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Three-part model for fractional response variables with application to Chinese household health insurance coverage

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  • Kuangnan Fang
  • Shuangge Ma

Abstract

A survey on health insurance was conducted in July and August of 2011 in three major cities in China. In this study, we analyze the household coverage rate, which is an important index of the quality of health insurance. The coverage rate is restricted to the unit interval [0, 1], and it may differ from other rate data in that the “two corners” are nonzero. That is, there are nonzero probabilities of zero and full coverage. Such data may also be encountered in economics, finance, medicine, and many other areas. The existing approaches may not be able to properly accommodate such data. In this study, we develop a three-part model that properly describes fractional response variables with non-ignorable zeros and ones. We investigate estimation and inference under two proportional constraints on the regression parameters. Such constraints may lead to more lucid interpretations and fewer unknown parameters and hence more accurate estimation. A simulation study is conducted to compare the performance of constrained and unconstrained models and show that estimation under constraint can be more efficient. The analysis of household health insurance coverage data suggests that household size, income, expense, and presence of chronic disease are associated with insurance coverage.

Suggested Citation

  • Kuangnan Fang & Shuangge Ma, 2013. "Three-part model for fractional response variables with application to Chinese household health insurance coverage," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(5), pages 925-940.
    • Handle: RePEc:taf:japsta:v:40:y:2013:i:5:p:925-940
    DOI: 10.1080/02664763.2012.758246
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    Cited by:

    1. Kuangnan Fang & Xinyan Fan & Wei Lan & Bingquan Wang, 2019. "Nonparametric additive beta regression for fractional response with application to body fat data," Annals of Operations Research, Springer, vol. 276(1), pages 331-347, May.
    2. Wang, Hongyang & Zhang, Dayong & Guariglia, Alessandra & Fan, Gang-Zhi, 2021. "‘Growing out of the growing pain’: Financial literacy and life insurance demand in China," Pacific-Basin Finance Journal, Elsevier, vol. 66(C).

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