Health Demand: Empirical Study of Effective Urban Households Demand in Indonesia

Abstract

BACKGROUND: Grossman's health demand model recognizes medical price as a determinant of the estimation model. This article aims to examine the role of medical expenses in health demand by utilizing the number of sick and disturbed days obtained from Susenas, a survey on the expenditure of household food and non-food consumption conducted by the Central Bureau of Statistics to measure health demand and health insurance as a medical price in a reduction model. Health insurance can replace medical expenses because those who have health insurance face relatively low medical costs and face lower medical prices than those without health insurance.
 
 METHODS: Using the Ordinary Least Squares (OLS) estimation technique, sebuah teknik estimasi model regresi for 6,642 households this was obtained through three stages: First, using 71,932 sample households of susenas that relied fully on the Susenas sampling method by BPS; Second, find households that have experienced health problems during the last 6 months; Third, find households that have health expenditures of 24,341. Furthermore, the estimation model is based on 6,642 households identified to be in urban areas using the Ordinary Least Squares (OLS) estimation method.
 
 FINDINGS: The health demand estimation model that can be used to determine the behavior of health demand among urban households is limited to households with formal primary school (SD) education levels. Taking advantage of certain wages, age, cigarette expenditure, and sports expenses, it was found that the number of sick days and felt disturbed in the household group that had health insurance was 5.68 days relatively greater than those without health insurance. However, expanding to higher education and older age was found to be 1.47 days and 1.57 days. Aging tends to decrease good health and health insurance tends to increase it.
 
 CONCLUSION: It was found that health stocks differed between insured households and households without health insurance in those with aging.