Geometric mean quantity index numbers with Benefit-of-the-Doubt weights

Geometric mean index numbers are a multiplicative aggregation of (price or quantity) ratios with their importance exponents/weights derived from one or more observed budget shares. In the specific context of composite indicator construction, we propose to use the budget shares as naturally generated by the linear Benefit-of-the-Doubt model. This approach is directly inspired by the literature on index number theory. Our basic model is easily extended to provide transitive composite indicator orderings in a multilateral setting. Also, a multi-factor decomposition is proposed to explain the intertemporal evolution of a single entity. We illustrate our results with social inclusion data for the EU-countries.

[1]  Ana S. Camanho,et al.  Benchmarking countries’ environmental performance , 2013, J. Oper. Res. Soc..

[2]  Sérgio P. Santos,et al.  Measuring active ageing: A Data Envelopment Analysis approach , 2016, Eur. J. Oper. Res..

[3]  Ali Emrouznejad,et al.  An aggregate measure of financial ratios using a multiplicative DEA model , 2010 .

[4]  Stéphane Blancard,et al.  A new sustainable human development indicator for small island developing states: A reappraisal from data envelopment analysis , 2013 .

[5]  Joe Zhu,et al.  Within-group common weights in DEA: An analysis of power plant efficiency , 2007, Eur. J. Oper. Res..

[6]  L. Cherchye,et al.  Legitimately Diverse, Yet Comparable: On Synthesizing Social Inclusion Performance in the EU , 2004 .

[7]  C. Lovell,et al.  One Market, One Number? A Composite Indicator Assessment of EU Internal Market Dynamics , 2005 .

[8]  K. Chin,et al.  Some alternative models for DEA cross-efficiency evaluation , 2010 .

[9]  Joe Zhu,et al.  DEA Cross Efficiency , 2014 .

[10]  Giovanni Angelini,et al.  DEA-Like Model and Common Weights Approach for the Construction of a Subjective Community Well-Being Indicator , 2013 .

[11]  Bruce Hollingsworth,et al.  Use of ratios in data envelopment analysis , 2003 .

[12]  Ana S. Camanho,et al.  Undesirable outputs and weighting schemes in composite indicators based on data envelopment analysis , 2015, Eur. J. Oper. Res..

[13]  Vinicius Amorim Sobreiro,et al.  Human development and data envelopment analysis: A structured literature review , 2015 .

[14]  Martin Ravallion,et al.  Troubling Tradeoffs in the Human Development Index , 2010 .

[15]  T. Sexton,et al.  Data Envelopment Analysis: Critique and Extensions , 1986 .

[16]  B. Golany,et al.  Alternate methods of treating factor weights in DEA , 1993 .

[17]  Laurens Cherchye,et al.  An Introduction to ‘Benefit of the Doubt’ Composite Indicators , 2007 .

[18]  Peter von der Lippe,et al.  Index Theory and Price Statistics , 2007 .

[19]  Marijn Verschelde,et al.  An environment-adjusted evaluation of citizen satisfaction with local police effectiveness: Evidence from a conditional Data Envelopment Analysis approach , 2012, Eur. J. Oper. Res..

[20]  Stergios Athanassoglou,et al.  Revisiting Worst-Case DEA for Composite Indicators , 2015 .

[21]  R. Dyson,et al.  Reducing Weight Flexibility in Data Envelopment Analysis , 1988 .

[22]  Elisa Fusco,et al.  Enhancing non-compensatory composite indicators: A directional proposal , 2015, Eur. J. Oper. Res..

[23]  S. M. Hatefi,et al.  A common weight MCDA–DEA approach to construct composite indicators , 2010 .

[24]  Laurens Cherchye,et al.  Creating composite indicators with DEA and robustness analysis: the case of the Technology Achievement Index , 2006, J. Oper. Res. Soc..

[25]  Abraham Charnes,et al.  Measuring the efficiency of decision making units , 1978 .

[26]  Nicky Rogge,et al.  Undesirable specialization in the construction of composite policy indicators: The Environmental Performance Index , 2012 .

[27]  B. W. Ang,et al.  Weighting and Aggregation in Composite Indicator Construction: a Multiplicative Optimization Approach , 2010 .

[28]  Emmanuel Thanassoulis,et al.  Weights restrictions and value judgements in Data Envelopment Analysis: Evolution, development and future directions , 1997, Ann. Oper. Res..

[29]  Philip J. Fleming,et al.  How not to lie with statistics: the correct way to summarize benchmark results , 1986, CACM.

[30]  Stefano Tarantola,et al.  Handbook on Constructing Composite Indicators: Methodology and User Guide , 2005 .

[31]  Francesca Giambona,et al.  Composite Indicator of Social Inclusion for European Countries , 2014 .

[32]  Bert M. Balk,et al.  Price and Quantity Index Numbers: Models for Measuring Aggregate Change and Difference , 2012 .

[33]  William W. Cooper,et al.  Choosing weights from alternative optimal solutions of dual multiplier models in DEA , 2007, Eur. J. Oper. Res..

[34]  Giannis Karagiannis,et al.  Productivity measurement in radial DEA models with a single constant input , 2016, Eur. J. Oper. Res..

[35]  H. Welsch,et al.  Meaningful environmental indices: a social choice approach , 2004 .

[36]  Zilla Sinuany-Stern,et al.  DEA and the discriminant analysis of ratios for ranking units , 1998, Eur. J. Oper. Res..

[37]  J. Paradi,et al.  DEA-R: ratio-based comparative efficiency model, its mathematical relation to DEA and its use in applications , 2007 .

[38]  Rodney H. Green,et al.  Efficiency and Cross-efficiency in DEA: Derivations, Meanings and Uses , 1994 .

[39]  R. Hill,et al.  A Taxonomy of Multilateral Methods for Making International Comparisons of Prices and Quantities , 1997 .

[40]  Jie Wu,et al.  Alternative secondary goals in DEA cross-efficiency evaluation , 2008 .

[41]  A. Charnes,et al.  Invariant multiplicative efficiency and piecewise cobb-douglas envelopments , 1983 .

[42]  János Aczél,et al.  Determining merged relative scores , 1990 .

[43]  Ozren Despic,et al.  SOME PROPERTIES OF GEOMETRIC DEA MODELS , 2013 .

[44]  I. Contreras,et al.  Constructing a composite indicator with multiplicative aggregation under the objective of ranking alternatives , 2013, J. Oper. Res. Soc..

[45]  J. Florens,et al.  Nonparametric frontier estimation: a robust approach , 2002 .

[46]  Christopher T. Whelan,et al.  Comparing Poverty Indicators in an Enlarged European Union , 2010 .

[47]  Chris Tofallis,et al.  On constructing a composite indicator with multiplicative aggregation and the avoidance of zero weights in DEA , 2014, J. Oper. Res. Soc..