A DEA Approach to Measure the Quality-of-Life in the Municipalities of the Canary Islands


The notion of the quality of life has always intrigued economists, sociologists and other researchers in the area of social science. Since the genesis of the definition of Gross Domestic Product (GDP) as a truthful measure of well-being and economic development, other sophisticated methodologies have been proposed in the literature to measure the quality-of-life (QOL) that extend in a multidimensional way this complex concept. Measuring QOL in municipalities consists in finding a set of comparable attributes that can be weighted by some metric in order to construct a synthetic index. Thus, the narrow vision obtained by a single measure as the GDP, in which differences in the QOL cannot be fully analyzed, is overcome. Based upon a refinement of data envelopment analysis (DEA)—the cross-efficiency method, the current paper develops a synthetic QOL index that is based in 19 partial indicators which present the tradeoffs of different dimension for the 87 municipalities of the Canary Islands in Spain. Marginal rates of substitution are calculated to evaluate the tradeoffs on QOL dimensions. A method is also proposed to determine the scores chart of each municipality which can be used as a tool to policy makers in order to establish a program of improving the ranking position of the municipality identifying the critical QOL factors.

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Fig. 1


  1. 1.

    NUTS represents the initials for Nomenclature of Territorial Units for Statistics used by the European Union for statistical purposes. It is classified according to the number of population in the regions of each European country. The European division model establishes five levels, of which NUTS I represent the highest one.

  2. 2.

    The index is calculated as the ratio of the sum of the class marks of educational level and the total population. The class marks range from 0 (illiterate) to 4.5 (Ph.D.).

  3. 3.

    DEA can be applied to scenarios where the data cannot be strictly interpreted as inputs or outputs or there is no direct functional relationship between the variables. In such situations, a general guideline to the classification of the variables is that variables for which lower levels are better are considered inputs, while outputs are those variables for which higher amounts are better.

  4. 4.

    CCR and BCC acronyms are sometimes used in reference to CRS and VRS models. The acronyms come from the initial of the authors of the papers that employed these two different envelopment surfaces (Charnes et al. 1978 and Banker et al. 1984).

  5. 5.

    The different assumptions about the scalar produce distinct envelopment surfaces: VRS, CRS or extensions of these basic models.

  6. 6.

    Marks are obtained for each of the factors as follows: A, B, C and D are given if the value belongs to the first, second, third and fourth quartile, respectively.


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The authors thank Eduardo Gonzalez, professor of the Department of Business Administration at the University of Oviedo for providing most of the data used in this research. Additional gratitude extends to Professor Alex Michalos and two anonymous referees for their valuable comments. The usual disclaimer applies.

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Correspondence to Juan Carlos Martín.

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Martín, J.C., Mendoza, C. A DEA Approach to Measure the Quality-of-Life in the Municipalities of the Canary Islands. Soc Indic Res 113, 335–353 (2013). https://doi.org/10.1007/s11205-012-0096-7

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  • Quality-of-life
  • Well-being
  • DEA
  • Cross-efficiency
  • Synthetic index