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2019 | 35 | 106-123
Article title

Count data modelling of health insurance and health care utilisation in Nigeria

Content
Title variants
Languages of publication
EN
Abstracts
EN
Aim/purpose – Estimation of the model of interdependent demand for health insurance and health care utilisation involves issues of stochastic dependence between health insurance and health care utilisation. This study explored a count data estimation technique to determine the most appropriate estimation method for the interdependence of health insurance and health care demand in Nigeria. Design/methodology/approach – The study employed Hidayat and Pokhrel (2010) framework to choose among the six alternatives of two classes of count data model. The data for the study were collected using a purposive sampling survey in the six geopolitical zones in Nigeria. Findings – The results showed that the general method of moments (GMM) estimator is preferable to model the determinants of medical care consumption with health insurance. Price of health care services is positively related to medical care consumption with health insurance and social health insurance. The income-medical care relationship indicated that medical care services are inferior good under private health insurance and a normal good with social health insurance during sick period. Research implications/limitations – The implication of this study is that the estimation method that accommodates endogenous regressors is the appropriate estimation technique for the interdependence of health insurance and health care utilisation. The limitation of this study is that the recall period was just six months prior to the survey. Originality/value/contribution – The study revealed that the estimation techniques for the interdependence of health insurance and health care utilisation must recognised the influence of individual and household characteristics on the decision to purchase health insurance and health care consumption. Hence, diagnostics tests are require to choose the most appropriate estimation technique.
Year
Volume
35
Pages
106-123
Physical description
Contributors
  • Department of Economics. Federal University of Technology, Akure
  • Department of Business Administration. Elizade University, Ilara-Mokin, Ondo State
References
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Document Type
Publication order reference
Identifiers
ISSN
1732-1948
YADDA identifier
bwmeta1.element.cejsh-3bdcf464-dcf6-4d6e-b28b-5b96b65bbf03
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