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6 Evaluation of Microcredit Self-help-groups
This chapter continues from the previous chapter and presents an impact assessment of
Microcredit self-help-groups, more or less on the lines of the previous chapter. The
previous chapter highlighted the excellent outreach in terms of asset holding and low cost
of credit amongst the strengths of RRBs, while the problem of default and monitoring
were found to be its weakness. This chapter attempts to subject Microcredit self-help -
groups to a similar analysis.
The data used in this section was collected during the course of field work conducted
over the period of April - September 2006 in Madhugiri taluk, Tumkur district, Karnataka
State. Madhugiri is one of the five most backward taluks identified by the ministry of
rural development and Panchayat along with the other taluks of Sira, Kunigal, Gubbi and
Pavagada. Madhugiri is about 150 kilometres from the state capital Bangalore. It is well
connected by roads. Surveys were conducted in many villages of Dodderi Hobli (An
administrative unit representing a groups of villages. Many Hob/is make a taluk) and a
few surrounding villages totalling 26.
A total seventy members interviewed belonged to as many as forty three groups in as
many as twenty six villages in Dodderi Hobli. A maximum of members from two groups
were interviewed per village to ensure a randomness of sample. However, not many
villages had more than three groups. But almost all villages had at least one group. Some
villages were located on main road connecting the taluk headquarters of Madhugiri and
the neighbouring Sira. These villages were easily accessible because of frequent private
buses. There is also passenger autorikshaws plying between some of these villages. A
few villages were located off the main road and had to be reached on two wheelers
because of inconvenient public transport. The government operated K.S.R.T.C does not
ply on these routes. Group members in villagers were identified and interviewed.
229
Geography and Demographics:
Madhugiri is a taluk in the district of Tumkur in Karnataka state. The area was selected
taking into account the high percentage of poverty besides being easily accessible by
road. Madhugiri is located at 13.66° N 77.21° E. The total population is 252278. GOK The
annual rainfall ranges from 453.5-717.7 mm of which more than 55% is received in
Kharif season. The elevation ranges between 450-900 m, with an average of 787 meters
(2582 feet) and the soils are red sandy loams in major areas, shallow to deep black in the
remaining areas. Also, Madhugiri is classified under 'very dry areas' where in moisture
indices are less than minus 60%. The principal crops grown are ragi, jowar, pulses and
Oilseeds.44Most of the rainfall occurs during the south-west monsoon. The area is
drought prone and it is one of the taluks with greatest percentage of drought years.45
Table 98 : Population
Total Population
Male Female Total
Dodderi 28713 {49.5) 29318 (50.5) 58031
Madhugiri 129878 (51.5) 122400 (48.5) 252278
Tumkur 1052663 (50.6) 1025913 (49.4) 2078576
Kama taka 19016168(50.6) 18534829
(49.4) 37551895
Total population of Madhugiri is 252278, of which 51.5% are men and 48.5% are
women. In Dodderi Hobli, females constitute more than 50.5% and males constitute less
than 50% of the population. In Tumkur district as a whole, the percentage of men in total
population is about 50.6% and that of women is about 49.4%. There appears to be a small
difference in the pattern of distribution of population which can be attributed to the
tendency of men to work in nearby towns leaving their families in the villages. Also, a
44 http://wgbis.ces.iisc.emet.in/energy/paper!IRI 09/trl 09 _ std2.htm 45 ibid
230
sizable population of young men also study in the nearby cities thereby skewing the trend
in favour of women. The trend, however, does not make a significant difference.
A social group wise break up of population figure is given in the table below. The taluk
has a total population of 252278.46 Scheduled Castes constitute over 23% of the
population and Scheduled Tribes a little over 11%. Both are over and above the state and
district average. The state average happens to be 18.6% and 8.18% respectively. The
spike in the tribal population is because of a tribal habitation in the taluk Madhugiri. The
habitation is called a Tanda. In the Hobli of Dodderi, the total population is about 58031,
with Scheduled Castes constituting about 17.84% and Scheduled Tribe about 9%, which
is close to the state average.
Table 99: Population According to Social Groups
Population According to Social Groups
sc ST
Male Female Total Male Female Total
Dodderi 5459 4896 10355 (17.84%) 2631 2551 5182 (8.92%)
Madhugiri 31107 28465 59572 (23.6%) 14438 13892 28330 (11.3%)
Tumkur 209506 203414 412920(19.87%) 86478 83505 169983(8.18)
Kama taka 3455824 3362601 6819043(18.16) 1528896 1483871 30 12737(8.02)
Source: GOK
Literacy figures are given in the following table. The taluk happens to be very backward
in terms of literacy. It is far lower than the national and state average. Kamataka has a
literacy of over 67% which happens to be a tad better than the all India average of
65.38%. Both male and female literacy are above average, at 76.29% and 57.45% for
male and female population respectively, as against the national average of 75.96% and
54.28%. Literacy in the district of Tumkur at 75% is more than state average of 67%. A
record 70% of the female population in the district of Tumkur are literates. But the taluk
46 As on April 2002-03
231
of Madhugiri performs very poorly at just about 41 %. In fact, only a third of the female
population happens to be literate. In Dodderi Hobli, only a little over 45% of the male
population is literate and about quarter of the female population is literate. The total
literacy happens to be around 35.15%.
Table 100: Literacy Figures
Literacy figures (In%)
Male Female Total
Dodderi 45.8 24.5 35.15
Madhugiri 51 30.8 40.9
Tumkur 79 70 75
Kama taka 76.29 57.45 67.04
India 75.96 54.28 65.38
Source: GOK
The peasants or Vokkaliga community are the most dominant community. They are the
landowning community and are relatively better off. The trading classes of Arya Vaishya
and Balija along with the Muslims are the other visible communities in the semi urban
areas. The 'Nayak', 'Holeya' and 'Madiga' are the Scheduled Castes and most of the
agricultural labours belong to either of these castes. The Lambanis are the most important
of the Scheduled Tribes. The OBC community of Vokkaliga is both politically and
economically influential throughout Karnataka.
Agriculture:
Agriculture is the primary occupation in the taluk. A large number of families rely on
agriculture for their livelihood. Over 71% of the families in the Hobli of Dodderi are
engaged in agriculture, which happens to be higher than the state average of 66.19% of
the households. When entire Madhugiri taluk is considered, it is found that the percentage
is higher at over 76%. The major landowning community is the relatively wealthy
Vokkaliga community. A few big Landlords also belong to the 'Reddy' community.
232
Table 101 : Distribution of Agricultural Households
Agricultural families
Total families Agricultural families percentage
Dodderi 10741 7645 71.18
Madhugiri 49883 38229 76.64
Tumkur 426667 317527 74.42
Kama taka 6417103 4247449 66.19
Source: GOK
The area is semi-arid and has very few means of irrigation. So crops suitable for dry
conditions are by far the most popular. Pulses, groundnuts and millets are the most
popular crops. Pulses appears to be the most popular crop covering almost 44% of the
cropping area (Net Sown Area) in the Taluk ofMadhugiri and about 52% of the cropping
:tre:~ in the Hobli of Dodderi. Groundnut happens to be the only major commercial crop.
Together with other oil-seed, groundnut covers about 21.5% of the total cropped area in
the taluk of Madhugiri and about 21.4% in the Hobli of Dodderi. Amongst cereals ragi or
fmger millets and maize happens to be most popular. In the Taluk of Madhugiri, about
4.7% of the total cropped area is under ragi and about 4% under maize. But in the Hobli
of Dodderi, ragi occupies about 6.5% of the total cropped area and maize an insignificant
less than 1%. Sugarcane, coconut, cotton and mangoes are also grown but sparsely, in
patches with sufficient water supply. Same is the case with the cereal crop paddy. It
should be noted that such crops need relatively more water supply and this is ensured by
bore wells. Therefore, farmers who can afford to own bore wells grow these crops.
Table 102 : Crop Pattern in Madhugiri and Dodderi
Crop pattern (total area under the crop in hectares)
Madhugiri Dodderi
Area under crop percentage Area under crop percentage
Paddy 2534 2.4 441 2.3
Ragi 4920 4.7 1233 6.5
233
Jowar 1096 1 165 0.9
Bajra 27 0.02 10 0.05
Maize 4289 4 52 0.27
Total Cereals 13929 13.2 2152 11.3
Groundnut 22579 21.5 4072 21.4
Sugar care 1095 1 10 0.05
Cotton 155 0.15 149 0.8
Pulses 44403 42.2 10228 53.7
Coconut 1138 1.1 337 1.8
Mango 444 0.4 28 0.15
Total 105182 19058
Source: GOK
The area is mostly dependent on rains for irrigation. Apparently, close to half the total
cultivable area appears to be irrigated in the taluk of Madhugiri. But it is quite clear from
the table that most of the irrigation is through a network of tanks and wells which
invariably get dried up in summers and also during monsoon in drought stuck year. There
is problem of accumulation of silt in the tanks as well as breach of tanks during heavy
monsoons due to poor maintenance. Wells too are not helpful in these days because of
falling ground water level. Reckless exploitation of ground water table has lead to
competitive drilling of bore wells. There are instances of bore wells being dug up to the
depth of 400 - 500 feet. There is not much scope for canal irrigation in this region.
Though other taluks of Tumkur district have a decent canal network feeding the water
from river Hemavathi, Madhugiri still relies mostly on tanks and wells. A small river runs
through a part of Madhugiri called Jayamagali. But the river is rain fed and it is dry for a
good part of the year. Also, the river gathers enough ~ody only when the monsoon is
strong and bountiful. Since Madhugiri is a drought prone taluk, the river in flow can be
seen only once in every few years. In Tumkur district as a whole, almost 66% of the net
sown area is under irrigation. Also, only a third of the whole of Kamataka is irrigated. It
is also worth noting that the Sujala Watershed Development Programme is being
implemented by the Government of Kamataka. The programme is partly funded by the 234
World Bank. In the light of depleting ground water table, the programmes intend to
improve the watershed and related resources.
Table 103 : Irrigation Pattern in Madhugiri and Dodderi
Area Under Irrigation (in Hectares)
Madhugiri % Dodderi % Tumkur % Kama taka
Total Cultivable Area 68277 100 15314 100 726988 100 13246535
Wells 11652 17 2016 13 64884 8.93 1070903
Tanks 11836 17.3 1102 7.2 62981 8.66 1248909
Canals 1673 2.45 83 0.5 20852 2.87 656130
Total Irrigated Area 30791 45 4455 29 482071 66.31 3919662
Source: GOK
The objective of the programme is to "improve the productive potential of selected
watershed and their associated natural resource base, and strengthen community and
institutional arrangement for natural resource management." The programme involves the
active intervention of local communities and NGOs in developing new water resources
and improving existing resources. If the programme is successfully implemented there is
a possibility of the irrigation scenario improving in the long run.
NGOs and Group Formation:
A lot of NGOs are active in this region. They are actively involved in various
community development programmes including literacy, microcredit and tribal welfare.
Therefore the people in the area are quite aware of NGOs and their style of functioning.
The NGOs active in the area are also promoting the formation of groups. Concurrent
microcredit programmes offered by various institutions are operating in the area. So the
area is very heterogeneous when it comes to type and operation of Microcredit groups.
The NGOs promote the formation of groups, motivating women to come together to form
groups. In the initial stages, the NGO also nurture the groups. The NGO themselves
manage the accounts of the group until one of the member or members of the group are
trained and are confident enough to manage the group themselves. The NGO will play an
235
%
100
8.08
9.43
4.95
29.59
instrumental role in providing these groups an access to bank credit. At times they act as
a financial intermediary between the groups and the banks wherein the banks sanction
credit to the NGOs for on lending to the groups. The NGOs are promoting groups called
the Swsahaya groups. NGOs play a very important role here. It should be understood that
the cost of formation/promotion/nurturing the groups are all internalized by the NGOs.
The resource base and balance sheets of these NGOs are opaque at the best and absent at
the worst. Therefore aggregated data is not available for such groups. There are groups
promoted and nurtured by banks as well.
Profile of Field work respondents:
A total of 70 members of various Self-help-groups were interviewed to collect the
required data. All of them were women. In case of multiple members of a family holding
membership in Self-help-groups, only one of them was included. Hence, each on~ uf th~
respondents represents a particular household. The households included joint families as
well as nuclear families. Members of the household staying away temporarily, even as
guests and other visitors were excluded from the count of members in the household.
More than 40 households consisted of less than or equal to four members, i.e. a little
over 57% of the sample had less than or equal to four members. About 26 households,
that is, a little over 37% of the sample consisted between 4 and 8 members. Only four
households consisted of joint families with more than 8 members, that is, less than 6%.
Table 104 : Size of the Households
Numbers of members in the households
Number of Members No ofHouseholds Percentage
<=4 40 57.14
4 to 8 26 37.14
More than 8 4 5.71
Total 70 100.00
236
Women belonging to the OBC castes con:!'tlitllated the majority of over 64% of the
respondents. They mostly belonged to the if'J,Jdaliga and Balija castes; the former is
professionally associated with cultivation mdl the later, trade. There were only seven
respondents who belonged to Scheduled Tribe$;. That is about 10% of the sample. They
constituted about 9% of the local populati•O•l .. Therefore they were marginally over
represented in the sample. About 17% oftltoe:~]Jondents belonged to Scheduled Castes.
There were 4 Muslim respondents, which is ~U~omTt 5.7% of the sample. There were only
two respondents who belonged to the others" c.ategory. This consists of upper caste
communities like Lingayats and Brahmins ..
Table 105: Social Groups
Social Groups in the sample
Caste Frequency Percentage
sc 1') 17 ~~
ST 7 10
OBC 45 64.3
Muslim 4 5.7
Others 2 2.8
Total 70
Calculating the annual income of a ]u~~m:e!t()ld is fraught with difficulties. The
respondents' opinion was not considered a1 F.uc:e value but a detailed break of the stream
of income of the households from vari<l-& as.sets were summed together to get the
approximate annual income. About 15.7% Ulff the respondent households had an annual
income ofupto Rs.lOOOO. More than a third ofiboe respondent households belonged to the
annual income class of over Rs.lOOOO but I~ than Rs.20000. Almost a quarter of the
respondent households had an annual inc!:'~: of over Rs.20000 but less than Rs.30000.
Only 4.3% of the respondent households h:a\dlann annual income of over Rs.30000 but less
than Rs.40000. Almost 20% of the responll·e~n't Jnouseholds had an annual income of over
Rs.40000.
2311
Table 106 : Annual Income Class
Annual Income ofHouseholds
Income Class frequency percentage
Up to 10000 11 15.7
10001-20000 25 35.7
20001-30000 17 24.28
30001-40000 3 4.3
400001-50000 6 8.57
50001 above 8 11.4
total 70
About 41.4% percent of the respondents belonged to agriculture labour households. They
did not own any asset except their own labour. Marginal farmers constituted over 34%.
They not only own small patches of land but also milch cattle. Almost a fifth of the
respondent households belonged to the category of small farmers who own over 2.5 acres
but less than 5 acres. Only 5. 7% of the respondents belonged to the category of medium
large farmers who owned more than 5 acres of land.
Table 107: Frequency distribution according to Asset Class
Asset Class
Frequency Percentage
Agriculture Labour 29 41.4
Marginal Farmer 24 34.3
Small Farmer 13 18.6
Medium Large Farmers 4 5.7
Total 70
Half the respondent households owned cattle mostly milch animals. Buffalos were most
popular followed by cows. A few of the families also owned sheep and goats.
238
...
Table 108: Cattle Heads per Households
Cattle Heads Per Households
Cattle Heads Frequency Percentage
No Cattle 35 50
1 29 41.4
2 2 2.9
3 3 4.3
4 1 1.4
A third of the respondents were illiterates, a little over 20% had some form of primary
education. More than 37% had attended some form of high school. Only about 20% of
the respondents had higher secondary education. Of the total sample, 10% were also
graduates who had mostly studied BA at the colleges close to their village. The
percentage of literates in the groups is clearly more than the actually percentage of
literates in the area. The female literacy in the Hobli of Dodderi was just about 35%;
however, the literacy level amongst the respondents was much higher at over 65%.
Table 109: Education
Pattern of Education amongst respondents
Education level frequency percentage
Illiterate 23 32.9
Primary 14 21.4
High school 20 37.1
Higher secondary 6 20.5
Graduation 9 10
Total 70
239
Most of the respondents were married. But there were a few female headed households
consisting of widows and women deserted by their husbands. Very few of the women
were unmarried.
Table 110: Marital status
Marital Status of Respondents
Frequency Percentage
Married 60 85.7
Unmarried/Widows 10 14.3
Most of the respondents belonged to cultivator households with the primary listed
occupation of agriculture. A little over 12% of the respondents were housewives. They
call themselves housewife but they did work on their own field, at times had reared
chickens, raised a small vegetable patch. Therefore the classification of the respondents
into housewife is not watertight. 18.6% of the respondents belonged to agriculture labour
households. Over 42% of the respondents listed their occupation as others, including
Anganwadi helpers, cooks, domestic servants, petty traders, peddlers, stone cutters and
cattle herd.
Table 111: Occupation of Respondent Borrowers
Occupation of Borrowers
Occupation frequency percentage
Farmer 18 25.7
agriculture labour 13 18.6
others 30 42.9
Housewife 9 12.8
total 70
A third of the respondents listed the occupation of their spouse, husbands in this case as
farmers. Over 18% of the respondents' spouse worked as agricultural labours. Other
240
occupation of the spouses was petty traders, masons, painters, drivers, auto drivers and
stone cutters.
Table 112: Occupation pattern of the Spouse of Respondent
Occupation of the Spouse
Occupation frequency percentage
farmer 20 28.6
agriculture labour 13 18.6
others 27 38.6
No spouse 10 14.28
total 70
There appears to be a weak correlation between the occupations of the wife and the
husband. In case of the respondent working as an agriculture labour, there was more than
50% probability that the husband is also an agriculture labour. Also women who were
living without their spouses (widows, deserted wives) we also likely to be agriculture
labour.
Table 113 : Occupation among AL
AL Women and occupation of their Spouse
spouse occupation Distribution of AL Women
No Spouse 2
Agriculture 1
Agricultural Labour 7
Others 3
Grand Total 13
Respondents who were engaged in agriculture (mostly as farm hands) were more likely to
have a spouse who is also engaged in agriculture. The probability was higher than
80%.The correlation was stronger at about 0.63.
241
Table 114: Occupation Pattern
Women engaged in agriculture and occupation of their spouse
Spouse occupation Distribution of women in agriculture
No Spouse 1
Agriculture 15
Agricultural Labour 0
Others 2
Grand Total 18
Women engaged in other occupation, which includes stone cutters, petty shop keeper,
Anganwadi helpers, cooks in schools, beedi rollers, tailors, domestic helps, teachers in
private schools amongst others. The spouse of women engaged in other occupation was
also more likely to be employed in 'other' occupations like stone cutters, petty shop
keepers, electricians, painter and drivers.
Table 115: Occupation Pattern
Women in Other Occupation and Occupation of their Spouse
Spouse Occupation Distribution ofWomen in 'Other' Occupation
No Spouse 5
Agriculture 5
Agricultural Labour 5
Others 15
Grand Total 30
In case of housewives, the spouses are most likely to be associated with 'other
'occupation, though the respondents might not have recognised their contribution in their
own agricultural fields as an occupation.
242
Table 116: Occupation Pattern
Housewives and Occupation of their Spouse
Spouse Occupation Distribution of Housewives
No Spouse 0
Agriculture 3
Agricultural Labour 1
Others 5
Grand Total 9
The correlation between the occupation of the respondents and their spouses reveal a
strong correlation between respondents whose primary occupation is agriculture and the
spouse also involved in agriculture. It is as high as 0.64 and significant as well. The
respondent who was an agriculture labour was also more likely to have a spouse who
works as an agriculture labour as well. The correlation was not very strong at 0.433 but
was significant. Respondents who were involved in other occupations were also likely to
have a spouse who was also involved in other occupation at 0.322 but it is significant at
0.007. Other significant results from the correlation exercise are a significant but weak
negative correlation betweei1 respondents who were housewives and spouses' involved in
agriculture. It is very much expected because, in most cultivator households, all members
of the family, many a times including children work on farms to reduce the expenses on
hired labour. So a woman whose household is involved in agriculture is least likely to
stay back home as a housewife. There is a significant but weak negative correlation
between respondents involved in agriculture and spouses involved in other occupations.
This negative correlation might be because, these respondents worked only in their own
farms, when their husbands were involved actively in cultivation, otherwise they have no
compelling reason to go and work in farms.
Table 117 : Correlation Results
Correlation
Respondent I Spouse Occupation I Spouse Agriculture I Spouse other
243
Agriculture Labour Occupation
Agriculture 0.641 -0.28 -0.332.
sig 0.000 0.018 0.005
AL -0.221 0.433. 0.1523
Slg 0.066 0.000 0.209
Others -0.356. -0.042 0.322
Slg 0.002 0.727 0.007
Housewife -0.054 -0.074 0.134
sig 0.657 0.544 0.269
* Correlation significant at 0.01 levels, rest significant at the 0.05 level.
This is broadly the occupation pattern of the respondents and their spouses. The
occupation pattern assumes importance because annual income of the household depends
on the occupation of the respondent and the occupation of the spouse.
In the table below, occupation pattern of spouses and the distribution of below poverty
line households are given. Significantly, spouses of the respondents, (therefore
respondents, because of a high cotrelation between the two) who are involved in
agriculture are more likely to belong to a household below poverty line. Eight out of
thirteen agricultural labour households are well below poverty line. That is, over 60% of
the agricultural labour households are well below poverty line. The chance of a
household being under poverty line reduces if the spouse of the respondent is involved in
other occupations. Only about 36% of such households belonged to the below poverty
line class. Nearly 47% of the agricultural households were well below poverty line, i.e.
about 15 of 32 households. Other occupations seem to pay a regular and more reliable
· income stream than agriculture or agriculture labour.
Table 118: Poverty line and Occupation of Spouse
Occupation of Spouse and Income below
poverty line
244
Spouse
Occupation Frequency Percentage
No Spouse 3 8.57
Agriculture 15 42.86
AL 8 22.86
Others 9 25.71
Grand Total 35
Indebtedness and Institutions:
There is strong evidence suggesting that indebtedness is high in the Dodderi region.
Though there were many banks in and around Dodderi, informal sources played a more
dominant role. About 40% of the respondents said they had secured a loan from informal
sources in the preceding one year period. Needless to say they all had borrowed from
their respective groups too.
Table 119: Borrowings from Informal Sources
Borrowed From Informal Sources
Borrowed Frequency Percentage
Yes 28 40
No 42 60
More than 80% of the respondents said they had never interacted with banks before they
joined the Self-help-group. Some said they were apprehensive if the bank officials would
help them. Besides a third of them being illiterate had a problem of documentation and
processing the assorted forms and paperwork that is required to avail facilities of banks.
Only 19 of the respondents had interacted with a bank even before they joined the Self
help-group. Of these only about 15 had actually secured a loa.TJ. from a bank. More than
78% of the respondents had not availed any sort of loan facility from banks. However, of
the little over twenty percent who had secured loans from various banks, a third were
individuals with income below poverty line.
245
Table 120 : Banking in Pre-SBG era
Interacted with bank before
Interacted with back before frequency percent
Yes 19 27.1
No 51 72.9
Borrowed From Banks Before
Borrowed From Banks
Before Frequency Percentage
Yes 15 21.5
No 55 78.5
In terms of social groups who were able to secure loans from banks even before joining
the Self-help-groups, it seems that the marginalised social groups were the most affected.
In fact, more than 70% of those who secured loans from banks belonged to the OBC
groups. Only about 16% were SCs. Only one of the respondents belonged to the ST
group and had managed to secure a loan from the banks.
Table 121: Banking amongst social groups
Banking and Social Groups
Social Groups No of respondents familiar with banking
Others 1(5.6%)
Muslims 0
OBC 14(73.7%)
sc 3(15.8)
ST 1{5.6%)
Grand Total 19
Most of these loans were sanctioned under various welfare programmes promoted by the
State, including IRDP, PMRY, JRY and a few crop loans. The other programmes
supported self employment initiatives like purchasing tailoring machines, petty trade and
246
road-side eatery. There were also few crop loan accounts secured by the hypothecation of
agricultural lands. The interest rate paid for the loan varied between 9% for crop loans to
18% for unsecured loans.
Table 122: Banking and BPL Social Groups
Banking BPL and Social Groups
BPL APL total
Gen 1 1
M 0 0
OBC 7 5 12
sc 0 1 1
ST 1 0 1
Grand Total 9 6 15
When the case of those who were able to secure bank loans before joining Self-help
groups is considered for two criteria of social groups as well as that of BPL, it is noticed
that none of the BPL- SCs got a loan, whereas 7 OBC who were BPL had secured a loan.
There appears to be a problem with respect to accessing formal loans, more so in case of
economically weaker sections and marginalised social groups. At the same time, the
OBCs seem to access bank loans with relative ease. Even the BPL-OBC seems to have
better access to bank loans than their SC-BPL counterparts.
Group Information
There were about seventy groups covered in the survey, all but one were functioning
well. The dysfunctional group was about to be disintegrated because the only literate
member of the group who was the leader of the group and maintained the accounts was
leaving to Bangalore to work in a garment factory. The other members of the group were
illiterate and were not confident of running the group. They also failed to get the help of
Anganwadi staff, since the nearest Anganwadi was far off and the staff there refused to
help the group. However, there were several other groups entirely made up of illiterate
women functioning with the help of the local Anganwadi staff.
247
There were mainly two types of groups, Streeshakti and Swasahaya. The Streeshakti
programme is promoted by the Department of Women and Child Development,
Government of Kamataka. This programme was launched in 2000-01 with an objective
of "empower(ing) rural women and make(ing) them self reliant by inculcating the habit
of saving and proper utilisation of financial resources." 47 Under this programme,
Anganwadi staff organise rural women who come from below poverty line households
into Self-help-groups. The selection criteria also include women from landless agriculture
labour, women belonging to Scheduled Castes and Scheduled Tribes. The government
also contributes a one time revolving fund of Rs 5000 to add to the corpus of each group.
The groups are also eligible for saving-incentives, according to which, group saving
between Rs 75000 and Rs 100000 gets a saving-incentive of Rs 15000 and those who
save more than Rs 100000 get an incentive of Rs 20000. Also, the programme is tied to
various workshops and training in income generating activities. The groups were also
linked to the nearest bank under the NABARD SHG-Bank linkage scheme.
The groups in the field area were linked to more than 5 commercial banks in the nearby
towns (State Bank of Mysore, Madhugiri, Vijaya Bank Madhugiri, Indian Overseas
Bank, Madhugiri, State Bank of Mysore Badavanahalli and Kamataka Bank Madhugiri)
two co-operative banks and one regional rural bank (Kalpatharu Grameena Bank). About
60% of the respondents belonged to Streeshakti groups. Only 40% of the respondents
belonged to Swasahaya groups.
Table 123: Type of Groups
Type of Group
Group type frequency Percentage
Streeshakti 42 60
Swasahaya 28 40
47 GOK http://www .dwcd.kar.nic.in/dwcd _ english/prg_ women.html#streeshakthi
248
'Swasahaya' is a generic term for the Self-help-groups formed by NGOs and individuals
themselves and is heterogeneous in character. There were many NGOs active in the
region including small local NGOs like KIDS, WLARS and, along with well known
NGOs like BASICS ltd. Each group has its own design and structure.
Many groups in the taluk of Madhugiri were enterprising. One of the groups in the village
Hosahalli had pooled in savings and their loan to buy twenty Jersey cows. One group
"Priyadarshini Streeshakti sangha were manufacturing Phenyl and were distributing it
across Anganwadi in Madhugiri taluk. Wax candle making, basket weaving were other
popular activities taken up by the groups in Madhugiri taluk.
6.1.1. Membership and Outreach
Outreach of the programme has been significant. There were over one lakh SHGs all
over Karnataka by the end of 2005. The total loan disbursed by banks to these SHGs was
Rs 49613 lakhs. In the district of Tumkur, the data for the year 2005 is not available. By
2004, there were as many as 6661 groups spread over all the taluks of the district, and the
loan availed by these groups from various banks amounted toRs 138.06lakhs. A further
break up of figures at taluk and Hobli levels is not available. This figure does not include
NGO promoted groups that are not linked to the banks but are financed by the internal
funds and donations received by the NGOs. Since such groups are not regulated by the
State, their actual figures are unavailable.
Table 124: Outreach of SHGs
Breadth of Outreach of SHGs (Rs lakhs)
Kama taka Tumkur
Year No ofSHGs Bank loan NoofSHGs Bank Loan
2003 62178 14401.4 3718 58.36
2004 103866 28361.8 6661 138.06
2005 120000 49613 NA NA
249
Outreach of Microcredit SHGs in terms of absolute numbers makes much less sense than
in terms of percentage of a section of the population. The breadth of outreach refers to the
proportion of population participating in Microcredit programmes. This proportion gives
a more accurate description of the potential of the programme to reach out to a proportion
of population. It is found that in Kamataka, despite the backing of the State, active
involvement of NGOs, banks and NABARD as well as the hype surrounding the
programme, only close to 5% of the total female population of the state are covered under
the microcredit programme. The programme is being promoted as a replacement of the
formal financial institutions. In addition, there is a gradual withdrawal of formal
institutions from the rural financial markets. This means, the formal institutions are being
replaced with a less efficient system that is no where close to the formal institutional
system in terms of scale of operation.
The depth of outreach is calculated as the proportion of poor population that is covered
under the programme. The larger the proportion of poor included in the programme the
larger will be the outreach. In Karnataka, a crude depth of outreach is calculated using the
available data. Since no specific break up of macro level data for the number of below
poverty line women participating in the programme is available, the total number of
women in the programme is considered to calculate the depth of outreach. Therefore the
actual depth of outreach will be significantly smaller than that presented here. The dept of
outreach was just about 23.65%. That means a large population of below poverty line
women are effectively left out of the programme.
In terms of the social groups, there is no break of data on social groups of members,
therefore the estimate presented here is a crude percentage based to total number of
women participating rather than taking into account just those being to the particular
social group. The actual data will therefore be significantly lower. Accordingly, the
percentage of SC and ST women covered under the programme is much less that 53%
and 59% respectively. A large proportion of the women being to marginalised social
groups will find themselves excluded by both microcredit programmes as well as the
formal institutions.
250
Table 125: Depth of Outreach
Outreach of Microcredit SHGs in Kamataka
Population SHG members as a % of population
SCwomen 3362601 52.93
STwomen 3012737 59.08
BPL (rural) 7525400 23.65
Total Female population 37551895 4.74
The information on outreach in Dodderi has to be extracted from the field study. The
following section presents a study on the membership and outreach of the programme.
The number of members in each group varied widely between ten and twenty. 31 groups
consisted of 20 members followed by 15 groups with fifteen members. There were six
groups with seventeen members, five groups with eighteen members. There were also
three groups with twelve members, two with fourteen members and one group each with
ten, eleven, thirteen and nineteen members. This difference in membership is noticeable
given the incentives for having a larger group in terms of savings and the associated
saving-incentive for the Streeshakti groups. Though ideally Streeshakti groups should
consist of twenty members, the rule is at times not enforced because of absence of
potential members fulfilling the eligibility criteria. Many women were reluctant to join
the groups because they were not sure about their ability to meet the mandatory weekly
saving. In one instance, a woman could not join the group despite her desire because her
husband did not want her to.
Table 126: Group membership
Number of Members in the group
No of members in the group Frequency
10 1
11 1
251
12 3
13 1
14 2
15 15
16 4
17 6
18 5
19 1
20 31
It was also noticed that only half the respondents actually met the below poverty line
criteria48 even when 60% of the respondents were affiliated to Streeshakti, a programme
which has been exclusively designed to reach out to those below poverty line along with
other weaker sections of the society. In fact, less than 43% of the Streeshakti members
were below poverty line. In all possibility the programme is getting diluted at the level of
implementation.
Table 127: Programme Outreach
Programme Outreach
Streeshakti 42.80%
All programmes 50%
Also, others eligible to form Streeshakti groups are landless agricultural labour and those
belonging to socially marginalised groups. Landless agricultural labours were well
represented in the groups. More than 46% of the respondents were landless agricultural
labour, half of which belonged to the below poverty line class. In fact, poverty appears
48 Poverty line of per capita annual income ofRs 5007 was considered, based on the planning commission's 1999-00 definition ofRs 362. 68 per head per month, inflated for the year 2006 arriving at Rs 417 per head per month.
252
more severe in case of marginal land holders. As much as 62.5% of the total marginal
farmers in the sample were found to be well below the poverty line. 40% of the small
framers represented in the sample were also below poverty line. Only a handful of
medium large farmers were beyond the poverty line. There were almost 30 landless
agricultural labours in the sample, there were 24 marginal farmers, which is almost 35%,
and there were about 12 respondents who were small farmers, i.e. about 17%. Landless
agricultural labours and marginal farmers are thus well represented.
Table 128: Landholdings and poverty
Landholdings and Poverty
Landholdings Below Poverty Line Total percentage
AL 15 30 50
Marginal Farmer 15 24 62.5
Small Fanner 5 12 41.67
Medium Large Farmer 0 4 0
In terms of asset holding class and social groups that are actively participating in the
Microcredit programme, respondents belonging to Other Backward Castes constituted the
most dominating participants in terms of numbers. Amongst the landless agricultural
labours participating in microcredit programmes, the OBCs constituted over 17%,
followed by SCs at 12.86%. The STs were close behind at little less than 8%.
Amongst the marginal farmers, OBCs constituted a little over 27%, SCs and STs were at
a distant 3%. This means, the participation rate of SCs decrease when their asset holding
improves. On the other hand, participation of OBCs improves from close to 17% to over
27.14%.
Table 129: Social Groups and Poverty Line
Social Groups and BPL (%)
Category Agriculture Labour Marginal Farmers Small Farmers
Gen 1.43 1.43 0
253
M 4.29 0 0
OBC 17.14 27.14 17.14
sc 12.86 2.86 0
ST 7.14 2.86 0
Grand Total 42.86 34.29 17.14
Literacy:
Literacy appears to be a strong variable affecting the participation of women in
microcredit programmes. The pattern corroborates Sen (2000), wherein an increase in
social opportunities is expected to facilitate economic participation (Sen, Amarthya
2000). It is noted that only 24% of the total female population was literate in the Dodderi
llobli. But about 67% of the group members/respondents were found to be literates. More
than 37% had been to high school alone. Illiteracy seems to be a positively affecting non
participation. There are two possible factors working for the non-participation of illiterate
women. One could be the confidence and the support of family members, which is very
crucial. A literate woman is more likely to find it easy to convince her family about her
ability to handle money than an illiterate woman. Secon~ factor is possible exclusion of
such members during the formation of the group. Since groups rely on self-selection,
there is a strong possibility that members perceived as weak are excluded from groups.
The preference till now is in favour of literate clients. With the increase in outreach there
is a chance that more illiterate women will join microcredit groups.
6.1.2. Cost of Credit
The cost of credit has two components to it. One is the interest rate, the cost incurred on
the loan, the other being transaction costs49• (Swaminathan 2007, Adams and Nehman
49 Adams and Nehman ( 1979) also consider the costs incurred on commission, bribes paid out to middlemen negotiating the loan along with the cost incurred due to change in inflation. Those costs are ignored
254
(1979).Each group had a different repayment structure and varying interest rate on
internal lending and bank loan. In few groups, the internal loans i.e. loans lent out of the
pooled weekly savings were lent to members at a higher rate of interest than bank loans.
The interest rates varied between 12% and 36%. Over 45% of the loans carried an
interest rate of 24% per annum. Close to 13% of the loans carried an interest rate of 36%
per annum. About a third of the loans carried an interest rate of 18% per annum. This
kind of high interest rate is rather regressive when a regional rural bank operating in the
vicinity offers loans at a lower rate of9% or at a maximum of 12%.
Table 130: Interest rate pattern
Interest rate pattern
Interest rate (%) frequency percentage
15 7 10
18 21 30
24 32 45.7
36 9 12.89
Repayment designs also varied between groups. In a few groups there were no deadlines
on the repayment of internal loans as long as the interest was paid regularly. In a few
groups even internal loans were for a period of either ten or twelve months.
Most of the groups were linked to banks and they had current loans in those branches.
There was considerable flexibility on bank loans as well. The groups were at liberty to
make a choice between monthly instalments or make a one shot payment at the end of the
loan term. Bank loans were given for a period of ten months. They generally charged one
percentage point below the Prime lending rate, which at the time of field survey was
13%. Hence, the groups were getting loans at the rate of 12%. However, the groups
charged over and above this for their on lending.
In Streeshakti groups, the differential interest accrued on the on-lent loans are again
pooled and divided amongst the members themselves. In a few groups, respondents were
of the opinion that such a practice was more or less like a saving where they pay higher 255
interest rate only to increase their own savings. Higher interest rates are justified in such
cases. But in the Swasahaya groups, more so groups promoted and run by NGOs and
other organisations, the interest differential is retained by the organiser/promoter as a
charge for their service. 7.14% of the Swasahaya groups charges 12% per annum. Most
of these groups were community initiatives rather than promoted by NGOs and other
organisations. More than half of these groups charged an interest rate of 24%. More than
10% of the groups also charged an interest rate of 36%. In case of Streeshakti groups,
35% of the groups charged an interest rate of 15% but more than 42% of the groups
charged 24% and 11.9% of the groups charged 36% interest rate. High interest rate is not
justified especially in case of Swasahaya groups because there are alternative channels
where they can definitely access cheaper loan facilities. They are being charged for no
apparent reason. This phenomenon is actually weaker in the region where the field work
was conducted. Large scale commercial operation is not extensive in this region.
However, in the slums of Bangalore, there are NGOs engaged in promotion of groups and
linking them to Banks. Those NGOs were charging 36% for the loans they secured from
banks at 12%. One such NGO operating in the slums of II Phase, J.P.Nagar Bangalore
Karnataka did not entertain a request from the author to meet their clients or group
operations. In fact, their clients were issued a warning not to talk to the author. Later
however it was found out that their operations were opaque. Not only did they charge
36% on their loans but also imposed penalties by the day for every day of delay in
deposition of the monthly instalment. They also threatened to confiscate kitchen utensils,
radios, TV and other possessions of the borrowers in case of delay in repayment. Such
cases are not isolated but are widely prevalent (Hulme 2000).
Table 131: Interest rates among Groups
Pattern of Interest rate among groups
Rate of Interest (%) Swasahaya % Streeshakti %
12 2 7.14 1 2.4
15 2 7.14 2 4.8
18 6 21.43 15 35.1
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24 15 53.57 18 42.9
36 3 10.71 5 11.9
Transaction Costs:
Transaction costs include costs incurred on documentation, travelling and the opportunity
cost incurred on every visit to the lender to secure a loan. In case of Microcredit groups,
the transaction costs are low. The group operations are generally localised, not much is
spent on travelling. In case of groups that are linked to banks, chosen members acting as
representatives travel to the bank and deposit their weekly collection and instalments.
The transportation charges are borne by the group. Group members also take turns to
travel to the bank. The transportation cost was zero in case of groups in the villages close
to the branch. In fact, as many as 15 groups out the 70 covered in the study were at a
walk able distance from the banks. Transaction cost was as high as Rs 24 per person on a
round trip from the farthest village Basavanahalli. For the other villages it varied
between Rs 10 and Rs 24. Another important component of the cost incurred on
documentation. Individuals applying for loans in commercial banks are required to
provide many documents along with their loan application. The documents include a no
due certificate from two commercial banks and two co-operative banks operating in the
surrounding area, an encumbrance certificate and property papers (in case of crop loans).
The commercial banks as well as the co-operative banks charge some money to provide
the no due certificate, even if the applicant has never had any relationship with the banks
before. The encumbrance certificate also costs money, along with the regular fees, the
officials at the sub-registrars' office demand bribes as well. Also, opening an account
requires an initial deposit of Rs 300 as the minimum balance. So this component of
transaction cost is therefore very high in case of individual loans. The documentation has
been simplified in case of loans to Self-help-groups. They need to open an account and
maintain the minimum balance and they are not required to provide any other documents
or no-due certificates.
Apart from these costs, there is the opportunity cost of visiting banks. The opportunity
cost could be in terms of the hours of labour lost because of the visit to the bank. In case
257
of group loans, procedures have been simplified and representatives are required to travel
to banks far fewer times than to negotiate individual loans. Group loans are faster
because the documentation required is simpler. Therefore, opportunity cost is also lesser
than individual loans. Besides, all the members of the group will not be going to the
bank unless the loan has been sanctioned and their signatures are required. So collective
number of days' labour lost because of bank visits is far less compared to individual
loans.
6.1.3. Income Generation
Microcredit has been often called Micro-enterprise loan as well as ''penny capitalism"
(Hulme and Mosley 1998). One of the objectives of the Streeshakti programme in
Kamataka is "to create self confidence in rural women by involving them in income
generating activities thereby contributing to poverty alleviation."50 Microcredit is seen as
a tool that can provide women a chance to indulge in small income generating activities
and thereby make a dent on poverty. This approach also justifies the high interest rate
charged by groups on their loans. However, group members also need money to finance
their non-income generating activities like consumption, meeting unexpected expenditure
and repayment of old debt. Lending to groups and charging them a higher rate only to
finance non-income generating activities portends trouble in long term. There could as
well be a Microdebt-trap in the making. It is therefore imperative to check the pattern of
loan usage and the possible pitfalls.
In Dodderi Hobli, it was found that, a fifth of the respondents had used their loans on
consumption. This included meeting household expenses, health related expenditure
(During field work as well as a few months preceding the field work, Madhugiri taluk
and Tumkur district suffered a large scale break out of Chikkungunya epidemic. Because
of which a large number of loans were spent on health related problems), ceremonial
50 GOK http://www.dwcd.kar.nic.in/dwcd _ english/prg_ women.html#streeshakthi
258
expenditures and children's education. More than a fifth of the respondents also had spent
their loans on agriculture related expenditure; mostly including current expenditure like
hiring labour, seeds and manure. Microcredit loans were insufficient to undertake capital
expenditure.
About 14.3% of the respondents had invested their loans on petty trade, including petty
shops, florists, incense making/selling, small tea shops and road side eateries. More than
18% of respondents had invested their loans on animal husbandry. Milch animals were
popular in the region because of the vibrant co-operative milk unions. There were as
many as 17 milk collection centres in the Hobli and average distance to the nearest milk
collection centre was less than a kilometre. The average milk production was about 10
litres per day. Infact milk production else where in Madhugiri taluk was high, and the
taluk average was about 33 litres per day, which is higher than the District average of 26
litres. However, average distance to the nearest milk collection centre was moi"~ than 5
kilometres and average production of milk of Kamataka was far higher at 98 litres per
day.
Goats were also popular among those who got smaller loans. Goats were seen as hardy
animals. Goats also grow up fast and gestation period is also short at about 5 months.
Kidding is mostly uncomplicated and does not require the service of veterinarians.
Besides, goats do not need special feeds, most of the time they graze all by themselves.
Because of its low maintenance cost, goats happen to be popular. Goats sold for meats
also fetch handsome returns. Over 24% of the respondents had spent their loans on other
activities like building/repairing their dwellings, re-lent it at a higher rate of interest, used
the loan to purchase gold ornaments.
Table 132: Investment Pattern of Borrowers
Investment Pattern of Borrowers
Type frequency percentage
Animal husbandry 13 18.6
Agriculture 16 22.8
259
Consumption 14 20
Petty trade & other trade 10 14.3
Others 17 24.3
It becomes evident that a large proportion of the respondents will not be able to repay
their loans from the proceedings of their investments. A few people have managed to
generate more income than the rest. More than 25% of the respondents had failed to
generate any income. More than 20% had managed to generate an income of less than Rs
2000. Therefore, half the respondents are in the danger of getting in to a debt trap. Not
only have they failed to generate enough income, they also end up paying high rate of
interests. In such a scenario, factors influencing the generation of income assume
importance.
A simple muitiple regression model is used to test the factors affecting income generation
amongst the respondents. The regression is given as
Many variables were checked for their influence on the dependent variable i.e. income
generated using the loan. They were age, caste of the respondent, occupation of the
respondent, occupation of the spouse of the respondent, project on which the loan was
invest, loan in terms of money, asset holding of the respondent's family including
irrigated land, dry land, cattle heads, type of group and marital status of the respondent. A
stepwise regression was used to select a model with the highest possible r2• Separate
dummies were created in case of caste of respondent according to social groups of SC,
ST, OBC, Muslim and General. Another set of dummies was created to separate the
effects of main occupation of the respondents including agriculture, agricultural labour,
petty trade, others and housewife. Dummies were created for the occupation of the
spouse, including agriculture, agricultural labour, trade and others. Investment pattern
dummy was created to separate the effects on investments on agriculture, trade, animal
husbandry and consumption. Interaction dummy for similar occupation between the
260
respondent and the spouse were created but did not strengthen the model any further.
Therefore those dummies were abandoned. A stepwise multiple regression was run on the
variables and the strongest model was retained as the fmal model. The final model
included quantum of loan, caste of the respondent, marital status and pattern of
investment.
The~ of the model was 0.621 and the adjusted ~ was 0.571. The model summary is
given below. The regression was greater than the residual.
Table 133: Model Summary
Model Sum of Squares df Mean Square F sig
Regression 9.975 8 1.247 12.475 .000
Residual 6.097 61 0.001
Total 16.071 69
The betas are given in the table below.
Table 134: Regression Coefficients
Unstandardized Coefficients Standardized Coefficients
B Std Error Beta t sig
Constant -0.00372 0.123 -0.3 0.976
Loan qua 0.000016 0.00 0.167 2.032 0.046
Stdum 0.158 0.128 0.99 1.23 0.223
maritdum -0.149 0.114 -0.19 -1.303 0.197
Occothers 0.136 0.95 0.122 1.436 0.156
Dairy dum 0.998 0.129 0.81 7.751 0.000
Agridum 0.786 0.117 0.689 6.729 0.000
Tradedum 1 0.138 0.73 7.268 0.000
Otherdum 0.569 0.119 0.509 4.779 0.000
Loanqua =quantum of loan
261
Stdum = Dummy variable representing respondents belonging to the social group of ST
(stdum= 1 when respondent is a ST)
Maritdum= Dummy variable for the marital status of respondents (maritdum= 1 for
married respondents)
Occothers = interaction dummy between respondents who were listed under 'other'
occupation and spouses under similar occupation category
Dairydum= dummy variable for investment on milch animals
Agridum= dummy variable for investment on agriculture
Tradedum= dummy variable for investment on trade (petty shops, flower, tea stalls)
Otherdum= dummy variable for investment on other projects like beedi rolling, incense
rolling, buying autorikshaws, tailoring machine etc
Therefore the regression equation becomes
Income generated = -0.00372+ (0.00016) Loanqua+ (0.0998) Dairy-dum + (0.786)
Agridum +Tradedum+ (0.569) Otherdum
Quantum of Loans: (Loanqua) The variable was found to have a positive effect on the
potential to generate income on loans~ The effect was very weak but is significant. For
every unit (Rupees) increase in the loan quantity, only 0.00016 units (Rupees) of income
were generated, other things remaining the same. This seems to indicate the potential to
generate significant income regardless of the size of the loans. Intuitively, a larger loan
should enable the borrower a much wider choice of projects to be undertaken and
therefore will have a positive effect. When the quantum of loan is small, the range of
choices narrows down to resource constraint. The narrowed choices represent the second
best alternative; therefore, the returns on such activities will be lower. When loans are
larger, the borrower will be able to choose the best option and invest accordingly.
Investment in milch animal: (Dairydum) Loans used to finance milch animals were found
to impact income generation positively. For every increase in the investment over milch
animals, there was an increase in the income generation by over 98%, other things
remaining the same. Investment over milch animals was profitable because of a robust
262
milk union in the region. The average distance to milk collection centres was just about
one kilometre. Though the gestation period for cows and buffalos are long (9-llmonths)
but the onset of lactation period is very remunerative. Often, the cost incurred on
maintaining, feeding the cattle is also very low. This factor also makes investment on
milch animals attractive.
Investment in Agriculture: (Agridum) Loans when used to invest on cultivation was
found to have a positive effect on income generation. According to the regression
coefficient, for every increase in agricultural investments, the probability of increase in
income was about 78%, other things remaining the same. Most of the loans were in the
form of current expenditure on farms. Loans were spent on hiring labour, manure, seeds,
raising flowerbed and vegetable patches. Flower beds and vegetable patches have a short
gestation period and income starts trickling down well before the end of the loan term.
However, crops with longer gestation period like cereals and oil seeds could prove to be a
gamble. In case of failure the borrowers will be hit very hard.
Investment in Trade: (Tradedum) Investment in trade related activities seems to have a
positive effect on generation of income. This variable is the most importance because the
success ratio of investment in trade is 100%. For every increase in trade related
investments, the increase in income generation was 100%, other things remaining the
same. In case of trade, the gestation period is very short. In fact, there will be immediate
returns. The extent of returns depends on various factors, the location of the shop/hawker,
season, presence (absence) of competition. The dummy trade includes florists, hawkers,
petty shop owners and tea stalls. Initial capital requirement is flexible in these activities,
ranging from just a few hundred rupees to several thousands.
Investment on other projects: (Otherdum) This variable includes beedi rolling, incense
making, purchasing of small transport vehicles and money lending. Investment of loans
on such activities is found to have a positive impact on the generation of income. For
every increase in investment in such activity, the probability of an increase in income is
by only about 56%, other things remaining the same. Unlike petty trade, activities like
263
beedi rolling, incense making, tailoring had a low profit margin. In case of both Beedi
rolling and incense making, the commission was very low, besides, the contract excludes
them from marketing the products.
Other variables in the table were not found to be insignificant. It is implicit that when
loans are used for consumption activities, no income is generated.
Therefore income generation is not affected by caste, annual income, asset holding of the
household (land, cattle) and occupation of the borrower or that of the spouse of the
borrowers. Variables like education and age were found to be uninfluential in the model.
What affects the generation of income is the pattern of investment alone along with the
quantum of loans. When borrowers spend their loans on any other activity apart from
consumption, they stand a better chance of generating income, what ever social group,
asset holding class, annual income class they belong to. All others variables are not found
to affect the ability of the borrowers to generate income. However the ability of the
individuals to make the maximum possible use of the loan and their entrepreneurial
capabilities also affect the generation of income which remains unexplained by the
model. The variation in the generation of income amongst borrowers operating under
similar conditions can be only attributed to the individual's entrepreneurial capabilities.
Some borrowers inherently make good business decisions while the others fail.
The three parameters of outreach and membership cost of credit and generation evaluated
the impact of Microcredit programmes on the borrowers. The study shows that on the
outreach front, Microcredit programmes have a lot to be desired. A significant proportion
of deserving population is excluded from the programme. Even though there are strict
eligibility criteria in the State backed Microcredit programmes, implementation is often
found to be diluted. None of the target groups (below poverty line, marginal social
groups or agricultural labours) have unconstrained access to these programmes.
The loans offered under such programmes are needlessly expensive. More so the NGO
run programmes where, the interest rates are exorbitant and the differential is pocketed by
the NGO as a service fee is pathological. The symptom might not be manifest
264
immediately, but in due course of time it will manifest in terms of micro-debt trap. The
high rates in conjunction with a failure to invest the loan on a project with high returns
will definitely become problematic in due course. Income generation itself is affected by
the pattern of investment and the quantity of loan. Also individual abilities and
entrepreneurial capabilities affect income generation. Therefore, these factors should be
considered before promoting a programme like Microcredit as an alternate livelihood
provider. Three more parameters are used to evaluate the impact of such programmes, viz
repayments, profitability and sustainability.
6.1.4. Repayments
Repayments in Microcredit groups have been very high irrespective of country and credit
design. Grameena bank has recorded a repayment of over 98.45%.51 It is as high as 97%
in ACCION's Latin American Microcredit programmes.52 In India SEWA bank has
recorded repayment rates of over 90% consistently over the past decades.
The groups included in the field study are no exception. All the groups in the sample
were repaying their instalments promptly. The only group that was being disbapded has
completed the last instalment of its latest loan from a bank. Most often then not, groups
were very prompt in repayments. Continued access to larger loans acted as an incentive
for borrowers to repay on time. No other factor appears to have a singular influence on
the repayments. Members belonging to different social groups have similar repayment
rates, as well as members belonging to different asset holding classes or members of
different annual income class. No other factor can be singularly held responsible for the
very high rate of repayments except for the design features like peer pressure, social
sanctions and dynamic incentives all acting in conjunction.
During the field study it was noticed that peer pressure worked positively on repayment.
Members were deterred from defaulting because of strong peer pressure as well as fear of
51 Grameen Bank URL http://www.grameen-info.org/bank/bank2.html 52 http://www .accion.org/about_ our_ history. asp
265
sanctions. In one case, one of the borrowers had failed to pay up her monthly instalment
for a group loan sanctioned by a commercial bank; two other members of the group
promptly took her to task forcing her to pay up. The banks generally do not bother about
repayments in case of group loans. The officials are certain that the loans will be paid up.
The recovery of loans is more or less outsourced to the group members themselves. The
whole group will loose further access to loans in case of default by one of the members.
Self-interest drives group members to force the defaulting members to repay at any cost.
The case of NGO sponsored groups can be much violent than the State promoted loans.
The NGO charge a higher rate of interest and also are know to pressurise borrowers.
There are penalty clauses in the debt contracts and a day's delay will carry a penal
interest. Because of the obvious costs, borrowers are forced to repay the loan on time.
However there are studies pointing out that any problem in the Microcredit market is
slow to develop and problems of repayment and debt trap like situation takes time to
develop. Also, improving social and economic conditions of the borrowers because of
repeated borrowings from Microcredit agencies, might lead to a weakening of social
sanctions, thereby affecting the ability of the groups to force defaulting members to
repay. (Yaqub, Shahin 2003) In Kamataka, Microcredit programme is young and
repayment problems are yet to start. The potential problem lies in the multiple
memberships in group in the region. Though there is specific guidelines discouraging
multiple membership (a single individual becoming a member of more than one group), it
is widely prevalent. Many people apply for multiple memberships because they will be
able to get a larger loan. But such people are dangerous to the health of the whole group.
There is a possibility that they borrow from more than one group and find it difficult to
repay both the loans endangering all the groups involved. This problem will intensify
with increasing multiple membership and further access to larger loans.
6.1.5. Profitability
There are various credit designs and model currently popular in India. Broadly there are
two types of designs in terms of lender. In one of the two models, banks directly lend to
the groups and groups are at liberty to distribute the loan amongst their members. In the
266
other design, NGOs lend to the group. They themselves could be lending their own
money or a bank could have given a loan to the NGO. In both cases, lending to groups
has proved profitable, at least for the time being.
In case of banks, the repayments are prompt. Group lending can be declared as priority
sector lending. The banks not only meet their priority sector targets but also will not have
to worry about defaults and the banks charge around 12% on their loans. Just one
percentage point below the prime lending rate. So the returns are attractive.
In case of NGOs, the margin of profit varies with the interest charged on loans and the
cost they incur on screening, monitoring and operating the groups. NGOs do incur
substantial costs in promoting and operating groups. But, they do charge a hefty interest
for their loans. They typically charge two to three times more than the bank. The margin
is retained by them as a service fee. Though profit is not expected to be the primary
objective ofNGOs, they do end up with profits. In fact, there are NGOs who publish their
annual balance sheet with profits as well. 53
6.1.6. Sustainability
The sustainability of the programme is a measure of the longevity of the programme. For
now the programme appeared to be well-oiled and smooth. Sustainability examines the
health of the programme in years to come.
In Dodderi region, there is a positive response to Microcredit programmes as of now. The
borrowers have one more channel of credit. The programme is still in its infancy, groups
have had two to three credit cycles. None of the groups had crossed three credit cycles.
The loans have been small sized, rarely have they been medium sized. The average loan
size is little less than Rs 5000. Less than 5% of the respondents had been sanctioned a
loan of more over and above Rs 20000. There has not been any prominent problem of
repayments because the loans are smaller, and the instalments are therefore small.
53 Organisations like BASIX publish balance sheet at regular intervals. It is available at http://www .basixindia.com!BASICS%20Ltd%20Financials%20%20March%202007 .pdf
267
However, groups are eligible for larger loans once they repay their current loan. All
members will have to borrow the money regardless of their preference. Once groups
graduate to larger loans, maintaining a high repayment rate could be problematic. Two
potential factors might have an impact on the repayments and the profitability of the
programme.
Income generation: The ability of the borrowers to invest the loans on productive
activities and generate income assumes importance. Microcredit programmes typically
offer short term but expensive loans. In fact, their interest rates are comparable to that of
money lenders. Borrowers will have to choose activities that have short gestation period.
Any other choice will prove burdensome. Besides, if these loans are used for
consumption, the borrower will have to make provision to repay the loan by mobilising
other resources.
Microcredit appears to be convenient because they are timely, members can access loans
in times of need. But borrowers need to be very careful how they make use of the loans.
Now that the loans are still small, there are no major issues with repayments but as
groups go for larger loans, repayment as well as the ability to generate income in short
periods of time will assume importance.
Multiple memberships: Another factor that will affect a sustainability of the Microcredit
programmes are the issue of multiple membership. Multiple memberships are not yet
widely prevalent, but it is gaining ground. Multiple memberships refer to a single person
becoming a member in two or more groups. Initially there will not be any problem with
multiple memberships because of smaller loan size. But after reaching a critical size,
repaying multiple medium/large loans will prove to be burdensome. The situation then
will be no different from the prevailing situation in Vidharb, North Kamataka or Andhra
Pradesh. Before perpetuating groups, these issues need to be weighed carefully.
Apart from these factors there are also institutional factors. How long can the peer
pressure work? How long can social sanctions deter borrowers from defaults? There are
no definite answers. Sickness amongst older groups is not uncommon elsewhere. (Y aqub,
Shahin 2003)
268
In short, from the lenders' point of view Microcredit programmes have been a success.
The repayments are high and the return on loans is good. If the current repayments are
maintained, there should be no problem for the lender to continue their operation.
However, recent developments calls for caution, because of reckless target oriented
approach to increase Microcredit might lead to dilution of eligibility conditions. It is
already reflected in multiple memberships, it might not too long for the default rates to
increase.
6.2. Comparative Assessment of Microcredit and Regional Rural Banks
6.2.1. Depth and breadth of Outreach
The primary justification for today's expanding Microcredit programmes world wide is
the programme's supposed ability to reach out to the poorest of the poor ( Fernando
2004). According to the neo-classicist the major advantage of informal credit markets is
the absence of rationing that is strongly present in the formal markets. This claim is
empirical verified by measuring the outreach of the programmes. Outreach ofMicrocredit
self-help-groups and RRBs have already been studied in the previous sections. The
outreach of the Microcredit self-help-groups was found to be skewed in favour of OBCs,
despite stringent eligibility conditions, a large percentage of population were well above
poverty line. In case of RRBs, the outreach was better with a greater participation of
weaker social groups of Scheduled Castes at 24.5% as against 17% in self-help-groups.
The breadth of outreach of RRBs in terms of social group is stronger when compared to
the proportion of SCs in total population of the region. As against the outreach of RRB at
24.5%, the proportion of SCs in the total population ofDodderi was only 18%. In terms
of asset class, close to 46% of the small borrowers were landless agriculture labours and
more than 43% were marginal farmers. However the depth of outreach (borrowers as a
percentage of below poverty line population) of Microcredit self-help-groups is stronger
at 5.49% than 4.34%. When all the small borrowal accounts in rural branches are taken as
269
a proxy for all commercial bank (including RRBs) lending to the poor, the depth of
outreach shoots up to 9.54%. It is obvious that all commercial bank small borrowal
accounts will not be owned exclusively by the poor, but also by non-poor. The actual
figure will be some where lower than 9.54%. The number is big enough to be corrected
for the non-poor small borrowers and still be significant vis-a-vis RRBs and Microcredit
self-help-groups. The strong outreach of all commercial banks is because of the sheer
expanse of banking network. Also, the depth of outreach of commercial banks assumes
significance in the light of reducing number of branches in the rural areas and a steady
decline in small borrowal accounts. If there is an impetus in the right direction,
commercial banks might as well prove to be the best possible rural credit delivery
vehicle.
IRDP despite all its drawbacks is another programme which is strikingly robust in terms
of outreach (Swaminathan2007, Swaminathan). A study by Madhura Swaminathan
indicates that 27% of the beneficiaries were women and 42% of the beneficiaries
belonged to marginalised social groups. With a robust outreach, IRDP has set high
standards that informal programmes might never be able to match.
Table 135: Comparison of Outreach of various Programmes
Outreach of Rural Credit Programmes
Grameen BancoSol BRl SEWA
Poverty rate % 50 63 18 29
Population (m) 144.4 9.2 224 1048.3
Absolute Poverty (m) 72.2 5.8 40.32 304
Breadth of outreach (m) 7.24 0.062 0.38 0.3
depth of outreach % 10.03 1.07 0.94 0.10
%of Female clients 97.5 100
%Landless
%SC+ST NA NA NA
(m) Millions$ All India# Madhura Swaminathan 1990
* 2002 **2004 *** source: field study
270
RRB SHGs) All SCBs)
29 29 29
1048.3 1048.3 1048.3
304 304 304
13.195 16.7 29.068
4.34 5.49 9.54
21.4 z100 13.8
43 41.4
24.5+3.4 17+10
IRDP"
29
1048.3
304
20
6.58
27
37.6
42
Among the international rural credit delivery vehicles, outreach varies widely. Grameen
Bank has a widespread outreach. The bank is servicing more than 7 million borrowers
currently, and the depth of outreach is about 10.03%, i.e. the bank is serving more than
10% of the poor population of the country. Despite being the best performer in terms of
outreach of all the Institutions studied here, Grameen Bank fails to impress because of the
tall talks of Microcredit and poverty alleviation. For an institution that was awarded
Nobel peace prize, the outreach is pale given that Indian commercial banks are close
behind without any pretension of trying to alleviate poverty. In Bolivia, BancoSol reaches
out to a little over 1% of the poor population. Considering the fact the Bolivia is plagued
by high urban poverty, outreach could have been much better. But BancoSol too fails to
match the outreach of a State backed programme like IRDP or Indian commercial banks.
The Indonesian BRI also has an outreach of less than 1%. It is also very popular among
donors along with Grameen and BancoSol. But it manages to reach only 1% of the total
poor population of the country. Comparing the outreach of SEW A with other Institutions
operating at the national levels is expecting rather too much from a very locally operated
Institution. It does reach out to about 0.1% of the poor population in India.
6.2.2. Cost of Credit
The cost of credit from various sources is different because of difference in interest
charged, transaction costs incurred on the loan and the transportation costs to travel to the
lender's premises. This section attempts to compare the cost of credit in various
institutions.
First the cost of credit from a RRB, SHG and moneylender is calculated for a
hypothetical loan. The loan size considered in this example is Rs 16000 since that is the
average size of a RRB loan. A fifteen member SHG is considered and the transaction
costs and transportation costs are based on the number of members of the group. The
transaction cost incurred by the group on opening an account with a bank is shared by all
the members. So are the transportation costs. If Rs 300 is the minimum balance in the
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account opened in a bank, it will work out to be Rs 20 per head. Also interest rate
charged by SHG is assumed to be 24% because majority of the group in the region were
charging a similar rate of interest. The case is based on the data derived from the field
study. The RRB in the case represents D Kymara branch of KGB. Money lender's from
the same region is considered. And the interest rate charged by the money lender is also
an average of interest rates charged by the money lenders in the region, the data for
which was collected during the field work.
In this case it is found out that despite the high transaction and transportation costs, RRB
loan works out cheaper than loans from SHGs and money lenders. Money lenders remain
the most expensive option. For a loan of Rs 16000, the money lender will charge an
interest ofRs 5760 per annum, where as SHGs charging interest ofRs 3840 at the rate of
24% per annum. RRB had two different slabs of interest rates. At the rate of 12% per
annum the interest charges was about Rs 1920 and at the rate of 9%, the interest charged
is about Rs 1440. Therefore the total amount payable is Rs 18685 and Rs 18205 for RRB
charging a rate of 12 and 9% respectively. The total amount payable is Rs 20150 for the
SHG and Rs 21760 for the money lender.
Table 136: Cost of Credit a Hypothetical case
Loans and cost incurred on a average RRB loan
RRB SHG (15) Money Lender
Principle 16000 16000 16000 16000
Interest Rates 12% 9% 24% 36%
Transaction Cost 690 690 20 0
Transportation cost 75 75 10 0
Interest to be paid per annum 1920 1440 3840 5760
Total Loan to be repaid 18685 18205 19870 21760
In case the principle considered is the smaller and of the size an average SHG loan, then
the results slightly vary. RRB loan at the rate of 9% will still be the cheapest at Rs 6215
payable on a loan of Rs 5000 at the end of one year. But at the rate of 12%, the RRB
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loans would be more expensive than the SHG loans. SHG loans will be cheaper than a
loan from the moneylender at Rs 6230 and Rs 6800 respectively.
Table 137: Cost of an average SHG loan
Loans and cost incurred on an average SHG loan
RRB SHG (15) Money Lender
Principle 5000 5000 5000 5000
Interest Rates 12% 9% 24% 36%
Transaction Cost 600 450 1200 1800
Transportation cost 690 690 20 0
Interest to be paid per annum 75 75 10 0
Total Loan to be repaid 6365 6215 6230 6800
1n case of international examples, the cost of credit varied between a high of 32% for BRI
and about 8% for Grameen banlc Calculating transaction cost for each of these examples
is not possible given the limitation of the data and the international nature of the
examples. Therefore effort is made to include transaction costs incurred by borrowers in
these institutions as calculated in other studies.
BRI in Indonesia started out like Indian RRBs; it was a State owned bank and credit was
targeted and subsidised. In the period before liberalisation of Indonesian economy in
19&3, the bank charged 12% on their loans but to pay 15% on deposits. However, after
19&3; BRI was deregulated and since then it has been charging market rate of interest and
is therefore profitable.
Table 138: Comparison of Cost of Credit
Cost of Credit
Interest rates Transaction Costs Total costs
Grameen 8% to 20%
Banco Sol 22%
273
BRI 32%
SEWA 14.5% to 17%
RRB 9 to 12% Rs690
SHG 15 to 36%
* Source Field work
6.2.3. Income Generation
Most of the international rural credit vehicles were mostly concentrating on income
generating activities. The risk of default on loans is very high for these institutions not
only because more of the borrowers belong to vulnerable section, but also because the
loans are unsecured. Because of this increased risk, the credit design relies heavily on
short gestation, revenue generating projects. For obvious reasons the credit design cannot
finance non-income generating expenses. Thus, it was the mandate of institutions like
BRI and BancoSol to lend to clients who are already involved in income generating
activities. Especially BRI's Kupedes loan excludes start ups because of the perceived
high risk in such ventures. Grameen bank is an exception. The bank has loans for
building/renovating houses as well as education and such activities.
In India, many SHGs have the autonomy to decide on the quantity, purpose, pricing and
repayment policy of the group. There is scope to finance consumption and other non
income generating activities. However, most SHGs prefer to fmance income generating
activities because the probability increases. The field survey indicates that only 20% of
the loans from SHGs were used for consumption purposes, rest did manage to invest in
income generating activities. The precondition for borrowing from the bank was that the
loan applicant is 'economically active'. There is no special provision for consumption
loans.
The RRBs also do not finance consumption activities; however, the Kisan credit card
system has improved the probability of borrowers financing consumption activities
274
through formal credit instead of the conventional informal credit. Formal credit for
consumption assumes importance because informal credit is much more expensive than
formal as seen in the previous section. The money lenders are the most expensive
alternative. But people in rural areas need credit for a variety of non-income generating
purposes like meeting health care costs, education, unforeseen expenditures and
ceremonial expenses. In recent years, with the proliferation of expensive super-speciality
hospitals coupled with the decaying public health system, the health care costs are
increasing. This increase in the health care costs is fuelling credit demand. All the above
mentioned countries have poor public heath care system. There were only 0.6 doctors per
1000 population in India, in Bangladesh and Indonesia it was 0.3 and 1 respectively54•
None of the above mentioned rural credit vehicles financed expenditure like these.
SEW A bank's individual loans are also meant for income generating activities. However,
their rural group loans are largely decided by the borrowers themselves, so the purpose of
the loan is also decided by the group members themselves. In such cases, though the
emphasis is on income generating activities, there is a fair chance that loans are also
sanctioned for consumption purposes.
There is however possibility of diversion of loans to activities other than stated in the
loan application, large scale data on which is unavailable.
6.2.4. Repayments
The international examples in the study gained the popularity they did initially because of
very high repayment rates. Though they were mostly lending small sized loans to people
who could not offer any collateral, they never had the problem of high over dues or
defaults. Only Indian RRBs had the perennial problem of high over dues. In recent years,
RRBs have made serious attempts to reduce NPAs which shows on the balance sheet of
the RRBs. According to Hulme and Mosley (1996), the average arrears rate (defined as
54 Economist pocket world in figures 2007
275
the proportion of loans more than six months in arrears) during 1988-92 was 0.6%, 3%
and 42% for BancoSol, BRI and RRBs respectively. As on 2005, NPA of BancoSol
defmed as the portfolio at risk was close to 4% of the outstanding loans. It was 2.57%
and 2% for Grameen Bank and BRI respectively. It was over 12% by the end of 2004 for
RRBs. The international examples have been better at recovering loans. All of three
international institutions intensively monitor their borrowers whereas RRBs are
extremely weak on the monitoring front.
6.2.5. Profitability and Sustainability
Most of the institutions in the study have been profitable for a long time. Banco Sol issued
dividends to its shareholders only three years after it was established in 1993. The
institution charges market rates and it was as high as 65%, but in recent years larger
number of loans and economies of scale has driven the effective interest rate to about
22%. BRI also charges market rate of interest. There is no built in subsidies. Hence the
venture has been profitable. In fact, the East Asian crisis hardly had an impact on BRI.
The other banks at the same time suffered huge losses. Deposits increased from Rp 7. 7
trillion in June 1997 just before the crisis to about Rp 17.1 trillion at the end of 1999.
Kupedes was also stable during the period. Repayments rate was 98% in June 1997 and
remained the same in December 1999. Grameen Bank claims to self sufficient in terms
of its capital needs. The bank also made of profit of$15.85 million (Tk 1039 million).
For these institutions, profitability, interest rate charged and their sustainability are
interlinked. If they are to survive in the markets for a long period of time, they need to be
self reliant. Initially institutions like BancoSol and Grameen Bank were heavily
supported by donors. But donor support is not a continuous stream of income and cannot
be relied on for years. All of them have overgrown donor support. For this they charge
market rate of interest and that is how their loans are very expensive. In case of Indian
RRBs, the institutions were backed by the State and therefore establishment costs were
absorbed by the State, therefore loans from RRBs have been cheaper than in most of the
276
institutions studied. This is an important contrast between RRBs and it international
counterparts. Had there been some sort of support, BRI and BancoSol would not have to
price their loans so high. Also with the backing of the State, RRBs need not worry about
sustainability, even if they run into losses; they always can look forward for a
recapitalisation programme backed by the State. But the other international institutions
have to earn profits in order to stay in business. So for them profitability and
sustainability is inter-linked. Most of them have managed to survive because they have
been earning profits.
This is the typical fallout of implementation of neo-classical ideas in rural credit markets.
Expensive loans for borrowers and handsome dividends for the equity holders. This
situation is not justified at any cost because the borrowers happen to be the poorest of
population and the lender is far better off then the borrowers. This is exactly the situation
proposed by David Harvey 55 that with the implementation of neo-liberal programmes,
there have been massive shift of wealth to the top tenth of the top one percent of the
population.
Table 139 : Summary Statistics
RRBs SEWA SHG Linkage IRDP#
1990-93 2005 * 2002-03 2005 * 1989-90
No ofBorrowers 12 million 13 million 29593 16.7 million 20 million
% of female clients 9% 21.4% 100% 27%
No of advance Ale 14167000 50849
Advances (Rs crores) 32688.63 13.84 3904
Profits (crores) 614 0.51
Deposits( crores) 53390
Average loan size 3084.5 16000 2627 5000 3230
@constant prices 286.6 817.9 143 255.6 432.7
55 Harvey David, "A brief History ofNeo-liberalism" Quoted in Mobiot, George (2007) "How Neo-liberals stitched up wealth of nations" The Hindu august 29 2007
277
Interest on loans 12-16% 6%-13.5% 14.5/17% 24-36%
Recovery 52% 92% ;:::JOO%
42.7% 50% BPL,
Landless 41.4% Landless-
Beneficiaries BPL 44%BPL 44%MF Landless 37.6%
SCST 28% 27% SC/ST -42%
Source: * Field Study# Madhura Swaminathan and V.K.Ramachandran @ constant prices Base year 1960-61 consumer price index for agriculture workers, 1\ 7th plan document, GOI
Firstly, in terms of absolute outreach, the IRDP programme emerges as a biggest
programme. The total number ofbeneficiaries was about 20 million in 1989-90. No other
programme with similar intention, ever reached the scale of this programme. The total
number of borrowers of RRB is about 13 millions. Together with the other commercial
banks the outreach of the State backed banks are high. The outreach of all commercial
banks in rural areas is close to 30 million. The scale and geographical spread of this
extent is hardly difficult to be matched by any other informal agency. The spread
achieved by the commercial bank is because of the State directed policy. Had there been
no change in the policy of the State in last decade, the outreach without doubt would have
been much higher. The number of borrowers in case of Microcredit SHGs is about 16.7
million. In case of SEW A it is less than thirty thousand. It is clear that informal agencies
can hardly match the scale and the geographical spread achieved by the State backed
commercial banks, including RRBs. State backed programmes have the resilience to
reach out wide and deep. Any attempt to supplant informal programmes like Microcredit
programmes in place of commercial banks, is flawed. The empirical evidence makes the
lack of depth and outreach of informal programmes amply clear.
Secondly, IRDP did very well in reaching out to women, as high as 27% of the
beneficiaries were women. Microcredit self-help-groups basically targeted women;
hence the outreach of such programme is very high among women.
278
Thirdly, the very premise on which Neo-classicists advocated the liberalisation of interest
rates and perpetuation of informal sources was that such a development would increase
the supply of credit. Empirical proof goes against the theory. Since IRDP was operational
earlier than Microcredit programme, the average loans are stated in both nominal and real
terms. The nominal figures are not comparable due to the difference in the period of
operation. The real average loan ofRRB at Rs 817 (1960-61 prices) is still the biggest in
its class. IRDP loan in real terms at over Rs 400(1960-61 prices) is the second biggest
loan. The average real loan from the Microcredit self-help-groups still remain very low at
around Rs 255 (1960-61 prices).
Fourthly, recent developments have hit the rural population on two counts. One is that the
withdrawal of formal agencies from rural area means the drying up of one important
source of credit. Secondly the perpetuation of informal credit agencies means that the size
of the loan is small and the quantum of loan is insufficient. Given the small siz.;; of loans
from the Microcredit self-help-groups, it is also doubtful if there will be any creation of
micro-enterprise/penny capital.
Fifthly, the RRBs appear to :be the cheapest source of credit in the rural areas. RRBs
used to charge anywhere between 12-16% during 1990-93, in 2006 RRBs charge
anywhere between 9% and 13%. Whereas in the SEWA bank borrowers are charged 17%
for funds lent out of the Banks own resources and 14.5% for the funds lent out of the
resources mobilised from financial institutions like HDFC for the purpose of on lending.
fu the Microcredit self-help-groups the interest rate charged is upwards 15%, many a
times as high as 36%. Some groups also charge a penalty for delay in payments of
instalments.
Lastly, in terms of targeting, the RRBs fare better. In 1990-93, 44% of the total
beneficiaries of RRB loans belong to the below poverty line population group. In fact,
prior to the 1990s, the mandate of RRBs was to serve people with an annual income of
less than Rs.l 0000 which was the official definition of poverty line. By 2005, more than
40% of the beneficiaries were landless, an equal number were the marginal farmers. The
279
participation of the landless in Microcredit self-help-groups is high. It was around 40% in
2005. However only 34% of the members were marginal farmers and over 18% of the
members were small farmers. Both landless agricultural labour and marginal farmers put
together constitute about 75.7% of the beneficiaries. It is higher in case ofRRB at 86.2%.
In case of targeting marginalised social sections, it was comparable for both RRBs as
well as Microcredit self-help-groups at about 28% and 27% respectively.
It is obvious from the above statistics that any attempt to supplant the existing formal
institutional credit system with informal programmes like Microcredit self-help-groups is
faulty on many counts. Not only is it going to dry up the cheapest source of credit for
rural population, but also leaves then with the alternative that is far inferior in quality and
insufficient in terms of size and scale. The role of State in such a context becomes very
important. If there is willingness on the part of the State, the formal institutional agencies
ca.J. be coxed to serve a section of population that would otherwise be left out by the
formal agencies. The earlier mixture of carrot and stick policy of the State was successful
in perpetuating formal institutional agencies even in the remote rural areas. However
unprofitable conducting business in rural areas were, the banks were actively involved.
They did perform a vital function of .a financial intermediary in rural areas. They
mobilised deposits from rural areas. Rural population needed a safe avenue to save and
secure their savings. Also the formal institutions met the partial credit needs of rural
population. In the early years their role was recognised and profitability came next only
to national interests. Once the attitude of State towards rural credit changed, the formal
institutional agencies have a reduced interest in serving rural areas. Despite this
disinterest they have been better than informal programmes like l\1icrocredit self-help
groups as well as money lenders.
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7 Conclusion
In the context of the agrarian distress, it is clear that the State is indispensable in the rural
credit markets. It is more than evident that political will has been the driving factor in the
perpetuation of formal institutions, mostly scheduled commercial banks in rural credit
markets till late 1980s. The policy impetus was responsible for the increase in the
proportion of cash debt of rural households from formal sources from 29% in 1971 to
about 66% in 1991. Again the policy of the State is to be blamed for the reduction of
proportion of cash debt of rural households from formal sources to 57% in 2002.
Simultaneously, the proportion of cash debt of rural households from money lenders
which varies inversely with that of the formal sources was decreasing till 1991 but has
again increased in 2002. The active involvement of State ensured that a steady trickle of
credit from formal sources reached the targeted population. The onset of the process of
liberalisation has erased the gains made during the previous policy regime. This
decreasing activity of formai agencies juxtaposed with the increased activities of
moneylenders becomes very critical given that indebtedness is the most conspicuous
symptom of the current distress.
The second chapter traced the problems specific: to rural credit markets and the policy
response to such problems. The problems of inadequacy of credit, artificial constraints to
access credit viz fragmented and imperfect markets, multiform interest rates were
countered by a policy response in the form of 'social & development banking' which
resulted among others, in the nationalisation of commercial banks and establishment of
specialised rural credit delivery vehicles like Regional Rural Banks. However, this policy
was reversed during the early 1990s in the guise of liberalisation. As detailed in Chapter
2, Liberalisation of financial sector brought with it the factor of de-regulation of interest
rates, reduction in the portion of directed credit, dilution of branch licensing requirements
and the quest for profitability. These measures translated into dispirited operation of
commercial banks in rural areas which lead to a situation where it became tougher for
rural population to access bank loans while the better-off section of population were
readily offered cheaper credit products. The third chapter presented an empirical enquiry
that analysed the changing focus of commercial banks. Accordingly there is a substantial
281
reduction in directed credit which hit the target group very hard. This is evident in the
reduction in the proportion of priority sector loans despite the expansion of the definition
of "priority sector". This was one of the developments that hurt the rural population the
most. The dilution of branch licensing also affected the rural areas substantially. The
liberalisation as a package provided a systematic road map for the State to gradually
withdraw from rural credit markets. Not only has the State legitimised the withdrawal,
but is also encouraging banks to engage in profitable operations (mostly in urban areas).
The other section of Chapter documented the symptomatic feature of credit crisis because
of the withdrawal of State from rural areas. The symptom is manifest in the rapidly
reducing rural credit deposit ratio even as the reduction is less rapid in urban branches. It
is also evident in the increase in the commercial bank credit to retail sector, including
personal loans, loans for professionals at the cost of critical sectors like agriculture and
industry. All these symptoms support the argument of the thesis that the State no longer
seems to support a banking system which is 'inspired by a larger social purpose that had
to subserve national priorities and objectives' .56
The fourth chapter examined the recent developments in rural credit scenario in terms of
two most important agencies of rural credit. The agencies were.Regional Rural Banks and
Microcredit self-help-groups. As detailed in the chapter, RRBs have been an integral part
of the rural fabric. They have played crucial role in the mobilisation of savings in rural
areas as well as fulfilling the credit needs of critical sectors. RRBs have a wide branch
network that is mostly rooted in rural areas. They have branches even in less developed
states like Bihar, Orissa, Uttar Pradesh and Jharkhand, in disturbed areas like Jammu &
Kashmir and north-eastern states. RRBs have been very active in mobilising deposits
even from backward states like Bihar, Uttar Pradesh and Madhya Pradesh. Credit
disbursal of RRBs has also increased manifold. But in recent years the share of credit in
rural areas has shown signs of weakness, while the share of credit in semi-urban and
urban branches has increased. The proportion of priority sector loans has declined in
56 Preamble to the bank company acquisition act of 1969
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almost all the states compared to the early nineties, but the decline is stark in the states of
Jammu & Kashmir, Manipur, Nagaland, Tripura and West-Bengal. The apparent
proportion of agricultural credit is increasing, but it is actually the rise in indirect credit
on agriculture. The direct credit to agriculture has been steadily decreasing. Despite the
decline, more than half of the outstanding RRB credit is on agriculture and allied activity.
This highlights the rural character of RRBs and its potential to address the agrarian
distress. However, in case of RRBs there has been a steady increase of personal loans, at
the cost of industry and small transport operators. In the current banking scenario, it is
surprisingly easy to get a loan for foreign vacation than to setup a small scale industry.
Also the proportion of small & tiny borrowal accounts has been steadily decreasing and
the current situation is such that borrowing a larger loan has become easier than a small
loan.
Further investigations on RRBs in chapter five reveals that,
• The majority of the clientele were either landless agriculture labours or marginal
farmers. However, the participation of marginalised social groups was not very
impressive, with the people from other castes dominating the clientele, while
borrowers from Scheduled Castes made up to less than a quarter of the total
borrowers.
• It is also highlighted in the chapter that the cost of credit from RRBs was one of
the lowest despite the high transaction costs. Crop loans were by far the most
popular loans along with being the cheapest. Most of the borrowers said they had
invested their loans on cultivation. Cash loans fmancing activities like petty trade,
hotels and floriculture were also popular.
• Econometric analysis of repayment revealed that repayments were affected by the
activity the loan is invested on as well as the asset class of the borrowers.
Significant independent variables included investing the loan on activities like
petty trade, cultivation and other activities. Landless agricultural labours were
also found to influence repayments positively.
• RRBs as financial institutions did have a problem of accumulated losses before
liberalisation. Many of them were recapitalised in the mid and late nineties with
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the realisation that the RRBs were special institutions and that they needed a long
period of time to be viable. The difficult conditions under which they operated
like the geographical spread, their clientele and target group oriented business
approach were duly recognised. This attitude however changed after
liberalisation. The beginning though was made in Khusro committee (1989),
which was largely ignored. The Narasimham committee (1991) however was
quick to point out the fragile financial health of a large number of RRBs and
suggested ways to make these banks viable. Along with this the profitability of
RRBs assumed importance. In the light of these recommendations, several
measures to improve the profitability of RRBs were introduced. It included
permission for RRBs to engage in full fledged banking services like any other
commercial banks, downward revision of target group lending, strengthening the
capital base and mergers. These recommendations along with the dilution of
branch licensing tran5latcd into closure of many rural banks as well as branches
and reluctance to open new branches. But this policy stress on profitability is
critically flawed because several key factors are not only being neglected but the
policy itselfhas faulty focus.
• The policy that encouraged the closure of rural banks coupled with a reluctance to:
open new branches pursuing profits stems from an ill thought out assumption of
un-profitability and un-viability of rural branches. The drastic wind up of rural
branches appears to be a hasty move and the lack of serious efforts to make the
banks profitable, short sighted. There are empirical evidences to show that not all
rural bank branches were unprofitable. For example, 12 RRBs in Uttar Pradesh,
both the RRBs in Kerala, 8 RRBs in Andhra Pradesh and 5 RRBs in Karnataka
have made profits steadily since 1995. International example for a viable State
backed rural bank network includes rural bank branches in Costa Rica. They have
been operating profitably from a long time, also in the experience of that bank;
small farmers were least likely to default. The key to the success of the bank in
Costa Rica is the monitoring and the dynamic incentives, which have proved to be
the Achilles' heals of RRBs.
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• RRBs fare very poorly in terms of monitoring and offering dynamic incentives.
The monitoring is weak owing to insignificant staff to account ratio even as there
is a lack of motivation & incentive to monitor borrowers closely. At the same
time, dynamic incentive has been a feature excluded from the credit design of
loan products in RRBs. Also the conditions under which RRBs operate are not
conducive for undertaking intensive monitoring. Not only are their operations
widespread, but also the staff are not motivated to monitor borrowers intensely.
• Another serious associated problem is the appraisal of credit worthiness of an
applicant which is difficult for the managers, given that a single branch serves
many villages, typical located several kilometres away from the branch, and the
officers will have no time to go and visit each of the applicant before making up
mind to grant loans, instead, they rely on the recommendation of set of influential
set of people in various villages. The repayment of such loans is of course any
body's guess.
• Fresh recruitments m banks have been frozen for a while, because the
management of banks feel that with the advent of computerisation, fewer staff
members will be needed to work, has in a way affected profitability. As is
mentioned earlier, defaults are an inverse function of monitoring. That means
defaults can be kept in check with proper monitoring. Monitoring in tum is a
function of the number of employees of the bank. Intensive monitoring can reduce
wilful defaults by a great extent. It is because of intensive monitoring that
Grameen bank, SEW A Bank and other group credit schemes have been
successful. Similar arrangements to monitor borrowers should pay off the banks
handsomely. But the freeze on recruitment is affecting monitoring activities and
hence the profitability adversely. Therefore a reasonable policy on recruitment
could probably help in improving the profitability ofRRBs.
• The RRBs face a deep rooted problem of default, which is mostly due to faulty
incentive structure. While the same person borrowing from a Microcredit Self
help-group would pay up the instalments regularly, she would default on a loan
from the RRB. Despite the additional transaction costs that need to be incurred on
a loan from the local RRB, people still borrow from RRBs, one of the reasons
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being lax enforcement and monitoring of the loan and an incentive in terms of a
reasonable chance to default. Any attempt to recover loans is stiffly resisted
because there are far too many other defaulters who are not being asked to pay up.
Besides, frequent politically motivated loan write-otis have built in an incentive
structure that discourages even the prudent of borrowers to wait for a populist
loan waiver. Coupled with lax monitoring, these write off is harming the
profitability of the bank more than any other factor. However, it should be
remembered that there are both wilful defaulters as well as those who hit be
genuine causes. Where as by intensive monitoring, the wilful defaulters can be
penalised; genuine defaulters affected by crop failure, natural calamities, sickness
and loss of livelihood should be offered appropriate help.
• The increasing focus on profitability, manager at branch levels have an incentive
to lend less risky and more profitable loans say the salary backed personal loans,
housing loans and Loans against collateral. Since they are made answerable to the
economic health of the bank, a natural incentive effect becomes operational,
because of which the original mandate of the program to "lend to the
disadvantaged groups" is automatically diluted. All these factors need to be taken
into account to improve the profitability of the banks. When these factors are
considered, meeting the credit demand of rural population while keeping the
bank's balance sheets should be very much possible.
The sixth chapter dealt with the impact assessment of Microcredit programmes. As
elaborated in earlier chapters the State is encouraging the formation of Microcredit self
help-groups in a big way. The expansionary policy in support of self-help-group is the
influence of neo-liberal reforms. As envisaged by the neo-liberal theory, State is
withdrawing from a direct role in rural credit markets. Microcredit and such programmes
are providing the required alibi for the State to withdraw from the rural credit market, at
the same time, installing inferior machinery in its place. Microcredit self-help-groups are
not a substitute for State backed institutions like commercial banks or RRBs. It can just
be a yet another source of quick and small scale credit.
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There are a variety of Microcredit self-help-groups. Of them, the State backed groups are
better than the others. The cost of credit is cheaper in State backed groups than the others.
Though there are strict eligibility criteria for membership in such groups, it is found that
membership is often diluted and implementation is rather weak. In Dodderi Hobli of
Tumkur district Karnataka, it was found that only 50% of the members in State back
groups were below poverty line. The rest belonged to higher asset class. In terms of
social groups, members belonging to schedule castes were under represented; Scheduled
Tribes were marginally over represented compared to their proportion in the population
of the Hobli. Also the participation among OBCs was very high. Participation of
landless agricultural labour and small farmers was high but that of marginal farmers were
low. Literacy had a major impact on the outreach of self-help-groups. The finding
corroborates Sen (2000) that social opportunities increase economic participation.
Majority of the group members were literate even though only about 30% of the
population were literate. Illiteracy appears to be negatively influencing self-selection of
members during the formation of groups. The lack of social opportunities like education
will therefore seriously affect the participation of women in programmes like
Microcredit. In this context as well the role of State becomes crucial.
Most of the groups charged an interest rate of about 24%, a few groups also charged 36%
and above. The high rate of interest in State backed groups is justified because the pooled
interest was again divided amongst the members; it was an indirect way of saving. But
the same is not true for groups sponsored by NGOs and other private for-profit
organisations. In such cases there could be a problem of Micro-debt trap as the loan size
increases. The higher interest rates coupled with smaller loans impose a restriction on the
choice of activity that can be financed by the loan. Because the interest rates are higher
and the instalment cycles are shorted, consumption and activities with long gestation
period can be very burdensome. The choice of activity will therefore be limited to those
with short gestation period like petty trade.
More than a fifth of the respondents had invested the loan on cultivation; an equal
number had used their loan on consumption expenditures. Trade and milch animals were
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also popular as alternative investment avenues. It was also found that investment in petty
trade was most remunerative for borrowers, followed by investment on milch animals
and cultivation. The quantum of loan was also a significant variable affecting the
revenue stream of the borrowers but was very weak. Repayments were generally high.
Most of the groups investigated were prompt in repayments. The groups were also active,
only one of them was disintegrating after having paid up the last instalment. Most groups
were operating profitably. They were accessing cheap credit and were lending amongst
themselves at a higher rate of interest. The pooled interest was again divided among
members. However, in groups promoted by NGO and for-profit institutions, the interest
differential was retained by the lender as service fee. The effective cost of credit in such
groups is comparable to that of moneylender. It would not be wrong to call such self
help-groups neo-moneylender because both moneylenders and such groups operate on
similar terms and conditions. These terms of operation is unconvincing and might prove
very costly for the borrowers.
There are several problems associated with Microcredit programme.
• Microcredit self-help-groups can never match the spread and scale of the formal
institutions like RRBs. Also, the formal institutions perform an important function
of mobilising deposits, which cannot be performed by the Microcredit self-help
groups. These groups have provision for compulsory weekly saving but not
voluntary savings over and above the compulsory portion. The number of
products both credit and deposit offered by commercial banks cannot be matched
by Microcredit self-help-groups. These groups are good only to the extent of
inculcating the habit of saving and serving immediate but small credit needs of
the members. It cannot be expected to play a bigger role.
• Institutional credit and non-institutional credit are imperfect substitutes. The
presence of deep rooted market segmentation inherent in the rural credit system
prevents many from accessing non-institutional credit. Such lacunae only serves
to reinforce the market segmentation thereby including a large number of non
target group clients. Such market segmentation in the case of this study was
determined by the literacy factor. However, other important segmentation based
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on caste groups and asset classes were not very strong in the case of this study but
this might not be the case else where.
• The loans offered by microcredit self-help-groups are very small and insufficient
to be of much help. It was found in this study that the average micro-loan is about
a third of the average loan from an RRB. The quantity of the loan restricts the
choice of activities that could be taken up to generate income. The short
repayment cycle pressurises the borrower into taking an activity with very short
gestation time.
• The expansion of Microcredit self-help-groups has been skewed in favour of the
better off states. The south Indian states account for more than two thirds of all
the groups linked. States with high level of poverty, like Assam and Bihar has
only about 1% to 1.5% of the SHGs linked to banks in India, better off state like
AP, has the maximum concentration of SHGs.
• There is also an increasing threat of indebtedness in member households. Since
the screening and verification is weak at times, multiple memberships are widely
prevalent. As noted in the fourth chapter the theory of group lending can work
only when there is exclusivity of memberships. Multiple memberships not only
increase the burden of weekly savings and instalments, but also threaten the
solvency of the whole group.
The assumption of timely credit rather than cheap credit, the other is the cost of credit.
How far the assumption is true is debatable. The assumption of timely credit appears to
be an alibi for winding up the bank branches. Rural population need credit that is timely
yes, but also cheap credit. When the better off class of people are being given cheaper
loans to buy consumer durables and vehicles for personal use, how far can the state duck
from its responsibility of providing cheap credit to vulnerable sections of population and
still justify its stand?
These serious draw backs make it amply clear the Microcredit programmes can just be
yet another source of credit. It should not crowd out other institutional source of credit.
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The policy makers should recognise the limitation of the programme and revise their
level of expectation from the programme.
Microcredit institutions are a product of the Neo-liberal school of thought which believes
that "when a significant market failure occurs, there are strong incentives for non market
institutions to develop which go at least part of the way towards remedying the
deficiency" (Stiglitz and Amott 1991). Nevertheless, it has been observed that the non
market institutions that so arose can be dysfunctional having an effect opposite to those
intended. The dysfunction is probably due to the presence of non market forces like the
incentive structure, class structure and institutional factors. Firstly, the incentive structure
can be faulty as in the case of bank managers who shirk away lending to critical sectors
in favour of less risky alternatives.
Secondly libcralisation of financial sector has had its effect of the classes of society.
Extending Patnaik's (2007) view on agrarian crisis to rural credit markets, liberalisation
of financial markets has just led to a situation where the economically better-off section
of the population is trying to capitalise on the vulnerability of the economically weak..
The State, playing an active role in providing credit to rural population, deprives the
segment of private ·lenders of a lucrative informal rural credit market. If the State is
providing subsidized credit, the informal lenders prove very expensive and they will be
confined to a smaller portion of the market. However in the absence of the State, informal
agencies will thrive because their client base will increase. Expanding and lucrative
informal agencies operating in rural areas make a good business proposal. It is no
coincidence that many informal agencies operating around the world are being funded by
multinational corporations and venture capitalist, all in the guise of poverty alleviation.
This is just the self-interest of a section of lenders working against the interests of rural
borrowers. Once the stage was set, foreign banks, venture capitalists, international
agencies and NGOs of myriad hues have started Microcredit programmes. Now there are
agencies providing rating for Microcredit programmes, so that investors are better
informed to make more profits. Self interest is driving them, but, borrowers as a class are
ending up loosing a lot. Also, there is nothing philanthropic about NGOs capitalising on
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the desperation of vulnerable sections to charge very high interest rates and still clam to
be making entrepreneurs out of poor.
In the context of increasing influence ofNeo-liberal policies on rural credit, it is a pity to
note that Indian rural population, mostly farmers are at the mercy of informal sources
with respect to their credit needs. The farmers are being not only hit by lower
productivity gains, lower price realisation but also drying up of formal credit channels.
The formal financial sector a few decades earlier had achieved significant gains in
addressing the credit needs of the farmers and the rural population in general. After the
liberalisation of the financial sectors, those gains stand eroded. Before long the scenario
will not be much different than the one portrayed by the 'All India Rural Credit survey'.
At such a juncture, it is high time that State rethinks about its stand and responds
positively to the need of the hour.
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