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Public and Private School Grade Inflation Patterns in Secondary Education

  • Pedro Luís Silva ORCID logo EMAIL logo , Stephen L. DesJardins , Ricardo Biscaia ORCID logo , Carla Sá ORCID logo und Pedro N. Teixeira ORCID logo
Veröffentlicht/Copyright: 16. April 2025
The B.E. Journal of Economic Analysis & Policy
Aus der Zeitschrift The B.E. Journal of Economic Analysis & Policy Band 25 Heft 2

Abstract

We examine the extent of grade inflation in courses taken during high school and how such differences vary across student and school characteristics. Using administrative data, we assess grade inflation in Portuguese high schools over a decade. We propose a relative measure of grade inflation, comparing students’ high school grades to their national exam ranks. Examining various school types, we find that private schools tend to inflate grades more than their public school peers, particularly at the top of the ability distribution. A regional disaggregation indicates that the northern districts exhibit higher probabilities of grade inflation.

Keywords: grade inflation; grading standards; high school grading; postsecondary access equity; upper secondary education
JEL Classifications: I21; I23; I24
Corresponding author: Pedro Luís Silva, Centre for Research in Higher Education Policies (CIPES), Rua 1O Dezembro 399, 4450-227 Matosinhos, Portugal; Department of Applied Economics, Universitat Autònoma de Barcelona, Barcelona, Spain; and Institute of Labor Economics (IZA), Bonn, Germany, E-mail:

Funding source: Fundação para a Ciência e a Tecnologia

Award Identifier / Grant number: 10.54499/PTDC/CED-EDG/5530/2020

Award Identifier / Grant number: 10.54499/UIDB/03182/2020

Award Identifier / Grant number: 10.54499/UIDP/00757/2020

Award Identifier / Grant number: 10.54499/2023.08911.CEECIND/CP2880/CT0001

  1. Research funding: This work was supported by Fundação para a Ciência e a Tecnologia under the grant numbers 10.54499/PTDC/CED-EDG/5530/2020, 10.54499/UIDB/03182/2020, 10.54499/UIDP/00757/2020 and 10.54499/2023.08911.CEECIND/CP2880/CT0001.

  2. Disclosure statement: FCT – Foundation for Science and Technology (Portugal) provided funding for this research under the projects doi https://doi.org/10.54499/PTDC/CED-EDG/5530/2020, doi https://doi.org/10.54499/UIDP/00757/2020, doi https://doi.org/10.54499/UIDB/03182/2020 and doi https://doi.org/10.54499/2023.08911.CEECIND/CP2880/CT0001. Any errors or omissions are the authors’ responsibility. The views contained herein are not necessarily those of the funders.

Appendix:

see Tables A1–A5 and Figure A1.

Table A1:

Number of exams per subject.

2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Total %
Portuguese 47,607 49,283 50,104 49,477 50,322 51,320 53,375 55,806 54,587 54,743 516,624 0.25
Mathematics A 27,298 27,888 31,127 31,395 31,793 33,190 32,466 34,406 32,202 33,013 314,778 0.15
Physics and Chemistry 26,752 27,990 29,697 30,416 29,675 27,921 28,142 27,587 26,848 26,296 281,324 0.14
Biology and Geology 28,235 28,074 28,870 29,502 29,686 28,132 27,989 26,949 25,726 25,732 278,895 0.13
Geography 14,265 13,758 14,354 15,021 15,796 17,045 18,182 17,955 18,589 19,132 164,097 0.08
History 10,556 10,488 10,492 11,468 11,653 12,430 14,241 15,397 15,318 16,028 128,071 0.06
Philosophy 0 0 3,960 5,490 7,918 10,273 11,285 11,109 11,435 12,485 73,955 0.04
Applied Mathematics 7,013 6,305 6,437 6,566 6,634 7,106 7,569 7,727 8,172 8,063 71,592 0.03
Economics 4,563 4,376 4,470 5,038 5,626 5,838 6,647 6,714 6,920 7,335 57,527 0.03
Geometry 6,017 5,630 5,847 5,608 5,106 5,283 5,378 5,381 5,529 6,058 55,837 0.03
Drawing 4,172 4,205 3,757 3,947 3,770 3,388 3,607 3,533 3,389 3,273 37,041 0.02
History of Culture and Arts 2,360 1822 2,244 2,325 2,196 2,604 2,573 2,606 2,798 2,666 24,194 0.01
Spanish (level 1) 1936 2038 2,286 2,163 1,468 1,646 1,678 1761 1873 2,101 18,950 0.01
Portuguese Literature 1749 1,595 1750 1,695 1,683 1779 1918 1967 1,684 1,488 17,308 0.01
Mathematics B 1723 1,698 1,677 1,656 1,209 978 866 759 477 540 11,583 0.01
French 1,412 1,170 1,047 996 878 1,020 980 997 1,014 904 10,418 0.01
German (level 1) 688 528 519 610 626 821 936 898 954 770 7,350 0.00
History B 700 580 682 712 630 641 706 796 717 686 6,850 0.00
Total 187,046 187,428 199,320 204,085 206,669 211,415 218,538 222,348 218,232 221,313 2,076,394 100

  1. For the rank within the subject to be meaningful, we only consider subjects with more than 130 exams per year.

Table A2:

Ordered logit regression results (average marginal effects).

Variables Model (1) Model (2) Model (3) Model (4) Model (5)
Relative Relative Relative Relative Relative Relative Relative Relative Relative Relative
Inflation Deflation Inflation Deflation Inflation Deflation Inflation Deflation Inflation Deflation
HS type
 Private 0.0857*** −0.0858*** 0.1558*** −0.1424*** 0.1472*** −0.1370*** 0.1160*** −0.1113*** 0.0978*** −0.0972***
(0.0012) (0.0012) (0.0014) (0.0010) (0.0014) (0.0010) (0.0014) (0.0011) (0.0016) (0.0013)
 Private with association −0.0273*** 0.0273*** −0.0014 −0.0050*** −0.0076*** 0.0007 −0.0307*** 0.0246*** −0.0088*** 0.0016
(0.0014) (0.0014) (0.0014) (0.0014) (0.0013) (0.0013) (0.0013) (0.0014) (0.0016) (0.0016)
 TEIP 0.0210*** −0.0211*** 0.0028** −0.0003 0.0034*** −0.0008 0.0061*** −0.0035*** −0.0021 0.0030*
(0.0013) (0.0013) (0.0012) (0.0013) (0.0012) (0.0013) (0.0012) (0.0013) (0.0015) (0.0016)
Female 0.0686*** −0.0688*** 0.0742*** −0.0744*** 0.0738*** −0.0742***
(0.0006) (0.0006) (0.0006) (0.0006) (0.0006) (0.0006)
Age −0.0843*** 0.0846*** −0.0781*** 0.0784*** −0.0755*** 0.0758***
(0.0005) (0.0005) (0.0005) (0.0005) (0.0005) (0.0005)
% Of science students 0.1864*** −0.1871*** 0.1173*** −0.1179***
(0.0025) (0.0025) (0.0031) (0.0031)
Observations 2,076,394 2,076,394 2,076,394 2,076,394 2,076,394
Pseudo R2 0.0014 0.050 0.0622 0.066 0.0751
Exam subject FE Yes Yes Yes Yes Yes
Year FE Yes Yes Yes Yes Yes
HS type * exam grade Yes Yes Yes Yes
HS course FE Yes Yes
Municipality FE Yes

  1. Source: Authors’ calculations. Note: Robust standard errors in parentheses ***p<0.01, **p<0.05, *p<0.1. Estimated marginal effects for the “No Grade Inflation” probability are not reported.

Table A3:

Number of exams per subject and high school type.

High school type (%) Total
Public Private Private w/Association TEIP
Portuguese 0.82 0.07 0.05 0.06 516,624
Mathematics A 0.79 0.10 0.06 0.05 314,778
Physics and Chemistry 0.80 0.08 0.06 0.06 281,324
Biology and Geology 0.81 0.08 0.06 0.06 278,895
Geography 0.85 0.05 0.04 0.07 164,097
History 0.85 0.03 0.04 0.08 128,071
Philosophy 0.82 0.06 0.04 0.07 73,955
Applied Mathematics 0.86 0.03 0.04 0.07 71,592
Economics 0.80 0.12 0.04 0.05 57,527
Geometry 0.83 0.09 0.04 0.05 55,837
Drawing 0.87 0.04 0.04 0.05 37,041
History of Culture and Arts 0.88 0.03 0.03 0.05 24,194
Spanish (level 1) 0.88 0.02 0.02 0.08 18,950
Portuguese Literature 0.83 0.02 0.04 0.11 17,308
Mathematics B 0.87 0.05 0.05 0.03 11,583
French 0.88 0.03 0.04 0.05 10,418
German (level 1) 0.87 0.02 0.03 0.08 7,350
History B 0.69 0.20 0.07 0.03 6,850
Total 0.82 0.07 0.05 0.06 2,076,394
Table A4:

2018 higher education undergraduate programmes, that have the same exam(s) in all combinations of exams allowed to access their programme.

Mandatory exams in all No. HE No
combinations allowed programmes programme-
0 1 2 3 combinations
Selective 0 578 278 169 0 1,025 616
Programmes 1 7 9 14 9 39 61
Total 585 287 183 9 1,064

  1. Source: Application data for public higher education (Silva 2024). Notes: This analysis includes all 1,064 undergraduate programs (degree-institution pairs) in public higher education in 2018. A program is considered selective if the minimum application score (the score of the last student admitted in the first round) is 170 out of 200. Of the 1,064 programs, 39 were classified as selective. Among these, 7 programs had no mandatory exams in the allowed exam combinations for admission. In 9 of the 39 selective programs, one exam was mandatory across all allowed combinations; in 14 programs, two exams were mandatory in all combinations; and in 9 programs, three exams were mandatory in all combinations. This includes the 9 medical degree programs that required Mathematics A, Physics and Chemistry, and Biology and Geology as mandatory exams for admission.

Table A5:

Distribution of mandatory exams to access higher education programmes in 2018.

No. Programme-Combinations for
which the exam is mandatory
Exam subject Selective (%) Non-selective (%) N
Biology and Geology 0.19 0.20 138
Drawing 0.02 0.01 5
Physics and Chemistry 0.36 0.25 178
History 0.00 0.01 6
History of Cultures and Arts 0.00 0.00 2
English 0.00 0.00 2
N 64 616 680

  1. Source: Application data for public higher education (Silva 2024). Notes: Other subjects were also used for admission to higher education programs, but they were not mandatory. For example, in Program A (Economics at Institution A), students could apply with either the Mathematics A exam or a combination of Mathematics A and the Portuguese exam. In this case, Mathematics A is a mandatory exam. In contrast, Program B (Economics at Institution B) allows students to apply with either Mathematics A or a combination of the Economics and Portuguese exams, with no mandatory exam requirement, giving students the flexibility to choose from the available options. In this table, we rank the number of programs and the corresponding distribution where mandatory exams are required.

Figure A1: Internal score distribution by school type. Source: Authors’ calculations.
Figure A1:

Internal score distribution by school type. Source: Authors’ calculations.

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Received: 2024-04-15
Accepted: 2025-03-11
Published Online: 2025-04-16

© 2025 Walter de Gruyter GmbH, Berlin/Boston

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  12. Letter
  13. Parental Investments During Labor Shocks: Evidence from Vietnam’s Marine Disaster
https://doi.org/10.1515/bejeap-2024-0136
Schlagwörter für diesen Artikel
grade inflation; grading standards; high school grading; postsecondary access equity; upper secondary education

Artikel in diesem Heft

  1. Frontmatter
  2. Research Articles
  3. FRAND Licensing of Standard-Essential Patents: Comparing Realistic Ex-Ante and Ex-Post Contracts
  4. To Commit or Not to Commit in Product-Innovation Timing Games
  5. Coordinated Minimum Wage Policies: Impacts on EU-Level Income Inequality
  6. Regulatory Contestability and Cost Pass-Through
  7. Explaining the Economic Characteristics of Different International Peacekeeping Institutions
  8. Setting Reserve Prices in Repeated Procurement Auctions
  9. Public and Private School Grade Inflation Patterns in Secondary Education
  10. Estimating Labor Supply Elasticities in Korea: The Role of Limited Commitment Between Spouses
  11. Strategic Brand Proliferation: Monopoly versus Duopoly
  12. Letter
  13. Parental Investments During Labor Shocks: Evidence from Vietnam’s Marine Disaster
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Heruntergeladen am 22.10.2025 von https://www.degruyterbrill.com/document/doi/10.1515/bejeap-2024-0136/html
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