yang signifikan terhadap persamaan maturitas.Kata kunci : simultanitas, struktur modal, maturitas hutang.1. INTRODUCTIONIn principle, every company needs fundingand the fulfillment of these funds may come frominternal sources or external sources. The selectionof the financial structure is a matter which concernsthe composition of funding that will be used by acompany. This will then determine how much debtwill be incurred to finance its assets.Capital structure which forms the basisfor permanent funding consists of long-termdebt, preferred stock and shareholders’ equity.The basic element of a corporate financial policyincludes the choice of debt level and also thestructure of debt maturity (Barclay, Marx, &Smith, 2003). Barclay and Smith (1995) suggestthat when firms choose debt as a source offunding, they should also consider other financialfactors such as debt maturity, priority andwhether to use public debt or private debt.Barclay et al. (2003) further postulate that whenit comes to funding, other factors often occursimultaneously.Vol. 2 No. 1 September 2012Hal - 1

Forum Bisnis Dan KewirausahaanJurnal Ilmiah STIE MDPLeverage and debt maturity are the twindimensions that cannot be separated from thecorporate capital structure, in other words, when afirm issues new debt, it needs to decide the periodof maturity and the size of the debt levelconcurrently (Elyasiani, Guo, & Tang, 2002). Inaddition, Barclay and Smith (1995) assert thatwhen firms choose debt as a source of funding,they also need to consider the maturity of debtbecause the selection of debt maturity will affectthe value of the firm. In essence, these studiescontend that the choice of debt policy and debtmaturity structure should be consideredsimultaneously.Barclay, Marx, and Smith (1997) is thepioneering study in examining the simultaneitybetween the policies on leverage and debt maturityamong U.S. firms based on a simultaneousequations framework. Their findings revealstrategic complementarities between maturity andleverage. Using a different system of simultaneousequations, Barclay et al. (2003) show that althoughleverage and maturity are strongly correlated interms of both unconditional and conditionalcorrelations, there is evidence that both leverageand debt maturity are not complements. They,however, note that their model is possiblymisspecified. Stohs and Mauer (1996) argue thefindings by Barclay and Smith (1995) on therelationship between debt maturity and growthopportunities are misspecified because they do notcontrol the differences in leverage in their ordinaryleast squares (OLS) debt maturity regression.When Stohs and Mauer (1996) add leverage to theright hand side of their debt maturity regression,they discover that coefficient on the growthopportunities variable has a statistically significantpositive relationship.Therefore, it is improper to take one aspredeterminant when analyzing how firms choosethe other. The coefficients estimated in the OLSregression of debt maturity model on the leverageand others variables will suffer from simultaneousequation bias (Barclay et al., 2003).Even though, Barclay et al. (2003) find thatthe coefficient on debt maturity in the leverageregression and the coefficient on leverage in thedebt maturity regression have a different signwhich indicate that leverage and debt maturity arenot complementary to each other, but they believethat leverage and debt maturity are stronglycorrelated to each others. Elyasiani et al. (2002)and Sunarsih (2004) suggest a positive relationshipbetween leverage and maturity, implying leverageand maturity are complementary to each other andthere is simultaneity between leverage and debtmaturity policies. Johnson (2003), however, finds anegative relationship between leverage and shorttermdebt.Other subsequent empirical studies byElyasiani et al. (2002), Johnson (2003), Sunarsih(2004) and Billett, King, and Mauer (2007) provideevidences of strategic complementarities betweenleverage and maturity. Based on these models ofsimultaneous equations framework, this studyattempts to examine the simultaneity between thepolicies on leverage and debt maturity amongMalaysian public-listed firms during the periodfrom 1999 to 2010.The remaining of this study is structured asfollows: the next section presents the reviews oftheoretical literatures and past empirical studies.Thereafter, the research framework and hypothesis,which are constructed from the formulatedresearch, are presented in section three, whilesection four discusses the empirical findings andprovides the potential explanation of the results.Finally last section will concludes the overallresearch with some suggestions for further researchin this field.2. THEORETICAL LITERATURE ANDHYPOTHESIS DEVELOPMENTThis part discusses the relationshipbetween the control variables on leverage and debtmaturity. This will enable conclusions to be madeon the influences of each variable on the leverageand debt maturity. This part also tests thehypothesis formulated for each variable.In this study, Johnson (2003) argues thatthere exists a positive relationship betweenHal - 2 Vol. 2 No. 1 September 2012

Forum Bisnis Dan KewirausahaanJurnal Ilmiah STIE MDPleverage and longer term debt maturity. Thesesimultaneous equation results are consistent withthe single equation model done by Barclay andSmith (1995) who find that firms with longermaturity have higher leverage. The relationship isalso consistent with Stohs and Mauer (1996) andBarclay et al. (1997) that find negative relationshipbetween leverage and short-term maturity orpositive relationship between leverage and longtermmaturity.For others explanatory variables there havebeen a great deal of research into both capitalstructure theory and debt maturity theory, butrelatively little into how the two theories may relateto each other. In order to lay a theoreticalframework for this study, a review of capitalstructure theory and debt maturity theory literatureshould be done independently. These studies alsoexplore how and why existing researches suggestthat there might be a link between the two proxies.2.1. Theoretical Literature Under LeverageTheoretical researches generally suggestthat leverage is significantly positive to growthopportunities. According to signaling theory, highperforming firms are capable of using moreleverage financing since leverage has its deadweight costs, which make less valuable firms morelikely to fall into bankruptcy (Chen, 2004). Thesignaling theory predicts that firms with higherearnings with good growth prospect will use higherleverage.Several studies have been conducted todetermine whether there is a relationship betweenleverage and firm size. Titman and Wessels (1998),Crutchley and Hansen (1989) and Rajan andZingales (1995) argue that the possibility of a largecompany that went bankrupt is small, so size has apositive effect on the level of debt taken.Elyasiani et al. (2002) state that if firmswith NOLs have low tax benefits of debt, anegative relationship can be expected betweenNOLs and leverage. Firms with higher netoperating loss will have lower leverage to enablethem to manage their debt and pay it on time.Generally, leverage is negatively correlated toNOLs dummy. This is a direct implication of thetrade-off theory of Deangelo and Masulis (1980).Capital structure also plays an importantrole in assessing regulation due to the interactionbetween the investment and financial decisions of aregulated firm and also the pricing choices ofregulators (Spigel&Spulber, 1994). A number ofstudies suggest that rate regulation creates anincentive for regulated firms to increase their levelof debt and there exists a positive relationshipbetween regulated firms and leverage.This study also looks at the relationshipbetween the signaling effects of debt by using theabnormal earnings as a proxy of signaling effect.According to signaling theory, firms with higherreturns always optimize their leverage becausehigher returns always give positive signal to themarket (Flannery, 1986 & Diamond, 1993).Optimism of companies about the future will beindicated by an increase in the stock price.According to the pecking order theory,profitability negatively affects leverage (Myers,1977). This is supported by Megginson (1997) whosuggests the tendency of profitable firms to have aninverse relation with leverage. In other words,firms which are profitable tend to have smalleramount of loans. Furthermore, this is in line withTitman and Wessels (1988) and Fama and French(2002) who find a negative relationship betweenprofitability and leverage.The literatures on the relationship betweentangibility and leverage suggest that tangibility ispositively related to leverage. If a firm has higherasset tangibility, then these assets can be used ascollateral, reducing the risk faced by lender such assuffering from agency cost of debt. Therefore, highleverage is expected to be associated with highfraction of tangible assets. In the case ofbankruptcy, the expected value of tangible assetsshould be higher than intangible assets. Harris andRaviv (1990) suggest that leverage should increasewith liquidation value and this is supported byBarclay et al. (2003). Both of them suggest thattangibility is positively related to leverage.Vol. 2 No. 1 September 2012Hal - 3

Forum Bisnis Dan KewirausahaanJurnal Ilmiah STIE MDP2.2. Theoretical Literature Under Debt MaturityIn general, firms with higher growthopportunities prefer to use smaller proportion oflong-term debt whereby they control theirunderinvestment activities and agency cost throughshort-term debt (Myers, 1977 &Ozkan, 2002).Their finding was consistent with Arslan and Karan(2006) whereby the coefficient was negativelysignificant in their study. They state that firms withgreater growth opportunities prefer to use shortermaturity to solve the underinvestment problem.Leland and Thoft (1996) show that the optimalcapital structure of a firm also depends on debtmaturity and it is lower when the firm is financedby short-term debt.Marsh (1982) finds that firms with largersize more often choose long-term debt maturity,whereas small firms will choose short-term debt.Bevan and Danbolt (2000) in their researchdocument a positive effect of firm size on debtmaturity. Thus, small firms are expected to use lesslong-term debt than the larger firms. Titman andWessels (1998) state that the possibility of largecompanies getting into bankruptcy is small andthus, it can positively affect the level of debt takenby the companies. Large firms, in general, tend tohave more stable cash flows and more diversifiedassets. This means that large companies will uselong-term debt more than small companies do. Thelatter prefer to use short-term debt maturity.Johnson (2003) argues that firms that havegreater net operating loss carryforwards tend to useshort-term debt maturity. It means that there is anegative relationship between NOLs dummy andthe debt maturity. If firms with NOLs have low taxbenefits of debt, the negative coefficient will affectthe debt maturity.Barclay et al. (2003) state that optimal debtmaturity should be longer for regulated firmsbecause regulatory control restrict managers’discretion over corporate investment decisions andthereby able to control aspects of underinvestmentissues. The positive relationship between regulateddummy and debt maturity is also supported byBarclay and Smith (1995) who argue that regulatedfirms can borrow longer leverage due to lessdiscretion in investment decision, and also lessagency problem. Flannery (1986) argues that utilityfirms are expected to issue longer term debtmaturity than other industrial firms.Based on the signaling theory, companieswith higher returns will give positive signal to themarket. Hence, firms with positive informationabout future prospect prefer to use short-term debtthat can be refinanced after information is revealed(Flannery, 1986). According to signaling theory,the selection of maturity structure selected bymanagers will provide useful information toinvestors.This study also sees the relationshipbetween asset maturities against debt maturity. Ifthe debt has a maturity that is longer than thematurity of its assets, then there is a tendency forcompanies that do not have enough cash to paydebts until it matures. Conversely, if the debt has amaturity shorter than maturity of its assets, thencompanies which do not have enough funds willchoose to refinance according to priority. Thisargument is supported by Myers (1977). Thisargument is also in line with Stohs and Mauer(1996) who assert that when debt maturity isshorter than asset maturity, the firm may not havesufficient cash to meet its obligations when theyfall due; in other words, when the maturity of debtis longer than its asset maturity, the firm will havedebt obligations to meet while cash flows fromasset stop. Therefore, the following hypothesis istested that asset maturity has positive relationshipwith debt maturity.Table 1: Summary of HypothesisLeverage EquationH1aDebt maturity has a positive effect onleverageH2Growth opportunities have a positiveeffect on leverageH3 Firm size has a positive effect on leverageH4 NOL has a negative effect on leverageH5Regulated firm has a positive effect onleverageHal - 4 Vol. 2 No. 1 September 2012

Forum Bisnis Dan KewirausahaanJurnal Ilmiah STIE MDPTable 1: ContinuedLeverage EquationH6Abnormal earnings has a positive effecton leverageH7Profitability (ROA) has a negative effecton leverageH8Tangibility has a positive effect onleverageDebt Maturity EquationH1bLeverage has a positive effect on debtmaturityH9Growth opportunities have a negativeeffect on debt maturityH10Firm size has a positive effect on debtmaturityH11NOL has a negative effect on debtmaturityH12Regulated firm has a positive effect ondebt maturityH13Abnormal earnings has a negative effecton debt maturityH14Asset maturity has a positive effect ondebt maturityH15Term structure has a positive effect ondebt maturity(MGS) and Treasury-bills (T-bills) are sourcedfrom the Bank Negara Malaysia’s website. Thepopulation of this study consists of companieslisted on Bursa Malaysia from 1999 to 2010. Thetotal number of listed companies is 850 from 12different industrial sectors, namely plantation,property, consumer, construction, trading/services,technology, mining, industrial products, hotels,infrastructure project, finance and Real EstateInvestment Trusts (REITs).The sample is derived based on apurposive sampling technique. This technique isused to select the sample based on specific criteriaand certain consideration adjusted to the purpose ofstudy. The initial sample used in this studycomprises of 850 companies listed on BursaMalaysia.Table 2: List of Sample DataSource: Based on past related studyAccording to tax hypothesis, the firm’sdebt maturity will increase with the slope of theyield and they are expected to have a positiverelationship, which are supported by Barclay andSmith (1995) and Stohs and Mauer (1996). Kim etal. (1995) state that the increase in the slope ofterm structure and the interest rate volatility canmake firms to choose longer term debt maturity intheir capital structure. Hence, term structure isexpected to have a positive relationship to debtmaturity.3. METHODOLOGYThe financial data are obtained fromDataStream and the industrial classifications arederived from Bursa Malaysia. The data for monthendyields of Malaysian Government SecuritiesSource: Data streamThe target sample in this study must meetthe following criteria: first, the companies are nonfinancialfirms listed on Bursa Malaysia; andsecond, the companies must have continuouslypublished their financial reports from 1999 to 2010.A total of 51 firms in the financial sector areexcluded because of their financial structures arelikely to be influenced by different factors (e.g.capital adequacy regulations) than other nonfinancialfirms. In addition, 21 firms are excludeddue to incomplete data. Therefore, the final samplesize for this study consists of 778 listed firms (seeTable 2).Vol. 2 No. 1 September 2012Hal - 5

Forum Bisnis Dan KewirausahaanJurnal Ilmiah STIE MDP3.1. Analytical TechniquesThis technique is used to test thesimultaneity between leverage and debt maturity asthe dependent variables in order to determine therelationship of the two policies and the independentvariables such as growth opportunities, regulatedfirm, firm size, NOL carryforwards, abnormalearnings, profitability, tangibility, asset maturity,and term structure that affect leverage and debtmaturity. The basic model of leverage and debtmaturity equation is formulated as follows:Where:3.2 VariablesBased on the research problems anddevelopment of hypotheses, the variables that areexamined in this study and their measurement arelargely adopted from existing literature. Thedependent variables are leverage and debt maturity;the explanatory variables include growthopportunity, regulated firms, firm size, NOLs,abnormal earnings, profitability, tangibility, assetmaturity and term structure. The definition of thesevariables is listed in table 4.Table 4: Measurement of VariablesVariablesDependent VariablesLeverageMeasurementRatio of book value of total debtVariablesDebtMaturityIndependent VariablesGrowthRegulatedFirmsFirm SizeNetOperatingLossAbnormalEarningsProfitabilityTangibilityAssetMaturityTermStructureMeasurementto total assetRatio of long term debt to totaldebtGROW is total asset plus marketcapitalization then minuscommon equity, divided by totalasset.The measurement of regulatedfirms are using dummy variable,1 for utilities companies andothers are 0.Measured by using the naturallogarithm of total assets of eachcompanyNOL carryforwards dummyequals one form firms with netoperating loss carry forwards andzero otherwiseThe difference between earningsin year t+1 and t, then divided byearnings in year t.Ratio of EBITDA to total assets.Ratio of tangible asset divides bytotal assets.Ratio of fixed assets to annualdepreciation expensesThe difference between themonth end yields on long term10-year government bonds(MGS) and matched with thefirm’s fiscal year end.Source: Secondary data that has been processed20124. RESULTS AND DISCUSSION4.1. Summary Statistics and Correlation Matrixof VariablesTable 5 reports the descriptive statistics forthe entire sample which are used for the singleequation and also simultaneous equations regressionanalysis. The data was analyzed by using Eviews 7,covering a total of 5721 observations.Hal - 6 Vol. 2 No. 1 September 2012

Forum Bisnis Dan KewirausahaanJurnal Ilmiah STIE MDPMean (Median) leverage is 0.26 (0.24), itmeans that on average, Malaysian firms only use26.00% as leverage to finance their project. Themean for debt maturity is 0.39 which means that onaverage, the long term debt represent 39% of thetotal debt incurred by Malaysian firms. For growthopportunities, the mean is about 1.07, whichsignifies that investment opportunity is high inMalaysia. It is in line with a study conducted byJensen (1986) which finds that firms with higherinvestment opportunity usually have high growth,active in investment, lower free cash flow andlower asset in place.The mean of regulated firm is 0.03 withstandard deviation about 0.17 which signals thatthe distribution of data is not normal. This alsomeans that the utility firms or other regulated firmsin Malaysia is relatively fewer in number than nonregulatedfirms. The abnormal earnings variableswhich are tested to see the signaling effect have anaverage figure of about 0.11 with the minimumvalue at -369.03 and the maximum value at110.96. This data shows abnormal distributionand can produce biased result as well.Meanwhile, the mean figure of ROA stands at3.94 with a standard deviation of 14.04,indicating that the firms are highlyprofitable. Theaverage tangibility figure is 0.41 with a standarddeviation of 0.21; this means that the data isnormally distributed.In addition, the means of asset maturityand term structure among Malaysian firms standat 36.40 and 1.5 respectively. The high figure ofasset maturity indicates that most Malaysianfirms have lower depreciation on assets whichimplies that the firms have the ability to issuelong-term debt maturity. Furthermore, thestandard deviation of term structure is less thanits average of about 0.93; it denotes that thelower the standard deviation from its average,the better the result will be since the data isnormally distributed.Table 5: Descriptive Statistics for Entire SampleMean Median Max Min Std. Dev. ObsLev 0.2640 0.2357 10.273 0.0000 0.2872 5721DM 0.3890 0.3453 1.0000 0.0000 0.3130 5721GROW 1.0666 0.9090 19.101 0.2372 0.7579 5721SIZE 12.779 12.565 18.451 7.7098 1.3385 5721NOL 0.2381 0.0000 1.0000 0.0000 0.4259 5721REGUL 0.0295 0.0000 1.0000 0.0000 0.1693 5721ABNR 0.1134 0.0269 110.96 -369.037 5.5641 5721ROA 3.9408 4.0800 771.45 -93.4700 14.038 5721TANG 0.4063 0.3976 0.9875 0.0000 0.2069 5721ASMAT 36.406 13.356 3352.4 -2142.26 112.99 5721SPRED 1.5143 1.2940 4.0550 0.0390 0.9313 5721Source: Secondary data that has been processed 2012Note: The number of observations is 5806 inEquation 1 and 6024 in Equation 2 consisting of thesample of listed companies during the 1999-2010periods. LEV is generated by dividing total debt tototal asset. DM is long term debt divided by totaldebt. GROW is total asset plus market capitalizationthen minus common equity, divided by total asset.REGUL used a dummy variable, 1 for utilitiescompanies and other are 0. SIZE is measured by logof total assets. NOL carryforwards dummy equalsto1 for net operating loss and 0 otherwise. ABNR isthe difference between earnings in year t+1 and t,Vol. 2 No. 1 September 2012Hal - 7

Forum Bisnis Dan KewirausahaanJurnal Ilmiah STIE MDPthen divided by earnings in year t. PROFIT is theratio of EBITDA to total assets. TANG istangible asset divide by total assets. ASMAT isthe ratio of fixed assets to annual depreciationexpenses. SPREAD is measured by thedifference between the month-end yields on longterm 10-year government bonds (MGS) andthree-month Treasury-bills and matched with thefirm’s fiscal year-end.Table 6 and 7 presents the correlationmatrix among the variables in the leverageequation and debt maturity equation,respectively. These correlations express somesimple relations among the variables beforegenerating the simultaneous equations regressionresults. It can be seen in both tables that leverageand debt maturity are positively correlated andsignificant at 1% level.Table 6: Correlation Matrix for LeverageLEV DM GROW SIZE NOL REGUL ABNR ROA TANGLEV 1-----DM 0.0392*** 1(2.9920) -----GROW 0.3562*** 0.0452*** 1(29.0404) (3.4485) -----SIZE 0.0261** 0.3614*** -0.0154 1(1.9887) (29.5287) (-1.17) -----NOL 0.1814*** -0.0673*** -0.0047 -0.1652*** 1(14.0491) (-5.1364) (-0.3568) (-12.7585) -----REGUL 0.0388*** 0.203618*** 0.0393*** 0.2900*** -0.0421 1(2.957) (15.8444) (2.9993) (23.0870) (-3.2101) -----ABNR 0.1165*** -0.0029 0.0787*** -0.0096 0.0127 0.0034 1(8.9371) (-0.2175) (6.0153) (-0.7295) (0.9705) (0.2613) -----ROA -0.2021*** 0.0609*** 0.1329*** 0.0813*** -0.2064*** 0.0252* -0.0083 1(-15.7248) (4.6457) (10.2131) (6.2147) (-16.0712) (1.9198) (-0.6301) -----TANG 0.0607*** 0.1812*** -0.0743*** 0.0693*** 0.004 0.0325** 0.006 -0.0565*** 1(4.6301) (14.0353) (-5.6761) (5.2890) (0.3052) (2.4806) (0.4580) (-4.3094) -----Source: Secondary data that has been processed 2012Note: The number of observations is 5275 consistingof the sample of listed companies during the 1999-2010 period. LEV is generated by dividing total debtto total asset. DM is long-term debt divided by totaldebt. GROW is total asset plus market capitalizationthen minus common equity, divided by total asset.REGUL used dummy variable, 1 for utilitiescompanies and other are 0. SIZE is measured by logof total assets. NOL carryforwards dummy equals 1for net operating loss and 0 otherwise. ABNR is thedifference between earnings in year t+1 and t, thendivided by earnings in year t. PROFIT is the ratio ofEBITDA to total assets. TANG is tangible assetdivided by total assets.Hal - 8 Vol. 2 No. 1 September 2012

Forum Bisnis Dan KewirausahaanJurnal Ilmiah STIE MDPTable 7: Correlation Matrix for Debt MaturityDM LEV GROW SIZE NOL REGUL ABNR ASMAT SPEARDDM 1-----LEV 0.0404*** 1(3.1405) -----GROW 0.0392*** 0.3410*** 1(3.0437) (28.1456) -----SIZE 0.3652*** 0.0323** -0.0280** 1(30.439) (2.5043) (-2.1732) -----NOL -0.0524*** 0.1804*** -0.0122 -0.1401*** 1(-4.0683) (14.2349) (-0.9484) (-10.9827) -----REGUL 0.2051*** 0.0411*** 0.0348*** 0.2931*** -0.0396** 1(16.2583) (3.1921) -2.7045 -23.7877 (-3.0777) -----ABNR 0.0089 0.1093*** 0.0672*** -0.0015 0.0065 0.0017 1(0.6889) (8.5297) -5.223 (-0.1213) (0.5063) -0.1326 -----ASMAT 0.1275*** -0.0119 -0.0693*** 0.0880*** 0.0429*** -0.0281** 0.2532*** 1(9.9765) (-0.9253) (-5.3889) (6.8545) (3.3353) (-2.1812) -20.3117 -----SPREAD -0.0328** -0.0004 0.0670*** 0.0006 -0.013 0.005 -0.0152 -0.0198 1(-2.5477) (-0.0305) (5.2147) (0.0446) (-1.0097) -0.3845 (-1.1759) (-1.5354) -----Source: Secondary data that has been processed 2012Note: The number of observations is 5275 consistingof the sample of listed companies during the 1999-2010 period. LEV is generated by dividing total debtto total asset. DM is long-term debt divided by totaldebt. GROW is total asset plus market capitalizationthen minus common equity, divided by total asset.REGUL used dummy variable, 1 for utilitiescompanies and other are 0. SIZE is measured by logof total assets. NOL carryforwards dummy equals 1for net operating loss and 0 otherwise. ABNR is thedifference between earnings in year t+1 and t, thendivided by earnings in year t. ASMAT is the ratio offixed assets to annual depreciation expenses.SPREAD is measured by the difference between themonth-end yields on long term of 10-yearsgovernment bonds (MGS) and three-monthTreasury-bills and matched with the firm’s fiscal year.In addition, all variables are significantlycorrelated to the leverage at 1%level except for theasset maturity and term structure. Only ROA is foundto have a significant negative relationship withleverage. Debt maturity is positively and statisticallysignificant to the growth opportunities, size, regulatedfirm, ROA, tangibility and asset maturity at 1% level.However, theNOL carrryforwards is negative andsignificant to debt maturity at 1% level and termstructure is also negatively significant to the debtmaturity at 5% level.In this study also do some test like VarianceInflation Factor (VIF) that is used to detect theexistence of the symptoms of multicollinearitybetween the explanatory variable. The resultshows that there are no independent variablesVol. 2 No. 1 September 2012Hal - 9

Forum Bisnis Dan KewirausahaanJurnal Ilmiah STIE MDPthat have VIF values greater than 10. Therefore,it is concluded that there is no multicollinearitybetween independent variables in bothregression models.4.2. Regression AnalysisThis study investigates empirically therelationship between leverage and debt maturityby using a simultaneous equations model on debtmaturity and leverage for all sample panel data.This study also estimates a single equationwithout endogeneity and with endogeneity forboth leverage and debt maturity using pooledEGLS with AR(1) to compare with previousstudies. Estimation using EGLS will potentiallyreduce the number of observation since it is ableto determine and adjust the data to be used. EGLSis also able to overcome the problem onheteroscedasticity and autocorrelation as evidentfrom the Durbin-Watson analysis equals to 1.91for leverage and 2.12 for debt maturity.The results of all regression analysis inTable 8 report that growth opportunity issignificantly positive in all regression both insingle and simultaneous equation to the leverage.It means that Malaysian firms which have highgrowth opportunity will take much moreleverage in the determination of capital structure.However, the growth opportunity does not affectthe determination of debt maturity. Thus,Malaysian firms cannot rely on growthopportunity in determining debt maturity. Insum, there is a relationship between leverage andgrowth opportunity as predicted, while on theother hand, growth opportunity does notsignificantly affect debt maturity and thus, theproposed hypothesis is rejected.Regulated firm and firm size arestatistically significant in both hypothesis ofleverage and debt maturity either in single andsimultaneous regression. This is in line with astudy conducted by Barclay et al. (2003) andJohnson (2003). The positive relationship thatexists between regulated firm and leverages isbecause regulated firms always maintain optimalleverage to reduce the agency risk (Bradley, Jarrelland Kim., 1984). While for maturity regression,positive coefficient at 1% level of significantwhich is in accordance to Barclay and Smith(1995) who state that regulated firm can borrowlonger term debt due to less discretion ininvestment decision, and also less agencyproblems.Furthermore, firm size is also positivelysignificant in both regressions in accordancewith the findings by Bevan and Danbolt (2002)and Barclay et al. (2003). All empirical studiessuggest positive relation between firm sizes toleverage due to the fact that larger firms havesmaller probability of facing bankruptcy thusallowing them to take higher leverage whichalso means having easy access to the bondmarket (Titman and Wessels, 1998) and (Rajanand Zingales, 1995). Meanwhile, therelationship between debt maturity and firm sizeis positively significant. Positive effect of firmsize, in accordance with the proposedhypothesis, and the results support the studyconducted by Titman and Wessels (1998),Bevan and Danbolt (2000) and Barclay andSmith (1995).While, for net operation losscarryforwards variable is positively significant toleverage but only significant in single equations.The positively significant relationship betweennet operating loss carryforwards and leveragecontradicts with the predicted sign which is inline with studies by Barclay, Marx and Smith(1997) and Harris and Raviv (1991). It indicatesthat firms in Malaysia with higher net operatingloss carryforwards will have higher leverage dueto the losses generated by the net operating losscarryforwards which cause equity to fall invalue.Abnormal earnings have significant affectand the hypothesis is accepted but it contradictswith the predicted sign. In this study, negativerelationship between abnormal earnings andleverage is supported by Muradoglu andSivaprasad (2009). Thus, for Malaysian firms withhigher abnormal earnings, they will use lowerleverage, however the study by.Hal - 10 Vol. 2 No. 1 September 2012

Forum Bisnis Dan KewirausahaanJurnal Ilmiah STIE MDPTable 8 : Three Different Estimators of LEV and DM EquationSource: Secondary data that has been processed 2012Standard errors in parentheses are for coefficient and P values for diagnostic test. ***,**,* Statisticallysignificant at the 1%, 5%, and 10% level, respectively (two-tailed test)Modigliani and Miller (1958) findpositively significant relationship only for utilitiessectors. Therefore, it is possible for industry inMalaysia to have negative relationship betweenabnormal earnings and leverage.On the other hand, debt maturity equationaccepted the proposed hypothesis, which is in linewith study conducted by Barclay and Smith (1995)and Sunarsih (2004) that argue abnormal earningsgive good signal to the market which means thatthe firm is of good quality; more valuable firm willuse more short term debt than long term debt.As expected, profitability and tangibilityare consistent and thus support the proposedhypothesis in leverage equation either in single orsimultaneity regression. This is also in line withasset maturity which is consistent to proposedhypothesis and positively significant to debtmaturity equation. Thus, Malaysian firms can takethese three variables namely, profitability,tangibility and asset maturity into considerationsin determining the level of debt in capitalstructure.In addition, the result of term structurerejects the hypothesis in all regression, either in asingle and simultaneous regression. Therefore,term structure cannot be used by Malaysian firmsas a reference in determining the level of debtespecially in debt maturity.Lastly, for the simultaneity test, thisstudy found that negative and statisticallysignificant between leverage and debt maturitywhich is not in accordance with predictedsign.This may be due to leverage and maturityVol. 2 No. 1 September 2012Hal - 11

Forum Bisnis Dan KewirausahaanJurnal Ilmiah STIE MDPare substitutes in addressing the under and overinvestment problems (Barclay et al., 2003).Other explanations regarding discrepancybetween the predicted sign and the result may alsobe due to the definition of long term debt adoptedin this study in which it has no clear standard.According to Barclay et al. (2003), they state thatmeasurements for debt maturity equal to thefraction of the firm’s total debt measured for morethan 3 years. Whereas in this study, long term debtis a variable collected from Datastream with theterms of debt that have maturity of more than oneyear; this proportion is similar to short term debt byJohnson (2003), in which the proportion of debtmatures within three years. Thus, it can bepossible, that the long-term debt in this studycomes under the category of short-term debt asused by Johnson (2003).In Malaysia, most companies are usingshort-term debt maturity than long- term debt andonly a few companies issue Sukuk (Mustapha,Ismail, &Minai, 2011). This also confirms thefinding by Demirguc-Kunt and Maksimovic (1999)that the most fundamental difference betweendeveloped and developing countries is thatdeveloping countries would prefer to use short termdebt rather than using long term debt. So, note thatthere is possibility that the long term debt in thisstudy is actually included in the category of shortterm debt as it stated by Johnson (2003).simultaneous equations framework in whichleverage and debt maturity are endogenous. Basedon the analysis of the results and discussion thathave been described in the previous section, it canbe concluded that results of this study indicate thepresence of simultaneity between leverage and debtmaturity with negative coefficient and significantlyproven. This is shown by the negative sign on thevariable leverage and debt maturity in bothleverage and debt maturity equation. This showsthat the relationship between leverage and debtmaturity are complementary, which means there isa negative direction of the simultaneity relationshipbetween the two equations. Thus, the coefficientestimated in an OLS regression of single equationswill suffer from simultaneous equation bias.In addition, this study does not includesome exogenous variables used in the past studies,which are considered to have significant effects onthe two policies. There are several variables thataffect the leverage and debt maturity variables. As arecommendation for further research, adding somevariables such as non-debt tax shield, dividend yieldand covenants, could potentially increase theaccuracy in analyzing the relationship ofsimultaneity between leverage and debt maturity.APPENDIX ATable 9: Hypotheses Testing SummaryOn the basis of the above explanation, it ispossible that the negative results obtained from thisstudy are based on the factors that have beendescribed. It is likely that this study supports thefinding in Johnson (2003). Thus, the negativecoefficient between debt maturity and leverage isconsistent with Johnson (2003) in which higherleverage firms use lower short term debt to mitigateinvestment opportunity problems.5. CONCLUSION AND SUGGESTIONSThis study investigates empirically therelationship of simultaneity between leverage anddebt maturity and factors that influence it, using aHal - 12 Vol. 2 No. 1 September 2012

Forum Bisnis Dan KewirausahaanJurnal Ilmiah STIE MDPTable 9: ContinuedTable 10 : Multicollinearity Test of LeverageEquationSource: Secondary data that has been processed2012Source: Secondary data that has been processed 2012Table 11: Multicollinearity Test of Debt Maturity EquationSource: Secondary data that has been processed 2012Vol. 2 No. 1 September 2012Hal - 13

Forum Bisnis Dan KewirausahaanJurnal Ilmiah STIE MDPTable 12: Summaries of Prior StudiesAuthors/ Proxy Leverage Debt maturitySimultaneity between Variablesleverage and debt maturity usedA B C D E F G H I J K L M N OLeverage Debt Maturity M/B Regulation Firm Size Profitability (ROA) Tangibility Effective Tax Rate NOL Dummy Volatility NDTS Abnormal Earning Asset Maturity Commercial Paper Dummy Term Structure Liquidity Risk Source: Secondary data that has been processed 2012Note: This table shows the author of the previousresearch drawn at randomly in this study. Theyconsist of: A. Rajan and Zingales. (1995), B =Titman, S., Wessels, R. (1998), C = Ozkan, A.(2002), D = Chen, J.J (2003), E = Jong, A.de.(2008), F = Barclay and Smith. (1995), G = Stohsand Mauer (1996), H = Guedes, J. and Opler, T.(1996), I = Jhonson, S.A. (1997), J = Stephen, A etal., (2011), K = Elyasiani, E et al., (2002), L =Barclay, M.J., et al., (2003), M = Johnson, S.A.(2003), N = Sunarsih. (2004), O = Fan, J., Titman,S., Twite, G. (2006).REFERENCES[1] Arslan, O., & Karan, M.B 2006, “Ownershipand Control Structure as Determinants ofCorporate Debt Maturity: a panel study of anemerging market”, Journal of CorporateGovernance, Vol. 14, p.312- 324.[2] Bank Negara Malaysia, Quarterly Bulletins &Annual Report, Kuala Lumpur, various issues.[3] Barclay, M. J., Marx, L. M., & Smith, C.W.1997, Leverage and maturity as strategiccomplements, working paper, University ofRochester.[4] Barclay, M.J., Marx, L.M., & Smith, C.W.2003, “The joint determination of leverageand maturity”, Journal of Corporate Finance,Vol. 9, p. 149-147.[5] Barclay, M.J., & Smith, C.W. 1995, “Thematurity structure of corporate debt.”, Journalof Finance, Vol. 50,p. 609-631.[6] Barclay, M.J., Smith, C.W., & Watts, R.L.1995, “The determinants of corporate leverageand dividend policies”, Journal of AppliedCorporate Finance, Vol. 7, p. 4-19.Hal - 14 Vol. 2 No. 1 September 2012

Forum Bisnis Dan KewirausahaanJurnal Ilmiah STIE MDP[7] Bevan, A.A., &Danbolt, J. 2000, “ Capitalstructure and its determinants in the UnitedKingdom: a decompositional analysis”,Working Paper University of Glasgow.[8] Billet, M.T., King. T-H.,&Mauer, D.C. 2007,“Growth opportunities and the choice ofleverage, debt maturity, and Covenants”,Journal of Finance, Vol. 62(2), p. 627-729.[9] Bradley, M., Jarrell, G.A., & Kim, E.H. 1984,“On the existence of an optimal capitalstructure: Theory and evidence”, Journal ofFinance, Vol. 39, p. 857-878.[10] Chen, J.J. 2004, “Determinants of capitalstructure of Chinese listed companies”, Journalof Business Research, Vol. 57, p. 1341-1351.[11] Crutchley Claire and Robert Hansen 1989, “ATest of the Agency Theory of ManagerialOwnership, Corporate Leverage, andCorporate Dividends”, FinancialManagement, Vol.18 Winter 1989, p.36-46.[12] DeAngelo, H., and R.W. Masulis 1980,“Optimal Capital Structure under Corporateand Personal Taxation”, Journal of FinancialEconomics Vol. 8, p. 3-29.[13] Demirguc-Kunt, A., &Maksimovic, V. 1999,“Institutions, financial markets and firm debtmaturity”, Journal of Financial Economics,Vol. 54, p. 295-336.[14] Diamond, D.W. 1993, “Seniority and maturityof debt contracts”, Journal of FinancialEconomics, Vol. 33, p. 341-68.[15] Elyasiani. E., Guo, L., & Tang, L. (2002). Thedeterminants of debt maturity at issuance: Asystem-based model. Review of QuantitativeFinance and Accounting, Vol. 19, p. 351-377.[16] Flannery, M. J. 1986, “Asymmetricinformation and risky debt maturity choice”,Journal of Finance, Vol. 41, p. 19-37.[17] Fama, E. F. dan K. R. French 2002, “TestingTrade-Off and Pecking Order Predictionsabout Dividends and Debt”, Review ofFinancial Studies, Vol. 15, p. 1-33.[18] Harris, M., &Raviv, A. 1991, “The theory ofcapital structure”, Journal of Finance, Vol. 46,p. 297-355.[19] Johnson, S. A. 2003, “Debt maturity and theeffects of growth opportunities and liquidityrisk on leverage”, Review of Financial Studies,Vol. 16(1), p. 209-236.[20] Leland, H.E., &Toft, K.B. 1996,“Optimalcapital structure, endogenousbankruptcy, and the term structure of creditspreads”, Journal of Finance,Vol. 51, p. 987–1019.[21] Marsh, P. 1982, “The choice between equityand debt: An empirical study”, Journal ofFinance, Vol. 45, p. 1471–1493.[22] Megginson, W.L. 1997, “Corporate FinanceTheory”. Addison Wesley EducationalPublishers.[23] Modiglini, F., & Miller, M.H. 1995, “The costof capital, corporate finance and the theory ofinvestment”, American Economic Review,Vol. 48, p. 201-97.[24] Myers, S.C. 1977, “Determinants of corporateborrowing”. Journal of Financial Economics,Vol. 5, p. 147–175.[25] Muradoglu, G. Y., and Sivaprasad, S. 2009,“Using firm level leverage as an investmentstrategy”, SSRN Working Paper Series.[26] Mustapha, M., Ismail, H., &Minai, B. 2011,“Determinants of debt structure: Empiricalevidence from Malaysia”, 2 nd InternationalConference on Business and EconomicResearch Proceeding.[27] Ozkan, A. 2002, “The determinants ofcorporate debt maturity: evidence from UKFirms”, Applied Financial Economics, Vol. 12(1), p. 19-24.Vol. 2 No. 1 September 2012Hal - 15

Forum Bisnis Dan KewirausahaanJurnal Ilmiah STIE MDP[28] Rajan, R.G., &Zingales, L. 1995, “What dowe know about capital structure? someevidence from international data”, The Journalof Finance, Vol. 50(5), p. 1421 – 1460.[29] Spiegel, Yossef.,& Daniel F. Spulber, 1994,“The capital structure of a regulated firm”,Rand Journal of Economics, Vol. 25, p. 424-440[30] Sunarsih 2004, “Analisissimultanitaskebijakan hutang dan kebijakan maturitashutang serta faktor-faktor yangmempengaruhinya”, JurnalSiasatBisnis, Vol.9(1), p. 65-84.[31] Stohs, M. H., & Mauer, D. C. 1996, “Thedeterminants of corporate debt maturitystructure”, Journal of Business, Vol. 69, p.279- 312.[32] Titman, S., &Wessels, R. 1988, “Thedeterminants of capital structure choice”,Journal of Finance, Vol. 43, p. 1–19.Hal - 16 Vol. 2 No. 1 September 2012