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Estimating the attributes of willingness to pay for a community based health insurance scheme in Odisha state, India

Author

Listed:
  • Denny John

    (MBA, MPH, FRSPH, Tutor-Health Economics, People's Open Access Education Initiative, 34 Stafford Road, Eccles, Manchester, UK M30 9ED, Email: djohn1976@gmail.com)

  • Vijender Kumar

    (MA (Economics), Consultant, PART Pvt. Ltd, Kamla Nagar, New Delhi, Mob: +919873805308, Email: vijender1232@gmail.com)

Abstract

This paper aims to quantify, using an utility maximisation approach, the extent to which an attribute affects the decision making process at individual as well as group level for a community based health insurance scheme launched among tribal populations of Madan Rampur block in Kalahandi district, Odisha. Analysis has been performed using mixed logit modelling incorporating conditional as well as multinomial logit models because of the dependency of both the choice specific and the individualistic attributes of the choice maker on the decision making process. The price of the health care insurance plan has been taken as the choice specific attributes, while the gender ratio of group, average age along with male, children, working and literacy population percentage have been taken as group-specific attributes. This choice modelling provides a tool for community based health insurance (CBHI) schemes’ efficient designing, evaluation and implementation in low- and middle-income countries.

Suggested Citation

  • Denny John & Vijender Kumar, 2015. "Estimating the attributes of willingness to pay for a community based health insurance scheme in Odisha state, India," Econometrics Letters, Bilimsel Mektuplar Organizasyonu (Scientific letters), vol. 2(2), pages 12-33.
  • Handle: RePEc:bmo:bmoart:v:2:y:2015:i:2:p:12-33
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    File URL: http://dx.doi.org/10.5455/Elet.2015.2.2.2
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    More about this item

    Keywords

    Discrete choice analysis; Community Based Health Insurance (CBHI); Utility Approach; Criteria for Decision-Making Under Risk and Uncertainty;

    JEL classification:

    • I10 - Health, Education, and Welfare - - Health - - - General
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions

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