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<article xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" article-type="research-article" xml:lang="en">
<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">SAJEMS</journal-id>
<journal-title-group>
<journal-title>South African Journal of Economic and Management Sciences</journal-title>
</journal-title-group>
<issn pub-type="ppub">1015-8812</issn>
<issn pub-type="epub">2222-3436</issn>
<publisher>
<publisher-name>AOSIS</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="publisher-id">SAJEMS-20-885</article-id>
<article-id pub-id-type="doi">10.4102/sajems.v20i1.885</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Original Research</subject>
</subj-group>
</article-categories>
<title-group>
<article-title>Determinants of the capital structure of Portuguese firms with investments in Angola</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<contrib-id contrib-id-type="orcid">http://orcid.org/0000-0001-6919-0015</contrib-id>
<name>
<surname>Mota</surname>
<given-names>Jorge H.F.</given-names>
</name>
<xref ref-type="aff" rid="AF0001">1</xref>
</contrib>
<contrib contrib-type="author" corresp="yes">
<contrib-id contrib-id-type="orcid">http://orcid.org/0000-0002-6613-8796</contrib-id>
<name>
<surname>Moreira</surname>
<given-names>Antonio C.</given-names>
</name>
<xref ref-type="aff" rid="AF0001">1</xref>
</contrib>
<aff id="AF0001"><label>1</label>Department of Economics, Management, Industrial Engineering, and Tourism, University of Aveiro, Portugal</aff>
</contrib-group>
<author-notes>
<corresp id="cor1"><bold>Corresponding author:</bold> Antonio Moreira, <email xlink:href="amoreira@ua.pt">amoreira@ua.pt</email></corresp>
</author-notes>
<pub-date pub-type="epub"><day>28</day><month>02</month><year>2017</year></pub-date>
<pub-date pub-type="collection"><year>2017</year></pub-date>
<volume>20</volume>
<issue>1</issue>
<elocation-id>885</elocation-id>
<history>
<date date-type="received"><day>25</day><month>01</month><year>2014</year></date>
<date date-type="accepted"><day>12</day><month>10</month><year>2016</year></date>
</history>
<permissions>
<copyright-statement>&#x00A9; 2017. The Authors</copyright-statement>
<copyright-year>2017</copyright-year>
<license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by/2.0/">
<license-p>AOSIS. This work is licensed under the Creative Commons Attribution License.</license-p>
</license>
</permissions>
<abstract>
<sec id="st1">
<title>Background</title>
<p>This article seeks to complement the previous literature and clarify the particularities of the capital structure policy of firms with foreign direct investment in Angola.</p>
</sec>
<sec id="st2">
<title>Aim</title>
<p>This article seeks to identify the determinants of the capital structure of Portuguese firms with direct investment in Angola and to understand whether the determinants normally considered by standard finance theory are in line with those used by firms when structuring their capital structure policy to participate in the specific market of Angola.</p>
</sec>
<sec id="st3">
<title>Setting</title>
<p>This article examines 26 large Portuguese firms with investments in Angola using econometric panel data for the period 2006&#x2013;2010.</p>
</sec>
<sec id="st4">
<title>Methods</title>
<p>The study applied fixed and random effects methods and panel-corrected standard errors that maintain efficiency and unbiased behaviour even in the presence of panel-level heteroscedasticity and contemporaneous correlation of observations among panels.</p>
</sec>
<sec id="st5">
<title>Results</title>
<p>The results provide evidence that the determinants normally considered by standard finance theory are in fact &#x2013; in terms of sign and coefficient dimension &#x2013; those used by firms for structuring their capital structure policy when involved in the internationalisation process of entering Angola. Specifically, age, asset structure, return on assets and tangibility have a positive influence on the capital structure of Portuguese firms that have invested in Angola, while non-debt tax shields and liquidity have a negative influence on these companies&#x2019; leverage ratios. When comparing our results with studies that have analysed the capital structure determinants of listed Portuguese firms &#x2013; firms belonging to the PSI 20 Index and large firms in the Portuguese corporate sector &#x2013; we found similarities in the sign and coefficient dimension of the determinants of capital structure. However, the profitability coefficient sign is in line with the trade-off framework (i.e. profitability is positively related to debt) but not with pecking order theory (i.e. profitability is negatively related to debt).</p>
</sec>
<sec id="st6">
<title>Conclusion</title>
<p>Our results suggest that the high-growth Angolan market is seen by larger Portuguese firms as a low-risk diversification process because of the economic hardship Portugal has gone through, as well as cultural and linguistic similarities to Portugal. As such, the Angolan market is seen as an extension of the Portuguese domestic market that has increased potential. This scenario potentially reduces the firm default probability and the cost of debt. Maintaining the tax shield benefits of debt and decreasing the cost of debt &#x2013; through a reduction in the default probability &#x2013; have induced profitable firms to use more debt.</p>
</sec>
</abstract>
</article-meta>
</front>
<body>
<sec id="s0001">
<title>Introduction</title>
<p>Capital structure has always been a polemical subject when it comes to financial theory. The selection of which capital structure to follow in a given project is a crucial decision, given the need to maximise returns for all firms&#x2019; stakeholders (Abor &#x0026; Biekpe <xref ref-type="bibr" rid="CIT0002">2009</xref>) and the way this choice can interfere with firms&#x2019; capacity to deal with an external competitive environment (Abor <xref ref-type="bibr" rid="CIT0001">2005</xref>).</p>
<p>Since the groundwork research done by Modigliani and Miller (<xref ref-type="bibr" rid="CIT0038">1958</xref>), several studies have attempted to determine the optimal capital structure, particularly research concerned with bankruptcy cost, agency theory and pecking order theory. These theories suggest that the selection of an appropriate capital structure depends on the features that determine the various costs and benefits associated with debt and/or equity financing. Therefore, the study of the determinants that influence capital structure is clearly of vital importance.</p>
<p>Although much research has been done on market imperfections, bankruptcy costs and information asymmetry, there are few studies on firms&#x2019; capital structure in Africa (Abor <xref ref-type="bibr" rid="CIT0001">2005</xref>; Abor &#x0026; Biekpe <xref ref-type="bibr" rid="CIT0002">2009</xref>; Boateng <xref ref-type="bibr" rid="CIT0011">2004</xref>; Ezeoha &#x0026; Okafor <xref ref-type="bibr" rid="CIT0022">2010</xref>). Moreover, documented studies have not been conducted on the determinants of the capital structure of firms belonging to less intensely developed countries with investments on the African continent. Accordingly, the main purpose of this article is to identify the key determinants of the capital structure of Portuguese firms with investments in Angola.</p>
<p>Angola had a civil war from 1975 to 2002. The end of the civil war provided a wide range of investment opportunities, mainly because of the shortage of numerous goods and services, as well as the presence of a significant domestic market with a high purchasing power in some social strata. This opportunity combined with the small psychic distance between Portugal and Angola to open a window of opportunity for many Portuguese firms to invest in Angola, where they innovated and sometimes created completely new concepts for this market but, sometimes, took on high risks. By studying the decisions made about the capital structure of Portuguese firms with investments in Angola, one can explore how these investors decide what the best capital structure policy for their investments is, providing this field of study with a new perspective.</p>
<p>This article analyses Portuguese firms that have direct investments in Angola, in the form of either branches or subsidiaries but with headquarters in Portugal, with the goal of identifying the determinants of their capital structure. The objective is to understand whether the determinants normally considered by standard finance theory are, in fact, those used by firms for structuring their capital structure policy when participating in the specific market of Angola.</p>
<p>The article is organised as follows: After this brief introduction, a review of the literature on capital structure is described in the section &#x2018;Capital structure: Literature review&#x2019;. In the section &#x2019;Determinants of capital structure and research hypotheses&#x2019;, the determinants of capital structure are examined. In the section &#x2018;Data, estimation methodology and model&#x2019;, the research methodology is presented. The results are presented in the section &#x2018;Main results and discussion&#x2019;. Lastly, the discussion of findings and conclusions are presented.</p>
</sec>
<sec id="s0002">
<title>Capital structure: Literature review</title>
<p>The capital structure theory has been quite often debated in the corporate finance literature. It concerns the ways firms use equity and debt capital to finance their assets.</p>
<p>Modigliani and Miller (<xref ref-type="bibr" rid="CIT0038">1958</xref>) developed three crucial irrelevance propositions about capital structure theory: the value of a firm or project is independent from its financial structure, the value of the firm or project increases with debt in direct proportion to the equity/debt capital ratio and, lastly, the weighted average cost of capital remains unchanged regardless of the financing source used. Although this fundamental theory has replaced Durand&#x2019;s (<xref ref-type="bibr" rid="CIT0021">1952</xref>) traditional theory, in which he states that capital structure influences firms&#x2019; value, research contradicting this idea has been carried out to explain the way firms finance themselves. Along these lines, Modigliani and Miller (<xref ref-type="bibr" rid="CIT0038">1958</xref>) draw some further conclusions: a firm&#x2019;s market value is independent of its capital structure, the higher the expected returns, the higher the risk involved and, lastly, the rate of return demanded by shareholders of indebted firms is higher than the rate of return demanded by shareholders of non-indebted firms.</p>
<p>Myers (<xref ref-type="bibr" rid="CIT0039">1977</xref>) asserts that firms that are quite indebted may not perform projects in which the net present value is positive, as generated cash flows will mostly be destined to cover already assumed commitments and the surplus will not be enough to cover the initial investment. Later, Myers (<xref ref-type="bibr" rid="CIT0041">1993</xref>) claimed that it is possible to estimate the optimal debt ratio of a firm by considering the net tax benefits, which are related to the existence of debt and its associated costs.</p>
<p>Brealey, Myers and Allen (<xref ref-type="bibr" rid="CIT0012">2007</xref>) argue that capital structure acknowledges that debt ratios objectives may vary from firm to firm. Accordingly, firms with tangible assets and high earnings before income taxes may need to establish high debt ratios so that they can secure tax benefits. Corporations with low profits &#x2013; with risky intangible assets &#x2013; should resort to their own equity.</p>
<p>According to Crnigoj and Mramor (<xref ref-type="bibr" rid="CIT0019">2009</xref>) and Tahir and Alifiah (<xref ref-type="bibr" rid="CIT0060">2015</xref>), the current theory of capital structure is based on two strands: the trade-off and pecking order theories. Falling within the first thread, Chang and Yu (<xref ref-type="bibr" rid="CIT0017">2010</xref>) state that the optimal capital policy of firms is based on the trade-off between debt tax benefits and bankruptcy costs.</p>
<p>According to the pecking order theory, firms do not seek an optimal capital structure. The structure instead reflects financing options taken in the past (Myers <xref ref-type="bibr" rid="CIT0040">1984</xref>; Myers &#x0026; Majluf <xref ref-type="bibr" rid="CIT0042">1984</xref>), that is, a hierarchical order is followed when choosing financing sources because of information asymmetry. This hierarchy of sources stems from the financing of investments, first, with internal funds (i.e. retained earnings), followed by new debt issuance and, lastly, by new shares issuance (Brealey et al. <xref ref-type="bibr" rid="CIT0012">2007</xref>).</p>
<p>This information asymmetry theory also is one of the fundamental theories that help explain capital structure. Information asymmetry occurs when managers have more information than investors (Brealey et al. <xref ref-type="bibr" rid="CIT0012">2007</xref>). The cited authors argue that information asymmetry jeopardises the choice between internal or external financing and new share issuance.</p>
<p>According to Istaitieh and Rodr&#x00ED;guez-Fern&#x00E1;ndez (<xref ref-type="bibr" rid="CIT0029">2006</xref>), the capital structure literature can be classified according to the following typology: the stakeholder theory of capital structure, the theory of market structure and the competitive strategy theory. The first theory relies on the idea that debt affects non-financial agents such as collaborators and suppliers, as well as shareholders and creditors. Therefore, both non-financial agents (i.e. clients, workers and suppliers) and financial agents (i.e. shareholders and bondholders) need to be taken into account.</p>
<p>Regarding the second theory, the level of debt might affect the market, and the market structure also can impact the capital structure of firms (Santos, Moreira &#x0026; Vieira <xref ref-type="bibr" rid="CIT0053">2013</xref>, <xref ref-type="bibr" rid="CIT0054">2014</xref>, <xref ref-type="bibr" rid="CIT0055">2015</xref>). Ultimately, the last theory &#x2013; competitive strategy theory &#x2013; states that the capital structure of firms is related to their competitive strategy, as both aspects strive to leverage the firms (Istaitieh &#x0026; Rodr&#x00ED;guez-Fern&#x00E1;ndez <xref ref-type="bibr" rid="CIT0029">2006</xref>; Oinoa &#x0026; Ukaegbu <xref ref-type="bibr" rid="CIT0044">2015</xref>).</p>
<p>In their definition of capital structure, Silva and Queir&#x00F3;s (<xref ref-type="bibr" rid="CIT0059">2009</xref>) claim that it is important to analyse the trade-off between equity and debt as this trade-off will influence the degree of enforceability and the cost of each financing source in the capital structure. An accurate definition of short-, medium- or long-term maturities and of sources of capital (i.e. equity and/or debt) is important to minimise capital costs and the risk of not fulfilling firms&#x2019; financial obligations and, at the same time, to maximise the return of invested capital (Menezes <xref ref-type="bibr" rid="CIT0036">2003</xref>).</p>
<p>Boateng (<xref ref-type="bibr" rid="CIT0011">2004</xref>) developed a different perspective on the definition of capital structure. He argues that this structure needs to be defined based on the properties of the various costs and benefits linked to debt and equity. However, Ezeoha and Okafor (<xref ref-type="bibr" rid="CIT0022">2010</xref>) and Chadha and Sharma (<xref ref-type="bibr" rid="CIT0015">2015</xref>) claim that the definition of capital structure depends on the dominant character of firms&#x2019; structure in each country and on the level of development of the markets involved.</p>
<p>In addition, Parsons and Titman (<xref ref-type="bibr" rid="CIT0047">2008</xref>) and Chadha and Sharma (<xref ref-type="bibr" rid="CIT0015">2015</xref>) assert that changes in capital structure are influenced not only by the availability of capital generated internally but also by market conditions. Andrikopoulos (<xref ref-type="bibr" rid="CIT0004">2009</xref>) also states that managers&#x2019; salaries and firms&#x2019; value should be taken into account when defining their capital structure.</p>
<p>Titman and Wessels (<xref ref-type="bibr" rid="CIT0061">1988</xref>) conclude that capital structure is chosen in a systematic way, which agrees with Modigliani and Miller&#x2019;s (<xref ref-type="bibr" rid="CIT0038">1958</xref>) argument. However, the evidence against the hierarchy of financing theory shows that external financing is valued and that firms issue more shares than debt (Frank &#x0026; Goyal <xref ref-type="bibr" rid="CIT0023">2003</xref>). After studying the Indian market, Handoo and Sharma (<xref ref-type="bibr" rid="CIT0025">2014</xref>) concluded that liquidity, size, profitability and growth might have different results when measured as short-term debt, long-term debt or total debt ratio, each having a different impact on the leverage structure of listed Indian firms.</p>
<p>Hovakimian, Hovakimian and Tehranian (<xref ref-type="bibr" rid="CIT0027">2004</xref>), after studying financing options, concluded that the importance of return on shares is related to the search for leverage. Nevertheless, the cited authors also argue that firms with high profits do not compensate for accumulated deficits with leverage through the issuance of debt.</p>
<p>Rocca et al. (<xref ref-type="bibr" rid="CIT0051">2009</xref>) conclude that the diversification of choices is important in debt financing. Diversified firms cannot be considered a homogeneous group, and they increase their use of debt to profit from tax deductions and benefits.</p>
<p>Saito and Hiramoto&#x2019;s (<xref ref-type="bibr" rid="CIT0052">2010</xref>) study of the impacts of international activities on capital structure found that Brazilian multinationals use more debt in international activities, at 9.6&#x0025; of their leverage, of which 5.8&#x0025; comes from long-term sources. International activity, therefore, increases short- and long-term leverage. The cited authors also maintain that international activity is positively related with the use of external debt and that multinationals, on average, add more than 12.7&#x0025; external debt to their capital structure. The effect of foreign presence on the leverage of domestic firms was subsequently analysed by Anwar and Sun (<xref ref-type="bibr" rid="CIT0006">2015</xref>), who concluded that the impact of a foreign presence on leverage is important, although this varies from industry to industry because of heterogeneity of productivity patterns.</p>
</sec>
<sec id="s0003">
<title>Determinants of capital structure and research hypotheses</title>
<sec id="s20004">
<title>Asset structure</title>
<p>As leverage is negatively influenced by asset structure, firms tend to prefer short-term rather than long-term debt (Daskalakis &#x0026; Psillaki <xref ref-type="bibr" rid="CIT0020">2008</xref>). Therefore, small- and medium-sized businesses, having fewer fixed assets, usually find it more difficult to secure loans (Abor &#x0026; Biekpe <xref ref-type="bibr" rid="CIT0002">2009</xref>), while firms with greater fixed assets do not apply for loans as often (Psillaki &#x0026; Daskalakis <xref ref-type="bibr" rid="CIT0049">2009</xref>).</p>
<p>Brito, Corrar and Batistella (<xref ref-type="bibr" rid="CIT0013">2006</xref>) and Menike (<xref ref-type="bibr" rid="CIT0037">2015</xref>) argue that asset structure positively influences long-term debt, that is, firms that have fixed assets to offer as collateral for their debts are considered more creditworthy. However, Karadeniz et al. (<xref ref-type="bibr" rid="CIT0032">2009</xref>) maintain that fixed assets and returns on assets have a negative influence on debt and debt ratio. Therefore, the following hypothesis was formulated for the present study:</p>
<disp-quote>
<p><bold>H1</bold>: A relationship exists between capital structure and asset structure.</p>
</disp-quote>
</sec>
<sec id="s20005">
<title>Age</title>
<p>Age is usually expected to have a positive effect on capital structure &#x2013; as represented by debt to equity ratio &#x2013; given that firms increase their liquidity capacity over the years. Abor and Biekpe (<xref ref-type="bibr" rid="CIT0002">2009</xref>) conclude that age is important when obtaining funds through loans as firms that have been in their business for a considerable period have collateral to offer to banks if they cannot pay their debt. Menike (<xref ref-type="bibr" rid="CIT0037">2015</xref>) also found that the younger the firm, the more prone it is to resort to long-term debt.</p>
<p>For Bhaird and Lucey (<xref ref-type="bibr" rid="CIT0010">2010</xref>), the age of a firm positively influences profit retention but negatively influences long-term financing. Ahmed, Ahmed and Ahmed (<xref ref-type="bibr" rid="CIT0003">2010</xref>) assert that age negatively influences leverage. It is worth pointing out, in this context, that leverage variation might be explained by the increase in the age of firms, which could compel managers to focus a significant part of their attention on the intrinsic characteristics of their firm and its financing decisions (Chadha &#x0026; Sharma <xref ref-type="bibr" rid="CIT0015">2015</xref>; Kayo &#x0026; Kimura <xref ref-type="bibr" rid="CIT0033">2011</xref>). Therefore, the following hypothesis was considered in the present study:</p>
<disp-quote>
<p><bold>H2</bold>: A relationship exists between capital structure and age.</p>
</disp-quote>
</sec>
<sec id="s20006">
<title>Liquidity</title>
<p>Liquidity is measured through the current assets/current liabilities ratio, providing information on whether firms can meet their short-term financial commitments. Ahmed et al. (<xref ref-type="bibr" rid="CIT0003">2010</xref>) conclude that liquidity has a negative impact on the debt to equity ratio, that is, equity capital will increase more substantially over time than liabilities. Ant&#x00E3;o and Bonfim (<xref ref-type="bibr" rid="CIT0005">2008</xref>) and Sbeiti (<xref ref-type="bibr" rid="CIT0056">2010</xref>) assert that liquidity has a negative impact on financial leverage, which is to say that firms with higher levels of liquidity tend to avoid increasing their use of external debt, a finding that gave rise to this hypothesis in the present study:</p>
<disp-quote>
<p><bold>H3</bold>: A relationship exists between capital structure and liquidity.</p>
</disp-quote>
</sec>
<sec id="s20007">
<title>Intangibility</title>
<p>The level of intangible activity is expected to have a positive impact on leverage as firms with high expenditures on research and development need higher levels of external capital than internal capital. This result suggests that internal financing is not enough to support the high-level growth of these firms regarding their increased need for investment (Bhaird &#x0026; Lucey <xref ref-type="bibr" rid="CIT0010">2010</xref>). Thus, the following hypothesis was suggested for the present study:</p>
<disp-quote>
<p><bold>H4</bold>: A relationship exists between capital structure and intangibility.</p>
</disp-quote>
</sec>
<sec id="s20008">
<title>Profitability</title>
<p>Based on pecking order theory, Myers (<xref ref-type="bibr" rid="CIT0040">1984</xref>) argues that decisions on capital structure follow a hierarchical order when it comes to choosing financing sources. This hierarchy mainly consists of financing investments with retained earnings, followed by new debt issues and, lastly, by the issuance of new equity. Consequently, firms&#x2019; profitability has a negative impact on their use of debt (Chang, Lee &#x0026; Lee <xref ref-type="bibr" rid="CIT0016">2009</xref>; Nunkoo &#x0026; Boateng <xref ref-type="bibr" rid="CIT0043">2010</xref>). Rebelo (<xref ref-type="bibr" rid="CIT0050">2006</xref>) also asserts that profitability has a negative impact on total debt, and Abor (<xref ref-type="bibr" rid="CIT0001">2005</xref>) claims that profitability has a negative impact on short-term debt.</p>
<p>Some other studies (Chadha &#x0026; Sharma <xref ref-type="bibr" rid="CIT0015">2015</xref>; Chang et al. <xref ref-type="bibr" rid="CIT0016">2009</xref>; Crnigoj &#x0026; Mramor <xref ref-type="bibr" rid="CIT0019">2009</xref>; Daskalakis &#x0026; Psillaki <xref ref-type="bibr" rid="CIT0020">2008</xref>; Psillaki &#x0026; Daskalakis <xref ref-type="bibr" rid="CIT0049">2009</xref>) found that profitability positively influences leverage, based on the trade-off theory. According to Jensen and Meckling (<xref ref-type="bibr" rid="CIT0030">1976</xref>), Myers (<xref ref-type="bibr" rid="CIT0039">1977</xref>) and Harris and Raviv (<xref ref-type="bibr" rid="CIT0026">1990</xref>), the tax shield benefits of debt outweigh any increase in debt cost, and this is related to a potential increase in the probability of default, which will induce profitable firms to use more debt. Psillaki and Daskalakis (<xref ref-type="bibr" rid="CIT0049">2009</xref>) add that:</p>
<disp-quote>
<p>The pecking order theory is especially appropriate for small and medium-sized firms &#x2026; These firms do not typically aim at a target debt ratio &#x2026; Instead, their financing decisions follow a hierarchy, with a preference for internal over external finance, and for debt over equity. (pp. 325&#x2013;326)</p>
</disp-quote>
<p>Abor and Biekpe (<xref ref-type="bibr" rid="CIT0002">2009</xref>) link profitability with age, risk and growth. They found that profitability has a negative relationship with age and growth. At the same time, risk has a positive link with profitability. Lastly, Brito et al. (<xref ref-type="bibr" rid="CIT0013">2006</xref>) found that profitability is not a crucial factor in capital structure. Thus, the following hypothesis was formulated for the present study:</p>
<disp-quote>
<p><bold>H5</bold>: A relationship exists between capital structure and profitability.</p>
</disp-quote>
</sec>
<sec id="s20009">
<title>Tangibility</title>
<p>Firms with higher tangible assets can use debt more easily as creditors believe these firms can fulfil their obligations more easily. Therefore, tangibility should positively influence leverage.</p>
<p>While Couto and Ferreira (<xref ref-type="bibr" rid="CIT0018">2010</xref>) and Chadha and Sharma (<xref ref-type="bibr" rid="CIT0015">2015</xref>) assert that tangibility is a determinant factor of capital structure, Nunkoo and Boateng (<xref ref-type="bibr" rid="CIT0043">2010</xref>) argue that tangibility has a positive influence on leverage. <xref ref-type="fn" rid="FN0001"><sup>1</sup></xref> In addition, Onaolapo and Kajola (<xref ref-type="bibr" rid="CIT0046">2010</xref>) contend that tangibility is negatively influenced by profitability, and Serrasqueiro and Nunes (<xref ref-type="bibr" rid="CIT0057">2010</xref>) maintain that there is no positive relationship between debt and tangibility. However, Ahmed et al. (<xref ref-type="bibr" rid="CIT0003">2010</xref>) suggest that leverage has no statistical relevance in terms of asset tangibility. Accordingly, the following hypothesis was suggested in the present study:</p>
<disp-quote>
<p><bold>H6</bold>: A relationship exists between capital structure and tangibility.</p>
</disp-quote>
</sec>
<sec id="s20010">
<title>Non-debt tax shields</title>
<p>Non-debt tax shields (NDTS) are characterised by the weight assigned to the depreciation of assets (Rebelo <xref ref-type="bibr" rid="CIT0050">2006</xref>). Although, for Chadha and Sharma (<xref ref-type="bibr" rid="CIT0015">2015</xref>), NDTS influence the capital structure of Indian manufacturing firms, according to Rebelo (<xref ref-type="bibr" rid="CIT0050">2006</xref>), NDTS do not seem to be a factor when it comes to technology firms&#x2019; level of debt. However, Serrasqueiro and Nunes (<xref ref-type="bibr" rid="CIT0057">2010</xref>) say that there is no relationship between NDTS and debt. Therefore, it was decided to test the following hypothesis in the present study:</p>
<disp-quote>
<p><bold>H7</bold>: A relationship exists between capital structure and NDTS.</p>
</disp-quote>
</sec>
<sec id="s20011">
<title>Growth</title>
<p>The growth of firms is expected to have a positive impact on leverage. However, some studies have concluded otherwise, which might be a consequence of using different variables for growth, such as net assets growth rate (Couto &#x0026; Ferreira <xref ref-type="bibr" rid="CIT0018">2010</xref>; Rebelo <xref ref-type="bibr" rid="CIT0050">2006</xref>), total assets growth rate (Chang et al. <xref ref-type="bibr" rid="CIT0016">2009</xref>; Nunkoo &#x0026; Boateng <xref ref-type="bibr" rid="CIT0043">2010</xref>) or speed of adjustment (Oinoa &#x0026; Ukaegbu <xref ref-type="bibr" rid="CIT0044">2015</xref>). Sbeiti (<xref ref-type="bibr" rid="CIT0056">2010</xref>) argues that growth needs to be defined through the following ratio: total assets book value minus net assets book value and the market value of equity over the total assets book value.</p>
<p>Another definition given for growth is firms&#x2019; market value divided by the firms&#x2019; book value (Karadeniz et al. <xref ref-type="bibr" rid="CIT0032">2009</xref>). Although Abor and Biekpe (<xref ref-type="bibr" rid="CIT0002">2009</xref>) define growth as sales growth, Brito et al. (<xref ref-type="bibr" rid="CIT0013">2006</xref>) use a sales logarithm (Ln).</p>
<p>Studies have produced contradictory results. While Couto and Ferreira (<xref ref-type="bibr" rid="CIT0018">2010</xref>) assert that growth does not explain the level of debt, Rebelo (<xref ref-type="bibr" rid="CIT0050">2006</xref>) and Chadha and Sharma (<xref ref-type="bibr" rid="CIT0015">2015</xref>) argue that growth has a positive impact on the total debt. Moreover, Chang et al. (<xref ref-type="bibr" rid="CIT0016">2009</xref>), Nunko and Boateng (<xref ref-type="bibr" rid="CIT0043">2010</xref>) and Sbeiti (<xref ref-type="bibr" rid="CIT0056">2010</xref>) found that growth has a negative impact on leverage, when growth is measured by the market-to-book ratio (Chang et al. <xref ref-type="bibr" rid="CIT0016">2009</xref>) and by market leverage (Sbeiti <xref ref-type="bibr" rid="CIT0056">2010</xref>).</p>
<p>Karadeniz et al. (<xref ref-type="bibr" rid="CIT0032">2009</xref>) maintain that growth and debt are not correlated in Turkish firms. However, Brito et al. (<xref ref-type="bibr" rid="CIT0013">2006</xref>) assert that growth has a positive relationship with long-term debt. This evidence goes against bankruptcy cost and agency cost theories but confirms the information asymmetry theory, that is, firms finance their growth through debt to indicate to the market that their shares are underestimated (Brito et al. <xref ref-type="bibr" rid="CIT0013">2006</xref>).</p>
<p>Lastly, Abor and Biekpe (<xref ref-type="bibr" rid="CIT0002">2009</xref>) also argue that growth has a positive relationship with long-term debt as growth usually puts pressure on retained earnings. For example, high-growth Ghanaian firms incur more external debt when they finance operations. Nevertheless, as financing opportunities can create conflicts between creditors and managers, small firms use more short-term debt (Abor &#x0026; Biekpe <xref ref-type="bibr" rid="CIT0002">2009</xref>).</p>
</sec>
<sec id="s20012">
<title>Size</title>
<p>As large firms are usually more diversified than smaller firms are, they are less prone to financial difficulties and have fewer bankruptcy costs (Brito et al. <xref ref-type="bibr" rid="CIT0013">2006</xref>; Omet et al. <xref ref-type="bibr" rid="CIT0045">2015</xref>). Therefore, it is expected for size to have a positive influence on leverage.<xref ref-type="fn" rid="FN0002"><sup>2</sup></xref></p>
<p>Although Nunkoo and Boateng (<xref ref-type="bibr" rid="CIT0043">2010</xref>) maintain that size has a negative influence on leverage, most studies argue otherwise (Ahmed et al. <xref ref-type="bibr" rid="CIT0003">2010</xref>; Brito et al. <xref ref-type="bibr" rid="CIT0013">2006</xref>; Crnigoj &#x0026; Mramor <xref ref-type="bibr" rid="CIT0019">2009</xref>; Daskalakis &#x0026; Psillaki <xref ref-type="bibr" rid="CIT0020">2008</xref>; Menike <xref ref-type="bibr" rid="CIT0037">2015</xref>; Psillaki &#x0026; Daskalakis <xref ref-type="bibr" rid="CIT0049">2009</xref>; Sbeiti <xref ref-type="bibr" rid="CIT0056">2010</xref>).</p>
<p>Bhaird and Lucey (<xref ref-type="bibr" rid="CIT0010">2010</xref>) were able to determine that size has a positive relationship with profit since surviving firms are increasingly dependent on internal capital and their accumulated profits are reinvested. Lastly, Karadeniz et al. (<xref ref-type="bibr" rid="CIT0032">2009</xref>) found that size does not appear to be linked to debt ratio.</p>
</sec>
</sec>
<sec id="s0013">
<title>Data, estimation methodology and model</title>
<sec id="s20014">
<title>Data</title>
<p>Studies of capital structure and the main factors considered when choosing it are increasingly important in the corporate finance literature. In this study, the goal was to analyse a specific case not studied before: Portuguese firms with direct investments in Angola. Thus, this study had the objective of verifying how the following factors influence the capital structure of Portuguese firms with subsidiaries or branches in Angola: asset structure, age, liquidity, intangibility, profitability, tangibility and NDTS. Although other determinants influence capital structure (i.e. growth and size), they were not included in this study because of the unavailability of data for the firms in our sample. <xref ref-type="table" rid="T0001">Table 1</xref> below summarises the hypotheses tested and the corresponding random variables linked with their measurement.</p>
<table-wrap id="T0001">
<label>TABLE 1</label>
<caption><p>Explained variables, explanatory variables and hypotheses.</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th valign="top" align="left">Variables</th>
<th valign="top" align="left">Hypotheses</th>
<th valign="top" align="left">Variables description</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left"><bold>Explained</bold></td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">Leverage ratio</td>
<td align="left">-</td>
<td align="left">Leverage_Ratio = Ln(total liabilities/total assets)</td>
</tr>
<tr>
<td align="left"><bold>Explanatory</bold></td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">Asset structure</td>
<td align="left">H1: A relationship exists between capital structure and asset structure</td>
<td align="left">Asset_Structure = Ln(fixed assets/total assets)</td>
</tr>
<tr>
<td align="left">Age</td>
<td align="left">H2: A relationship exists between capital structure and age</td>
<td align="left">Age = Ln(Age)</td>
</tr>
<tr>
<td align="left">Liquidity</td>
<td align="left">H3: A relationship exists between capital structure and liquidity</td>
<td align="left">Liquidity = Ln(total net assets/short-term debt)</td>
</tr>
<tr>
<td align="left">Intangibility</td>
<td align="left">H4: A relationship exists between capital structure and intangibility</td>
<td align="left">Intangibility = Ln( intangible assets)</td>
</tr>
<tr>
<td align="left">Profitability</td>
<td align="left">H5: A relationship exists between capital structure and profitability</td>
<td align="left">Return_on_sales = Ln(net income/sales); Return_on_Assets&#x00A0;= Ln(earnings before interests/total assets)</td>
</tr>
<tr>
<td align="left">Tangibility</td>
<td align="left">H6: A relationship exists between capital structure and tangibility</td>
<td align="left">Tangi = Ln(tangible fixed assets/total assets)</td>
</tr>
<tr>
<td align="left">Non-debt tax shields</td>
<td align="left">H7: A relationship exists between capital structure and NDTS</td>
<td align="left">Non-Debt_Tax_Shields = Ln(depreciation/total net assets)</td>
</tr>
</tbody>
</table>
</table-wrap>
<p>The sample in study comprises 26 firms dating to the period 2006&#x2013;2010, which were chosen according to the availability of data. The data were gathered by using a list of the Portuguese firms with direct investments abroad, provided by the Agency for Investment and External Trade of Portugal in Luanda.</p>
<p>Based on this list, an analysis of the firms&#x2019; websites was conducted with the objective of collecting the information available. Firms without any website or information were first contacted via e-mail to acquire the required data. In the cases in which no information was acquired, telephone calls were made. The banks on the list were not considered, given that they have a different tax code, accounting rules and operation modes. Information, thus, was collected from the following firms: Compta, Auto Sueco, FDO, Conduril, Enoport, Eurico Ferreira, Galp, Visabeira, Martifer, Mota-Engil, Monteadriano, Orey, Petrotec, PT, Sumol, Tom&#x00E1;s de Oliveira, Obrecol, EFACEC, Glintt, Opway, M. Couto Alves, Abrantina, Soares da Costa, Somague, Teixeira Duarte and MSF.</p>
<p>The data were extracted from the consolidated financial reports and statements of these 26 firms, which were normally made available on their websites. The collected data cover the following variables: total assets, fixed assets, tangible fixed assets, intangible assets, total net assets, depreciations, equity capital, short-term debt, long-term debt, total debt, liabilities, net profits, distributed dividends, sales, earnings before taxes, price per share, size and age.</p>
</sec>
<sec id="s20015">
<title>Estimation methods and model</title>
<p>According to Hsiao (<xref ref-type="bibr" rid="CIT0028">2003</xref>), panel data methodology uses a set of data that follows a given sample over a period, providing multiple observations for each variable in the sample. This methodology increases the amount of data because of the cross between longitudinal and time series study methods. This increases the degrees of freedom and decreases the collinearity between explanatory variables, which leads to a greater efficiency of the econometric estimation. This methodology also allows the researcher to analyse various economic issues that cannot be accurately studied using only longitudinal or time series studies. The main advantages of this methodology are (Wooldridge <xref ref-type="bibr" rid="CIT0062">2010</xref>) that the estimates are more efficient as the variables are less collinear, the opportunity to analyse individual dynamics, more information about the ordering of events over time and the opportunity to control any heterogeneity not identified individually.</p>
<p>Fixed and random effects models were considered (two estimation methods inside the panel data models) when specifying the econometric model. The rationale behind the choice between the two models are: the fixed effects model is the most suited to analyse the exclusive impact of variables that change over time &#x2013; that is, this model is suitable for studying the causes of change inside an entity (Gujarati <xref ref-type="bibr" rid="CIT0024">2003</xref>; Hsiao <xref ref-type="bibr" rid="CIT0028">2003</xref>); in random effects model, changes in individuals or cases are seen to be random and not correlated with the independent variables included in the conceptual model, allowing the variables that do not change over time to play an important role as explanatory variables, in marked contrast to the fixed effects model (Johnston &#x0026; Dinardo <xref ref-type="bibr" rid="CIT0031">1997</xref>).</p>
<p>Complementarily, a test created by Hausman allows researchers to ascertain which model is more suitable: the null hypothesis assumes that the random effects estimator is the most appropriate (Johnston &#x0026; Dinardo <xref ref-type="bibr" rid="CIT0031">1997</xref>). Thus, if the null hypothesis is rejected, the random effects model cannot be the most appropriate, and the fixed effects model should be chosen (Gujarati <xref ref-type="bibr" rid="CIT0024">2003</xref>).</p>
<p>Although, panel data models can be estimated even when there are severe deviations from the classical assumptions and &#x2018;complex error compositions&#x2019; are present (Basu &#x0026; Rajeev <xref ref-type="bibr" rid="CIT0007">2013</xref>; Couto &#x0026; Ferreira <xref ref-type="bibr" rid="CIT0018">2010</xref>; Marques &#x0026; Fuinhas <xref ref-type="bibr" rid="CIT0035">2012</xref>:11; Petersen <xref ref-type="bibr" rid="CIT0048">2009</xref>), the inadequate verification of the existence of heteroscedasticity and autocorrelation phenomena in panel data models can lead to inefficiency and biased estimates of coefficients and standard errors.</p>
<p>Therefore, the panel data model needs to be complemented by carrying out tests to verify the presence or absence of <italic>heteroscedasticity</italic> and cross-sectional independence. Furthermore, whenever there are divergences regarding the classical assumptions of the aforementioned cases, it is necessary to introduce the respective corrections, not to compromise the suitability of the results.</p>
<p>The procedure needs to be as follows. After testing for the presence of heteroscedasticity and panel autocorrelation, if any deviation from the classical assumptions is detected, Beck and Katz&#x2019;s (<xref ref-type="bibr" rid="CIT0009">1995</xref>) correction factor &#x2013; panel-corrected standard errors (PCSE)<xref ref-type="fn" rid="FN0003"><sup>3</sup></xref> &#x2013; should be applied. The PCSE estimator performs well in the presence of panel-level heteroscedasticity and contemporaneous correlation of observations among panels.<xref ref-type="fn" rid="FN0004"><sup>4</sup></xref></p>
<p>Marques and Fuinhas (<xref ref-type="bibr" rid="CIT0035">2012</xref>), who studied the robustness of results obtained by the PCSE estimator as compared with the results obtained by standard panel data estimators (i.e. fixed and random effects), assert that the use of the PCSE model is indeed the most adequate method, as this provides the best results. To test the formulated hypotheses empirically and take into account the defined methodology, the following model was defined<xref ref-type="fn" rid="FN0005"><sup>5</sup></xref>:
<disp-formula id="FD0001"><alternatives><mml:math id="M1" display="block"><mml:semantics><mml:mtable columnalign="left"><mml:mtr><mml:mtd><mml:mi>L</mml:mi><mml:mi>e</mml:mi><mml:mi>v</mml:mi><mml:mi>e</mml:mi><mml:mi>r</mml:mi><mml:mi>a</mml:mi><mml:mi>g</mml:mi><mml:mi>e</mml:mi><mml:mo>&#x005F;</mml:mo><mml:mi>R</mml:mi><mml:mi>a</mml:mi><mml:mi>t</mml:mi><mml:mi>i</mml:mi><mml:msub><mml:mi>o</mml:mi><mml:mrow><mml:mi>i</mml:mi><mml:mi>t</mml:mi></mml:mrow></mml:msub></mml:mtd></mml:mtr><mml:mtr><mml:mtd><mml:mtext>&#x2003;</mml:mtext><mml:mo>=</mml:mo><mml:msub><mml:mi>&#x03B2;</mml:mi><mml:mn>1</mml:mn></mml:msub><mml:mo>+</mml:mo><mml:msub><mml:mi>&#x03B2;</mml:mi><mml:mn>2</mml:mn></mml:msub><mml:mi>A</mml:mi><mml:mi>s</mml:mi><mml:mi>s</mml:mi><mml:mi>e</mml:mi><mml:mi>t</mml:mi><mml:mo>&#x005F;</mml:mo><mml:mi>S</mml:mi><mml:mi>t</mml:mi><mml:mi>r</mml:mi><mml:mi>u</mml:mi><mml:mi>c</mml:mi><mml:mi>t</mml:mi><mml:mi>u</mml:mi><mml:mi>r</mml:mi><mml:msub><mml:mi>e</mml:mi><mml:mrow><mml:mi>i</mml:mi><mml:mi>t</mml:mi></mml:mrow></mml:msub><mml:mo>+</mml:mo><mml:msub><mml:mi>&#x03B2;</mml:mi><mml:mn>3</mml:mn></mml:msub><mml:mi>A</mml:mi><mml:mi>g</mml:mi><mml:msub><mml:mi>e</mml:mi><mml:mrow><mml:mi>i</mml:mi><mml:mi>t</mml:mi></mml:mrow></mml:msub><mml:mo>+</mml:mo><mml:msub><mml:mi>&#x03B2;</mml:mi><mml:mn>4</mml:mn></mml:msub><mml:mi>L</mml:mi><mml:mi>i</mml:mi><mml:mi>q</mml:mi><mml:mi>u</mml:mi><mml:mi>i</mml:mi><mml:mi>d</mml:mi><mml:mi>i</mml:mi><mml:mi>t</mml:mi><mml:msub><mml:mi>y</mml:mi><mml:mrow><mml:mi>i</mml:mi><mml:mi>t</mml:mi></mml:mrow></mml:msub></mml:mtd></mml:mtr><mml:mtr><mml:mtd><mml:mtext>&#x2003;</mml:mtext><mml:mo>+</mml:mo><mml:msub><mml:mi>&#x03B2;</mml:mi><mml:mn>5</mml:mn></mml:msub><mml:mi>I</mml:mi><mml:mi>n</mml:mi><mml:mi>t</mml:mi><mml:mi>a</mml:mi><mml:mi>n</mml:mi><mml:mi>g</mml:mi><mml:mi>i</mml:mi><mml:mi>b</mml:mi><mml:mi>l</mml:mi><mml:mi>e</mml:mi><mml:mo>&#x005F;</mml:mo><mml:mi>A</mml:mi><mml:mi>c</mml:mi><mml:mi>t</mml:mi><mml:mi>i</mml:mi><mml:mi>v</mml:mi><mml:mi>i</mml:mi><mml:mi>t</mml:mi><mml:mi>y</mml:mi><mml:mo>&#x005F;</mml:mo><mml:mi>L</mml:mi><mml:mi>e</mml:mi><mml:mi>v</mml:mi><mml:mi>e</mml:mi><mml:msub><mml:mi>l</mml:mi><mml:mrow><mml:mi>i</mml:mi><mml:mi>t</mml:mi></mml:mrow></mml:msub><mml:mo>+</mml:mo><mml:msub><mml:mi>&#x03B2;</mml:mi><mml:mn>6</mml:mn></mml:msub><mml:mi>R</mml:mi><mml:mi>e</mml:mi><mml:mi>t</mml:mi><mml:mi>u</mml:mi><mml:mi>r</mml:mi><mml:mi>n</mml:mi><mml:mo>&#x005F;</mml:mo><mml:mi>o</mml:mi><mml:mi>n</mml:mi><mml:mo>&#x005F;</mml:mo><mml:mi>s</mml:mi><mml:mi>a</mml:mi><mml:mi>l</mml:mi><mml:mi>e</mml:mi><mml:msub><mml:mi>s</mml:mi><mml:mrow><mml:mi>i</mml:mi><mml:mi>t</mml:mi></mml:mrow></mml:msub></mml:mtd></mml:mtr><mml:mtr><mml:mtd><mml:mtext>&#x2003;</mml:mtext><mml:mo>+</mml:mo><mml:msub><mml:mi>&#x03B2;</mml:mi><mml:mn>7</mml:mn></mml:msub><mml:mi>R</mml:mi><mml:mi>e</mml:mi><mml:mi>t</mml:mi><mml:mi>u</mml:mi><mml:mi>r</mml:mi><mml:mi>n</mml:mi><mml:mo>&#x005F;</mml:mo><mml:mi>o</mml:mi><mml:mi>n</mml:mi><mml:mo>&#x005F;</mml:mo><mml:mi>a</mml:mi><mml:mi>s</mml:mi><mml:mi>s</mml:mi><mml:mi>e</mml:mi><mml:mi>t</mml:mi><mml:msub><mml:mi>s</mml:mi><mml:mrow><mml:mi>i</mml:mi><mml:mi>t</mml:mi></mml:mrow></mml:msub><mml:mo>+</mml:mo><mml:msub><mml:mi>&#x03B2;</mml:mi><mml:mn>8</mml:mn></mml:msub><mml:mi>T</mml:mi><mml:mi>a</mml:mi><mml:mi>n</mml:mi><mml:mi>g</mml:mi><mml:msub><mml:mi>i</mml:mi><mml:mrow><mml:mi>i</mml:mi><mml:mi>t</mml:mi></mml:mrow></mml:msub><mml:mo>+</mml:mo><mml:msub><mml:mi>&#x03B2;</mml:mi><mml:mn>9</mml:mn></mml:msub><mml:mi>N</mml:mi><mml:mi>o</mml:mi><mml:mi>n</mml:mi><mml:mo>&#x2212;</mml:mo><mml:mi>D</mml:mi><mml:mi>e</mml:mi><mml:mi>b</mml:mi><mml:mi>i</mml:mi><mml:mi>t</mml:mi><mml:mo>&#x005F;</mml:mo></mml:mtd></mml:mtr><mml:mtr><mml:mtd><mml:mtext>&#x2003;</mml:mtext><mml:mi>T</mml:mi><mml:mi>a</mml:mi><mml:mi>x</mml:mi><mml:mo>&#x005F;</mml:mo><mml:mi>S</mml:mi><mml:mi>h</mml:mi><mml:mi>i</mml:mi><mml:mi>e</mml:mi><mml:mi>l</mml:mi><mml:mi>d</mml:mi><mml:msub><mml:mi>s</mml:mi><mml:mrow><mml:mi>i</mml:mi><mml:mi>t</mml:mi></mml:mrow></mml:msub></mml:mtd></mml:mtr><mml:mtr><mml:mtd><mml:mtext>&#x2003;</mml:mtext><mml:mo>+</mml:mo><mml:msub><mml:mi>d</mml:mi><mml:mrow><mml:mn>1</mml:mn><mml:mi>i</mml:mi></mml:mrow></mml:msub><mml:mo>+</mml:mo><mml:msub><mml:mi>d</mml:mi><mml:mrow><mml:mn>1</mml:mn><mml:mi>t</mml:mi></mml:mrow></mml:msub><mml:mo>+</mml:mo><mml:msub><mml:mi>&#x03BC;</mml:mi><mml:mrow><mml:mi>i</mml:mi><mml:mi>t</mml:mi></mml:mrow></mml:msub></mml:mtd></mml:mtr></mml:mtable></mml:semantics></mml:math><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="SAJEMS-20-885-e001.tif"/></alternatives><label>[Eqn 1]</label></disp-formula></p>
</sec>
</sec>
<sec id="s0016">
<title>Results and discussion</title>
<p>To carry out the data analysis in this study, static panel data and econometric methodologies using the program STATA 11 were chosen. This study&#x2019;s data produced an unbalanced panel, given the lack of information for all variables in all the years covered. <xref ref-type="table" rid="T0004">Table A1</xref> in <xref ref-type="app" rid="app001">Appendix A</xref> shows the descriptive statistics.<xref ref-type="fn" rid="FN0006"><sup>6</sup></xref></p>
<p>Following established procedure, an initial analysis of the data was made. The results of the specification tests are outlined in <xref ref-type="table" rid="T0002">Table 2</xref>.</p>
<table-wrap id="T0002">
<label>TABLE 2</label>
<caption><p>Specification tests</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th valign="top" align="left">Type of test</th>
<th valign="top" align="center">Random effects</th>
<th valign="top" align="center">Fixed effects</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left">Modified Wald test (&#x03C7;2)</td>
<td align="center">-</td>
<td align="center">234.59<xref ref-type="table-fn" rid="TFN0001">&#x002A;</xref></td>
</tr>
<tr>
<td align="left">Wooldridge test F(N(0,1))</td>
<td align="center">4.501</td>
<td align="center">4.501</td>
</tr>
<tr>
<td align="left">Hausman test</td>
<td align="center">20.26<xref ref-type="table-fn" rid="TFN0001">&#x002A;</xref></td>
<td align="center">-</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn id="TFN0001"><label>&#x002A;</label><p>shows a significance level of 1&#x0025;.</p></fn>
</table-wrap-foot>
</table-wrap>
<p>A Wooldridge test was carried out to test the presence of autocorrelation. The results support the following conclusion: at a significance level of 5&#x0025;, the null hypothesis of no first order serial correlation cannot be rejected, that is, there is no serial correlation.</p>
<p>Following Baum&#x2019;s (<xref ref-type="bibr" rid="CIT0008">2001</xref>) guidelines, a modified Wald test was run to test for groupwise heteroscedasticity in the residuals of a fixed effect regression model. As seen in <xref ref-type="table" rid="T0002">Table 2</xref>, the null hypothesis of homoscedasticity is rejected, so the claim can be made that the errors exhibit groupwise heteroscedasticity. Lastly, the results of a Hausman test &#x2013; the null hypothesis posits that the individual-level effects are adequately modelled by a random effects model &#x2013; support the following conclusion: the null hypothesis is rejected, and the fixed effects model is the most suitable model for this study.</p>
<p>Given that there is a deviation in classical assumptions, in particular when it comes to the existence of heteroscedasticity, the PCSE estimator had to be used to rectify the deviation.</p>
<p><xref ref-type="table" rid="T0003">Table 3</xref> displays the results of the model using fixed effects and random effects and applying the PCSE estimators. For the first two models, the results are presented without any model correction [i.e. conventional standard errors (CSE)], using robust standard error (RSE).</p>
<table-wrap id="T0003">
<label>TABLE 3</label>
<caption><p>Models with application of the robust standard error to random and fixed effects models</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th valign="top" align="left" rowspan="3">Variables</th>
<th valign="top" align="center" colspan="4">PCSE<hr/></th>
<th valign="top" align="center" colspan="4">RSE<hr/></th>
<th valign="top" align="center" colspan="4">CSE<hr/></th>
</tr>
<tr>
<th valign="top" align="center" colspan="2">Hetonly<hr/></th>
<th valign="top" align="center" colspan="2">Corr(AR1) hetonly<hr/></th>
<th valign="top" align="center" colspan="2">Fixed effects<hr/></th>
<th valign="top" align="center" colspan="2">Random effects<hr/></th>
<th valign="top" align="center" colspan="2">Fixed effects<hr/></th>
<th valign="top" align="center" colspan="2">Random effects<hr/></th>
</tr>
<tr>
<th valign="top" align="center">Coefficient</th>
<th valign="top" align="center"><italic>p</italic></th>
<th valign="top" align="center">Coefficient</th>
<th valign="top" align="center"><italic>p</italic></th>
<th valign="top" align="center">Coefficient</th>
<th valign="top" align="center"><italic>p</italic></th>
<th valign="top" align="center">Coefficient</th>
<th valign="top" align="center"><italic>p</italic></th>
<th valign="top" align="center">Coefficient</th>
<th valign="top" align="center"><italic>p</italic></th>
<th valign="top" align="center">Coefficient</th>
<th valign="top" align="center"><italic>p</italic></th>
</tr>
</thead>
<tbody>
<tr>
<td align="left">Asset_Structure</td>
<td align="center">0.2079</td>
<td align="center">0.009<xref ref-type="table-fn" rid="TFN0002">&#x002A;&#x002A;&#x002A;</xref></td>
<td align="center">0.2011</td>
<td align="center">0.016<xref ref-type="table-fn" rid="TFN0002">&#x002A;&#x002A;</xref></td>
<td align="center">0.1703</td>
<td align="center">0.316</td>
<td align="center">0.2174</td>
<td align="center">0.098<xref ref-type="table-fn" rid="TFN0002">&#x002A;</xref></td>
<td align="center">0.1703</td>
<td align="center">0.050<xref ref-type="table-fn" rid="TFN0002">&#x002A;</xref></td>
<td align="center">0.2174</td>
<td align="center">0.003<xref ref-type="table-fn" rid="TFN0002">&#x002A;&#x002A;&#x002A;</xref></td>
</tr>
<tr>
<td align="left">Age</td>
<td align="center">0.1483</td>
<td align="center">0.000<xref ref-type="table-fn" rid="TFN0002">&#x002A;&#x002A;&#x002A;</xref></td>
<td align="center">0.1390</td>
<td align="center">0.017<xref ref-type="table-fn" rid="TFN0002">&#x002A;&#x002A;</xref></td>
<td align="center">0.2784</td>
<td align="center">0.267</td>
<td align="center">0.1473</td>
<td align="center">0.052<xref ref-type="table-fn" rid="TFN0002">&#x002A;</xref></td>
<td align="center">0.2784</td>
<td align="center">0.400</td>
<td align="center">0.1473</td>
<td align="center">0.046<xref ref-type="table-fn" rid="TFN0002">&#x002A;&#x002A;</xref></td>
</tr>
<tr>
<td align="left">Liquidity</td>
<td align="center">-0.4566</td>
<td align="center">0.000<xref ref-type="table-fn" rid="TFN0002">&#x002A;&#x002A;&#x002A;</xref></td>
<td align="center">-0.5174</td>
<td align="center">0.000<xref ref-type="table-fn" rid="TFN0002">&#x002A;&#x002A;&#x002A;</xref></td>
<td align="center">-0.6412</td>
<td align="center">0.000<xref ref-type="table-fn" rid="TFN0002">&#x002A;&#x002A;&#x002A;</xref></td>
<td align="center">-0.5255</td>
<td align="center">0.007<xref ref-type="table-fn" rid="TFN0002">&#x002A;&#x002A;&#x002A;</xref></td>
<td align="center">-0.6411</td>
<td align="center">0.000<xref ref-type="table-fn" rid="TFN0002">&#x002A;&#x002A;&#x002A;</xref></td>
<td align="center">-0.5255</td>
<td align="center">0.000<xref ref-type="table-fn" rid="TFN0002">&#x002A;&#x002A;&#x002A;</xref></td>
</tr>
<tr>
<td align="left">Intangibility</td>
<td align="center">0.0148</td>
<td align="center">0.289</td>
<td align="center">0.0149</td>
<td align="center">0.341</td>
<td align="center">-0.0205</td>
<td align="center">0.271</td>
<td align="center">0.0128</td>
<td align="center">0.508</td>
<td align="center">-0.0205</td>
<td align="center">0.542</td>
<td align="center">0.0128</td>
<td align="center">0.479</td>
</tr>
<tr>
<td align="left">Return_on_sales</td>
<td align="center">0.0248</td>
<td align="center">0.378</td>
<td align="center">0.0291</td>
<td align="center">0.318</td>
<td align="center">0.0382</td>
<td align="center">0.353</td>
<td align="center">0.0322</td>
<td align="center">0.238</td>
<td align="center">0.0382</td>
<td align="center">0.315</td>
<td align="center">0.0322</td>
<td align="center">0.210</td>
</tr>
<tr>
<td align="left">Return_on_assets</td>
<td align="center">0.1178</td>
<td align="center">0.073<xref ref-type="table-fn" rid="TFN0002">&#x002A;</xref></td>
<td align="center">0.1517</td>
<td align="center">0.046<xref ref-type="table-fn" rid="TFN0002">&#x002A;&#x002A;</xref></td>
<td align="center">0.4089</td>
<td align="center">0.008<xref ref-type="table-fn" rid="TFN0002">&#x002A;&#x002A;&#x002A;</xref></td>
<td align="center">0.1780</td>
<td align="center">0.175</td>
<td align="center">0.4089</td>
<td align="center">0.000<xref ref-type="table-fn" rid="TFN0002">&#x002A;&#x002A;&#x002A;</xref></td>
<td align="center">0.1780</td>
<td align="center">0.002<xref ref-type="table-fn" rid="TFN0002">&#x002A;&#x002A;&#x002A;</xref></td>
</tr>
<tr>
<td align="left">Tangi</td>
<td align="center">0.1675</td>
<td align="center">0.029<xref ref-type="table-fn" rid="TFN0002">&#x002A;&#x002A;</xref></td>
<td align="center">0.1997</td>
<td align="center">0.031<xref ref-type="table-fn" rid="TFN0002">&#x002A;&#x002A;</xref></td>
<td align="center">-0.1126</td>
<td align="center">0.498</td>
<td align="center">0.2158</td>
<td align="center">0.091<xref ref-type="table-fn" rid="TFN0002">&#x002A;</xref></td>
<td align="center">-0.1126</td>
<td align="center">0.623</td>
<td align="center">0.2158</td>
<td align="center">0.028<xref ref-type="table-fn" rid="TFN0002">&#x002A;&#x002A;</xref></td>
</tr>
<tr>
<td align="left">Non-Debt_Tax_Shields</td>
<td align="center">-0.1999</td>
<td align="center">0.015<xref ref-type="table-fn" rid="TFN0002">&#x002A;&#x002A;</xref></td>
<td align="center">-0.2664</td>
<td align="center">0.003<xref ref-type="table-fn" rid="TFN0002">&#x002A;&#x002A;&#x002A;</xref></td>
<td align="center">-0.2093</td>
<td align="center">0.271</td>
<td align="center">-0.2586</td>
<td align="center">0.083<xref ref-type="table-fn" rid="TFN0002">&#x002A;</xref></td>
<td align="center">-0.2093</td>
<td align="center">0.021<xref ref-type="table-fn" rid="TFN0002">&#x002A;&#x002A;</xref></td>
<td align="center">-0.2586</td>
<td align="center">0.000<xref ref-type="table-fn" rid="TFN0002">&#x002A;&#x002A;&#x002A;</xref></td>
</tr>
<tr>
<td align="left">Constant</td>
<td align="center">-1.1304</td>
<td align="center">0.002<xref ref-type="table-fn" rid="TFN0002">&#x002A;&#x002A;&#x002A;</xref></td>
<td align="center">-1.2423</td>
<td align="center">0.006<xref ref-type="table-fn" rid="TFN0002">&#x002A;&#x002A;&#x002A;</xref></td>
<td align="center">-1.6314</td>
<td align="center">0.081<xref ref-type="table-fn" rid="TFN0002">&#x002A;</xref></td>
<td align="center">-1.1820</td>
<td align="center">0.002<xref ref-type="table-fn" rid="TFN0002">&#x002A;&#x002A;&#x002A;</xref></td>
<td align="center">-1.6314</td>
<td align="center">0.223</td>
<td align="center">-1.1820</td>
<td align="center">0.023<xref ref-type="table-fn" rid="TFN0002">&#x002A;&#x002A;</xref></td>
</tr>
<tr>
<td align="left">Observations</td>
<td align="center">70</td>
<td align="center">-</td>
<td align="center">70</td>
<td align="center">-</td>
<td align="center">70</td>
<td align="center">-</td>
<td align="center">70</td>
<td align="center">-</td>
<td align="center">70</td>
<td align="center">-</td>
<td align="center">70</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left"><italic>R</italic><sup>2</sup>/Pseudo <italic>R</italic><sup>2</sup></td>
<td align="center">0.5717</td>
<td align="center">-</td>
<td align="center">0.5913</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">-</td>
</tr>
<tr>
<td align="left">F test</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">12.29</td>
<td align="center">0.000<xref ref-type="table-fn" rid="TFN0002">&#x002A;&#x002A;&#x002A;</xref></td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">15.72</td>
<td align="center">0.000<xref ref-type="table-fn" rid="TFN0002">&#x002A;&#x002A;&#x002A;</xref></td>
<td align="center">98.11</td>
<td align="center">0.000<xref ref-type="table-fn" rid="TFN0002">&#x002A;&#x002A;&#x002A;</xref></td>
</tr>
<tr>
<td align="left">Wald (&#x03C7;2)</td>
<td align="center">82.69</td>
<td align="center">0.000<xref ref-type="table-fn" rid="TFN0002">&#x002A;&#x002A;&#x002A;</xref></td>
<td align="center">57.82</td>
<td align="center">0.000<xref ref-type="table-fn" rid="TFN0002">&#x002A;&#x002A;&#x002A;</xref></td>
<td align="center">-</td>
<td align="center">-</td>
<td align="center">37.49</td>
<td align="center">0.000<xref ref-type="table-fn" rid="TFN0002">&#x002A;&#x002A;&#x002A;</xref></td>
<td align="center">0.1703</td>
<td align="center">0.050<xref ref-type="table-fn" rid="TFN0002">&#x002A;</xref></td>
<td align="center">0.2174</td>
<td align="center">0.003<xref ref-type="table-fn" rid="TFN0002">&#x002A;&#x002A;&#x002A;</xref></td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn><p>PCSE, panel-corrected standard errors; RSE, robust standard errors; CSE, conventional standard errors.</p></fn>
<fn><p>Dependent variable: Liabilities/Total Assets; Corr(AR1) &#x2013; first order autocorrelation AR(1), in which the coefficient of AR(1) is the same for all panels; hetonly specifies that deviations are taken as heteroscedastic. The item of test F tests the null hypothesis of there not being significance for the model on the whole (of the estimated parameters). The Wald test (&#x03C7;2) evaluates the null hypothesis of there not being significant for all coefficients of all explanatory variables.</p></fn>
<fn id="TFN0002"><p>&#x002A;&#x002A;&#x002A;, &#x002A;&#x002A;, &#x002A;, refer to significance level from 1&#x0025;, 5&#x0025; to 10&#x0025;, respectively.</p></fn>
</table-wrap-foot>
</table-wrap>
<p>The results of the fixed effect and random effect models, with CSE and RSE, allow a comparison of the robustness of results achieved by the PCSE estimator with the results achieved by fixed and variable effects estimators. The analysis was then continued using data from the PCSE estimator as it is considered to be more robust and to provide better results.</p>
<p>From all the hypotheses subjected to empirical analysis, only two were not statistically significant: Hypotheses 4 and, partially, 5. These postulated the existence of a relationship between capital structure and the level of intangibility and return on sales and/or return on assets. For the second hypothesis, only the relationship with return on sales was not statistically significant.</p>
<p>The analysis results shown in <xref ref-type="table" rid="T0003">Table 3</xref> confirm that variables such as asset structure, age, liquidity, tangibility and NDTS have a <italic>p</italic>-value below 5&#x0025;. The return on assets has a <italic>p</italic>-value below 10&#x0025;. This leads to the rejection of the null hypothesis of the aforementioned variables not being statistically significant.</p>
<p>As can be observed, the asset structure (i.e. Hypothesis 1) has a positive impact on the leverage ratio (0.2079). This conclusion goes against what Rebelo (<xref ref-type="bibr" rid="CIT0050">2006</xref>) proposes but corroborates the findings of Brito et al. (<xref ref-type="bibr" rid="CIT0013">2006</xref>), who claim that the asset structure has a positive influence on long-term debt, which overlaps with its negative impact on short-term debt (Chadha &#x0026; Sharma <xref ref-type="bibr" rid="CIT0015">2015</xref>; Handoo &#x0026; Sharma <xref ref-type="bibr" rid="CIT0025">2014</xref>; Omet et al. <xref ref-type="bibr" rid="CIT0045">2015</xref>).</p>
<p>A firm&#x2019;s age (i.e. Hypothesis 2) also has a positive impact on the leverage ratio (0.1483). This conclusion agrees with the results achieved by Abor and Biekpe (<xref ref-type="bibr" rid="CIT0002">2009</xref>) and Chadha and Sharma (<xref ref-type="bibr" rid="CIT0015">2015</xref>). They assert that age is an important factor when accessing capital through loans. The case of Portuguese firms with investments in Angola shows that the age of firms can be used as an advantage to obtain financing for their investments in Angola.</p>
<p>Liquidity (i.e. Hypothesis 3) has a negative impact on the leverage ratio (-0.4566), which is in agreement with the results obtained by Sbeiti (<xref ref-type="bibr" rid="CIT0056">2010</xref>), who maintains that firms with a higher level of liquidity usually avoid the use of external debt. Concerning the firms studied, the liquidity level is in most cases used to finance their own assets in Angola.</p>
<p>Profitability was divided into return on sales and return on assets (i.e. Hypothesis 5). However, only the positive (0.1178) relationship between the leverage ratio and returns on assets is statistically significant, which is in agreement with Psillaki and Daskalakis (<xref ref-type="bibr" rid="CIT0049">2009</xref>), Crnigoj and Mramor (<xref ref-type="bibr" rid="CIT0019">2009</xref>) and Chang et al.&#x2019;s (<xref ref-type="bibr" rid="CIT0016">2009</xref>) conclusions. Therefore, we can say that it is clear that the firms analysed choose to invest in Angola when their return on assets allows it, an approach that tries to diminish investment risks and pursue a path of sustained growth. The fact that return on sales is not statistically significant is related to the fact that, when firms decide to invest in Angola, they consider not only normal, short-term business outcomes but also the outcomes of normal, long-term investment.</p>
<p>The assets&#x2019; tangibility (i.e. Hypothesis 6) has a positive influence on the leverage ratio (0.1675) since firms with higher tangible assets can more easily use debt because they have collateral to present to banks. This conclusion was also reached by Nunkoo and Boateng (<xref ref-type="bibr" rid="CIT0043">2010</xref>), Handoo and Sharma (<xref ref-type="bibr" rid="CIT0025">2014</xref>), Chadha and Sharma (<xref ref-type="bibr" rid="CIT0015">2015</xref>) and Omet et al. (<xref ref-type="bibr" rid="CIT0045">2015</xref>).</p>
<p>NDTS (i.e. Hypothesis 7) maintain a negative relationship with the leverage ratio (-0.1999). This conclusion contradicts the findings of authors such as Rebelo (<xref ref-type="bibr" rid="CIT0050">2006</xref>) and Serrasqueiro and Nunes (<xref ref-type="bibr" rid="CIT0057">2010</xref>), who did not find any evidence that this factor has an influence on debt. The present study shows that the investment of Portuguese firms in Angola has an increasingly higher importance in depreciations of assets, as a consequence of the investments made.</p>
</sec>
<sec id="s0017">
<title>Conclusion</title>
<p>In this study, the factors that influence the choice of the capital structure of 26 Portuguese firms with investments in Angola were examined. With the exception of these firms&#x2019; profitability, we found similarities in the sign and coefficient dimension of capital structure determinants when we compared our results with studies that analysed the capital structure determinants of listed Portuguese firms, firms belonging to the PSI 20 Index and large firms in the Portuguese corporate sector (Ant&#x00E3;o &#x0026; Bonfim <xref ref-type="bibr" rid="CIT0005">2008</xref>; Couto &#x0026; Ferreira <xref ref-type="bibr" rid="CIT0018">2010</xref>; Serrasqueiro &#x0026; Rog&#x00E3;o <xref ref-type="bibr" rid="CIT0058">2009</xref>). These comparisons allowed us to conclude that making direct investments in a foreign market &#x2013; specifically an African market such as Angola &#x2013; during the process of internationalisation of firms&#x2019; investment does not change financing policy, in particular, the sign and coefficient dimension of capital structure determinants. The studies that were used in our comparison of results used samples of large Portuguese, non-financial firms with their investments focused on the Portuguese and European markets (i.e. their main markets). Moreover, the firm size of our sample matches the firm size of other samples of large Portuguese, non-financial firms, with the only difference being their international investments.</p>
<p>Regarding the results, as expected, asset structure is positively related with the leverage ratio, with a coefficient of 0.2079. Likewise, tangibility is also positively related with the leverage ratio. When the sign and coefficient dimension of the relation between tangibility and leverage in our study is compared to the above-mentioned studies, we can conclude that our result of 0.1675 is similar to the other studies&#x2019; results. Serrasqueiro and Rog&#x00E3;o (<xref ref-type="bibr" rid="CIT0058">2009</xref>) got 0.13159; Ant&#x00E3;o and Bonfim (<xref ref-type="bibr" rid="CIT0005">2008</xref>), 0.07; and Couto and Ferreira (<xref ref-type="bibr" rid="CIT0018">2010</xref>), 1.2405 &#x2013; in this case, only regarding the coefficient sign. This result is in tune with more recent studies outside Portugal (Chadha &#x0026; Sharma <xref ref-type="bibr" rid="CIT0015">2015</xref>; Handoo &#x0026; Sharma <xref ref-type="bibr" rid="CIT0025">2014</xref>; Omet et al. <xref ref-type="bibr" rid="CIT0045">2015</xref>).</p>
<p>A firm&#x2019;s age and profitability &#x2013; represented by the return on assets &#x2013; are also positively related with the leverage ratio. In the specific case of the relationship between profitability and leverage, compared with other studies in terms of sign and coefficient dimension, our result of 0.1178 has the same dimension but with an inverse sign in contrast to what was obtained by Serrasqueiro and Rog&#x00E3;o (<xref ref-type="bibr" rid="CIT0058">2009</xref>), -0.17137; and Couto and Ferreira (<xref ref-type="bibr" rid="CIT0018">2010</xref>), -0.1330. This result is also similar to that of more recent studies outside Portugal (Chadha &#x0026; Sharma <xref ref-type="bibr" rid="CIT0015">2015</xref>; Handoo &#x0026; Sharma <xref ref-type="bibr" rid="CIT0025">2014</xref>; Omet et al. <xref ref-type="bibr" rid="CIT0045">2015</xref>).</p>
<p>Lastly, liquidity and NDTS are negatively related with the leverage ratio. The liquidity coefficient is -0.4566, as compared with Ant&#x00E3;o and Bonfim&#x2019;s (<xref ref-type="bibr" rid="CIT0005">2008</xref>) -0.01. The NDTS coefficient is -0.1999, as compared with Ant&#x00E3;o and Bonfim&#x2019;s (<xref ref-type="bibr" rid="CIT0005">2008</xref>) -0.04 and Couto and Ferreira&#x2019;s (<xref ref-type="bibr" rid="CIT0018">2010</xref>) -0.0003.</p>
<p>In general, this leads to the conclusion that the capital structure determinants normally considered by standard finance theory are, in fact &#x2013; in terms of sign and coefficient dimension &#x2013; similar to those used by Portuguese firms investing in the Angolan market. However, the sign of the profitability coefficient is in line with the trade-off framework (i.e. profitability is positively related to debt) and not with pecking order theory (i.e. profitability is negatively related to debt). The explanation offered for this finding is that internationalisation to Angola is seen by Portuguese firms as a diversification strategy involving a market in which the cultural and language differences are quite low. As such, taking into account the high-growth rate of the Angolan market <italic>vis-&#x00E0;-vis</italic> the Portuguese market in the period studied, this investment was seen by creditors as a low-risk, high-potential one. Angola is considered, on the one hand, an extension of the Portuguese domestic market and, on the other hand, a way out of the crisis in the Portuguese economy. This scenario potentially reduces the firms&#x2019; default probability and, as a consequence, the cost of debt. As it maintains the tax shield benefits of debt and decreases the cost of debt (i.e. through a reduction in default probability), this opportunity has induced profitable firms to use more debt.</p>
<p>It is possible to advance that the determinants of the capital structure of firms from less intensely developed countries investing abroad on the African continent do not necessarily differ from other previous studies (Abor <xref ref-type="bibr" rid="CIT0001">2005</xref>; Abor &#x0026; Biekpe <xref ref-type="bibr" rid="CIT0002">2009</xref>; Ant&#x00E3;o &#x0026; Bonfim <xref ref-type="bibr" rid="CIT0005">2008</xref>; Boateng <xref ref-type="bibr" rid="CIT0011">2004</xref>; Couto &#x0026; Ferreira <xref ref-type="bibr" rid="CIT0018">2010</xref>; Serrasqueiro &#x0026; Rog&#x00E3;o <xref ref-type="bibr" rid="CIT0058">2009</xref>), which has important consequences for firms seeking a foothold in Africa. However, generalisations need to be taken cautiously, as the Portuguese firms analysed in this sample covered a period of economic hardship in Portugal, while the Angolan economy was booming.</p>
<p>This research also has important implications as it complements studies especially in less-endowed countries or in Africa. For example, results obtained in the hospitality industry in Turkey (Karadeniz et al. <xref ref-type="bibr" rid="CIT0032">2009</xref>) show that countries with lack of funds supply, because of underdeveloped capital marks, as is the case of African countries, might be good opportunities for firms investing abroad if these are able to lower the risks. Moreover, when analysing the Ghanaian case, one can claim that the African market is an important opportunity for internationalisation as debt is the main financing option of Ghanaian firms (Abor <xref ref-type="bibr" rid="CIT0001">2005</xref>; Abor &#x0026; Biekpe <xref ref-type="bibr" rid="CIT0002">2009</xref>) and joint ventures are natural market entry options to reduce business risk and leverage market potential (Boateng <xref ref-type="bibr" rid="CIT0011">2004</xref>).</p>
<p>It is important also to emphasise that foreign firms investing in Africa need to seriously take into account corporate governance decisions as government policies may not only discriminate between indigenous and foreign shareholders (Boateng <xref ref-type="bibr" rid="CIT0011">2004</xref>; Ezeoha &#x0026; Okafor <xref ref-type="bibr" rid="CIT0022">2010</xref>) but also change the rules of the game that may jeopardise foreign investment and local development alike (Boateng <xref ref-type="bibr" rid="CIT0011">2004</xref>).</p>
<p>This study has some limitations that conditioned the research. The first limitation is the small dimension of the sample, which consisted of 26 firms. Another limitation is the size of the firms studied. As they are all large firms, it was not possible to test whether size influences capital structure. This limitation is linked to the ease of obtaining data from large firms, as opposed to smaller firms. Lastly, not all firms had data for every year considered in this study. Although this lack of data is situational, it led to an unbalanced panel.</p>
<p>Considering the results of this study, it would be interesting to study in the future the same factors in firms of different sizes, such as small- and medium-sized businesses versus large firms. The purpose of this future study would be to discover the strategic differences between both types of firms.</p>
</sec>
</body>
<back>
<ack>
<title>Acknowledgements</title>
<sec id="s20018">
<title>Competing interests</title>
<p>The authors declare that they have no financial or personal relationships that may have inappropriately influenced them in writing this article.</p>
</sec>
<sec id="s20019">
<title>Author&#x2019;s contributions</title>
<p>The article is a joint work of the two authors in all of its phases.</p>
</sec>
</ack>
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</ref-list>
<app-group>
<app id="app001">
<title>Appendix 1</title>
<table-wrap id="T0004">
<label>TABLE 1-A1</label>
<caption><p>Summary statistics.</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th valign="top" align="left">Variable</th>
<th valign="top" align="center">Observations</th>
<th valign="top" align="center">Mean</th>
<th valign="top" align="center">Standard deviation</th>
<th valign="top" align="center">Minimum</th>
<th valign="top" align="center">Maximum</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left">Leverage_ratio</td>
<td align="center">104</td>
<td align="center">1.099187</td>
<td align="center">3.391286</td>
<td align="center">0.1881</td>
<td align="center">35.2465</td>
</tr>
<tr>
<td align="left">Asset_structure</td>
<td align="center">104</td>
<td align="center">0.3917452</td>
<td align="center">0.2297208</td>
<td align="center">0.0093</td>
<td align="center">0.8718</td>
</tr>
<tr>
<td align="left">Age</td>
<td align="center">102</td>
<td align="center">47.97059</td>
<td align="center">30.07629</td>
<td align="center">1</td>
<td align="center">110</td>
</tr>
<tr>
<td align="left">Liquidity</td>
<td align="center">104</td>
<td align="center">2.22868</td>
<td align="center">6.71436</td>
<td align="center">0.0019</td>
<td align="center">50.2408</td>
</tr>
<tr>
<td align="left">Intangible_activity_level</td>
<td align="center">100</td>
<td align="center">6.73E+08</td>
<td align="center">2.06E+09</td>
<td align="center">0</td>
<td align="center">1.02E+10</td>
</tr>
<tr>
<td align="left">Return_on_sales</td>
<td align="center">88</td>
<td align="center">4.648626</td>
<td align="center">22.63219</td>
<td align="center">-4.9775</td>
<td align="center">179.7684</td>
</tr>
<tr>
<td align="left">Return_on_assets</td>
<td align="center">104</td>
<td align="center">2.504371</td>
<td align="center">2.539035</td>
<td align="center">-0.0243</td>
<td align="center">11.5703</td>
</tr>
<tr>
<td align="left">Tangibility</td>
<td align="center">104</td>
<td align="center">0.1914587</td>
<td align="center">0.113603</td>
<td align="center">0.014</td>
<td align="center">0.4168</td>
</tr>
<tr>
<td align="left">Non-debt_tax_shields</td>
<td align="center">104</td>
<td align="center">0.4322817</td>
<td align="center">3.817053</td>
<td align="center">0</td>
<td align="center">38.9781</td>
</tr>
</tbody>
</table>
</table-wrap>
</app>
</app-group>
<fn-group>
<fn><p><bold>How to cite this article:</bold> Mota, J.H.F. &#x0026; Moreira, A.C., 2017, &#x2018;Determinants of the capital structure of Portuguese firms with investments in Angola&#x2019;, <italic>South African Journal of Economic and Management Sciences</italic> 20(1), a885. <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.4102/sajems.v20i1.885">https://doi.org/10.4102/sajems.v20i1.885</ext-link></p></fn>
<fn id="FN0001"><label>1</label><p>For more discussion see among others Serrasqueiro and Rog&#x00E3;o (<xref ref-type="bibr" rid="CIT0058">2009</xref>), Ant&#x00E3;o and Bonfim (<xref ref-type="bibr" rid="CIT0005">2008</xref>) and Kyereboah-Coleman (<xref ref-type="bibr" rid="CIT0034">2007</xref>).</p></fn>
<fn id="FN0002"><label>2</label><p>For more discussion see, among others, Couto and Ferreira (<xref ref-type="bibr" rid="CIT0018">2010</xref>), Serrasqueiro and Rog&#x00E3;o (<xref ref-type="bibr" rid="CIT0058">2009</xref>), Ant&#x00E3;o and Bonfim (<xref ref-type="bibr" rid="CIT0005">2008</xref>) and Kyereboah-Coleman (<xref ref-type="bibr" rid="CIT0034">2007</xref>).</p></fn>
<fn id="FN0003"><label>3</label><p>Which is the most efficient when the data do not have serial correlation (autocorrelation), comparing its results with those achieved from the classical panel data estimators (Fixed and Random Effects).</p></fn>
<fn id="FN0004"><label>4</label><p>Additionally, it allows: the error term to be correlated over the firms, the use of firstorder autoregressive process for error term over time and the error term to be heteroscedastic (Cameron &#x0026; Triverdi, <xref ref-type="bibr" rid="CIT0014">2009</xref>; Marques &#x0026; Fuinhas <xref ref-type="bibr" rid="CIT0035">2012</xref>).</p></fn>
<fn id="FN0005"><label>5</label><p>In this model, &#x03B2; values represent the coefficients of the independent variables. <italic>i</italic> represents the entity (firm) and <italic>t</italic> represents the temporal unit (year). &#x03BC;<sub>it</sub>represents the error term.</p></fn>
<fn id="FN0006"><label>6</label><p>From observation of the descriptive statistics, it is possible to conclude that the debt of Portuguese firms with direct investment in Angola is on average around 110&#x0025;. Moreover, the liquidity, return on sales, return on assets and NDTS are variables with some degree of volatility, as their standard deviations are above their mean values. The Portuguese firms with direct investment in Angola appear to be moderately volatile in asset structure, intangibility and tangibility, which suggests some degree of stability.</p></fn>
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