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Measuring Human Development: A Multi-criteria Approach

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Abstract

In 2010 the Human Development Index (HDI) was revised with several major changes. Many of its problems were tackled, although some drawbacks still persist. This paper proposes a multi-criteria approach to measure human development, propounding two innovations for the computation of the HDI: (1) the introduction of a double reference point scheme in the normalization; (2) an aggregation function which deals with the problem of substitutability between components. In particular, for each component of the HDI the value of each country is normalized by means of two reference values (aspiration and reservation values) by using an achievement scalarizing function that is piecewise linear. Aggregating the new normalized values, we calculate a range of indices with different degrees of substitutability: (1) a weak index that allows total substitutability; (2) a strong index that measures the state of the worst component and allows no substitutability; and (3) a mixed index that is a combination of the first two.

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Notes

  1. For a survey, see Kovacevic (2011), which was part of a comprehensive review undertaken by the Human Development Report Office (HDRO) of the United Nations Development Program (UNDP). Some significant contributions are McGillivray (1991), Desai (1991), Kelley (1991), Dossel and Gounder (1994), Gormely (1995), Ravallion (1997), Palazzi and Lauri (1998), Anand and Sen (2000), Chakravarty (2003), Chatterjee (2005), Foster et al. (2005), Chowdhury and Squire (2006), Gaertner and Xu (2006), Lind (2010), Herrero et al. (2010), De Muro et al. (2011), Nguefack-Tsague et al. (2011), Pinar et al. (2013), Foster et al. (2012), Rende and Donduran (2013), etc.

  2. Let us recall that, as highlighted by authors such as Desai (1991) and Palazzi and Lauri (1998), the additive form of the HDI is problematic because it implies perfect substitution across components. It assumes that the level of priority to be given to a component is invariant to the level of attainments. In addition, if a society were to seek policies to maximize its HDI, it might emphasize one component and disregard the others (see Klugman et al. 2011a).

  3. Note that the range normalization is a particular case of our framework.

  4. The HDI excludes other ‘broader dimensions’ of the concept of human development, such as empowerment, sustainability and equity. The 2010 HDR decided not to introduce any new dimensions in the HDI, stressing that the HDI can be characterized as an index of opportunities and freedoms, according to the two types of freedoms (opportunity freedoms and process freedoms) suggested by Sen (2002), that are valued by the human development approach (see, e.g., Klugman et al. 2011a).

  5. Given that the transformation function from income to capabilities is likely to be concave (Anand and Sen 2000), the natural logarithm continues to be used to measure this HDI component.

  6. UNDP (2011) reminds us that the low value for income can be justified by the considerable amount of unmeasured subsistence and nonmarket production in economies close to the minimum, not reflected in the official data.

  7. The choice of equal weights has been widely criticized, with diverse methodologies proposed to set weights (see, e.g., Kelley 1991; Chowdhury and Squire 2006; Lind 2010; Nguefack-Tsague et al. 2011; Tofallis 2012; Pinar et al. 2013; Foster et al. 2012), was also unchanged in 2010.

  8. In part, this is an empirical criterion similar to the one used by UNDP (2011) to set the minimum and maximum values (goalposts), according to the situation of countries worldwide in recent years.

  9. For the presentation of the results, we have selected the 10 most populated countries, which represent about 60 % of world population. These countries, listed on the basis of their HDI, are distributed amongst the 4 groups of countries as defined in the 2011 HDR: Very High Human Development (United States, Japan), High Human Development (Russian Federation, Brazil), Medium Human Development (China, Indonesia, India, Pakistan) and Low Human Development (Bangladesh, Nigeria).

  10. We have carried out a sensitivity analysis of the weights of the components, showing that for a slight modification of one of them (for instance, 10 %) the ranking is almost equal (90 % of countries maintain their position or vary one or two positions), whereas major changes in the weights involve greater variations in the rankings. These results are in line with the role of the weights in the achievement scalarizing functions (see Luque et al. (2009) or Ruiz et al. (2009) for more details).

  11. The results of Table 5 for all countries are available from the authors upon request.

  12. Specifically, Spearman’s correlation coefficient rho (ρ) amongst the ranks of countries listed according to the DRP-WI using criteria I and II is 0.999, and 0.992 amongst the DRP-SI ranks using both criteria.

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Authors and Affiliations

  1. Department of Applied Economics (Mathematics), University of Malaga, Campus de El Ejido, 29071, Malaga, Spain

    Mariano Luque & Beatriz Rodríguez

  2. Department of Applied Economics (Economic Policy), University of Malaga, Campus de El Ejido, 29071, Malaga, Spain

    Salvador Pérez-Moreno

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  1. Mariano Luque
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  2. Salvador Pérez-Moreno
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  3. Beatriz Rodríguez
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Correspondence to Beatriz Rodríguez.

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Luque, M., Pérez-Moreno, S. & Rodríguez, B. Measuring Human Development: A Multi-criteria Approach. Soc Indic Res 125, 713–733 (2016). https://doi.org/10.1007/s11205-015-0874-0

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