Open Access

Higher education innovation and reform model based on hierarchical probit

Jingying Chang

Jingying Chang

Hennan Quality InstitutePingdingshan, China
Search for this author on
Sciendo|Google Scholar
Chang, Jingying
, 
Weibin Lan

Weibin Lan

Hennan Quality InstitutePingdingshan, China
Search for this author on
Sciendo|Google Scholar
Lan, Weibin
 and 
Wenhao Lan

Wenhao Lan

Institute of Computing Technology Chinese Academy of SciencesBeijing, China
Search for this author on
Sciendo|Google Scholar
Lan, Wenhao
  
Dec 30, 2021
Higher education innovation and reform model based on hierarchical probit's Cover Image
About this article
Previous Article
Next Article
Cite
Download Cover
Published Online: Dec 30, 2021
Page range: 175 - 182
Received: Jun 17, 2021
Accepted: Sep 24, 2021
DOI: https://doi.org/10.2478/amns.2021.2.00154
Keywords
© 2021 Jingying Chang et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.

Fig. 1

Comparison of the impact of academic qualifications on happiness scores
Comparison of the impact of academic qualifications on happiness scores

Semiparametric ordered probit model estimation results

Full sample (1) Full sample (2) Town (3) Rural (4)
Edu 0.102*** (0.013) 0.119*** (0.016) 0.079*** (0.016) 0.145*** (0.021)
Urban 0.214*** (0.028) 0.234*** (0.030)
Age −0.055*** (0.005) −0.055*** (0.005) −0.059*** (0.007) −0.052*** (0.006)
Age2 0.001*** (0.000) 0.001*** (0.000) 0.001*** (0.000) 0.001*** (0.000)
Edu2_urban −0.105* (0.044)
Control Var Control Control Control Control
Log likelihood −22717.567 −22714.489 −9861.211 −12831.042
LR 32.666 32.193 17.315 34.220
p 0.000 0.000 0.000 0.000
Standard deviation 1.465 1.465 1.476 1.521

Descriptive statistics of each variable

Variable Average value Standard deviation Minimum Max
Happiness 2.523 0.621 1 3
Age 47.832 15.78 16 99
Gender 0.489 0.5 0 1
Edu 2.5 1.304 1 8
Marriage 0.837 0.369 0 1
Health 3.015 1.247 1 5
Job 0.739 0.439 0 1
Status 2.939 0.999 1 5
Health_change 3.44 1.226 1 5
Inc 8799.7 19125.7 0 442,000

Introducing cross-terms to determine the impact path results

(5) (6) (7) (8) (9)
Edu2 0.162*** (0.031) 0.117** (0.036) −0.005 (0.036) −0.016 (0.036) −0.078* (0.039)
Urban 0.249*** (0.029) 0.245*** (0.029) 0.219*** (0.028) 0.223*** (0.028) 0.224*** (0.028)
Age −0.055*** (0.005) −0.055*** (0.005) −0.055*** (0.005) −0.053*** (0.004) −0.055*** (0.005)
Age2 0.001*** (0.000) 0.001*** (0.000) 0.001*** (0.000) 0.001*** (0.000) 0.001*** (0.000)
Control Var Control Control Control Control Control
edu_linc 0.004* (0.002)
Edu health 0.026*** (0.004)
Edu job 0.107*** (0.015)
Edu status 0.039*** (0.005)
Log likelihood −22755.746 −22753.389 −22731.603 −22724.076 −22715.474
LR 35.960 33.352 38.652 350545 28.105
P 0.000 0.000 0.000 0.000 0.000
Standard deviation 1.453 1.448 1.447 1.451 1.442
Language:
English
Publication timeframe:
1 times per year
Journal Subjects:
Life Sciences, Life Sciences, other, Mathematics, Applied Mathematics, General Mathematics, Physics, Physics, other
Journal RSS Feed