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Capital structure and CEO tenure in
microfinance institutions*
Daudi Pascal Ndaki
University of Agder, Norway.
Mzumbe University, Tanzania.
E-mail: daudi.p.ndaki@uia.no. Phone number: +47 38 14 10 00
Leif Atle Beisland (Corresponding author)
School of Business and Law, University of Agder, Servicebox 422, 4604 Kristiansand, Norway.
E-mail: leif.a.beisland@uia.no. Phone number: +47 38 14 10 00
Roy Mersland
University of Agder, Norway.
E-mail: roy.mersland@uia.no. Phone number: +47 38 14 10 00
Main message
There is a positive association between CEO tenure and the debt proportion of microfinance
institutions.
Key points
Microfinance institutions need improved access to debt capital to cover a huge and increasing
world demand for microfinance services.
More experienced CEOs may be more aligned with the microfinance institution’s mission and
they may have a better understanding of the business model of microfinance.
Capital providers may require a proven track record within the institution to supply funding.
*JEL classification: G21, G32, M12
Introduction
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While much research efforts have been put into understanding whether poor people
benefit from accessing financial services, less is known about the management and finance -
and the interaction of the two - of Microfinance institutions (MFIs). This is unfortunate
because the management of MFIs will affect capital availability for the microbanking
industry, and the capital availability potentially has considerable and direct influence on the
industry’s customer impact (Tchuigoua et al., 2017). The little MFI-management research
available finds evidence of a significant chief executive officer (CEO) influence on MFI
performance (Galema et al., 2012; Randøy et al., 2015). This paper aims at making a
contribution in this field as it studies the relationship between CEO tenure and the MFI’s
capital structure.
Although this issue has been studied in other contexts of non-financial firms (e.g.,
John & Litov, 2010) and traditional banks (e.g., Yeh, 2011), it is of particular relevance to
microfinance because increased leverage and tapping into capital markets is considered
necessary to cover a huge and increasing world demand for microfinance services
(Ledgerwood et al., 2013). Therefore, it is possible to argue that in many ways the most
successful MFI CEO is the one that can attract the most debt possible to the organization
under his/her management. This study is further a direct response to the call for research
issued by, e.g., Tchuigoua (2015) requesting more knowledge on how managers influence
MFIs’ capital structure.
The setting for this study is different from previous research settings studying the
managerial influence on a firm’s capital structure. MFIs are organizations that provide small
loans and other financial services to economically poor families to support their
entrepreneurial activities (Bruhn et al., 2012; Earne & Sherk, 2013). Availability of credit
motivates economically poor persons to seek out and identify business opportunities within
their economic system (Milana & Ashta, 2012; Bruhn et al., 2012). In this way, access to
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financial services is recognized as a tool to fight poverty (Armendariz & Morduch, 2010;
Ashta, 2012). MFIs are therefore considered to be ‘social enterprises’ or ‘hybrid
organizations’, i.e. firms with both social and financial objectives (Ashta & Hudon, 2012;
Battilana & Dorado, 2010).
The demand for microcredit is huge and on average MFIs have reported growth rates
of more than 30 percent during most of the years over the last couple of decades, which is
around three times that of Western banks (Mersland & Strøm, 2012). Continued high growth
is likely as several market opportunities for MFIs remain untapped (Randøy et al., 2015).
Furthermore, huge populations still have no access to banking services in their neighborhoods
(De Koker, 2013).
Continued microfinance growth depends not only on customer demand but also on
MFIs’ access to funding. In the 1970s and 1980s, MFIs operated as social organizations. They
provided banking services to the poorest families who traditional commercial banks
considered too risky clients (Earne & Sherk, 2013; Milana & Ashta, 2012). The loans were
financed primarily with donations provided by generous philanthropist and development
agencies (Ghosh & Van Tassel, 2011). Donors were motivated by the possibility of poverty
alleviation through the provision of small loans to low-income families (Fehr & Hishigsuren,
2006). Debt financing was not emphasized as access to donor funding prevailed, and most
MFIs were operating with non-profit status (Jegers & Verschueren, 2006). However, these
forms of organizations soon started to face funding constraints (Fehr & Hishigsuren, 2006).
Access to donations and subsidies did not match the huge demand for microcredits by low-
income families (Gosh & Van Tassel, 2013; Ashta & Hudon, 2012).
To accommodate new sources of capital, many MFIs underwent changes, for example,
by becoming regulated and integrated into the formal financial sector, and to shift their
incorporation from non-profit entities to shareholder-owned banks (Fehr & Hishigsuren,
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2006; Daher & Le Saout, 2013). Such a shift expanded MFIs sources of capital to include
funders from both local and international contexts in the category of individuals, commercial
banks, institutional investors, and private equity funds (Earne & Sherk, 2013; Astha, 2012).
Most of these new funders demand market returns from the MFIs; hence they can be
considered as commercial investors (Earne & Sherk, 2013; Fehr & Hishigsuren, 2006). In
total, commercial debt-investments in the microfinance industry increased by seven billion
from 2007 to 2010 (Sapundzhieva, 2011).
Overall, MFIs need debt to grow their portfolios to fulfill their missions of expanding
their services to more poor clients; “Funding is crucial to improving financial inclusion”
(Tchuigoua et al., 2017, p. 133). The question we seek to answer in this paper is whether the
tenure of the CEO influences the MFI’s intake of debt. This is an unanswered question not
only in the microfinance literature but also in the social enterprise literature in general. While
traditional agency theory predicts that CEOs with longer tenure will avoid debt financing
because it includes stricter control by debt holders and increases bankruptcy risk (Jensen &
Meckling, 1976), several arguments that suggest a positive association between debt financing
and CEO tenure can be presented for MFIs, or in more general terms, social enterprises. For
instance, more experienced CEOs may be more aligned with the MFI’s mission and they may
have a better understanding of the business model of microfinance. Moreover, given the
entrepreneurial characteristics of the microfinance industry, capital providers may require a
proven track record within the bank to supply funding. As discussed in the paper, all these
aspects may lead to higher debt levels among experienced CEOs, contrary to the predictions
drawn based on traditional agency theory.
The empirical findings of this paper support the view that financing choices of MFIs
are influenced by the profile of the managers. Specifically, the results show that the CEO
tenure has a positive and significant effect on the MFI’s debt ratio. In a young industry like
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microfinance, we do not consider this finding surprising though important for policy makers
and boards of MFIs. In more general terms, our results contribute to a growing strand of
literature suggesting that standard management and governance theories on how to control
CEOs may not be valid when applied on hybrid organizations operating with both a financial
logic and a social logic (Battilana & Lee, 2014).
The rest of this paper is organized as follows. Following this introduction, the next
section presents a literature review and hypotheses. We then outline the research design. We
continue with a discussion of descriptive statistics. Thereafter, we present the empirical
results and analyses. The final section discusses the results and concludes the paper.
Literature review and hypotheses
Though Modigliani and Miller (1958) put forward the theory of capital structure and
its irrelevance for the value of the firm, subsequent literature often struggles to confirm the
theory. If the capital structure is not irrelevant, the determinants of capital structure become
an important research question. However, prior studies do not provide conclusive evidence as
to which are the determinants of a firm’s capital structure (Tchuigoua et al., 2017). Barton and
Gordon (1987) posit that managerial choices, in general, can help to explain the level of debt
in the capital structure. Recent theories argue that managers avoid contracting debt to protect
their jobs, to shield away from debt covenants, and ease the raising of equity capital (Douglas,
2002).
Agency theory predicts conflict of objectives between the agent, i.e., the CEO, and the
principals, i.e., owners, debt providers, and donors (Jensen & Meckling, 1976). Likewise,
there can be a conflict between different types of principals. For example, equity holders may
prefer financing more projects with debt as long as the project will result in higher returns
(Myers & Majluf, 1984) while funders with development objectives (e.g., donors) may see
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this as risky (Conning, 1999). Therefore, several types of stakeholders may influence a firm’s
financial behavior.
However, and what is the core of this paper, is that a firm’s financing choices and
capital structure are likely to be significantly influenced by the motivations and profile of a
firm’s CEO (Barton & Gordon, 1987; Hackbarth, 2008). Financing with debt requires
sufficient cash flow to allow for the payments of instalments and interests. In the case of
losses, there is no profit distribution to equity holders while debt holders must be paid. As
such, financing with debt is associated with a higher possibility of bankruptcy of the firm
which obviously is risky to the job of the CEO (Jensen & Meckling, 1976). Agency theory
predicts that CEOs become increasingly entrenched as they gain experience in their positions
and according to this theory, we should expect a negative relationship between the MFI’s debt
ratio and the tenure of its CEO (John & Litov, 2010)
The risk involved in debt financing is the most reasonable explanation for the findings
in many empirical studies that there is a negative relationship between the tenure of the CEO
and the firm’s intake of debt (Berger et al., 1997; Chen et al., 2010). A long tenure exposes
the CEO to various stimuli relevant to decision-making that ensure their survival in the
position (Hambrick & Fukutomi, 1991) and as time passes, the CEOs become wary of any
financial risk that may jeopardize their jobs (Chen et al., 2010; Hambrick & Fukutomi, 1991).
However, another stream of capital structure theories suggests that managers maintain
high debt ratios to discourage takeovers, to justify their ability to generate sufficient income to
cover operating expenses and to repay other debts (Israel, 1992). High debt ratios can also be
related to the pecking order theory; the pecking order theory says that companies prioritize
their sources of funding according to the cost of the funding (Myers, 1984). Internal financing
is, according to the pecking order theory, the preferred source of financing, but when external
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financing is needed, debt is preferred to equity. Due to its high cost, (externally raised) equity
is a financing means of last resort.
It is likely that CEOs of MFIs follow a pecking order because retained profits,
subsidies and donations do not match the huge demand of microcredits by low-income
families (Gosh & Van Tassel, 2013; Tchuigoua, 2015). Experienced CEOs may to an even
larger extent follow a pecking order because longevity of tenure in the position increases
CEOs’ discretional power in general (Berger et al., 1997), as well as their influence on firms’
financing (Hambrick & Fukutomi, 1991). Moreover, other characteristics of the microfinance
industry may provide additional arguments for a positive relationship between CEO tenure
and debt financing.
First of all, microfinance is considered a development enhancing industry providing
financial services that may improve poor customers’ quality of life. MFIs are thus hybrid
organizations with both financial and social objectives. Such an industry may be attractive for
managers with broader and more social oriented motivations compared to managers of
commercial firms (Battilana & Dorado, 2010). Besley and Ghatak (2005) theorize on how
mission-oriented organizations, like MFIs, are staffed and managed by ‘motivated agents’
who work for the fulfillment of the organizations’ missions. Randøy et al. (2015) test this
theory on microfinance data and find that in particular founders of MFIs can be considered
motivated agents in the sense put forward by Besley and Ghatak (2005). In line with the
finding in Randøy et al. (2015) it can be argued that the more tenured a CEO is, the more
aligned he/she will be with the MFI’s mission of reaching out to as many customers as
possible (Conning, 1999).
Considering increased discretional power following longer tenure it can well be
argued that MFIs managed by CEOs with longer tenure will have higher ratios of debts
compared to MFIs managed by less tenured CEOs. Taken together, we argue that CEOs in
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hybrid organizations become more aligned over time with the missions of the organizations
they manage, and in MFIs such alignment may result in a willingness to take on more debt in
order to reach out to more clients with microloans.
Another argument for a positive relationship between CEO tenure and use of debt
financing is the fact that the microfinance industry is a new industry and MFIs can be
considered entrepreneurial firms (Randøy et al., 2015). In such situations, investors may be
more reluctant to provide funds when the CEO has relatively short tenure. It is well known
that investors when considering investing in entrepreneurial firms evaluate the CEO and the
management team more thoroughly compared to when investors consider well-established
enterprises where previous years’ results and traditional financial indicators play a significant
role in investment decisions (Ghosh & Van Tassel, 2011). Investors need time to get to know
the CEO, which may lead to less debt leverage in MFIs managed by CEOs with shorter tenure
in their positions.
A third argument for increased debt levels in MFIs with more experienced CEOs is the
fact that the microfinance business model is complicated and it takes time for a new hired
CEO, especially if he/she has no previous microfinance experience, to learn it. Client
screening and monitoring is different from traditional banking since it depends mainly on the
judgments of the credit officer and little on formal documentation (Armendariz & Morduch,
2010). In such a situation an inexperienced CEO will probably be reluctant to increase the
intake of debt until understanding better the MFI’s business model. Moreover, liability
management is still not core in most MFIs (Labie & Mersland, 2011). Most of the managers’
attention is still devoted to asset management, i.e. loan portfolio management and the risk
within. It is, therefore, reasonable to believe that CEOs with less experience in their jobs will
have less time available to seek out more debt opportunities.
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Taken together, traditional governance literature on the relationship between CEO
tenure and debt leverage predicts a negative relationship between the CEO’s tenure and the
MFI’s debt ratio. However, since MFIs are hybrid organizations it can be argued that their
CEOs over time improve their knowledge on the microfinance business model and become
increasingly aligned with the organization’s mission; these factors could lead to a positive
relationship between the MFI’s debt ratio and the CEO’s tenure. Moreover, since MFIs are
entrepreneurial firms, investors might be more willing to provide loans to organizations with
more experienced CEOs. Because traditional agency theory and more specific theories on
microfinance and hybrid organizations to some extent contradict, we present hypotheses for
both a positive and a negative relationship between the CEO’s tenure and the MFI’s debt ratio
(stated as alternative hypotheses to the null hypothesis of no association):
Hypothesis 1a: There is a positive relationship between an MFI’s debt ratio and the tenure of
its CEO.
Hypothesis 1b: There is a negative relationship between an MFI’s debt ratio and the tenure of
its CEO.
Given the ambiguity of the theory, all tests will be two-sided.
Research design
The sample
This study uses secondary data from the five largest rating agencies specialized in the
assessment of MFIs. The five rating agencies include MicroRate, Microfinanza, Planet
Rating, Crisil and M-Cril. There are no differences in the rating agencies’ methods relevant
for the variables included in this study (for more details on the microfinance ratings, see
Beisland and Mersland, 2012). The rating reports are publicly available at the rating agencies’
websites or at www.ratingfund2.org.
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In our sample, a large firm bias is avoided because the very largest MFIs operating as
commercial banks are excluded from the dataset as traditional rating agencies like Standards
and Poor and similar agencies rate these. Moreover, the dataset does not include small savings
and credit cooperatives or development programs offering credit to poor people as part of
their social services. Overall, the MFIs included are typical representatives of professional
providers of microfinance services.
We follow a procedure by Hambrick and Quigley (2014) of excluding CEOs with one
year or less in the firm; the CEO needs some tenure before it is reasonable to expect a CEO
effect. We further exclude observations of MFIs managed by CEOs with more than or equal
to 20 years of experience since in such an MFI, CEO effects normally are difficult to separate
from firm effects (Hambrick & Quigley, 2014). The final sample makes up a panel dataset
containing information for up to six consecutive years from 453 MFIs located in 76 countries
collected from 1996 to 2011.
Measurement and definition of variables
Dependent variable: Capital Structure
Similar to prior studies, we use the ratio of total debts to total assets as our measure of
capital structure (e.g., Berger et al., 1997) and the core dependent variable applied in this
study. Market values are not available for the unlisted MFIs of our sample, hence the values
of total debts and total assets are based on book values that are reported in the rating reports.
Because some MFIs engage in deposit taking, the amount of total debt includes the deposit
amount accepted as voluntary savings.
Test variable: The CEO’s tenure
The CEO’s tenure is a personal trait defined as the longevity in a position (Chen et al.,
2010; Hambrick & Fukutomi, 1991). The focus is on the CEO because of his/her highest
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position among the top management team (Hambrick & Fukutomi, 1991). The numbers of
years of the CEO in position represent the measure of tenure (Berger et al., 1997).
Control variables
The selected control variables account for variations in capital structure that are not to
be attributed to variations in CEO tenure. Because the study pertains to observations that have
been collected from several countries, we include country-level control variables in addition
to firm-level variables. The firm control variables include variables at the CEO level as well
as at the MFI level.
CEO control variables include CEO founder status, CEO duality status, and CEO
gender status. When the CEO is also the founder of the firm, he or she is often the
psychological owner of the firm. This psychological ownership creates a structural power that
induces personal feelings of responsibility and strong attachment to the firm’s decision-
making (Van Dyne & Pierce, 2004). In this context, a founder CEO may to a larger extent
than a hired CEO influence financing choices (Galema et al., 2012). Finkelstein (1992) argues
that holding the two title positions of CEO and chair of the board by the same person defines
the CEO’s structural power in an organization and we expect that CEO-duality is a
characteristic that potentially can influence MFIs’ financing as well. Additionally, the gender
of the CEO might influence the level of external financing of a firm; in the microfinance
literature studies have looked into whether having a female CEO influences the MFI
performance and they find a positive association in this relationship (e.g., Strøm, et al., 2014).
When it comes to MFI control variables, we first include ‘tangible assets’ measured as
the ratio of net fixed assets to total assets (Tchuigoua, 2015). Debt capacity may be influenced
by the amount of fixed assets available to serve as a guarantee for debt (Barclay et al., 2006).
Likewise, we control for the MFI’s loan focus measured as the gross loan portfolio to total
assets ratio (Tchuigoua, 2015). We further include MFI profitability measured as return on
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assets (ROA) (Mersland & Strøm, 2009). To control for the MFI’s risk, we include portfolio
at risk for 30 days (PaR30) (Daher & Le Saout, 2013). It can be expected that MFIs with a
larger share of their portfolios at risk are unattractive to external funders and thus will have
less leverage in their capital structure, see evidence from the banking literature (Gropp &
Heider, 2010). Empirical evidence in MFIs indicates a significant positive relationship
between size (total assets) and external financing (Tchuigoua, 2015). Size is controlled for in
this study as well, and similarly to other studies we use total assets to proxy for size.
In the microfinance industry, several types of ownership coexist (Mersland, 2009) – a
characteristic that needs to be controlled for in the empirical investigation. While MFIs
owned by shareholders are allowed to distribute profits to their shareholders, MFIs organized
as Non-Governmental Organizations (NGOs) or member-based cooperatives do not have
shareholders and typically do not distribute profits (Mersland, 2009). Moreover, shareholder-
owned MFIs may more easily access additional equity compared to NGOs that need to turn to
donors or cooperatives dependent on members that are also their customers. Therefore,
ownership type may have an effect on the MFI capital structure.
The age of an MFI indicates its accumulated business experience. Older MFIs are
probably likely to have better access to capital compared to younger ones. This study uses the
number of years since microfinance startup as a control for the MFI’s experience. We further
include a dummy variable indicating whether the MFI is allowed to mobilize savings from
local depositors. Such a possibility gives the MFI an additional source of debt to finance its
credit operations and should, therefore, be controlled for. Moreover, board size is included as
a control variable because larger boards have larger networks and may influence an MFI’s
access to external finance (Stearns & Mizruchi, 1993).
To control for country effects we first include a self-constructed proxy for the
microfinance market competition in the country in which the MFI is situated. Similar to
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Mersland et al. (2011) we also include the Heritage Index of Economic Freedom which is a
composite measure of a country’s Rule of Law, Government’s economic involvement,
Regulatory efficiency and level of Market Openness; all important elements considered by
investors before making an investment. Table 1 shows definitions and measurements of all
variables used in the study. Because of right skewness, we apply a logarithmic transformation
to the tangible assets, loan focus and the total assets variables.
Table 1
Methods
Empirical studies on CEO characteristics and their effects on capital structure face a
familiar challenge of omitted variable bias and endogeneity. The omitted variable bias can
manifest on the CEO level. For instance, other CEO characteristics (e.g., CEO founder status,
CEO duality, CEO gender) that correlate with the CEO tenure may influence our results, thus,
as mentioned, we control for these variables. Endogeneity may be a problem due to the
presence of firms’ unobserved heterogeneity. Such heterogeneity may simultaneously explain
the firm’s characteristics - the CEO tenure as well as the firm’s capital structure decision. To
account for such problems, we estimate the following general dynamic panel model (Baltagi,
2008);
𝑦𝑖𝑡 =𝛾𝑦𝑖,𝑡−1 + 𝛽′𝑥𝑖𝑡 + 𝜀𝑖𝑡
𝜀𝑖𝑡 = 𝜂𝑖+ 𝜐𝑖𝑡
Where 𝑦𝑖𝑡 is the dependent variable, 𝑦𝑖,𝑡−1 is the lagged dependent variable, γ is the
coefficient on the lagged dependent variable, β is the column vector of coefficients, 𝑥𝑖𝑡 is the
k × 1 vector of independent variables, the error term has two components; 𝜂𝑖 is the time
constant fixed effects (unobserved), and 𝜐𝑖𝑡 is the idiosyncratic error.
The dynamic panel data regression is estimated using the generalized method of
moments (GMM). To implement the GMM, we follow a procedure outlined by Roodman
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(2009). In our panel data, the debt ratio represents the dependent variable measured repeatedly
within an MFI on an annual basis. Hence, we cluster the models at the MFI level. Likewise,
GMM assumes no autocorrelation in the residuals, hence, we include time dummies (years) in
the models (Roodman, 2009).
Descriptive statistics
In Table 2 we report descriptive statistics for dependent and independent variables. On
average 39 percent of the total assets are financed with debts. The average CEO tenure in our
sample is slightly less than seven years. 34 percent of the CEOs are founders, 26 percent are
female and 14 percent are also the chair of the board. The average MFI has seven board
members.
Table 2
Moreover, in Table 2 the average return on assets is 2 percent, and portfolio at risk
(PaR30) is 5 percent. Of the MFI’s total assets, 5 percent are comprised of tangible (fixed)
assets. The loan focus ratio of 0.78 indicates that gross loans are equal to 78 percent of the
total assets. 30 percent of MFIs accept deposits indicating the importance of controlling for
this variable in our models. 38 percent of the MFIs are organized as shareholder firms and
these include banks or non-bank financial institutions. The remaining are either member based
cooperatives or Non-Governmental Organizations (NGOs). The average of total assets is
US$1.27 million. The average MFI is 12 years old while the oldest started with small
agricultural loans already 51 years ago illustrating that the business of microfinance is not a
new phenomenon. The mean level of market competition, as assessed based on information in
the rating reports, is 4.58 on a 7-point scale.
Results and analysis
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In Table 3, we present our results from the dynamic panel-data estimation on the CEO
tenure and its effect on the MFI’s debt ratio. Results are referred to as significant when the p-
value of the regression coefficients is below 0.1. We include explanatory variables
successively to test the stability of our results. In Model 1, we run the regression with the
CEO tenure only, and the result indicates that CEO tenure has a positive and significant effect
on the debt ratio. We add board size and other MFI-specific control variables in Model 2, and
the results hold as in Model 1, that is, the CEO tenure has a positive and significant effect on
the debt ratio. In Model 3, we add the CEO control variables (CEO=female,
CEO=chairperson, and CEO=founder), and the results are similar to those reported in Model
1 and Model 2.
Table 3
In Model 4, we add the country control variables (competition and heritage), and we
observe that the coefficient of the CEO tenure remains positive and has a significant effect on
the debt ratio. Taken together, the 4 regression specifications suggest consistent and robust
results. We note that risk (PaR30) is significantly negatively related to the debt ratio, which is
a result we find expected and reasonable. The significantly negative relation between ROA
and the debt ratio suggests that more profitable MFIs have less debt – a result somewhat
inconsistent with a study of Tchuigoua (2015), which suggests that more profitable MFIs are
better able to mobilize local deposits compared to less profitable MFIs. Interestingly, few of
the control variables turn out to have a significant relationship with the MFI’s debt level; CEO
tenure is one of very few explanatory variables that consistently show up as significantly
related to the debt ratio in our analysis. This further indicates that the tenure of the CEO is
really an important factor when it comes to the MFI’s ability to take on debt.
As noted in the previous discussion, in some MFIs, voluntary savings form an
important part of the debt. To check the robustness of our results and since most MFIs do not
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accept deposits, we re-run all regressions excluding voluntary saving in the debt ratio (not
reported). The results mirror those presented in Table 3. The main difference is that the
alternative analysis shows an insignificant relationship between the ROA and the debt ratio.
A particularly interesting finding in the robustness test is a significant relationship
between the dummy ‘voluntary saving’ and the MFIs’ debt level. Voluntary savings are
excluded in this analysis, so the result suggests that MFIs mobilizing voluntary savings are
also those best able to attract funding from debt investors. Our explanation of this finding is
that MFIs engaged in mobilizing deposits are the most sophisticated and advanced MFIs,
hence the MFIs with the best capability to liaison with more professional debt markets. The
finding may also be related to what Beisland et al. (2015) refer to as the monitoring effect of
savings: the depositors want to keep the MFI viable and therefore monitor the actions of the
entity. Such depositor monitoring may be a type of governance mechanism considered
favorable by professional debt providers.
Discussions and Conclusion
MFIs face huge demand for their services, in particular loans. To service the high
demand for microloans we contend that MFIs need to shift their funding focus from donors to
the capital markets (Gosh & Van Tassel, 2013; Tchuigoua et al., 2017). It is therefore relevant
to search for factors influencing the MFIs’ ability to attract debt. In this study, we argue that
the debt ratio in MFIs is likely to be affected by the profile and motivation of the CEO
(Barton & Gordon, 1987). The traditional literature on the relationship between CEO tenure
and a firm’s debt level generally predicts that CEOs are being entrenched with time and could
shy away from debt. In this paper we also present a rival hypothesis. We argue that MFIs can
be considered complex development agencies and that their CEOs with time will increasingly
be aligned with the mission to serve as many clients as possible (Besley & Ghatak, 2005).
17
Moreover, since MFIs are entrepreneurial organizations (Randøy et al., 2015), providers of
debt are probably more willing to lend to MFIs with more experienced CEOs.
The result supports the hypothesis that with an increasing tenure, CEOs in MFIs take
on more debt. With increased debt levels the MFIs are able to grow and expand their
microfinance services. We argue that this finding has important practical implications. Most
MFIs are still young and liability management is still not core in their modus operandi (Labie
& Mersland, 2011). Faced with high demand for their services MFIs will need to increasingly
leverage their equity with debt. This study indicates that increasing leverage levels requires
experienced CEOs. Even though MFIs, like those studied in this paper, are normally rated by
third party agencies, they still fit the characteristic of entrepreneurial organizations and our
results are consistent with the notion that investors depend on a personal trust relationship
before deciding to lend to an MFI. Such relationships take time to build resulting in increased
leverage for the more experienced CEO.
Also our study could have theoretical implications. The results indicate that the
entrenchment theory, i.e., as CEOs gain experience they become increasingly able to obtain
personal benefits - for instance in the form of job security - does not necessarily seem to apply
for hybrid organizations like MFIs. Rather the opposite seems to be true. When the CEOs
stays with the organization over time he/she might become aligned with and able to better
fulfill its mission. Experienced CEOs seem to search out more opportunities for the MFI,
increase its leverage and thereby make further expansion of services possible. Hence, standard
management and governance theories on how to control CEOs may not be valid when applied
on hybrid organizations.
Of note, our results do not discriminate between different explanations for the
findings. Therefore, we cannot say whether the increased debt ratios associated with more
experienced CEOs should be attributed to more competent, motivated and mission aligned
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CEOs, or to lenders being more willing to provide loans to MFIs managed by more
experienced CEOs. There is thus a need for more research on hybrid organizations and
whether their CEOs become entrenched or aligned with the missions of their organizations as
they gain more experience in their positions. In general there is a need for more research on
hybrid organizations and their management and governance systems.
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Acknowledgements
We would like to thank Øystein Strøm, Lars Oxelheim, Ronny Manos, Javier Estrada, Carlo
Milana (the editor), and seminar participants at the 5th European Research Conference on
Microfinance, 2017, Portsmouth, United Kingdom, for valuable comments and advice.
20
References
Armendariz, B., & Morduch, J. (2010). The economics of microfinance (2 ed.). Cambridge,
Mass: MIT Press.
Ashta, A. (2012). Co-Creation for Impact Investment in Microfinance. Strategic Change, 21,
71-81.
Ashta, A., & Hudon, M. (2012). The Compartamos Microfinance IPO:Mission Conflicts in
Hybrid Institutions with Diverse Shareholding. Strategic Change, 21, 331-341.
Baltagi, B. H. (2008). Econometric analysis of panel data (4 ed.). Chichester: Wiley.
Barclay, M., Smith, C. W., & Morellec, E. (2006). On the Debt Capacity of Growth Options.
Journal of Business, 79, 37-59.
Barton, S. L., & Gordon, P. I. (1987). Corporate strategy: useful perspective for the study of
capital structure? Academy of Management Review, 12, 67-75.
Battilana, J., & Dorado, S. (2010). Building Sustainable Hybrid Organizations: The Case of
Commercial Microfinance Organizations. Academy of Management Journal, 53, 1419-
1440.
Battilana, J., & Lee, M. (2014). Advancing Research on Hybrid Organizing– Insights from the
Study of Social Enterprises. The Academy of Management Annals, 8, 397-441.
Beisland, L. A., & Mersland, R. (2012). An Analysis of the Drivers of Microfinance Rating
Assessments. Nonprofit and Voluntary Sector Quarterly, 41, 213-231.
Beisland, L. A., Mersland, R., & Strøm, R. Ø. (2015). Audit Quality and Corporate
Governance: Evidence from the Microfinance Industry. International Journal of
Auditing, 19, 218-237.
Berger, P. G., Ofek, E., & Yermack, D. L. (1997). Managerial Entrenchment and Capital
Structure Decisions. Journal of Finance, 52, 1411-1438.
Besley, T., & Ghatak, M. (2005). Competition and incentives with motivated agents.
American Economic Review, 95, 616-636.
Bruhn, M., Carpena, F., & Zia, B. (2012). The Oxford handbook of entrepreneurial finance. In
D. J. Cumming (Ed.), Microfinance for entrepreneurs, New York: Oxford University
Press (pp. 825-858).
Chen, H. L., Hsu, W. T., & Huang, Y. S. (2010). Top management team characteristics, R&D
investment and capital structure in the IT industry. Small Business Economics, 35,
319-333.
Conning, J. (1999). Outreach, sustainability and leverage in monitored and peer-monitored
lending. Journal of Development Economics, 60, 51-77.
21
Daher, L., & Le Saout, E. (2013). Microfinance and Financial Performance. Strategic
Change, 22, 31-45.
De Koker, L. (2013). Financial Inclusion and Financial Integrity: Aligned Incentives? World
Development, 44, 267.
Douglas, A. V. S. (2002). Capital structure and the control of managerial incentives. Journal
of Corporate Finance, 8, 287-311.
Earne, J., & Sherk, L. (2013). Funding. In J. Ledgerwood, J. Earne, & C. Nelson (Eds.), The
New Microfinance Handbook: A financial market system perspective, Washington, D.
C.: World Bank Publications (pp. 379-412).
Fehr, D., & Hishigsuren, G. (2006). Raising capital for microfinance: Sources of funding and
opportunities for equity financing. Journal of Developmental Entrepreneurship, 11,
133-143.
Finkelstein, S. (1992). Power in top management teams: dimensions, measurement, and
validation. Academy of Management Journal, 35, 505-538.
Galema, R., Lensink, R., & Mersland, R. (2012). Do Powerful CEOs Determine Microfinance
Performance? Journal of Management Studies, 49, 718-742.
Ghosh, S., & Van Tassel, E. (2011). Microfinance and competition for external funding.
Economics Letters, 112, 168-170.
Gosh, S., & Van Tassel, E. (2013). Funding microfinance under asymmetric information.
Journal of Development Economics, 101, 8-15.
Gropp, R., & Heider, F. (2010). The Determinants of Bank Capital Structure. Review of
Finance, 14, 587-622.
Hackbarth, D. (2008). Managerial Traits and Capital Structure Decisions. Journal of
Financial and Quantitative Analysis, 43, 843-881.
Hambrick, D. C., & Fukutomi, G. D. S. (1991). The seasons of a CEO's tenure. Academy of
Management Review, 16, 719-742.
Hambrick, D. C., & Quigley, T. J. (2014). Toward more accurate contextualization of the
CEO effect on firm performance. Strategic Management Journal, 35, 473-491.
Israel, R. (1992). Capital and ownership structures, and the market for corporate control.
Review of Financial Studies, 5, 181-198.
Jegers, M., & Verschueren, I. (2006). On The Capital Structure Of Non‐Profit Organisations:
An Empirical Study For Californian Organisations. Financial Accountability &
Management, 22, 309-329.
22
Jensen, M. C., & Meckling, W. H. (1976). Theory of the firm: Managerial behavior, agency
costs and ownership structure. Journal of Financial Economics, 3, 305-360.
John, K., & Litov, L. (2010). Managerial Entrenchment and Capital Structure: New Evidence.
Journal of Empirical Legal Studies, 7, 693-742.
Labie, M., & Mersland, R. (2011). Corporate Governance Challenges in Microfinance. In B.
Armendariz & M. Labie (Eds.), The Handbook of Microfinance, Singapore: World
Scientific Publishing Co. pte. Ltd. (pp. 283-298).
Ledgerwood, J., Earne, J., & Nelson, C. (Eds.). (2013). The New Microfinance Handbook: A
financial market system perspective. Washington, D. C.: The World Bank.
Mersland, R. (2009). The cost of ownership in microfinance organizations. World
Development, 37, 469-478.
Mersland, R., Randøy, T., & Strøm, R. Ø. (2011). The impact of international influence on
microbanks' performance: A global survey. International Business Review, 20, 163-
176.
Mersland, R., & Strøm, R. Ø. (2009). Performance and governance in microfinance
institutions. Journal of Banking & Finance, 33, 662-669.
Mersland, R., & Strøm, R. Ø. (2012). The past and future of microfinance innovations. In D.
Cumming (Ed.), The Oxford Handbook of Entrepreneurial Finance, New York:
Oxford Unviersity Press, Inc. (pp. 859-891).
Milana, C., & Ashta, A. (2012). Developing Microfinance: A Survey of the Literature.
Strategic Change, 21, 299-330.
Modigliani, F., & Miller, M. H. (1958). The cost of capital, corporation finance and the theory
of investment. American Economic Review, 48, 261-297.
Myers, S. C. (1984). The capital structure puzzle. Journal of Finance, 39, 575-592.
Myers, S. C., & Majluf, N. S. (1984). Corporate financing and investment decisions when
firms have information that investors do not have. Journal of Financial Economics,
13, 187-221.
Randøy, T., Strøm, R. Ø., & Mersland, R. (2015). The Impact of Entrepreneur-CEOs in
Microfinance Institutions: A Global Survey. Entrepreneurship Theory and Practice,
39, 927-953.
Roodman, D. M. (2009). How to do xtabond2: An introduction to difference and system
GMM in Stata. The STATA, 9, 86-136.
Sapundzhieva, R. (2011). Funding microfinance-a focus on debt financing. Microfinance
Bulletin, 1-8.
23
Stearns, L. B., & Mizruchi, M. S. (1993). Board composition and corporate financing: The
impact of financial institution representation on borrowing. Academy of Management
Journal, 36, 603-618.
Strøm, R. Ø., D’Espallier, B., & Mersland, R. (2014). Female leadership, performance, and
governance in microfinance institutions. Journal of Banking & Finance, 42, 60-75.
Tchuigoua, H. T. (2015). Capital Structure of Microfinance Institutions. Journal of Financial
Services Research, 47, 313-340.
Tchuigoua, H. T., Durrieu, F., & Kouao, G. S. (2017). Funding Strategy and Performance of
Microfinance Institutions: An Exploratory Study. Strategic Change, 26, 133-143.
Van Dyne, L., & Pierce, J. L. (2004). Psychological ownership and feelings of possession:
Three field studies predicting employee attitudes and organizational citizenship
behavior. Journal of Organizational Behavior, 25, 439-459.
Yeh, T. L. (2011). Capital structure and cost efficiency in the Taiwanese banking industry.
Service Industries Journal, 31, 237-249.
24
Table 1: Definition and measurement of variables used in the study
Variable
Definition/measurement
Dependent variable
Debt ratio
Total debt (book value of debt + Voluntary savings) Total assets (book value)
⁄
Independent test variable
CEO tenure
Number of years in the CEO position
CEO control variables
CEO founder
Dummy variable, one if the CEO has founder status, and zero otherwise
CEO chair
Dummy variable, one if the CEO is also chair of the board, and zero otherwise
CEO female
Dummy variable, one if the CEO is female and zero otherwise
MFI specific control variables
Return on assets
Net income before donations/Average assets
PaR30
Outstanding loan past due for>30 days/Gross outstanding portfolio
Tangible assets
Natural logarithm of (Net fixed assets/Total assets)
Loan focus
Natural logarithm of (Gross loans/Total assets)
Voluntary savings
Dummy variable, 1 if an MFI accepts voluntary deposits, and zero otherwise
Total assets
Natural logarithm of (Total assets)
MFI age
Difference between the observation year and the year of establishment of
microfinance activities
Shareholding firm
Dummy variable, one if the MFI is a shareholding firm, and zero otherwise
Board size
Number of board members
Country control variables
Markets competition
7 point scale where 1 indicates low level and 7 indicates high level of competition in
the market where the MFI operates. The variable is constructed based on information
in the rating reports.
Heritage
An index that measures the country’s degree of economic freedom.
25
Table 2: Descriptive statistics
Variable
Obs.
Mean
Std. Dev.
Min
Max
Debt ratio
978
0.39
0.18
0.00
0.64
CEO tenure
805
6.69
4.12
2.00
19.00
Board size
1012
6.75
3.08
1.00
21.00
Return on assets
1041
0.02
0.12
-0.99
0.56
Portfolio at risk for >30 days
959
0.05
0.08
0.00
0.82
Tangible assets
1071
0.05
0.04
0.00
0.38
ln(Tangible assets)
1071
0.04
0.03
0.00
0.29
Loan focus
1075
0.78
0.11
0.07
0.97
ln(loan focus)
1075
0.57
0.07
0.04
0.68
Voluntary saving
1078
0.30
0.46
0.00
1.00
Shareholders firm
1072
0.38
0.48
0.00
1.00
Total assets
1075
1.27
2.57
0.04
20.79
ln(Total assets)
1075
15.32
1.47
10.49
19.45
MFI age
1067
12.40
8.40
1.00
51.00
CEO=female
1078
0.26
0.44
0.00
1.00
CEO=chairperson
1066
0.14
0.35
0.00
1.00
CEO=founder
1080
0.34
0.48
0.00
1.00
Competition
1047
4.58
1.49
1.00
7.00
Heritage
862
56.41
6.80
0.532
0.78
Note: In Table 2, total assets are in US dollar millions.
26
Table 3: Dynamic panel-data estimation, one-step system GMM: CEO tenure and its
effect on the Debt ratio
Dependent variable
Debt ratio=[Total debt+voluntary savings/Total assets]
Independent variables:
Model 1
Model 2
Model 3
Model 4
CEO=tenure
0.006**
(2.051)
0.010**
(2.378)
0.015**
(2.172)
0.013**
(2.032)
Board size
0.004
(1.598)
0.005
(1.627)
0.001
(0.222)
Return on assets
-0.151
(-
1.614)
-0.147
(-
1.567)
-0.167*
(-
1.795)
Portfolio at risk for >30
days
-0.212
(-
1.398)
-0.303**
(-
2.042)
-0.351**
(-
2.333)
ln(tangible assets)
0.017
(0.996)
0.016
(0.909)
0.022
(1.377)
ln(loan focus)
0.035
(0.509)
0.037
(0.546)
0.034
(0.488)
Voluntary saving
0.138**
(2.366)
0.136**
(2.463)
0.128**
(2.241)
Shareholders firm
0.086
(1.052)
0.094
(1.026)
0.082
(0.973)
ln(total assets)
0.027
(0.554)
0.041
(0.713)
0.010
(0.219)
MFI age
0.002
(0.372)
0.001
(0.088)
0.001
(0.157)
CEO=Female
-0.003
(-
0.114)
0.006
(0.225)
CEO=Chairperson
-0.150
(-
1.278)
-0.186
(-
1.215)
CEO=Founder
-0.089
(-
1.537)
-0.067
(-
1.269)
Competition
-0.012**
(-
2.034)
Heritage
-0.045
(-
0.528)
(Debt ratio)i,t-1
0.588***
(7.189)
0.637***
(7.015)
0.621***
(6.429)
0.595***
(6.546)
Constant
0.128
(1.630)
0.496
(0.798)
0.762
(1.022)
0.348
(0.602)
Time dummies
Yes
Yes
Yes
Yes
Observations
695
693
687
687
Number of MFIs
221
220
217
217
F-statistic p-value
0.000
0.000
0.000
0.000
Hansen p-value
0.239
0.155
0.137
0.123
Sargan p-value
0.163
0.160
0.144
0.157
Arellano-Bond test for
AR(1)
0.000
0.001
0.001
0.001
Arellano-Bond test for
AR(2)
0.320
0.519
0.511
0.645
Note: In Table 3, we report coefficients, and robust t-statistics in parentheses. ***, **, and * denote 0.01, 0.05,
and 0.1 significance levels.
27
Author biography
Daudi Pascal Ndaki is a lecturer of international finance at the School of Business at Mzumbe
University in Tanzania, and a member of the Center for Research on Social Enterprises and
Microfinance (CERSEM) at the University of Agder in Norway. His research interests include the role
of chief executive officers in the microfinance industry.
Leif Atle Beisland is Professor of Financial Analysis at the School of Business and Law at the University
of Agder in Norway. His research covers both general accounting research and more specific research
on governance and financial reporting in the microfinance industry. He is also involved in several
research projects on the use of microfinance services among persons with disabilities.
Roy Mersland is Professor of International Business and Development at the School of Business and
Law at the University of Agder. He has international management, consulting and research
experience, especially in the fields of corporate governance, banking and microfinance, from more
than 20 countries in Latin America, Asia, Africa, and Europe. His current research covers a broad
spectrum of areas in microfinance, with a particular focus on the management, governance and
performance of microfinance institutions.
