An empirical study on the determinants of health care expenses in emerging economies

BMC Health Serv Res. 2020 Aug 24;20(1):774. doi: 10.1186/s12913-020-05414-z.

Abstract

Background: Emerging countries continue to suffer gravely from insufficient healthcare funding, which adversely affects access to quality healthcare and ultimately the health status of citizens. By using panel data from the World Development Indicators, the study examined the determinants of health care expenditure among twenty-two (22) emerging countries from the year 2000 to 2018.

Methods: The study employed cross-section dependence and homogeneity tests to confirm cross-sectional dependence and to deal with homogeneity issues. The Quantile regression technique is employed to test for the relationship between private and public health care expenses and its determinants. The Pooled mean group causality test is used to examine the causal connections among the variables.

Results: The outcome of the quantile regression test revealed that economic growth and aging population could induce healthcare costs in emerging countries. However, the impact of industrialization, agricultural activities, and technological advancement on health expenses are found to be noticeably heterogeneous at the various quantile levels. Unidirectional causality was found between industrialization and public health expenses; whereas two-way causal influence was reveled amongst public health expenditure and GDP per capita; public health expenditure and agricultural activities.

Conclusion: It is therefore suggested that effective and integrated strategies should be considered by industries and agricultural sectors to help reduce preventable diseases that will ultimately reduce healthcare costs among the emerging countries.

Keywords: Agricultural activities; Economic growth; Health care expenditure; Industrialization; Quantile regression.

MeSH terms

  • Aged
  • Aged, 80 and over
  • Cross-Sectional Studies
  • Delivery of Health Care / statistics & numerical data
  • Developing Countries / statistics & numerical data*
  • Health Expenditures / statistics & numerical data*
  • Humans