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Determinants of the capital structure of listed Vietnamese companies.

I. Introduction

Vietnam is one of the most dynamic economies in the Asia-Pacific region and has experienced dramatic changes in its financial system in recent years. Accordingly, Vietnamese enterprises are increasingly able to seek financial capital through stock and bond markets, in addition to traditional sources such as bank lending and trade credit. This paper explores whether these changes have altered the capital structure of Vietnamese companies. Thus, we study the capital structure of listed Vietnamese companies in the broader context of financial development (the recent expansion of domestic equity and debt capital markets). Previous research on the capital structure of Vietnamese enterprises is limited. Vietnam is absent in international analyses of capital structure in emerging markets (e.g. Booth et al. 2001; Deesomsak, Paudyal and Pescetto 2004; Lucey and Zhang 2011), and only two country-specific peer-reviewed studies are discernible (Nguyen and Ramachandran 2006; Biger, Nguyen and Hoang 2008).

We enhance the understanding of capital structure in Vietnam relative to the extant literature (Nguyen and Ramachandran 2006; Biger, Nguyen and Hoang 2008) in a number of ways: (i) we examine a large sample of listed companies whilst most prior work has focused on unlisted companies and SMEs; (ii) we cover the period 2007-11 with prior work examining the period up to 2003 (1)--this is critical since there have been major changes in Vietnam's financial system in recent years (see discussion in section II); and (iii) within this context, we compare the financing policies between state-owned enterprises (SOEs) and private corporations. Accordingly, we provide the first insights into the capital structure of listed companies in one of the most dynamic emerging markets in the world (see Table 1).

From a more academic perspective, it is noteworthy that the capital structure literature has consistently found considerable differences in the capital structures of developed, as distinct to emerging country, companies. For instance, in countries with developed bond capital markets, pecking order theory is supported, whereas in developing countries a "modified" pecking order is observed (i.e., internal finance, equity and debt) (see, for instance, Chen 2004; Delcoure 2007). Further, studies in developed economies find a negative relationship between growth and debt ratios (Rajan and Zingales 1995; Wald 1999), while studies in developing countries indicate that firms finance their growth with debt (especially bank loans) (Chen 2004; Delcoure 2007; Biger, Nguyen and Hoang 2008). These differences are attributed to stronger financial systems in developed countries, as reflected in deeper capital markets and more competitive banking sectors. This is important from a broader macroeconomic perspective, since there is an association between financial development and economic growth, as evidenced in an established literature (see, for instance, Love 2003) that includes evidence specific to the case of Vietnam (O'Toole and Newman 2012). Though as noted by Guariglia and Poncet (2008), in the case of China, at least, rapid growth has been possible despite the existence of large financial distortions.

To summarize, this paper provides the first insights into the capital structure of listed companies in Vietnam in the broader context of rapid financial development. We do so by employing a panel GMM (generalized method of moments) system estimator to analyse the determinants of the capital structure of 116 non-financial firms listed on either the Ho Chi Minh Stock Exchange or the Hanoi Stock Exchange for the period 2007-11. The rest of this paper is structured as follows: section II describes the context leading to, and provides measures of, Vietnam's recent financial development. Section III reviews the theoretical and empirical literature on capital structure. Section IV develops hypotheses, discusses the data employed and specifies the econometric model utilized. Section V presents the empirical results, while section VI discusses the results and provides related conclusions.

II. The Vietnamese Context

In 1986, Vietnam implemented Doi Moi, a policy which set in motion the transformation from a centrally-planned to a market-oriented economy. As part of this liberalization process, the government promoted private ownership and, in 1992, launched a state-owned enterprise (SOE) reform programme. At the heart of this programme is "equitization" by transforming SOEs into joint stock companies so as to enhance their financial autonomy and efficiency. Most SOEs were privatized, with the government keeping control of key industries such as airlines, electricity and telecommunications. As a result of these changes, two stock markets were established. (2) Ho Chi Minh Stock Exchange (HOSE) was founded in July 2000, while the second exchange, the Hanoi Stock Exchange (HNX), was founded in March 2005. HNX is mainly for small- and medium-sized enterprises.

Two decades on, the impact of these reform processes are clearly evident, both in terms of an increased role of private firms and private capital in the economy and in terms of the relative decline in the importance of SOEs (see Table 1). There has been an impressive reduction in the number of SOEs (from around 12,000 in 1991 to 1,200 in 2010) as well as a reduction in the public sector's share of total profits and investment (IMF 2010; World Bank 2012). The equitization of the economy is apparent from Table 1. Starting with five listed stocks with market capitalization accounting for 0.2 per cent GDP in 2000, the two stock exchanges now have 700 firms with a capitalization equivalent to 20 per cent of GDP in 2011. As they develop and mature, these nascent equity markets have experienced high volatility (see Figure 1).

The bond market is at an even earlier stage of development (see Table 1). Most local currency bond issuance is from the government or government-sponsored institutions. Vuong and Tran (2010) note that the corporate bond market has been in existence since the early 1990s; however, it has been small in scale and only in recent years has it grown to a meaningful size (see Table 1). Overall the bond market only accounts for about 15 per cent of GDP, which is well below the East Asian average of about 65 per cent (see Leung 2009).

Historically, Vietnam has had a bank-based financial system (Kovsted et al. 2003). Despite the development of equity and bond markets, Vietnam remains principally a bank-based financial system. This is evident from a bank credit to GDP ratio of 121 per cent in 2011, which places the equivalent ratios for equity and corporate bond markets into context (see Table 1). Further, it is evident that over the last decade there has been a strengthening of the banking system. This is apparent from Table 1, where key banking ratios indicate that banks have become more profitable, stable and cost-efficient, as well as having to operate in a more competitive environment. III. III.

III. Literature Review: Capital Structure

Research on capital structure originated from the irrelevance theory of Modigliani and Miller (1958) (henceforth referred to as MM). In response, optimal capital structure (Stiglitz 1969; Jensen and Meckling 1976) and finance hierarchy theories have emerged, yet they adopt competing approaches. The former suggests firms have a targeted gearing ratio at which the benefits of debt's tax-shield balances out with agency and financial distress costs. By way of contrast, the latter rejects the existence of well-defined leverage, with issues of information asymmetry and transactions costs determining a preference for internal equity followed by debt and with external equity being last in the pecking order (Myers 1984).

III.1 The Influence of Contextual Factors

A wide range of empirical research has been undertaken to examine the validity of the trade-off and pecking order theories. The empirical literature tends to focus on testing theoretical predictions about the impact of firm-specific factors on leverage (see section IV. 1) and exploring the influence of external and contextual factors, such as market conditions and institutional characteristics.

Contextual factors that are particularly relevant to the Vietnamese context are the level of capital market development and ownership structure. For instance, in the former case, evidence for the United Kingdom by Marsh (1982) and for the United States by Friend and Lang (1988) supports the pecking order theory. In contrast, research in developing and transitioning economies finds a "modified" pecking order (i.e., internal finance, equity and debt) (see Chen 2004; Delcoure 2007). In these countries, underdeveloped bond markets drive firms to equity issuance for long-term financing.

Ownership structure is another factor that can influence capital structure; be it family controlling interests (Bunkanwanicha, Gupta and Rokhim 2008) or the impact of state ownership (Rajan and Zingales 1995). In the latter case, Bradley, Jarrell and Kim (1984) and Booth et al. (2001) acknowledge government influence on firms' debt policy. In particular, the former recognizes that highly geared firms dominate state-regulated industries like electricity or airlines, while the latter reports state credit programmes granted to preferred sectors (for example, agriculture in Thailand).

Another example comes from China, where most of the listed firms are equitized SOEs or formerly SOEs. Chen (2004), using data from 1995 to 2000, concludes that these firms are protected from bankruptcy by the government, causing the pecking order and trade-off models to have limited explanatory power in China. However, Huang and Song (2006) report an insignificant relationship between leverage and state ownership when analysing a much larger data set spanning 1994 to 2003. This might imply that equitized Chinese SOEs are gradually becoming more independent from government.

III.2 The Capital Structure of Vietnamese Firms

Despite the established nature of the empirical literature on capital structure, a shortage of research in the Vietnamese context is apparent. As was mentioned above, Vietnam is absent in international analyses of capital structure in emerging markets (e.g. Booth et al. 2001; Deesomsak, Paudyal and Pescetto 2004; Lucey and Zhang 2011) and only two country-specific peer-reviewed studies are discernible (Nguyen and Ramachandran 2006 and Biger, Nguyen and Hoang 2008).

Nguyen and Ramachandran (2006) explore the capital structure of 558 small and medium-sized enterprises (SMEs) for the period 1998-2001, while Biger, Nguyen and Hoang (2008) explore a larger sample of 3,778 mainly unlisted enterprises for the period 2002-2003, (3) This body of evidence indicates that Vietnamese firms relied mostly on short-term bank loans rather than equity, since equity markets were nascent in the periods covered by the research. With respect to the determinants of capital structure, commonly observed factors in the international empirical literature such as size and profitability are applicable to Vietnam (see section IV.1). However, the impact of growth and tangibility raised some contrasting evidence. Nguyen and Ramachandran (2006) find that firm growth is positively associated with short-term debt, as high-growth firms have a high demand for working capital. Further, tangibility had a negative relationship with gearing. According to Nguyen and Ramachandran (2006), this is due to the dominance of short-term debt in total debt, which does not necessarily require collateral. Biger, Nguyen and Hoang (2008) add that Vietnamese banks paid more attention to liquidity than tangibility because they were mainly granting short-term loans.

In addition to universally observed factors, these studies also research some Vietnam- specific factors. For instance, they consistently prove that SOEs have more debt than their private counterparts due to their close relationship with state-owned banks. More interestingly, when "networking" and "social relationship with banks" are included into the regression model, profitability becomes insignificant (Nguyen and Ramachandran 2006). This might imply that some factors are far more important than profitability in helping firms access bank loans in Vietnam.

Some limitations in these prior studies on Vietnamese capital structure highlight the need for further research. Firstly, most prior work focused on unlisted companies and SMEs. Second, as acknowledged by Nguyen and Ramachandran (2006), the reliability of data employed in previous studies is questionable, as financial information was drawn from unaudited statements. Finally, with data sets dating back to 1998-2001 and 2002-03 for Nguyen and Ramachandran (2006) and Biger, Nguyen and Hoang (2008), respectively, their findings reflect an outdated context. For instance, during the period 1998-2003, Vietnam was in the early stages of transition from a command to a market economy; it is therefore understandable that distortions in financing activities (i.e., social relationships with banks) should have still been dominant. Similarly, as state-owned firms dominated the economy, close relationships between SOEs and leverage was understandable. However, the question remains whether the subsequent development of stock and bond markets, coupled with the continuing restructuring and equitization of SOEs, has altered the nature of the capital structure in Vietnam enterprises (see section II and Table 1).

IV. Methodology

IV.1 Hypotheses

In this section, we develop testable hypotheses on characteristics determining the debt ratios of Vietnamese listed firms. We do so by exploring universally observed and frequently researched determinants (i.e., profitability, tangibility, size, growth opportunity and liquidity) (see Frank and Goyal 2009; Welch 2011) and a country-specific factor (i.e., state ownership).

Theoretical predictions about the relationship between profitability and leverage are inconsistent. For instance, according to trade-off theory, profitable firms should borrow more, as they need to shield income from tax. Pecking order theory anticipates a negative relationship. As internal financing is the most favoured source of finance, profitable firms with available retained earnings will borrow less. Despite the theoretical dispute, most empirical evidence, including Fama and French (2002), confirm the negative relationship between profitability and leverage. More notably, international studies such as Rajan and Zingales (1995) for the G7 economies and Wald (1999) for some developed economies confirm the negative impact of profitability across countries.

H1: There is an inverse relationship between profitability and leverage/liabilities as profitable firms prefer internal funds to finance their business.

Both theoretical models and empirical analyses mostly confirm that companies with more tangible assets are highly geared. In developing countries, the agency issue and information asymmetry between firms and lenders can be pronounced (Booth et al. 2001; Chen 2004; Nguyen and Ramachandran 2006). This is evident in the case of Vietnam where the legal system is still perceived as weak, and as a result credit is extended principally on the basis of collateral or relationships (Leung 2009; Nguyen and Ramachandran 2006).

H2: Tangibility positively relates to leverage! liabilities because collateralized assets significantly mitigate the information asymmetry and agency cost between lenders and borrowers.

Generally, capital structure theories predict that large firms are more leveraged. For instance, large firms may have greater bargaining power with lenders, thereby lowering their cost of debt. Further, larger firms are less likely to be adversely affected by information asymmetry problems than small ones, as they are better known and are willing or required to disclose more information (Rajan and Zingales 1995). Most international empirical research confirms theoretical propositions (e.g. Friend and Lang 1988; Frank and Goyal 2009). This is also true for Vietnam, where studies report a positive relationship between size and leverage (Nguyen and Ramachandran 2006; Biger, Nguyen and Hoang 2008).

H3: Size favourably influences leverage/liabilities since large firms have less pronounced information asymmetry problems.

Capital structure theories disagree over the relationship between firm growth and gearing. According to the agency cost model, financial covenants and restrictions imposed by lenders leave less flexibility for firms to pursue investment opportunities; thus firms with growth potential will avoid debt. In contrast, pecking order theory predicts that high-growth firms often exhaust internal funds so they subsequently employ the second preferred source of finance: debt. On the empirical side, studies in developed economies find a negative relationship between growth and debt ratios (Rajan and Zingales 1995; Wald 1999). However, studies in developing countries, including those for Vietnam, indicate that firms finance their growth with debt (especially bank loans) (Chen 2004; Nguyen and Ramachandran 2006; Delcoure 2007; Biger, Nguyen and Hoang 2008).

H4: Growth is positively related to leverage! liabilities as found by the majority of empirical studies in developing countries.

Intuitively, creditors regard liquidity as an indicator of a firm's ability to fulfil short-term debt obligations, so high liquidity should enable better access to debt capital. However, according to pecking order theory, firms with accumulated cash and liquid assets will prefer this available internal fund over borrowing. This negative relationship is consistently reported in empirical analyses (e.g. Deesomsak, Paudyal and Pescetto 2004; de Jong, Kabir and Nguyen 2008). There is limited evidence on liquidity in the Vietnamese context. This factor is important in understanding short-term sources of finance, and is particularly relevant in developing countries like Vietnam where current liabilities tend to be dominant elements of the capital mix (Vuong and Tran 2010).

H5: Liquidity has an adverse impact on leverage! liabilities since high-liquid firms have available internal funds to finance their business.

From the discussion in section III, it is evident that ownership structure is another factor that can influence capital structure and that related evidence in the Vietnamese context shows that state-controlled firms are more leveraged due to their relationship with state-owned commercial banks (SOCBs) (Nguyen and Ramachandran 2006; Biger, Nguyen and Hoang 2008). However, since these studies were undertaken, considerable changes have been enacted in the Vietnamese economy, including the development of equity and capital markets and the continued equitization and restructuring of SOEs (see section II). Accordingly, it is feasible that SOEs have become gradually more independent from the state in their financing activities (IMF 2010). Despite this possibility, we hypothesize that there remains a positive relationship between SOEs and leverage, since capital markets are still relatively undeveloped and the government still maintains control of key sectors, especially the commercial banking system.

H6: Ceteris paribus, state-owned firms are more leveraged/have higher liabilities than non-state-owned counterparts.

In line with the previous hypotheses (that is, H4 and H6), we hypothesize that Vietnam will continue to exhibit the capital structure characteristics of a developing country (see discussion in section III.1). This contrasts with the traditional measures of financial development (Rajan and Zingales 2003), such as deposits to GDP and number of listed firms to population, that in the case of Vietnam suggest there has been rapid financial development in terms of domestic capital markets and the banking system (see section II). Results in line with H7 would suggest financial development in Vietnam is still at an early stage despite the impressive statistics presented in Table 1.

H7: Vietnam will continue to exhibit the capital structure characteristics of a developing country.

IV.2 Data

The data used are from the audited financial statements of listed firms available in a database provided by FPT Securities Company. A stratified random sampling technique based loosely on industry classification was employed. Sampling firms on industry classification is relevant, since the nature of each industry also influences the capital structure of firms (Titman and Wessel 1988). Given that data quality and availability were far from perfect in the earlier three years of our sample, some "re-sampling" occurred when the securities selected did not have the available data for the relevant years. This allowed us to have a balanced panel. Our sample represented 66 per cent of the Bloomberg VNINDEX index and 16 per cent of the Bloomberg VNHINDEX as the indices stood on 2 January 2007 and 3 August 2007, respectively. Although that latter number seems low, it is noteworthy and indicative of data issues in the early stage of market formation in Vietnam that not all the stocks included in our sample were included in the two Bloomberg indices. Accordingly, our sampling was based on a broader universe than was available at the time through these two indices.

Table 2 describes the sample in terms of industry classification and ownership. The sample consists of 116 non-financial firms listed on HOSE and HNX. Our data cover the period 2007 to 2011. In terms of 2014 market weights, twenty-one of the firms in our sample are among the top fifty companies as measured by market capitalization.

Table 3 lists the company-specific dependent and independent variables used to test hypotheses 1 to 6. We use only book values in our measures of total, short-term and long-term leverage (TLEV, SLEV and LLEV, respectively; see Tables 2 and 3). This is because reliable market values for debt and equity are difficult to obtain since the financial system is largely bank-based, the corporate bond market has low liquidity and equity markets are highly volatile (see Figure 1 and Table 1). Further, due to Welch's (2011) critique of gearing measures that ignore trade credit, we use total liabilities in our measurement of TLEV and SLEV. This is particularly important in the context of Vietnam, given the popularity of trade credit as a financing tool (Nguyen and Ramachandran 2006).

With respect to the independent variables, measures that are standard in the literature generally or common in the past studies on Vietnam are employed for PROF, TANG SIZE, GROW and LIQ in order to maximize comparability (see Table 3). (4) With respect to STATE, a dummy variable was constructed where firms with over 50 per cent of state-owned shares were assigned a value of 1.

Table 4 provides the correlation coefficients among the company-specific variables. For the dependent variables, Table 4 also reports tests for multicollinearity. VIF values are well below 10, and the average VIF is very close to 1.

IV.3 Model Specification

Following from the discussion above, we define our model for our three measures of total, short-term and long-term leverage (TLEV, SLEV and LLEV) as

[LEV.sub.i,t] = [[beta].sub.0] + [[beta].sub.1] [PROF.sub.i,t] + [[beta].sub.2] [TANG.sub.i,t] + [[beta].sub.3] [SIZE.sub.i,t] + [[beta].sub.4] [GROW.sub.i,t] + [[beta].sub.5] [LIQ.sub.i,t] + [[beta].sub.6] [STATE.sub.i] + [[beta].sub.7] [TAX.sub.i] + [[beta].sub.8] [IND.sub.i] + [[epsilon].sub.i,t] (1)

We control for industry (IND) and corporate tax (TAX), since the tax rate changed during the period of our analysis (see Table 1). Further, in line with the extant literature, we use averages of the time-varying company-specific variables (PROF, TANG, SIZE, GROW and LIQ) to reduce noise and account for slow adjustment (see Rajan and Zingales 1995).

IV.4 Model Estimation

We estimate a panel estimator, so in the econometric model we need to include [a.sub.i] and [b.sub.t], where [a.sub.i], captures the time-invariant unobserved firm-specific fixed effects, and [b.sub.t] captures the unobservable individual-invariant time effects.

In order to evaluate the type of panel estimator that we implement, we formally test the explanatory variables for endogeneity, with the use of a Hausman test for the hypothesis that the explanatory variables are strictly exogenous. If the null hypothesis is rejected, it leads to the conclusion that the explanatory variables in our econometric specification are endogenously determined. In our empirical estimates, the Hausman test rejects the null hypothesis at all conventional significance levels. This leads to the conclusion that we need to tackle the econometric issue of endogeneity for our explanatory variables.

Initially, we embark upon the use of the single-equation GMM panel estimator developed by Arellano and Bond (1991) to deal with the endogeneity of our explanatory variables. We implement the GMM single-equation estimator instead of the two-stage least squares method because, as mentioned in Biom and Klette (1999), the GMM is asymptotically efficient under nonrestrictive assumptions about error autocorrelation and heteroscedasticity. We test the validity of the instruments with the use of the Sargan test under the null hypothesis that the instruments used are valid. The Sargan test results in a p-value of zero, confirming that the instruments used are not valid. The fact that the GMM single-equation estimator yields invalid instruments suggests that the empirical findings in our analysis based on this estimator would be weakened. The results of the Sargan test of the GMM single-equation estimator are not reported by the authors, but are available upon request.

A possible reason for the weak instruments in our study is that the time dimensions of the panels are very small (five time series observations). The single-equation estimator suffers from the problem of weak instruments when the time series component of the panel is small. This implies that there is a weak correlation between the regressors and the instruments. As a result of this problem, the estimated coefficients suffer from poor precision (see, among others, Staiger and Stock 1997). We can overcome this problem by using the panel GMM system estimator proposed by Blundell and Bond (1998), which radically reduces the imprecision associated with the single-equation estimator.

A system of equations in first differences and levels is estimated by the GMM system estimator. The system estimator combines the standard set of transformed equations in first differences (used in the GMM single-equation estimator) with an additional set of equations in levels. The first set of transformed equations continues to use the lag levels as instruments. The level equation, on the other hand, uses the lagged first differences as instruments. Their validity is based on the following two moment conditions: (5)


where Y represents the dependent variables, W denotes the explanatory variables in our econometric specification and z represents the lag structure of the GMM estimator. In addition to reducing the poor precision of the GMM single-equation estimators, the GMM system has the added advantage of dealing with explanatory variables being jointly determined with the independent variables. (6)

V. Results and Discussion

V.1 Descriptive Results

In Table 3, it is reported that total leverage of Vietnamese firms is 48 per cent, which is slightly lower than the 52 per cent observed during the 2002-03 period by Biger, Nguyen and Hoang (2008). This is possibly due to differences in the size of firms being analysed or it may reflect the increasing popularity of equity finance as attested by the rising number of listed firms (see Table 1). However, the still relatively underdeveloped nature of equity and bond capital markets is apparent in that, consistent with past research, firms continue to be heavily reliant on short-term financing (SLEV = 37 per cent; LLEV =11 per cent). Our sample had a higher profitability (PROF = 10 per cent) and growth rate (GROW = 36 per cent) over the 2007-11 period than the unlisted sample in Biger, Nguyen and Hoang (2008) covering the period for 2002 to 2003 (PROF = 3 per cent and GROW = 17 per cent). This is most likely due to listing requirements that ensure firm profitability.

Table 2 highlights the difference in terms of leverage between industries and reports the proportion of state-owned firms in each industry. Generally, state-owned firms have higher ratios in all three measurements of debt (TLEV = 51.65 per cent; SLEV = 38.06 per cent; LLEV = 13.59 per cent). Nevertheless, an independent t-test only confirms the statistical difference between two groups in TLEV (p<.1). Further, though there are no significant differences in profitability, size and liquidity, the two groups are divergent in their tangibility (p<.10) and growth (p<.1). State-owned firms possess more fixed tangible assets, while non-state-owned firms experience rapid growth. This is understandable since state-owned firms tend to dominate fixed-asset-intensive industries such as construction and public utilities. Private firms, by way of contrast, dominate the high-growth electronics-technology industry.

V.2 Econometric Results

Table 5 presents the results of the econometric analysis of equation (1). We need to mention that in all cases the fixed and time effects are significant, suggesting that the company and time-specific shocks differ significantly across the firms in our sample, justifying the use of the panel. In addition, all estimated models pass the diagnostic tests. The Jarque-Bera normality test indicates that the residuals of the models are normally distributed, implying that the empirical estimates obtained are not due to any outliers in the data. The Sargan tests confirm the validity of the instruments in all GMM system models. We further test the validity of the GMM system estimator by performing the Hansen J Statistic to establish if the over-identified restrictions of the estimator are equal to zero. Our results show that we cannot reject the null hypothesis that the over-identified restrictions of the GMM are equal to zero. This confirms that our empirical model is correctly specified.

The models for TLEV and SLEV have high explanatory power ([R.sup.2] of 0.59 and 0.50), respectively. The model for LLEV, however, had a good deal less explanatory power ([R.sup.2] of 0.46), hinting that a broader range of factors drive long-term finance decisions. With respect to the explanatory variables, Table 6 shows that the results are, in general, in line with the hypotheses (section IV. 1) and past studies on capital structure in the Vietnamese context.

Profitability (PROF) has a significant and negative relationship with all measures of leverage. This lends strong support for hypothesis 1 and pecking order theory in that all other things being equal, firms prefer internal sources of finance. (7)

With respect to hypothesis 2, the impact of tangibility varies by measure of capital structure. Tangibility is not a relevant determinant of total leverage (TLEV); however, it is significant in predicting short-term (SLEV) and long-term leverage (LLEV), but in opposite directions. Indeed, tangibility exerts the second-largest effect on debt ratios just behind profitability. The negative association of TANG to SLEV is consistent with prior Vietnamese studies (Nguyen and Ramachandran 2006; Biger, Nguyen and Hoang 2008). One interpretation of this relationship is that firms with few tangible assets tend to rely more on short-term liabilities such as trade credit (see section IV). Conversely, the positive association between TANG and LLEV reflects high information asymmetry and agency costs (Leung 2009) that make Vietnamese banks reliant on collateral as the primary credit risk tool. This evidence is in line with international findings (see Chen 2004; Frank and Goyal 2009).

The results for the impact of SIZE on capital structure are in line with hypothesis 3 and in line with past research in Vietnam (see Table 6). The message is clear, namely that firm size enhances long-term and short-term borrowing capacity from commercial banks.

As predicted by hypothesis 4, GROW is positively associated with TLEV and LLEV, though the relationship with SLEV is not statistically significant. The latter is perhaps not surprising, since short-term creditors are more concerned with liquidity than long-term prospects. More generally, the results with respect to GROW confirm previous findings for Vietnam (see Table 6) and in emerging markets more generally. This should be a disappointment to policy-makers in Vietnam, since in developed countries with deep capital markets, the relationship tends to go in the other direction because high-growth enterprises finance their expansion through the equity issuance (Rajan and Zingales 1995; Wald 1999). Accordingly, the fact that our research confirms the findings of previous research in Vietnam some ten years on indicates that the development of equity markets in Vietnam in the intervening period has been limited, with high-growth firms still relying principally on bank debt.

The results presented in Table 5 generally support hypothesis 5, since liquidity (LIQ) is negatively associated with TLEV and SLEV. There is, however, no statistically significant relationship between LIQ and LTEV. Unsurprisingly, long-term lenders are more interested in growth (GROW) and tangibility (TANG) than liquidity. The negative relationship between LIQ and TLEV and SLEV is, nevertheless, consistent with pecking order theory in that it indicates that liquid firms prefer to use accumulated cash and liquid assets rather than resorting to external finance. Since previous studies on Vietnamese capital structure did not explore liquidity variables, this is an addition to the literature (see Table 6).

With respect to hypothesis 6, the empirical analysis finds that state ownership (STATE) positively influences TLEV and SLEV but has no impact on LLEV. This result is consistent with the Vietnamese literature, where a positive relationship between state ownership and leverage is consistently found (see Table 6). Unfortunately, neither Nguyen and Ramachandran (2006) nor Biger, Nguyen and Hoang (2008) has an equivalent variable to our LLEV, so it is difficult to know whether the absence of a relationship between STATE and LLEV can be attributed to the equitization of SOEs and the development of capital markets in Vietnam (see section II).

Irrespective of what is driving the result with respect to LLEV, the overriding conclusion is that the state still plays an important role in overall leverage (TLEV) and short-term financing (SLEV). This finding puts the equitization programme and the development of capital markets in context. Key sectors, such as construction, public utilities and finance, remain largely under actual or tacit government control. Further, the government can act as a tacit or actual debt guarantor for those firms it dominates, leading to better access to credit for those firms thanks to lower bankruptcy and agency costs; indeed, bankers feel it is safer to lend to companies that have some connection with the government (Malesky and Taussig 2009). The government can also grant financial support through industrial policy schemes (via the banking system) that prioritize specific industries, for instance, the agricultural sector and rural areas (Kovsted et al. 2003; Malesky and Taussig 2009).

In line with the above, our results suggest that listed SOEs continue to benefit from having a close relationship with SOCBs. This is understandable since the restructuring of SOCBs is in its early stages; among the five SOCBs, there are three equitized banks in which the government still maintains a large controlling stake. (8) Further, the preponderant joint stock banks (JSBs) (purportedly private banks) in Vietnam were subject to considerable direct and indirect state influence, since the state, SOEs and SOCBs all held substantial amounts of equity in these banks. Hence, listed SOEs can take advantage of their relationship with both SOCBs and JSBs to increase their borrowing capacity. The large SOE sector would appear to be "the source of an uneven playing field" (WB 2012, p. 42), supported by the fact that the SOEs tend to get preferential access to banking credit as well as to funds mobilised from the government's international bond issuances and overseas development assistance.

The preceding analysis paints a picture of inertia in the capital structure of Vietnamese enterprises. Despite the equitization of the economy and measures of financial development suggesting considerable financial development has been achieved (see section II and Table 1), capital structures remain dominated by short-term finance and state influence (H6), while growth firms continue to finance via debt (H4). This is in line with H7, suggesting that the process of financial development in Vietnam is not complete. This is, in turn, broadly consistent with the literature on capital structure in developing countries which has pointed out some key financing patterns. Firms in these countries have tended to prefer and rely on short-term debt/liabilities (Chen 2004; Delcoure 2007). The ownership structure also helps to explain the peculiar capital structure in developing countries; firms with governmental links are more likely to have access to bank credit (Deesomsak, Paudyal and Pescetto 2004; Li, Yue and Zhao 2009). Firms with growth opportunities also tend to finance with bank debt rather than other sources of capital due to underdeveloped bond markets and high costs of equity issuance (Booth et al. 2001; Chen 2004).

VI. Conclusion

This paper explored the capital structure of listed Vietnamese firms. We employed a panel GMM system estimator to analyse the determinants of the capital structure of 116 non-financial firms listed on either the Ho Chi Minh Stock Exchange or the Hanoi Stock Exchange for the period 2007-11. The determinants of three different measures of leverage (total leverage, short-term leverage and long-term leverage) were explored relative to firm-specific factors (profitability, tangibility, size, growth opportunity and liquidity) and an economy-specific factor (state ownership).

From this analysis, we concluded that, despite the emergence in recent years of equity and (to a lesser extent) a corporate debt capital market, the capital structure of Vietnamese enterprises is still dominated by the use of short-term financing sources. The results indicate that profitability and liquidity negatively affect leverage, while growth and state-ownership exert a positive impact. The influence of size and tangibility diverges across the different measures of leverage; they have a positive relationship with long-term leverage but a negative effect on short-term leverage. Determinants are also different in the extent of their influence. Among the studied factors, profitability and tangibility have the largest impact on leverage ratios. Some factors like size, tangibility and growth opportunity are more relevant to long-term debt, while liquidity relates more to short-term leverage. From these results, it is clear that pecking order theory better explains financing decisions in Vietnam than tradeoff theory.

Further, the significant impact of country-specific factors like state-ownership confirms the importance of institutional differences in understanding capital structure. Accordingly, our results show that state-controlled enterprises continue to have preferential access to finance and that high-growth firms still rely principally on external debt rather than on equity issuance. These results indicate that policy-makers need to continue to pursue policies that will deepen capital markets and ensure that bank finance is allocated on a purely commercial basis.

The relative immaturity of capital markets in Vietnam should be an issue of concern to policymakers, since Lee (2012) finds that financial system development is an important lead indicator or precursor to economic expansion whether the financial system is bank-based or market-based. Further, Lee (2012) finds that in nearly all cases, the development of a banking system and the development of capital markets are complementary. Consequently, policy-makers should ensure that Vietnamese equity and corporate bond markets continue to develop, even if the financial system is to remain principally bank-based (see Table 1). This will give Vietnamese corporations much greater flexibility in financing and will inevitably lower the cost of capital, resulting in capital structures governed by corporate needs and efficient allocation of capital rather than based on legacy relationships with the banking system. As Leung (2009, p. 47) put it in her assessment of Vietnamese finance:

   regulatory prejudices and the inability to address
   asymmetric information problems have resulted,
   either directly or indirectly, in discriminatory
   access to finance in favour of state-owned
   enterprises (SOEs), with adverse implications
   both for the development of the domestic private
   sector and macroeconomic stability.

This noted, it is understandable why, in some contexts such as the agricultural and rural sectors, explicit policies, tacit influences and interventions may be used as transitory measures to cushion the harsher effects of market forces. In the long term, however, such actions tend to be self-defeating (Kovsted et al. 2003).

Overall, our analysis of the capital structure of Vietnamese companies in the context of financial development uncovered an interesting paradox. On the one hand, conventional measures of financial development used by multinational institutions such as the World Bank suggest rapid and substantive progress in both the banking system and in domestic capital markets (especially equity capital markets) (see section II).

On the other hand, our results show that the capital structure of Vietnamese enterprises is still dominated by the use of short-term financing sources. State-controlled enterprises continue to have preferential access to finance, and high-growth firms still rely principally on external debt rather than equity issuance. These results contrast with the equivalent results of capital structure studies in developed countries. The suggestion is that financial development is still at an early stage; this is not to say that the financial development that has occurred has, thus far, not had a beneficial impact. A recent study by O'Toole and Newman (2012) suggests that the financial development that has occurred in Vietnam has had a positive impact on economic growth. Thus, though there has been financial development and associated benefits from this progress, our results indicate that there is a need and scope for considerably more financial development in Vietnam.

DOI: 10.1355/ae31-3e


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Dung Thuy Thi Nguyen is Lecturer at Department of Banking--Insurance, Academy of Finance, No. 8 Phan Huy Chu Street, Hoan Kiem District, Hanoi, Vietnam; email:

Ivan Diaz-Rainey is Senior Lecturer in Finance at the Department of Accountancy and Finance, University of Otago, PO Box 56, Dunedin 9054, New Zealand; email:


(1.) Note we do not examine the intervening period (2003 and 2006), as most firms listed during 2006 and 2007 (see Table 1).

(2.) See Kovsted et al. (2003) for a detailed historical analysis of Vietnam's multistage process of financial reform arising as a result of Doi Moi.

(3.) Most, if not all, of these firms will have been unlisted, since there were only twenty-two listed firms in 2003 (see Table 1).

(4.) PROF is profitability and is measured as Earning Before Tax scaled by Total Assets; TANG is tangibility and is measured as Tangible Fixed Assets scaled by Total Assets; SIZE is the log of Total Assets; GROW is growth measured by the percentage change in total assets; and LIQ is liquidity measured as the ratio of Current Assets over Current liabilities.

(5.) The time-varying matrix of instruments for the first difference GMM estimator can be observed in Blundell and Bond (1998).

(6.) The three-stage least squares (3SLS) panel estimator also estimates a system of equations simultaneously and is regarded as an alternative to the GMM system estimator. However, we implement the GMM system estimator, given that it accommodates for the possibility of joint determination of an equation system with different instruments for different equations (Schmidt 1990).

(7.) In the extant literature (e.g. Wald 1999; Rajan and Zingales 1995), the more popular measurements of PROF are (EBIT/Total Assets) and (Cash/Total assets) as they can eliminate the influence of capital structure and taxation on profitability. As a robustness exercise, we ran regressions with these two alternative measures of PROF. Both alternatives generated analytically equivalent results for all three measures of leverage/liabilities.

(8.) VIETCOMBANK (Bank for Foreign Trade of Vietnam), VIETINTBANK (Vietnam Joint Stock Commercial banks for Industry and Trade) and BIDV (Bank for Investment and Development of Vietnam) were equitized in 2007, 2008 and 2011, respectively, with the government holding 91 per cent of Vietcombank, 89 per cent of Vietintbank and 78 per cent of BIDV after equitization.

Andros Gregoriou is Professor in Finance at Brighton Business School, Brighton University, Moulsecoomb, Brighton, BN2 4AT, United Kingdom; email:


Vietnamese Indicators of Economic and Financial Development

Indicator                      Variable   2000    2001    2002

Macroeconomic Environment
GNI per cap, PPP (cur.$)                   1400    1510    1620
Population, total (Million)               77.63   78.62   79.54
GDP growth (annual %)                      6.79    6.89    7.08
Corporate Tax Rate (%)         TAX
Real interest rate (%)

Capital Markets
Market return (VN Index)                  110.6   11.8    -22.1
Listed firms                                5     11       20
Listed/Population (million)                 0.06   0.14     0.25
Market/GDP (%)                              0.2    0.3      0.5
Bonds/GDP (%)                               0.3    0.6      0.8
Corp./GDP (%)                               0      0        0

The Banking System
Banking credit/GDP (%)                     35.1    39.7    44.8
Deposits/GDP (%)                            8.4     8.8     9.1
Bank ROE                                   -8.5    -3.8     7.9
Bank Cost-Income Ratio                     57.6    47.6    47.5
Bank Z-Score                                7.5     7.3    10.7
Bank Concentration                         84.2    83.3    81.6

Indicator                      2003    2004    2005    2006    2007

Macroeconomic Environment
GNI per cap, PPP (cur.$)        1750    1920    2120    2330    2560
Population, total (Million)    80.47   81.44   82.39   83.31   84.22
GDP growth (annual %)           7.34    7.79    8.44    8.23    8.46
Corporate Tax Rate (%)                                 28      28
Real interest rate (%)                          2.6     3.6     2.7

Capital Markets
Market return (VN Index)       -9.0    42.1    29.6    144.5    22.5
Listed firms                   22      26      41      193     253
Listed/Population (million)     0.27    0.32    0.50    2.32     3.00
Market/GDP (%)                  0.4     0.6     1.1     22.7    43.3
Bonds/GDP (%)                   2.2     3.5     5       8.3     13.8
Corp./GDP (%)                   0       0       0       0        0.5

The Banking System
Banking credit/GDP (%)         51.8    61.9    71.2    75.4    96.2
Deposits/GDP (%)                9.6    11.0    12.0    12.6    15.0
Bank ROE                       10.2    12.8    11.2    15.3    16.3
Bank Cost-Income Ratio         46.1    51.0    39.9    44.5    36.2
Bank Z-Score                   11.0    11.9    12.5    14.6    24.0
Bank Concentration             79.7    77.3    73.6    67.0    48.9

Indicator                      2008    2009    2010    2011

Macroeconomic Environment
GNI per cap, PPP (cur.$)        2740    2840    3060    3260
Population, total (Million)    85.12   86.03   86.93   87.84
GDP growth (annual %)           6.31    5.32    6.78    5.89
Corporate Tax Rate (%)         28      25      25      25
Real interest rate (%)         -5.2     3.8     1.1    -3.2

Capital Markets
Market return (VN Index)      -66.0    65.0    -6.0    -28.0
Listed firms                    338     457     649      700
Listed/Population (million)     3.97    5.31    7.47     7.97
Market/GDP (%)                 15.2    37.6    45       20
Bonds/GDP (%)                  15.6    13.3    15.4     15.6
Corp./GDP (%)                   0.7     1.2     1.8      1.4

The Banking System
Banking credit/GDP (%)         94.5     123   135.8   120.9
Deposits/GDP (%)               14.7    14.1    14.1
Bank ROE                       12.3    13.3    12.5
Bank Cost-Income Ratio         46.6    47.0    40.9
Bank Z-Score                   25.8    22.2    21.6
Bank Concentration             41.9    42.2    39.4

Sources: Asian Development Bank (2012), World Bank (2012a),
World Bank (2012b) and our own calculations.


Sample Classified by Industry, Ownership and Measure of Leverage

                           Total            firms

                     Number     %     Number    %

Construction           25     21.6      18     15.5
Real Estate            16     13.8      3      2.6
Public Utilities       16     13.8      10     8.6
Electron. & Tech.      12     10.3      3      2.6
Food & Beverage        23     19.8      4      3.4
Natural resources      16     13.8      6      5.2
Drugs                  8       6.9      0      0.0
Total                 116     100.0     44     37.9

                            TLEV                 SLEV

                     Rank   Mean    SD    Rank   Mean    SD

Construction          1     0.64   0.14    1     0.53   0.16
Real Estate           2     0.54   0.17    2     0.35   0.16
Public Utilities      3     0.48   0.19    7     0.28   0.18
Electron. & Tech.     4     0.42   0.19    4     0.33   0.15
Food & Beverage       6     0.40   0.16    3     0.34   0.14
Natural resources     5     0.40   0.20    6     0.32   0.15
Drugs                 7     0.37   0.19    5     0.33   0.17


                     Rank   Mean    SD

Construction          3     0.11   0.14
Real Estate           2     0.18   0.12
Public Utilities      1     0.20   0.20
Electron. & Tech.     4     0.08   0.11
Food & Beverage       6     0.05   0.06
Natural resources     5     0.08   0.07
Drugs                 7     0.04   0.04


Company-Specific Variables and Descriptive Statistics

                Abr.      Variable

Dependent       TLEV        Total
Variables                 leverage
                SLEV     Short-term
                LLEV      Long-term
                PROF    Profitability

Independent     TANG     Tangibility
               SIZE *       Size
                GROW       Growth

                LIQ       Liquidity

               STATE      Ownership

                     Measurement                 References

Dependent       = Total Liabilities /           Welch (2011)
Variables           Total Assets
               = Current Liabilities /          Welch (2011)
                    Total Assets
                = Non-Current Liab. /
                    Total Assets
                  = Earnings before              Nguyen and
                 Tax / Total Assets         Ramachandran (2006);
                                             Biger et al. (2008)
Independent       = Tangible Fixed           Rajan and Zingales
Variables       Assets / Total Assets    (1995); Biger et al. (2008)
                 = LN (Total Assets)      Wald (1999); Chen (2004)
                 = Percentage change     Titman and Wessels (1988);
                   in Total Assets         Nguyen and Ramachandran
                 = Current Assets /       Deesomsak, et al. (2004);
                 Current Liabilities        de Jong et al. (2008)
                  1 = State-Owned;
                 0 = Not State Owned

               Hypoth.    N    Mini.   Maxi.   Mean     SD

Dependent       H1-H6    116   0.10    0.87    0.48    0.20
                H1-H6    116   0.07    0.81    0.37    0.18

                H1-H6    116   0.00    0.60    0.11    0.13

                 H1      116   -0.03   0.34    0.10    0.08

Independent      H2      116   0.00    0.92    0.20    0.18
                 H3      116   10.13   16.30   13.45   1.30
                 H4      116   -0.08   1.52    0.36    0.33

                 H5      116   0.21    21.95   2.51    2.67

                 H6      116   0.00    1.00    0.38    0.49

Note: * An alternative size variable used in the literature
is LN (Sales) (e.g. Titman and Wessel, 1988; Biger, Nguyen
and Hoang 2008). Unreported analyses showed that both
measures provided analogous results.


Correlation Coefficients between Variables and VIF Coefficients

         TLEV       SLEV       LLEV       PROF       TANG

TLEV      1
SLEV      0.757 *    1
LLEV      0.458 *   -0.234 *    1
PROF     -0.374 *   -0.253 *   -0.213 *    1
TANG      0.059     -0.116      0.246 *   -0.081 *    1
SIZE      0.061      0.065      0.003      0.177 *   -0.139 *
GROW      0.016      0.009      0.012      0.064     -0.133 *
LIQ      -0.404 *   -0.427 *   -0.020      0.065     -0.111 *
STATE     0.135 *    0.058      0.078 *    0.017      0.229 *

         SIZE       GROW       LIQ        STATE   Tolerance   VIF

PROF                                              0.789       1.270
TANG                                              0.854       1.170
SIZE     1                                        0.893       1.120
GROW     0.029      1                             0.952       1.050
LIQ     -0.149 *    0.039      1                  0.758       1.320
STATE   -0.085 *   -0.102 *   -0.153 *   1        0.880       1.140

* indicates significance at the 5% level.

Note: All correlations are Pearson correlations apart from
those between STATE and the other variables which are
Kentall's tau correlations.

Econometric Results

                      (1)                (2)                (3)

Variable              TLEV               SLEV              LLEV

Constant        0.32 (2.33) *      0.77 (3.02) *      0.26 (3.11) *
PROF            -1.66 (-6.24)%     -1.23 (-5.62) *    -0.93 (-2.33) *
TANG            -0.03 (-0.99)      -0.33 (-3.72) *    0.22 (4.05) *
SIZE            0.123 (0.44)       0.09 (2.66) *      0.06 (3.02) *
GROW            0.166 (2.44) *     0.110 (-1.65)      0.11 (2.33) *
LIQ             -0.044 (-7.21) *   -0.066 (-7.00) *   0.088 (0.97)
STATE           0.198 (3.36) *     0.140 (2.22) *     0.221 (1.34)
TAX             YES                YES                YES
IND             YES                YES                YES
[a.sub.j]       (0.00)             (0.00)             (0.00)
[b.sub.t]       (0.00)             (0.00)             (0.00)
SE              0.112              0.123              0.100
NORM(2)         (0.55)             (0.40)             (0.28)
Diff Sargan     (0.69)             (0.59)             (0.43)
J Statistic     (0.75)             (0.79)             (0.81)
Hausman test    80.88              82.32              87.88
[R.sup.2]       0.59               0.50               0.46
N               580                580                580

Notes: SE represents the standard error of the panel
estimator, [a.sub.i] and [b.sub.t] are the fixed and time
effects. Sargan tests follow a [chi square] distribution
with r degrees of freedom under the null hypothesis of valid
instruments. Note: The Difference/Sargan test is applicable
to the GMM system estimator due to the transformations
involved. The J statistic is based upon the over identified
restrictions of the GMM system estimator, and is computed to
establish if our model is correctly specified. NORM(2) is
the Jarque/Bera normality test. The Hausman test follows a
[chi square] distribution with 6 degrees of freedom,
resulting in a critical value of 12.59, at the 95%
confidence level. The endogenous explanatory variables in
the panel are GMM instrumented setting, z [greater than or
equal to] 1. (.) are p values, (.) are t statistics, *
indicates significance at the 5% level. N denotes the number
of observations in our sample.

Findings Relative to Hypotheses and Previous Vietnamese Studies

Determinant        Findings          Hypotheses    Previous Studies

Profitability      Negatively        Strong        (a) significant
                   associated with   supports H1     (b) negative
                   TELV, SLEV and

Tangibility        Negatively        Partly        (a) and (b):
                   assoc, with       supports H2     negative
                   SLEV Positively
                   assoc, with

Size               Positively        Strongly      (a) and (b):
                   relates to SLEV   supports H3     positive
                   and LLEV

Growth             Positively        Supports H4   (a) and (b):
                   assoc, with                       positive
                   TLEV and LLEV

Liquidity          Negatively        Supports H5   (a) and (b):
                   assoc, with                       not studied
                   TLEV and SLEV

State Ownership    Positively        Supports H6   (a) and (b):
                   assoc, with                       positive
                   TLEV and SLEV

Source: (a) = Nguyen and Ramachandran (2006).
(b) = Biger, Nguyen and Hoang (2008)
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Author:Nguyen, Dung Thuy Thi; Diaz-Rainey, Ivan; Gregoriou, Andros
Publication:Journal of Southeast Asian Economies
Article Type:Report
Geographic Code:9VIET
Date:Dec 1, 2014
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