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Figure: 4.1
Figure: 4.2
Andhra PradeshSTUDY AREA
Figure: 4.3
STUDY AREA
Srikakulam District
Figure: 4.4
Figure: 4.5
Srikakulam District
Pathapatnam Mandal
STUDY AREA
Figure: 4.6
Survey Villages in Pathapatnam Mandal
Figure: 4.7
RELATIVE PERFORMANCE OF SELECTED SELF-HELP GROUPS
OF THE BREDS AND IKP
In this chapter an attempt is made to assess the functioning of SHGs and
to make a cross section comparison of functioning of selected Self-Help Groups
in the two SHPIs. The SHGs take many forms. This study focuses on thrift and
credit activities of the SHGs. The performance of SHGs is examined at the
group level from its organizational, functional and development view points.
The performance of SHGs is evaluated with the data ascertained from 40 sample
SHGs from 5 villages each SHPI, as a whole 400 SHG members are selected
from the 80 selected SHGs selected from 10 villages which are equally selected
from both the selected SHPIs, IKP and BREDS ( details are presented in
Annexure I). The analysis is attempted to assess the performance of SHGs and
their role in financial service delivery. The analysis is mainly focused on
thrift, details of credit activities with own funds of SHGs, repayment of
internal loans, details of bank linkage, economic activities pursued with bank
credit and quality of maintenance of SHG records. In the light of these aspects
this chapter is broadly divided into four different sections. The profile of the
selected SHGs is presented in the first section (4.1). The financial aspects of the
selected SHGs are presented in the second (4.2). The organizational aspects of
the SHGs are discussed in the third section (4.3). The overall assessment of the
performance of the selected SHGs is outlined in the fourth section (4.4) and the
conclusions are presented at the end (4.5).
4.1. Profile of the Selected SHGs:
In the Srikakulam district of Andhra Pradesh as a whole by March 31,
2012 there are 31, 423 SHGs. The 102 number of registered NGOs in the
Srikakulam district are organizing the functioning of the 26,312 SHGs which
are covered under NGO activities. In the selected Pathapatnam Mandal the total
number of registered SHGs are to the extent of 1236 and 6 NGOs are involved in
the SHG activities in the Pathapatnam mandal. Among the registered NGOs
leading one is BREDS and it is organizing 513 SHGs. The remaining SHGs
under the organization of IKP there are 1098 registered SHGs.
91
The following Table 4.1 presents the profile of the selected SHGs covered
under the organization of the BREDS (NGO) in the Pathapatnam mandal.
Table 4.1.Selected SHGs covered under BREDS
Sl.NoName of the
VillageSl.No
Name of the Group
Date of Formation
Bank Name & Account No.
1 Peduru
1Mahalaxmi Maridamma
6/6/2000SBI,Ganguvada, 01190047017
2Sri Neelamani Mahasakthi
12/10/2004SBI,Ganguvada, 01170017455
3 Sri Siridi Sairam 21/10/04SBI, Ganguvada, 11692021769
4Vanna Maridamma
28/8/12SBI, Ganguvada, 11692022369
2 Kannayya Pata
5Kanka Mahalaxmi
7/6/1999SBI,Ganguvada, 01190046735
6Chinatala Polamma
7/6/1999SBI,Ganguvada, 01190126735
7 Sri Girilaxmi 18/4/05SBI,Ganguvada, 11692022253
8 Saraswathi 16/7/99SBI,Ganguvada, 11692462253
3 Mettupeta
9 Satyasai 23/1/06SBI,Ganguvada, 11692023198
10 Ganguvada 7/9/2002SBI,Ganguvada, 11692027921
11 Durgadevi 10/12/1999SBI,Ganguvada, 30356068585
12 Vandalamma 13/5/99SBI,Ganguvada, 11692032249
4 Konchadapeta
13 Sri Mahalaxmi 22/1/08SBI,Ganguvada, 116920244545
14Sri Tirumalaswami
25/6/07SBI,Ganguvada, 11692023631
15 Polamma 14/11/02SBI,Ganguvada, 1190047310
16 Rajyalaxmi 20/6/99SBI,Ganguvada, 01190047353
5 Bommika
17 Bhagyalaxmi 20/4/99SBI,Ganguvada, 01190046175
18 Durga Bhavani 20/2/06SBI,Ganguvda, 01170017824
19 Sri Sai Durga 5/8/2008SBI,Ganguvada, 30447812911
20 Sai Bhavani 21/8/08SBI,Ganguvada, 30461627603
6 Baddumarri
21 Sri Rama 29/7/08SBI,Ganguvada, 30441575826
22 Sri Gowri 20/2/98SBI,Ganguvada, 11692018611
23 Mavullamma 14/2/02SBI,Ganguvada, 01190047060
24Sri Kothammavaru
16/7/99
SBI,Ganguvada, 11692071890
92
7 J.C.Peta
25 Sri Manikanta 26/7/04SBI,Ganguvada, 11692021656
26 Chaithanya 8/5/2010SBI,Ganguvada, 11692027295
27 Bhavani 20/6/2005SBI,Ganguvada, 11692729521
28 Ganesh 16/10/07SBI,Ganguvada, 11692023971
8 Rajannapeta
29 Kranthi 14/9/2002SBI,Ganguvada, 11692031269
30 Vijayala Jyothi 6/9/2001SBI,Ganguvada, 11692037065
31 Arunodaya 7/8/2001SBI, Ganguvada, 11692025389
32 Sri SiridiSai 6/23/1905SBI,Ganguvada, 11692035910
9 Dwarakapuram
33 Ambadker 13/09/02SBI Ganguvada, 11692024986
34Yendala Mallikarjuna
13/09/02SBI,Ganguvada, 11692038003
35 Bhavani 13/09/02SBI Ganguvada, 11692025957
36 SriVenkateswara 6/5/1999SBI,Ganguvada. 11692037463
10 Kasi Puram
37 Siridi Sai 22/5/99SBI,Ganguvada, 116920035606
38 Sri Seeta Rama 22/5/99SBI,Ganguvada, 11692035863
39 Bhavani 7/6/1999SBI,Ganguvada, 11692025968
40 Chavitamma 16/7/99SBI,Ganguvada, 11692026972
From the above Table it can be observed that out of 513 SHGs operating
by BREDS randomly 40 SHGs are selected from the 10 selected villages from
the Pathapatnam mandal. The information relating to the names of the selected
villages, selected Groups, their date of formation extent of bank linkage received
by them are presented. From the each selected SHG randomly 5 members are
selected for the in depth study
The following Table 4.2 presents the profile of the selected SHGs covered
under the Governmental organization IKP in the Pathapatnam mandal.
93
Table 4.2.Selected SHGs covered under IKP
Surveyed SHG Particulars in IKP Operational Area
Name of the Village Sl.NoName of the
GroupDate of
FormationBank Name & Account No.
1 Ganguvada
1 Sri Manjunadha 13/9/2002SBI, Ganguvada, 11692032294
2 Sri Majji Gowramma 12/10/2007SBI, Ganguvada, 11692023982
3 Swami SHG 15/3/11SBI, Ganguvada, 31611516827
4 Simhadri SHG 9/10/2001SBI, Ganguvada, 11692035965
2 Singupuram
5 Ramanamma 14/5/99SBI, Ganguvada, 11692034665
6 Tulasi SHG 13/10/2007SBI, Ganguvada, 11692024001
7 Anjeneya 8/12/2000SBI ,Ganguvada, 11692023109
8 Sri Venkateswara 15/4/02SBI, Ganguvada, 116920371174
3Pedda Laxmipuram
9 Srilaxmi 31/10/97SBI,Ganguvada, 11692031722
10 Saraswathi 17/4/02SBI, Ganguvada, 11692035433
11Sri Panchamukha Anjeneya
3/9/2010SBI, Ganguvada, 31534852607
12 Sri Sai Mahila SHG 16/7/99SBI, Ganguvada, 11692035013
4 B Gopalapuram
13 Neelamanidurga 4/6/1999SBI, Ganguvada, 1169203964
14 Kanakadurga 4/6/1999SBI, Ganguvada, 11692029904
15 Bhagyasri 27/6/2009SBI, Ganguvada, 30412744213
16 Sri Majunadha 7/10/2002SBI, Ganguvada, 11692132307
5 Labara
17 Uma Maheswari 16/5/99SBI,Ganguvada, 11692037076
18 Vijayalaxmi 18/10/02SBI,Ganguvada, 11692037543
19 Neelamanidurga 5/12/2006SBI,Ganguvada, 11692023519
20 Ravanamma 15/4/99SBI,Ganguvada, 11692034790
6 Pedda Sariyapalli
21 Laxmi 18/10/02SBI,Ganguvada, 11692031733
22 Sumangali 13/2/06SBI,Ganguvada, 11692023370
23 Pallavi 16/7/99SBI,Ganguvada, 11317781223
24 Sanghavi 16/7/99SBI,Ganguvada, 11317781234
7 Seetharampalli25 Venkateswara 8/7/1999
SBI,Pathapatnam, 11317805676
26 Kanakadurga 20/9/06 SBI,Pathapatnam, 11317792202
94
27 Santhosimatha 5/10/2002SBI,Pathapatnam, 11317771882
28 Jabilli 14/10/05SBI, Pathapatnam, 1131775672
8 Praharajapalem
29 Vennala 26/7/07SBI,Pathapatnam, 11317783139
30 Saibaba 26/7/07SBI,Pathapatnam, 30212537699
31 Sri Ganesh 31/7/07SBI,Pathapatnam, 30215323968
32 Sri Mahalaxmi 3/8/2007SBI,Pathapatnam, 30215323833
9 Pathapatnam
33 Sri Kalki Bhagavan 31/7/07SBI,Pathapatnam, 30215323617
34 Indiramma 28/8/2009SBI,Pathapatnam, 30663636493
35 Neelamanidurga 5/10/2002SBI,Pathapatnam, 11317792508
36 Ramalingeswara 5/10/2002SBI,Pathapatnam, 11317771521
10 Antharabha
37 Sannajaji 13/8/2004SBI,Pathapatnam, 11317774566
38 Majji Gowramma 26/7/2007SBI,Pathapatnam, 3021324748
39 Ayyappa 11/3/2009SBI, Pathapatnam, 30707037763
40 Jaddamma SHG 16/2/09SBI,Pathapatnam,30685887004
From the above Table it can be observed that out of 1098 SHGs operating
by IKP the profile of the selected 40 SHGs from the 10 selected villages of the
Pathapatnam mandal are presented. The information relating to the names of the
selected villages, selected Groups, their date of formation extent of bank linkage
received by them are presented. From the each selected SHG randomly 5
members are selected for the in depth study.
4.2. Demographic and Financial Aspects of the Selected SHGs:
In this section an attempt is made to analyze the general as well as
financial aspects of the selected SHGs from the BREDS groups and IKP groups
of the Srikakulam district.
A. Distribution of SHGs on the basis of Age
Age of the SHG is a significant indicator of sustenance of the group.
Taking this into consideration, the selected SHGs are classified into different
groups basing on their age. The age for the purpose of the present study is
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computed as difference in years, between the month and year of group formation
and cut off date fixed for the study. Tables 4.3 give these details.
Table 4.3Distribution of SHGs based on Age Selected SHPIs
Sl. No
Age BREDS groups IKP groups Total
1Less than 3 years of formation
11(27.50)
2(5.00)
13(16.25)
2Completed 4 years of formation
6(15.00)
2(5.00)
8(10.00)
3Completed 5 years of formation
4(10.00)
32(80.00)
36(45.00)
4Above 5 years of formation
19(47.50)
4(10.00)
23(28.75)
Total40
(100.0)40
(100.0)80
(100)Source: Data collected through Field Survey Figures in brackets are percentage to total.
All the selected SHGs of both the SHPIs have completed three years of
existence. In case of BREDS 47.50 per cent of selected SHGs have completed
above five years and 27.50 per cent of them complete 3 years of formation. As
can be seen from the above table, there is significant difference in the age-wise
distribution pattern of SHGs between the selected SHPIs considered. In IKP
groups, 45.00 per cent of the selected SHGs have completed 5 years of
existence, while another 28.75 per cent have completed above 5 years of
existence. The distribution pattern suggests that majority of the SHGs selected
were formed in the years 2004 and after.
The age wise distribution pattern is analyzed in a different angle i.e.
cumulative method. As pointed out earlier all the selected SHGs have completed
two years of existence, while 45 per cent in both SHPIs are functioning for more
than 5 years. This indicates that majority of the selected SHGs are sustaining
over a period. 28.75 per cent of selected SHGs in both the SHPIs have
completed above 5 years of functioning. These groups, as per the records were
started in 2004 and after. Further, 16.25 per cent of SHGs selected in both SHPIs
have completed 3 years of functioning.
96
B. Matching Grant
The SHG model of thrift and credit is basically intended to inculcate the
habit of regular savings and lending the accumulated savings to members to
cater household credit needs. In order to expand the capital base the SHGs
access funds from District Rural Development Agency (DRDA), government or
other institutions for matching grant (revolving fund). A SHG is eligible for
matching grant, if the group has record of continued savings and credit
operations successfully without any default for six months. Initially the matching
grant was given at 1:4 ( accumulated saving : matching grant) which later
came down to 1:3 as the number of groups seeking match grant increased over a
period of time.
Table 4.4Details of time lag between SHG formation and release of Matching Grant
Sl. No.
Period BREDS groups IKP groups Total
1 Between 0 - ½ year 21
(52.50)27
(67.50)48
(60.00)
2 Between 1 and 1½ years 16
(40.00)13
(32.50)29
(36.25)
3 Between 1½ and 2 years3
(7.50)-
3(3.75)
Total40
(100.0)40
(100.0)80
(100.0)Source: Data collected through Field Survey Figures in brackets are percentage to total
The data presented in table 4. 4 reveal the time lag between the SHG
formation and release of matching grant. Around 60 per cent of the selected
SHGs belonging to both the selected SHPIs were able to get matching grant
within zero and half-year of formation. About 36.25 per cent of selected SHGs
of both the selected SHPIs obtained access to matching grant within 12 to 18
months of their formation. One important aspect is that the number of SHGs
formed in BREDS has out numbered SHGs formed in IKP in getting matching
grant at the earliest.
The factors responsible for the delay in getting the matching grant are
both internal and external. Internal factors are: improper functioning with respect
97
to saving, credit operations record maintenance, conduct of meeting etc. These
factors in a way illustrate the inherent weakness of the group. The external factor
is lack of adequate funds with the agency that provides the match grant. Thus,
there prevails a little uncertainty in respect of getting matching grant
immediately after one year of formation and functioning. However, when a
group satisfies the eligibility norm sooner or later it gets matching grant. In case
of some groups exclusively formed by very poor women uncertainty of getting
matching grant sometimes result in dropouts. In this context, the role of SHPI
offices assumes importance as it continuously monitors the affairs of the group
and also persuades the donor for early release of matching grant. What is most
important here is that the SHGs need to demonstrate that they are functionally
strong and financially well managed. More than 50 per cent of the selected
SHGs in both the selected SHPIs had access to matching grant. This clearly
demonstrates that the SHGs in the study area are financially sound and
functionally strong.
C. Distribution of SHGs based on own funds
The SHG model of micro credit is a saving led or savings linked credit
model. In this model the members of the group mobilize their small savings,
rotate the accumulated savings among themselves and earn some operational
profit in the form of interest on money lent within the group. Thus, the funds of
the group initially consist of savings of the members, interest and matching
grant. Data regarding the funds of the SHGs is ascertained from the records
of the each SHG. These details are given in table 4.5.
98
Table 4.5Distribution of SHGs based on own funds
(Value in Rs.)
Sl. No Category BREDS groups IKP groups Total
1 Below 25007
(17.50)12
(30.00)19
(23.75)
2 2500 - 500014
(7.50)7
(17.50)21
(12.50)
3 Above 5000 5
(2.50)1
(7.50)6
(5.00)
4 No own funds14
(72.50)20
(45.00)34
(58.75)
Total40
(100)40
(100)80
(100)Source: Data collected through Field Survey Figures in brackets are total amount of the groups
The above table reveal that depending on the amount of own funds the
selected SHGs are classified into four categories. Number of SHGs with own
funds less than Rs.2, 500/- and more than Rs.5, 000 are few in both the SHPIs.
Comparatively a majority of SHGs are placed in the category of below Rs.2, 500
in the two selected SHPIs. Further, among different categories considerable
number of SHGs figured in the category of Rs.2, 500 to Rs.5, 000.The pattern of
distribution of the selected SHGs on the basis of own funds indicate significant
difference between the two studied SHPIs. The SHGs selected from the BREDS
are relatively better in promoting own funds. The more numbers of SHGs
selected from the IKP are not able to promote their own funds. The pattern of
distribution of SHGs belonging to both SHPIs reveals that majority of SHGs
have not able to depend upon created on own funds.
In relative terms, the average amount of own funds are higher for those
SHGs belonging to BREDS than SHGs from the IKP. This observation needs
to be carefully interpreted as it cannot be concluded that SHGs of BREDS are
more efficient in capital mobilizing the internal funds consists of monthly
savings and interest on loans circulated among members. As far as savings are
concerned it is almost mandatory that each member saves Rs.30/- per month.
Thus the difference in own capital between SHGs belonging to two selected
99
SHPIs may be due to income accrued though savings that are positively related
to the age of the group and interest on amount of money that was put to rotation
internally.
The general premise is that the poor women have very less propensity to
save and therefore savings do not come forth from this section of the society.
The data presented in the above table sufficiently demonstrates that the poor
women are now slowly habituated to regular savings that gives capital base for
their group. Strong capital base of the group help the group member to cater to
their micro credit needs instantly. The SHG model is motivating the poor to save
one rupee per day to have access to institutional credit. Once the savings are
accumulated, they facilitate for internal leading and there by the group earns
operational profit.
D. SHG and Bank linkage
Linking SHG to the bank is a model evolved in order to improve the
access of the rural poor to formal banking services. NABARD’s sincere efforts
to create access to rural people to finances of banks have contributed a lot to this
SHG-bank linkage. This model gathered momentum since 1998. The policy
support to these efforts was provided by the Reserve Bank of India (RBI) which
urged banks to mainstream functioning of SHGs as business activity. An
important feature of SHG and bank linkage is that loans are generally advanced
to individuals who are members of SHGs. The group (SHG) is, in fact, viewed as
standing in the place of collateral. The presence of the group has been called a
form of “social collateral”. The NABARD task force, for instance, identifies
three ways of banking with the poor (a) by means of banking with the poor (b)
by means of conventional bank lending, linking SHGs with bank lending and (c)
banks lending to micro finance institutions for on lending to groups or
individuals. The task force goes on to say that the second and third methods are
characterized by low transactions costs and high repayment (NABARD, 2000).
As pointed out earlier micro credit means ‘small loans’ and the scale of
‘smallness’ varies many a time. The NABARD task force estimated the credit
100
requirements per family Rs.6000 in rural areas and Rs.9000 in urban areas but
recommended that average loan given to members of SHGs should be around
Rs. 1000 (NABARD, 2000).
The micro credit cell of the RBI, however, has proposed a ceiling of
Rs.25, 000 for micro finance and suggests that the ceiling may be raised to Rs.
40,000 for borrowers with a track record of regular repayment over two to three
years. Bank linkage are generally advanced for self employment projects, (some
times loans are also given for consumption as well) .Recently NABARD has
increased the ceiling to Rs.1, 00,000. In case of micro enterprises the ceiling
limit is Rs. 3 lakhs to 5 lakhs the importance and relevance of SHG- bank
linkage program has been accepted by Government of India (GOI) and the
program is declared as a national priority. Any SHG which completes 6 months
of active, disciplined functioning can approach bank for loan.
Table 4.6Distribution of SHGs on the basis of time lag in getting bank linkage
Sl. No.
SHPIs BREDS groups IKP groups Total
1 Between 0 - ½ year 38
(95.00)31
(77.50)69
(86.25)
2Between 1 and 1 ½ years
02(5.00)
09(22.50)
11(13.75)
Total40
(100.0)40
(100.0)80
(100.0)Source: Data collected through Field Survey Figures in brackets are percentage to total
The above table 4.6 gives the distribution of selected SHGs on the basis
of time lag in getting bank linkage. Majority of SHGs got bank linkage in less
than 1/2 year. In this study all the 80 SHGs of both the selected SHPIs had bank
linkage very quickly. In both the selected SHPIs majority of SHGs got access to
institutional credit within 0 to 6 months of formation. Sometimes delay in bank
linkage may be due to external factors like the bank manager denying on the
ground that some SHGs in the same village are default. One conclusion drawn
101
from the data is that two is no striking variation in the number of SHGs that got
bank linkage in a specific time period considered for analysis within the SHPIs.
E. Nature of the Current Borrowings
The nature of the current borrowings of the SHGs is indicated by the
purpose-wise distribution of bank linkage provided to the selected SHGs in both
the selected SHPIs. The details pertaining to the purpose-wise distribution of the
bank linkage extended to the selected SHGs in both the selected SHPIs are
presented in the following Tables 4.7 and 4.8.
Table 4.7Purpose-wise distribution of bank linkage-BREDS groups
(Rs. In lakhs)Sl. No.
PurposeAmount
sanctionedPurpose wise Proportion
1 Agriculture 5.10 15.00
2Coir making &Coconut oil
6.12 18.00
3 Minor Forest Produce 5.44 16.00
4 Leaf making 5.95 17.50
5 Money lending 4.06 12.00
6 Small business 4.42 13.00
7 Others 2.89 8.50
Total 33.98 100 Source: Data collected through Field Survey.
Table 4.8Purpose-wise distribution of bank linkage-IKP groups
(Rs. In lakhs)Sl. No.
PurposeAmount
sanctionedPurpose wise Proportion
1 Agriculture 6.66 17.402 Coir making &
Coconut oil4.02 10.50
3 Minor Forest Produce 11.48 30.004 Leaf making 6.51 17.005 Money lending 1.53 4.006 Small business 4.02 10.507 Others 4.06 10.60
102
Total 38.28 100 Source: Data collected through Field Survey
The data relates to the current loan the total bank linkage for the SHGs is
estimated at Rs. 33.98 lakhs and 38.28 lakhs for BREDS groups and IKP groups
respectively. Data on purpose wise bank credit reveals that animal rearing
absorbed a major share followed by agriculture. Dairy is an economic activity on
which major loan amount is used. This is understandable as many of the SHG
members are poor without land base, and in the absence of non-agriculture skills
the obvious choice is dairy. Members who have land base use bank credit for
capital formation in agriculture in the form of purchase of electric motor, oil
engine and agriculture equipment etc. About 16 per cent of bank credit in both
SHPIs is used for activities relating to services and business sectors. As far as
diversification of occupation is concerned few members have taken up
provisions store, Pan and tea stall in IKP groups. In case of BREDS groups
diversification in the employment is not reported. In IKP groups there is no
difference in the pattern of purpose wise utilization of bank credit. Yet,
difference exists with regard to proportion of credit used for different
purposes as is evident from the data. In BREDS, the pattern of purpose wise
utilization of bank credit is more towards services. However there is marginal
difference between the selected SHGs of both the selected SHPIs in case of
purpose-wise distribution of bank linkage.
F. Determinants of Current Borrowings of SHGs
Causality is crucial for empirical verification of postulated hypothesis as
well as policy prescriptions. This could be mostly accomplished through the
adoption of the familiar multiple regression analysis. With the helps of available
regression technique the determinants of current borrowing of the rural women
SHG members is analyzed in order to clearly established cause and effect
relationship. On the front of determinants of current borrowings purely, tested
above five variables are taken into consideration. The mathematical notation of
the function can be written as:
103
Y = F (WC, OCC, CE, PPA, ML) ……………………. (1)
Where: Y is total amount borrowed,
WC is required working capital (in rupees),
OCC is the current Occupation,
CE is borrowings diverted for consumption expenditure (in rupees),
PPA is the purchasing power of productive asset and
ML is money lending form the various sources.
While assuring that all the variables could have additive influence, the
model may be presented as:
Yi = a + b WCi + cOCCi + dCEi + e PPAi +fMLi+ Ui ……….. (2)
Where Ut is an error term and other variables are as explained above.
If the variables have multiplicative influence, the model can be presented as:
Yi = a WCib, OCCi
c, CEid, PPAe + MLi
f+ Ui …….………….. (3)
Logarithmic transformation of the model on both sides could give
LogYi = log a + b.log WCi + c.logOCCi + d.log CEi + e.log PPAi + f.logMLf +
log Ui …. (4)
In this study, the Logarithmic transformation is used because log liner
form is proved to be better than a linear form for standard specification of the
equation.
In the above model the following hypotheses are postulated in the present
study relating to determinants of current borrowings of the households.
The Improvements in levels of living increases the need for total working
capital expenditure required for their activities of the SHG members which in
turn will increase the demand for credit. So a positive relationship is expected
between working capital expenditure and total amounts borrowed by the SHG
members. The nature of the current occupational earnings influences the current
borrowings of the SHG members in the positive direction hence a positive
relationship is expected between the nature of current occupation and total
104
current borrowings. The extent of borrowings diverted for consumption
expenditure will increase the further need of current borrowings. Hence a
positive relationship is expected between borrowings diverted for consumption
expenditure and level of current borrowings of the SHG members. Generally the
extent of the purchasing of productive assets by the SHG members by the SHG
members determines the credit needs of the SHG members. The above
hypotheses have been empirically examined and in the selection of suitable
model, the suitable economic and statistical criteria have been employed. The
regression equations are estimated relating to all the selected SHG members,
SHG members of BREDS groups and SHG members of IKP groups separately.
The results are provided in the following Table 4.9.
Table 4.9Regression equations analyzing determinants of current borrowing of
Selected SHG members
SHPI InterceptCoefficient of independent variables
R2F.
valueWC OCC CE PPA MLAll SHG members
184.070.47*(2.96)
0.26**(2.13)
0.30*(2.86)
0.43**(2.21)
0.56(0.41)
0.78 123.62
SHG members of BREDS groups
197.320.56*
(3.04)0.78**(2.01)
0.26**(1.98)
0.16**(1.86)
0.13(0.32)
0.71 216.34
SHG members of IKP groups
87.280.72**(2.05)
0.61(0.16)
0.32*(2.98)
0.78(0.55)
0.61**(2.10)
0.66 162.73
Note: Figures in the parenthesis are t ratios * Coefficients are significant at 1per cent level; ** Coefficients are significant at 5 per cent level; *** Coefficients are significant at 10 per cent level,
The regression results presented in the above Table indicate that the
coefficient of multiple determinations is found significant in all the three
equations. The correlation coefficient of the aggregate model is as high as 0.78
per cent. The estimated coefficients of the variable WC (the requirement of
Working Capital) is found significant at 1 per cent level in case of all SHG
members, it is also significant at 1 per cent level for SHG members of BREDS
and 5 per cent significant at the level of SHG members of IKP groups. Variable
CE (Consumption Expenditure requirement of members) found 1 per cent level
significance in the case of all the SHG members taken together and in case of the
105
SHG members of IKP groups. In case of SHG members of BREDS it is
possessed statistical significance at 5 per cent level. The variable PPA (Purchase
of Productive Assets) is found significant at 5 per cent level for all SHG
members as whole and SHG members from the BREDS and it is not significant
at even at 10 per cent in case of SHG members from the IKP groups. Similarly
the variable OCC (Occupational requirement of credit) possessed 5 per cent level
of statistical significance for all SHG members and for the members of BREDS.
It is possessed with 10 per cent level significance in the case of SHG members of
IKP groups. The coefficient of the variable ML (Required amount for Money
Lending) is not arrived statistical significance at any level in any equation.
However, all the variables turned out with theoretically expected signs in all
equations.
The above analysis ultimately reveals that, working capital expenditure
requirement, Consumption expenditure requirement are major determinants of
current borrowings of all the SHG members. Occupational pattern of the SHG
members is also determine the current borrowings of the members. The
requirement of credit for money lending is not able to determine the current
borrowings of the SHG members. Across SHG members from different SHPIs in
case of the SHG members from BREDS, Working Capital Expenditure and
Purchase of Productive Assets emerged as important determinants of their
current borrowings. In case of the SHG members of IKP groups Consumption
expenditure and working capital expenditure variables emerged as important
determinants of their current borrowings.
G. Credit operations and Utilization of group funds
The SHGs plays a significant role in catering to the credit requirements,
of poor and currently has emerged as an important link. For poor in general
there is a thin line distinguishing consumption credit and production credit.
Further, these poor households need ‘micro credit’ sometimes instantly to meet
some emergencies. All definitions concur on micro credit as the provision of
‘small loans’, the scale of ‘smallness’ vary depending on the need. The poor
106
depend on institutional sources of production and investment requirement. But
for consumption needs like social functions, health and educational needs the
poor exclusively depend on non-institutional sources viz., money lenders and
traders. These non-institutional sources charge high interest rates there by
become a major share of the income of the poor. Further, there is inter-
generation transfer of credit burden.
The purpose wise classifications of group credit details of the two SHPIs
are given in table 4.10& 4.11. The data here is limited to only current
borrowings only. The total amount of borrowings for the selected SHGs in
BREDS is about Rs. 20.32 lakhs and Rs. 26.54 lakhs in IKP groups. Among two
SHPIs the SHGs, those formed in IKP groups have relatively extended more
credit than in BREDS, while in the IKP groups, SHGs has comparatively lent
more credit. The average loan per member is estimated at Rs.3440 in BREDS
groups and Rs.3375 in IKP groups respectively.
Table 4.10Purpose-wise classification of group credit-BREDS groups
(Value in Rs.)Sl. No.
Purpose Group creditPurpose wise proportion
1 Consumption expenditure8,21,626(3,395)
40.44
2 Business1,86,520(3,462)
9.18
3 Minor Forest Produce3,76,420(3,255)
18.52
4 Educational expenses40,400(3,375)
1.99
5 House repairs1,96,400(3,630)
9.67
6 Money lending1,27,600(3,510)
6.28
7 Purchase of animals1,07,934(3,660)
5.31
8 Agriculture1,75,100(3,500)
8.61
Total20,32,000
(3,440)100.0
Source: Data collected through Field Survey
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Figures in brackets are per member credit
The details of purposes on which the credit borrowed from group funds
was spent in case of BREDS groups members reveal that the distribution pattern
is no way different from that of IKP groups. The purpose wise classification of
group credit shows that about 50 per cent of loans are for meeting consumption
expenses in both the selected SHPIs. If the loan amount borrowed to meet social
functions is added the percentage would increase to about 70 per cent.
Interestingly few members also use the borrowed amount for productive
purposes like crop expenses and petty business needs. Investment like house
repairs, repayment of hand loans are some other purposes for which amount is
borrowed. Thus, a major proportion of group credit was used for unproductive
yet necessary household consumption expenditure. In the absence of SHGs these
poor women rely on non institutional sources for money. Thus, to a very great
extent the SHG movement is successful in relieving the poor women from the
clutches of the money lender.
Table 4.11Purpose-wise classification of group credit - IKP groups
(Value in Rs.)Sl.
No.Category Group credit
Purpose wise proportion
1 Consumption expenditure10,83,440
(3,367)40.82
2 Business1,48,100(3,180)
5.58
3 Minor forest produce5,48,300(3,300)
20.66
4 Educational expenses39,400(3,100)
1.48
5 House repairs1.35,300(3,397)
5.10
6 Money lending43,800(3,105)
1.65
7 Purchase of animals2,00,360(3,650)
7.55
8 Agriculture 4,55,300(3,270)
17.16
Total26,54,000
(3,375)100
Source: Data collected through Field Survey
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Figures in brackets are per member credit
From the above table 4.11 it can be noticed that in IKP groups the major
share of the group credit is to spend on household consumption needs. On the
whole, the members of the SHGs promoted by BREDS spent Rs.8, 21,626 on
consumption while those SHGs promoted by IKP groups incurred Rs.10,
83,440 /- on the same item. Consumption is a major expenditure in human lives
especially in case of poor households and the data is in consonance with it. Next
to consumption the important item of expenditure is medical care for which
money is borrowed. Education seems to be a low priority area as expenditure on
festivals, business, repairs and ceremonies has outsized the expenditure on
education. The expenditure on education is less because in India it is free in all
interior areas. Of all the items or purposes for which group credit was obtained,
ceremonies were the only item for which more group credit was obtained.
Ceremonies were the only item which had no concrete utility yet expenditure on
ceremonies was next only to consumption. It shows the importance of the people
attach to religious ceremonies and rituals. Expenditure on agriculture occupies
fourth position after consumption, ceremonies and medical expenses.
Table 4.12Details of purpose -wise and priority-wise utilization of loans by the SHG
members
Sl. No Activities BREDS groups IKP groups Total1 Domestic
ceremonies128
(47.94)139
(52.06)267
2 Purchase of productive assets
145(87.34)
21(12.66)
166
3Agriculture activities
132(77.20)
39(22.80)
171
4 Children’s education
64(70.33)
27(29.67)
91
5Family health
123(57.21)
92(42.79)
215
6Repaying old debts
131(74.86)
44(25.14)
175
Source: Data collected through Field Survey Figures in brackets are percentage to total.
The table 4.10 shows the purpose wise priority wise utilization loans by
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the SHG members in the selected study area. Out of the 267 respondents 52.06
per cent of the respondents belonged to IKP groups, 47.94 per cent of the
respondent belonged to BREDS groups who are utilized their loans for their
domestic ceremonies. 87.34 and 12.66 per cent of the respondents both the
SHPIs are utilized their loan for Purchase of Productive activities, 77.20 and
22.80 per cent of the respondents belong above two SHPIs, who are utilized their
loan for Agricultural activities. 70.33 and 29.63 per cent of the respondents
utilized their loan for the purpose of children’s education from the above two
SHPIs. 57.21 and 42.79 per cent of the respondents utilized their loan for the
purpose of family health. 74.86 and 25.14 per cent of the respondents utilized
their loan for the purpose of repaying old debts.
The findings of the study therefore show that there is a drastic change in
the pattern of purpose-wise and priority wise utilization of loans by the SHG
members in economic activity is more among the members of BREDS groups
rather than the members of IKP groups.
H. Repayment of Group Credit
Repayment of group credit is one of the important yard stick to assess the
efficient functioning of the SHGs. Mobilizing internal savings and by efficient
utilization of the mobilized savings, the SHG members are expected to learn the
management of SHG. This will help these SHGs obtain access to the bank credit.
Recovery of the loan amount borrowed from the SHGs own funds is ascertained
and analyzed separately for each SHPI. Recovery of loan amount is not analyzed
separately for different purposes as the conditions of loan, the interest etc., are
same for all purposes. In case of BREDS groups about 78.64 per cent of the
current borrowings from group credit are repaid, while this figure is estimated at
nearly 67.74 per cent in case of IKP groups.
110
Table 4.13Details of repayment of group credit - BREDS groups
(Amount in Rs.)Sl. No.
Items BREDS groups
1 Total loan Amount26,54,000
(100)
2 Amount repaid20,87,000
(78.64)
3 Amount outstanding5,67,000(21.36)
Source: Data collected through Field Survey Figures in brackets are percentage to total.
From the above table in case of BREDS groups the SHGs are marginally
ahead of their counterparts in the repayment of loans. Their total loan amount is
Rs.20,87,000 and the repayment is to the tune of 78.64 per cent of the loan
amount is recovered. The difference in loan recovery is too narrow to draw any
significant conclusions. Members of the group exert pressure (peer pressure)
regarding loan repayment. This is because proper repayment of group credit
enables the group to have bank linkage.
Table 4.14Details of repayment of group credit-IKP groups
(Amount in Rs.)Sl. No. Items IKP groups
1 Total loan Amount20,32,000
(100)
2 Amount outstanding6,55,489(32.26)
3 Amount repaid13,76,511
(67.74) Source: Data collected through Field Survey Figures in brackets are percentage to total.
The outstanding amount against group credit in case of SHGs promoted by
both SHPIs reveals that the SHGs promoted by the BREDS are far ahead of their
counterparts in the repayment of loans. They had paid back 78.64 per cent of the
group credit. Thus, from the above discussion on loan recovery clearly reveals
111
that performance is considerably good in case of the SHG members of BREDS
groups and the performance is not that much good in case of IKP groups.
The following economic variables are identified as the influencing
factors of the recovery performance. The ratio of total demand to number of
supervisors is considered as an important economic variable because if the
number of supervisors is increased, over dues will decline. Proper timely and
active supervision of the government agencies checks the attitude of the SHG
members directing of loans for unproductive purposes. Also it helps the SHG
members to invest it on the purpose which it is granted and helps them for
repayment of the loan, so it is hypothesized that there is an inverse relationship
between supervision and the percentage of over dues to total demand. The
common reason noticed for poor repayment of credit in the rural areas is that,
due to the high degree of their economic and social backwardness they will have
tradition bound custom bound high level consumption patterns. Much proportion
of their loan amounts generally will be diverted on social and religious
performances. The high level unproductive consumption patterns restrict the
level of repayment of institutional loans.
4.3. Organizational Aspects of the Selected SHGs:
In this section an attempt is made to analyze the different issues relating to
the organizational aspects of the selected SHGs in the selected two SHPIs of the
Srikakulam district.
A. Motivation Impact
It is not enough that training facilities and other socio-economic
development programmes are provided for women in need the objective of such
programmes will be fulfilled only if the target population knows about the
facilities available and can make use of them as most of the women covered
under these programmes are poor women and it is important that the
dissemination of information or motivation must be carefully planned.
112
Table 4.15Motivation for joining in the different types of Education centers
Sl. No Motivation BREDS groups IKP groups Total
1To help the women to be literate
88(44.00)
61(30.50)
149(37.25)
2To participate in the literacy drive
64(32.00)
67(33.50)
131(32.75)
3To join in the SHGs not applicable
48(24.00)
72(36.00)
120(30.00)
Total 200(100)
200(100)
400(100)
Source: Data collected through Field Survey Figures in brackets are percentage to total.
The above table shows the percentage of motivation for joining the other
non-SHGs members in non-formal education centers by the SHG members.
Attendance to literacy centers and non-formal education centers reflect the
attitude of the people towards education and human development. The data
indicate that some of the SHG members motivated one by many ways like to
help the women to be literate, to make them to participate in literacy drive and
encourage them to join in the educational centers. Among the SHG members
from the BREDS groups, 44 per cent are motivated. 32.00 per cent of the SHG
members of IKP groups are able to participate in the literacy drive and 24.00 per
cent encourage joining them in the SHGs. Thus, it is clear that the SHG
members from IKP groups are showing much interest in attending adult literacy
centers. It clearly indicates the participatory role of the SHG members of
BREDS groups are participating in socio-economic as well as human
development programmes.
B. Participation in the proceedings of SHGs
The success of empowerment through Self-Help Groups movement
produced a tremendous awareness generation effort among young girls and
women about making them Self-Reliant through the capacity of earning their
own livelihood. It is quite interesting to note that all the habitations in the state
have at least one woman Self-Help Groups to enable the women come together
on common platform to decide on all issues concerning their day-to-day life.
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They are quite active in participating in various committees without any fear
because of realizing the value of the team spirit.
Table 4.16Percentage of participation of the SHG members in the proceedings of
SHGs meetingsSl. No Proceedings BREDS groups IKP groups Total
1Fear in addressing gathering
79(39.50)
136(68.00)
215(53.75)
2Sharing views with official effectively
48(24.00)
22(11.00)
70(17.50)
3Sharing view with members effectively
73(36.50)
42(21.00)
115(28.75)
Total 200(100)
200(100)
400(100)
Source: Data collected through Field Survey Figures in brackets are percentage to total.
The above table gives the per centages of SHG members participating in
the proceedings of meetings or their communication skills. Out of the total SHG
members, 53.75 per cent of SHG members reported that they have fear in
addressing a gathering or a group, followed by sharing views with members
effectively (28.75 per cent) and sharing views with Government officials (17.50
per cent). Among the members of BREDS groups are more than half (36.50 per
cent) reported that they share views with the members effectively, 24 per cent
reported that they share views with Government officials effectively, while
39.50 per cent have fear to address a gathering. On the whole, in the
participation of women in the proceedings of the Self-Help Groups meetings, the
proportion of members of BREDS groups (36.50 per cent) are much higher than
the proportion of members of IKP groups (21.00 per cent).
It is important to note that there is a lot of difference of women SHG
members in teaching problems before and after being the members of SHGs.
Previously the women neither come out of the house, nor discussing problems
with their members, family members or the Government officials. There is a
change in being members of SHGs over various women’s issues and dealing the
issues with the Government employees and NGOs. The source of credit has been
changed due to joining in the Self-Help Groups programme. The important
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factor in encouraging strategy is to save the poorest women from the shackles of
money lenders and land lords.
Table 4.17Distribution of SHG members who got credit before and after joining SHGs
Credit sourceBREDS groups IKP groups Total
Sl.No
Before After Before After Before After
1 Money lender58
(29.00)10
(5.00)105
(52.50)70
(35.00)163
(40.75)80
(20.00)
2 Relatives48
(24.00)20
(10.00)30
(15.00)20
(10.00)78
(19.50)40
(10.00)
3 Own money27
(13.50)45
(22.50)10
(5.00)8
(4.00)37
(9.25)53
(13.25)
4Borrowed fromland lords
42(21.00)
-55
(27.50)67
(33.50)97
(24.25)67
(16.75)
5Govt. and NGOs
25(12.50)
125(62.50)
-35
(17.50)25
(6.25)160
(40.00)Total 200
(100)200
(100)200
(100)200
(100)400
(100)400
(100)Source: Data collected through Field Survey Figures in brackets are percentage to total.
The findings of the table 4.17 reveal that there is a distinct change in the
source of credit patterns by the SHG members before and after joining the SHG
programme. It is significant to note the proportion of members from BREDS
groups who get credit from own source by the SHGs is increasing.
C. Capacity building training
SHG members have to attended the capacity-building training in order to
equip with impart skills regarding personal development, book-keeping and
management, stress management etc. This reflects the impact of SHGs
movement on the life style of selected SHG members. The information relating
to the SHG persons attended to the capacity building training in both the selected
SHPIs is presented in the following Table 4.18.
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Table 4.18
Percentage of attendance of SHG members in capacity building training
Sl. No
Attendance of capacity building
BREDS groups IKP groups Total
1Yes 162
(81.00)89
(44.50)251
(62.75)
2No 38
(19.00)111
(55.50)149
(37.25)Total 200
(100)200
(100)400
(100)Source: Data collected through Field Survey Figures in brackets are percentage to total
From the above Table it can be noticed that as a part of the process by
employment, 62.75 per cent of the SHG members reported that they have
attended capacity building trainings. Among the members from the BREDS
groups, 81 per cent of SHG members have attended the capacity-building
training in order to import skills regarding personal development, book-keeping
and management, stress management etc. this reflects the impact of SHGs
movement on the life style of selected SHG members.
D. Performance of Book-Keeping by the SHG Members
The SHG members are expected to maintain all the records relating to the
group activities. They have to keep book-keeping in an orderly manner. The
following Table 4.19 provides information relating to how far the selected SHG
members in both the SHPIs are able to maintain book keeping.
Table 4.19Performance of book-keeping by the SHG members
Sl. No
SHG membersBREDS groups IKP groups
Yes No Total Yes No Total
1Performance of the SHG members account register
118(46.46)
82(56.16)
200(50)
85(45.21)
115(54.25)
200(50)
2Knowledge of savings books
136(53.54)
64(43.84)
200(50)
103(54.79)
97(45.75)
200(50)
Total 254(100)
146(100)
400(100)
188(100)
212(100)
400(100)
Source: Data collected through Field Survey Figures in brackets are percentage to total
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Above table shows the performance of book-keeping by the SHG
members. One of the findings of the study shows that being SHG members, their
capacity to maintain book-keeping is increasing in themselves and 46.46 per cent
reported that they learnt the training how to keep the account registers and 53.54
per cent reported that they have knowledge of savings books.
E. Knowledge about computers by the SHG members
An attempt is made to know the details relating to their knowledge about
computers and internet by the selected SHG members. The information relating
to the knowledge about computers and usage of internet facility by the selected
SHG members is presented in the following Table 4.20.
Table 4. 20Knowledge about computers by the SHG members
Sl. No
Knowledge of computer
BREDS groups IKP groups Total
1 Yes5
(2.50)2
(1.00)7
(1.75)
2 No195
(97.50)198
(99.00)393
(98.25)
Total200
(100)200
(100)400
(100) Source: Data collected through Field Survey Figures in brackets are percentage to total
The above table 4.20 shows that among the sample SHG members, 1.75
per cent of the SHG members have knowledge about computers and internet.
The proportion of SHG members having knowledge about computers and
internet is higher in case of the selected members from the BREDS groups (2.50
per cent) than the SHG members selected from the IKP groups (1 per cent).
Though the Government of Andhra Pradesh is reputed for its information and
technical knowledge throughout the globe, the access to this knowledge is not
available to all selected villages. Hence, the Government has to put more steps to
create knowledge about computers in order to increase the market facilities
through internet to the rural women who are living in the interior areas.
117
4.4. Assessment of Functioning of the Selected SHGs:
The SHGs in order to accomplish their objectives of empowering women
need to be strong and sound financially and must be functionally very systematic
and organized. Improper functioning of SHGs results in loss of confidence by
the poor women on these groups and may eventually lead to liquidation of the
groups. In view of this, the functional and management aspects of SHGs assume
greater significance. Analysis on both functional and management aspects will
facilitate to have an understanding of the overall performance of the SHGs. An
attempt is made here to analyze the functional and management aspects of the
selected SHGs. This analysis involves three steps, identification of indicators
which would capture or have bearing on the functioning of the SHGs, assigning
weights to the indicators and calculation of composite weight for each SHG.
NABARD (1998) has identified certain indicators and termed them as
‘check list’ and advised banks to assess the performance of SHGs before
extending bank linkage, using the check list. This study used some of the
indicators of NABARD and added some more. These indicators are: Size of the
SHG, Economic status of the members, Literacy status of the members, Amount
to save, time period for routine savings collection, Time taken from SHG
formation and opening bank account, Number of meetings held in a month,
Timing of the routine meetings, Attendance of members during the past 10
meetings, Participation of members in the discussion. Issues relating to child and
women health and family planning are discussed. Percentage of utilization of
internal funds, Loan recovery, Maintenance of records of the group, Awareness
levels of SHG members of various governments’ welfare and development
programs are taken in to consideration.
The second step is assigning weights. The indicators listed above have
hierarchy of characteristics are mentioned here. Weights are numerical values
(3, 2, 1, and 0) assigned in descending order by considering place in the
hierarchy of each indicator. For example, in case of indicator 7 (number of
meetings held in a month) the assigning weights is as follows. Once in a week (4
118
times in a month)-weight 3, once in a fortnight (2 times in a month) - weight 2,
once in a month-weight 1.
In case of indicator 8 i.e., timings of the routine meeting of the SHG,
NABARD’s direction is to hold the meeting from 7 pm onwards. This is the time
when poor women return from work and therefore can actively participate in the
proceedings. If the meeting is held in the morning it may not be convenient for
all the members to attend and actively participate as they will be in a hurry to
leave for their work. For this indicator the assigning of weights is 7 pm onwards-
weight 3. 8 am onwards-weight 2, No specific timings-weight 1. The following
Table provides details of indicators and weight.
119
Table 4.21Details of Indicators and Weights
Sl. No. Indicator Definition Weight
1 Size of the SHGa) 15 to 20 memebrs 3b) 10 to 15 memebrs 2c) Less than 10 members 1
2 Economic status of membersa) All are below poverty line (BPL) 3b) Majority are BPL 2c) Few are BPL 1
3 Literacy status of members
a) More than 50 per cent of members can read and write
3
b) 25 to 50 per cent members can read and write
2
c) Less than 25 per cent members can read and write
1
4 Amount to be saveda) Fixed 2b) Varying 1
5 Time period for routine savingsa) Weak 3b) Fortnight 2c) Month 1
6Time taken from SHG formation and opening of bank saving account
a) Within 3 months 3b) 3 to 6 months 2c) more than 6 months 1
7Number of meeting held in a month
a) Four time (every weak) 3b) Two times (every fortnight) 2c) Once (monthly) 1
8 Timing of the routine meetinga) 7 pm on wards 3b) 8 am 2c) No specific timings 1
9Attendance of members during past 10 meetings
a) More than 90% 3b) 70 to 90% 2c) Less than 70% 1
10Participation of members in the discussion
a) Majority 3b) Few 2c) Leader only 1
11Discussion of issues relating of women and child health
a) Discussed regularly 2b) Occasionally 1
12Percentage of utilization of internal funds)
a) Above 90% 3b) 70% to 90% 2c) Less than 70% 1
13 Loan recoverya) Above 90% 3b) 70% to 90% 2c) Less than 70% 1
14Maintenance of records of the group
a) Regular and up to date 2b) Irregular and not up to date 1
15Awareness of government development and welfare programmes
a) All members are aware 3b) Majority are aware 2c) Only few aware 1
Source: NABARD Report 2008-2009
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While estimating the weight scores of the above performance indicators,
the third step is calculating composite weight to each SHG. The composite
weight is sum of weights of all indicators listed in the table. For example: if a
selected SHG gets the best weight for all the indicators the total weight would be
42 (which most unlikely to happen). After calculating the total weight for all the
SHGs they are classified into four categories. Table 4.23 gives these details. The
criterion for classification is:
Less than total weight score 10 - very poor performance,
11 to 20 total weight - poor performance,
21 to 30 total weight - good performance,
31 Above - Very good performance
The performance scores of all the selected SHGs are estimated and the results
are presented in the following Table 4.22.
Table 4.22Percentage Distribution of SHGs on the Basis of performing Score
Sl. No
SHPIsVery poor
Poor GoodVery good
1 BREDS groups 4 22.0 53.0 21.0
2 IKP groups 9 37.0 42.0 12.0 Source: Data collected through Field Survey
From the above Table it can be noticed that 21 per cent of the selected
groups from BREDS and only 12 per cent of selected groups from IKP are
very good in performance as these SHGs got a total composite weight ranging
from 30 to 42. At the same time, it is to note that 9 per cent of groups in case of
IKP and 4 per cent groups in case of BREDS are registered as very poor
performing SHGs. Similarly 22 per cent of groups selected from BREDS and 37
per cent of the selected groups from the IKP are classified as poor performing
groups. One fact clearly emerged from the evidence is that majority of the SHGs
of both SHPIs are classified as good performing groups.
Having explained the pattern of distribution of SHGs based on
composite weights, the analysis shifts to examine the relative dispersion in the
121
composite total weights score of the selected SHGs with the help of Coefficient
of variation. These values are given in table 4.23.
Table 4.23Details of dispersion of values of performance weight age score
Sl. No Year BREDS groups IKP groups
1 Mean 28.6 29.7
2 Standard Deviation 6.1 6.7
3 Co-efficient of variation 21.33 22.5 Source: Data collected through Field Survey
From the above Table it can be observed that as per the value of the CV
there is much variation in the performance of the SHGs belonging to the two
SHPIs. The value of Coefficient of Variation presented in the above Table
reveals that, relatively speaking there is greater variation in case of groups
belonging to BREDS than the groups belonging to IKP in case of the dispersion
values of performance weight age scores are concerned.
4.5. Conclusion:
All the selected SHGs from both the SHPIs have completed 3 years of
functioning. In both the selected SHPIs considerable numbers of SHGs are
functioning for over 5 years indicates sustenance of SHGs over a period of time.
Nearly 80 per cent of the selected SHG members are depending on agriculture
and allied activities in case of both the selected SHPIs. About 60 per cent of the
studied selected SHGs belonging to both SHPIs are able to get matching grant
within 6 months of formation. A good proportion of the selected SHGs in both
the SHPIs have limited extent of. Purpose wise classification of credit borrowed
from groups own funds reveal that consumption and agriculture activities are the
two important items for which the credit is utilized in both the selected SHPIs.
The analysis of determinants of current borrowings reveal that, Working
Capital Expenditure requirement, Consumption expenditure requirement are
major determinants of current borrowings of all the SHG members. Occupational
pattern of the SHG members is also determine the current borrowings of the
members. The requirement of credit for money lending is not able to determine
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the current borrowings of the SHG members. Across SHG members from
different SHPIs in case of the members from BREDS groups Working Capital
Expenditure and Purchase of Productive Assets emerged as important
determinants of their current borrowings. In case of the members of IKP groups
Consumption expenditure and working capital expenditure variables emerged as
important determinants of their current borrowings.
Recovery of amount borrowed from group funds reveals a very
encouraging picture as more than 73 per cent of the group credit is repaid in case
of BREDS groups but relatively lower proportion recovery is recorded in case of
the IKP groups where the selected SHGs repaid amount of credit is very poor.
High differences in respect of recovery of loan amount are noticed between the
SHGs selected from the two SHPIs.
In both the selected SHPIs, majority of the SHGs are able to get bank
credit linkage in less than six months of functioning. There is no striking
variation in the number of SHGs that got bank linkage in a specific time period
considered for analysis. Purpose wise classification of bank credit reveals that
animal rearing absorbed a major share followed by agriculture. Coir making,
coconut oil preparation, minor forest produce are the emerging economic
activities for which major loan amount is used. Analysis on the performance of
the SHGs revealed that 35 per cent of the selected SHGs in case of BREDS and
27 per cent in case of IKP groups are very good in performance. Further, many
of the selected SHGs in both the selected SHPIs are classified as poor
performing. There is significant difference in the performance of selected SHGs
in both the selected SHPIs regarding the overall performance. The members
selected from the BREDS groups are able to utilize the SHG activity in more
productive manner than the members selected from the IKP groups. There is
much evidence indicating that in both the selected SHPIs there is marginal
variation in the functional and management aspects of the SHGs. This may be
attributed to the more extent of infrastructure and facilities available to the
members selected from the BREDS groups, who are having added advantage
when compared to the members selected from the IKP groups.
123
References
1. Das Gupta.A. “Selp Help Group and Micro Credit rural Banting for
women’s social welfare, March 2000.
2. Dwarakanath.H.D. Rural Credit and women Self Help groups,
Kurukshetra, November 2002. Vol.1 pp. 8-15
3. Harikanth.Ch. Harikishna, “Micro Finance and Self Help Groups in
Andhra Pradesh” Issues and Chalenges, Satavahana journal, vol.1 No.1,
September 2008. Pp 140-141.
4. Mahendra Varman.P. “Impact of Self Group on formal Banking Habits”
Economic Political weekly, Vol.XL, No. 17, April 23, 2005, pp. 1705-
1713.
5. M.S.Sriram, “ Microfinance and State Exploring Areas and Structures of
Collaboration”, Economic Political Weekly, vol.54, No. 11, April 23,
2005, pp. 1704.
6. Dr.Suresh.M.Sambaiah, “Micro Finance In India-New Policy Initiatives”
Satavahana Journal.Vol.1. September. 2008, pp. 100.
7. Navin Bhatia, Anju Bhatia “Micro Finance Institutions of Bangladesh
Lessons for India” Kurukshetra, Feb 2004. Pp.22.
8. U.B.Singh, Himmat Singh and Gurnam Singh, “Role of Self help Groups
in the Shiwalik Foot hills of Haryana”. Indian Journal of Agriculture
Economic, July-Sept. 2001, pp. 472-473.
9. Mahammad Yunus, Grammen Bank, Micro Credit and Millennium
development Goals, 2004 epw, pp. 56.
10. Dr.C.L. Dadhich, “Microfinance for Poverty alleviation in India”,
Vol.XXXI, No.3,4, April-june, 2002 (epw).
11. N.Jayaseelan, “Risk Management in Microfinance Agriculture”- A
National Journal of Agriculture&Rural Development, Aug-Sep 2006,
p.56.
12. S.Madheswarm and Anita Dharmadhikar, “Empowering Rural Women
Through Self Help Groups lessons from Maharastra rural credit project,
epw, June-July, 2006.
124
13. T.S.Raghavendhra, “Three Groups in shinnoga District performance
evolution of Self Help Groups”, Indian Journal of Agriculture Economics,
July-Sept 2001, pp. 465-466.
14. Rimjhim Mousumi Das., Micro-Finance through SHGs: A boon for the Rural
Poor’; Kurukshetra,Feb,2004, New Delhi,P. 43.
15. Om Raj Singh ‘Role of NGOs in Fostering Self-Help Groups: A Case Study
of MYRADA’, Kurukshetra,Feb, 2003,P. 34.
16. Joseph Lalrinliana, and Easwaran Kanagaraj, ‘SHGs and Rural Development
in Mizoram, Kurukshetra,Jan, 2006,p.37.
17. NABARD, ‘Banking with the Poor, A Hand Book on Self-Help Groups’
NABARD,Hyderabad,2003,pp,4-5.
18. Tamil Selvi, P., and Ratha Krishana,T., ‘Role Performance of SHG Leaders’
Social Welfare,Jan, 2004, p.38.
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