FINANCIAL
INCLUSION & SOCIAL CAPITAL: A CASE STUDY OF SGSY BENEFICIARIES IN KASHMIR
VALLEY
Audil Rashid Khaki
American University of Middle East, Kuwait
E-mail: Audil.Rashid@aum.edu.kw
Mohiuddin Sangmi
Department of Business & Financial Studies
University of Kashmir, India
E-mail: sangmi2k@gmail.com
Submission: 13/01/2016
Revision: 11/02/2016
Accept: 12/05/2016
ABSTRACT
The
interaction between economic dimensions and socio-political dimensions of
poverty are believed to be interlocked with a continuous interaction among each
other. These interactions are believed to manifest in an intertwined
relationship; and thus remain at the centre of policy making throughout the
developed world. Access to economic resources (Financial Inclusion) is believed
to encourage micro entrepreneur to take on profitable activities which in turn
provide an enabling environment for him/her to gather access to social networks
which may be beneficial to him in terms of access to raw material, marketing
support and business ties. Whereas financial inclusion is believed to have a
positive impact on social capital, the reverse is also true; the amount and
quality of social capital provides a micro-entrepreneur with easy access to
diverse sources of finance. Microfinance Institutions around the world heavily
rely on group financing mechanism by leveraging on social collateral as a
replacement to financial collateral in financing micro-entrepreneurs.
The
present study is an attempt in this direction to understand the relationship between
financial inclusion and social capital.
The
study attempts to evaluate the impact of access to finance on socio-political
empowerment of the beneficiaries of Swarnjayanti
Gram Swarozgar Yojana (SGSY), now known as National Rural Livelihood Mission
(NRLM). Results indicate that access to finance has a positive impact on almost
all the socio-political indicators of empowerment, the impact being relatively
lesser for financial literacy and economic awareness.
Keywords: Financial Inclusion, Social Capital,
Microfinance, Poverty Alleviation.
1. INTRODUCTION
Broadly
Social Capital can be defined as the norms and networks facilitating collective
actions for mutual benefits (WOOLCOCK, 1998, p 155). Bennet Lynn (1997) defines
social capital as ‘those features of social organisation such as networks,
norms and trust that facilitates coordination and cooperation for mutual
benefit’ He further defines networks as ‘local clubs, temple associations, work
groups and other forms of associations beyond the family and kinship groups.
Social
capital is context dependent and takes many different forms, forming a complex
web of interaction and communications (FUKUYAMA, 1995; FUKUYAMA, 1999; LIN,
1999B; PUTNAM, 1993; WHITE, 2002), including obligations (within a group), trust,
intergenerational closure, norms, and sanctions with underlying assumption that
the relationships between individuals are durable and subjectively felt
(BOURDIEU, 1983).
Social
capital can be understood at three basic levels; Country Level, Community
Level, and at Individual Level. At a country level, social capital refers to
the degree of trust in Government & other societal institutions (FUKUYAMA,
1995), which in other words include the participation in the civil institutions
and conformity to the legal and civil norms of the administration.
At
a community level, social capital comprises of ‘neighbourhood networks’
(JACOBS, 1961), features of social life – networks, norms and trust (PUTNAM,
1993) that enable an individual to pursue collective goals with a collective
effort. And at an individual level, social capital refers to individual
characteristics like; charisma, status, individual interactions and access to
networks (GLEASAR et.al., 2000).
It
is generally believed that social capital is positively associated with
economic progress. Through linkages at various levels, wider social and
economic impacts can occur through the labour market, the capital market, the
social capital at various levels, and through clients’ participation in social and
political processes (MCGREGOR et al., 2000).
Microfinance
has been found to reduce Putnam effects; Rafael and Gomez (2001) establish a
microeconomic foundation for the effect of social capital on improved economic
performance. Small-scale self employment
which is synonymous with micro entrepreneur is a group of low income
self-employed people with fewer resources at disposal and lesser assets to
offer as collateral. Microfinance heavily relies on group formation for
financing micro-entrepreneurs by leveraging their social capital as collateral
by replacing financial collateral.
This
social association between these groups acts as social collateral (GOLDMARK,
2001) suggesting methods which work through social enforcement of maintaining
reputation and social standing within the community making group mechanisms
more secure leading to high repayment rates (WOOLCOCK, 2001; GOMEZ; SANTOR,
2001).
Results
establish that Social Capital has a positive implication for microfinance
institution that rely heavy on the idea that individual social capital can
overcome a borrowers lack of financial collateral. Lack of sufficient social
capital and interconnectedness in the population, especially in the form of
lack of cooperation among businesses and among support organisations, is
believed to obstruct the successful provisioning of microfinance services
(LASHLEY, 2002).
The
role of Promoting agencies in group formation and mobilisation involves social
intermediation which in turns leads to the creation of social capital
(SRINIVASAN, 2000).
With
an aim to understanding the dynamics of financial inclusion and its iteraction
with social capital in Kashmir valley, a study on the participants of Swarnjayanti Gram Swarozgar Yojana
(SGSY), now known as National Rural Livelihood Mission (NRLM) has been
undertaken in the valley of Kashmir.
Kashmir
has by far been ignored by the researchers in the field and in order to fill
this gap, present study has been undertaken to make a modest contribution to
what little is already known about the dynamics of financial inclusion in the
Valley.
The
paper is divided into 5 sections; section 1 presents a brief background and
understanding of social capital and its interaction with access to finance,
besides objectives of the study. Section 2 evaluates the existing literature
for any evidences on the relationship between financial inclusion and social
capital. Section 3 presents the research methodology adopted, the sampling
design, tools of measurement and analysis and sample characteristics. Section 4
presents the results of the study and section 5 populates the summary,
limitations of the study, suggestions and directions for future research.
The
objectives of the study are outlined below:
a)
To examine the existing literature for the
dynamics and nature of the relationship between financial inclusion and social
capital.
b)
To evaluate the impact of access to
finance (credit) on the socio-political empowerment of the participants of SGSY
Scheme in Kashmir.
c)
To suggest on the basis of study results,
measures to improve the effectiveness of financial inclusion on the social
capital of participants.
2. LITERATURE REVIEW
Social
Capital and Access to Finances, both from formal or informal sources, interact
at various levels and manifest through various intertwined relationships. While
social capital in different forms and at various levels substantially increases
the provision for and access to financial services and economic empowerment,
access to finance also impacts social capital at various levels. Not only
provision for financial services, social capital has in also been found to
improve the impact of financial access on micro-entrepreneurs through various
economic and social processes and vice versa.
Sanders
and Nee (1996) explains the positive effect of social capital (social
relations) on a micro-entrepreneur through Instrumental Support, Productive
Information and Psychological Aid. Instrumental
support in the form of start-up support through non-interest bearing
capital usually by friends and family can directly affect the performance of a
micro-entrepreneur.
Social
Capital can help in improving the earnings of a micro-entrepreneur through productive information dissemination;
this information may be in the form of advertising through the word of mouth,
providing valuable leads and customer referrals (HOLZER, 1987), information
about trusted suppliers and competitors which can improve the productivity.
What
is more important for a micro-entrepreneur to keep him going about his venture
is the motivation; social capital can be an effective psychological aid which prevents a micro-entrepreneur from
liquidation and dissolution during the times of emotional stress.
Darity
and Goldsmith (1995) demonstrate a positive relationship between psychological
well-being and individual productivity, the results indicate that individuals
lacking strong social networks are more prone to depression and suffer more
during unemployment spells and distress. It is thus believed that the social
capital at whatever level and in whatever form leads to an increase in the
productivity and decrease in vulnerability of a micro-entrepreneur.
A
very important component of social capital is ‘neighbourhood effects’, which
may be defined as the characteristics other than personal (the community level
characteristics) that can affect the individuals’ economic outcome (GOMEZ;
SANTOR, 2001), often referred to as spillovers in the microfinance literature.
Since spillovers can be in the form of inflow or the outflow, here spillover
inflow is specifically being referred to.
The
neighbourhood characteristics affect the participants either directly or
indirectly by generating the demand or through facilitation (GOMEZ; SANTOR,
2001). Neighbourhood effects may be helpful in various ways by creating a
spillover effect due to integration and interaction, by sharing complimentary
products, skills and resources (GOMEZ; SANTOR, 2001), and thus greater
commercial concentration and integration generate larger demand for the
products & services of a micro-entrepreneur (CICCONE; HALL, 1996).
Socio-economic
neighbourhood characteristics may lead to spillovers which can be positive or
negative. Generally favourable neighbourhood characteristics encourage
investment in civic amenities as well as helps in reducing outward mobility (DIPASQUALE;
GLAESER, 1999). Besides community level social capital, there are other factors
which pertain to individual characteristics of these entrepreneurs, the
individual level social capital, which exists in the form of individual
heterogeneity can also be a reason of success or failure (GOMEZ; SANTOR, 2001).
It
is not just that Social Capital increases efficiency of microenterprises but
the reverse is also true; the interaction between these groups amongst themselves
and within their community can create co-operation and trust which not only
facilitates their activities but the benefits extend beyond the group level by
virtue of a spill-over effect directed outwards giving an impetus to social
capital development in their communities (ZOHIR; MOTIN, 2004).
The
development of social capital at community level takes place through diffusion
of development impact across community. Grameen women have been found to be
more active with an emphasis on productive role of women rather than just the
reproductive role; this norm has been found to be picked up by the non-Grameen
women and also due to the socio-political activism of Grameen women outside
their solidarity groups (KABEER, 2003).
Further
microfinance services even if they are slightly misdirected are believed to
reduce poverty; microfinance services provided to non-poor have been found to
reduce poverty by providing labour opportunity to the poor as employees of
micro entrepreneurs (MOSLEY; ROCK, 2004). It has also been argued that
microfinance may affect poverty even without affecting the borrower’s income,
either by relatively easier & cheaper credit, or by stimulating economic
activities and development of social capital (MOSLEY, 2001; ZOHIR; MOTIN,
2004).
The results
even though not encouraging to a welfarist mind reveal an important dimension
of microfinance programmes – the creation of social capital; the microfinance
services have been found to increase spending on education on healthcare which
may extend beyond the programme participants. Microfinance through creation of
social capital has been found to reduce migrations by increased employment
opportunities, development of demand for the products and increased income (ZOHIR;
MATIN, 2004, MAKINA; MALABOLA, 2004).
Theoretically
the field of finance has been abuzz with a generalisation that access to
finance improves particularly the welfare of poor and excluded sections by
allowing them to take on the opportunities which in absence of financial
support would have to be forgone by the poor.
Rogaly
(1996) refers to such uncontested generalisation in the microfinance literature
as ‘Microfinance Evangelism’, which necessarily assumes that poor immediately
and invariably benefit from access to finance. Nevertheless sufficient evidence
is available in the literature about the positive association between
microfinance and economic empowerment, impact of financial access on
socio-political empowerment is also well documented in the microfinance
literature.
Microfinance
tries to improve double bottom line – financial as well as social, while as
conventional financial system caters to improve just the financial bottom
line. The ability to take various
opportunities is believed to exhibit a positive association with socio-cultural
and economic variables of the participants. Academic circles are abuzz with the
generalisation that access to finance has a direct and positive impact on the
socio-economic condition of the beneficiaries/participants (WEISS; MONTGOMERY,
2005; MKNELLY; DUNFORD, 1999; PITT; KHANDKER, 1998; KHANDKER, 1998; AMIN et
al., 1995; PITT et al., 2003; KHANDKER, 2003, GANESAN; SASIKALA, 2010, FREDRICK;
KALAICHELVI, 2010).
In
their study conducted in Ghana, Cheston and Khun (2002) found that microfinance
has led to a positive development in self confidence, self-esteem,
participation, bargaining & negotiating power and decision making of the
participants. In order to study the relationship between social capital and
economic empowerment, in their study on 612 group borrowers and 52 individual
borrowers of Calmeadow Metrofund, Gomez and Santor (2001) found a positive
association between neighbourhood effects and earnings.
In
a society dominated by male, particularly in developing economies, women find
it hard to engage themselves in social, economical and political process.
Taking into consideration the increased marginal returns on financial inclusion
of women, microfinance has always had a feminist orientation for so many
reasons.
Most
of the studies in the field of microfinance have thus been undertaken to
understand the socio-economic impact of access to finance on women.
Microfinance can be considered as a powerful tool in improving the
socio-economic status of participants more particularly of women participants (HERME;
LENSINK, 2007).
Several other studies evidence that
participation in a microfinance program exerts significant impact on various
aspects of women empowerment, and other social variables (SCHULER; HASHEMI,
1994; HASHEMI et al., 1996; STEELE et al., 2001; HASHEMI; RILEY, 1996; SCHULER et
al., 1998; SARAVANAN; DEO, 2010, MAKINA; MALABOLA, 2004).
Lyngdoh
and Pan (2011) reveal a significant relationship between financial inclusion
and economic transformation of women; access to finance has been found to exert
a positive impact on social outcomes, political participation, decision making
and inclusive growth also.
Theory
suggests that a larger control over resources by women can enhance human
capital of children. Working on BIDS Survey Data, Pitt et al. (2003) shows that
an increase of 10 percent in credit to women causes an increase of 6.3 percent
in the arm circumference of daughters and an annual increase of 0.36 cm and
0.50 cm in the height of girls and boys respectively.
The
other latent variables that show a positive relationship with access to finance
are; decision about implementation of household borrowings, power to oversee
and conduct major household transactions, family planning, fertility control,
contraceptive use, and parental issues (AMIN et al.,1995; PITT et al., 2006).
Microfinance
to women has also a significant and positive relationship with women’s autonomy
with purchasing, women’s awareness and activism & some little impact on
household attitudes. Contrary to that credit flowing to men has been found to
have a net negative impact on all the variables mentioned above (PITT et al.,
2006). In order to study the relationship between microfinance &
empowerment, Pitt et al. (2006) also employed the same data set from BIDS Survey.
Results
suggest that participation in the program has a significant and positive impact
on women empowerment. While as credit flowing to women has been found to be
positively associated with women empowerment (AMIN et al., 1995), the credit
going to men has been found to create an opposite or negative impact on women
empowerment; under the condition that only one person is eligible to
participate in a program (PITT et al., 2006). Access to finance and
participation in a program leads to a positive impact on average annual
household income (33614 tk against 18686 tk for non-participant), education of
parents (3.25 for participants vs. 1.95 for non-participants), mortality of
children, contraceptive use (61.4% for participants and 38.6% for non-participants),
family planning, decision making, household participation, bargaining power and
social mobility (AMIN et al., 1995).
Membership
has also been found to increase mobility, authority, and aspiration; other
parameters like – times loan received, etc were also found to have a positive
impact on mobility, authority, and aspiration.
In
their study for assessing the impact of participating in SHG activities across
India, NCAER suggests a positive impact of programme participation on net
household income, asset holdings, self confidence, innovation, participation
and respect. Another NCAER (National Council for Applied Economic Research)
study by Shukla et al. (2011) indicates that microfinance activities have led
to increased savings, increase in productive activities (Jose et al, 2009),
financial literacy, and increase in the living standard of participants in
India. Studies have generally shown that microfinance have had a positive
association with various socio-economic parameters of participants, particularly
children education, nutritional status and empowerment (JOHNSON; ROGALY, 1997).
From
whatever little research that has been conducted in order to assess the
relationship between microfinance and health and education, it has been found
that microfinance interventions tend to improve education, healthcare and
hygiene, and nutritional indicators of the participants and also at places
where MFI are present, specifically due to the positive outward spillovers (WRIGHT,
2000; LITTLEFIELD; MORDUCH; HASHEMI, 2003).
Robinson
(2001) found that globally microfinance leads to enhancement in the standard of
living, quality of life, self confidence and also in the diversification of
livelihood strategies and thereby increasing their income. Similar relationship
is indicated by Kotishwar and Khan (2010); results indicate that microfinance
activities have significantly improved the quality of life including the
standard of living of participants.
Pahazhendi
and Badatya (2002) found that there exist a significant positive relationship
between NABARD’s SHG – Bank Linkage Programme and socio-economic conditions of
the participants. Empirical evidence suggests that the programme membership has
lead to a perceptible and wholesome change in the living standards of SHG members
in terms of ownership of assets, increase in savings, borrowing capacity,
income generating activities and income levels (KHAKI; SANGMI, 2012; PAHAZHENDI;
SATYASAI, 2000, HEPHZIBAH; SELVI, 2011; DUNN et al., 2001; BARNES, 2001).
Evidence
also suggest that membership has lead to an increase in the healthcare, food
and education spending along other expenditures (NEPONEN, 2003; SRINIVASAN;
KUPPUSAMY, 2010; MKNELLY; DUNFORD, 1998, 1999; PITT et al., 2003).
Pitt
et al. (2003) however found that the impact on children’s health is significant
for female borrowings while as the same is missing for male borrowers and even
negative in some cases. Noponen (2005) shows that the programme specifically
for rural women clients in Tamil Nadu, India, has a positive impact on
livelihood, social status and other socio-political indicators of their clients
which is more likely to increase as they spend much time with the programme.
The study further shows that the clients have seen an increase in the ownership
of assets.
3. RESEARCH METHODOLOGY
Microfinance
primarily aims at empowerment and poverty alleviation, and in order to know the
success or failure of a programme MFIs often go for studying the impact. It is
however argued that it is difficult to attribute to microfinance development
the broad range of developmental effects given the complexities in assessing
the impact that can directly be attributed to the interventions (WEISS; MONTGOMERY,
2005).
In
the recent times, in order to assess the impact of microfinance various tools
have been developed over time. One of these widely used tools in longitudinal
studies is available from Assessing the Impact of Microfinance Services (AIMS)
Project. This approach identifies impact as;
Impact
= (yt+1
– yt)p (1)
Where
yt and yt+1 are the identified impact variable at times t
& t+1 respectively, and p signifies the matching of borrowers and
non-borrowers. This approach is slightly weak for application owing to the
difficulties in matching borrowers and non-borrowers. The present study has
adopted a basic AIMS tool for impact assessment with a slight adjustment with
regard to the control group.
Whereas
non-borrowers are generally being used in the toolkit, here the impact variable
has been studied for the same stock of beneficiaries of the scheme before the
program and after the program. This methodology for impact assessment has been
used by National Council for Applied Economic Research (NCAER) in majority of
its impact assessment studies. The present study tries to understand the impact
of access to finance and particularly provision for credit to the beneficiaries
of Swarnjayanti Gram Swarozgar Yojana
(SGSY) now restructured into National Rural Livelihood Mission (NRLM).
3.1.
Database
Data
has been drawn from primary sources through a well structured interview
schedule. Detailed and in-depth interviews and informal discussion have been
conducted to collect the required data as per the interview schedule from the
beneficiaries of SGSY Scheme.
Due
to time and resource limitations, the study has been conducted in the Kashmir
Division of the State of Jammu and Kashmir, India and as such the beneficiaries
of the Scheme from Kashmir Division only have been studied. Besides, secondary
data has been collected from the Nodal Offices and Programme Offices of
Directorate of Rural Development (Kashmir) at District and Block Levels.
Further,
discussions with the officials from top management to middle management of
Banking functionaries, NABARD and other Government Institutions have been
conducted to get an insight and pave a direction into the working of the Scheme
in the Valley.
3.2.
Sample
Selection and Sampling Design
The
study covers all the regions of Kashmir Valley; it has covered three districts,
viz. Anantnag (Southern Region), Baramulla (Northern Region) and Srinagar
(Central Region) which have been purposively selected in order to gather
representation from all three regions.
A
multistage mixed sampling design has been adopted for selecting sample SHGs and
sample beneficiaries to be interviewed for the study. The number of SHGs
criterion has been used for the selection of districts for sampling; however
Srinagar has been selected ignoring the number of SHG criterion in order to
enable inclusion of different neighbourhood settings. In Anantnag and
Baramulla, four blocks have been selected from each District while as Srinagar
comprised of just one block. Nine blocks in total have been selected from three
districts with both Individual beneficiaries as well as Group beneficiaries.
The
methodology for impact assessment of the beneficiaries at the household and
individual levels is based on the information obtained from a primary sample
survey. A well structured interview schedule has been used to collect the
information on various socio-political parameters of sample members. In order to assess the impact of the program
allocation, the ‘pre and post’ or ‘before and after’ approach has been
followed. Relevant information has been collected as per the pre-structured
interview schedule.
The
responses have been collected on a recall basis with recall period of one year;
responses have been collected in two rounds of interviewing with a 20 minutes
pause between pre and post responses in order to avoid the bias that could have
arisen due to remembering of earlier responses. The consistency of the
responses was ascertained by using a question in a different style to capture
the same information. The interviews started with an informal chat and in case
of SHGs by an informal group discussion, which was immediately followed by the
formal interviews.
A
complete list of SHGs and Individual Swarozgaris
which have availed the facility/second grading during the last one year, was
collected from the respective Program Officers of the chosen districts. The
information was sorted blockwise and the 4 blocks from each district were
chosen. The criterion for selection of the blocks was purely
geographical/spatial where blocks have been chosen in such a way so as to cover
all the geographical regions of the district, Srinagar however comprised of one
block only where samples were chosen with geographical representation from all
regions. From district Anantnag, blocks Shahabad, Dachnipora, Qaimoh and
Shangus were chosen; similarly from district Baramulla, blocks Baramulla,
Sopore, Pattan and Singpora were chosen; while as Srinagar comprised of just
one single block.
Table 3.2.1: Sample Composition
Gender |
Type |
Total |
|||
Individual
Swarozgari |
SHG
Swarozgari |
||||
Male |
District |
Srinagar |
26 |
6 |
32 |
Anantnag |
24 |
1 |
25 |
||
Baramulla |
11 |
1 |
12 |
||
Total |
61 |
8 |
69 |
||
Female |
District |
Srinagar |
2 |
58 |
60 |
Anantnag |
18 |
52 |
70 |
||
Baramulla |
3 |
69 |
72 |
||
Total |
23 |
179 |
202 |
||
Total |
District |
Srinagar |
28 |
64 |
92 |
Anantnag |
42 |
53 |
95 |
||
Baramulla |
14 |
70 |
84 |
||
Total |
84 |
187 |
271 |
Source: Field Survey
A
total of 271 effective respondents were selected from all three districts (See
table 3.2.1); 187 group respondents and 84 Individual respondents, 69 male
respondents and 202 female respondents. Out of 202 female respondents, 179 were
group members and 23 were individual Swarozgaris;
and from a total of 69 male respondents, 8 are group beneficiaries while as 61
are individual beneficiaries.
A
total of 92 respondents have been selected from district Srinagar, 64 group
respondents and 28 individual respondents; a total of 95 respondents from
district Anantnag with 53 and 42 group respondents and individual respondents
respectively; and a total of 84 respondents from district Baramulla, 70 group
respondents and 14 individual respondents. The sampling plan that has been
followed at various levels is presented in the table 3.2.1 and 3.2.2.
Table 3.2.2: Blockwise Composition of Sample
District |
Type |
Total |
|||
Individual |
SHG |
||||
Srinagar |
Block |
Srinagar |
28 |
64 |
92 |
Total |
28 |
64 |
92 |
||
Anantnag |
Block |
Dachnipora |
13 |
18 |
31 |
Qaimoh |
13 |
6 |
19 |
||
Shahabad |
5 |
20 |
25 |
||
Shangus |
11 |
9 |
20 |
||
Total |
42 |
53 |
95 |
||
Baramulla |
Block |
Baramulla |
14 |
0 |
14 |
Pattan |
0 |
26 |
26 |
||
Singpora |
0 |
25 |
25 |
||
Sopore |
0 |
19 |
19 |
||
Total |
14 |
70 |
84 |
Source:
Field Survey
3.3.
Measurement
Scale and Design of the Research Instrument
In
order to capture the impact of access to finance on various socio-cultural
variables, five dimensions, spread over 20 variables have been identified and
put together in the form of a well structured questionnaire; the wider
dimensions for impact assessment are Participation & Confidence, Problem
Solving & Leadership, Bargaining & Negotiating Power, Health &
Hygiene, and Financial awareness as shown in Table 3.3.2.
The
given socio-cultural indicators have been measured on a scale usually used in
psychometric analysis called Cantril’s Self Anchoring Ladder. The Cantril
Self-Anchoring Striving Scale (Cantril, 1965) has been included in several
Gallup research initiatives, including Gallup's World Poll of more than 150
countries, representing more than 98% of the world's population, and Gallup's
in-depth daily poll of America's wellbeing (GALLUP-HEALTHWAYS WELL-BEING INDEX;
HARTER; GURLEY, 2008; DIENER et al., 2009).
With
most psychological or sociological scales, researchers will utilize Cantril Scale
in ways they find empirically and conceptually appropriate. Besides, Cantril
Scale has also been included in surveys, alongside a number of items, measuring
many facets of wellbeing (i.e., law and order, food and shelter, work,
economics, health, and daily experiences), which provides the opportunity to
analyze how the Cantril Scale differentiates respondents in relationship to
these other variable.
The
ladder consists of 11 points and 10 steps from 0 to 10 where ‘0’ means ‘worst
possible’ and ’10’ means ‘best possible’. The item queries respondents as to
which step of the ladder they personally feel they stand at present and
similarly the step of the ladder they feel they stood before participation to
the program.
For
the purpose of dimension reduction Principal Component Analysis has been used
with a Varimax rotation and eigen values equal to or more than 1. Five factors
were extracted with significant communalities ranging from 0.496 to 0.861 which
indicates that a fair amount of variance has been extracted by the factor
solution. The factors finally extracted have been named indicating various
statements/variables grouped under the respective sets.
Thus
five factors spread over 20 variables with a total explained variance of 65
percent have been named as: Financial
Awareness (18.43% V.E.), Problem
Solving & Leadership (16.40% V.E.), Bargaining & Recognition (14.73% V.E.), Health & Hygiene (9.53% V.E.), and Participation & Confidence (5.37% V.E.). Financial Awareness
has the highest explained variance is the highest impact factor which suggests
that social empowerment can substantially be improved through financial
literacy.
The
adequacy of the sample size was confirmed using both the Kaiser-Meyer Olkin
(KMO) Sampling Adequacy Test and Bartlett’s Test of Sphericity (BTS). KMO
Values of 0.895 and a Chi-Square at 2390.58, (P≤0.000) indicate that the
correlation matrix is not an identity matrix, thus validating the suitability
of factor analysis.
Exhibit 3.3.1: KMO and Bartlett's Test
Kaiser-Meyer-Olkin
Measure of Sampling Adequacy. |
.895 |
|
Bartlett's Test of
Sphericity |
Approx. Chi-Square |
2390.587 |
Df |
190 |
|
Sig. |
.000 |
Exhibit
3.3.2: Factor Analysis – Dimension Reduction.
Factor/ Dimension |
Element/Variable |
Factor
Loadings |
Communalities |
Initial
Eigen Values |
Rotated
Eigen Values |
Explained
Variance |
F1 Financial
Awareness |
Awareness about
Financial Products |
.702 |
.563 |
7.030 |
3.691 |
18.453 |
Awareness about Govt.
And Bank Schemes |
.702 |
.602 |
||||
Maintenance of
Economic Affairs |
.830 |
.782 |
||||
Awareness about Bank Deposits |
.775 |
.680 |
||||
Awareness About Bank
Advances |
.764 |
.716 |
||||
Awareness about
Insurance Products |
.694 |
.553 |
||||
F2 Problem
Solving & Leadership |
Handling Problems |
.820 |
.739 |
2.352 |
3.281 |
16.405 |
Decision Making |
.678 |
.617 |
||||
Leadership |
.562 |
.648 |
||||
Recognition |
.575 |
.567 |
||||
F3 Bargaining
& Recognition |
Societal Recognition |
.753 |
.658 |
1.456 |
2.946 |
14.730 |
Membership Public
Institutions |
.719 |
.636 |
||||
Negotiating Power |
.831 |
.707 |
||||
F4 Health
& Hygiene |
Healthcare
Expenditure |
.760 |
.671 |
1.049 |
1.908 |
9.538 |
Education Expenditure |
.741 |
.861 |
||||
Food Expenditure |
.649 |
.636 |
||||
F5 Participation
& Confidence |
Gram Sabhi
Participation |
.490 |
.496 |
1.013 |
1.075 |
5.377 |
Satisfaction in Life |
.518 |
.569 |
||||
Authority in Public
matters |
.483 |
.498 |
||||
Participation in
Public Meetings |
.793 |
.701 |
For
the purpose of summarising, Gallup in its major research initiatives has formed
three distinct groups and the same has been adopted for the current study:
·
Thriving
(>7): Well being that is strong, consistent and
progressing with a positive outlook towards future.
·
Struggling
(5-7): Well being that is moderate, inconsistent and
have relatively negative outlook towards future.
·
Suffering
(<4): Well being that is weak, high risk and highly
negative outlook towards present as well as future life.
3.4.
Sample
Characteristics
The
State of Jammu and Kashmir has 21.63% of its population living Below Poverty
Line (Economic Survey 2007-08). Jammu and Kashmir has been found to lag behind
all other states of the Northern Region with financial Exclusion to the extent
of 67% (Report of the Committee on Financial Inclusion, 2008; Sangmi and
Kamili, 2010).
NSSO
data (59th Round) indicates that the proportion of non-indebted
farmer households was most pronounced in Jammu and Kashmir (68.2%) in the Northern
Region. The State has witnessed an absolute absence of complimentary
institutions to support financial inclusion initiatives of various banking and
non-banking entities; the State is also a victim of unequal participation by
the banking fraternity (KHAKI; SANGMI, 2012).
The
present study is concentrated on the Kashmir valley of the State only. The
socio-economic profile of the districts under study is presented in the table
3.4.1 below.
Table 3.4.1: Development and Poverty
Indicators of districts under study
District^ |
No. of SHGs formed since inception* (March 2012) |
Poverty Ratio (October 2007)** |
Contribution to NSDP at Current Prices (%)** |
No of SSI Units** |
Employment in SSI Units** |
Bank Branches 2010-11 ** |
Srinagar |
88 |
6.51 |
14.57*** |
10021 |
48403 |
151 |
Ganderbal |
387 |
24.23 |
137 |
641 |
24 |
|
Budgam |
1974 |
26.64 |
5.52 |
4121 |
27873 |
39 |
Anantnag |
1131 |
14.46 |
11.04*** |
4312 |
18723 |
65 |
Kulgam |
512 |
22.59 |
149 |
660 |
29 |
|
Pulwama |
448 |
26.18 |
6.85*** |
2816 |
13307 |
37 |
Shopian |
173 |
16.42 |
115 |
392 |
18 |
|
Baramulla |
1153 |
26.49 |
11.17*** |
4184 |
17216 |
94 |
Bandipora |
402 |
31.09 |
117 |
421 |
17 |
|
Kupwara |
937 |
32.55 |
4.37 |
1812 |
6351 |
47 |
*Source:
Directorate of Rural Development Kashmir (DRDK) |
||||||
**Source:
Directorate of Economics and Statistics, Government of Jammu and Kashmir |
||||||
***
Indicates figures of 2004-05 for the respective districts combined |
||||||
^
District Leh and Kargil has been excluded from the study. |
For
the present study, a Sample of 3 districts out of a total of 14 districts has
been taken, the general characteristics of which are presented in the table
3.4.2. The sample consists of a total of 271 beneficiaries from three districts
chosen across from all the regions of the Valley – North, Centre and South.
District Baramulla has been chosen from North, Anantnag from South and Srinagar
from Centre.
The
Sample consists of 92 respondents from Srinagar – 28 Individual Beneficiaries
and 64 Group beneficiaries, 95 respondents from Anantnag – 42 and 53 Individual
and Group Beneficiaries respectively, and 84 Respondents from Baramulla – 14
and 70 Individual and Group Beneficiaries respectively. Overall 84 Individual
beneficiaries and 187 group beneficiaries which composed of 69 Male respondents
and 202 female respondents have been selected. While as majority of male
respondents were found to be independent beneficiaries (61 out of 69), female
respondents were generally group beneficiaries (179 out of 202).
Table 3.4.2: Sample Characteristics.
Sample Characteristic |
Frequency |
Percentage |
Sample Characteristic |
Frequency |
Percentage |
Type |
|||||
Group |
187 |
69.00 |
Male |
8 |
|
Female |
179 |
||||
Individual |
84 |
31.00 |
Male |
61 |
|
Female |
23 |
||||
Total |
271 |
100.00 |
Total |
||
|
Male |
69 |
25.46 |
||
|
Female |
202 |
74.54 |
||
District |
|||||
Srinagar |
92 |
34.00 |
Individual |
28 |
|
Group |
64 |
||||
Anantnag |
95 |
35.00 |
Individual |
42 |
|
Group |
53 |
||||
Baramulla |
84 |
31.00 |
Individual |
14 |
|
Group |
70 |
||||
Total |
271 |
100 |
|||
Activity Involved |
Education |
||||
Crewel |
87 |
32.10 |
Illiterate |
155 |
57.20 |
Sozni |
80 |
29.52 |
Primary |
21 |
7.75 |
Spinning and Knitting |
35 |
12.92 |
Middle |
55 |
20.30 |
Diary and LiveStock |
34 |
12.55 |
Secondary |
34 |
12.55 |
Vegetables |
22 |
8.12 |
Graduates & Above |
6 |
2.21 |
Other |
13 |
4.80 |
Total |
271 |
100.00 |
Total |
271 |
100 |
|||
Family Composition |
Occupation |
||||
Nuclear <5 Members |
94 |
34.69 |
Trading |
42 |
15.50 |
Nuclear 5-10 Members |
147 |
54.24 |
Agriculture |
17 |
6.27 |
Joint 5-10 Members |
10 |
3.69 |
Both Trade & Agriculture |
168 |
61.99 |
Joint >10 Members |
20 |
7.38 |
Daily Wagers |
44 |
16.24 |
Total |
271 |
100 |
Total |
271 |
100 |
Source: Field Survey
3.5.
Tools
of Analysis
The
data has been categorised, edited and arranged in a logical order. In the
process certain errors were detected which have been corrected subsequently.
Tabular analysis has been done both manually and using MS Excel and SPSS 20.0
version. Statistical tools like percentage, average and scaling techniques have
been used.
In
order to assess the impact of financial access on Socio-political profile of
beneficiaries, same stock of beneficiaries have been taken at two time periods
to draw the comparison between the pre- and post- scores using paired samples
t-test.
4. RESULTS AND DISCUSSIONS
Traditionally
Poverty has been understood to be the lack of access to basic facilities and
sources of income, while as the present concept of Poverty has evolved to
include numerous social and economic parameters. Poverty in the
multidimensional context is interpreted as lack of assets or sources of income,
powerlessness, lack of skill, vulnerability defencelessness and volatility in
returns or income.
The
determining assets may be human (capacity build up), natural, physical, social
(social capital and networks), and financial (access to credit) (WORLD BANK,
2000, p 34). The lack of access to these enabling assets incapacitates an
individual to take on profitable activities and thus leading to multiple deprivations.
Studies
also reveal that multidimensional poverty can be reduced, as a long term
strategy, by improvements in one dimension which would eventually lead to a
spill-over effect to the other dimensions and thus reduce vulnerabilities and
deprivations (WRIGHT, 2000; LITTLEFIELD; MORDUCH; HASHEMI, 2003).
Many
theorists believe that the most important component in multidimensional poverty
mix is ‘access to finance’; and the present study, in line with the notion,
tries to assess the impact of financial inclusion on the socio-political
empowerment of beneficiaries (NEPONEN, 2003; SRINIVASAN; KUPPUSAMY, 2010;
MKNELLY; DUNFORD, 1998, 1999; PITT et al., 2003).
It
has also been argued that microfinance may affect poverty even without
affecting the borrower’s income, either by relatively easier & cheaper
credit, or by stimulating economic activities and development of social capital
(MOSLEY, 2001; ZOHIR; MOTIN, 2004). Microfinance
Programmes are believed to be an important force in the creation of social capital
in deprived section of the society; the microfinance services have been found
to increase spending on education on healthcare which may extend beyond the
programme participants.
Microfinance
through creation of social capital has even been found to reduce migrations by
increased employment opportunities, development of demand for the products and
increased income (ZOHIR; MATIN, 2004, MAKINA; MALABOLA, 2004).
The
present study attempts to look for the impact of financial inclusion on the
extent and direction of changes in the socio-cultural variables across various
empowerment levels on Cantril’s Ladder. The summarised results presented in the
table 4.1 below clearly indicate that access to finance (credit) has a
significant and positive impact on almost all the parameters of socio-political
empowerment.
The
classical concept of microfinance which lays its foundation on group formation
and development of entrepreneurial skills lays emphasis on the development of
social capital at community levels. As indicated in the table below, financial
inclusion has significantly increased the leadership ability, bargaining and
negotiating ability and social interactions of beneficiaries; which are the
most important determinants of success for a micro-entrepreneur.
The
results further indicate that even though the impact is positive and
significant on all dimensions, there are only a few variables where impact has
been sufficient enough to upgrade the beneficiaries from one category of
empowerment to the other.
Whereas
participation in a microfinance programme enables beneficiaries to upgrade from
‘struggling’ status to ‘striving’ status in case of dimensions ‘problem solving
and leadership’ and ‘health and hygiene’, it fails to make any such impact on
other dimensions – ‘participation & confidence’, ‘bargaining &
recognition’ and ‘financial awareness’. The results, however, indicate that the
reduction in the deprivations within each empowerment category is sub
Table 4.1: Socio-Political
Impact of Financial Inclusion (Paired Sample Statistics)
Paired Sample Statistics |
|||||
Pair Description |
Mean (Pre) |
Mean (Post) |
Mean Difference |
t |
P. Value |
Gram
Sabha Participation |
.0111a |
.0111a |
-- |
-- |
-- |
Public
Meetings |
.3284 |
.8598 |
-.53137 |
-17.497 |
.000 |
Authority |
.9151 |
1.2583 |
-.34317 |
-11.877 |
.000 |
Satisfaction |
1.3690 |
1.7343 |
-.36531 |
-12.466 |
.000 |
Participation & Confidence |
.6559 |
.9659 |
-.30996 |
-22.851 |
.000 |
Handle
Problems |
.7712 |
1.1734 |
-.40221 |
-13.478 |
.000 |
Taking
Decisions |
.8118 |
1.2251 |
-.41328 |
-13.586 |
.000 |
Leadership |
.5830 |
1.1808 |
-.59779 |
-19.732 |
.000 |
Recognition |
1.4428 |
1.8044 |
-.36162 |
-12.367 |
.000 |
Problem Solving & Leadership |
.9022 |
1.3459 |
-.44373 |
-25.989 |
.000 |
Societal
Recognition |
.4760 |
1.0037 |
-.52768 |
-17.368 |
.000 |
Membership |
.1328 |
.5904 |
-.45756 |
-15.092 |
.000 |
Negotiating
Power |
.2509 |
.8856 |
-.63469 |
-20.117 |
.000 |
Bargaining & Recognition |
.2866 |
.8266 |
-.53998 |
-25.650 |
.000 |
Healthcare |
.7528 |
1.0664 |
-.31365 |
-10.746 |
.000 |
Childcare |
.5488 |
.8984 |
-.34959 |
-11.476 |
.000 |
Hygiene |
.9852 |
1.2288 |
-.24354 |
-9.323 |
.000 |
Health & Hygiene |
.7454 |
1.0369 |
-.29151 |
-16.335 |
.000 |
Awareness
Financial Products |
0.0000 |
.0221 |
-.02214 |
-2.472 |
.014 |
Awareness
Government Schemes |
0.0000 |
.0369 |
-.03690 |
-3.216 |
.001 |
Management
of Economic Affairs |
.0037 |
.0332 |
-.02952 |
-2.866 |
.004 |
Awareness
Bank Deposits |
0.0000 |
.0037 |
-.00369 |
-1.000 |
.318 |
Awareness
Bank Advances |
0.0000 |
.0037 |
-.00369 |
-1.000 |
.318 |
Insurance
Awareness |
.0000a |
.0000a |
-- |
-- |
-- |
Financial Awareness |
.0006 |
.0258 |
-.02522 |
-2.767 |
.006 |
Source: Field Survey
Whereas
financial literacy is considered a pressure point for the success of
microfinance programmes, the results indicate that financial literacy is the
lowest impact dimension with only 2 out of 6 variables implying a significant
impact (p=0.01).
The
participants have clearly not witnessed a large enough impact in their financial
literacy to alleviate their disempowerment status; the participants continue to
remain deprived on account of their financial awareness. Theory suggests that
the inability of financial inclusion programmes to enhance the quality of
financial and economic awareness hampers the progress of a microenterprise
which may further lead borrowers to choose incorrect coping strategies at the
time of distress or seasonal slack.
Social
capital at all levels is an important in determining a successful coping strategy;
any failure in either choosing a coping strategy or reaching a desired level of
social capital may result in a downward spiral of deprivations. Results from
the present study indicate that participants have substantially enhanced their
social capital in terms of public interactions, bargaining and negotiating
power, leadership qualities, membership in social and political organisations,
problem solving, decision making, healthcare and hygiene.
The
other impact variables like authority in public matters, satisfaction, and
societal recognition have shown somewhat positive impact. The variable –
‘participation in Gram Sabha activities’ have not shown any improvements at
all, the discussion with the participants reveal that local political structure
is practically missing in the valley.
Variables
relating to financial literacy and economic awareness have not exhibited
substantial impact, only 2 out of 6 variables pertaining to financial awareness
are significant (P=0.01). The summarised results imply that financial inclusion
has substantially improved the socio-political status of the participants, it
may thus be concluded that financial inclusion leads to the creation of social
capital.
5. CONCLUSIONS,
SUGGESTIONS AND LIMITATIONS OF THE STUDY
The
theoretical generalisations that access to finance leads to socio-political
empowerment have not been rigorously researched. Very little research has been
conducted in the Kashmir Valley in the field of Financial Inclusion and its
impact, and in order to fill this gap, the present study is an attempt to
contribute to what little is already known of the relationship between
financial inclusion and the creation of social capital.
In
order to achieve this objective, the present study has tried to assess the impact
of credit on the socio-political status of the beneficiaries of Swarnjayanti Gram Swarozgar Yojana
(SGSY), now known as National Rural Livelihood Mission (NRLM) in Kashmir. The
results are consistent with a generally accepted notion that participation in
financial inclusion programmes helps to increase the social capital of
participants.
Financial
inclusion enables participants to take a greater role in decision making,
having greater access to financial and economic resources, building greater
social networks, having greater bargaining and negotiating power, surviving
shocks and having greater freedom and mobility.
The
study has the following major limitations:
a) The
study has failed to account for the spillover effect; the measurement of
spillover impact of programme on the non-participants or the spillover impact
of other complementary programmes on the programme participants/beneficiaries
under observations has not been determined and/or adjusted for.
b) The
study has heavily relied on a methodology with inbuilt recall limitation in
which same set of beneficiaries have been asked to recall their status as it
was in absence of the programme support. Efforts have been made to avoid the
bias arising out of remembering the responses by taking an adequate pause
between the pre and post (present) responses but still the recall limitation
can’t be ruled out.
In
view of the results arrived at, a few measures are suggested to increase the
effectiveness of financial inclusion on the overall socio-economic development
of the participants. An effective monitoring and pre-sponsorship appraisal may
help in increasing the impact of these programmes. It has been widely seen that
the participants of most of the microfinance programmes are non-poor
households.
An
effective targeting of poor and ultra poor household must be ensured in the
implementation of these programmes. Effective and hassle free credit to
entrepreneurial and ambitious groups of individuals may prove more than a
handful in these programmes, by leveraging the group dynamics by way of sharing
their social capital and networks.
Support
assistance from NGO’s and Trade Federations in terms of marketing and logistic
support must be arranged to form a symbiotic and a win-win proposition for both
the parties. Melas, Expos and
Financial Literacy Camps should be organised to boost the morale of these
micro-entrepreneurs while also providing them a networking opportunity to
increase their business activity through such events.
Further,
researchers must take up financial inclusion as a serious subject for study in
the area. There is also a need to follow the participants for longer durations
with close monitoring to get a better insight about the relationship between
various socio-economic dimensions of poverty and financial inclusion.
Note:
The Research has been carried between April,
2014 to December, 2014.
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