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Malmquistův index produktivity×Analýza obálky dat s posuvným oknem×
OborAnalýza efektivnostiAnalýza efektivnosti
RodinaRegression modelRegression model
Rok vzniku19941984
TvůrceFäre, Grosskopf, Norris & ZhangCharnes, Clark, Cooper & Golany
TypNon-parametric productivity indexNon-parametric panel efficiency model
Původní zdrojFäre, R., Grosskopf, S., Norris, M., & Zhang, Z. (1994). Productivity growth, technical progress, and efficiency change in industrialized countries. American Economic Review, 84(1), 66–83. link ↗Charnes, A., Clark, C. T., Cooper, W. W., & Golany, B. (1984). A developmental study of data envelopment analysis in measuring the efficiency of maintenance units in the U.S. Air Forces. Annals of Operations Research, 2(1), 95–112. DOI ↗
Další názvyMPI, Malmquist Index, Malmquist DEA Productivity Index, Malmquist Verimlilik EndeksiSliding-Window DEA, Temporal DEA, Rolling-Period DEA, Pencere VZA
Příbuzné12
ShrnutíThe Malmquist Productivity Index (MPI) is a non-parametric measure of total factor productivity (TFP) change over time. Formally grounded in distance functions by Caves, Christensen, and Diewert (1982) and operationalized using Data Envelopment Analysis by Färe, Grosskopf, Norris, and Zhang (1994), MPI decomposes productivity growth into two components: efficiency change (catching-up to the frontier) and technical change (shift of the frontier itself).Window Data Envelopment Analysis (Window DEA) is a non-parametric panel efficiency method that evaluates decision-making units (DMUs) over time by embedding each DMU's observations across a rolling temporal window into a single cross-sectional DEA problem. Introduced by Charnes, Clark, Cooper, and Golany in 1984, it enables longitudinal efficiency tracking without requiring a full panel, increasing discriminatory power by pooling observations across consecutive periods.
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ScholarGatePorovnat metody: Malmquist Productivity Index · Window DEA. Získáno 2026-06-18 z https://scholargate.app/cs/compare