Evaluating Educational Performance of OECD Countries with Common-Weight DEA-Based Models

Ucar E., KARSAK E. E.

Journal of the Knowledge Economy, 2023 (SSCI) identifier

  • Publication Type: Article / Article
  • Publication Date: 2023
  • Doi Number: 10.1007/s13132-023-01619-9
  • Journal Name: Journal of the Knowledge Economy
  • Journal Indexes: Social Sciences Citation Index (SSCI), Scopus, IBZ Online, ABI/INFORM, EconLit
  • Keywords: Common-weight DEA-based approach, Data envelopment analysis, Education efficiency, Performance assessment, PISA data, Rank reversal
  • Galatasaray University Affiliated: Yes


To establish more efficient and equitable education systems for students, increasing importance has been attached to the efficient usage of educational resources and the evaluation of students’ success in education. Until recently, studies that focus on efficiency assessment in education have generally employed conventional data envelopment analysis (DEA) models that enable each country to specify its most favorable set of factor weights, and thus may yield an impractical weighting scheme as well as poor discriminatory characteristics for evaluation purposes. This study assesses education efficiency of OECD countries through implementing common-weight DEA-based models and using the PISA 2018 database. The results obtained by conventional DEA and common-weight DEA-based models are comparatively evaluated with regard to rankings as well as dispersions of input and output weights. Although conventional DEA determines ten countries as efficient, most of the common-weight DEA-based models employed herein yield full ranking. In vast majority of these approaches, Estonia and Finland are found to be the best performing countries. Rank reversal phenomenon in these models is also addressed and a weighted aggregate ranking index incorporating the rank reversal issue is developed.