Compara mètodes

	Índex de Productivitat Malmquist	Anàlisi d'Envolupant de Dades per Finestres
Camp	Anàlisi d'eficiència	Anàlisi d'eficiència
Família	Regression model	Regression model
Any d'origen	1994	1984
Autor original	Färe, Grosskopf, Norris & Zhang	Charnes, Clark, Cooper & Golany
Tipus	Non-parametric productivity index	Non-parametric panel efficiency model
Font seminal	Färe, 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.	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.
Àlies	MPI, Malmquist Index, Malmquist DEA Productivity Index, Malmquist Verimlilik Endeksi	Sliding-Window DEA, Temporal DEA, Rolling-Period DEA, Pencere VZA
Relacionats	1	2
Resum	The 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.