Table 6.

Heterogeneity analysis of the effect of boarding on students’ mental health.

$\mathit{D}\mathit{e}\mathit{p}\mathit{e}\mathit{n}\mathit{d}\mathit{e}\mathit{n}\mathit{t} \mathit{v}\mathit{a}\mathit{r}\mathit{i}\mathit{a}\mathit{b}\mathit{l}\mathit{e}\mathit{:} \Delta \mathit{M}\mathit{H}{\mathit{T}}_{\mathit{i}\mathit{s}}=\mathit{M}\mathit{H}{\mathit{T}}_{\mathit{i}\mathit{s},\mathit{e}\mathit{n}\mathit{d}\mathit{l}\mathit{i}\mathit{n}\mathit{e}} - \mathit{M}\mathit{H}{\mathit{T}}_{\mathit{i}\mathit{s},\mathit{b}\mathit{a}\mathit{s}\mathit{e}\mathit{l}\mathit{i}\mathit{n}\mathit{e}}$	(1)	(2)	(3)
	ATT a	SE	t-Value
(1) Differences between students aged 10 or more and students aged 10 or less	0.16	(0.11)	1.49
(2) Differences between male and female students	0.01	(0.08)	0.07
(3) Differences between grade 4 and grade 5 students	−0.20 **	(0.08)	−2.60
(4) Differences between myopic students and non-myopic students	0.11	(0.12)	0.91
(5) Differences between students whose distance from their school to their county town is greater than or equal to 32 km and students whose distance is less than 32 km b	−0.12	(0.08)	−1.62
(6) Differences in student’s father educational level (whether above high school)	0.01	(0.12)	0.06
(7) Differences in student’s mother educational level (whether above high school)	−0.05	(0.11)	−0.43
(8) The differences between students with parents migrating for work and students with one parent not migrating for work	0.28 **	(0.14)	2.04
(9) The difference between the students whose family assets are in the top 50% of the broader population and the students in the bottom 50%	0.06	(0.06)	0.88
N	16,685	16,685	16,685

Note: *** p < 0.01, ** p < 0.05, * p < 0.1. Standard errors were calibrated by using the bootstrap method (100 times). The table shows the regression results of the heterogeneity analysis for different groups. Each regression equation controlled the personal characteristics of the students (including gender, age, grade, myopia, standardized mathematics scores of the students at baseline, and the distance from the school to the county) and family background (including the natural logarithm of family finance, the educational level of parents, and whether parents migrate for work). ^a ATT, average treatment effect for the treatment, indicating the real effect of boarding on students’ mental health. ^b Fifty percent of the students in the sample had a distance of more than 32 km from their school to the county, while the other 50% had a distance of less than 32 km from their school to the county. Data source: Authors’ survey.