Chapter II

Microfinance in India

Microfinance in India - How it all began?

The international consensus on formal-informal linkages and related issues can be gauged

from the main conclusion of the Third International Symposium on the Mobilisation of

Personal Savings in Developing Countries organised by UN in 1984 as mentioned in the

previous chapter. First official interest in informal group lending in India took shape

during 1986-87 on the initiative of NABARD. Certain research projects on Self-Help

Groups (SHGs) were initiated as a channel for delivery of microfinance in the late 1 980s.

Amongst this the Mysore Resettlement and Development Agency (MYRADA) sponsored

action research project on "Savings and credit management of SHGs" was partially

funded by NABARD in 1986-87. In 1988-89, in collaboration with some of the member

institutions of the Asia-Pacific Rural and Agricultural Credit Association (APRACA),

NABARD undertook a survey of 43 NGOs in 1 I states in India, to study the functioning

of microfinance SHGs and their collaboration possibilities with the formal banking

system. Both these research projects threw up encouraging possibilities and NABARD

initiated a pilot project called SHG linkage project (Satish 2005).

But by then microfinancing by non-formal organisations had already started in India.

Self-Employed Women's Association (SEWA) owned by women of petty trade groups

was established on co-operative principles in 1974 in Gujarat. The earliest steps in

microfinance in India can be traced to this initiative undertaken for providing banking

services to the poor women employed in unorganised sector in Ahmedabad. Shri Mahila

SEW A Sahkari Bank was set up by registering it as an urban Co-operative bank. Since

then the bank has been providing banking services to the poor. This Microfinance

Institution (MA) model . has not been replicated elsewhere in the country, though

'Shreyas' in Kerala and 'Working Women's forum' (WWF) in Tamil Nadu were set up

with the objective of promoting people's co-operatives.

37

At the national level, while the SHG movement has had a longer history through NGOs'

work at the community level, the linking of SHGs to microfinance is of more recent

origin. It is only in the late 1980s that a few NGOs initiated experimentation in

channelising microfinance through SHGs mobilised by them. MYRADA mobilised

multi-purpose SHGs around group savings and introduced credit. Professional Assistance

for Development Action (PRADAN) in its Madurai project formed women's SHGs with

the explicit objective of mobilising savings and rotating this as credit to group members,

eventually towards the goal of forming a community banking system. The following table

presents the operational features of different microfinance models prevalent in India.

Table 2.1: Operational Features of Different Microfinance Models in India

Operational Features SHG Grameen (GB) Individual Banking

Client Groups Primarily women Primarily women Primarily men

Service focus Savings and credit Credit-regular cycle Individual clients

Role of MFI and Staff Guide and facilitate Organise (groups Organise

(groups may develop dependent on Staff)

autonomy)

Meetings Monthly Weekly Individual transactions-

often daily

Savings deposits Rs 20- I 00 per month Rs. 5-25 per week Flexible

Interest on Savings Bank rate (4.25% + 6-9% 6%+

Profit share)

Initial loan size Rs. 5000-1 0000 Rs. 2000-5000 Rs. 5000-15000

Effective Interest rate 24-28% 32-38% 23-38%

(usual range)

Insurance At a very preliminary stage: usually loan-linked, some life and Health:

Sometimes links to National companies

Development Services Some Associated A few small social Enterprise support

Programmes projects

Source: Smha (2005)

As can be seen from the table above group-based MRs target women as clients. This is

because they not only target poor people but the most vulnerable section of the poor. It

has also been proved by a series of studies in Bangladesh that improving the conditions

38

of poor females has positive effect on children's education and health (Pitt et al 1 998).

Before comparing the two main models of microfinance viz., the SHG and GB model we

consider their special features in the next sections.

Grameen Bank Groups

This model was developed and practised in Bangladesh (as we have mentioned in the

previous chapter). The groups are small mainly five members to start with thrift. They

don't manage their resources. The individual savings are deposited in the bank, and the

member gets loan directly from the bank. The GBG only helps the bank to screen the

borrowers and ensure repayment. Although the bank benefits, the GBG does not develop

any skill in financial management. In fact it does not have much financial resources to

manage. Although 0.5% of the loan amount is deducted to develop a group fund, that is

negligible in comparison to at least 2% per month of rate of interest. The GBG thus

permanently depends on the bank or the NGO promoting it. The banks have lent mostly

to women GBGs and the repayment rates are almost 100%. The socio-economic

environment has also been affected with increase in income generating potential of the

rural women. Pakistani economist Abidjan has raised a few questions about the GB

model used in Bangladesh and elsewhere. According to him micro-credit has, in some

circumstances, contributed positively to help the poor survive economic crises in the

short term but its effect on women empowennent IS questionable

( www .microcreditsummi t .org).

In India very few NGOs like ADITHI in Bihar, Activists for Social Alternatives (ASA) in

Tamil Nadu, Loyalam Bank of Rural Development and Organisation (RDO) in Manipur

and Society for Helping and Awakening Rural Poor through Education (SHARE) in

Andhra Pradesh use GB model for group lending (Tiwari and Fahad 1 997). Only one

commercial bank the Oriental Bank of Commerce (OBC) is experimenting with the GB

model in Dehradun in Uttaranchal and Hanumangarh in Rajasthan (Rao et al. 2001 ). In a

span of four years, since 1997, OBC has expanded the GB model to 64 villages with 769

groups and 3,845 members. Rs. I 0.2 million in savings has been generated and Rs.35.1

39

million has been disbursed, out of which 64% has already been repaid. A facilitator who

is paid an honorarium by the group members maintains all group level accounts. The

success of the project can be assessed from the study carried out by Dadhich (200 I) on

the specialised branch of OBC in Rudrapur village in Vikasnagar block of Dehradun

district covering 41 vi11ages with 447 women Groups and 3 male groups. The project has

brought about perceptible changes in the lives of poorer people with a large number of

women taking up subsidiary occupations like manufacturing of pickles, dairy, grocery

shops and diversification of agricultural activities. Consequently family incomes have

substantially increased along with real empowerment of women. This success was

achieved at economically viable costs. An analysis of ~he income and expenditure of the

specialised branch revealed that the branch became a profit centre right from the second

year of its existence. The most commendable achievement of the specialised micro-credit

branch is its ability to maximise the outreach in a shortest possible time. Besides, the -..

transactions costs are lower, which makes the project viable even when it charges the

lowest interest rate in the world (prime lending rate). The project gets refinance from

NABARD at a concessional rate of 7%, which is passed on to the beneficiaries at 8.5-

10% depending on the size and duration of the Joan. RBI has come up with policies like

permitting banks to adopt any model of micro-credit for purveying micro financial

services and allowing banks total freedom in designing financial products for the poor

(Capoor 2001 ). Thus the GB model when appropriately designed can be quite successful

as demonstrated by the OBC project.

Self-Help Groups-Bank Linkage Model

Though the SHG-Bank Linkage was introduced all over India from 1992-93 it became a

regular component of the Indian financial system since 1996 when Reserve Bank of India

(RBI) recognised this as a mainstream banking activity. The salient features of such

groups can be understood from the following table.

40

Table: 2.2 Some Basic Features of SHGs promoted by Banks/NGOs

I. Organisation Homogeneity in terms of economic/socio-economic status,

common identity of activities etc.

2. Nature of target Generally poor and weaker sections of the people in rural

areas and particularly poor women.

3. Management Selected/elected leader and duty generally rotated. Holds

meeting regularly.

4.Financia1 instruments

(a) Common fund Created out of savings, interest earned on loan, donations,

etc.

(b )Savings mobilisation While m certain cases no fixed rate of savings, in some

cases regular and fixed rate of savings, and in some cases as

per the capacity of the members.

(c) Loaning Decided by the purpose, quantum and the resources

available with the SHGs. Purpose of loans for individuals

include consumption, clearing outside debt, social, medical,

education, business, agriculture, etc., and loans for common

production activities.

(d) Repayment Period Generally lower than prescribed by banks.

(e) Rate of interest Varies from 12-20%. In a few cases the interest rates are

fixed by the NGOs.

5. Linkage with banks Banks treat the SHGs as borrowers.

Source: Desa1 and Namboodn (2001)

According to Singh (2003) presence of SHGs in villages is necessary to overcome

exploitation, create confidence for economic self-reliance of rural poor, particularly

among women who are mostly invisible in the social structure. These groups enable them

to come together for a common objective and gain strength from each other to deal with

exploitation, which they are facing, in several forms. A group becomes the basis for

action and change. It also helps build relationship for mutual trust between the promoting

organisation and the rural poor. The SHGs play an important role in:

41

l

(i) Differentiating between consumer credit and production credit;

(ii) Analysing the credit system for its implications and changes in the economy,

culture and social position of the target group;

(iii) Providing easy access to credit and facilitating group/organisation for effective

control;

(iv) Ensuring repayment and continuity through group dynamics;

(v) Setting viable norms for interest rates, repayment schedules, gestation period,

extension, writing off bad debts; and

(vi) Assisting group members in getting access to the formal credit institution.

There are four models that are prevalent in this kind of group formation:

(a) Bank deals directly with the SHG, providing financial assistance for onward

lending to individuals,

(b) Banks give direct assistance to the SHG while the NGOs provides training and

guidance to the SHG for effective functioning,

(c) NGO is the financial intermediary between the bank and a number of SHGs. With

the NGO accepting the contractual responsibility for loan repayment to the bank

the linkage between the bank and the SHG is indirect, and

(d) Banks give loans directly to the individuals/SHG and the NGO. The NGO assists

the bank in monitoring, supervising and recovery of loans.

The first three models are prevalent in India. The disbursement under the first model has

remained unchanged between 1997 and 2000 (Dasgupta 2001 ). Major changes have taken

place in case of second and the third model. Share of second model have increased from

45% in 1997 to 70% in 2000 that of third model has decreased from 42% in 1997 to 16%

in 2000. Lending institutions are thus becoming more comfortable in dealing with the

SHGs through NGOs while retaining their financial intermediary function, which is a

positive development. The scenario in this regard at the end of March 2004 is shown in

the following table. The rise in importance of the second model is evident from its share

having climbed to 81% of the total disbursement whereas that of NGOs as financial

intermediary has declined and at present stands at a meagre 4.5%.

42

Table 2.3: SHG-Bank Linkage Model-wise Cumulative Position upto 31 51 March 2004

Model I Model II Model III

Amount Percentage of Amount Percentage of Amount Percentage of

disbursed total disbursed total disbursed total

(Rs. Million) (Rs. Million) (Rs. Million)

5498.69 14.5 31647.18 81.0 1896.21 4.5

Source: NABARD (2003-04)

In India three kinds of lending institutions are mainly associated with SHG-Linkage -

commercial banks (CBs), Regional Rural Banks (RRBs) and Co-operative Banks (CoB).

Table 2.4 in the next page presents the cumulative participation of banks in SHG-Iinkage

across regions.

Table 2.4: SHG-bank Linkage- Agency-wise Cumulative Participation upto 31 sr March

2004

Region Commercial Banks Regional Rural Co-Operative Banks Total

(CBs) Banks (RRBs) (CoB)

No. of Bank No. of Bank No. of Bank No. of Bank

SHGs Loan SHGs Loan SHGs Loan SHGs Loan

Northern 19796 493.93 21427 515.7 11173 313.95 52396 1323.58

Region

North- 2279 77.58 9521 117.45 478 7.1 12278 202.13

Eastern

Region

Eastern 49678 965.21 73174 1210.17 35385 429.70 158237 2605.08

Region

Central 45297 1087.65 71951 1504.57 9761 171.05 127009 2763.27

Region

Western 28803 812.89 17109 400.35 8903 195.57 54815 1408.81

Region

Southern 392569 19111.03 212816 9034.34 68971 2593.84 674356 30739.21

Region

Total 538422 22548.29 405998 12782.58 134671 3711.21 1079091 39042.08

Source: NABARD 2003-04

43

We have calculated the relevant percentages, which would allow us to compare the

participation of different kinds of banks and the regional spread of the programme. Table

2.5 below presents the scenario. Among the banks the bulk of the linkage is done by the

commercial banks (49.8%) followed by the RRBs (37.6) and CoBs (12.5%). The divide

is more pronounced if we consider the share in loans. CBs provide 57.8% of the total

loans followed by RRBs (32.7%) and CoB (9.5% ). Such differences may arise, apart

from other reasons, due to different resource-base and competence in identifying

appropriate strategies for such lending among the institutions.

The regional spread in linkage is very much skewed in favour of the southern region

which is linked to 62.49% of total linked SHGs and gets 78.73% of the total loans.

Similar figures for the north-eastern region are 1.14% and 0.52% respectively. Agency­

wise we find that the commercial banks are more active in the southern region than the

other regions. RRBs are -more active in north-eastern and central regions than other

banks. The co-operative banks are more active in northern and eastern regions than other

banks with the percentage share of SHGs linked through these banks being 26.28% in the

eastern region.

Table 2.5: Bank-wise and Region-wise Percentage share of SHGs linked and Loans

Advanced to SHGs

Commercial Banks Regional Rural Banks Co-operatives Total

Region/Banks %share of %share of %share of %share of %share of %share of %share %share of SHGs Bank loans SHGs Bank loans SHGs Bank loans of SHGs Bank loans

Northern 3.68 2.19 5.28 4.03 8.30 8.46 4.86

N-Eastern 0.42 0_34 2.35 0.92 0.35 0.19 1.14

Eastern 9.23 4.28 18.02 9.47 26.28 11.58 14.66

Central 8.41 4.82 17.72 11.77 7.25 4.61 11.77

West em 5.35 3.61 4.21 3.13 6.61 5.27 5.08

Southern 72.91 84.76 52.42 70.68 51.21 69.89 62.49

Banks 49.80 57.80 37.60 32.70 1250 9.50 100

Bansal (2004) have dealt with issue of explanation of such differences in spread of the

SHG-Iinkage programme across regions. She tried to probe whether the spread of the

programme across India has a systematic pattern. To investigate this she calculated the

44

3.39

0.52

6.67

7.08

3.61

78.73

100

coefficient of correlation of the number of SHGs linked with the population, Human

Development Index (HDI), incidence of poverty and spread of NGOs across Indian

states. The results are presented in the following table.

Table 2.6: Association between number of SHGs linked and various State-level Variables

Variables Co-efficient of Correlation

State Population 0.46

Incidence of Poverty

All States -0.01167

States with poverty below national average -0.505

States with poverty above national average -0.089

Number of NGOs in the state 0.39

State HDI -0.06478

The results indicate that at the macro level the SHGs have moved away from poorer

states and are mainly following the presence of NGOs in various states. This result is in

tune with what we have seen in Table 2.3 where we found that the model in which NGOs

form the SHGs and bank finance them directly have gained importance in India over the

years. Thus the role of NGOs and other Self-Help Promotional Institutions (SHPis) in

forming SHGs should be further scrutinised.

Role of NGOs and SHPis

The major factor behind the satisfactory growth of SHGs is the role of NGOs and SHPis.

Apart from the NGOs, Banks, socially committed individuals, farmer's clubs and

government functionaries also act as SHPis. Whatever gains the SHG members have got

or the benefits banks have received is because of hard work of the field workers who are

generally women. But this assistance does not come for free. The costs include:

(i) Salary of field workers,

(ii) Travel cost of field workers from one village to another,

(iii) Training costs of field workers other staff members and SHG members, and

45

(iv) monitoring, controlling and supervision.

As per information provided by Mahila Arthik Vikas Mahamandal (MA VIM), a

parastatal organisation and the most important SHPI in MRCP (Maharashtra Rural Credit

Project), the average cost per SHG per annum in the first year ranges from Rs. 620 toRs.

3,513 depending upon the items included in the cost calculated. The cost however

declines over time as the SHG members themselves take up some of the responsibilities.

This decline depends on the strategy of concentrating on a fewer villages at first,

stabilising a large number of groups there and then moving on to other villages. The

following table shows us the region-wise spread of NGOs and other partner agencies and

the cumulative number of SHGs linked by them. Southern region is served by 41.1% of

the partner agencies that link 61.1 % of the total SHGs linked through partner agencies in

India. Thus the NGOs and other agencies are not only predominantly operational in

number in the southern states they also link bulk of the total SHGs in this region. In this

respect, the partner agencies in the eastern region constitute 22.5% of the total agencies in

India but link only 3% of the total SHGs promoted by such institutions in India.

Table 2.7: SHG-bank-linkage Region-wise Details of Partner Agencies

Regions No. of Partner Cumulative No. of SHGs promoted by Agencies Partner NGOs and other agencies upto 31st

march 2004

Northern 231(7.6%) 53492(3.5%)

N-Eastern 101(3.4%) 9246(0.6%)

Eastern 680(22.5%) 46200(3.0%)

Central 462(15.3%) 375124(24.7%)

Western 308(10.2%) 106603(7.0%)

Southern 1242(41.1%) 926895(61.1%)

Total 3024 1517560

Source: NABARD 2003-04

NABARD gives grant support to the various institutions who act as SHPis to cover the

costs of SHG formation. As can be seen from the following table the NGOs get bulk of

the amount sanctioned for the purpose and they shoulder the burden of promoting and

linking maximum number of SHGs among the agencies entrusted to do so.

46

Table 2.8: Grant Support to Agencies functioning as SHPI upto 31 51 March 2004

Institution Grant Sanctioned (In No. of SHGs to be Grant No.of No.of Rs. Million) promoted and linked Released(in Rs SHGs SHGs

million) promoted linked

ARBs 27.58 35045 9.32 31042 15535

Cooperatives 12.4 15550 1.05 3697 946

NGOs 151.218 115279 69.72 75186 38599

Source: NABARD 2003-04

Thus given the increased importance of 'NGO promoted SHG model' and 'direct bank

financing to the group model' it is natural that the NGOs have got the lion's share of

funds sanctioned for self-help promotional activities. And as the above table suggests

they have promoted and linked a huge number ofSHGs.

After having studied the different modes of disbursement of credit to the poor, this study

will consider the socio-economic and political scenario that accounts for the success of

different forms of lending in different geographical regions. ·A major enquiry of this

thesis is to find out the socio-economic factors affecting the spread of the SHG-bank

linkage program in different regions of India. The causes of success of two different

forms of lending (Grameen model in Bangladesh and SHG model in India) in two

countries whose rural areas are not very different from each other, can provide the basis

for identifying the factors responsible for spread of a program across regions within a

country. We have presented the operational features of SBG and GB model in Table 2.1.

Given the features of these two systems and the fact that rural poor in India are not so

different from that of Bangladesh (where GB model is more prevalent) why have two

such different systems dominate rural finance in the two countries? Answers to this

query may shed some light on socio-economic milieu required for the growth of such

forms of lending.

47

Factors affecting dominance of SHG Model in India and Grameen Model in

Bangladesh

The difference between Northern and Southern India for instance is more pronounced

than those between rural communities in West Bengal, UP, Bihar and Orissa and their

neighbours in Bangladesh (Harper 2002). Thus it is not very normal for two different

systems to have evolved in the two countries (especially in between the above spoken

regions). The following reasons are put forward as plausible explanations for the

differences.

• Political Structure: Bangladesh has experienced Jess democracy than India. The

GB system imposes strict discipline on the beneficiaries, which is facilitated by

the fact that rural people were accustomed to strict discipline under the military

regime. In India however the NGOs see credit as an entry point for wider and

more liberal goals li,ke strengthening of social and institutional capital (Fernandez

2001)

• Donor Assistance: The GB system is dependant on donor assistance whereas

SHG-Jinkage depends on the formal banking system for funds. Development aid

to India was $1.00 per head of the population in 1999, while the equivalent figure

for Bangladesh was $9.00 (World Bank Report, 2002). This difference may have

Jed to the predominance of GB system in Bangladesh.

• Homogeneity: Bangladeshi village communities are generally more socio­

economically homogeneous and less divided by caste than their Indian

counterparts. It therefore may be easier in Bangladesh to persuade people to form

groups, which follow a standardised system. The more flexible SHG system may

be more appropriate for the India situation.

• Population Density: Population in India is about 300 people per square kilometre

whereas for Bangladesh the figure is 850 per square kilometre. Bank workers

under GB model visit all groups each and every week. In case of the SHG system

the banker or the NGO worker may visit an SHG more frequently at the beginning

when the groups are formed. The aim being to help the group keep their own

records and run their own meetings. Once this is achieved frequent visits are not

48

required. Some parts of Northern hills and the Sundarbans in India are thinly

populated. Thus it unlikely that the GB system could spread all over India.

• Financial system: The Indian banks have more than 70,000 branches in the rural

areas. There is a long history of government led poverty alleviation through the

banking system. The GB model is ideally suited for donor-funded banks whereas

any branch of a bank can finance a number of SHGs through its own funds in

India (which is recognised by both RBI and the Government of India). It would

have been difficult to introduce SHG system in Bangladesh, where the branch

coverage is much less and the bankers are under less compulsion to find new

ways of reaching the poor.

• Institutional inflexibility: NABARD in India has successfully marketed the SHG

linkage system, through subsidised refinance, training for bankers and for NGOs.

The single-product approach imposes some uniformity and questions have been -..

raised about whether NABARD should finance GB groups in India. In

Bangladesh the PKSF wholesale fund, which provides 20% of the on lending

finance to the country's MAs has set a criteria to debar institutions which do not

follow the GB system of lending (Alamgir 1 999). Thus institutional inflexibility

in terms of financing particular forms of lending may have caused the

predominance of different kinds of system in the two countries.

The factors discussed above can be considered as the possible determinants of the

respective lending practices in the two countries. These along with other factors may be

considered to understand the variation in micro-finance penetration across the regions in

India. Whether they really affect the lending is a matter of further research. We will take

up these issues at length in our study on the Indian system of lending for the poor. Before

doing that in the next section we review some of the pioneering and recent works on the

impact of such programs in India and elsewhere.

49

Studies in Microfinance

The impact of SHG-bank linkage has been studied by NABARD in 22 districts of I I

states covering 223 SHGs (NABARD 2002). The major findings of the study are as

follows:

• Average value of assets per household which incJuded livestock and consumer

durables etc., increased by 72% from Rs. 6,843 in pre-SHG situation to Rs.

II, 793 in post -SHG stage.

• Housing conditions generally improved with a shift in the ownership from kuchha

to pucca houses.

• Almost al1 members developed saving habit in the post-SHG situation as against

only 23% of the households before the programme was initiated. Average annual

savings per household registered over threefold increase from Rs. 460 to Rs.

I,444.

• The average borrowing per year per household increased from Rs. 4,282 to Rs. '•

8,341. The share of consumption loans declined from 50% to 25%. About 70% of

loans taken in post-SHG situation were for income generating purposes.

• Overa11 loan repayments improved from 84% to 94% between the two periods

with an impressive improvement of 29 percentage points in the repayment of the

loans to the banks.

• Average net income per household increased toRs. 26,889 or about 33%.

• About 43% of the incremental income generated was from Non Farm Sector

(NFS) activities followed by farm (28%) and off-farm (2 I%) activities.

• About 74% of the sample members had income below Rs. 22,500 in the pre-SHG

situation. In the post SHG situation 17% of the member households improved

their income above this figure.

• Employment increased by I 8% from 3 I 8 man-days to 375 man-days per

household between pre and post-SHG situations.

• The involvement in the group significantly contributed m improving the self-

confidence of the members.

50

• The members were relatively more assertive m confronting social evils and

problem situations. (NABARD 2002)

Thus the NABARD study showed not only improvement in economic condition but also

the social status of member households due to such linkage.

National Institute of Banking Management (NIBM) conducted a study in four districts of

Maharashtra promoted by Maharashtra Rural Credit Project (MRCP) (Dasgupta et al.

2001 ). All these are woman groups. The average size of the groups was found to be 16 by

NABARD and 17.5 by NIBM. According to NIBM 69% of the SHGs were of the size

11-20. According to both studies 50% of the members were illiterate whereas 55% of the

office bearers were atleast secondary level educated in SHGs under MRCP. Agricultural

labour, marginal and small farmers constitute about 85% of the SHGs' membership.

NIBM found average savings or thrift rate to be Rs.24 per month per member. The rate of

savings in the new groups is more than that of the old groups indicating increasing ',

confidence in this kind of group formation. The average amount of savings mobilized is

Rs. 10,658 per group. Eleven percent of the groups, mostly older, had average savings

over Rs. 20,000, a significant achievement for those who are not expected to have

savings capacity! SHGs have in most cases started lending with their own fund from the

eighth month from their formation (under MRCP). The time lag is less for new groups.

They extend loans at 2% per month followed by 3%. Though among the SHGs under

MRCP 50% took loans from the banks there is a clear tendency to reduce loans from

banks. The credit process has tremendous effect on informal money lending. Only 7% of

the SHG members in comparison to 54% earlier continue to take loans from the

moneylenders. Besides, there has been a significant social impact too. 'Mute' members

earlier, can now organize meetings, discuss and communicate with others, liaison with

different agencies and take important decisions.

A large chunk of the groups formed have only women as their members in both

Bangladesh and India. The reason being that the effect of income-generation among

women would not only improve their social status but will also have positive affects on

51

the family as a whole especially the· children. Pitt et al. (2003) considers the effect of

additional resources (through micro-credit programmes) supplied to and controlled by

women, as compared to men, on child health outcomes. They have used survey data from

15 Bangladeshi village collected in 1991-92. They have found that women's credit has

large and statisticaJJy significant impact on health outcomes of both boy and girl children.

Whereas credit provided to men had no statisticaJJy significant impact on children's

health.

Apart from the socio-economic impact of the microfinance programme on the member

households an important issue, which must be raised, is: Are the poor getting the benefits

of this programme? In other words have the targeting been proper? Amin et al. (2003)

evaluates whether microcredit programs such as GB reach relatively poor and vulnerable

in two Bangladeshi villages. They find that while microcredit is successful at reaching the

poor, it is less successful at' reaching the vulnerable (a household is considered vulnerable

when in addition to having low consumption levels it is unable to smooth consumption in

the face of idiosyncratic income fluctuations). A similar enquiry was attempted by Basu

and Srivastava (2004) in case of SHG-bank linkage program by using data from the state

of Andhra Pradesh in India. Their results suggest that households in two income quintiles

above the poorest households are more likely to be SHG members than the poorest and

the top two income quintiles. In a related enquiry they also found that poorer and more

difficult to reach villages are likely to have relatively fewer SHGs.

The whole idea of encouraging entry of formal institutions in rural areas is to diminish

the dominance of informal moneylenders. Inforaml financial markets across India offer a

wide range of products to meet local demand. Finance companies and chit funds offer

both savings and credit services, whereas local moneylenders and pawnbrokers offer

credit with varying terms and conditions. Friends and relatives are also an important

source of credit. Sinha (2005) have used survey data on MFI clients from the states of

Andhra Pradesh, Tamil Nadu, Karnataka, Kerala, Uttar Pradesh, Rajasthan, Assam and

Manipur. The foJiowing table summarises his findings.

52

Table 2.9: Sources of Credit

Status Share in Credit by source

MFI Formal Costly Informal Personal Informal

Sources Sources

Client 87 8 38 36

Non-client - 17 58 55

As can be seen from the table the clients of the MFis are less dependent on costly

informal sources moneylenders, private financiers, pawnshops and pawnbrokers. Further,

the percentage of households who borrowed at a very high rate of interest (>=60% per

annum) is comparatively lower in case of clients (14%) than non-clients (23% ). Thus

dependence on costly informal sources have been lower for microfinance clients though

there is a long way to go before the dependence can be eliminated.

Areas !'f Further Research

The importance of access to finance by the poor has been accepted by policy­

practitioners all over the world. Though questions have been raised about its targeting,

sustainability, impact, outreach etc. The literature so far reviewed is mainly concerned

with one or more of these aspects. Concentration of such services in certain pockets of an

economy may have severe implications for the poor of the un-served areas. We have

already discussed possible determinants of availability of such services when we

compared the Indian and the Bangladeshi economy in terms of having different socio­

economic structures giving birth to different kinds of credit delivery systems for the rural

poor. Honohan (2004) have studied non-uniform development of microfinance across

countries. In an attempt to discover what national characteristics make for deeper

microfinance penetration, a regression analysis of cross-country variation in MFI

penetration ratios was carried out on worldwide data. He found no strong relationship

between penetration rates and potential determinants such as such as head count ratio

though a statistically significant regression was identified. A large population, high GNP

per capita and poor institutions may be associated with lower penetration of MFis. This is

53

consistent with the idea that the presence of a market for microfinance (e.g. many poor

people) and good country institutions help the microfinance industry grow.

As we have already mentioned, in India the spread of microfinance has been uneven and

has been mainly concentrated in the south. One of the factors identified by Bansal (2004)

and voiced by many is the presence of a large number of active NGOs in Southern India

who have been instrumental in proliferation of SHGs in that region. This may be a part

of the story. Though the NGOs are instrumental in educating the people about the

benefits of group-lending there are definitely other socio-economic factors, which

determine banking habits of the rural poor. At the same time the willingness of the banks

to take up microfinance seriously and think poor to be bankable also must depend on

certain characteristics of the prospective clients. In light of the cross-country studies,

which we have already mentioned, we felt the need for a similar kind of study to be

conducted across states and other regional configurations in India. This kind of an

analysis is more appropriate across regions within a country than across countries. '

Countries may be different due different kinds of political histories, institutions etc.,

whereas regions within a country are more or less similar on these counts. Thus

concentration of certain services in particular regions within a country given certain

similarities in political and institutional structure can shed more light on the socio­

economic determinants of the lending programmes.

In our study we have tried to find out the plausible determinants of SHG-Linkage across

states. Taking into account state, time and regional effects along with a host of socio­

economic variables. Different specifications of the linkage have been used to perform the

tests depending on the absolute number of linked groups, number of linkages per capita

and share of a state in total linked SHGs. Lagged values of the dependent variables have

also been considered as explanatory variables to test whether the learning effect is a

significant determinant of SHG-Iinkage. This is the subject matter of chapter III of this

thesis.

54

As we have seen in our previous di'scussion that a large number of poor people in a

certain area implies a large number of clients for MFis. Thus more poor people implies

higher penetration of MAs provided there are proper institutions at place. Time-series

data on poverty and inequality measures are not available for India and the states for the

later half of the 1 990s. Again, questions have been raised about the comparability of such

measures across the years. So we have used large sample estimates of poverty and

inequality (Sen and Himanshu estimates, 2004) for the years 1993-94 (50'h Round of

National Sample Survey (NSS) data) and 1999-2000 (551h NSS) to test for the association

between people below poverty-line, average consumption expenditure of the people lying

in the lowest quartile in the consumption ladder with number of SHGs linked across

states. We have used separate regressions for these years to test for the association.

Further regressions were run using poverty and inequality measures in 1993-94 as

explanatory variables where the dependent variables are SHGs linked across states in

1 999-2000. This was done .to find out whether over time states with more people below

poverty line initially, had experienced higher linkage of SHGs. This has profound

implications for policy as access to finance has been recognised as one of the important

measures to reduce poverty. We will take up these issues in chapter IV of this thesis.

State -level studies cannot capture the intra-state differences in development. We have

also seen that for a long time the focus of financial policy in India has been the district for

example, the Lead Bank Scheme and the Service Area Approach. In this era of

decentralisation districts are becoming increasingly important as geographical units.

Devolution of funds and operationalising various policies are much more effective, if

districts are kept in mind rather than the states. Looking at smaller areas like districts or

development blocs can better identify regional disparities in development in India.

Sharma Committee ( 1997) identified hundred most backward districts in our country

after considering various parameters. Even developed states like Maharashtra, Haryana

and Kamtaka have districts belonging to this category. Thus the district-level

determinants of the spread of the SHG-linkage program have been considered in chapter

V of this study. We have considered data on SHG-Iinkage across districts in 1999-2000

and included socio-economic variables from the Census data (200 1) and also estimated

55

certain variables at the district-level from NSS 551h round data on Consumer Expenditure

at the household leveL

Regarding impact of the microfinance programs we have seen that a lot of work has been

done at the micro-leveL Where studies have considered impact of the programme on welJ

being of the member-households. But at the policy-level scaling up of the outreach of

such programs is increasingly becoming a matter of concern. Given the success of the

SHG-linkage program we have tried to find out its association with banking habits of the

people in the respective locations. Unless the formal financial institutions establish

banking relations beyond the Self-Help groups to individual members within the groups

and non-members in the same locality, outreach of such institutions would be limited in

the rural areas. The SHG-Linkage program aJlows the banks to be familiar with banking

habits of people in the program areas and also makes members and non-members aware

of financial products spe~ificaJly designed for them. This overtime can translate into

sustainable banking relationships with increase in willingness of the banks to be involved " in rural finance along with growth of healthy savings and borrowing habits among the

rural people. In chapter VI we have used panel data models to find out the association

between SHGs linked per capita and deposit accounts per capita and between SHGs

linked per capita and small borrowal credit to deposit ratio across states. We have found

significant positive impact of SHG-Iinkage program on both savings and borrowing

habits of people in the rural areas. Specifically, it takes almost two years for banks to

develop credit relationships with people in areas where SHGs have already been linked.

Panel-causality tests were carried out to determine the direction of causality. In case of

affect on savings behaviour it was found that causality runs from SHGs linked per capita

to deposits per capita and the affect is positive. Causality, in either direction, was found

to be absent between borrowing behaviour and SHGs linked per capita.

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