Inequality in Medical Expenditure between Urban Employees and Rural Individuals from a Health Equity Perspective: Based on a Life-cycle Model

Authors

  • LIAO Pu China Institute of Actuarial Science, Central University of Finance and Economics, Beijing 102206, China
  • LIU Jinhao School of Insurance, Central University of Finance and Economics, Beijing 102206, China
  • FENG Lu School of Economics and Management, Beijing University of Posts and Telecommunications, Beijing 100086, China

DOI:

https://doi.org/10.20069/3gdtmn58

Keywords:

health equity, medical expenditure, health decision, urban-rural disparities, life-cycle model, simulated method of moments

Abstract

Promoting health equity stands as a fundamental objective within China’s medical system reform efforts. Through policy introduction and reform deepening, significant strides have been made in enhancing health equity. Nonetheless, due to China’s typical urban-rural dual economic structure, a noticeable health gap persists between urban and rural regions. Despite prevailing literature predominantly grounded in econometric methodology, focusing on health inequality, it fails to unveil individuals’ medical expenditure decision-making processes and inherent mechanisms.

This study establishes a framework for optimal consumption, savings, and medical expenditure decision-making based on lifetime expected utility maximization. Herein, medical expenditure and natural laws jointly dictate disease recovery and mortality rates. Parameters for income and basic medical insurance systems for urban and rural individuals are calibrated, with medical expenditure estimations derived via the Simulated Method of Moments for structural estimation of urban and rural individual characteristics. Leveraging the calibrated parameters and framework, this paper addresses medical expenditure decisions for urban and rural individuals, disentangles reasons behind expenditure disparities, and simulates policy counterfactuals to mitigate urban-rural medical expenditure gaps.

Findings indicate that optimal savings and medical expenditures across the life cycle exhibit a distinct inverted U-shape for urban and rural individuals. Notably, the turning point for optimal savings and medical expenditures among urban workers occurs pre-retirement, contrasting with rural individuals at age 80. The significant medical expenditure gap between urban and rural cohorts is attributed to income differentials, subjective preference variations, and disparities in basic medical insurance systems, albeit with diminishing importance. Moreover, improving rural income, augmenting medical insurance coverage, technological advancements in healthcare, and universal health insurance introduction emerge as viable means to narrow the urban-rural medical expenditure gap.

This paper expands upon existing literature in three key areas. First, it incorporates individuals’ health status distinction in endogenizing death/disease risks via the Markov model, thus establishing a more refined endogenous health risk model for discussing medical expenditure decision-making. Second, it reveals the internal logic and behavioral characteristics of individuals’ medical expenditure decision-making within a life cycle framework, supplementing existing literature effectively. Third, diverging from prevailing econometric methods, this study employs structured model to gauge urban and rural individuals’ subjective preferences, scrutinizing medical expenditure inequality, its underlying causes, and potential policy ramifications.

The research reveals urban and rural individuals’ medical expenditure behavioral traits and disparities, offering a theoretical underpinning for policy implementations aimed at narrowing urban-rural medical expenditure gaps. Such insights are instrumental for government agencies in accurately formulating policies to foster health equity between urban and rural populations.

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Published

2024-04-04

How to Cite

Inequality in Medical Expenditure between Urban Employees and Rural Individuals from a Health Equity Perspective: Based on a Life-cycle Model. (2024). Modern Economic Science, 46(2), 1-16. https://doi.org/10.20069/3gdtmn58

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