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The Determinants of Demand for Life Insurance in an Emerging Economy—India

Author

Listed:
  • Preeti Kakar

    (National Council for Applied Economic Research, Parisila Bhavan, 11 Indraprastha Estate, New Delhi 110002; e-mail: pkakar@ncaer.org)

  • Rajesh Shukla

    (National Council for Applied Economic Research, Parisila Bhavan, 11 Indraprastha Estate, New Delhi 110002; e-mail: rkshukla@ncaer.org)

Abstract

Social security is virtually non-existent in India. While governments play a role providing some security to poor households (through the public distribution system targeted at households below the poverty line), in general financial security remains the responsibility of individuals. Life insurance is one of the most important social security measures undertaken in the country. Based on primary data generated through the National Council of Applied Economic Research’s (NCAER) National Survey of Household Income and Expenditure (NSHIE), this article attempts to identify determinants of life insurance ownership in the country. An analysis using logistic regression has corroborated that insured households tend to be more prosperous, more educated and more optimistic about future security than non-insured households. Both the level of education and occupation of the chief earner of a household are major determinants of life insurance participation, apart from asset-ownership. Further, households that are more optimistic about the adequacy of future income and savings show higher levels of participation. No rural–urban divide has been noticed with respect to these influencing factors.

Suggested Citation

  • Preeti Kakar & Rajesh Shukla, 2010. "The Determinants of Demand for Life Insurance in an Emerging Economy—India," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 4(1), pages 49-77, January.
  • Handle: RePEc:sae:mareco:v:4:y:2010:i:1:p:49-77
    DOI: 10.1177/097380100900400103
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    References listed on IDEAS

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    1. Chuang, Hwei-Lin, 1997. "High school youths' dropout and re-enrollment behavior," Economics of Education Review, Elsevier, vol. 16(2), pages 171-186, April.
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    More about this item

    Keywords

    Life Insurance; Logistic Regression; Logit Analysis; JEL Classification: C31; JEL Classification: C35; JEL Classification: C80; JEL Classification: G22;
    All these keywords.

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General
    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies

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