Table 2.

Impact of the NRCMS on medical expenditure (IV analysis)

	Two-part model
	Pr (OOP > 0)	Log of OOP if positive
Overall effects
NRCMS treatment effect	0.032 (0.081)	− 0.320 (0.277)
F statistics for weak identification test	413.315	323.614
N	3136	2389
Subgroup analyses by income
High income	0.036 (0.075)	0.071 (0.279)
N	916	715
Middle income	0.013 (0.092)	− 0.134 (0.505)
N	1011	768
Low income	0.030 (0.131)	− 0.904** (0.391)
N	1209	906

Notes: Results from LPM models on the probability of incurring any positive OOP payments and ordinary least square (OLS) models on the log transformed expenditure outcomes controlling for the province and year dummies. Robust standard errors clustered at county level in brackets.

Other independent variables include age, gender, household size, marital status, ethnicity, eastern region, central region, household income, asset index, education level, occupation, number of major diseases, severity of illness in the last month, health risk variables and urbanicity index at community level.

Income quintile groups are computed on the basis of the total equalised disposable income attributed to each member of the household. We divide the sample population into three groups equally represented by 33.33% of the total population each, with two quintile cut-off points.

^**Indicates statistical significant at the 5% level.