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Publication Date: October 25, 2022
DOI:10.14738/abr.1010.13307. Avogan, K. (2022). Analysis of the Influence of Governance Quality on the Performance of Savings and Credit Cooperatives in Togo.
Archives of Business Research, 10(10). 125-144.
Services for Science and Education – United Kingdom
Analysis of the Influence of Governance Quality on the
Performance of Savings and Credit Cooperatives in Togo
AVOGAN Komlan
FASEG, University of Lomé, Department of Management Sciences
ABSTRACT
The objective of this paper is to analyze the influence of governance quality on the
performance of savings and credit cooperatives in Togo. To do so, a governance
quality index of fifty-five savings and credit cooperatives was calculated over the
period from 2013 to 2019. The data was collected from the supervision unit of
microfinance institutions and their managers. The results show that governance
quality has a significant and positive effect on the financial performance of
cooperatives. It positively influences the number of active borrowers and the
percentage of female borrowers. However, it has a negative relationship with loan
size. This paper presents the synthetic nature of governance quality in the Togolese
context with a dynamic panel data model. It shows that improved governance has a
positive impact on performance. It constitutes a tool for promoting good
governance practices for the various actors involved in the microfinance sector and
even a basis for developing a good governance charter for this sector.
Keywords: savings and credit cooperative, governance quality, performance, Togo.
INTRODUCTION
Over the past few decades, microfinance has evolved considerably and has become an integral
part of the development policies of many countries around the world. In recognition of the
contribution of microcredit to poverty alleviation, the United Nations General Assembly
declared 2005 the "International Year of Microcredit”. This spotlight is intended to give impetus
to microcredit programs around the world. To date, microfinance and its impact go far beyond
the simple granting of microcredit to poor people excluded from the traditional banking system.
These services include loans, savings mechanisms, insurance, transfers, and even "micro- pensions". The millions of microfinance clients around the world prove that access to financial
services enables poor people to increase their household income, acquire assets and reduce
their vulnerability to crises. Microfinance also helps reduce the extreme vulnerability that
characterizes the daily lives of poor households (Morduch and al., 2003).
Despite the success and popularity of this financial and social inclusion tool, there have also
been failures around the world due to bankruptcies and crises that call into question their
sustainability. Many of these institutions have failed to reconcile their dual objectives.
Mayoukou (2017), notes cases of bankruptcy in several countries including Morocco (2009),
Nicaragua (2009), Bosnia-Herzegovina (2008), the state of Andhra Pradesh in India (2010),
Zambia (2008), Pakistan (2008). The author highlights spectacular bankruptcies in two
countries. In Cameroon, he cites the case of the microfinance savings and credit cooperative
(COOPEMIF) in 2010 and the Coopérative financière de l'estuaire SA (COFINEST) in 2011.
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Similar facts were also noted in 2013 in Congo-Brazzaville regarding Holy Service, Caisse pour
le commerce et le développement (CCD), Congolaise de caution mutuelle (COCAM), Crédit HLM
SA, SIDE SA, Mutuelle de crédit d'aide sociale (MUCASO). West Africa was not spared. Some
networks went bankrupt, such as UCECB in Burkina, the first network in French-speaking Africa
(1969); others were in difficulties, such as FECECAM-Benin, PADME-Benin, and FUCEC-Togo.
As of December 31, 2021, 14 microfinance institutions were under provisional administration,
distributed as follows: Benin (7), Burkina (2), Côte d'Ivoire (1), Niger (2), Senegal (1), and Togo
(1) (BCEAO, 2022). Thirty-four (34) approvals were withdrawn from microfinance institutions
in Togo during the period from 2017 to 2019. Honlonkou (2010) showed that the control
system of these microfinance institutions has design and implementation problems that explain
poor performance results. In another study of the financial sector crisis, Fischer and Desrochers
and Fischer (2002) identify agency problems related to the "manager-member" conflict as the
main cause of financial cooperative failures. In the case of cooperatives, both the diffusion of
membership and the lack of members' skills that can limit control over their activity, managers
generally enjoy a large amount of discretionary space are the causes. Acclassoto and Goudjo
(2012) point out that the activities of microfinance institutions require a mode of governance
that guarantees their sustainability. Unfortunately, these authors note that the modes of
governance put in place lead to the accumulation of counter-performances and are at the origin
of the crises observed. These governance practices explain the crisis in the microfinance sector
today. Governance is one of the primary factors whose quality determines the viability of a
microfinance institution. The quality of governance is denounced everywhere. Thus, these
studies highlight an interdependence between the quality of governance and the performance
of microfinance institutions. In the study by Wele (2009) on the quality of microfinance
institutions in Benin, it was found that the quality of the governance system varies significantly
depending on the institutional form observed. However, he notes a deterioration in the quality
of governance throughout the sector. While direct credit institutions seem to have more
effective governance, mutual or cooperative institutions and NGOs or projects with a
microfinance component still face significant challenges in improving the quality of their
governance. Tlili (2019) undertook a similar study on a sample of 18 MFIs belonging to Arab
countries in the MENA region over the period 2007-2012. The analysis of the governance index
shows that the governance quality of MFIs is closely related to the observed institutional form.
It found a significant and negative effect between the governance index and two aspects of
performance (financial and social).
Our study is an extension of this work, taking into consideration the specificities of savings and
credit cooperatives. Its objective is to analyze the influence of governance quality on the
performance of savings and credit cooperatives in the togolese context through the
construction of a governance index. Thus, we briefly present the literature review and
hypotheses, the methodological approach, and the results.
LITERATURE REVIEW AND HYPOTHESES
Theoretical framework of corporate governance
Corporate governance has become a generic concept used by political scientists, managers,
politicians, international organizations, and many others to describe a mode of management
involving a diversity of actors (Ndengutse and al., 2012). Attempting to define a concept as
broad and multifaceted as governance presents a definite challenge, a bit of folly perhaps
(Lacroix and Pier-Olivier, 2012). It would therefore be simplistic to give a single definition to
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Avogan, K. (2022). Analysis of the Influence of Governance Quality on the Performance of Savings and Credit Cooperatives in Togo. Archives of Business
Research, 10(10). 125-144.
URL: http://dx.doi.org/10.14738/abr.1010.13307
show this broad and multifaceted aspect of corporate governance even if the 1992 Cadbury
Report definition seems according to Madhar (2016) commonly accepted: "Corporate
governance is the system by which companies are directed and controlled. The governance
structure organizes the distribution of rights and responsibilities among the various
participants in the company, such as the Board, management, shareholders, and other
stakeholders. It defines the rules and procedures for making business decisions. In doing so, it
establishes the mechanisms through which the company's objectives are set, as well as the
means to achieve these objectives and control their achievement. For Gomez (1997), corporate
governance "designates the system of rules and measures that orders social actors in the double
sense of the term: it puts the order in their actions and it gives them orders". Corporate
governance, therefore, covers all the principles relating to the management and supervision of
a company. It is about ensuring the balance of power within the company (Benaziz, 2017).
Charreaux (1997) notes that these definitions are too focused on the manager. To go beyond
the shareholder vision, which is very narrowly focused on the contribution of financial
resources alone, to better understand the existing relationships between the governance
system and value creation, he defines corporate governance as "the set of organizational
mechanisms that have the effect of delimiting the powers and influencing the decisions of
managers, in other words, that govern their discretionary space."
These different definitions show that the governance that originated in capitalist firms as a
result of conflicts between the principal and the agent has been extended to all stakeholders.
Trebucq (2003), points out that agency costs are not the only factors that can explain the
impossibility of achieving superior performance. It would certainly be wise to integrate other
elements into the analysis, such as the ability of individuals, their level of knowledge, their
learning effects, and their level of information. Moving in the same direction, Charreaux (2002a)
calls for going beyond the legal-financial vision, by taking into account the managerial and
perceptual dimensions of shareholding, leading to a different explanation of ownership
structures. Also, savings and credit cooperatives (SACCO) differ from other forms of enterprise
and impose particular governance by their principles and values. The main characteristic that
distinguishes the governance of the cooperative society from that of the capital stock company
lies in the separation between ownership and management, and the mutualist principles of the
non-profit type can lead to divergences in the behavior of management concerning the interests
of the owner base (Di Salvo, 2002). This characteristic appeals to stewardship theory, whose
conceptual richness lies in its explanatory power of sustainable value creation through
organizational learning and innovation. Cornforth (2004) states that stewardship theory posits
that managers want to do a good job and will act as effective stewards of an organization's
resources.
Governance mechanisms in credit unions
Not all corporate governance mechanisms identified in the literature are equally important in
the context of microfinance institutions. The heterogeneity within microfinance institutions
means that the governance mechanisms used in bank-like commercial companies differ from
those used in savings and credit cooperatives. In studying the relationship between governance
and performance, many authors focus primarily on the characteristics of the board of directors
(Godard, 1998; Adams and Mehran, 2003; Kpapper and Love, 2004). The board of directors is
characterized by its composition, size, responsibilities of the board chair and CEO, specialized
board committees, and duality. The composition of the board is concerned with skills, age,
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seniority, and the proportions of independent directors or employee directors. The specialized
committees include the audit or accounts committee, the executive compensation, and
appointment committee, and the ethics and/or governance committee.
In the context of microfinance institutions, several variables are selected for the governance
assessment such as internal and external governance mechanisms. The internal governance
mechanisms identified in the literature are the characteristics of the board of directors (size,
composition, independence or not, length of the term of the president and members, separation
of power between the general manager and the president of the board, etc.), the legal status,
the credit methodology, the presence of institutional investors, and the membership of a
network. External governance mechanisms include supervision and/or regulation, rating by
rating agencies, external auditing, and market discipline (Hartarska, 2005; Mersland and Strøm
2009a). In their assessment of microfinance governance in sub-Saharan Africa, Tchakoute- Tchuigoua (2010) and Koudou (2013) chose various variables. They took internal governance
mechanisms such as board composition (size and independence), credit methodology,
ownership variables (legal status and the existence of institutional), and organizational form
(membership or not in a network).
Internal governance mechanisms
For internal governance mechanisms, we have retained the characteristics of the board of
directors imposed by the legislator as an internal control mechanism for the proper conduct of
business. In addition to the board of directors, other variables are taken into account, such as
the characteristics of the manager, and the characteristics of the decentralized financial system
(credit methodology, internal control system, quality of information, membership in a
network).
Board of Directors and DFS Performance
The board of directors is a preferred mechanism for internal control of management. According
to Nam (2004), it is responsible for the effectiveness of governance mechanisms and specifically
internal control systems. Zahra and Pearce (1991) propose the following four attributes of the
board: composition, characteristics, structure, and process. Composition refers to the size of
the board and the type of directors who sit on it. Characteristics refer to the individual profile
of directors (age, education, academic background, values, and work experience) and the type
of board (level of independence, mode of operation, etc.). Structure describes how the board is
organized (number and type of committees, members of these committees, a form of leadership
on the board, etc.). Process describes how decisions are made by the board (frequency of
meetings, level of consensus, etc.). Similarly, the roles and recognition of the attributes of the
board remain quite disparate. The characteristics retained in this study are size, diversity,
gender of the chair, number of meetings, attendance, level of education, age, seniority, and
expertise.
Characteristics of the leader
Lazonik and O'Sullivan (2000) argue that value creation is no longer limited to disciplining
leaders, but involves the managerial capabilities, knowledge, and specific skills of leaders. The
leader is usually recruited based on his or her skills, which are linked to professional
experience, management practices, and training. Monchatre and Rolle (2003) believe that a
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Avogan, K. (2022). Analysis of the Influence of Governance Quality on the Performance of Savings and Credit Cooperatives in Togo. Archives of Business
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URL: http://dx.doi.org/10.14738/abr.1010.13307
leader's skills, acquired in particular through training, can contribute to the positive
transformation of organizations and introduce an increase in economic performance. Singh et
al (2008) state that managers have different characteristics, particularly in terms of education
and experience.
This competency is valued differently according to several approaches including that through
operational skills. Liu and al, (2014) note that women leaders are a good channel of
communication to connect with their clients and working women because of their different life
experiences and perspectives. Agarwal et al. (2009) add to this literature by analyzing life cycle
patterns in financial decisions related to credit behavior, they report that younger people make
more mistakes than older people. Charreaux (1994) considers compensation policy as a
governance mechanism to sanction or incentivize managers to act in the interest of
shareholders or investors. In this regard, Adams and Mehran (2003) note that banks rely little
on stock options as a means of compensating executives. The microfinance sector proceeds
from the banking sector sharing almost the same realities; this implies that the observations of
Adams and Mehran could be similar while taking into account the heterogeneity of the sector.
The characteristics retained are related to gender, seniority, level of education, and
remuneration. To these characteristics are added the manager's evaluation, frequency of
reporting, and presence on the credit committee.
Characteristics of the microfinance institutions
The particularity of MFIs, unlike commercial banks, lies in their lending methodology. They can
grant loans to people individually (individual loans) or people in a group (group loans). Group
lending with joint and several guarantees is a method that allows the MFI to grant credit to
people who do not have any material guarantee. Cuevas and Fischer (2006) consider the credit
methodology (group lending or individual lending) as a governance mechanism to reduce
conflicts arising from the credit relationship. For better management of credit risks, control
systems (internal and external audits and controls) are put in place. According to Honlonkou
(2009), this mechanism determines and locates responsibilities and eventually punishes those
responsible for infractions to dissuade them from repeating them. Also, according to the
provisions of the law regulating microfinance institutions in WAMU, decentralized financial
systems are required to produce a quarterly report to the Supervision Unit, for a total of four
periodic reports. The characteristics retained relate to the methodology of credit and its
preponderance, the presence of the internal control system, the internal credit and risk
management committee, and the quality of the information system.
External governance mechanisms
The choice of variables for the study takes into account the specificity of savings and credit
cooperatives and the law in force in the microfinance sector in WAEMU. The external
governance mechanisms taken into account are as follows: membership in a network,
regulation or supervision (membership in the APSFD and compliance with prudential
standards), external audit, and rating.
Quality of governance and performance
Most research on governance quality and firm performance has shown that governance
positively influences performance (Black, 2001; Bauer et al., 2004; Brown and Caylor, 2006; Da
Silva and Leal, 2008; Tobossi, 2018). In contrast, other studies have found a negative (Guest,
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2009) or neutral (Chang, 2003) relationship. Gompers et al. (2003) analyze the relationship
between the GIM index and Tobin's Q. In the first step, the authors perform a simple correlation
analysis and find no relationship between the GIM index and Tobin's Q. In the second stage,
they measure the impact of this index on the firm's capital expenditures using linear regression
and find a negative relationship between these two variables. Recall that the GIM index
inversely measures the quality of governance. Thus, we can conclude that the results of
Gompers et al. (2003) show a positive relationship between governance quality and
performance. Following these authors, Villalonga and Amit (2006) apply the same index and
the same performance variables to family firms in the Fortunes database in the United States.
Using regression analysis, these authors reach the same conclusions. Brown and Caylor (2006)
use their GOV-Score index that integrates the internal and external dimensions of governance.
Their analysis is based on data collected on 1,868 companies in February 2003 in the ISS
database. Using Pearson and Spearman correlation tests, they find a positive relationship
between this index and Tobin's Q. In particular, they find that poorly governed firms perform
less well and pay their shareholders fewer dividends. This result is confirmed by regression
analysis. Da Silva and Leal (2008) focus exclusively on the Brazilian case. They construct their
governance index: the Corporate Governance Index (CGI). This index is calculated based on 15
binary questions related to the dissemination of financial information, the composition and
functioning of the board, the ownership structure, and the protection of shareholders' rights.
The value of the index is equal to the sum of the points obtained by the company on all the
questions. Companies with an index value of less than 5 have "poor governance", those with an
index value between 5 and 9 have "less good governance" and those with an index value greater
than 9 have "good governance". Through regression, they show that this index has a positive
and significant effect on the economic profitability of the firm. Moungou Mbenda and Niyonsaba
Sebigunda (2015) also used the governance quality index to assess the performance of 300
SMEs in Cameroon over the year 2011. Their analysis shows that the GQI value is relatively low
for most SMEs. However, a positive and significant relationship between the GQI and SME
performance indicators is observed.
The governance indices used in different contexts have tested the link between the quality of
corporate governance and certain financial performance attributes. The results of various
studies presented above show that there is a link between the governance index and financial
performance measures. Indeed, most of these indices are designed to assess shareholder
governance in trove as a signal to investors. These indices incorporate several corporate
governance mechanisms in their calculation and it is difficult to know which ones significantly
influence performance. In the microfinance sector, research aimed at constructing governance
indices is rare. However, we can mention the work of Wélé (2009) who, inspired by the
governance mechanisms in microfinance proposed by Briceno-Garmendia and Foster (2007),
presents a model that makes it possible to calculate an aggregate index of governance quality.
However, the link between this index and the performance of MFIs has not been addressed. de
Tlilli (2019) in his study, found a significant and negative effect between the governance index
and the different aspects of performance. Based on this reasoning, two hypotheses (2) follow:
• the quality of governance influences positively the financial performance of credit
unions
• the quality of governance influences positively the social performance of credit unions.
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Avogan, K. (2022). Analysis of the Influence of Governance Quality on the Performance of Savings and Credit Cooperatives in Togo. Archives of Business
Research, 10(10). 125-144.
URL: http://dx.doi.org/10.14738/abr.1010.13307
METHODOLOGICAL APPROACH OF THE STUDY
Study sample
There were 76 microfinance institutions in Togo at the end of December 2019, of which nearly
70% were in Lomé. They are composed of 70 savings and credit cooperative or mutualist
institutions (including 6 networks taken on a unit basis), 4 associations, and 2 companies. The
data was collected from the Cellule d'Appui et de Suivi des Institutions Mutualistes ou
Coopératives d'Epargne et de Crédit (CAS-IMEC) and from microfinance institutions over the
period from 2013 to 2019. Over the period, only 60 IMECs provided their data and two IMECs
were chosen per network, which gives a total of 66 IMECs in our sample. Following the data
processing, 55 are usable questionnaires. The geographical distribution of the sample was
based on the administrative division of Togo. The number of questionnaires for Lomé commune
is 38, compared to 17 for the interior of the country.
Operationalization of the variables
The operationalization is linked to the retained variables, namely the governance variables, the
performance variables, and the control variables (Appendix 1).
Financial performance variables
The Return On Assets (ROA), operational self-sufficiency (OSS), and portfolio, at risk (PAR) are
the financial performance variables selected. ROA is the financial performance variable often
used in microfinance (Hartarska, 2005; Lafourcade and al., 2006; Mersland and Strom, 2009;
Bassem, 2009). It measures profitability regardless of the underlying funding structure of the
institution and allows for comparisons between commercial and non-commercial MFIs (Bruett,
2005). Lin and Ahlin (2011) and Nawaz (2010) show the extent to which an MFI covers its costs,
through its revenues, by comparing financial revenues to financial and operational expenses,
including the provision for loan impairment. Operational self-sufficiency (OSS), the most
commonly observed performance measure, is used to quantify the institutional performance
and sustainability of MFIs (Bassem, 2009; Hartarska, 2005; Mersland and Strøm, 2009). CGAP
(2009) recommends Portfolio at Risk (PAR) to assess the quality of the portfolio at risk in the
banking sector and microfinance institutions. Portfolio at risk is measured by the ratio of
outstanding loans with at least one 90-day past due date to total gross outstanding loans
including those in default. The regulations in force in the WAEMU zone set the maximum value
of the 90-day PAR at 3%.
Control variables
The age of the institution, the size of the institution, and the area of intervention are the control
variables retained. Age has been used by several actors to assess performance in various
aspects (Bassem, 2008; Kablan, 2009; Kasman et al., 2010; Tchakoute Tchuigoua and Nekhili,
2012; Solhi and Rigar 2014; Ellouz Ziadi et al., 2017; Djofouet, 2019; Kemdong Tenekeu &
Nzongang, 2020). Pugh et al. (1968) emphasize that the seniority of an organization allows it to
better formalize its behavior. According to Diop and Wade (2020), experience in terms of years
of existence can be synonymous with a better knowledge of the threats and opportunities of its
sector of activity, its strengths, and weaknesses.
Size, as measured by total assets, is according to some authors a factor determining the
performance of microfinance institutions (Hartarska, 2005; Bassem, 2009; Mersland and
Strom, 2009; Tchakoute Tchuigoua, 2010; Tchakoute Tchuigoua and Nekhili, 2012; Solhi and
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Rigar 2014; Ellouz Ziadi and al., 2017; Djoufouet, 2019; Douanla and al, 2019; Djontu and
Nzongang 2019; Kemdong Tenekeu and Nzongang, 2020). For the latter, the larger size allows
for economies of scale in contrast to Kablan (2009) who shows that large institutions are rather
the least efficient. The Experian logarithm of total assets is often used in data analysis.
Microfinance has as its area of intervention the rural environment. It is this area that is home
to many poor populations excluded from the traditional banking system. Some studies of the
performance or efficiency of microfinance institutions use the area of operation or location
(Kobou and al., 2010; Mondjeli, 2013; Djontu and Nzongang, 2019 and Kemdong Tenekeu and
Nzongang, 2020).
Specification of the analysis model
The need to take into account the individual effect but also the time effect leads us to estimate
the performance of the 55 financial cooperatives over the period 2013 to 2019. We used a
dynamic panel model to analyze the influence between governance quality and performance. A
linear type relationship was established between these variables to conduct regressions with
the various estimation analyses that are required. Thus, the general linear model for panel data
is as follows (Bourbonnais, 2009):
Performanceit = β0+ β1 IGOUV it + β2 AGEit + β3 SIZEit + β4 ZONEit +εit
with : i = 1, ..., 55 : index allowing to go through the 55 MFIs ; t = 1, ..., 7 : index allowing to go
through the 7 years of observation (2013 to 2019); Performance it : performance of MFI i
observed in year t ; β0 : constant term for MFI i and εit : error term.
ROA!" = β# + + β$IGOUV!" + β%AGE!" + β&SIZE!" + β'ZONE!" + ε!" (1)
OSS!" = β# + + β$IGOUV!" + β%AGE!" + β&SIZE!" + β'ZONE!" + ε!" (2)
PAR!" = β# + + β$IGOUV!" + β%AGE!" + β&SIZE + β'ZONE!" + ε!" (3)
Breadth!" = β# + + β$IGOUV!" + β%AGE!" + β&SIZE!" + β'ZONE!" + ε!" (4)
Depth!" = β# + + β$IGOUV!" + β%AGE!" + β&SIZE!" + β'ZONE!" + ε!" (5)
TP!" = β# + + β$IGOUV!" + β%AGE!" + β&SIZE!" + β'ZONE!" + ε!" (6)
The governance quality index groups together several criteria assessed by binary values. It thus
makes it possible to integrate the diversity of governance dimensions, while synthesizing the
information and assessing the weight and impact (±) of each indicator in the index (Moungou
Mbenda and Niyonsaba Sebigunda, 2015). We adopt the methodology of Wélé (2009) who
speaks of the aggregate or synthetic governance index. Thus, to calculate the governance index,
we transform the starting variables into binary variables (0 or 1) after calculating the median
value. Those that are already binary variables are not modified. When the starting value is
greater than or equal to the calculated median, the variable takes on the value 1. Otherwise, it
takes on the value 0. By adding up the values of these 27 binary variables, we obtain the
governance score for each MFI. The governance index (IGOUV) is obtained by dividing the
governance score by the total number of variables considered (27). The MFI that obtains a
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Research, 10(10). 125-144.
URL: http://dx.doi.org/10.14738/abr.1010.13307
governance index close to 0 has a low governance quality, while the MFI that has a governance
index close to 1 has a good governance quality.
RESULTS
Description of financial performance variables
The table 2 presents the descriptive statistics of the selected variables.
Table 2: Descriptive statistics of variables
Variable Mean Std. Dev. Min Max Observation
Average OC 291422.94 818347.33 10158.784 7797124.3 385
TP .985715 2.614826 .0317029 23.15343 385
Breadth 13507.41 21727.23 53 226943 385
Depth 40.68903 18.22489 5.77 100 385
ROA 21.28842 13.75899 .37 46.41 385
OSS 105.1199 49.82601 1.52 344.96 385
BY 9.314877 16.85842 .1 105.4 385
AGE 18.59221 8.564549 8 40 385
SIZE 1.98e+09 3.17e+09 4431171 2.64e+10 385
Source: Data from our surveys
Over the seven years of observation, savings and credit cooperatives granted a minimum loan
of 10,158 FCFA compared to a maximum of 7,797,124 FCFA. The average loan granted over the
period was 291,422 FCFA. The indicator used to measure social performance in terms of
outstanding loans and which is generally accepted in the literature is the size of the loan or
credit (Tchakoute Tchigoua, 2010). This is an indicator that allows us to assess the pursuit of
the social mission of MFIs when the value of the loan size is less than one (01). The average loan
size is 0.986. Also, it varies from .032 to 23,153. Overall, the savings and credit cooperatives
studied lend to the disadvantaged social stratum. These results are not in line with Tchakoute
Tchigoua (2010) who found an average loan size of 1.085. The results show that 83.12 percent
of the savings and credit cooperatives have a loan size of less than 1. This implies that they
particularly target the poorest, unlike the rest of the sample. When considering the percentage
of female borrowers (depth), the average outreach is 40.68 percent with some disparities. The
average number of active borrowers (breadth) is 13,507. Taking these two dimensions together
to express social outreach (SP = Depth*Breadth), the results show that savings and credit
cooperatives lend to an average of 5,094 women. The Microfinance Information Exchange
(MIX) classifies MFIs into three categories based on the number of borrowers. An MFI is
considered "small" if it has fewer than 10,000 borrowers; "medium" if it has between 10,000
and 30,000 borrowers; and "large" if it has more than 30,000 borrowers. According to this
classification, 13.51% of the savings and credit cooperatives studied are large; 21.3% are
medium, and 65.19% are small. The average profitability is 21% with a variation of. 37% à
46,41 %. These results show that the majority of SACCOs are profitable. The operational self- sufficiency of SACCOs varies from 1.52% to 344.96% with an average of 105%. These results
show an operational insufficiency over the study period. The minimum and maximum values of
the portfolio at risk are respectively 0.1% and 105.5%. The average of the portfolio at risk at 90
days is 9%. This result is three times higher than the norm of less than 3% and shows that there
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is still room for improvement in the quality of the credit portfolio. The savings and credit
cooperatives examined have a certain maturity in the microfinance activity since the average
age is 18.59 years. The most mature has 40 years of experience and the youngest has 8 years of
experience. In addition, there are large disparities in the distribution of this variable. The
results show that all the credit unions in the study are mature institutions. The average size of
the credit unions is 1.976 billion with a standard deviation of 3.168 billion. The smallest size is
4,431,161 and the largest size is 26.36 billion. On the one hand, the need for space for training
sessions before the establishment of the credit or training to strengthen the management
capacities of credit beneficiaries in the exercise of their activities, and on the other hand, the
national coverage of certain SACCOs, explain the importance of the total assets recorded.
National coverage or the creation of branches (or service points) requires significant
investments that increase the fixed assets of these institutions. Thus, we have SACCOs that have
imposing buildings for the exercise of their activities.
Analysis of the governance index
The analysis of the governance index (IGOUV) was done through the presentation of the results
and their assessment of the control variables. The following table shows the descriptive
statistics of the governance index.
Table 3: Descriptive statistics for the governance index
Years Better
governed
Median Mean Min Max Std. Dev.
2013 39 0,481 0,52 0,22 0,78 0,12
2014 29 0,519 0,52 0,22 0,78 0,11
2015 28 0,519 0,52 0,22 0,78 0,11
2016 40 0,481 0,52 0,22 0,78 0,12
2017 40 0,481 0,52 0,22 0,78 0,12
2018 40 0,481 0,52 0,22 0,78 0,11
2019 28 0,519 0,52 0,26 0,78 0,11
IGOUV 244 - .5185185 .2222222 .7777778 .1137797
Source: Data from our surveys
Over the observation period, the number of best-governed credit unions has moved up and
down. The average governance index is 0.5185. The results show that the majority of the credit
unions analyzed have better governance quality. The years 2015, 2019, and 2014 show the
lowest numbers of credit unions (28 out of 55) that are better governed. Better governance
quality does not mean exemplary governance here. Credit unions that qualify as better
governed in a year are those whose governance index is higher than the median governance
index for that year. This change in the average governance index, however, hides some
disparities.
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Research, 10(10). 125-144.
URL: http://dx.doi.org/10.14738/abr.1010.13307
Profile of better-governed SACCOs by age
Table 4: Profile of the best- governed SACCOs by age
AGE
Years Median age Less mature More mature Total better
governed
2013 15 17 18 35
2014 10 16 19 35
2015 10 17 18 35
2016 11 16 19 35
2017 12 16 19 35
2018 14 17 18 35
2019 15 15 19 34
Total 114 130 244
Source: Data from our surveys
For a more in-depth analysis, a classification of the best-governed SACCOs was carried Oi
sabotage the best-governed SACCOs whose age is greater than or equal to the median are
considered the most mature. The results show that the quality of governance is not necessarily
linked to excessive maturity. There are no major differences between the most and least mature
institutions in terms of governance quality. However, the older the SACCO, the better the quality
of governance.
Profile of best governed SACCOs by size
Table 5: Profile of the best-governed SACCOs by size
SIZE
Years Median size Large SACCOs Small SACCOs Total
2013 1965724556 14 25 39
2014 1331929868 15 14 29
2015 996325774 13 15 28
2016 1718895352 23 17 40
2017 1947252135 23 17 40
2018 1289794396 22 18 40
2019 1544992124 17 11 28
Total 127 117 244
Source: Data from our surveys
The best-governed savings and credit cooperatives are divided into 127 larger sizes and 117
smaller sizes, i.e. 52.05% versus 47.95%. Beyond this apparent equality, it is worth noting that
the larger size SACCOs have better governance quality throughout the study period except in
2013 and 2015. These data show that size has an impact on the quality of governance.
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Profile of the best-governed COOPECs according to the area in which they are located
Table 6.1: Profile of the best-governed SACCOs according to the area of activity Area of activity
Years Urban area Rural area Total
2013 26 13 39
2014 18 11 29
2015 17 11 28
2016 26 14 40
2017 26 14 40
2018 26 14 40
2019 17 11 28
Total 156 88 244
Source: Data from our surveys
Table 6.2: Summary of the best-governed SACCOs according to location
Rural area Urban area
Year Better % better Better % better
Total governed NO governed Total governed No governed
2013 17 13 4 76% 38 26 12 68%
2014 17 11 6 65% 38 18 20 47%
2015 17 11 6 65% 38 17 21 45%
2016 17 14 3 82% 38 26 12 68%
2017 17 14 3 82% 38 26 12 68%
2018 17 14 3 82% 38 26 12 68%
2019 17 11 6 65% 38 17 21 45%
Total 119 88 31 74% 266 156 110 59%
Source: Data from our surveys
Over the seven years of observation, 63.93% of the best-governed SACCOs reside in urban
areas. If we relate the best-governed institute number in each zone, it is easy to see that the
institutions in the rural zone have a better quality of governance than those in the urban zone.
These results could be explained by the involvement of the cooperators in the management,
unlike the urban institutions, whose management is often disconnected from the real
cooperators.
Link between the governance index and the governance variables
To estimate the equations, different assumptions have been made about the coefficients and
the error term, which leads to different models that use specific estimation methods. The
assumptions made are tested in order to determine the model that best exploits the information
contained in the data. From the File tests in table 7, the ROA, OSS and PAR models have common
effects. The null hypothesis of the existence of common effects is rejected for the DEPTH,
BREADTH and TP models. They then behave as individual effects which are of two kinds (fixed
effects and random effects). The Hausman test must be performed to determine which model
to use. The Hausman test on the models did not reflect the individual effect at first sight for
confirmation. According to the results of the Hausman test, there are fixed effects in the
BREADTH and TP models. On the other hand, at the level of ROA, DEPTH models, the results
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Avogan, K. (2022). Analysis of the Influence of Governance Quality on the Performance of Savings and Credit Cooperatives in Togo. Archives of Business
Research, 10(10). 125-144.
URL: http://dx.doi.org/10.14738/abr.1010.13307
negate the existence of fixed effects. However, the Breusch Pagan random effects validation test
is performed on all models. Given the results of these tests, it should Given that there are
random effects in all the models. Finally, the tests of autocorrelation of the Durbin-Watson
errors and normality of the Jarque Bera errors were performed. cording to the results of the
normality test of the errors, it should be noted that for all the models studied, the errors follow
a normal distribution except for the ROA model for which the probability of the Chi-square is
higher than the significance level which is 5%. The Durbin-Watson statistics are between zero
and two, which allows Watson’s conclude that there is no problem of autocorrelation of the
errors across the models considered.
Table 7: Summary of estimates
Fisher test Hausman Breusch Jarque-Bera Durbin- Model
(Prob) test Pagan test test
Watson test retained (effects)
ROA 0.2002 0.0517 0.000*** 0.4918 1.3563942 random
OSS 0.5791 0.6763 0.000*** 0.000*** 1.5918723 random
PAR 0.0875* 0.0875* 0.000*** 0.0005*** 1.5919414 random
Breadth 0.000*** 0.000*** 0.000*** 0.000*** .76660159 random and fixed
Depth 0.0172** 0.5847 0.000*** 0.000*** .96465734 random and fixed
TP 0.000*** 0.0130* 0.000*** 0.000*** .77680955 random and fixed
Source: Data from our surveys
These different estimates lead to the regression results presented below.
Table 8: Financial performance regressions
ROA OSS PAR
Coef. p-value Coef. p-value Coef. p-value
IGOUV .467333 0.000*** .6941774 0.520 5.770857 0.031**
AGE -.38688 0.000*** -.4270537 0.760 3.755744 0.313
SIZE -.11698 0.000*** .1346604 0.007** .0569908 0.538
ZONE .16568 0.000*** 0 0 - -
Constant 6.5577 0.000*** 3.442009 0.285 -6.748342 0.526
R-squared 0.2448 0.0287 0.0198
Prob>F 0.0000 0.0472 0.0875
Significance threshold of 1% (*** p<.01) ; 5% (** p<.05) and 10% (* p<.1)
Source: Data from our surveys
Although having a positive coefficient, operational self-sufficiency does not have a significant
relationship with the governance index. The results show that the quality of governance
(IGOUV) significantly and positively explains the financial performance measured by the return
on assets at the respective 1% threshold. These results are similar to those of Moungou Mbenda
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and Niyonsaba Sebigunda (2015). Their analysis shows that governance quality measured by
the governance quality index significantly improves all performance indicators. They show that
the unit improvement in the GQI leads to a more proportional improvement in the turnover of
the Cameroonian firms studied. These results are consistent with previous studies by
Tchakoute Tchuigua (2010) on a sample of 64 microfinance institutions from 4 Sub-Saharan
African diamonds. These studies show that governance positively influences the performance
of microfinance institutions. Other authors (Wamba et al., 2014; Messomo, 2017; Djoufouet,
2018) also attest to the positive relationship between the quality of governance mechanisms
and the performance of the microfinance institutions in the Cameroonian context. In light of the
above, the hypothesis that the financial performance of savings and credit cooperatives is
confirmed.
Table 9: Social performance regressions
BREADTH DEPTH TP
Coef. p-value Coef. p-value Coef. p-value
IGOUV 1.3095 0.012** .5402374 0.038** -1.256347 0.017**
AGE -.4003 0.194 -.2980423 0.043* .5703665 0.059*
TAILLE .34344 0.000*** -.0670178 0.002** .6193661 0.000***
ZONE .13242 0.651 .2656836 0.055* -.1034719 0.717
Constant 3.5358 0.003*** 5.961297 0.000*** -16.25607 0.000***
R-squared 0.1415 0.0268 0.3995
Prob>F0.0000 0.0001 0.0000
Significance threshold de 1% (*** p<.01) ; 5% (** p<.05) and 10% (* p<.1)
Source: Data from our surveys
Governance quality has a significant and positive influence on the number of active borrowers
and the percentage of female borrowers at the 5% threshold. This result shows that improving
governance quality increases the number of active borrowers in general and the number of
female borrowers in particular. This is contrary to Tlili (2019) who finds no effect between
governance and the number of active borrowers in microfinance institutions in 7 MENA
countries between 2007 and 2012. In contrast, governance is significantly and negatively
associated with loan size. Loan size decreases as cooperative managers implement or
strengthen their governance mechanisms. This is explained by a refocusing on the primary
mission of these cooperatives as governance quality improves. This result could also be
explained by the increase in the number of active borrowers and the percentage of female
borrowers. The increase in the number of female borrowers leads to a decrease in the size of
the loans. This result confirms the one found by Tlili (2019). Based on this result, the hypothesis
is that cooperatives are partially verified.
After verification of the hypotheses, we proceed to the verification of the influence of the control
variables on the different aspects of the performance. Age has a significant negative influence
on the return on assets at the 1% level. These results show that as savings and credit
cooperatives age, their economic profitability deteriorates. This could be explained by the
familiarity of the managers of these institutions with their clients and proxy lending. This
relationship also stems from the increase in the size of loans whose default deteriorates the
return on assets. These results are not consistent with those found by Deh et al. (2021), who
find that the oldest banks in the West African Economic and Monetary Union improve their
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Avogan, K. (2022). Analysis of the Influence of Governance Quality on the Performance of Savings and Credit Cooperatives in Togo. Archives of Business
Research, 10(10). 125-144.
URL: http://dx.doi.org/10.14738/abr.1010.13307
performance through the experience they have acquired during their years of existence, their
knowledge of the sector, and the reputation they have acquired. All of this allows them to
increase their market share, minimize the cost of risk and consequently increase their
performance. These results are contrary to those found by Tchakoute Tchuigoua and Nekhili
(2012) who find that age contributes significantly and positively to the improvement of the
economic profitability of 148 microfinance institutions in 56 countries over the period from
2001 to 2006. Age has no effect on operational autonomy and the portfolio at risk. Our results
are consistent with Tchuigoua and Nekhili (2012). Following a multiple regression performed
on a sample of 148 microfinance institutions from 56 countries over the period 2001 to 2006.
Djoufouet (2018) finds no relationship between age and performance for 62 microfinance
institutions in Cameroon over a period from 2009 to 2015. The estimation shows a significant
and positive effect of size on operational self-sufficiency at the 5% threshold. This result is
consistent with that of Mba Fokwa (2020) in the Cameroonian context at the 1% threshold. On
the other hand, Deh et al (2021) in their study on the operational performance of WAEMU banks
find a significant and negative relationship between size and performance. They conclude that
large banks have very high operating expenses such as overheads, which for the most part are
fixed operating expenses that can be paid out. Thus, any decline in net banking income that does
not result in a decline in fixed bank operating expenses negatively impacts the net bank
operating margin. This ultimately impacts the bank's operational performance. Unlike
operational autonomy, size has a significant and negative effect on return on assets. This
implies that any increase in the size of these cooperatives leads to a decrease in their
profitability. The increase in total assets could be synonymous with an increase in fixed assets
that reduces the results of the cooperatives. This situation is also explained by the increase in
the number of active borrowers and the size of loans following the increase in size at the 1%
threshold. The high loan size means that any delay or insolvency of borrowers creates financial
difficulties for cooperatives. Also, the cooperatives could no longer play the role of outreach
with an increasing number of borrowers. Djontu Nzongang (2019) find a similar result in the
Cameroonian context. The rationale for this result is that increasing size challenges the
proximity linkages that are the source of effectiveness for microfinance institutions. Mba Fokwa
(2020) draws a different conclusion to our results. The area of operation does not have a
significant impact on performance in all dimensions except economic profitability. Our results
are consistent with those of Djontu and Nzongang (2019) who find a positive effect. They justify
this result by the fact that the majority of microfinance institutions are located in rural areas,
close to the poor population, in given financial and social inclusion mission. The results can also
be explained by the knowledge and solidarity of the cooperators who live in an environment
where everyone lives together. However, the number of female borrowers increases as the
cooperatives move closer to rural areas with a predominantly female poor population.
CONCLUSION
The objective of this paper is to analyze the influence of governance quality on the performance
of savings and credit cooperatives in Togo. The quality of governance is assessed by a
governance index. The construction of this synthetic index of governance quality takes into
account 27 variables related to internal and external governance mechanisms. These
mechanisms include the characteristics of the board of directors, the manager, the cooperative,
membership in the professional association of decentralized financial systems, external audit,
and rating. These mechanisms are derived from the theoretical framework based on banking,
non-governmental, and microfinance governance. The study focuses on a sample of 55 savings
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and credit cooperatives over the period from 2013 to 2019 in Togo. The results show that
governance quality positively impacts performance as measured by economic profitability,
operational autonomy and portfolio at risk, number of active borrowers, and, percentage of
female borrowers as opposed to average loan size. The control variables influence performance
in different ways. There is a significant and positive association between age and average loan
size. This relationship is negative with the number of female borrowers and economic
profitability. Size has a significant and positive effect on operational autonomy, the number of
active borrowers, and average loan size. Area positively impacts the percentage of female
borrowers. This paper is one of the few studies on governance quality using a synthetic
governance index in Togo. The results of this paper are of several interests. First, they show
that improved governance has a positive impact on the performance of savings and credit
cooperatives. Second, they constitute a tool for promoting good governance practices for the
various actors involved in the microfinance sector, starting with the managers of microfinance
institutions. The limitation of this study lies in the assessment of governance quality through
the calculation of governance indices. All the initial variables were transformed into binary
variables. This could lead to a loss of information due to this transformation. This study only
considers savings and credit cooperatives. Future studies could consider institutions from the
entire sector to highlight differences or similarities in governance.
Annexe
Table: summary of the operationalization of the variables
Variables Measure Authors
Financial performance
Returm on assets (ROA) = 1 if RAO >3% and 0 if not Hartarska (2005)
Messomo (2017) Operational self-sufficiency (OSS) = 1 if OSS >130% and 0 if not
Portfolio at risk 90 (PAR) = 1 if PAR< 3% and 0 if not
Social performance
Number of active borrowers (Breadth) The number Hartarska (2005)
Tchakoute Tchuigua (2010)
Wamba & al., 2014
Djoufouet, 2018
Tlili, 2019)
Percentage of female borrowers
(Depth)
The percentage of women
Loan size (TP) Average credit to GDP per capita
Characteristics of the Board of Directors
Board size Number of administrators Wanda Robert, 2010
Hartarska (2005)
Tchakoute Tchuigua (2010)
Gender diversity in the board of
directors
Number of women on the board Strøm & al. (2014)
Djoufouet (2018)
Gender leadership on the board = 1 if female president of the
board and 0 if not
Frequency of Board Meetings Nombre de réunions statutaires
du conseil par an.
Salloum & Azoury (2010)
Tchakouté Tchuigoua (2014)
Board of Directors Attendance Rate = 1 if the rate is 100% and 0 if not Vafeas (1999)
Jensen (1993)
Education level of directors = 1 when the level is superior or
equal to the Mastery, and 0 if not
Charreaux & Pilot-Belin
(1990)
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Avogan, K. (2022). Analysis of the Influence of Governance Quality on the Performance of Savings and Credit Cooperatives in Togo. Archives of Business
Research, 10(10). 125-144.
URL: http://dx.doi.org/10.14738/abr.1010.13307
Beamish&Dhanaraj (2003)
Age of directors = 1 if age ≥46, and 0 otherwise Maati-sauvez (2016)
Seniority of directors = 1 if number of years≥3 and
otherwise 0
Sahgal (2013)
Expertise on the Board = 1 if an expertise exists in the CA
and 0 otherwise
Tchakouté Tchuigoua (2014)
Wamba & al. (2014)
Characteristics of the manager
Gender of the leader = 1 if female president of the
board and 0 otherwise
Djoufouet et Nzongang, 2020
Seniority of the manager = 1 if at most two persons have
managed the institution and 0
otherwise
Shleifer & Vishny (1989
Manager's level of education = 1 if higher degree greater than
or equal to master's and 0
otherwise
Schatt & Allemand (2010)
Frequency of report writing = 1 if at least two in a year and 0
if not
Schatt & Allemand (2010)
Remuneration of the manager = 1 if the manager is paid and 0 if
not
Boukharrazi (2018)
Manager's evaluation = 1 if evaluation other than the
DG itself and 0 otherwise
-
Presence of the manager in the credit
committee
= 1 if the manager is present and
0 if not
-
Credit methodology and membership
Credit method 1= if both credits and 0 only of
individual credit
Tchakoute Tchuigua (2010)
Predominance of the credit mode = 1 if the SACCO grants more
solidarity credit and 0 otherwise
Tchakoute Tchuigua (2010)
Network membership = 1 if belonging to a network and
0 if not
Tchakoute Tchuigua (2010)
Compliance with regulations
(Membership in APSFD)
= 1 if member of APSFD and 0 if
not
-
Risk management
Internal control system = 1 if the IC exists and 0 if not -
Existence of internal credit committee = 1 if the ICC exists and 0 if not -
Quality of the information system = 1 if the IS is good and 0
otherwise
-
Existence of a risk management unit = 1 if the service exists and 0 if
not
-
Compliance with prudential norms = 1 if all prudential standards are
met and 0 otherwise
-
External audit = 1 if the SACCO is audited and 0
if not
Tchakoute Tchuigua (2010)
Rating =1 if the SACCO is noted and 0
otherwise
Tchakoute Tchuigua (2010)
Control variables
Age of institution (AGE) Number of years the SACCO has
been operating
Deh & al. (2021)
Tchakoute Tchuigoua &
Nekhili (2012)
Size of the institution (SIZE) Total assets of the SACCO Mersland et Strom, 2009 ;
Tchakoute Tchuigoua, 2010
Djontu & Nzongang (2019)
Zone d’activité (ZONE) =1 if the SACCO operates in the
rural area, and 0 otherwise
Djontu & Nzongang (2019
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