Picturing How PMSBY and PMJJBY Matters


In 2015, the Government of India launched two term plans viz. Pradhan Mantri Suraksha Bima Yojana (PMSBY) and Pradhan Mantri Jeevan Jyoti Bima Yojana (PMJJBY) with the objectives to cover the vast uninsured population. Under the schemes, the insured get term insurance coverage up to INR 0.2 million subject to certain terms and conditions by paying an annual premium of merely INR 12 and INR 330 respectively, the least among all the existing insurance policies available in the country. The present study seeks to report the motivating factors of the sample respondents of Dharmanagar, a town of the north-eastern Indian state of Tripura, for taking term insurance under PMSBY and PMJJBY. A model has been formed and the data reduction test has been carried out through Factor analysis. Using cross- sectional research design and based on the outcome of a pilot study, a survey with 50 questions has been used to collect data from a randomly chosen sample of 125 respondents. The result of the Independent Sample t-test has indicated that gender is a significant influencing factor in purchasing insurance plans.

Additionally, the findings of Cross Tabulations have validated that non- gender demographics also have a significant influence in taking insurance coverage. The outcome of Multiple Regressions has documented that financial literacy and uncertainties have a significant influence in purchasing the plans. An analysis of the relevance of each policy has been drawn and it acknowledges a few shortcomings like study period, study area, small sample size, selective hypotheses and variables, self-administered interview schedule rather than adoption or adaptation and power of statistical tools; it has also indicated the roadmap for future research.




Literature has indicated that life insurance can be studied theoretically from multi-dimensional perspectives such as adverse selection and demand elasticity (Thomas, 2009), as an investment tool (Mayers & Smith,1983), its density, penetration, GDP per capita, inflation, impact of development of the banking sector (Beck & Webb, 2003; Browne & Kim, 1993; Outreville, 1996a), as an emergency fund (Hammond, Huston & melander, 1967), as a bequest (Inkmann & Michaelides, 2012; Bhalla & Kaur, 2007) and the impact of culture on its demand (Park, Borde & Choi, 2002). Life Insurance products generally have been classified into (a) term life insurance policy, (b) whole life insurance policy, (c) endowment policy, (d) pension plan, (e) money back policy, etc. In 2015, the Government of India launched two term plans viz. Pradhan Mantri Suraksha Bima Yojana (hereinafter referred to as PMSBY) and Pradhan Mantri Jeevan Jyoti Bima Yojana (hereinafter referred to as PMJJBY) with the objective of covering the vast uninsured population. A term life insurance policy covers the life of the policy holder for a certain period of time; during this period, in case of any mishap, the dependants of the insured are given the policy amount. However, if the insured survives the policy period, nothing is paid to the policyholder or the beneficiaries. In other words, it only covers the risk of loss of life of the insured during the policy period against the payment of the stipulated premium. Under PMSBY, any citizen of India between 18 and 70 years of age, having a savings bank account, can take cover under this scheme by paying an annual premium of INR 12 only with a sum assured of INR 0.2 million, payable to the dependant(s) in case of any accidental death of the insured. Such compensation would be reduced to INR 0.1 million in case of permanent total disability with loss of both eyes or loss of both hands or feet, or loss of sight of one eye and loss of one hand or one foot. Under PMJJBY, an Indian citizen between 18 and 50 years of age having a savings bank account with a declaration of sound health can take cover by paying an annual premium of INR 330 only with a sum assured of INR 0.2 million payable to the dependant(s) in case of death of the insured due to any reason.

Literature has acknowledged the seminal contribution of researchers regarding social security schemes (Polanyi, 1944; Marshall, 1949; Wilensky & Lebeaux, 1958; Kerr et al. 1960; Pryor, 1968; Rimlinger, 1971; Heclo, 1974). Studies have validated that rising healthcare costs and fatal eventualities adversely impact the earnings of families (Wang et al.2011; Yang & Hall, 2008; Mokdad et al. 2003; Finkelstein, Fiebelkorn & Wang, 2003). Community Based Health Insurance (CBHI) schemes may well address the problem (Dror & Jambhekar, 2016; Dror, 2014; Dror & Jacquier, 1999). This emphasised the introduction of health insurance schemes in countries such as Africa (Arhin, 1995; World Bank, 1987, 1993; Vogel,1990; Abel-Smith,1986) but their presence is less in developing countries (Dumoulin & Kaddar, 1993; Baza et al. 1993; Carrin,1987); around 30 percent of the population of Thailand in 2001 had no health insurance (Surarathecha et al. 2005; Jirojanakul et al. 2004; Tangcharoensathien,1996). These schemes suffer from structural and implementation problems in India (Jha, 2014; Chatterjee et al. 2013; Jha et al. 2013; Jha & Gaiha, 2012; Svedberg, 2012; Arora, 2011; Johnson & Kumar, 2011; Reddy, 2011; Palacious, 2011; Jha et al. 2009; Kuruvilla & Liu, 2007; Mooji & Dev, 2004; Jalan & Ravaliion, 2003; Parekh, 2003; Saxena, 2001). A few studies have suggested the need for more market-oriented social insurance schemes in EU (Ferrera & Hemerijck, 2003; Esping-Andersen, 2002; Bonoli et al. 2000; Scharpf & Schmidt, 2000).


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