"Financial constraints and export decision: evidence from vietnamese manufacturing listed firms in Ho Chi Minh stock exchange"

Le Mai Thy et al | 587 Financial constraints and export decision: Evidence from Vietnamese manufacturing listed firms in Ho Chi Minh Stock Exchange LE MAI THY International University – Vietnam National University HCMC – lemaithy143@gmail.com PHAM DINH LONG HCMC Open University – long.pham@ou.edu.vn NGUYEN KIM THU International University – Vietnam National University HCMC – nkthu@hcmiu.edu.vn Abstract This research investigates the influences of financial constraints on export decision of 75 Vietnamese manufacturing listed firms in HOSE during 2007–2016 The financial constraints are approximated by financial variables including long-term debt to total capital, leverage and liquidity ratios The researcher then estimates the impact of these financial fundamentals on the export decision in population average probit models combing with Bootstrap method The empirical results confirm the negative influence of financial constraints on the decision of participating in the export markets which are consistent with previous theoretical works Financial constrained manufacturing firms are less likely to become exporters than others The robustness check of the findings by adding the interactions between each independent variables with three control variables also confirm the main findings of this research Keywords: export decision; financial constraints; Vietnamese listed firms Introduction On 11th January 2007, Vietnam officially joined World Trade Organization (WTO) (The Ministry of Finance, 2011) This enlarges the export market which creates more opportunities for Vietnamese firms to develop and join the global market, especially for 588 | ICUEH2017 manufacturing firms It is obvious that the growth of a country and its businesses go in tandem with the possibility of exporting and penetrating into foreign market Indeed, enterprises’ expansion beyond national borders is often promoted by the government’s policies, such as those on tax However, such an expansion will face several challenges Roberts and Tybout (1997), Bernard and Jensen (2004), Nguyen and Ohta (2007) have provided evidences of significant fixed (sunk) costs of entry into exporting that affect to firms’ export decision Compared with selling to domestic market, exporting requires higher fixed costs of market entry (Melitz, 2003) and investment expansion Dario Fauceglia (2014) finds that better financial system increases the export probability through the reduction of credit constraints However, for many developing countries where financial system is not advanced, the ability of accessing to financing is another hindrance to firm’s growth because these firms are from small to medium size and need external financing to cover production costs The influences of financial constraints at firm-level have been studied by many researchers (Chor and Manova, 2012; Freund and Clapper, 2009; Correa et al., 2007; Muul, 2012; Chaney, 2005; Berman and Hericourt, 2010) However, most of these researches concentrate on the relationship between financial constraints and the growth and/or the investment decisions of companies In addition, empirical work on the interaction between financial constraints and firm’s export decisions is still few at firm level in developing countries such as Vietnam Therefore, this research aims to fill the research gap for Vietnam, using firm-level data to examine whether financial constraints have influence on the export decision of Vietnamese manufacturing listed firms for the period from 2007 - 2016 Besides the contribution to micro-evidence literature of the impact of financial constraints on international trade, understanding the relation between financial constraints and export decision is helpful for Vietnamese Government to setup policies to develop the financial markets from which encourage firms to export more This study employs the panel data including historical data (e.g., sales, employment, exports, assets, debts proportions and other financial ratios etc.) from the Annual reports, Financial Statements of 75 manufacturing listed firms for period from 2007 to 2016, collected from the Ho Chi Minh Stock Exchange (HOSE) In particular, there is about 76% of exporters and 24% of non-exporters in the sample of 750 observations so the propensity to export is clearly skewed towards one Financial constraints in this paper are measured by three financial variables comprising of leverage and liquidity ratios following Nagaraj (2014) and long – term Le Mai Thy et al | 589 debt to total capital ratio following Egger and Kesina (2010) In order to estimate the influences of financial constraints on firms’ export decision, the study adapts the population average probit models combining with Bootstrap method The marginal effects of probit models are used to report the quantitative impact on the export decision in this study Liquidity is positively related while leverage and long – term to total capital are negatively related to export decision All these results support the hypothesis that the presence of financial constraints influence export decision of Vietnamese manufacturing listed firms The research is then organized as follows Section provides a literature review on financial constraints and firms’ export decision, regarding both theoretical and previous empirical work Section summarizes the empirical analysis of the research and the last section is the conclusion Literature Theoretical Work The theoretical literature highlighting the influences of financial constraints on firms’ export decision has been laid out in several studies Melitz (2003) has theoretically shown that firms’ heterogeneity in their productivity levels and sunk cost of market entry are the causality of why firms not engage in exporting In specific, Melitz adapts Hopenhayn’s (1992a) model to a monopolistically competitive industry in a general equilibrium setting His model integrates firm heterogeneity in a way such that a single statistic – an average firm productivity level summarizes the relevance of the distribution of productivity levels for aggregate outcomes completely Melitz also introduces the sunk market entry costs that firms face not only for their domestic market but also for any potential export market Firms are required to pay fixed perperiod costs and one-off costs to access the domestic and export markets The research’s results show that the more productive firms tend to enter the export market to gain market share and profit while less productive firms cannot, and the least productive firms are forced to get out of export market The causality of more efficient firms find it profitable to export because they can undertake the investment associated with new market entry after gaining knowledge of their productivity Chaney (2005) extends Melitz’s (2003) framework by including liquidity frictions and internal finance and assumes firms operating in an imperfectly competitive product market He proposes a theory of international trade with liquidity constraints as a key 590 | ICUEH2017 determinant of firm’s export behavior Chaney consequently finds that sunk costs associated with activities to enter the export market are sensitive to financial variables The most productive firms are more likely to become exporters because they are able to obtain enough liquidity from selling in domestic markets to overcome the liquidity constraints when starting to export and the less productive firms are unable to export because they can hardly find access to financial markets and cover foreign market entry cost This finding is consistent with the facts that exporters are not liquidity constrained Moreover, the scarcity of available liquidity and inequality of the liquidity distribution among firms lower the total exports Subsequently, Manova (2008) took a step forward to provide evidence on the link between credit constraints and exports of 91 countries in the period of 1980-1997 under the extension of Melitz’s (2003) model The paper highlights inter-sectoral differences in terms of liquidity across countries rather than firm-level financial constraints She focuses on the sector (sectors’ differences in tangibility and external finance need) and country’s comparable advantages in terms of financial development rather than on credit constraints at firm level “Vulnerable sectors” in her paper requires more external finance or use fewer collateralized assets She concludes that credit constraint has a negative impact on exports which is higher in countries with lower levels of financial development and in more financially vulnerable sectors.1She indicates that firms which have better financial availability export more because they have lower need of external finance and therefore are able to enter more market destinations, and sell more of each product Weak financial firms are less likely to become exporters Examining the interaction between firm-level constraints and exports, Muuls’ (2008) model extends Chaney’s (2005) model by incorporating external financing from Manova (2008) In particular, she proposes that enterprises have (three) liquidity sources in order to finance the exporting entry cost consisting of internal financial health, liquidity shocks and external finances She also formulates three predictions: (1) there are firms which could export profitably, but are prevented from doing so because of lacking sufficient liquidity, (2) if the first prediction holds, those firms which are more productive and less financial constrained will be able to export to more destinations but smaller markets She finds that higher productivity levels and lower credit constraints motivates firms be more likely to become exporters Credit constraints are important Manova (2008) defines vulnerable sectors require more external finance and employ fewer collateralized assests Le Mai Thy et al | 591 determinants of the extensive margin of trade in terms of destinations but not the intensive margin of trade in that dimension Li and Yu (2009) aims to examine the influences of a firm’s credit constraints and its productivity on its export decisions They formulate two main propositions: (1) firms for which it is easier to borrow from financial intermediaries export more, (2) foreign invested enterprises export more and are less sensitive to the availability of external finance from financial intermediaries Research’s findings support both of their model’s predictions above They also confirm that firms for which it is easier to borrow from financial intermediaries export more Consistent with Li and Yu (2009), Manova et al (2015) indicates that multinational firms’ affiliates can tap additional funding from their parent company or access foreign capital markets Thus, the credit constraints’ exposure to these affiliate firms is lesser than independent firms (Antras, Desai, Foley, 2009) Hence, they are more likely to become exporters than other firms as the fact that exporting activities requires additional financing In addition to Li and Yu’s conclusion, Javorcik and Spatareanu (2009) also find that not only multinational firms but also suppliers of these multinationals are less influenced by credit constraints Empirical Evidence Egger and Kesina (2010) examine the influence of financial constraints (or credit constraints) to the extensive and the intensive margin of exports collecting data from Chinese enterprises of the National Bureau of Statistic of China for the period of 2001 2005 They proxy credit constraints by four financial variables including long-run debt to capital ratio, financial costs to liquid funds ratio, liquid asset to capital ratio, ratio of surplus of profits over long-run debts to total assets They test the relation between firms’ propensity to export by means of a logit model and the intensive margin of exports by fractional response model following Papke and Wooldredge (1996) Then they confirm the negative effect of credit (financial) constraints on exports and consistent with previous theoretical work That is those firms are financial constrained are less likely to become exporters Cole, Elliot, Virakul (2010) examined the relationship between firms’ characteristics and their export decision and mainly emphasize the importance of financial variables as a proxy for sunk entry costs The authors used the annual survey of manufacturing firms in Thailand from 2001 to 2004 issued by Office of Industrial Economics, Ministry of Industry in Thailand The survey includes three main types of enterprise (i.e small, medium and large firms) covering 79 types of manufacturing activities in 23 industries 592 | ICUEH2017 with the final sample including 15,115 observations By using pooled probit estimation and GMM, they found that liquidity or leverage influence the export decision because these ratios explain the capacity to invest in sunk entry cots of firms when participating in export market The investment decision depends on firms’ internal financial health Moreover, some characteristics of firms including firm size, training, structure of ownership and R&D are also related to the probability of exporting Kiendrebeogo and Minea (2012) also focus on the effects of financial factors on manufacturing firms’ export participation by presenting the intuition according to which financial constraints reduce the probability of exporting using Probit model They acquire unbalanced panel of 1,655 Egyptian manufacturing firms from World Bank’s Enterprise Surveys database from 2003 to 2008 and use composite indicators of financial health based on two financial variables, namely ratio of net income to total assets and the share of new investment financed by equity Their main results show that financial constraints are the cause reducing the export participation of Egyptian firms Following Manova (2008), Manova (2013) tests her predictions by investigating data about 107 countries including 27 sectors from 1985 to 1995 and comes up with a conclusion that regression findings support her propositions that countries which are financially developed are more likely to export Nagaraj (2014) is also interested in investigating the relationship between financial constraints and exports decision of Indian manufacturing firms by using multiple estimators (e.g, fixed effects estimates, Probit estimates, GMM system estimator) and an unbalanced panel of 7,000 firms from 1989-2008 The rich panel allows Nagaraj (2014) to analyze the firms’ exporting decision over a long period which is long enough to address the persistent of exporting behavior She finds an evidence support on the negative relations between the two variables Productivity, a large size and ownership by foreign firms have a positive influence on firms’ propensity to export However, even a foreign firm with adverse financial health does not export Moreover, financial health is the cause not the effect of exports Firms face less financial constraints can increase its extensive margin of export (increase in export due to new exporters) Empirical Analysis Data and descriptive statistic This study utilizes the data from the Annual reports, Financial Statements of manufacturing listed firms for period from 2007 to 2016 in HOSE The data was Le Mai Thy et al | 593 collected from the official website of HOSE and other prestigious private websites such as vietstock.vn, cophieu68.vn and cafef.vn Those firms with any missing observations for any variables (e.g., sales, employment, exports, firms’ financial information etc.) in the model during the research period are dropped Hence, the final sample contains 75 listed manufacturing firms with adequate requested information during 10 years In order to proxy for financial constraints, this study follows the financial variables approach using two liquidity ratio and leverage ratios from Nagaraj (2014) and long-run debt to capital ratio from Egger and Kesina (2010) Firstly, leverage is measured as the ratio of short-term debt to current assets (Nagaraj, 2014) The lower the leverage, the better the ability of firms to raise funds and obtain the external finance for entry cost in export markets Thus, the researcher expects the negative effect of leverage on export decision Secondly, liquidity is used to measure firms’ capacity to invest or pay sunk entry costs in order start exporting (Nagaraj, 2014) Liquidity is measured as the ratio of the difference between current assets and current liabilities to total assets The higher the liquidity ratio, the better would be the financial health of the firm Finally, long – term debt to total capital ratio equal to long term debt divided by total capital of firm level (Egger and Kesina, 2010) This ratio computes the proportion of a company's long – term debt compared to its available capital for a long time The higher this ratio, the stronger the financial constraints the firms are subject to As a result, a firm is ceteris paribus more financially constrained the higher is the higher leverage and long – term debt to total capital ratios and lower is the liquidity ratio Bernard and Jensen (2004) find that exporters are more productive, bigger, and more capital intensive Hence, the three factors including firm size, labor productivity and human capital intensity are concerned as control variables and are measured in logaric Firm size is expressed by the number of permanent workers of the firm according to Greenway et al (2007), Egger and Kesina (2010), Bellone et al (2010), Wagner (2015) Labor productivity is measured in this study in term of sales to employment ratio following Wagner (2015), Egger and Kesina (2010) Human capital intensity is measured by the fixed assets to employment ratio following Raoul Minetti, Susan Chun Zhu (2011), Egger and Kesina (2010) Table below provides the descriptive statistics in terms of mean and standard deviation of variables which including two main parts The first part is financial constraints which summarizes three measurements capturing aspect of financial constraints The second part is control variables which summarizes three control variables in logaric forms 594 | ICUEH2017 Table Descriptive Statistics Observations Non exporters Exporters 181 569 Mean Standard deviation Mean Standard deviation LTDC 1019145 1471238 099618 1488349 LVR 3081978 2561828 3504263 2827597 LQD 2546156 1743458 2423332 1976783 lnSIZE 6.009017 8780968 6.851027 2423332 lnLAP 21.46669 1.169481 20.89699 1.107779 lnHCI 19.59212 1.151961 19.45675 1.270875 Financial Constraints Control variables On average, exporters have higher leverage but lower long-term debt to total capital and lower liquidity ratio than non-exporters Even thought exporters have bigger size, their labor productivity and human capital intensity is lower in comparison with nonexporters which are the reason to increase costs and demand for external finance to these companies The descriptive statistic is quite different with the data-set of others papers (Nagaraj, 2014; Manova, 2013; Kiendrebeogo and Minea, 2012, Egger and Kesina, 2010) due to the context of Vietnam where the study is conducted In which majority of Vietnamese exporters are only able to assemble and outsource products due to the lacking of domestic supplied materials and the competitiveness of Vietnamese enterprises and their products are not strong enough in comparison with others countries’ Moreover, the imperfect capital market and the financial systems are not advanced in Vietnam; it is still very difficult for firms to obtain external sources of funds regardless of their high demand for such external finance Exporters need external funds for their entry investments in exporting markets because their internal finance is not strong enough However, the stock market in Vietnam is not matured, so equity financing is not very effective for exporters to raise additional capital regularly Hence, borrowings seem to be better solution in which long – term debt requires much more collaterals (i.e lands, buildings, factories) and higher interest rate (i.e - 11% per year); exporters then rely more on short – term debts (i.e – % per year) to fulfill their need of investments due to their limited fixed assets Le Mai Thy et al | 595 Estimation In order to estimate the influences of financial constraints on export decision, the study adapts the population average probit models as in Nagaraj (2014) and Egger and Kesina (2010) The decision whether a company shall participate in the export market is indicated by a binary outcome model which explains the probability of a firm of starting to export A binary variable Expdit for exporting (unity) versus non-exporting (zero) for firm i in year t is as below: 0, if Expdit * = Expdit = 1, if Expdit * > 0, where Expdit * is the export revenue that firm i can generate in year t The export decision is driven by a latent variable of export revenues Expdit * As mentioned above, the three control variables including firm size, labor productivity, and human capital intensity are measured in logaric Financial constraints are represented by each of three measurements above including long-term debt to total capital, leverage and liquidity ratios For each of financial constraints’ measurement, this study will run a separate regression The three probit models estimates the influence of financial constraints on export decisions of Vietnamese manufacturing firms in HOSE from 2007 to 2016 are then as below: Pr(Expdit = 1|xit) = Ф(β0 + β1SIZEit + β2LAPit + β3HCIit + β4LTDCit + zitγ) (1) Pr(Expdit = 1|xit) = Ф(β0 + β1SIZEit + β2LAPit + β3HCIit + β4LVRit + zitγ) (2) Pr(Expdit = 1|xit) = Ф(β0 + β1SIZEit + β2LAPit + β3HCIit + β4LQDit + zitγ) (3) Results Running probit models with bootstrap option could give the correct standard deviation and address the heteroskedasticity, thus, its results are more favorable in this study Therefore, the following discussions will be based on the results from probit model with bootstrap The empirical results from population average probit models with bootstrap are given in Table below As same as with the researcher expectation, three main independent variables of interest are all significant In particular, liquidity is positively related to exporting probability while long-term debts to capital and leverage show negative relationship with probability of exporting Firms with higher liquidity ratio are more likely to start exporting If firms not face with liquidity constraints, these firms are able to have 596 | ICUEH2017 sufficient fund so that they can afford to pay the sunk entry costs when entering export markets On the other hand, firms with higher long-term debt to capital and leverage ratios are less likely to start exporting This is because the higher these two ratios the lower the ability of firms to raise funds and obtain the external finance for entry cost in export markets which hinder them from entering exporting All these results are consistent with a negative relationship between financial constraints and export probability In other words, the main hypothesis of this study is supported The results are consistent with previous papers’ findings, namely Nagaraj (2014), Manova (2013), Kiendrebeogo and Minea (2012), Egger and Kesina (2010), Cole et al (2010), Li and Yu (2009) Table Results Dependent variable: Export dummy variable Regression model Population average probit models (bootstrap with 50 replications) Marginal effects population average probit models (bootstrap with 50 replications) (1) (2) (3) (1) (2) (3) 0.077** 0.086** 0.086* 0.023** 0.026** 0.026** (0.036) (0.036) (0.050) (0.010) (0.011) (0.013) lnLAP 0.03** 0.032** 0.032** 0.009** 0.010** 0.010** (0.015) (0.016) (0.014) (0.004) (0.005) (0.005) lnHCI 0.012** 0.009** 0.019* 0.004** 0.003*** 0.006* (0.006) (0.004) (0.010) (0.002) (0.001) (0.003) lnSIZE LTDC LVR LQD -0.174 -0.052*** (0.068)** (0.020) -0.087** -0.026** (0.037) (0.011) 0.139* 0.042** (0.076) (0.021) Notes: Independent variable is a binary outcome whether a firm is an exporter or not Three control variables including lnSIZE, lnLAP, lnHCI are measured in logaric Financial constraints are measured as follows: LTDC = long-term debt/(long-term debt + shareholders’ equity); LVR = short-term debt/current assets; LQD = (current assets – current liabilities)/total assets Standard errors and bootstrap standard errors are reported in parentheses *, **, *** indicate significance at 10%, 5% and 1% respectively Marginal effects evaluated at mean Le Mai Thy et al | 597 For control variables, as can be seen from Table 2, all of three controls variables including firm size, labor productivity and human capital intensity are positive related to exporting probability It can be interpreted that firms with bigger size, higher labor productivity and higher human capital intensity are more likely to become exporters This results are also consistent with Bernard and Jensen (1999 and 2004), Greenaway and Kneller (2004), Cole, Elliot, Virakul (2010), Egger and Kesina (2010), Wagner (2012a, 2012b, 2015) Also in Table 2, the marginal effects of all variables after probit models are all statistical significant In particular, liquidity is positively related to exporting probability while long-term debts to capital and leverage variables have negatively relationship For three main measurements of financial constraints, an increase in the long – term debt to capital causes a reduction in the probability of exporting by 0.052 Similarly, with a negative sign of the marginal effects, it shows that an increase in the leverage causes a reduction in the probability of exporting by 0.026 In contrast with the negative relationship among long-term debts to capital and leverage to export decision, the liquidity’s marginal effects sign indicates a positive relationship, it can be interpreted that a decrease in the liquidity causes an increase in the probability of exporting by 0.042 These findings imply that financial constraints have negative effects to the entry decision into export market of Vietnamese manufacturing firms In other words, for those firms who have higher long-term debts to capital, higher leverage and lower liquidity are less likely to become exporters These findings obviously support the main hypothesis of this study These results one more time are consistent with previous researches including Nagaraj (2014), Manova (2013), Kiendrebeogo and Minea (2012), Egger and Kesina (2010), Cole et al (2010), and Li and Yu (2009) For more information, the empirical results for three control variables in this study are all significant and consistent with Bernard and Jensen (1999 and 2004), Greenaway and Kneller (2004), Cole, Elliot, Virakul (2010), Egger and Kesina (2010), Wagner (2012a, 2012b, 2015) The finding for each of control variable will be discussed in detail as follows Firstly, firm size has positive and significant effects across three models This means larger firms are more likely to become exporters than smaller ones The results shows an increase in firm size by one employee increase the probability of exporting by 0.023, 0.026 and 0.026, respectively This is supported by the same findings of Bernard and Jensen (1999 and 2004), Greenaway and Kneller (2004), Cole, Elliot, Virakul (2010), Egger and Kesina (2010), Wagner (2015) Another control variable that 598 | ICUEH2017 determines a firm’s export decision is labor productivity In all of three columns in Table above, the results show the positive relationship and all significant which means with one unit increase in labor productivity, the probability of exporting will increase by an average value of 0.010 This implies that firms that have higher productivity level of labors are more likely to enter the export market than the others This finding is supported by Bernard and Jensen (1999 and 2004), Girma et al (2004), Greenaway and Kneller (2004), Egger and Kesina (2010), Wagner (2012a) The last control variable that the researcher wants to mention here is the human capital intensity This variable is positive related to export decision and statistically significant It means firms that produce high-quality innovative products are more likely to become exporters Based on the result in Table 7, it can be interpreted that an increase in human capital intensity causes an increase in exporting probability by 0.4, 0.3 and 0.6 percent points The result is in line with Bernard and Jensen (1999 and 2004), Wagner (2012b, 2015) Robustness Check This study follows Egger and Kesina (2010), Nagaraj (2014) to explore the robustness of findings by adding the interactions between each of three main explanatory variables of interest, including long – term to total capital, leverage and liquidity, respectively, with three control variables firm size, labor productivity, and human capital intensity into the three probit models The new three probit models in this research are then as follows: Pr(Expdit = 1|xit) = Ф(β0 + β1SIZEit + β2LAPit + β3HCIit + β4LTDCit + β5LTDCitxSIZEit + β6LTDCitxLAPit + β7LTDCitxHCIit + zitγ) (1) Pr(Expdit = 1|xit) = Ф(β0 + β1SIZEit + β2LAPit + β3HCIit + β4LVRit + β5LVRitxSIZEit + β6LVRitxLAPit + β7LVRitxHCIit + zitγ) (2) Pr(Expdit = 1|xit) = Ф(β0 + β1SIZEit + β2LAPit + β3HCIit + β4LQDit + β5LQDitxSIZEit + β6LQDitxLAPit + β7LQDitxHCIit + zitγ) (3) The Table below shows the results after running probit models with interactions between variables Once again, the results confirm this study’s main hypothesis that manufacturing listed firms on HOSE that are subject to financial constraints are less likely to become exporters for the period of 2007 - 2016 In specific, the results show that the long-term debts to capital and leverage are negatively related to probability of exporting whilst the liquidity shows the positive relationship These results are consistent with the findings of this study’s main models mentioned above as well as Le Mai Thy et al | 599 previous researches including Nagaraj (2014), Manova (2013), Kiendrebeogo and Minea (2012), Egger and Kesina (2010), Cole et al (2010), Li and Yu (2009) The researcher also reports the marginal effects of three new population average probit models with interaction between variables in Table Adding the interactions into the population average probit models, the results show that an increase in the long term debt to capital causes a reduction in the probability of exporting by 0.175; and an increase in the leverage causes a reduction in the probability of exporting by 0.449 In contrast, a decrease in the liquidity causes an increase in the probability of exporting by 0.427 Table Robustness check’s results Dependent variable: Export dummy variable Regression model lnSIZE lnLAP lnHCI LTDC LTDCxlnSIZE LTDCxlnLAP LTDCxlnHCI LVR LVRxlnSIZE LVRxlnLAP Population average probit models with interactions Marginal effects population average probit models with interactions (1) (2) (3) (1) (2) (3) 0.029 0.055*** 0.108*** 0.001 0.017*** 0.033*** (0.033) (0.021) (0.019) (0.001) (0.006) (0.006) -0.006 0.011 0.039** -0.000 0.003 0.012** (0.027) (0.018) (0.016) (0.001) (0.005) (0.005) 0.024 0.014 0.014 0.001 0.004 0.004 (0.17) (0.011) (0.014) (0.001) (0.003) (0.004) -4.213** -0.175* (2.061) (0.092) 0.837*** 0.035*** (0.177) (0.011) 0.177* 0.007 (0.105) (0.005) -0.238** -0.010* (0.104) (0.005) -1.505*** -0.449*** (0.558) (0.169) 0.1*** 0.030*** (0.024) (0.007) 0.053* 0.016* (0.029) (0.009) 600 | ICUEH2017 LVRxlnHCI LQD LQDxlnSIZE LQDxlnLAP LQDxlnHCI -0.017 -0.005 (0.023) (0.007) 1.418** 0.427** (0.713) (0.217) -0.107*** -0.032*** (0.028) (0.009) -0.041 -0.012 (0.041) (0.013) 0.012 0.004 (0.030) (0.009) Notes: Independent variable is a binary outcome whether a firm is an exporter or not Three control variables including lnSIZE, lnLAP, lnHCI are measured in logaric Financial constraints are measured as follows: LTDC = long-term debt/(long-term debt + shareholders’ equity); LVR = short-term debt/current assets; LQD = (current assets – current liabilities)/total assets Standard errors and bootstrap standard errors are showed in parentheses *, **, *** specify significance at 10%, 5% and 1% respectively Marginal effects evaluated at mean Conclusion This study investigates the influences of financial constraints, through three measurements including long-term debts to capital, leverage and liquidity ratios, on export decision of Vietnamese manufacturing listed firms on HOSE for the period of 2007 up to 2016 Applying the population averaged probit models with bootstrap method, the main hypothesis is supported that Vietnamese manufacturing listed firms that are entitled to financial constraints are less likely to become exporters In particular, only manufacturing firms that have lower long-term debts to capital, lower leverage and higher liquidity are more likely to become exporters The results are consistent with previous researches of Nagaraj (2014), Manova (2013), Kiendrebeogo and Minea (2012), Egger and Kesina (2010), Cole et al (2010), Li and Yu (2009) The results also show that the long – term debt to total capital ratio influence the export decision at most by 0.052 Next is the liquidity ratio with 0.042 and leverage is last ranking with 0.026 in the effect on export decision of Vietnamese manufacturing firms Moreover, the other control variables used in this study consisting of firm size, labor productivity and human capital intensity are also positively related to the entry decision into export market of Vietnamese manufacturing firms In other words, firms with bigger size, higher productivity and higher human capital intensity are more likely to become exporters Le Mai Thy et al | 601 The study contributes to micro-evidence literature of the impact of financial constraints on Vietnamese manufacturing firms’ propensity to export by firstly adopting estimation strategies which estimate population average probit models for panel data in Ho Chi Minh City context In addition, by re-confirming the influences of previous variables consisting of firm size, labor productivity and human capital intensity, this study also supports the measurements of financial constraint by using financial ratios This research is useful for Vietnamese Government to understand the reason why some manufacturing are less likely to participate in the export market This calls for more attention from the Government to setup proper strategies in order to create favorable conditions and encourage firms to export In specific, the Government should develop the financial markets and financial sectors such as banking systems, financial intermediaries and institution from which financial constrained firms can be easier to get access into external funding and enter the export markets In addition, the Government should also issue some promotion policies (i.e investments incentives, tax incentives) for new entry into export so 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A Firm-level Examination” The world economy Wagner, J (2015) Credit Constraints and the Extensive Margins of Exports: First Evidence for German Manufacturing Economics Discussion Papers, No 2015-16 ... Michaela Kesina, (2010) “Financial constraints and exports: Evidence from Chinese firms? ?? Priya Nagaraj (2014) Financial constraints and export participation in India International Economics 140... more likely to export Nagaraj (2014) is also interested in investigating the relationship between financial constraints and exports decision of Indian manufacturing firms by using multiple estimators... multinationals are less influenced by credit constraints Empirical Evidence Egger and Kesina (2010) examine the influence of financial constraints (or credit constraints) to the extensive and