Pacific Business Review International

46 VolumeReview
Pacific Business 5 IssueInternational
1 (July 2012)

Role of Micro-Financing in Women Empowerment :

An Empirical Study of Urban Punjab
DR.SANGEETA ARORA*, SAPNA ARORA**

Women empowerment is a critical pre-requisite for the socio-economic development

of any community.Microfinance industry has always targeted women as she is
considered poor strata of the society. Microfinance industry as a tool of poverty
alleviation aims to bring a drastic change in lives of female which could magically
improve the life of family and society as a whole. The main objective of this research
paper is to study the perceived impact of micro credit on the women empowerment
in Urban India, with special reference to Punjab, one of the most prosperous states
of India. Factor Analysis techniquewas applied on the 26 variables on a sample size
of 334 females. These variables were summarized into six factors namely, socio-
economic status, personality factor, Financial liberation, familial relations, child
development and inhibiting factor. Regression model further analyzed that micro
credit has a significant impact on the socio-economic status, personality, financial
liberation and family relations. Moreover it was found that women haveadapted to
the inhibiting factors which are in their stride.
Keywords: Women Empowerment, Micro-Credit, Socio-economic, Livelihood, Dual
responsibility, Liberation.

Introduction The growing social awareness across the globe has

Poverty has a women's face. Worldwide, women and made the issue of gender equality and women
girls are poorer and more disadvantaged then men. empowerment significant in the development discourse
Gender inequality contributes to their vulnerability, with of recent past (Samanta, 2009). The economic well-
the result that women make up around 70% of the being of women is often used as an indicator of overall
world's poorest people. (Manjoor &Manders, 2009).In advancement as women contributes to nurture the
country like India women still have a very weak position society.In India, microfinance has become an important
in society. She is dominated by male person in Indian tool of economic development (Tiwari and Thakkur
household. Punjab, one of the prosperous state of India 2007). In this direction, the government of India (GOI)
has no dearth of cases showing the poor state of female. has made continuous attempts to formulate policies and
There are just 876 females for every 100 males in strategies that put more emphasis on empowering
Punjab reflecting the biases against women. Women women and on bringing women into "Mainstream".
suffer a lot from domestic violence and have to face Both the Indian government and NABARD have
gender biasness. The societies that discriminate against started various microfinance schemes since 1990s to
women have more poverty, lower standard of living raise poor women and their families above the poverty
and economic growth. To overcome such state, Women
empowerment is considered as a ray of hope.

*Reader, Department of Commerce and Business Management ,Guru Nanak Dev University, Amritsar
**Project Fellow, Department of Commerce and Business Management, Guru Nanak Dev University, Amritsar
Volume 5 Issue 1 (July 2012) 47
line. This paper presents an empirical work on the impact "gaining the ability to generate choices and exercise
of finance in the hand of women. The research has bargaining power", "developing a sense of self-worth,
focused on the empowerment of women with financial a belief in one's ability to secure desired changes, and
services at her disposal. Section-II outlines conceptual the right to control one's life" are important elements
framework of women empowerment; Section-III of women's empowerment. It is the process of
highlights the literature work that has been done on increasing the capacity of women to make choices and
women empowerment and micro-finance and finds the to transform these choices into desired actions and
gap between the earlier studies and the present study. outcomes (Krishna, 2003).
In section-IV, objective of the study and the research
methodology that has been used in the paper is discussed It can be summarized that women empowerment refers
along with data methodology. The analysis and to provision of leverages to women in the society who
interpretation of the data has been studied in Section V are otherwise deprived.
and finally the paper concludes with the Section VI.
Review of Literature
Conceptual Framework A lot of research work has been carried out in different
The term 'Empowerment' has been defined in different parts of the world to know the success of micro-credit
perspectives by various authors. Many of them have (finance) in empowerment of women. Goetz &Gupta
defined empowerment as a process of change in (1996); Gibb Sarah (2008) found that micro-credit has
existing power structure. It is concerned with power, failed to empower women as women could not change
and particularly with the power relations and the her traditional household role and could not retain control
distribution of power between individuals and group over money. Sijders and Dijstera (2009) also found that
(Kahlon, 2004). Batiwala (1994) describes micro-credit has failed to effect the political position of
empowerment as "the process of challenging existing women and hence overall empowerment was not
power relations and of gaining greater control, over observed. Similarly, Samanta (2009) propounded that
the sources of power". women have no control over credit which is the failure
of microfinance to empower women.
The concept of empowerment has been considered
from social aspect by many authors (Bennett 2002; However, Authors like Hashemi, Schuler and Riley
Malhotra 2002; Saraswathy 2008; Swain 2007). It has (1996); Hunt. J & Kasyanathan N. (2002) Agha
also been viewed from political aspect by few. et.al.(2004); Anna K.P. Saraswathy
Women's participation in politics, her awareness and &PanickerK.S.M.(2008); Aruna &Jyothimays (2011)
knowledge, her participation in political campaign are studied the impact of micro- credit and micro finance
considered. Puhazhendi and Badatya (2002) defined programme on the lives of women and found micro-
empowerment as, "Great depth of the concept of power, credit as a significant factor contributing to empower
which ranges from inner power (covering women in one way or other. On the other hand,some
characteristics like confidence, will and self-esteem) studies have concluded with the mixed impact of
to societal power." micro-finance on Women. Leach et. al. (2002) found
that micro-credit has succeeded in socially empowering
Some literature work has conceptualized empowerment women where economic empowerment could not be
as decision making ability. According to UNIFEM , possible due to lack of knowledge and understanding
48 Pacific Business Review International

among women about business. Berglund (2007) found lives residing in urban Punjab. This research is an
the individual empowerment but no empowerment attempt to draw the attention of policy makers towards
impact was found on groups. Schechter (2007) the urban India where the microfinance services can
observed that credit facilities helped women to run a serve in a more profitable and sustainable way to make
business and earn small profits but they were still found a drastic change in the lives of women.
dependent on family members.
Research Methodology
There is no dearth of work done on women The objective of the study is to determine whether
empowerment and microfinance; it was found that a microfinance services are instrumental in empowering
lot of research work has been done on Southern Region Women in Urban Punjab.
of India. But as far as Punjab is concerned, there is
paucity of research especially in Urban Punjab. There The sample size of 350 females' was selected to fill
is difference in the financial needs of urban and rural the questionnaire out of which responses of 334 were
people. So, this research paper has focused on Urban valid and complete. Table 1 provides the demographic
Punjab where microfinance industry is still in the profile of the respondents. Judgment and Convenience
nascent stage and not much research work has been Random sampling technique has been used for collecting
done to gauge the impact of microfinance on women's information from those who belongs to lower income

Table No. 1: Demographic Profile of the Sample

City Amritsar Jalandhar Ludhiana Total

Age
18-25 8 8 10 26
25-40 64 62 64 190
40-50 32 30 30 92
50and 8 10 8 26
above
Total 112 110 112 334
Income
P.M.(Rs.)
Nil 20 16 18 54
Less than
2000 22 20 26 68
2000-5000 60 62 58 180
5000-7500 9 10 9 28
7500-1000 1 2 1 4
Total 112 110 112 334
Volume 5 Issue 1 (July 2012) 49

Occupation
Domestic-Servant
Street-Vendors 30 36 32 98
Petty Shop-keepers 17 15 14 46
Housewife
Others 19 18 17 54

15 18 21 54
31 23 28 82
Total 112 110 112 334

strata.Micro credit female clients has been selected To analyze the impact of microfinance on Women,
from urban areas of Punjab namely i.e.., Amritsar, Multiple Regression model was applied on factors to
Ludhiana and Jalandhar. Those women who are availing test the null hypothesis i.e., Ho:There is no significant
loan from either informal or formal source have been impact of Microfinance services onwomen
the part of sample size. The sample contains 142 women empowerment.
taking loan from formal sources like Bank, MFI etc.
where 192 respondents were those who were taking Analysis and Interpretation
loan from informal channels such as moneylender, Factors impacting Women Status
employee, relative/friends etc. Various questions were The questionnaire contained twenty six statements
made regarding their perception about the benefits of reflecting the impact of micro credit services on women
credit on their lives. empowerment. The respondents were asked to rate
these statements on five point likert scale as to how
Most of the respondents chosen were illiterate or less they perceive the impact of micro credit on their lives,
educated, so the questionnaires were verbally explained ranging from highly agree to highly disagree. Table
to them and responses were recorded according to the 2contains the list of the statements provided towomen
answers provided by the sample population. Table 1 respondents. The responses were further analyzed
provides the demographic profile of the sample. using the technique of Factor analysis.
Further, In order to analyze the data, Factor Analysis
Technique was adopted which helped to load the
number of variables on few factors and reduced the
numbers of variables into more manageable factors.
Principal Component Analysis (PCA) was adopted to
rotate the variables followed by Varimax rotation.
Statistical Software SPSS 17.0 was used to analyze
the results.
50 Pacific Business Review International

Table 2: List of Statements

Sr. No. Statements

1 Poverty reduction
2 Improvement in Income level
3 Rise in unnecessary expenditures on consumption
4 Improvement in employment level
5 Improvement in consumption level of family
6 Improvement in standard of living
7 Better utilization of available resources
8 Developed entrepreneurship skill
9 Improvement in social status
10 Awareness of social issues
11 Increase in children enrollment to schools
12 It does not result into increase child labor in family business
13 It serves families instead of individuals
14 Confidence building and gaining self-respect
15 Increase in decision making power
16 Recognition in family
17 Improves market knowledge
18 Improved communication skill
19 Control over loan use
20 Increase in self-consumption
21 Positive impact on family health
22 Increase in mobility
23 Reduced domestic violence
24 Positive change in men’s attitude
25 Increased burden
26 Participation in group discussion

For this purposethe internal consistency of the data was adequacy was measured through Kaiser-Meyer-Olkin
verified through cronbach alpha which turned out to be and Bartlett's Test of Sphericity which were also found
0.880. This is a good indicator of reliability proving it to be favorable.
adequate for further analysis.Further, the sampling
Volume 5 Issue 1 (July 2012) 51
Table 3: Sampling Adequacy Tests

Reliability Statistics
Cronbach’s Alpha N of Items
0.880 26
KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling .868
Adequacy (KMO)
Barlett’s Test of Approx. chi-Square 3532.760
Sphericity Df 325
Sig. .000

Application of Factor Analysis came out to be significantly high. Similarly, sampling

In order to extract the factors that have impact on adequacy of the data was cross checked through anti-
women's lives, factor analysis has been carried out. image matrix.
For this purpose Principal Component analysis was used
and a six factor solution was obtained (after Varimax Rotated Factor Analysis
solution) on the basis of the criterion of Eigen Value Once the correlation variables are obtained, variables
greater than one (>1). Initially, correlation matrix was were explained through Eigen value. As table 4 reveals
obtained showing the inter-correlation amongst the that there are six factorsthat have Eigen values greater
variables. Moreover correlation between the variables than 1.

Table No. 4: Rotated Factor Matrix

Factors Eigen
Variables 1 2 3 4 5 6 Values
VAR 1 .736 .265 .063 .171 .090 .014 7.826
VAR 2 .814 .214 .096 .178 .085 .013 1.913
VAR 3 .243 -.083 .148 .146 -.139 .792 1.759
VAR 4 .630 -.113 .250 .230 .022 -.085 1.399
VAR 5 .594 .163 .019 .094 .074 .253 1.369
VAR 6 .704 .346 .023 .069 -.010 .143 1.037
VAR 7 .690 .232 -.086 -.022 -.027 .085 .972
VAR 8 .695 .289 .328 .086 -.028 -.111 .940
VAR 9 .550 .264 .475 -.059 -.338 .132 .915
VAR 10 .514 .288 .291 .003 -.316 .226 .794
VAR 11 -.228 -.214 .212 .138 .616 .115 .744
52 Pacific Business Review International

VAR 12 -.243 -.128 -.003 .113 -.647 .086 .699

VAR 13 .111 .515 -.067 .132 -.055 .014 .664
VAR 14 .248 .720 .051 .055 -.033 -.087 .656
VAR 15 .254 .717 .218 .112 -.003 .111 .576
VAR 16 .123 .676 .206 .149 .116 -.010 .512
VAR 17 .248 .615 .063 .091 .056 .082 .444
VAR 18 .340 .470 .167 .309 -.052 .122 .435
VAR 19 -.055 .193 .760 -.161 .200 .066 .400
VAR 20 .309 -.120 .627 .269 -.101 -.064 .383
VAR 21 .081 .300 .459 .460 -.238 .187 .347
VAR 22 .166 .166 .684 .263 .158 .037 .309
VAR 23 .167 .179 .078 .814 -.009 .027 .275
VAR 24 .147 .258 .073 .740 .060 -.014 .252
VAR 25 -.028 .325 -.112 -.218 .339 .512 .211
VAR 26 .367 .266 .090 .277 .349 -.018 .167
% of 30.099 7.358 6.764 5.380 5.266 3.989
variance
Cumulative 30.099 37.456 44.220 49.600 54.865 58.854
Variance
Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.

The second last row of the table shows the percentage factors were extracted on the basis of common
of variance explained by individual factor. It was dimensions reflected by the variables.
observed that these six factors jointly explained 58.854
percent of the variance. FACTOR 1: Improvement in Socio-Economic
Status This factor explained 30.09 per cent of the
Orthogonal Rotation with Varimax Rotation method was variance of all the factors. This factor is inclusive of
applied on all the twenty six variables loaded on six number of variables, namely, poverty reduction,
important factors extracted through Eigen values. Table improved income level and standard of living,
4 shows the rotated factor matrix. Varimax Rotation improvement in employment level, family consumption.
method is one of the popular method of orthogonal Women are now socially more active and aware about
rotation and it has helped in reducing the number of social issues. Theyconsider themselves in a better
variables and factor loadings greater than 0.50 (ignoring position economically as well as socially. With financial
signs) have been retained. services they are able to develop their entrepreneurial
skills and utilize the resources in an improved way (V7).
Explanation of Factors
Table 5 lists the factors extracted from the list of FACTOR 2: Enhancement in Personality Factor
variables and the variables attached therewith. The As women can easily avail credit services, they
Volume 5 Issue 1 (July 2012) 53
perceive themselves more confident (V14). Generally, are more knowledgeable about market (V17=0.615).
the women are so much occupied by household activities Women perceive contribution of micro finance services
that they are not recognized as an equal partner in towards the family rather than as an individual benefit.
household decisions. But with more credit services Combination of all these variables addsto their
available at their doorstep women take decisions and personality.

Table No. 5: Factors of Women empowerment as perceived by WomenClients

Factors Factors Name Statements Score

No.
1. Improvement in V 1:Poverty reduction 0.736
Socio-Economic V2:Improvement in Income 0.814
Status level
V4:Improvement in 0.630
employment level
V5:Improvement in
consumption level of family 0.594
V6:Improvement in standard
of living 0.704
V7:Better utilization of
available resources 0.690
V8:Developed
Entrepreneurship Skills 0.695
V9:Improvement in social
status 0.550
V10:Awareness of social 0.514
issues
2. Enhancement in V13:It serves families instead 0.515
Personality of individuals
Factor V14: Confidence building 0.720
and gaining self-respect.
V15:Increase in decision 0.717
making power
V16:Recognition in family 0.676
V 17:Improves market 0.615
knowledge
54 Pacific Business Review International

1.
3. Improvement in V 19:Control over loan use 0.760
Financial V20:Increase in self- 0.627
Liberation consumption
V22:Increase in mobility 0.684
2.
4. Improvement in V 23:Reduced domestic 0.814
Familial violence
Relations V24:Positive change in 0.740
men’s attitude
3.
5. Positivity V 11: Increase in children 0.616
towards Child enrollment to schools.
Development V 12:It does not result into 0.647
increase child labor in family
business
6.
4. Inhibiting Factor V 3:Rise in unnecessary 0.792
expenditures on consumption
V 25:Increased burden 0.512

FACTOR 3: Improvement in Financial positively with reduced domestic violence (V23=

Liberation 0.814). As a woman is capable to share the family
This factor is indicative of financial independence of responsibility and is a contributor in bringing funds at
women. In a country like India, where gender home, she is respected by her family. Moreover due to
discrimination exists even at household level, the woman shared responsibility, men's frustration can also be
diminished resulting into improved family relations.
is dominated by male person. Micro finance services
have a potential to liberalize women financially where
FACTOR 5: Positivity towards Child
she has power to control the funds. The variables that
Development
are highlighted include her control over loan use, self-
This factor is an indicator of the change in the attitude
consumption and increase in mobility. This factor is of women and contributes 5.266 per cent of the total
contributing 6.764 per cent towards women variance. She seems to be more aware about the
empowerment. importance of education for her child. It has been
observed that the funds are utilized for children welfare
FACTOR 4: Improvement in Familial Relations and their education. Women are able to perform her
As women are able to earn and feed her family, duties towards child in a greater efficient way. The
Microcredit has helped women to improve her familial same is proved through research that resources in
relations. This factor contributes 5.380 percent women hands' result in the form of enhanced children
variances towards women empowerment as women. enrollment to school (V11) and diminished child labor
The results showed that the attitude of men has changed in family business (V12).
Volume 5 Issue 1 (July 2012) 55
FACTOR 6: Inhibiting Factor pathway to empowerment.
This factor does not directly contribute to women
empowerment but shows that micro credit services The factors scores of factors those extracted with the
has led into increased expenditure on consumption help of factor analysis were used for further analysis
(V3). As such loans are easily available from informal i.e. Multiple Regression Analysis.
sources which are spent on unproductive purposes.
Moreover this factor also adds to the burden of women Application of Multiple Regression Analysis
as she is under dual responsibility. But still women The technique of multiple regressions has been used to
consider it as part of their empowerment; the reason analyze the impact of microfinance services on women
being that she perceives itself to be more progressive empowerment as perceived by them. Table 6 provides
rather than considering it as a restrictive factor in their the list of variables used in multiple regression analysis.

Table 6: Multiple Regression Analysis

Name of the Definition Label

Variable
Dependent Impact of Microfinance services Y
Variable Microfinance lead to the improvement
Services on in the status of women as
Women perceived by them
Empowerment
REGR factor Improvement in Socio- X1
Score1 Economic Status
Independent REGR factor Enhancement in X2
Variable Score2 Personality Factor
REGR factor Improvement in X3
Score3 Financial Liberation
REGR factor Improvement in Familial X4
Score4 Relations
REGR factor Positivity towards Child X5
Score 5 Development
REGR factor Inhibiting Factor X6
Score6

Dependent Variable that were extracted from factor analysis out of the list
Dependent Variable taken was the empowerment of of 26 variables as provided in the table 4.
women with microfinance services as perceived by
them and the same was rated on five point likert scale. Model formulation
Independent Variable Before formulating model for regression analysis, it is
necessary to validate the data by checking whether
All the six factors were taken as Independent Variables the multi-collinearity exists between data. For this
56 Pacific Business Review International

purpose, estimated partial correlation between correlation matrix also indicates the nonexistence of
dependent and independent variables was calculated collinearity as no correlation is too high. It is insignificant
which measures the correlation among women in case of X5 and the same variable is removed in later
empowerment and the factors affecting the women stage while forming equation.
micro credit clients (Table 7). Moreover, the Pearson

Table 7: Pearson Regression of Correlation between dependent and independent variables

X1 X2 X3 X4 X5 X6 Y

X1 1

X2 -.106 1

(.053) -

X3 -.173 -.081 1

(.001) (.143) -

X4 -.057 -.027 -.043 1

(.298) (.629) (.430) -

X5 .035 .016 .026 .009 1

(.525) (.768) (.630) (.874) -

X6 -.062 -.029 -.047 -.015 .009 1

(.262) (.602) (.395) (.779) (.864) -

Y .432** .217** .341** .119* -.73 .128* 1

(.000) (.000) (.000) (.030) (.184) (.019) -

** Correlation is Significant at 0.01level (2 tailed)

*Correlation is significant at 0.05level (2 tailed)

In order to obtain more accurate results, tests such as be 1.000 for each independent variable; hence it can
Variance Inflation factor (VIF) and Tolerance level (1/ be accepted from the analysis that there exists no
VIF) were measured to test the multi-collinearity. VIF collinearity among the data.
equivalent or below 10 is said to be acceptable as it
reflects that data is free from multi-collinearity. In this After checking the multicollinearity, we can estimate
case, the value of VIF and Tolerance level came out to the regression model. To meet the objective, the
Volume 5 Issue 1 (July 2012) 57
perceived impact of microcredit services on the lives Where,
of women has been studied. Following model was used Y= Dependent Variable;
for studying the relationship between dependent and =Intercept term β1,β2,β3,β4, β5,β6
independent variables: are Regression coefficients
Y= α+ β1X1+ β 2X2 +β 3X3 +β 4X4+ β 5X5+ β 6X6 +Ut. X1, X2, X3, X4, X5,X6 represent Independent variables;
Ut= Error term.

The model has been summarized in the table given below (Table 8):

Table No. 8 Model Summar

R R Adjusted Std. Error Durbin-

Square R Square of the Watson
Estimate
.621 .385 .374 .655 1.968

The value of R in the model shows a marked degree of it is confirmed through normal probability curve and
correlation.The value of adjusted R2 is 0.374 which histogram.
indicates that all the variables extracted could explain
37.4 per cent of the variation in the dependent variable. The significance of the model is measured through
Hence, the model can be confidently said to be a ANOVA (Analysis of Variance) to test the following
generalized model. The difference between R square null hypothesis:
and adjusted R square is also satisfactory (0.385-
0.374=0.009), which is interpreted as the 0.09% less H0:β1=β2=β3=β4=β5=β6=0
variation in the outcome if it is derived from the actual The Null hypothesis explains mean values of regression
population. To check whether the model fulfills the co-efficient are equivalent to zero. Table 9 has been
assumption of independent errors, Durbin- Watson test drawn to reveal the significance level for F statistics. F
is applied. The result of Watson test (1.968) is found to ratio is highly significant; hence the null hypothesis is
be near 2, which is considered to be significant. It has rejected i.e., there is no significance difference between
been proved through the test that the data meets the the mean values of co-efficient. It is evident that the
assumption of independent errors. To cross check the value of one or more regression coefficient is not equal
assumption of normal distribution of the standard errors, to zero.

Table No. 9: Analysis of Variance

Model Sum of Squares Df Mean Square F Sig.

Regression 87.864 6 14.644 34.142 .000
Residual 140.256 327 0.429
Total 228.120 333
58 Pacific Business Review International

All these favorably support the argument that the model Regression Equation
is significant and can predict the outcomes. The estimated equation is as follows:
Y=3.108+0.357 X1+0.180X2+0.282X3+0.98X4+
Table 10 reveals the coefficient for regression variables. 0.106X6
The beta value coefficient allows us to test the strength
of relationship between women empowerment and the This equation can be used to know whether the micro-
impact of micro credit services on the lives of Women finance services are instrumental in women
clients.Independent variables i.e., X1, X2, X3, X4, and empowerment given the values of the factors
X6 have positive correlation as well as significant determining the impact of such services on women
values at 5 per cent level of significance. X5 which respondents. The equation has been obtained by
has negative beta has been eliminated for the purpose capturing the values of beta co-efficient through Table
of interpretation as well as from regression model. 10.

Table No. 10: Factors influencing the empowerment of Women

Model B S.E Beta T Sig.

Constant 3.108 .036 86.724 .000
X1 .357 .036 .432 9.954 .000
X2 .180 .036 .217 5.004 .000
X3 .282 .036 .341 7.856 .000
X4 .098 .036 .119 2.740 .006
X5 -.60 .036 -0.73 -1.680 .094
X6 .106 .036 .128 2.949 .003

The significant t-value corresponding to each variable as well socially. Similar results are shown by other
confirms the significant contribution of each variables such as positive impact of micro credit services
independent variable to the model. All factors have on personality of women and financial status of
significant values except X5 hence excluded while respondents. The next highest contributing factor that
formulating equation. Larger the value of t statistics, leads to empowerment of women is inhibiting factor (X6)
the contribution of the respective variable is known to which is making an indirect contribution to empower
be greater. The same fact has been shown through women. The positive results (Beta=0.128) reflects that
beta values. it has very small contribution in women empowerment
and the respondents does not hesitate to avail micro
The value of Beta coefficient is highest in case of services due to this variable. The smallest Beta in case
X1(improvement in socio-economic status of women) of X4 i.e. 0.119 shows that micro credit services
revealing that 43.2 percent of the variation in the contribute least to the family relationship of women
women empowerment can be explained by this clients. As proved by Table No. 9, Standard error (S.E.)
variable. So, it can be said that micro credit services corresponding to the beta value is 0.036 shows that only
lead to improvement in status of women economically small portion of S.E. varies across the samples.
Volume 5 Issue 1 (July 2012) 59
Conclusion sector Midwives in Uganda', Health Service
In this paper the impact of micro credit services on the Research, 39(6pt2): 2081-2100.
empowerment of women clients has been discussed. • Aruna, M. (2011). "The role of microfinance in
The factor analysis and regression test revealed several Women Empowerment: A study on the SHG Bank
factors that can influence the lives of women. The six Linkage Program in Hyderabad". The Indian
factors socio-economic status; enhancement in Journal of Commerce and Management Studies.
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