Munich Personal RePEc Archive

Are there differences between unconditional and conditional demand estimates? implications for future research and policy

Hidayat, Budi (2007): Are there differences between unconditional and conditional demand estimates? implications for future research and policy. Published in: Cost Effectiveness and Resource Allocation , Vol. 6, (5. August 2008)

[img]
Preview
PDF
MPRA_paper_30196.pdf

Download (358kB) | Preview

Abstract

Background: Estimations of the demand for healthcare often rely on estimating the conditional probabilities of being ill. Such estimate poses several problems due to sample selectivity problems and an under-reporting of the incidence of illness. This study examines the effects of health insurance on healthcare demand in Indonesia, using samples that are both unconditional and conditional on being ill, and comparing the results. Methods: The demand for outpatient care in three alternative providers was modeled using a multinomial logit regression for samples unconditional on being ill (N = 16485) and conditional on being ill (N = 5055). The ill sample was constructed from two measures of health status – activity of daily living impairments and severity of illness – derived from the second round of panel data from the Indonesian Family Life Survey. The recycling prediction method was used to predict the distribution of utilization rates based on having health insurance and income status, while holding all other variables constant. Results: Both unconditional and conditional estimates yield similar results in terms of the direction of the most covariates. The magnitude effects of insurance on healthcare demand are about 7.5% (public providers) and 20% (private providers) higher for unconditional estimates than for conditional ones. Further, exogenous variables in the former estimates explain a higher variation of the model than that in the latter ones. Findings confirm that health insurance has a positive impact on the demand for healthcare, with the highest effect found among the lowest income group. Conclusion: Conditional estimates do not suffer from statistical selection bias. Such estimates produce smaller demand effects for health insurance than unconditional ones do. Whether to rely on conditional or unconditional demand estimates depends on the purpose of study in question. Findings also demonstrate that health insurance programs significantly improve access to healthcare services, supporting the development of national health insurance programs to address under-utilization of formal healthcare in Indonesia.

UB_LMU-Logo
MPRA is a RePEc service hosted by
the Munich University Library in Germany.