Ashish Kumar Gupta Research scholar faculty of commerce B.H.U. Varanasi, 221005 Contact No.- +91-9453231481 Email: ashishgupta88foryou@gmail.com |
Poverty is a barrier to a noble life. Self-employment is an important step to have constant incomes and remove the fetters of poverty. The word poverty is used in two senses, as a broad blanket word describe the whole range of deprivation and ill-being and in narrow sense, for purposes of measurement and comparison where it is defined as low-income or more particularly, as low consumption which is considered more stable and easier to measure. Fundamentally, poverty is a denial of choices and opportunities, a violation of human dignity. It means lack of basic capacity to participate effectively in society. It means not having enough to feed and clothe a family, not having a school or clinic to go to; not having the land on which to grow one’s food or a job to earn one’s living, not having access to credit. It means insecurity, powerlessness and exclusion of individuals, households and communities. In this paper researcher examine and analyze that micro-health and life insurance is good tool for poverty alleviation in rural area of Varanasi district.
Keywords: Poverty, micro-insurance, health risk, life risk, alleviation, tool
India is one of the developing country where the credit led market is largely appears for low-income section. The non-presence range of financial services for savings, pension and insurance makes very difficult for poor population to manage their finance and for them it is almost not possible to deal with the different types of risks. While some attempts were made by government with insurance companies, SHF’s and MFI’s to address the various risk by offering life insurance to borrowers and to their families, the previous group effort between insurance companies and micro-finance institutions generated the few cases and grow into much of an operational risk cover for MFIs. After that IRDA which is acting as an apex body of insurance has tightened the regulations for the insurance industry and also looking forward to develop other channels for distribution of micro-insurance products which are viable and can achieve scale.
Micro-health and life insurance are even more challenging in spite of the fact that numerous research studies indicate that health and life related problems are possibly the single major reason by which low-income population has shifted further towards poverty trap. The government has launched the Rashtriya Swasthya Bima Yojana, Aam Aadmi Bima Yojana and Janshree Bima Yojana etc. where the coverage has been notable but problems from place to place like customer education, facility distribution and the sustainability of the exercise considering the claims ratio (well over a 100%) carry on to cast doubts on the long term sustainability of schemes such as these. Generally, a lot more attention requires to be given on the design and distribution of insurance services to poor people.
In this research work an attempt has been made to examine and analysis the state of health and life risk in rural area of Varanasi district precisely for micro-health and life insurance and also traces the social change from this into the society.
Researcher presents a comprehensive review of literature till date which has been conducted at national and international level as follow-
Srinivasan & chalam (2002) [2] investigate in this study that there are various schemes and products present to protect against any type of risks. But these products do not provide proper satisfaction to the customers. The main objective of this study to shows the map of micro-insurance landscape and establish knowledge on a regulatory framework for the insurance industry in India and examine the demand for insurance from MSEs (Micro/Small Enterprises). A part from this, micro-life insurance is as a formal insurance product which is quite popular among the customers and most of the villagers are ready to purchase this product.
Kashyap, Anthony, & Krech (2006) [3] explore promotion of micro-insurance in India through marketing and branding of micro-insurance in rural and semi- urban areas. The main objective of this study is to evaluate the demand and potential supply of micro- insurance in terms of risk takers from various delivery channels in India along with explore the option of undertaking pilot proposals through the development of a basic process outline inclusive of estimated costs, co-operation between the insurance industry, governments, civil society, and enhance North-South partnerships.
The study of Cheriyan, Mukherjee and Haider (2006) [4] show that micro-insurance might be seen as an ideal self-help strategy for the rural population against the natural disaster. The main objective of this study is to emphasize the role of micro insurance in disaster management for low income group of the Indian society as well as to highlight, how micro-insurance can be used to mitigate the economic effects of disaster from risks.
v To know the awareness about micro-health & life insurance among rural group of people in Varanasi district.
v To examine and analyze poverty alleviation through micro-health & life insurance in rural area of Varanasi district.
The study and analysis has been done based on primary data collected through questionnaires from rural’s respondents of Varanasi district. Some important statistical methods such as, mean, standard deviation and one way ANOVA applied to make this analysis for more practical through SPSS. A questionnaire that includes 2 different questions was applied to 300 respondents in Varanasi District, in September 2013. The questionnaire was filled by the respondents in the presence of researcher.
Research Instrument : Questionnaire
Population Consist of : Varanasi District (Rural Area on Tehsil Basis)
Types of Sampling : Random Sampling
Approach : Descriptive
Research Techniques : Survey and Interview
Sampling Unit : Individual
Table No. 1: Micro-insurance as Tool for Health risk
Health Risk | Rajatalab | Pindra | Sadar | Total (In District) |
No of Resp. | No of Resp. | No of Resp. | No of Resp. | |
Strongly disagree | 0 | 0 | 0 | 0 |
Disagree | 2 | 8 | 0 | 10 |
No opinion | 46 | 34 | 55 | 135 |
Agree | 10 | 35 | 10 | 55 |
Strongly agree | 42 | 23 | 35 | 100 |
Total | 100 | 100 | 100 | 300 |
Mean | 3.92 | 3.73 | 3.8 | 3.8167 |
S.D. | 0.98144 | 0.90849 | 0.93203 | 0.94128 |
Source : Primary Data/ Field Survey
Table 1 reflects that less than fifty percent respondents were in favor of either no opinion or strongly agree where as 10% agree that micro-insurance a good tool for health risk for poverty alleviation in Rajatalab Tehsil. In Pindra Tehsil, majority of the respondents almost equally having agree, no opinion and strongly agree while rests, disagree that micro-insurance schemes as a good tool for minimizing health risk. In Sadar Tehsil, role of micro-insurance in reducing health risk was accepted by majority of the respondents (55%), (35%) and (10%) having no opinion, strongly and agree that it is a good tool for diminishing health risk. Overall it may conclude that most of the respondents having no opinion, strongly agree or agree and none respondents have strongly disagree that micro-insurance is a good tool for reducing health risk in Varanasi Tehsil.
Analysis of Factor on the basis of Demographic Variables with more than Two Categories using ANOVA;
Table No. 2: ANOVA Effect of Tehsil on Health Risk Factor
Factor | SS | df | MS | F | Sig. (p) |
MI good tool for health risk | 1.847 | 2 | 0.923 | 1.042 | 0.354 |
Since P > 0.05 so, null hypothesis is accepted and it may be concluded that there is no significant difference factor among the respondents in Tehsil of Varanasi district.
Table No. 3: ANOVA Effect of Occupation on Health Risk Factor
Factor | SS | df | MS | F | Sig. (p) |
MI good tool for health risk | 31.522 | 4 | 7.880 | 9.961 | 0.000 |
Since P < 0.05 so, null hypothesis is rejected and it may be concluded that there is significant difference among the respondents in various categories of occupation.
Table No. 3.1 Multiple Comparisons (Factor and Occupation Categories) | ||||
Tukey HSD | Factor = Health risk | |||
(I) Tehsil of respondents | (J) Tehsil of respondents | Mean Difference (I-J) | Std. Error | Sig. |
Own business | Wage | -0.34884 | 0.17485 | 0.271 |
Cleaner & Sweeper | 0.32763 | 0.20413 | 0.495 | |
Farmer | -0.66134* | 0.17539 | 0.002 | |
Other | 0.04478 | 0.16376 | 0.999 | |
Wage | Own business | 0.34884 | 0.17485 | 0.271 |
Cleaner & Sweeper | 0.67647* | 0.18826 | 0.003 | |
Farmer | -0.31250 | 0.15663 | 0.271 | |
Other | 0.39362 | 0.14349 | 0.050 | |
Cleaner & Sweeper | Own business | -0.32763 | 0.20413 | 0.495 |
Wage | -0.67647* | 0.18826 | 0.003 | |
Farmer | -0.98897* | 0.18876 | 0.000 | |
Other | -0.28285 | 0.17801 | 0.506 | |
Farmer | Own business | 0.66134* | 0.17539 | 0.002 |
Wage | 0.31250 | 0.15663 | 0.271 | |
Cleaner & Sweeper | 0.98897* | 0.18876 | 0.000 | |
Other | 0.70612* | 0.14415 | 0.000 | |
Other | Own business | -0.04478 | 0.16376 | 0.999 |
Wage | -0.39362 | 0.14349 | 0.050 | |
Cleaner & Sweeper | 0.28285 | 0.17801 | 0.506 | |
Farmer | -0.70612* | 0.14415 | 0.000 | |
* The mean difference is significant at the 0.05 level. |
Table exposes the significant difference among respondents of their occupation categories viz., farmer, wage-earners, own-business, cleaner-sweeper and other. Deviation might be due to the fact they are busy in their job, less earnings/ savings, unawareness, jobless or not interested in product and schemes of micro-health insurance programme.
Table No. 4: ANOVA Effect of Education on Health Risk Factor
Factor | SS | df | MS | F | Sig. (p) |
MI good tool for health risk | 4.057 | 4 | 1.014 | 1.147 | 0.335 |
Since P > 0.05 so, null hypothesis is accepted and it may be concluded that there is no significant difference among the respondents in various categories of education.
Table No. 5: Micro-insurance as Tool for Life Risk
Life Risk | Rajatalab | Pindra | Sadar | Total (In District) |
No of Resp. | No of Resp. | No of Resp. | No of Resp. | |
Strongly disagree | 0 | 0 | 0 | 0 |
Disagree | 3 | 0 | 3 | 6 |
No opinion | 85 | 47 | 74 | 206 |
Agree | 12 | 53 | 23 | 88 |
Strongly agree | 0 | 0 | 0 | 0 |
Total | 100 | 100 | 100 | 300 |
Mean | 3.09 | 3.53 | 3.2 | 3.2733 |
S.D. | 0.37859 | 0.50161 | 0.4714 | 0.48931 |
Source: Primary Data/ Field Survey
Above Table indicates that majority of the respondents (85%) having no opinion while rest either agree or disagree that micro-insurance as a good tool for coverage of life risk for poverty alleviation in Rajatalab Tehsil. In Pindra Tehsil, more than one half of the respondents were agree and rest having no opinion that micro-insurance scheme as a good tool for reducing life risk. In Sadar Tehsil, role of micro-insurance in minimizing life risk was no opinion by three fourth of the respondents, followed by agree that it is a good tool for decreasing life risk. Overall it may conclude that more than 68% of the respondents having no opinion while rest respondents agree that micro-insurance is a good tool for minimizing life risk. At the same time we also notice that none was in favor of either strongly disagree or strongly agree in Varanasi Tehsil.
Table No. 6: ANOVA Effect of Tehsil on Life Risk Factor
Factor | SS | df | MS | F | Sig. (p) |
MI good tool for life risk | 10.487 | 2 | 5.243 | 25.487 | 0.000 |
Since P < 0.05 so, null hypothesis is rejected and it can be concluded that there are significant effect factor among the respondents in Tehsil of Varanasi district.
Table No. 6.1: Multiple Comparisons (Factor and Tehsil Categories) | ||||
Tukey HSD | Factor = Life risk | |||
(I) Tehsil of respondents | (J) Tehsil of respondents | Mean Difference (I-J) | Std. Error | Sig. |
Rajatalab | Pindara | -0.44000* | 0.06414 | 0.000 |
Sadar | -0.11000 | 0.06414 | 0.201 | |
Pindara | Rajatalab | 0.44000* | 0.06414 | 0.000 |
Sadar | 0.33000* | 0.06414 | 0.000 | |
Sadar | Rajatalab | 0.11000 | 0.06414 | 0.201 |
Pindara | -0.33000* | 0.06414 | 0.000 | |
* The mean difference is significant at the 0.05 level. |
Table 6.1 reflects that there exists significant difference between Rajatalab-Pindara and Sadar. The respondents of these Tehsils rated factor ‘Life risk’ for disagreement reasons might it is useless, never seen/ heard, lack of motivation/ advertisement, not supported by insurance agents and financial crisis etc. while rest given their consent due to fact might be familiar with the product, having no financial crisis and understands products & schemes of life risk properly.
Table No. 7: ANOVA Effect of Occupation on Life Risk Factor
Factor | SS | df | MS | F | Sig. (p) |
MI good tool for life risk | 4.324 | 4 | 1.081 | 4.741 | 0.001 |
Since P < 0.05 so, null hypothesis is rejected and it may be concluded that there is significant difference among the respondents in various categories of occupation.
Table No. 7.1: Multiple Comparisons (Factor and Occupation Categories) | ||||
Tukey HSD | Factor = Life risk | |||
(I) Tehsil of respondents | (J) Tehsil of respondents | Mean Difference (I-J) | Std. Error | Sig. |
Own business | Wage | 0.28050* | 0.09386 | 0.025 |
Cleaner & Sweeper | -0.00547 | 0.10958 | 1.000 | |
Farmer | 0.30887* | 0.09416 | 0.010 | |
Other | 0.20980 | 0.08791 | 0.122 | |
Wage | Own business | -0.28050* | 0.09386 | 0.025 |
Cleaner & Sweeper | -0.28597* | 0.10106 | 0.040 | |
Farmer | 0.02837 | 0.08409 | 0.997 | |
Other | -0.07070 | 0.07703 | 0.890 | |
Cleaner & Sweeper | Own business | 0.00547 | 0.10958 | 1.000 |
Wage | 0.28597* | 0.10106 | 0.040 | |
Farmer | 0.31434* | 0.10134 | 0.018 | |
Other | 0.21527 | 0.09556 | 0.164 | |
Farmer | Own business | -0.30887* | 0.09416 | 0.010 |
Wage | -0.02837 | 0.08409 | 0.997 | |
Cleaner & Sweeper | -0.31434* | 0.10134 | 0.018 | |
Other | -0.09907 | 0.07738 | 0.704 | |
Other | Own business | -0.20980 | 0.08791 | 0.122 |
Wage | 0.07070 | 0.07703 | 0.890 | |
Cleaner & Sweeper | -0.21527 | 0.09556 | 0.164 | |
Farmer | 0.09907 | 0.07738 | 0.704 | |
* The mean difference is significant at the 0.05 level. |
Table 7.1 exposes the significant difference among respondents of their occupation categories viz., farmer, wage-earners, own-business and cleaner-sweeper. Deviation might be due to the fact they are busy in their job, less earnings/ savings, unawareness, jobless or not interested in product and schemes of micro-life insurance programme.
Table No. 8: ANOVA Effect of Education on Life Risk Factor
Factor | SS | df | MS | F | Sig. (p) |
MI good tool for life risk | 1.028 | 4 | 0.257 | 1.074 | 0.370 |
Since P > 0.05 so, null hypothesis is accepted and it may be concluded that there is no significant difference among the respondents in various categories of education.
The researcher discussed socio-economic development of the poor people, who are using micro-insurance as a tool to poverty alleviation. In order to provide insurance facility to poor one of the most promising avenue for stimulating rural poor lives development through various products of micro-insurance schemes. Normally, poverty is taken as relative and absolute material deprivation reflected in low levels of income and consumption. However, poverty has many dimensions. Though, all of them are not equally amenable to measurement. Low levels of income are not only result in low levels of consumption and material deprivation, but restricts human capability by restricting the access of the poor to education and health facilities too, thereby creating a vicious cycle of poverty. Poverty is also involves various forms of vulnerability and exposure to risk, powerlessness and social exclusion.
Suggestion: In case of health risk, we may suggest that the provider and insurers should provide more information through proper advertisement to poor people about its programmes/ products. As well as, insurers should launch low price health products/ schemes so that which can be purchased easily by the rural people. In case of life risk, 69% respondents have no opinion that micro-insurance is good tool for life risk in rural area of Varanasi district. So, the insurers should provide micro-life insurance according to their need and occupation. Dedicated and devoted agents should be given the task of giving full knowledge of the life risk products/ schemes to the rural people. At the same time advertisement in this direction will prove boon for them.
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[1] Research scholar, faculty of commerce, B.H.U. Varanasi, 221005 ,
Email – ashishgupta88foryou@gmail.com, Contact: 9453231481
[2] Srinivasan, Girija, (Consultant) & chalam, Ramesh S., Aruna (Rural Finance Practitioner); October 2002"Micro Insurance In India" http://www.microfinancegateway.org/gm/document-1.9.27360/224.pdf.
[3] Kashyap, Arun, Anthony, Michael, & Krech, Rüdiger; August 2006 “Micro insurance: Demand and market prospects- India” Allianz AG, GTZ and UNDP Public Private Partnership.
[4] Cheriyan, Anup, Mukherjee, Debanjan, and Haider, Imran; December 2006 "Role of micro-insurance in disaster management" Pravartak special anniversary issue on insurance and disaster management.