The effect of health insurance on hospitalization: Identification of adverse selection, moral hazard and the vulnerable population in the Indian healthcare market.

• A joint analysis of health insurance and hospitalization addressing endogeneity. • Higher uptake of insurance by chronically ill people indicates adverse selection. • Hospitalization increases with health insurance indicate a possible moral hazard. • Identifying thresholds of the continuous covariates with observed non-linear patterns. • Chronically ill females, older adults, rural residents are often neglected. The Indian healthcare sector is growing at a rapid pace; nevertheless, inequality in healthcare consumption and catastrophic healthcare expenditure is also increasing at an alarming rate. In addition to socioeconomic differences, poor healthcare infrastructure, and inadequate risk-pooling mechanisms; asymmetric information in the healthcare market is also a potential contributor to this inequity and increasing costs. The consequences of information asymmetry are adverse selection (AS) and moral hazard (MH). AS occurs if people with health risks (high-risk individuals) are more prone to buying health insurance as compared to low-risk individuals. MH occurs when insured individuals are more likely to use healthcare than the uninsured individuals, inflating insurance premiums and medical care costs. Empirically, AS and MH lead to endogeneity due to unobserved heterogeneity. In practice, endogeneity is often addressed by using the instrumental variable estimation technique; however, this approach suffers from identification problems. Therefore, in this paper, we use an instrument-free semi-parametric copula regression technique to examine how health insurance status affects hospitalization using a sample of individuals from a large nationally representative survey for India. Our results suggest the presence of AS and potential MH in the Indian healthcare market. We observe that chronically ill individuals are probable sources of AS, which leads to possible MH. A spline regression analysis suggests nonlinearity in health insurance choice and healthcare utilization across age, education, family size, and household consumption expenditure. We find chronically ill women in India exhibit less insurance coverage and lower hospital care usage. We also identify the vulnerable groups, such as older adults and rural residents, who have low insurance participation and high healthcare consumption. Our results indicate toward the need for evidence-based health care policy to manage the healthcare system and support the disadvantaged population of India. [ABSTRACT FROM AUTHOR]