Methods: This study uses the national representative 2007 and 2008 China Household Income Project (CHIP) data which collected NRCMI information at the village level and individual level. The analytical sample was 29,544 individuals in 7,202 households in 799 villages. A mixed-effects model was applied in the analysis which allowed to control for the time-invariant heterogeneity within both households and villages levels. This strategy reduced the selection bias which was induced by the fact that the individual participation and village implementation of NRCMI were not randomly assigned.
Results: The results show that more than 90% of villages in six provinces implemented NRCMI by 2007. The villages which had most residences with no NRCMI in 2007 had significantly less annual income per capita and located further to the nearest clinic. The non-participating households on average had more children family members (under 16 years old) and less older members (60 years old and above) than participating households. The mixed-effects analysis results show that the probability of having catastrophic health expenditure reduced by 34.2% point when having NRCMI. This result is consistent and robust when dividing the entire analytical sample into subgroups and adopting different thresholds of catastrophic health expenditure.
Conclusions: The results suggest that NRCMI did help to reduce the probability of experiencing CHE, although the magnitude of the effect was limited. To eradicate health payment-induced poverty, China has a long way to go, and it is far from enough to rely on the current NRCMI system only. More specifically, findings of this paper point out that NRCMI did not significantly lower the probability of having CHE among participants in west China and older population. It indicates that rural residents in regions where the economic development is less advantaged are less likely to be protected by NRCMI. Similarly, this paper did not find the evidence that NRCMI preferably reduced the probability of having CHE among the lowest income quantile families more than other income groups. These groups of the population are more likely to be trapped by health payment-induced poverty and have difficulties in making breakthroughs. Policymakers should consider providing additional protections to reduce their healthcare costs or enhancing their affordability by increasing their household subsidies.