Võrdle meetodeid

	Akna andmete ümbrikmeetod (Window Data Envelopment Analysis)	Malmquisti tootlikkuse indeks
Valdkond	Efektiivsusanalüüs	Efektiivsusanalüüs
Perekond	Regression model	Regression model
Tekkeaasta	1984	1994
Looja	Charnes, Clark, Cooper & Golany	Färe, Grosskopf, Norris & Zhang
Tüüp	Non-parametric panel efficiency model	Non-parametric productivity index
Algallikas	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.	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.
Rööpnimetused	Sliding-Window DEA, Temporal DEA, Rolling-Period DEA, Pencere VZA	MPI, Malmquist Index, Malmquist DEA Productivity Index, Malmquist Verimlilik Endeksi
Seotud	2	1
Kokkuvõte	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.	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).