Quadratic Data Envelopment Analysis

Timo Kuosmanen, Thierry Post

Research output: Contribution to journalArticleScientificpeer-review


Data Envelopment Analysis (DEA) offers a piece-wise linear approximation of the production frontier. The approximation tends to be poor if the true frontier is not concave, eg in case of economies of scale or of specialisation. To improve the flexibility of the DEA frontier and to gain in empirical fit, we propose to extend DEA towards a more general piece-wise quadratic approximation, called Quadratic Data Envelopment Analysis (QDEA). We show that QDEA gives statistically consistent estimates for all production frontiers with bounded Hessian eigenvalues. Our Monte-Carlo simulations suggest that QDEA can substantially improve efficiency estimation in finite samples relative to standard DEA models.
Original languageEnglish
Pages (from-to)1204-1214
JournalJournal of the Operational Research Society
Issue number11
Publication statusPublished - 2002
MoE publication typeA1 Journal article-refereed


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