Dr. Octasiano M. Valerio Mendoza presented the second research output from the CHINEQUALJUSTICE project at the Chinese Economists Society (CES) Annual Conference. https://chinequaljustice.iqs.edu/ This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 838534.

1. Measuring the Provincial Supply
of Higher Education Institutions
in China
Octasiano M. VALERIO MENDOZA
octasiano.valerio@iqs.url.edu
Mihály T. BORSI
Flavio COMIM
The Chinese Economists Society 2021 Annual Conference
June 18-20, 2021

2. Outline
I. Introduction
II. Objectives
III. Data
IV. Methodology
V. Results
VI. Conclusions
2

3. 3
Environmental Protection
Education and skills development
Reducing Inequality was placed as a top policy priority.
Middle-
income
High-
income

4. Education Development
4
Household
Registration System
(Hukou)
National College
Entrance Exam
(Gaokao)
Cultural Revolution
(1966-1976)
One-child Policy
(1979)
Nine-year compulsory
education (1986)
Secondary and
Vocational School
Expansion
(1980s-1990s)
211 and 985 Projects
(1995, 1998)
Higher Education
Expansion (1999~ )
Free Compulsory
Education Law (2006)
Central and Western
Higher Education
Revitalization Plan
(2016)
High School Education
Popularization Plan
(2017)
China Education
Modernization 2035
Plan
(2018)

5. China Modernization Plan 2035-2049
Consumption led-growth
• Strong middle class
• Dominant service sector (70-
80%)
• Increase in Education and Skills
Middle-Income Trap
• Declining demographic dividend
(Three-child policy)
• Increase in innovation and
productivity
• Human Capital
5
(Wang, Li, Abbey, & Rozelle, 2018; Khor, et al 2016; Zhang H. , 2014;
Zhang, Yi, Luo, Liu, & Rozelle, 2013; Cai, 2012; Knight, Li, & Deng,
2009; Glauben, Herzfeld, Rozelle, & Wang, 2012).

6. Higher Education Expansion
Higher education institutions (HEIs) increased from 1,208 to 2,956 in
1999 and 2019, respectively.
Undergraduate universities (104.36%)
Vocational colleges (242.89%)
Tertiary gross enrollment rates increased to 45.7%. (Doubling in a
decade).
Acceptance rates to 75%.
6

7. Human Capital in China remains low compared to
high income countries
8
0
10
20
30
40
50
60
Share of labor force with tertiary attainment
China USA Germany S. Korea Australia Japan
49.1
88.2
70.2
94.3
113.1
63.2
0
20
40
60
80
100
120
Tertiary gross enrollment rate
China USA Germany S. Korea Australia Japan
2631
4131
399 430
135
780
0
1000
2000
3000
4000
5000
Numer of Higher Education Institutions
China USA Germany S. Korea Australia Japan
1.9
12.7
4.8
8.4
5.5
6.2
0
2
4
6
8
10
12
14
HEI per million
China USA Germany S. Korea Australia Japan

8. Human Capital in China remains low compared to
high income countries
9
0
10
20
30
40
50
60
Share of labor force with tertiary attainment
China USA Germany S. Korea Australia Japan
49.1
88.2
70.2
94.3
113.1
63.2
0
20
40
60
80
100
120
Tertiary gross enrollment rate
China USA Germany S. Korea Australia Japan
2631
4131
399 430
135
780
0
1000
2000
3000
4000
5000
Numer of Higher Education Institutions
China USA Germany S. Korea Australia Japan
1.9
12.7
4.8
8.4
5.5
6.2
0
2
4
6
8
10
12
14
HEI per million
China USA Germany S. Korea Australia Japan
Outcomes Access Supply

9. Research Objective
Measure the quantity and quality of HE for 31 Chinese provinces.
10
Data
1. Lists of National Colleges and Universities (Ministry of Education, 2001-2017).
2. Best Chinese Universities Ranking (BCUR) of the Shanghai Jiao Tong Academic Ranking
of World Universities (ARWU)
3. China Statistics Yearbooks (2001-2017)

10. List of National Colleges and Universities
(MOE; 2001-2017).
Lists
oUndergraduate Universities
oVocational Colleges
oPrivate Colleges
Formats
oExcel (2011-2017).
oWord or Text Files (2001; 2003-2010).
oPictures (2002).
11

11. Excel Lists
12

12. Text Lists
13

13. 2002 List
14

14. Compiled Dataset
Beijing Tianjin Hebei Shanxi
Inner
Mongolia
Liaoning Jilin Heilongjiang Shanghai Jiangsu Zhejiang Anhui Fujian Jiangxi Shandong Henan
2001 59 29 51 26 18 64 35 41 37 70 35 41 32 31 56 52
2002 62 35 67 33 21 66 35 48 45 78 58 55 30 31 64 65
2003 69 37 73 44 22 70 40 53 56 93 62 62 39 48 76 65
2004 75 40 84 48 27 71 40 55 57 105 64 73 51 55 85 71
2005 78 41 87 59 32 71 44 61 59 111 67 81 50 66 98 83
2006 80 45 85 56 33 76 44 63 60 114 67 81 56 66 104 83
2007 80 46 88 59 37 79 44 68 60 118 73 89 72 66 110 82
2008 80 44 86 61 37 79 43 69 61 120 74 92 72 69 114 84
2009 82 45 91 63 39 86 45 69 61 122 77 95 75 72 116 89
2010 83 45 93 65 42 91 46 70 62 124 79 99 74 72 120 97
2011 82 45 94 66 45 94 48 73 62 126 80 104 76 73 126 108
2012 83 45 95 67 46 94 48 77 63 128 80 107 77 75 124 112
2013 84 45 101 70 47 102 51 78 65 130 80 106 78 79 127 119
2014 84 45 101 71 48 104 52 78 66 134 82 107 79 82 130 121
2015 91 45 118 79 53 116 58 81 67 162 105 119 88 97 143 129
2016 91 55 120 80 53 116 60 82 64 166 107 119 88 98 144 129
2017 92 57 121 80 53 115 62 81 64 167 107 119 89 100 145 134
15

15. Methodology
16
Chinese Higher Education Density Index (CHEDI):
𝐶𝐻𝐸𝐷𝐼𝑖,𝑡 =
𝐻𝐸𝐼𝑖,𝑡
𝐻𝐸𝐼𝑡𝑜𝑡𝑎𝑙,𝑡
𝑃𝑂𝑃𝑖,𝑡
𝑃𝑂𝑃𝑡𝑜𝑡𝑎𝑙,𝑡
(1)
𝐻𝐸𝐼𝑖,𝑡: number of higher education institutions in province i and period t
𝑃𝑂𝑃𝑖,𝑡: population of province i in period t
𝐶𝐻𝐸𝐷𝐼𝑖,𝑡 > 1 : 𝑜𝑣𝑒𝑟𝑝𝑟𝑜𝑝𝑜𝑟𝑡𝑖𝑜𝑛𝑎𝑡𝑒 𝑠𝑢𝑝𝑝𝑙𝑦
𝐶𝐻𝐸𝐷𝐼𝑖,𝑡 < 1 ∶ 𝑢𝑛𝑑𝑒𝑟𝑠𝑢𝑝𝑝𝑙𝑦

16. Best Chinese
Universities Ranking
(BCUR)
17
• Overall scores obtained by each
higher education institution
• Available for 2013, 2015, 2016,
2017

17. Methodology
18
Chinese Higher Education Quality Index (CHEQI):
𝐶𝐻𝐸𝑄𝐼𝑖,𝑡 =
𝑗=1
𝐽
𝑆𝐶𝑂𝑅𝐸𝑗 𝑖 ,𝑡
𝑃𝑂𝑃𝑖,𝑡
(2)
𝑆𝐶𝑂𝑅𝐸𝑗 𝑖 ,𝑡: score obtained by university j in province i at period t in the Best
Chinese Universities Ranking of the ARWU (BCUR)
𝑃𝑂𝑃𝑖,𝑡: population of province i in period t

18. Methodology
19

19. Methodology
20
Chinese Higher Education Index (CHEI):
𝐶𝐻𝐸𝐼𝑖,𝑡 =
𝐶𝐻𝐸𝐷𝐼𝑖,𝑡+𝐶𝐻𝐸𝑄𝐼𝑖,𝑡
2
(3)
𝐶𝐻𝐸𝐷𝐼𝑖,𝑡 𝑎𝑛𝑑 𝐶𝐻𝐸𝑄𝐼𝑖,𝑡 are normalized to take values between 0 and 1
𝐶𝐻𝐸𝐼𝑖,𝑡 = 𝐶𝐻𝐸𝐷𝐼𝑖,𝑡 ∙ 𝐶𝐻𝐸𝑄𝐼𝑖,𝑡 (4)

20. Methodology: Partial ranking (POSET) Analysis
21
𝑃 = (𝑋, ≤)
X includes i= 1,2,…,31 elements 𝑥𝑖 where each element represents a
vector of the quantity and quality dimensions
𝑥𝑖
= 𝑥𝐶𝐻𝐸𝐷𝐼
𝑖
, 𝑥𝐶𝐻𝐸𝑄𝐼
𝑖
is a vector that considers both the CHEDI and CHEQI of province i.
𝑥𝑖 ≤ 𝑥𝑗 𝑜𝑟𝑥𝑗 ≤ 𝑥𝑖

21. 22

22. 23

23. 24

24. 25

25. 26

26. 27

27. 28

28. 29

29. 30

30. 31

31. 32
Partial Ranking
POSET Analysis

32. Conclusions
I. Novel empirical framework to analyze the supply of higher education
A unique dataset compiled for Chinese higher education institutions
o Four-year, Two-year, Private
o Scores of the BCUR
Aggregative and non-aggregative approach
II. The large-scale expansion of higher education institutions since 1999
Supply of HE is disproportionately greater in 3 of the provincial-level municipalities
Supply is relatively low in provinces with large populations, areas bordering other
countries, and regions with large shares of ethnic minorities.
33

33. III. Most areas still managed to improve their densities but many of
the gains were due to the rise of vocational colleges rather than
undergraduate universities.
34
Country Year HEIs 4 yr 2 yr
China 2017 2631 1243 1388
USA 2017-18 4131 2828 1485
53%
36%
Advanced
Economy
Automation
& AI
Higher
Skilled
Labor
Force

34. Implications
35
Middle-
income
High-
income
0
10
20
30
40
50
60
Share of labor force with tertiary attainment
China USA Germany S. Korea Australia Japan
49.1
88.2
70.2
94.3
113.1
63.2
0
20
40
60
80
100
120
Tertiary gross enrollment rate
China USA Germany S. Korea Australia Japan
1.9
12.7
4.8
8.4
5.5
6.2
0
2
4
6
8
10
12
14
HEI per million
China USA Germany S. Korea Australia Japan

35. 37

36. 38

37. Thank you for your attention!
Questions and comments are welcome.
39
octasiano.valerio@iqs.url.edu

38. Thank you for your attention!
Questions and comments are welcome.
40
octasiano.valerio@iqs.url.edu