Productivity Measurement with Data Envelopment Analysis and Stochastic Frontier Analysis: A Review Article on Measurement of Productivity and Efficiency: Theory and Practice
Cite this article as:
Balk, Bert. 2021. “Productivity Measurement with Data Envelopment Analysis and Stochastic Frontier Analysis: A Review Article on Measurement of Productivity and Efficiency: Theory and Practice.” International Productivity Monitor, No. 40 (Spring 2021): 134–139. https://www.csls.ca/ipm-archive/ipm-issue-40/productivity-measurement-with-data-envelopment-analysis-and-stochastic-frontier-analysis-a-review-article-on-measurement-of-productivity-and-efficiency-theory-and-practice/
Abstract
Résumé
This review article evaluates Measurement of Productivity and Efficiency: Theory and Practice by Robin C. Sickles and Valentin Zelenyuk (Cambridge University Press, 2019, 600 pages). The book covers the full range of production theory and productivity measurement approaches — including DEA (Data Envelopment Analysis) and SFA (Stochastic Frontier Analysis) — and their empirical applications. The reviewer praises the comprehensiveness but notes that the dominant focus on non-parametric and parametric frontier methods contrasts with the index number approach preferred by national statistical offices, pointing to remaining gaps between academic and official productivity measurement practice.
Cet article de recension évalue l’ouvrage Measurement of Productivity and Efficiency: Theory and Practice de Robin Sickles et Valentin Zelenyuk (Cambridge University Press, 2019, 600 pages). L’ouvrage couvre l’ensemble de la théorie de la production et des approches de mesure de la productivité — y compris l’AED (analyse par enveloppement des données) et l’AFStochastique — et leurs applications empiriques. Le recenceur salue l’exhaustivité mais note que la focalisation dominante sur les méthodes de frontière non paramétriques et paramétriques contraste avec l’approche par indices de prix préférée des offices statistiques nationaux, soulignant les lacunes persistantes entre la pratique académique et officielle de la mesure de la productivité.