Skip to main content

Advertisement

SpringerLink
Log in

Using respondents’ uncertainty scores to mitigate hypothetical bias in community-based health insurance studies

  • Original Paper
  • Published:
The European Journal of Health Economics Aims and scope Submit manuscript

Abstract

Community-based health insurance has been implemented in several developing countries to help the poor to gain access to adequate health-care services. Assessing what the poor are willing to pay is of paramount importance for policymaking. The contingent valuation method, which relies on a hypothetical market, is commonly used for this purpose. But the presence of the hypothetical bias that is most often inherent in this method tends to bias the estimates upward and compromises policymaking. This paper uses respondents’ uncertainty scores in an attempt to mitigate hypothetical bias in community-based health insurance in one rural setting in Cameroon. Uncertainty scores are often employed in single dichotomous choice surveys. An originality of the paper is to use such an approach in a double-bounded dichotomous choice survey. The results suggest that this instrument is effective at decreasing the mean WTP.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

Notes

  1. CBHI is also sometimes called community health funds, mutual health organizations or rural health insurance.

  2. The use of the cheap talk in CV survey has produced controversial results. In some studies, the cheap talk has been effective to reduce the hypothetical bias. In other studies, the use of cheap talk has exacerbated the hypothetical bias. Furthermore, the use of budget reminder and substitutes was also ineffective in many studies.

  3. These authors found that a certainty level of “7 or higher” best corresponded with actual participation rates. They also recommend that lower levels of FCQ in hypothetical payment should be used to calibrate hypothetical values to actual contributions. The use of a certainty level of “7 or higher” in this paper reflects this more conservative approach to calibration.

  4. In addition to the use of visual aids, we chose enumerators that were from the local areas, and sometimes, the administration of the questionnaire was done in the local language.

  5. The DBDC yields four times efficiency gains as compared to the SDBC.

  6. Benefit transfer can sometimes be used when one does not have the budget or the time to carry out a survey.

References

  1. WHO: Primary health care. Report of the International Conference on Primary Health Care, Alma-Ata, Geneva, 6–12 Sept 1978

  2. Ahuja, R., Jütting, J.: Are the poor too poor to demand health insurance? In: Indian council for research on international economic relations. Working paper no. 118, New Delhi (2004)

  3. Jakab, M., Krishnan, C.: Review of the Strenghts and Weaknesses of Community Financing. Health Financing for Poor People: Resource Mobilization and Risk Sharing. The World Bank, Washington (2004)

    Google Scholar 

  4. Wiesmann, D., Jütting, J.: The emerging movement of community-based health insurance in sub-Saharan Africa: experiences and lessons learned. Afr. Spectr. 2/2000, 193–210 (2000)

    Google Scholar 

  5. Desmet, A., Chhowdhury, A., Islam, K.: The potential for social mobilization in Bangladesh. Soc. Sci. Med. 48, 925–938 (1999)

    Article  PubMed  CAS  Google Scholar 

  6. Jütting, J.: Financial Protection and Access to Health Care in Rural Areas of Senegal. Health Financing for Poor People: Resource Mobilization and Risk Sharing. The World Bank, Washington (2004)

    Google Scholar 

  7. Hsiao, W.C.: Unmet health needs of two billion. Is community financing a solution? In: Prekar, A.S. (ed.) Health, Nutrition and Population Discussion Paper. World Bank, Washington (2001)

    Google Scholar 

  8. Akerlof, G.: The market for lemons: quality uncertainty and the market mechanism. Q. J. Econ. 94, 488–500 (1970)

    Article  Google Scholar 

  9. Rothschild, M., Stigltiz, J.: Equilibrium in competitive insurance market: an essay on the economics of imperfect information. Q. J. Econ. 90, 630–649 (1976)

    Article  Google Scholar 

  10. Pauly, M.V.: The economics of moral hazard. Am. Econ. Rev. 3, 531–537 (1968)

    Google Scholar 

  11. Spence, M., Zeckhauser, R.: Insurance, information, and individual action. Am. Econ. Rev. 61, 380–387 (1971)

    Google Scholar 

  12. Arrow, K.J.: Essays in the Theory of Risk-Bearing. North-Holland, London (1970)

    Google Scholar 

  13. Jakab, M., Krishnan, C.: Community involvement in health care financing: a survey of the literature on the impact, strengths, and weaknesses. In: Preker, A.S. (ed.) Health Care Financing for Rural and Low-Income Populations, a Collection of Background Reports for the Commission on Macro-Economics and Health. World Bank, Washington (2001)

    Google Scholar 

  14. Ndiaye, P., Soors, W., Criel, B.: A view from beneath: community health insurance in Africa. Trop. Med. Int. Health 12(2), 157–161 (2007)

    Article  PubMed  Google Scholar 

  15. Champ, P.A., Bishop, R.C., Brown, T.C., McCollum, D.W.: Using donation mechanisms to value nonuse benefits from public goods. J. Environ. Econ. Manag. 33(2), 151–162 (1997)

    Article  Google Scholar 

  16. Gustafsson-Wright, E., Asfaw, A., Van der Gaag, J.: Willingness to pay for health insurance: an analysis of the potential market for new low-cost health insurance products in Namibia. Soc. Sci. Med. 69(9), 1351–1359 (2009)

    Article  PubMed  Google Scholar 

  17. Dror, M., Radermacher, R., Koren, R.: Willingness to pay for health insurance among rural and poor persons: field evidence from seven micro health insurance units in India. Health Pol. 82, 12–27 (2007)

    Article  Google Scholar 

  18. Mathiyazhagan, K.: Willingness to pay for rural health insurance through community participation in India. Int. J. Health Plan. Manag. 13, 46–47 (1998)

    Google Scholar 

  19. Dong, H., Kouyate, B., Cairns, J., Mugisha, F., Sauerborn, R.: Willingness-to-pay for community-based insurance in Burkina Faso. Health Econ. 12(10), 849–862 (2003)

    Article  PubMed  Google Scholar 

  20. Dong, H., Kouyate, B., Cairns, J., Sauerborn, R.: Differential willingness of household heads to pay community-based health insurance premia for themselves and other household members. Health Pol. Plan. 19(2), 120–126 (2004)

    Article  Google Scholar 

  21. Dong, H., Mugisha, F., Gbangou, A., Kouyate, B., Sauerborn, R.: The feasibility of community-based health insurance in Burkina Faso. Health Pol. 69(1), 45–53 (2004)

    Article  Google Scholar 

  22. Asenso-Okyere, W.K., Osei-Akoto, I., Anum, A., Appiah, E.N.: Willingness to pay for health insurance in a developing economy. A pilot study of the informal sector of Ghana using contingent valuation. Health Pol. 42(3), 223–237 (1997)

    Article  CAS  Google Scholar 

  23. Ataguba, J., Ichoku, E.H., Fonta, W.: Estimating the willingness to pay for community healthcare insurance in rural Nigeria. Poverty and Economic Policy, Dakar (2008)

    Google Scholar 

  24. Neill, H.R., Cummings, R.G., Ganderton, P.T., Harrison, G.W., McGuckin, T.: Hypothetical surveys and real economic commitments. Land Econ. 70(2), 145–154 (1994)

    Article  Google Scholar 

  25. Loomis, J., Gonzalez-Caban, A., Gregory, R.: Do reminders of substitutes and budget constraints influence contingent valuation estimates? Land Econ. 70(4), 499–506 (1994)

    Article  Google Scholar 

  26. Cummings, R.G., Taylor, L.O.: Unbiased value estimates for environmental goods: A cheap talk design for the contingent valuation method. Am. Econ. Rev. 89, 649–665 (1999)

    Article  Google Scholar 

  27. Landry, C.E., List, J.A.: Using ex ante approaches to obtain credible signals for value in contingent markets: evidence from the field. Am. J. Agric. Econ. 89, 420–429 (2007)

    Article  Google Scholar 

  28. Mozumder, P., Berrens, R.: Investigating hypothetical bias: induced-value tests of the referendum voting mechanism with uncertainty. Appl. Econ. Lett. 14, 705–709 (2007)

    Article  Google Scholar 

  29. Whitehead, J.C., Cherry, T.L.: Willingness to pay for a green energy program: a comparison of ex-ante and ex-post hypothetical bias mitigation approaches. Resour. Energ. Econ. 29, 247–261 (2007)

    Article  Google Scholar 

  30. Whittington, D., Kerry, S.V., Okorafor, A., Okore, A., Long, L.J., McPhail, A.: Giving respondents time to think in contingent valuation studies: a developing country application. J. Environ. Econ. Manag. 22, 205–225 (1992)

    Article  Google Scholar 

  31. Bulte, E., Gerking, S., List, J.A., de Zeeuw, A.: The effect of varying the causes of environmental problems on stated values: evidence from a field study. J. Environ. Econ. Manag. 49, 330–342 (2005)

    Article  Google Scholar 

  32. Bostedt, G., Ericsson, G., Kindberg, J.: Contingent values as implicit contracts: estimating minimum legal willingness to pay for conservation of large carnivores in Sweden. J. Environ. Resour. Econ. 39, 189–198 (2008)

    Article  Google Scholar 

  33. Jacquemet, N., Jameas, A., Luchini, S., Shogren, J.F.: Referenda under Oath. Unpublished working paper, GREQAM-CNRS, Universités d’Aix-Marseille II et III (2010)

  34. Carlsson, F., Kataria, M., Krupnick, A., Lampi, E., Löfgren, A., Qin, P., Sterner, T., Chung, S.: The truth, the whole truth, and nothing but the truth: a multiple country test of an oath script. Working Papers in Economics No 473, Department of Economics, University of Gothenburg (2010)

  35. Champ, P.A., Bishop, R.C.: Donation payment mechanisms and contingent valuation: an empirical study of hypothetical bias. Environ. Resour. Econ. 19(4), 383–402 (2001)

    Article  Google Scholar 

  36. Blumenschein, K., Blomquist, G.C., Johannesson, M., Horn, N., Freeman, P.: Eliciting willingness to pay without bias: evidence from a field experiment. Econ. J. 118(525), 114–137 (2008)

    Article  Google Scholar 

  37. Blumenschein, K., Johannesson, M., Yokoyama, K.K., Freeman, P.R.: Hypothetical versus real willingness to pay in the health care sector: Results from a field experiment. J. Health Econ. 20(3), 441–457 (2001)

    Article  PubMed  CAS  Google Scholar 

  38. Ethier, R.G., Poe, G.L., Schulze, W.D., Clark, J.E.: A comparison of hypothetical phone and mail contingent valuation responses for green pricing electricity programs. Land Econ. 76(1), 54–67 (2000)

    Article  Google Scholar 

  39. Johannesson, M., Blomquist, G.C., Blumenschein, K., Johansson, P.-O., Liljas, B., O’Conor, R.M.: Calibrating hypothetical willingness to pay responses. J. Uncertain. Risk 8, 21–32 (1999)

    Article  Google Scholar 

  40. Li, C., Mattson, L.: Discrete choice under preference uncertainty: an improved structural model for contingent valuation. J. Environ. Econ. Manag. 28, 256–269 (1995)

    Article  Google Scholar 

  41. Wang, H.: Treatment of don’t-know responses in contingent valuation surveys: a random valuation model. J. Environ. Econ. Manag. 32, 219–232 (1997)

    Article  Google Scholar 

  42. Cameron, T.A.: A new paradigm for valuing non-market goods using referendum data: maximum likelihood estimation by censored logistic regression. J. Environ. Econ. Manag. 15(3), 355–379 (1988)

    Article  Google Scholar 

  43. Hanemann, M., Loomis, W.J., Kanninen, B.: Statistical efficiency of double-bounded dichotomous choice contingent valuation. Am. J. Agric. Econ. 73, 1255–1263 (1991)

    Article  Google Scholar 

  44. Haab, T.C., McConnell, K.E.: Alternative methods for handling negative willingness to pay in referendum models. J. Environ. Econ. Manag. 32, 251–270 (1997)

    Article  Google Scholar 

  45. Hensher, D.A., Greene, W.H.: The mixed logit model: the state of practice. Transportation 30, 133–176 (2003)

    Article  Google Scholar 

  46. Poe, G.L., Clark, J.E., Rondeau, D., Schulze, W.D.: Provision point mechanisms and field validity tests of contingent valuation. Environ. Resour. Econ. 23, 105–131 (2002)

    Article  Google Scholar 

  47. Arrow, K., Solow, P.R., Leamer, E.E., Radner, R., Shuman, H.: Report of NOAA panel on contingent valuation method. Fed. Regist. 58(10), 4601–4614 (1993)

    Google Scholar 

  48. Carson, R.T.: Contingent valuation: a user’s guide. Environ. Sci. Technol. 34, 1413–1418 (2000)

    Article  CAS  Google Scholar 

  49. Whitehead, J.C.: A practitioner’s primer on contingent valuation. In: Alberini, A., Kahn, J. (eds.) Contingent Valuation Handbook. Edward Elgar Publishing, Cheltenham (2006)

    Google Scholar 

  50. Whittington, D.: Improving the performance of contingent valuation studies in developing countries. Environ. Resour. Econ. 22, 323–367 (2002)

    Article  Google Scholar 

  51. Mitchell, R.C., Carson, R.T.: Using Surveys to Value Public Goods: The Contingent Valuation Method. Resource for the Future, Washington (1989)

    Google Scholar 

  52. Loomis, J., Ekstrand, E.: Alternative approaches for incorporating respondent uncertainty when estimating willingness to pay: The case of the Mexican spotted owl. Ecol. Econ. 27, 29–41 (1998)

    Article  Google Scholar 

  53. Zhang, L., Wang, H., Wang, L., Hsiao, W.: Social capital and farmer’s willingness-to-join a newly established community-based health insurance in rural China. Health Pol. 76, 233–242 (2006)

    Article  Google Scholar 

Download references

Acknowledgments

This work was carried out with financial and scientific support from the International Labor Organization (40052113/0) under the Microinsurance Innovation Facility and the expertise of the European Development Research Network (EUDN). We will also like to thank the African Doctoral Dissertation Research Fellowship offered by the African Population and Health Research Center (APHRC) in partnership with the International Development Research Centre (IDRC) for financial assistance. The authors are grateful to Dr. Allegue Jean Duclos and two anonymous referees for useful comments. The usual disclaimer applies.

Author information

Authors and Affiliations

  1. CREM, UMR CNRS 6211, University of Rennes I, 7 Place Hoche, 35 065, Rennes Cedex, France

    Hermann Pythagore Pierre Donfouet & Eric Malin

  2. LEMNA, University of Nantes, Chemin de la Censive du Tertre, 44322, NANTES Cedex, France

    Pierre-Alexandre Mahieu

Authors
  1. Hermann Pythagore Pierre Donfouet
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Pierre-Alexandre Mahieu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Eric Malin
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Hermann Pythagore Pierre Donfouet.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Donfouet, H.P.P., Mahieu, PA. & Malin, E. Using respondents’ uncertainty scores to mitigate hypothetical bias in community-based health insurance studies. Eur J Health Econ 14, 277–285 (2013). https://doi.org/10.1007/s10198-011-0369-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10198-011-0369-0

Keywords

JEL Classification

Search

Navigation