IJERD – International Journal of Environmental and Rural Development (2010) 1–1

Research article
erd

Assessing Poverty Outreach of Microfinance Institutions in
Cambodia - A Case Study of AMK
THUN VATHANA
Angkor Mikroheranhvatho Kampuchea (AMK) Co. Ltd., Phnom Penh, Cambodia
Email: thunvathana@yahoo.com

PUM SOPHY
Angkor Mikroheranhvatho Kampuchea (AMK) Co. Ltd., Phnom Penh, Cambodia

SAY SAMATH
National Bank of Cambodia, Phnom Penh, Cambodia
Received 30 December 2009

Accepted 5 March 2010

Abstract The microfinance industry works to balance social and financial benefit, which isviewed as an effective way of helping the poor. The industry, however, faces the challenge
to measure the social bottom line, especially the depth of poverty outreach which refers toserving the poorest clients. This paper aims to investigate poverty outreach and analyze thedepth of outreach for AMK. It assesses the depth of outreach through two main measures:
the Wellbeing Score and Daily Food Expenditure per capita. The analysis is based on bothsecondary data and primary data from a survey in 2009 with 810 samples [648 clients (504group clients and 144 individual clients) and 162 non-clients] randomly selected in 18
provinces in Cambodia. The results of AMK’s depth of poverty outreach for group clients
based on the Wellbeing Score indicate that AMK reaches more poor and medium level
households than in the control group of non-clients, but less better-off clients. For
individual clients AMK reaches a larger share of medium households, less poor households
and a slightly smaller share of the better-off households than what is found in the general
population. The results based on the number of clients spending on food below Food
Poverty Line (FPL) confirm that AMK clients are poor with 56% of group clients and 58%
of individual clients below FPL. Therefore, we conclude that AMK achieves the social
bottom line in term of poverty outreach.
Keywords: Assessment, poverty outreach, microfinance, AMK, Cambodia

INTRODUCTION
Microfinance is a crucial tool to help the poor access financial services. For poor households,
having sources of reliable, convenient and reasonably-priced financial tools would improve theirsituation (Collins et al., 2009). Therefore, the Royal Government of Cambodia and its development
partners are increasingly paying attention to the connections between poverty and microfinance.
In Cambodia, microfinance institutions (MFIs) started in the early 1990s with support from theinternational community. In recent past years the industry has made significant progress and has
witnessed high growth from 2006 to 2008. During this period the number of clients has more thandoubled and the loan portfolio almost tripled. Meanwhile the number of licensed MFIs has
increased remarkably.
The obsession with growth of the industry has led to a situation where there is a concern that
MFIs are turning to commercial principles of operation and neglecting the poor. In conjunction
with the financial and economic crisis there is increasing concern about mission drift of MFIs sliding away from the original idea of helping the poor. Therefore it is crucial to measure thepoverty outreach and the depth of the outreach. Poverty outreach refers to how many poor people
microfinance is reaching, and depth of outreach (or depth of poverty outreach) refers to the poverty© ISERD

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level of clients served. The purpose of this article is to determine the level of poverty outreach andthen analyze AMK client data to assess the performance of AMK in terms of the depth of outreach.
Fig. 1 provides information about the trend in the microfinance industry from 2003 to 2009. It
reveals that the microfinance situation in Cambodia was determined by rapid growth. This resulted
in a tremendous increase of loan portfolio from $ 59 million in 2003 to $ 492 million in 2009. Overthe same period, the number of loans borrowed increased from 351,055 to 1,102,246. (refer to a
Figure in the text before presenting it)
1,020

no. of clients
portfolio in million $

1,000

400

351

200
-

59
2003

419

98

494

600
500

777

800
600

1,102
492

400

438

560

300
271

149

149

2005

2006

200

loan portfolio

no. of loans ('000)

1,200

100
0

2004

2007

2008

2009

Fig. 1 Evolution of loan portfolio and no. of clients
METHODOLOGYThis research assesses AMK’s depth of outreach through two main measures: Wellbeing Score andDaily Food Expenditure per capita. The Wellbeing Score, a relative measure, is the main tool as it
is a multidimensional measure of poverty and provides a good picture of the wellbeing situation forclient households. Client households are then classified into wellbeing groups according to their
particular Wellbeing Scores and information is presented for these groups. To provide an absolutemeasure of poverty, AMK also compares the Daily Food Expenditure per capita with the Food
Poverty Line (FPL) in rural areas. The AMK Wellbeing Score is based on Principal Component
Analysis and was defined in 2006 (reference?). The 22 indicators that comprise the Wellbeing
Score cover three poverty dimensions: expenditures, assets (physical, human and social), andvulnerability and food security. The specific indicators selected are the following:
PHYSICAL ASSETS- Total land area owned by household (HH)
- Floor, wall and roof materials for thehouse/dwelling- HH owns a television, a motorcycle and assets ofmodest, mid or high value

EXPENDITURES- Expenses in clothing and footwear pc- Total HH expense in food
- HH outflows include: inputs for income activities, buying
HH materials and durable assets- Main HH expenditures include food

HUMAN ASSETS- Number of adults (income earners)- Health: strategies to pay for healthcare- Education: literacy of head of household

SOCIAL CAPITAL- Number of good friends /neighbors in community

VULNERABILITY & FOOD SECURITY- Food Security- Household diet in the last year
- Self-reported level of difficulty in affording large expenses - Ordinal- Incidence of reducing nutritious quality of foods- Main income activities: casual labor or temporary migration (domestic or international)- Savings and reinvestment behavior- Coping strategies: less food consumption, less non-food expenses, selling personal property© ISERD

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The AMK-PCA model was based on the IFRI/CGAP Poverty Assessment Tool but wasadapted to the rural Cambodian context and applied to food security as the main poverty
benchmark. The AMK-PCA model achieved relatively good results. Note that the Kaiser-MeyerOlkin (KMO) index was 0.818 when applied to non-clients and 0.848 to the total 450 HH. In
general, index scores > 0.60 are acceptable, > 0.70 are good, > 0.80 are commendable, and > 0.90
are exceptional.
The analysis for this article is based on data collected from both AMK new clients and nonclients from 54 villages in 18 provinces over the period from March to May 2009. Eight hundred
and ten samples (648 clients and 162 non-clients) were interviewed. Among the 648 clients, 504
were group or Village Bank (VB) clients and 144 Individual (ID) clients. In order to assess how
AMK is reaching the poor, clients referred to in this study were those who joined AMK within ayear prior to the field survey.
The client sample selection was conducted in two steps: first, 54 villages with at least 18 newclients were randomly selected; and second, 12 clients per village were randomly selected plus 6
clients as potential replacements. One reason of choosing 12 clients is efficiency which is based on
past experience of AMK research team. For relative poverty study, 3 non-clients per village wereselected for interviews. This means that the ratio between client and non-client samples is 4:1. The
non-client samples had to be non-client households who were next to the selected client households.
Therefore, the total number of interviewed clients and non clients was 810.
RESULTS AND DISCUSSION
Currently, there are one million clients with 492 million US$ loan outstanding covered by 20
licensed MFIs, one commercial bank (ACLEDA small loan) and one licensed NGO, accordingly to
Cambodia Microfinance Association (CMA). Table 1 shows that the top three institutions which
include AMK account for 60% of the market share in term of client outreach.
Table 2 shows that more than half of AMK loans were used for productive purposes either forfarm or non-farm activities. Meanwhile AMK clients also used loans for different purposes: 10%
for food, 8% for health, 14% for buying assets (vehicles, land and gold), and 9% for otherconsumption.
Table 1 Market share by MFIs

Table 2 Loan uses by AMK clients

MFIs
No. of clients
Share (%)
AMRET
224,70820
ACLEDA
223,68720
AMK217,81820
VFC
98,7779
TPC
91,1708
PRASAC
87,945
8
Others158,141
14
Source:Authors,
calculated
from
CMA
Values were
calculatedon thebased
basisonof data
the data
from
CMA

Loan uses by AMK clients
Farm
Productive
purposesNon-farm
AssetsSavings
Land and gold
Food
Consumption
HealthOthers
Source:2009
Source:AMK
AMKfieldfield research, 2009

Share (%)
40
19
11
3
10
8
9

According to Gulli (1998), there is a positive correlation between reaching many poor people
and financial sustainability. Therefore AMK, as a social MFI, has worked hard to include the poor
from both rural and urban locations. So far, its performance in reaching large number of poor has
been higher than the national average of the industry. Also AMK has achieved financial
sustainability since 2004.
Assessment by Wellbeing Score
The average Wellbeing Score for VB clients was -0.020 and for non-clients was 0.080 (Fig. 2).
This indicates that clients were poorer than non-clients (the t-test for equality of means is not© ISERD

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significant while the independent t-test is: N=630, F=0.04, p-value=0.315). Regarding ID client
status, Fig. 2 shows that the average wellbeing score for AMK ID clients was 0.076 and theaverage wellbeing score for non-clients was -0.019, indicating that ID clients are wealthier thannon-clients (the t-test for equality of means is not significant while the independent t-test is: N=180,
F=3.15, p-value=0.609). It is important to realize that VB non-client scores and ID non-clientscores are different groups because they are from different locations.

0.1

0.1

0.08

0.08

0

0

-0.02

-0.02
-0.1

Non-clients

ID clients

VB clientsNon-clients-0.1

Fig. 2 Average household wellbeing score2.18382
1.54997
1.26964
1.10524.94888.81948.62845.51020.37470.26974.13943.05736-.04768-.14915-.26521-.40480-.53361-.68712-.83131-1.01454-1.22496-1.38553-1.69039-2.59744

Non-clients
VB clients

Wellbeing score

Wellbeing score

Fig. 3 shows the cumulative frequency for non-clients and VB clients; there is a small
difference in poverty levels between the two groups only in the upper 40% and lower 40% ofhouseholds on the cumulative frequency. Fig. 3 also shows the cumulative frequency for nonclients and clients, showing a margin of difference in poverty levels between the two groups
situated in the lower 50% part of the cumulative frequency.

0

20

40

60

80

2.062631.52463
1.27994
1.00018.84745.68935.62002.51323.39116.31039.17204.04037-.10395-.21063-.36026-.46233-.70948-.82535-1.07894-1.21978-1.41869-1.65048-2.33114

Non-clients
ID Clients

0100

Cumulative percent

20

40

60

80

100

Cumulative percent

Fig. 3 Accumulative Frequencies for Non-Clients and Clients

Assessment by tercile analysis
The Wellbeing Score is a relative poverty score and measures whether a household is worse off or
better off compared to other households in the general population. Each household sampled has
been assigned a Wellbeing Score: the lower the score, the poorer the household relative to all otherhouseholds with higher scores. The following steps were followed to develop the tercile results.
First the 126 non-client households from VB villages were sorted in ascending order according
to their Wellbeing Scores. Second these 126 samples were divided into terciles based on Wellbeing
Scores: the bottom third of the non-client households are grouped into the “poor” group, followedby the “middle” and the “better-off” group. Since there are 126 non-clients, each group contains 42.
The cutoff scores for each tercile define the limits of each poverty group and they were -0.3428 and
0.5309. Third, the 504 client households were then categorized into the same three groups based on
their scores using the cutoff scores defined above for the AMK-PCA case (i.e. -0.3428 and 0.5309).
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If the pattern of poverty among client households matches exactly that of non-client
households, the client households will divide equally among the three wellbeing groupings in thesame way as non-client households, with 33 percent falling into each group. Any deviation fromthis equal proportion would signal a difference between the client and non-client populations. The
results shown in Fig. 4 are that VB clients are slightly over-represented within the poorer tercile,remain the same in the medium and are under-represented in the higher tercile. Therefore AMK isreaching a larger share of the poor households, an equal share of medium classified households anda slightly smaller share of the better-off households than in the general population.
non-clients

38

33

33

clients

33

non-clientsclients

47
33

30

33

33

33

MediumBetter-off

31

22

Poor

MediumPoor

Better-off

VB: wellbeing group (% of households)

ID: wellbeing group (% of household)Fig. 4 Tercile analysis by wellbeing group

For the ID case, the same steps were followed. First the 36 non-client households were sorted
in ascending order according to their Wellbeing Scores. Second this 36 household sample wasdivided into terciles based on Wellbeing Scores: the bottom third of the non-client households aregrouped into the “poorer” group, followed by the “middle”-ranked group, and finally, the “betteroff” group. Since there are 36 non-clients, each group contained 12 households. The cutoff scoresfor each tercile define the limits of each poverty group and they were -0.755 and 0.568. Third, the144 client households were then categorized into the same three groups based on their scores using
the cutoff scores defined above for the AMK-PCA case (i.e. -0.755 and 0.568).
The results indicate that ID clients are under-represented within the poorer tercile, highly overrepresented in the medium and are slightly underrepresented in the higher tercile (Fig. 4). Therefore,
AMK is reaching a larger share of the medium households, less poor households and a slightly
smaller share of the better-off households than found in the general population.
Assessment by absolute poverty benchmark
The Wellbeing Score calibrates relative poverty but does not provide information on the absolutelevel of poverty, i.e. it measures the extent to which a household is worse off or better off
compared to other households, but does not assess the actual level of deprivation of the poorer
category of households or the level of affluence of the better-off households. To provide anestimate of absolute levels of poverty, AMK compared the Daily Food Expenditure per capita withFPL in rural areas. AMK Daily Food Expenditure figures include not only the cash expenses infood items but also quantify consumption from the household’s own production (including rice andother crops, vegetables or animals) and from other food items gathered, collected or fished.
The overall Cambodian Poverty Line for rural areas was set at Riel (R) 1,753 per person per
day and the FPL for rural areas at R 1,389 per person per day in 2004. The Cambodian FPL allows
a person to consume a food basket that provides at least 2,100 calories of energy per day. Therefore,
a person who consumes less than this FPL is not receiving the minimum amount of calories
necessary to maintain their health. Since there are no rural inflation figures in Cambodia, in order
to update the 2004 FPL to the prices at the time of the fieldwork, AMK uses a proxy: the rural FPL
is updated with the Phnom Penh Consumer Price Index (CPI) for food and beverages. Details of theproxy update are shown in Table 3.
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Table 3 Proxy update of poverty line (1 US dollar = 4,118 Riel)
Total Poverty Line 2004

AMK Proxy FPL 2009

Food Poverty Line (FPL)
2004

Riel / day

US$ / dayPhnom Penh

2,351

1,782

2,855

0.69

Other Urban

1,952

1,568

2,512

0.61

Rural

1,753

1,389

2,225

0.54

Several years ago almost all AMK clients were below the conventional definitions of thepoverty line (Chetan, 2007). This study indicates that the number of clients below the poverty line
has decreased but average food expenditure remains lower among ID clients than VB clients. Fig. 5
shows the Daily Food Expense per capita for both VB and ID AMK clients and compares it withthe updated rural FPL (AMK proxy for May 2009). This confirms that most clients are consuming
less than the minimum calorie intake per day and thus can be classified as poor, which partiallyconfirms AMK’s commitment to provide services to the poor.

100

30

N ati onal (R ural) Foo d

Nat iona l (Rural ) F ood

P ov ert y Li ne (p roxy updat e

P ov erty Line (prox y u pdat e
25

M ay 2009) = R 2 ,22580

M ay 20 09) = R2, 225

20

60
15

40
10

M ean = 2, 183. 1378

M ean = 2,24 7.33 66

S t d. Dev . = 836 .296 24

S td. Dev . = 1,0 97.6 7852

205

N = 504

N = 14 4000

2 ,0004, 0006,00 0Dai ly F oo d Exp en se P C: V B Cl ien ts

1,0 008,00 02 ,0003, 000
4 ,000Dai l y F oo d E xpen se PC : I D Cl ie nts

5, 0006, 000Fig. 5 Daily food expenditure per capita

As a national benchmark the overall Cambodian poverty headcount is estimated at 30.1%, butwith wide variations: it was 35% in rural areas, 22% in other urban areas and only 1% in Phnom
Penh as of 2007. As for national food poverty, 22% of the population in the rural, 11% in the urban
and 1% in Phnom Penh are considered to consume less than FPL. Note that the percentage of nonclient households who consumed less than this benchmark was lower (49%) but the significant test
cannot confirm that the differences are statistically significant (Chi Square (N = 180) = 0.051, p =0.821). Also note that the reasons for these large discrepancies in the poverty figures have not been
completely assessed and that this issue is yet to be resolved.
However, new AMK clients below FPL were 71% in 2006, 75% in 2007 and 63% in 2008
(AMK, 2008). In 2009, food poverty analysis has shown that 56% of VB client households
consumed less than FPL of R 2,225 (Table 4). Clients falling into the Poor tercile group had thehighest percentage of household below FPL at 68%, followed by the medium and the better-off at
54% and 44%, respectively.
The study also indicates that 58% of ID client households consumed less than FPL of R 2,225.
Meanwhile, the percentage of non-client households who consumed less than this benchmark wasslightly lower at 56%. Poor group has the highest percentage of household below FPL at 78%,
followed by the medium at 60% and the better-off at 39%.

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Table 4 Clients below the Cambodian FPL
Description
No. of HH below the FPL% of HH below the FPL
No. of HH below the FPL
ID Clients% of HH below the FPL

VB Clients

Clients

Nonclients

Overall

Poor

62
49
20
56

283
56
83
58

128
68
25
78

Medium Better-off
90
54
41
60

65
44
17
39

CONCLUSION
The results of the two measures of depth of poverty outreach (the AMK Wellbeing Score and therates of absolute poverty compared with Cambodian FPL for rural areas) allow the conclusion thatbased on the Wellbeing Score AMK is reaching less better-off clients than what is found in thecontrol group of non-clients, but more medium and poor level households. The results of AMK’s
depth of poverty outreach for VB clients in 2009 based on the number of clients who fell below theCambodian Food Poverty Line, confirm that indeed AMK clients are poor with 56% of clients
below the line.
The results of AMK’s depth of poverty outreach for ID clients in 2009 based on the Wellbeingscore indicate that these clients are on average relatively better-off than VB clients. However, thisis somewhat skewed upward due to a high proportion of very well off ID clients. With a Wellbeing
Score assessment only among the ID samples, AMK is reaching more medium clients than what isfound in the control group of non-clients but less in better-off and poor-level households. The
results of AMK’s depth of poverty outreach for ID clients in 2009 is based on the number of clientsspending less on food than the Cambodian Food Poverty Line, and this confirms that indeed AMK
clients are poor with 58% of clients falling below the Cambodian Food Poverty Line.
ACKNOWLEDGEMENTS
We thank AMK and its management for funding this research and all AMK research team members
who have contributed time and effort to make this research effort a reality. Special recognition is given
to Oliver Rogall, Doet Samnang and Vong Pheakyny for their expertise and knowledge that they
gradually shared. Our warmest appreciation also goes to other colleagues in AMK for their support
during the field surveys.

REFERENCESAMK (2008) Annual Report 2008. Angkor Mikroheranhvatho Kampuchea, Cambodia.
Chetan, T. (2007) Are financial and social objectives mutually exclusive? The experience of AMK Cambodia.
International Journal of Microfinance and Business Development, 18(1), 65-78.
Collins, D., Morduch, J., Rutherford, S. and Ruthven, O. (2009) Portfolios of the poor, How the world’s poor
live on $2 a day. Princeton University Press, USA.
Gulli, H. (1998) Microfinance and poverty, Questioning conventional wisdom. Microenterprise Unit,
Sustainable Development Department, Inter-American Development Bank, USA.

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