Composite indicators are becoming increasingly influential tools of environmental assessment and advocacy. Nonetheless, their use is controversial as they often rely on ad-hoc and theoretically problematic assumptions regarding normalization, aggregation, and weighting. Nonparametric data envelopment analysis (DEA) methods, originating in the production-economics literature, have been proposed as a means of addressing these concerns. These methods dispense with contentious normalization and weighting techniques by focusing on a measure of best-case relative performance. Recently, the standard DEA model for composite indicators was extended to account for worst-case analysis by Zhou et al. (Ecol Econ 62(2):291–297, 2007) [hereafter, ZAP]. In this note we argue that, while valid and interesting in its own right, the measure adopted by ZAP may not capture, in a mathematical as well as practical sense, the notion of worst-case relative performance. By contrast, we focus on the strict worst-case analogue of standard DEA for composite indicators and show how it leads to tractable optimization problems. Finally, we compare the two methodologies using data from ZAP’s Sustainable Energy Index case study, demonstrating that they occasionally lead to divergent results.

Athanasoglou, S. (2016). Revisiting Worst-Case DEA for Composite Indicators. SOCIAL INDICATORS RESEARCH, 128(3), 1259-1272 [10.1007/s11205-015-1078-3].

Revisiting Worst-Case DEA for Composite Indicators

Athanasoglou, S
2016

Abstract

Composite indicators are becoming increasingly influential tools of environmental assessment and advocacy. Nonetheless, their use is controversial as they often rely on ad-hoc and theoretically problematic assumptions regarding normalization, aggregation, and weighting. Nonparametric data envelopment analysis (DEA) methods, originating in the production-economics literature, have been proposed as a means of addressing these concerns. These methods dispense with contentious normalization and weighting techniques by focusing on a measure of best-case relative performance. Recently, the standard DEA model for composite indicators was extended to account for worst-case analysis by Zhou et al. (Ecol Econ 62(2):291–297, 2007) [hereafter, ZAP]. In this note we argue that, while valid and interesting in its own right, the measure adopted by ZAP may not capture, in a mathematical as well as practical sense, the notion of worst-case relative performance. By contrast, we focus on the strict worst-case analogue of standard DEA for composite indicators and show how it leads to tractable optimization problems. Finally, we compare the two methodologies using data from ZAP’s Sustainable Energy Index case study, demonstrating that they occasionally lead to divergent results.
Articolo in rivista - Articolo scientifico
Composite indicator; Convex optimization; DEA; Sustainability index; Worst-case;
Composite indicator; Convex optimization; DEA; Sustainability index; Worst-case; Developmental and Educational Psychology; Arts and Humanities (miscellaneous); Sociology and Political Science; Social Sciences (all)
English
2016
128
3
1259
1272
reserved
Athanasoglou, S. (2016). Revisiting Worst-Case DEA for Composite Indicators. SOCIAL INDICATORS RESEARCH, 128(3), 1259-1272 [10.1007/s11205-015-1078-3].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/139984
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