A Study on the Socio-economic Conditions of the Women Beneficiaries on Micro Credit in Madurai, Tamilnadu

Finance is the lubricant, which oils the wheels of development. All economics rely upon the intermediary function to transfer resources from savers to investors. In market economies, this function is performed by commercial banks, financial institutions and capital markets. In many developing countries, capital markets are at a rudimentary stage, and commercial banks are reluctant to lend to the poor largely because of the lack of collateral and high transaction costs. The poor would borrow relatively small amounts, and the processing and supervision of lending to them would consume administrative costs disproportionate to the amount of lending. Several studies have confirmed that complicated loan procedures and paperwork, combined with a lack of accounting experience, limit poor people’s access to formal sources of credit. Commercial lenders in rural areas prefer to deal mainly with large-scale farmers. The absence of commercial banks in certain areas has led to non-conventional forms of lending [1,2].


Introduction
Finance is the lubricant, which oils the wheels of development. All economics rely upon the intermediary function to transfer resources from savers to investors. In market economies, this function is performed by commercial banks, financial institutions and capital markets. In many developing countries, capital markets are at a rudimentary stage, and commercial banks are reluctant to lend to the poor largely because of the lack of collateral and high transaction costs. The poor would borrow relatively small amounts, and the processing and supervision of lending to them would consume administrative costs disproportionate to the amount of lending. Several studies have confirmed that complicated loan procedures and paperwork, combined with a lack of accounting experience, limit poor people's access to formal sources of credit. Commercial lenders in rural areas prefer to deal mainly with large-scale farmers. The absence of commercial banks in certain areas has led to non-conventional forms of lending [1,2].
In order to fill this void, financial institutions such as Rotating Savings and Credit Associations (ROSCAs), cooperatives and credit unions which patterned on traditional models of micro lending have emerged all over the world in recent years Geertz. These organisations use innovative strategies for serving their clientele. These three types of institutions mobilise savings and lend money to local common groups, professions or neighborhoods. These institutions which exist in many parts of the world may be considered the models of the present day microfinance institutions. Most of the famous microfinance institutions/programmes (MFI/Ps) in the world have drawn many lessons from these institutions.
The decade of the 1980s saw an unprecedented growth in the number of MFI/Ps all over the world. The pioneer in this field, the Grammen Bank of Bangladesh, was started in 1976. The Bank convinced the world that the poor are able to save and that they are creditworthy. Viewing the success of the institution various poverty alleviation and microenterprise programmes followed the Bank's strategy. Development and Employment Programme (TRDEP) in Bangladesh, the Self-Employed Women's Association (SEWA) in India etc, are the more reputed among them. While many of the programmes used the solidarity group methodology, others lent directly to individual borrowers. But several innovations have been made in repayment strategies, lending techniques, fixation of the periods of loan repayment, collaterals, etc. One of the most striking features of these programmes/ institutions is that the majority of their borrowers are women. The repayment levels of loans of these institutions are also very high.

Objectives of the Study
To evaluate the micro credit on women beneficiaries and to offer suitable suggestions based on the findings.

Period of study
The present study is based on the primary. The primary data have been collected from the respondents directly for the period of study is impounded to one year (i.e., 2014-2015).

Tools of analysis
In order to examine the association, chi-square test was used. It is calculated by adopting the following formula;

Abstract
Finance is the lubricant, which oils the wheels of development. All economics rely upon the intermediary function to transfer resources from savers to investors. In market economies, this function is performed by commercial banks, financial institutions and capital markets. The poor would borrow relatively small amounts, and the processing and supervision of lending to them would consume administrative costs disproportionate to the amount of lending. Today, economic independence is considered to be the prime basis for improving the status of women in India. It is generally agreed that availability of credit to women would result in reducing their dependency, enhancing their social and economic activities, as well as empowering them to assert more in the household decisions. In India, women cannot be viewed as a homogeneous group, as the society is stratified on the basis of class, caste and religion. It has been observed that the position of women and their demand for bank credit remain tied to class, caste and religious affiliations. In order to grasp the nature of these casual relationships, it is imperative to understand the socio-economic condition of women beneficiaries in the study area. This work attempts to analyses the major socio-economic variables and family profiles of the women beneficiaries. Micro finance should be used to meet the immediate demand of the poor women for Health, Education or consumption purposes. This will improve the quality of their life and will be ready to take active participation in economic activities. Today, economic independence is considered to be the prime basis for improving the status of women in India. It is generally agreed that availability of credit to women would result in reducing their dependency, enhancing their social and economic activities, as well as empowering them to assert more in the household decisions. In india, women cannot be viewed as a homogeneous group, as the society is stratified on the basis of class, caste and religion. It has been observed that the position of women and their demand for bank credit remain tied to class, caste and religious affiliations. In order to grasp the nature of these casual relationships, it is imperative to understand the socio-economic condition of women beneficiaries in the study area. This work attempts to analyze the major socio-economic variables and family profiles of the women beneficiaries. For this, the analysis of the present paper has been Profile of the sample women beneficiaries [3][4][5].

Age-wise classification of the respondents
Age is an important factor which has a bearing on the active participation in innovative activities and the risk-bearing ability. Usually, the young people have more risk-bearing capability and better exposure to the economy. The young persons are generally more energetic, change prone, progressive and innovative than the aged. The age of the members are classified as, less than 25 years, 26-35 years, 36-45 years and 46 and above. Table 1 presents the distribution of the sample women respondents according to their age.
It has been observed that out of 81 respondents engaged in manufacturing sector, 3 (3.70%) of them fall in the age group of less than 25 years, about 48 (59.26%) of them fall in the age group of 26-35 years, 26 (32.10%) of them and 4 (4.94%) of them fall in the age group of 36-45 years and 46 and above respectively.
It has been observed that out of 102 respondents engaged in Service sector, 12 (11.76%) of them fall in the age group of less than 25 years, 41 (40.20%) of them fall in the age group of 26-35 years, 46 (45.10%) of them and 3 (2.94) of them fall in the age group of 36-45 years and 46 and above respectively.
Further, it has been observed that out of 117 respondents engaged in trading sector, 10 (8.55%) of them fall in the age group of less than 25 years, 56 (47.86%) of them fall in the age group of 26-35 years, 30 (25.64%) of them and 21 (17.95%) of them fall in the age group of 36-45 years and 46 and above respectively.
Thus, it is concluded from the analysis that a majority, accounting 48.33% of the respondents belong to the age group of 26-35 years and 34.00% of the respondents fall in the age group of 36-45 years in the study area.
A look at the higher end of the age groups shows that only nearly 3% of the respondents of service sector belong to it. For manufacturing sectors, the percentage of age is around 5%. For trading sector, it is 17.95% which is the highest among all sectors. This shows that a number of aged and experienced people concentrate in trading sector. Where as the young people particularly concentrate only in service sector.
It is inferred that the age is a criterion for shift in various sector among women beneficiaries ( Table 2).
Null Hypothesis H 0 : Age of the sample respondents does not significantly Influence to shift in various sectors.
Alternative Hypothesis H 1 : There is a significant association between age group of the respondents and various sectors.
As the calculated value of χ 2 is greater than the table value at 5% level of significance, the investigator rejects the null-hypothesis (H o ). Therefore, there is some relationship between the age group of the respondents and the various sectors.

Education
Education brings better awareness about the environment and the facilities in the total area. The level of education motivates the psychological upliftment of persons and widens social awareness. It also plays an important role in understanding the financial and technical aspects of the area. In the present study, the level of education is classified into illiterate, upto high school, higher secondary school, graduate and Post-graduate.    Thus, it is concluded from the study area that 37.67% of the respondents come under high school level, which forms the majority, 10.67% of the respondents are illiterate, 12.00% of the respondents have completed higher secondary education, 15.66% of them are graduates and 24.00% of them are found with post graduation.
A comparison of educational status of respondents of the study area shows that the manufacturing sector and trading sector have least percentage of illiterate (7.41% and 6.84%) respectively and high percentage of the educated upto graduate and post-graduate level (62.96% and 54.70%) respectively.
On the other hand, the other one sector viz. service sector has high percentage in up to high school level (42.90%) respectively show in Table 4.
Null-Hypothesis H 0 : Educational status of the respondents does not significantly influence to shift in various sectors.
Alternative Hypothesis H 1 : There is a significant association between education of the respondents and various sectors.
As the calculated value of χ 2 is greater than the table value at 5% level of significance, the investigator rejects the null-hypothesis (H o ). Therefore, there is some relationship between the educational status of the respondents and the various sectors in the study area.

Marital status
The marital status of the beneficiaries creates the need to earn more since the family expenses would increase. It is thus an important social variable. The respondents are grouped as married, un-married and widow. The respondents are classified on the basis of their marital status show in Table 5. Table 5 reveals that out of 81 respondents in the manufacturing sector, 75 (92.59%) had been married, 4 (4.94) were un-married and two (2.47%) was a widow.
Thus, it is inferred from the table that the majority of the respondents nearly 91.00% had been married, 5.33% were un-married and 3.67% were widows in the study area.
The distribution of the sample respondents based on the reasons for availing credit is presented in Table 6.
It is observed that in the case of manufacturing sector out of 81 respondents, 38 respondents (46.91%) had availed credit to increase their family income. It is followed by education purpose with 18 respondents (22.22%), personal security, and self satisfaction and others account for 11.11% (9 respondents) respectively.
In the service sector, out of 117 respondents, 47 respondents (46.08%) had availed credit to increase their family income, followed by education purpose which accounted for about 26 respondents (25.49%), personal security is accounted for 11 respondents (10.79%), self-satisfaction and status accounted for 9 respondents (8.82%) each.
In the case of trading sector, out of 117 respondents, 53 respondents (45.36%) had availed credit to increase their family income. It is followed by the education purpose with 22 respondents (18.80%), personal security by 17 respondents (14.53%), and self-satisfaction, status, and others by 9 respondents (7.69%) respectively.
Thus, it is inferred from the table that majority of the respondents had availed credit mainly to increase their family income and for education purpose, accounting 46.00% and 22.00% respectively in the study area [6][7][8][9].

Annual income of the respondents before availing credit
The income of the respondents shows the personal income from all sources per year. Here the income of the respondents before availing      credit is studied. The annual income of the respondents before availing credit has been classified into four groups (below Rs.12000, Rs.12001-Rs.24000, Rs 24001 -Rs.36000, and above Rs.36001) and it has been shown in Table 7.
It is concluded from the table that the annual income before availing credit in the study area is that, about 26.33% of the respondents come under the category of below Rs.12000, 27.00% of the respondents belong to the category of Rs.12001 to Rs.24000, 29.00% of the respondents belong to the category of Rs.24001 to Rs.36000, and 17.67% of the respondents belong to the category of above Rs.36001.

Annual income of the respondents after availing credit
The annual income of the respondents after availing the credit has been classified into four groups and it has been shown in Table 8. Thus it could be concluded from the table regarding the annual income after availing credit in the study area is that, about 7.33% of the respondents come under the category of below Rs.12000, 18.33% of the respondents belong to the category of Rs.12001 to Rs.24000, 22.67% of the respondents belong to the category of Rs.24001 to Rs.36000, and 51.67% of the respondents belong to the category of above Rs.36001.
The null and alternative hypotheses are framed and tested in this study in Table 9.
Null Hypothesis H 0 : There is no relationship between annual income of the respondents and the various sectors Alternative Hypothesis H 1 : There is a relationship between annual income of the respondents and the various sectors.
As the calculated value of χ 2 is greater than the table value at 5% level of significance, the null-hypothesis (H o ) is rejected. Therefore, there is some relationship between the annual income of the respondents and the various sectors in the study area.

Summary of Findings
The study reveals that the sample respondents are mostly young in the age group of 26-35 years, accounting 32.10% and 45.10% and 25.64% of the respondents fall in the age group of 36-45 years. Nearly 3% of the respondents of service sector belong to the age group 46 and above. In manufacturing sectors percentage is around 5%. In trading sector, it is 17.95% which is the highest among all the sectors.
The Chi-Square test proves that there is a significant relationship between the age group of the respondents and the various sectors. It shows that more number of aged and experienced people concentrate in trading sector, whereas the young people concentrate only in service sector.
It is found that 10.67% of the respondents are illiterate, 37.67% of the respondents have education upto high school levels only, 12.00% of the respondents have completed higher secondary education, 15.60% of them are graduates and 24.00% of them are found with post graduation.
The Chi-Square test proves that there is a close relationship between the educational status of the respondents and the various sectors in the study area. It shows that the manufacturing sector and trading sectors have least percentage of illiterates (7.41% and 6.84%) and the high percentage age of the educated upto graduate and postgraduate level (62.96% and 54.70%). On the other hand, the other in service sector has high percentage in up to high school level (43.14%).
It is found that the majority of the respondents nearly 91.00% are married, 5.33% are un-married and 3.67% are widows.
It is observed that majority of the respondents have availed credit mainly to increase their family income and for education purpose accounting for 46.00% and 22.00% respectively.
The study has revealed that regarding the annual income pre-credit period in the study area 26.33% of the respondents come under the category of below Rs.12000, 27.00% of the respondents belong to the category of Rs.12001 to Rs.24000, 29.00% of the respondents belong to the category of Rs.24001 to Rs.36000 and 17.67% of the respondents    It is found that the annual income post-credit in the study area has increased 7.33% of the respondents come under the category of below Rs.12000, 18.33% of the respondents belong to the category of Rs.12001 to Rs.24000, 22.67% of the respondents belong to the category of Rs.24001 to Rs.36000 and 51.67% of the respondents belong to the category of above Rs.36001. Post-credit, really there is a significant improvement in their income level.
The Chi-Square test proves the fact that there is a close association between the annual income of the respondents and the various sectors in the study area [10-12].

Suggestions
In the light of the above discussion and findings, the following suggestions are made: It is suggested that the NGOs should be prevented from interfering with the SHG movement. Steps should be taken to keep them as voluntary organizations. They should not be allowed to use extraneous influences.
Savings by the members is one of the main indicators for economic development. So, the banks and post offices should introduce attractive, user -friendly schemes to encourage the thrift habit among the members.
Microfinance should be used to meet the immediate demand of the poor women for Health, Education or consumption purposes. This will improve the quality of their life and will be ready to take active participation in economic activities.
All service for women in rural areas should be integrated and offered as a package programme. All services and programmes related to agriculture, education, health care, nutrition, family planning and vocational training must be directed towards improving women's earning, increasing their productivity and making economic activity.

Conclusion
In conclusion, the micro-credit schemes have done well in different parts of the country, in implementing the poverty alleviation programmes more effectively, when compared to the Government and non -Government Organizations. So it is necessary that more and more micro-credit schemes are encouraged to sustain in future for various other activities which will bring the women to the main stream.

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Further, micro-credit schemes has helped in assisting the families of women respondents below poverty line by ensuring appreciable sustained level of income through different activities in the study area. Micro-credit scheme is a valuable contribution to the development planning as it presents an alternative way to rural women development. If the micro-credit schemes are conscientiously implemented, they can become a rural power in bringing out the creative and productive potential for rural women. In short the microcredit schemes are to be viewed as agents of change in rural areas for empowerment of rural women.