Proceedings of Global Business Research Conference
7-8 November 2013, Hotel Himalaya, Kathmandu, Nepal, ISBN: 978-1-922069-35-1
External Governance and MFI Sustainability: Evidence from
Africa
Tanweer Hasan* and Shakil Quayes
The present study investigates if external governance measures have any
impact on the sustainability of MFIs using data from 28 African countries over
the period 2003 through 2006 with data from the Mix Market. Results from the
empirical analysis are reported in the tables below. Results from the pooled
regression analysis, reported in Table 4, show that external governance
mechanisms, specifically regulations and getting rated by rating agencies, do
have positive impacts on the sustainability of MFIs in Africa.
__________
Tanweer Hasan,* Roosevelt University, USA, Phone: (847) 619-4886, Fax: (847) 619-4850,
Email: thasan@roosevelt.edu
Shakil Quayes, University of Massachusetts Lowell, USA, Phone (978) 934-2786, Fax (978) 934-3071,
Email: shakil_quayes@uml.edu
Reference
Barry, T. A., and Tacneng, R. (2011), “Governance and Performance: Evidence from
African Microfinance Institutions”, working paper.
Chao-Béroff R., TH. Cao, J-P. Vandenbroucke, M. Musinga, E. Tiaro, L. Mutesasira,
(2000), “A Comparative Analysis of Member-Based Microfinance Institutions In East
And West Africa”, Microsave.
Hartarska, V., 2004, “Governance and Performance of Microfinance Institutions in
Central and
Eastern Europe and the Newly Independent States”, World Development 33:10, 16271648.
Hartarska,V., Nadolnyak, D., 2007. “Do regulated microfinance institutions achieve
better sustainability and outreach? Cross-Country Evidence”, Applied Economics 39:10,
1-16.
Proceedings of Global Business Research Conference
7-8 November 2013, Hotel Himalaya, Kathmandu, Nepal, ISBN: 978-1-922069-35-1
Table 1: List of Countries in the Sample
(Total Sample Size = 427)
SL #
1
2
3
4
5
6
7
8
9
10
11
12
13
14
Name of the Country
Angola
Benin
Burkina Faso
Burundi
Cameroon
Chad
Congo
Congo, D R
Cote D’Ivoire
Ethiopia
Ghana
Guinea
Kenya
Madagascar
N
2
29
8
2
18
7
6
14
2
55
10
1
30
17
SL #
15
16
17
18
19
20
21
22
23
24
25
26
27
28
Name of the Country
Malawi
Mali
Mozambique
Niger
Nigeria
Rwanda
Senegal
Sierra Leone
South Africa
Swaziland
Tanzania
Togo
Uganda
Zambia
N
11
30
24
8
14
8
31
7
183
4
21
17
32
12
Table 2: Descriptive Statistics
Variable
N
Mean
Sustainability
Rated
Regulated
Age
Size
Risk
427
427
412
427
427
360
1.08
0.31
0.76
8.99
13.04
0.09
Standard
Deviation
0.39
0.46
0.43
5.95
28.22
0.11
Minimum
Maximum
0.13
0.00
0.00
1.00
0.04
0.00
2.98
1.00
1.00
37.00
287.50
0.94
Notes:
(1) Sustainability (Operational Self Sufficiency, OSS): calculated as OSS = [(Operating Income) /
(Financial Expense + Loan-Loss Expense + Operating Expense)]
(2) Rated: dummy variable, assigned a value of 1 if rating agency has rated the MFI, 0 otherwise
(3) Regulated: dummy variable, assigned a value of 1 if the MFI is regulated, 0 otherwise
(4) Age: In years and calculated as Age = (Current Year – Year of Establishment of the MFI)
(5) Size: Total assets of the MFI in millions, in US $
Proceedings of Global Business Research Conference
7-8 November 2013, Hotel Himalaya, Kathmandu, Nepal, ISBN: 978-1-922069-35-1
Table 3: Correlation Matrix for the Explanatory Variables
Variable
Rated
Regulated
Age
Size
Risk
Rated
1.00
-0.08
0.12**
0.27*
-0.17*
Regulated
Age
Size
Risk
1.00
-0.02
0.10**
0.01
1.00
0.42*
0.01
1.00
-0.11**
1.00
Notes:
(1) Size = log of total assets of the MFI
*
(2) indicates that the correlation coefficient is significant at 1% level.
**
(3) indicates that the correlation coefficient is significant at 5% level.
Table 4: Regression Analysis (N = 346)
Sustainabilityi = α + β1 Ratedi + β2 Regulatedi + β3 Agei + β4 Sizei + β5 Riski + εi
Variable
Constant
Coefficient
0.05
Rated
0.08
Regulated
0.10
Age
0.00
Size
0.06
Risk
-0.27
F-statistic
VIF Range
10.46
(0.00)*
1.03 – 1.39
Adjusted R2
12.06%
t-statistic
0.27
(0.79)
1.84
(0.07)***
2.12
(0.04)**
0.09
(0.93)
4.61
(0.00)*
-1.53
(0.13)
Notes:
(4) Size = log of total assets of the MFI
*
(5) indicates that the correlation coefficient is significant at 1% level.
**
(6) indicates that the correlation coefficient is significant at 5% level.