socio-economic empowerment of the poor...

International Journal of Economic Issues, Vol. 4, No. 1 (January-June, 2011) : 103-122© International Science Press

SOCIO-ECONOMIC EMPOWERMENT OF THE POORTHROUGH MICROFINANCE: AN EMPIRICAL STUDY OFNABARD SPONSORED MICROFINANCE PROGRAM IN

DEHRADUN DISTRICT (UTTRAKHAND, INDIA)

A. K. POKHRIYALAssistant Professor, Faculty of Commerce, H.N.B. Garhwal Central University,

Srinagar Garhwal, Uttrakhand, India

VIPIN GHILDIYALGraphic Era University, 566/6 Bell Road, Clement Town, Dehradun, Uttrakhand, India

Microfinance has been successful in bringing the social and economic empowermentto the poor throughout the world. In India also it has been a policy success yet therehas been a wide regional disparity. NABARD has been the major facilitator ofmicrofinance in India. The present work is an attempt made to assess the socio-economicimpact of NABARD sponsored microfinance programs in Uttrakhand state of Indianrepublic. The present work is based on the secondary and primary data. Primary datahas been collected from the Dehradun district using a questionnaire placed to 600people from different self help groups. Primary data has come from all the six blocksof the district. Analysis has been carried using t test, correlation and simple and multipleregression analysis. It is found that members of the self help groups have beenempowered socially and economically. But they demand more services like marketingassistance for their products from NABARD it order to reap the maximum benefits.JEL Classification: I32, O2, O18.Key words: Micro finance, SHG, Poverty, socio-economic empowerment, NGOs.

1. INTRODUCTION

Microfinance is a very renowned phenomenon worldwide now, which is helpful ineliminating poverty and strengthening the poor economically and socially. Almost allcountries are practicing it as a part of their policy for combating against poverty. InIndia also, it has become a policy success. In India microfinance programs areimplemented through self help groups. A self help groups is a group usually of 0-15people, which are from the same economic and social background. Initiated byNABARD (National bank for agricultural and rural development) that is the apexbody in the field of rural development, it has now come up a long way and has beenvery successful indeed. Yet there are regional disparities in the implementation andsuccess of microfinance programs. In South India microfinance has created various

104 / INTERNATIONAL JOURNAL OF ECONOMIC ISSUES

landmarks and has been very successful. It has now become a revolution for and ofthe common man there, but in other parts of India it has not been that successful.South India shares the majority of the self help groups. According to the recent findingsSouth India shares 46.35 per cent of the total self help groups up to 31 March 2010 andmore interestingly a whopping 76.39 per cent of the total loan disbursed to the selfhelp groups at all India level. Self help groups are very efficiently running andimproving the life conditions of the masses in South India. Keeping these disparitiesinto view the present study analyzes the socio-economic effect of the microfinanceprograms on the poor in Uttrakhand state, with the field work has been carried in theDehradun district. Uttrakhand is a hill state, which has come into existence on 9th

November 2000. Till 31 March 2010 there were 43997 self help groups in Uttrakhandforming 0.63 percentage at all India level and loan disbursed to these groups wereRs. 467.67 million, which constitute 0.32 per cent of the total loan disbursed at all Indialevel. Micro finance is an effective tool to eliminate poverty. It empowers the poorpeople especially poor women both economically and socially. Poor people cannotapproach the bank for their credit needs due to their incapability of furnishing thecollateral security. Many of them have no bank account. Microfinance is a provision ofmoney for them without any collateral. They use it in developing income generatingactivity for them, and sometimes in satisfying other needs too. Thus microfinance is apromise of regular income to these poor as they start indulging in various incomegenerating activities. Gradually they come out of the vicious trap of the poverty.

2. REVIEW OF LITERATURE

Impacts of micro finance were addressed by many researchers and some importantstudies are presented here.

Ahmad (1999) maintained that self help groups have been successful in Assam(North Eastern India) even in the period of insurgency too. Women are coming to theadministration directly for their just rights and to address their grievances boldly.Puhazhendhi (1999) analyzed that self help groups are performing well and have beena carrier to the economic and social empowerment of the poor. Bhatia and Bhatia(2000) explored that recovery of SHG’s is higher than other credit extended to borrowersand living standards of the SHG’s members, in terms of ownership of assets, increasein savings and borrowing capacity, income generating activities and income levels,changed significantly. Dasgupta (2000) in his paper assessed that the poor are reapingmany benefits through self help groups like mobilization of savings, access to thecredit etc. Gurumoorthy (2000) in his study found that SHG is a viable alternative toachieve the objectives of rural development and to get community participation in allrural development programs. Nagayya (2000) explored that an informal arrangementfor credit supply to the poor through SHG’s is fast emerging as a promising tool forpromoting income-generating enterprises. He advocates that NABARD and SDBI areplaying prominent role in implementing the microfinance programs. Rakesh Malhotra(2000) in his study explored the male dominance even in the in the usage of creditborrowed by the women participants. V. M. Rao (2002) maintained that due to thefailure of the formal financial system in India, SHG movement flourished well and

SOCIO-ECONOMIC EMPOWERMENT OF THE POOR THROUGH MICROFINANCE:/ 105

helping the poor to come out of the vicious circle of poverty. Satish (2001) in his papermaintains that for the efficient functioning of the self help groups, it is essential thathomogeneity of socio-economic status of the members, should be ensured whileforming SHG’s.

3. RESEARCH OBJECTIVE AND METHODOLOGY

In the light of prevailing scenario and success of microfinance programs and importanceof the role played by NABARD so far in promoting them, it is worthwhile to study thecontribution of microfinance programs in Uttrakhand. Thus to accomplish the abovesaid exploration the main objective of the present study is to “Analyze NABARDsponsored microfinance programs and their role in the empowerment of the poorpeople in study area.”

The above said main objective is divided into following sub objectives:1. To analyze the impact of NABARD sponsored micro-finance programs on

the socio economic empowerment of poor people.2. To analyze the functioning of self help groups in the study area.

3.1. Research Design

In the backdrop of the above adjectives, the present work is an exploratory anddescriptive research study. To suit this purpose ex-post facto research methodologyhas been adopted that is commensurate with both quantitative and qualitativetechniques of data analysis so that the variables of the study could be analyzed better.Both primary and secondary data has been incorporated. Secondary data has beentaken from the published and unpublished sources and primary data has been collectedthrough a structured questionnaire.

3.2. Study Area

The study area for the present work is decided to be Dehradun district of Uttrakhand.Dehradun being the capital city has a diverse and well developed banking infrastructurewhich assists microfinance activities to grow better, secondly NABARD has theirregional office which implies that it would have put more rigorous effort for thepromotion of Microfinance in Dehradun.

3.3. Sample Selection and Sample Size

For the present work we have employed both purposive and convenient samplingtechniques. In the region microfinance activities through self help groups are beingcarried out by various facilitators like NABARD, Block development offices, self helpgroups under Swarnjayanti Gram Swarojgar Yogna (SGSY) etc. As this work is confinedto the impact assessment of NABARD sponsored microfinance programs only, thereforewe have selected self help groups formed by various NGOs which are specificallyconnected with NABARD. NABARD encourages various NGOs by reimbursing themoney to them which they have spent to form and nurture self help groups therebypromotes microfinance activities. The data has been collected by placing the


questionnaire to the members of the self help groups which are formed by the NGOsworking in collaboration with NABARD. From every group we have selected threemembers randomly, thus we have tried to cover maximum as possible groups formaximum coverage of the program. The sample size has been decided to be 600respondents, which were from the various self help groups selected randomly fromall the six blocks of the district.

3.4. Data Collection and Analysis

The primary data has been collected through Survey method using structuredquestionnaire, which comprised all the possible variables for the assessment of theeffect of microfinance on the socioeconomic wellbeing of the participants. Questionnairewill comprise of close ended, dichotomous and multichotomous questions so as toreveal the demographic characteristics of the respondents as well as their perceptionregarding the effect of microfinance on the socio economic wellbeing (empowerment).For collecting the views of the respondents about the various aspects of microfinanceprograms we have used Likert scale having five points 1-5, 1 represent the highestlevel of dissatisfaction and 5 the highest level of satisfactions. Data analysis has beenstarted from scrutiny of the questionnaires for their correctness and completeness.Thus incomplete questionnaires have not been included for the analysis. Out of thesample size of 600 we have found 579 questionnaires worthy to be analyzed. For thebetter analysis, we have employed one sample t test, correlation and regression analysisin addition to descriptive and percentage analysis. T test is performed on variousvariables to test the significance of the mean and the correlation for finding out thedegree of association among variables. As the empowerment/ well being brought byusing microfinance is a systematic and sequential process. Correlation analysis hashelped us to find out whether there is any association between two consecutiveprocesses. Finally both simple and multiple regression analysis have been used tofind out the contribution of various independent variables on the dependent variableindicating socio-economic empowerment of microfinance.

4. DEMOGRAPHIC PROFILE OF THE RESPONDENTS

Data collected from the field survey shows that most of the microfinance participants(self help group members) are female. Female constitute 92.8 per cent (537 respondents)of the total respondents sampled while male accounts for only 7.2 per cent with thestrength of 62 out of total 579 respondents. Out of the total respondent surveyed 78respondents(13.4 per cent) reported to have age below 25 years, while 233 respondent(40.2%) having age group of 25 to 35 years. 242 respondents(41.8%) belong to 35-45years age group and only 27 respondents (4.6%) aged more than 45 years. Thus it isreported that most of respondents are young as altogether 95.4 per cent of therespondents are below 45 years of age. As far as education background is concernedstudy shows that majority of the group members which are 193 in number (33.3 per cent)have had education up to primary level only. Whereas 101 members (17.5 per cent)have had education up to Middle level (8 standard). 12.4 per cent of the total membershad joined school up to high school level (10th standard). Compared to that a good


proportion, 126 members (21.9 per cent) were intermediate passed. Very few have hadeducation above intermediated. Data shows that respondents graduated were only 24in number (4.6 per cent) and similarly only member (0.2 per cent) had a post graduatedegree. The proportion of the respondents who were illiterate and did not achieve anyformal education was 10.5 per cent. Thus the majority of the respondents were educatedup to some extent. Marital status of the respondents shows that only 36 respondents(6.2 per cent) are unmarried while 543 respondents (93.8 per cent) are married. Majorityof the respondents which are 357 in number (61.6 per cent) reported that they have anuclear family while 242 of them (38.4 per cent) were from joint family. 307 respondents(53 per cent) reported that they have 0-4 members in their family, 203 respondents(35.3 per cent) have 5 to 8 family members whereas only 69 members (11.7 per cent)have more than 8 members in their family. This shows increasing awareness about thefamily planning even among the rural people. Another point highlighted is that 346(59.8 per cent) respondents are from general category, 89 respondents (15.3 per cent)are from Scheduled Caste. Whereas 112 respondents (19.3 per cent) are from ScheduledTribe and 32 (5.6 per cent) are form Other Backward Classes. This shows thatmicrofinance programs are covering people from all the categories, and have not beenconfined to any special category of people. Though the coverage of the program towardsthe categories other than general is comparatively less. In addition to these basicinformation we have also enquired them about their income and poverty level beforeand after their participation into microfinance programs. 151 respondents (21.6 per cent)reported that their present income level is below Rs. 5000 per-month, while 416respondents (71.9 per cent) reported that their present income is between Rs. 5000 toRs. 10000 per-month, only 12 respondents (2 per cent) reported to have income levelmore than Rs. 10000 per month at present. About the income level before microfinance,541 respondents (93.4 per cent) asserted that their income level before microfinancewas below Rs. 5000 per month, whereas only 38 respondents (6.6 per cent) reported tohave income level between Rs. 5000 to Rs. 10000 per month and no one was havingincome above Rs. 10000. Similarly 45 respondents (7.7 per cent) reported that theywere below poverty line before their participation into microfinance programs whileonly 45 respondents (7.7 per cent) reported to be below poverty line after microfinance.343 respondents (59.2 per cent) reported that they were slightly above poverty linebefore microfinance, this figure grown to 483 respondents (83.5 per cent) afterwards.Similarly only 4 respondents (0.2 per cent) reported that they were high above povertyline before microfinance and 51 respondents (8.8 per cent) said they are high abovepoverty line after microfinance. This show a positive impact of microfinance programson the participants of microfinance programs.

5. STATISTICAL ANALYSIS AND DISCUSSION

5.1. Reliability Analysis – Cronbach’s Alpha

The Cronbach’s alpha has been calculated as part of the reliability test to assess howconsistent the results were and whether similar results can be generalized if the samplesize is increased. A value of 0.7 or higher is assumed to be very good. The Cronbach’s


alpha was calculated for section B and C of the questionnaire which is associated toassess the socio economic impact of microfinance on the masses, and level of servicesgained by forming Self Help Groups, in this section all the questions have same scale.The results are shown in the following table.

Table 1Cronbach’s AlphaReliability Statistics

Cronbach’s Alpha Cronbach’s Alpha Based on Standardized Items N of Items

.816 .818 17

It is very much apparent form the table presented above that the data collectedfulfills the reliability condition. We have computed the chronbach alpha coefficientfor 17 variables which will be primarily used for the statistical analysis. The coefficienthas a value .818 which is satisfactory as it is greater than .70.

5.2. Statistical Analysis

The following statistical analysis is done with the view of the following two mainhypotheses as discussed in chapter three.

H1 : Microfinance has increased socio-economic well being among participants.H2 : Microfinance program participants are satisfied with the level of service and

benefits they received by forming SHGs.

5.2.1. Section A: Assessing Socio Economic Well Being

Having tested the reliability of data collected for various variables we, are nowanalyzing the variables for testing the socio economic impact (the first main hypothesis)of the microfinance on the participants.

5.2.1.1. One Sample Statistics and t Test of Different VariableAt the first stage we have assessed the satisfaction level of the respondents for thevarious statements representing their economic and social well being, they haveattained due to their participation in microfinance programs. We are striving to assessthat whether or not respondents feel that as they have participated in microfinanceprograms they have an increment in income, food expenditure, savings, andenhancement in the level of physical asset, financial situation and living standard.Have they been able to avail better medical facilities, better education to their childrenafter their participation in microfinance program? Did the participation increase theirrole at the household level decision making, did their confidence level increase anddid they feel that their social status increase or not? For this purpose we have employedthe t test after having analyzed the descriptive for all these parameters. The descriptiveshows the mean of all these variables and standard deviation.

The mean represent the average satisfaction level of the respondents for the abovesaid parameters. The higher the mean the more satisfied the respondents are aboutthe parameters. Standard deviation shows the deviation of the individual observationform the mean value.


Table 2One Sample Statistics of Various Variables

Name of the variables N Mean Standard Standarddeviation error of mean

Increment in income 579 4.4093 .89015 .03699Increment in food expenditure 579 3.9827 .93549 .03888Increment in saving 579 4.6114 .81886 .03403Improvement in physical assets 579 4.0345 .90492 .03761Improvement in financial situation 579 4.2522 .80996 .03366Improvement in living standard 579 4.3109 .80444 .03343Better medical facilities 579 4.3644 1.06867 .04441Better Education Facilities 579 4.1744 1.05995 .04405Enhanced participation in decision making 579 4.3299 1.10048 .04573Increased confidence 579 4.4162 1.15172 .04786Increased Social status 579 4.3333 1.14114 .04742

Source: Field data.

Almost all the above variables show the mean value more than 4. All the responsesare collected using a five point likert scale (1 strongly disagree and 5 strongly agree).Thus the mean value 4 or above 4 indicates that the respondents are satisfied for allthe above parameters more than the average level of satisfaction (2.5) on the scale.Thus it is proved from the descriptive that the respondents strongly agree that theirincome, food expenditure, savings has been increased due to their participation inmicrofinance program. They are also in agreement that they could increase physicalassets, their financial situation improved, and living standard gone up. They couldavail better medical facilities and could have been able to provide better education totheir children. Due to microfinance they are now enjoying enhanced recognition inthe household decision making and their confidence and social status has beenincreased. We now examine whether or not the above results are statistical significantusing the one sample t test. The significance level for rejecting/accepting the hypothesisis determined to be 5 per cent or .05. we are comparing the mean scores of all theabove variables to a hypothetical mean 3 which shows above average satisfaction levelon likert scale.

We took the following null and alternative hypotheses:H0 : Participants are less satisfied than the above average level of satisfaction (3)

or (µ<3).H1 : Participants are satisfied more than the above average level of satisfaction or

(µ>3).The analysis in the table demonstrates that the t value for the variable increment

in income is 38.097 and significance level is 0.000 so at the 5% level of significance thenull hypothesis is rejected since the p value is less than .05 and it is strongly significant.So our results are in favor of alternative hypotheses.This means that the satisfactionlevel of the respondents, about the increment of their income after they have beenprovided with micro credit is more than above average satisfaction level. The same


hypothesis is used for examining the significance of the mean for other statementsindicating increment/enhancement in food expenditure, savings, physical assets,financial situation, living standard, better education, better medical facilities, confidenceand social statusIt is evident from the above table that the p value for all the variablesis .000 which is less than .05 and therefore the null hypothesis is rejected and alternativehypothesis is accepted. Conclusively it can be said that the mean is significantly abovethan 3 or respondents are satisfied more than the above average level for all the aboveparameters

5.2.1.2. Relationship Among Various Variables

As the income increases the people also increase food expenditure, and after it theytry to save with the belief that saving will assist them in the future. Savings is used tocreate physical asset and eventually the financial situation and living standard goesup. Increasing living standard generates confidence to them and they become sociallyactive thereby their social status enhances. Therefore, now we tried to find out thewhether or not there exist significant relationship among the various variables.

In order to test whether or not the variables significantly related or not. We havedecided the following null and alternate hypotheses:

H0 : No relationship exists among the various variables.H1 : Significant relationship among various variables.The table below demonstrated that our null hypothesis is rejected and their exist a

significantly positive relationship among various variables since p value is less than.005 for all cases. The correlation table reveals that increment in income is significantly

Table 3One-Sample t Test Results

Test Value = 3

95% ConfidenceInterval of the

Difference

T df Sig. Mean Lower Upper(2-tailed) Difference

Increase in Income 38.097 578 .000 1.40933 1.3367 1.4820Increment in food expenditure 25.278 578 .000 0.98273 0.9064 1.0591Increment in Savings 47.352 578 .000 1.61140 1.5446 1.6782Enhancement in physical Assets 27.509 578 .000 1.03454 .9607 1.1084Increment in financial situation 37.200 578 .000 1.25216 1.1860 1.3183Increment in Living standard 39.211 578 .000 1.31088 1.2452 1.3765Better medical facilities 30.722 578 .000 1.36422 1.2772 1.4517Better education 26.661 578 .000 1.17444 1.0879 1.2610Enhanced role in decision making 29.078 578 .000 1.32988 1.2401 1.4197Improved confidence level 29.589 578 .000 1.41623 1.3222 1.5102Improved social status 28.115 578 .000 1.3333 1.2402 1.4265

Source: Field Data.


and positively related to all other variables. Similarly enhancement in living standardand enhancement in social status is also significantly and positively correlated (r =.515,sig=.000). Thus we can conclude that those participants who have been able to increasetheir income also have been able to increase food expenditure and savings. Theirphysical assets have also been enhanced, their financial situation improved and livingstandard has gone up. They also have been able to attain better medical facilities,better education for their children, their role in household decision making has alsoincreased, and their confidence and social status have also improved. Similarlyparticipants who have enhanced living standard have also attained enhanced socialstatus. Correlation shows the degree of association among various variables but itdoes not show the causation between two or more variables. Therefore now we try toestablish that whether or not increment in income is the cause for other variables usingsimple regression and multiple regression techniques.

Table 4Pearson’s Coefficient of Correlation Among Various Variables (N=579)

5.2.1.3. Simple Regressions Analysis between Increment in Income and Other Variables

We have conducted the regression analysis to test whether or not the increment inincome is significant predictor of other variables and have come up with result givenin following tables.

In the Table 3 above, every row represent a different model showing the effect ofindependent variable increment in income on all other variables separately. Informationin the first model summary row indicates that the value of R-square for the model is0.259. This means that 25.9 per cent of the variation in the variable increment in foodexpenditure of respondents (dependent variable) can be explained by the independentvariable increment in income. In general, R square always increases as independent


variables are added to a multiple regression model. To avoid overestimating the impactof adding an independent variable to the model, we prefer to use the adjustedR-square value (it recalculates the R-square value based on the number of predictorvariables in the model). This makes it easy to compare the explanatory power ofregression models with different numbers of independent variables. The adjustedR-square for the first model is 0.258., which represent that 25.8 per cent of the variationsin the dependent variables are due to independent variable.

In the ANOVA table. The regression model is statistically significant(F ratio=201.994, probability level 0.000). The probability level 0.000 means that thechances are almost zero that the results of regression model are due to random eventsinstead of a true relationship. Here we develop null hypothesis and alternate hypothesesthat:

H0: There is no relationship between increment in food expenditure and incrementin income.

H1: Increment in food expenditure is significantly related to increment in income.Since the p value in anova table for the first model less than .05 therefore we reject

the null hypothesis and accept the alternative. Similarly the variable increment inincome represent respectively 54.1,20.4, 39.5, 54.7, 23.7, 28.9, 22.7, 27.7 and 27 per centvariation(as shown by adjusted R square column in model summary table) in thevariables Increment in food expenditure, increment in savings, enhancement in physicalassets, enhancement in financial situation, enhancement in living standard, bettermedical facilities, better education to their children, enhanced role in decision making,enhanced confidence level, enhanced social status as given by the model summarytable. The Anova table shows that all these models are statistically significant as the pvalue is less than .05 for all the models. We employ the above mention null andalternative hypothesis separately for each variable separately for testing its relationwith increment in income. For all the variables the alternative hypothesis is accepted

Table 5 Regression Analysis

Model Summary

Model R R Square Adjusted Std. Error ofR Square the Estimate

1 .509a 0.259 0.258 0.805812 .736a 0.542 0.541 0.55483 .453a 0.205 0.204 0.807544 .629a 0.396 0.395 0.630035 .740a 0.548 0.547 0.541466 .489a 0.239 0.237 0.933257 .538a 0.29 0.289 0.893918 .478a 0.229 0.227 0.967279 .527a 0.278 0.277 0.9795710 .521a 0.27 0.270 0.97494a Predictors: (constant), increase in income.


Table 6Anovab

Model Sum of Square Df Mean Square F Sig

1. Regression 131.162 1 131.162 201.994 .000a Residual 374.666 577 0.649 Total 505.827 578



4. Regression 150.154 1 150.154 378.284 .000a

Residual 229.037 577 0.397 Total 379.185 578







a Predictor: Increment in incomeb Dependent variables: Increment in food expenditure, increment in savings, enhancement in physical

assets, enhancement in financial situation, enhancement in living standard, better medical facilities,better education, enhanced role in decision making, enhanced confidence level, enhanced social status.

and null hypothesis is rejected since the p value is less than .05.The following coefficienttable shows that how significantly the independent variable increment in incomepredicts the value of various dependent variables separately. The beta coefficient inthe following table shows the effect of increment in income on the other variables. Forexample the beta coefficient for model 1 indicating the dependent variable incrementin food expenditure is .509 which shows that an increment of 1 unit in income causeincrement of .509 unit in food expenditure.


Table 7Coefficienta

Unstandardised StandardizedCoefficient Coefficient

Model Beta Standard. Error Beta t Sig.

1. Constant 1.623 0.169 9.583 .000Increase in Income 0.535 0.038 0.509 14.212 .000










a Dependent variables: Increment in food expenditure, increment in savings, enhancement inphysical assets, enhancement in financial situation, enhancement in living standard, better medicalfacilities, better education, enhanced role in decision making, enhanced confidence level, enhancedsocial status.

Similarly form the beta values for the other models we can reveal that 1 unitincrement in income cause increment of .736 , 453, .629, .74, .489, .538, 47.8, .527, and.521units respectively in the variables under discussion. Since the p value here again isless than .05 we can conclude that increment in income is a significant predictor of allother variables.Thus it is evident that participants of microfinance programs haveincrement in income and due to the increased income many other parameters havealso been changed for them. Their living standard has gone up and social statusimproved.

5.2.1.4. Multiple Regressions Between Increment in Living Standard and Different RelatedVariables

We now measure the composite impact of various independent variables on thedependent variable “Improvements in living standard” using multiple regressiontechnique.


Table 8Model Summary

Model R R Square Adjusted R Square Std. Error of the Estimate

1 .867a .752 .749 .40269a Predictors: (Constant), Increase in Income, Increment in food expenditure,Increment in Savings,

Enhancement in physical Asset, Increment in financial situation.

Information in the Model summary table indicates that the value of R-square forthe model is 0.752. This means that 75.2 per cent of the variation in the improvementof living standards of respondents (dependent variable) can be explained from thefive dependent independent variables. The adjusted R-square for the model is 0.749,which indicates only a slight overestimate with the model. Even R square also representthat 74.9 per cent of the variations in the dependent variables are due to independentvariables.

Table 9ANOVAb

Model Sum of Squares df Mean Square F Sig.

1 Regression 281.126 5 56.225 346.736 .000a

Residual 92.915 573 .162Total 374.041 578

a Predictors: (Constant), Increment in financial situation, Increment in food expenditure, Increase inIncome, Increment in Savings, Enhancement in physical Assets:

b Dependent Variable: Increment in Living standard.

The overall regression results are shown in the ANOVA table above. The regressionmodel is statistically significant (F ratio=346.736, probability level 0.000). The probabilitylevel 0.000 means that the chances are almost zero that the results of regression modelare due to random events instead of a true relationship. Here we develop nullhypothesis and alternate hypotheses that:

H0 : There is no relationship between improvements in the living standard ofrespondents and increment in income, increment in food expenditure,increment in savings, enhancement in physical assets and increment infinancial situation.

H1 : Increment in income, increment in food expenditure, increment in savings,enhancement in physical assets and increment in financial situation aresignificantly related to improvement in living standard.

The null hypothesis is rejected and the alternative hypothesis is accepted andtherefore it is revealed that all the five independent variables are significantly relatedto the dependent variable.

In the significance column in above table, we have noticed that beta coefficientsfor increment in income, increment in food expenditure, increment in savings, andincrement in financial situation are all significant as the p value is less than .005. Thebeta coefficient for all the independent variables in the above table shows the effect ofthese on the dependent variable. For example the beta coefficient for the variableincrement in income shows the value.234 which mean that every time the income


increases by 1 unit it leads the living standard o increase on an average by .234 units.The coefficient table shows that the variable increment in financial situation is themost significant predictor of improvements in living standard with a beta coefficient0.397 (probability 0.000) followed by increment in savings (beta .296 and probability .001),improvement in income (beta .23 and probability of .000) and increment in foodexpenditure (beta .116, probability .000). Thus for all these variables we can concludethat the independent variables are significant predictors of the dependent variable.The p value is less than .05 for all these four variables. The only independent variablewhich has a negative beta value is enhancement in physical assets which indicatedthat enhancement in physical assets by 1 unit represent a decrement on an average of.041 unit in living standard. So for the independent variable enhancement in physicalassets we accept the null hypothesis and conclude that enhancement in physical assetsand improvements in living standard are not related and enhancement in physicalassets does not affect improvements in living standard. One important fact to beconsidered here is that though the variable enhancement in physical assets shows anegative value, it cannot be out rightly rejected as a predictor because the multipleregression technique looks at the combination of these five variables to predict theindependent variable. The coefficient table shows the contribution of each independentvariable but only in combination with other independent variables. If we look at thecorrelation table, it shows that the variables enhancement in physical capital andenhancement in living standard are highly and positively correlated (r=.603, sig=.000).The overall model summary shows that it is a good model to predict the dependentvariable. Thus the concluding remark is that because of participation in microfinanceprograms the respondents became economically better off.

Having proved the economic betterment through microfinance, we now try toanalyze whether or not the participants’ social status improved after they joinmicrofinance program. Again we have employed the multiple regression technique toanalyze the causal relationship between the various independent variables and thedependent variable improvements in social status indicating the social well being ofthe respondents. The independent variables are increment in income and improvementsin living standard. As already indicated in the above t test analysis that participantsare satisfied more than average level of satisfaction that the social status increased

Table 10Coefficientsa

Unstandardized StandardizedCoefficients Coefficients

Model B Std. Error Beta t Sig.

1 (Constant) .125 .103 1.214 .225Increase in Income .212 .030 .234 7.130 .000Increment in food expenditure .096 .025 .112 3.781 .000Increment in Savings .290 .034 .296 8.467 .000Enhancement in physical Assets -.036 .032 -.041 -1.154 .249Increment in financial situation .395 .036 .397 11.057 .000

a Dependent Variable: Increment in Living standard.


after they join microfinance activity. Moreover there exists a significant positive relationamong these variables. The multiple regression analysis shows the following results.

Table 11Model Summary

Model R R Square Adjusted R Square Std. Error of the Estimate1 .555a .308 .306 .95070a Predictors: (Constant), Increment in Living standard, Increase in Income.

The above table indicates that the value of R-square for the model is 0.308. Thismeans that 30.8 per cent of the variation in the improvement of social status of respondents(dependent variable) can be explained by the two independent variables. The adjustedR-square for the model is also 0.306 which is almost same to the R square value.

Table 12ANOVAb

Model Sum of Squares df Mean Square F Sig.1 Regression 232.055 2 116.028 128.372 .000a

Residual 520.612 576 .904Total 752.667 578

a Predictors: (Constant), Increment in Living standard, Increase in Income.b Dependent Variable: Enhanced social status.

The overall regression results are shown in the ANOVA table below shows thatthe regression model is statistically significant (F ratio=128.372, probability level 0.000).The null alternate hypotheses are as follows for the above said purpose:

Ho: There is no relationship between improvements in social status of respondentsand increment in income and enhancement in living standard.

Ha: Increment in income and enhancement in living standard are significantlyrelated to enhancement in social status.

Since the p value is less than 0.05, we reject the null hypothesis and accept the alternatehypothesis. Thus the two variables are significantly related to the dependent variable.

The coefficient table below shows that the variables increment in income andenhancement in living standard are significant predictor of enhancement in social status.Table shows that every single unit change in increment in income brings .310 unitchanges in enhancement in social status. Similarly .285 unit change in enhancement insocial status is represented by one unit change in increment in living standard.

Table 13Coefficientsa

Unstandardized StandardizedCoefficients Coefficients

Model B Std. Error Beta t Sig.1 (Constant) .837 .223 3.750 .000

Increase in Income .398 .066 .310 6.024 .000Increment in Living standard .404 .073 .285 5.526 .000

a Dependent Variable: Enhanced social status.


Thus the above analysis shows that due to the participation in the microfinanceprogram income of the participants increased and this brings enhancement in livingstandard and social status. As the variable enhancement in living standard indicatesthe economic well being and the other variable enhancement in social status representsthe social wellbeing, it can be concluded that microfinance brings them socio economicwellbeing.

5.2.2. Assessment of the Services and Benefits Availed by Members of Self Help Groups

This section provides the analysis of the services and benefits availed by the membersof self help group keeping the second main hypothesis into consideration. We havetried to assess the satisfaction level of the members on the various statements on likertscale showing various services and benefits to the members.

Table 14Descriptive Statistics

N Minimum Maximum Mean Std.Deviation

Reasonability of Interest Rate on microcredit 579 1.00 5.00 3.5354 1.79678Operational Assistance from NABARD 579 1.00 5.00 1.8670 1.51621Increment in Employment 579 1.00 5.00 4.2332 1.45136Capacity Building services from NABARD 579 1.00 5.00 2.0950 1.66158Ease of process of availing Loan 579 1.00 5.00 4.2388 .53272Marketing Assistance from NABARD 579 1.00 5.00 1.1952 .59547Valid N (listwise) 579

Source: Field data.

As shown in table above, the mean for three statements is above 3 which show themembers are more satisfied than average level. Whereas for the other three it is below2.5 showing that they are not satisfied with these statements. The following table showsthe results of the t test.

We have developed the following null and alternative hypothesis for the variablesreasonability of interest rate on microcredit, increment in employment and ease of theprocess of availing microcredit.

H0 : Participants are less satisfied than the above average level of satisfaction (3),in terms of reasonability of interest rate on microcredit, increment inemployment and ease of the process of availing microcredit.

H1 : Participants are satisfied more than the above average level of satisfaction.It can be concluded that the respondent are more satisfied than the above average

level, that the interest rate on the microcredit is reasonable, that the microfinance activityhas yielded them the increased employment opportunities for them and that the processof availing micro credit is easier. With the following t test results we have rejected thenull hypothesis since the p values are less than 0.005(significance level), for the variablesreasonability of interest rate on microcredit, increment in employment, Ease of theprocess of availing microcredit.


For the other three variables we have developed the following null and alternativehypothesis:

H0 : The satisfaction level of the participants is equal to average level (2.5) in termsof receipt of operational assistance, Capacity building services, Marketingservices from NABARD.

H1: Participants are satisfied less than the above average level of satisfaction.


Test Value = 3


Difference

t df Sig. Mean Lower Upper(2-tailed) Difference

Reasonability of interest rate on microcredit 7.170 578 .000 .53541 .3887 .6821Ease of process of availing microcredit 82.321 578 .000 1.2388 1.7804 1.8673Increment in employment 20.445 578 .000 1.23316 1.1147 1.3516

Source: Field survey.

The table below shows that the p values for all three variables is less than thesignificance value .05. Hence the null hypothesis is rejected for all these variables andthe alternative hypothesis is accepted. Thus it can be concluded that that participantsare not receiving operational assistance, capacity building services and marketingassistance form NABARD.

The above analysis leads the first main hypothesis to be fully supported and thesecond main hypothesis is partially supported.


Test Value = 2.5


Difference

t df Sig. Mean Lower Upper(2-tailed) Difference

Operational assistance from NABARD -10.046 578 .000 -.63299 -.7567 -.5092Capacity building services form NABARD -5.865 578 .000 -.40501 -.5406 -.2094Marketing services form NABARD -52.728 578 .000 -1.30484 -1.3534 -1.2562

Source: Field survey.

6. ASSESSMENT OF THE FUNCTIONING OF SELF HELP GROUPS

Another objective of this study is the assessment of the functioning of the self helpgroups in the region. The first part of the questionnaire consist if the question regardingthe functioning of the groups. We have chosen the guidelines framed by NABARD in


this respect as the criteria against which the functioning of the groups is examined.NABARD rates a self help groups having a size of 15 to 20 members as very good, of11 to 15 as good and of 0-10 as unsatisfactory. 24.5 per cent of the respondents in ourfield survey have reported to have 0- 1- members in their group, whereas 65.3 per centhave group size of 11-15 members and rest of the members have group size more than15 members. So most of the groups fulfill the criteria. Another fact is the poverty levelof the group member. Conceptually self help group members come from the samesocio economic background, and as per NABARD all members should be very poor ormost should come from very poor level for attaining a rating of very good or good.Field survey shows that 19.5 per cent of the respondent reported that all of groupmembers are very poor, whereas 74.5 per cent respondents have most of their groupmembers are very poor. 93.8 per cent respondents reported that their group meetingis conducted every month, while 5.8 respondents say that their group meeting is heldevery fortnightly and mere 0.4 per cent respondents reported that they used to haveweekly meeting of their group. This shows that the timings of the group meetings arefixed. Fixed timing of the meeting is a condition which a group must fulfill essentiallyto be ranked very good. Another aspect is the strength of the members in the meetings,44.2 per cent reported that 90 per cent of their group members attend the meetings,whereas 35.8 per cent respondents reported that 70-90 per cent of the members jointhe meetings and only 20 per cent reported that less than 70 per cent members joingroup meetings. 97.2 respondents reported that they have all accounting booksmaintained. The make timely entries in accounting books. Only 2.8 per cent respondentsreported that they do not have well maintained accounting books.75 per cent of therespondents says that in their group they use the entire savings for interloaningpurpose, 24.7 per cent says that they use partly savings for interloaning while only 0.2per cent says that no saving is used for interoaning. Thus the groups also fulfills thesetwo conditions to be ranked very good or good. The average repayment rate of theloan taken by the members is more than 90 per cent as reported by 51.6 per cent of therespondents, 41.6 per cent of the respondents reported that repayment rate in theirgroup is between 70-90 per cent. 3.8 per cent respondents say that their group’srepayment rate is 50-70 per cent. Only 3 per cent of the respondents say that they havea repayment rate less than 50 per cent. Thus almost all the groups show a goodrepayment rate. But the only point groups are lacking is the level of information aboutthe schemes of NABARD and government. NABARD provides various services andlaunches various scheme for the betterment of the poor people who are engaged inself help groups. But our most of our respondents reported that they lack any suchinformation or receive late information. 42.8 per cent of the respondents say that theyreceive late information about NABARD’s schemes and programs of their benefits.39.8 per cent say that they never receive any such information. Only 17.8 per centrespondents say that they get complete and timely information. Thus the groupsrunning in the region are functioning well as they have qualified for the rank of verygood or good at least on most of the criteria. Moreover 44 per cent of the respondentsreported that they are associated with the groups for 1 to 2 years, 48.2 per cent saysthat they are continuously associated for 2 to 5 years, 7.8 per cent respondents were in


association for 5 to 7 years and no respondent was there in the group for more thanseven years. Thus it is evident that the groups are not sustaining a long. that is verymuch required for reaping the maximum benefits out of microfinance.

7. CONCLUSION AND SUGGESTIONSThe study concludes that microfinance has brought economic and social empowermentto the participants. Like self help groups in other regions, here also the main participantsof the group are the women, which shows that microfinance through self help groupsefficient strategy for the women empowerment. Microfinance has caused the incrementin income of the respondents. They have been able to increase their food expenditureand savings. They have been able to build physical assets and their financial situationhas gone up. Their living standard has also enhanced due to participation in microfinanceprograms. Almost most of the members are women who have been confined to theirhousehold activities earlier, but due to their participation in microfinance programsthey have been conferred the opportunity to come out of home and participate in groupactivities. Most of them are now active members of the self help groups. More over theyinteract with the bank official as the representative of their group, they get their bankaccount opened, deposit their savings to the bank and start the process of obtainingbank credit. This whole process leads to increment in their confidence and social status.Women who have not been given much importance so far are now playing a crucial roleat their household level also. Thus the participation in microfinance programs has beena turning point of their lives. As far as the services and benefits are concerned, thoughthey availed increased employment opportunities, credit facility at reasonable rate yetthere are still many important aspects are overlooked in this process. There is a lack of acapacity building programs and operational assistance to the group members. They arealso not provided with any kind of marketing assistance by NABARD. Moreover manyof the times the loan provided to the members is not adequate. Most of the times theloan is provided to the self help groups. The following suggestion can be posed:

(i) Amount of loan per member should be increased, so that it can becomesufficient to use fruitfully. So far in its best case also it is less than Rs. 10000per member. This amount cannot be expected to be sufficient for initializing aentrepreneurial activity.

(ii) The group members should be provided with the capacity building and othertraining programs. So that they can develop a positive attitude towardsmicrofinance programs, and actively participate in them. These capacitybuilding programs can help them in starting a fruitful entrepreneurial activity.

(iii) They should also be provided with the operational assistance, which theyrequire in the efficient functioning of their enterprise. Many of the respondentsare women and they are not very well qualified and they find themselvesincapable of running their enterprise well.

(iv) Another critical assistance which is badly required is the marketing assistanceto them. It is experienced that the respondents have not been able to markettheir product. They therefore require marketing assistance. NABARD can assistthe self help groups.


(v) A lot of effort is required to make self help groups sustainable. It is observedthat the life of a group is not more than 7 years. Reason behind this is thatmost of the groups are NGO promoted and NGO forms the groups under anyproject and as the project time gets over they separates them from these groupsand eventually the groups get dissolved.

(vi) Large sized NGO should be promoted in this region, like they are operatingin southern region of the country.

(vii) During the data collection process it is observed that the spread of themicrofinance programs is not equal. The blocks which are far away from themain city do not have same number of self help groups. Thus efforts shouldalso be increased to include these far-flung areas.

ReferencesNABARD: Status of Microfinance in India 09-10, available at www.nabard,org.Ahmad, M. A. (1999), Women Empowerment: Self Help Groups, Kurukshetra, April.Gurumoorthy, T. R. (2000), Self Help Groups Empower Rural Women, Kurukshetra, Feb.Malhotra, Rakesh (2000), Access of Rural Women to Institutional Credit: Issues and Alternatives,

Research Paper 6, BIRD, Lucknow.Naggayya, D. (2000), Micro-Finance for Self Help Groups, Kurukshetra, August.Puhazhehdhi, V. (1999), Evaluation Study of SHG’s: Important Findings of Evaluation Study in

Tamil Nadu, Paper Presented in a Workshop, Dated 26-27 August, BIRD, Lucknow.Bhatia, N. & Bhatia, A. (2002), Lending To Groups, Yojana, Feb.Dasgupta, R. (2001), An Informal Journey Through SHG’s, Indian Journal of Agricultural Economics,

Vol. 56 (3), July-Sept.Rao, V. M. (2000), Women Self Help Groups: Profiles From Andhra Pradesh and Karnataka,

Kurukshetra, April.Satish, P. (2001), Some Issues in the Formational of SHG’s. Indian Journal of Agricultural Economics,

Vol. 56 (3), July-Sept.Goetz, Anne Marie (2001), Women Development Workers: Implementing Rural Credit Programmes in

Bangladesh. Sage publications, New Delhi.Morduch, Jonathan and Barbara Haley (2002), Analysis of Effects of Micro Finance on Poverty

Reduction. NYU Working Paper 1014, June 28, 2002. www.nyu.edu/wagner/working papers.htmlSimanowitz, Anton and Alice Walter (2002), Ensuring Impact. www.Imp– Act.org.K. Murthy (eds.) Micro Credit, Poverty and Empowerment, pp. 245-285. Sage Publications, New Delhi.Diener, Ed and Robert Biawas-Diener (2005), Psychological Empowerment and Subjective Well Being,

in Measuring Empowerment. (Ed) Deepa Narayan. OUP: New Delhi.Basu, Priya and Pradeep Srivastava (2005), Micro Finance and Rural Credit Access for the Poor in

India. Economic and Political Weekly, 40(17), pp. 1747-1756.Kabeer, Naila and Helzi Noponen (2005), Social and Economic Impacts of PRADAN’s Self Help

Group Micro Finance and Livelihoods Promotion Programme: Analysis from Jharkhand, India.http//www.lmp.act.org

Malhottra, Anju and Sidney Ruth Schuler (2006), ‘Women Empowerment as a Viable in theInternational Development’, in Deepa Narayanan(ed) Measuring Empowerment. pp. 71- 88. OxfordUniversity Press, Delhi.

Satyasai, K. J. S. (2008), ‘Rural Credit Delivery in India: Structural Constraints and SomeCorrective Measures’, Agricultural Economics Research Review, 21 (Conference Number),387-394. Annexure 1: Tables and Graphs.

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