MCDM'13 - paper no. 4


Back to MCDM'13 contents


Josef Jablonsky


Happy Planet Index (HPI) is an aggregated index that measures the extent to which each nation produces long and happy lives per unit of environmental input. The HPI uses global data on life expectancy, experienced well-being, and ecological footprint to rank countries. The last HPI report was published in 2012 and it contains data for 151 countries from all continents. The aim of the paper is to re-calculate the HPI using DEA models and other multiple criteria decision making techniques and compare the results obtained results. MCDM methods evaluate alternatives (countries) according to the set of criteria with respect to given preferences. Most of them allow ranking of alternatives according to aggregated indices defined by various methods. DEA models compare the countries with the best performers in the data set and measure the efficiency of transformation of multiple inputs into multiple outputs. Even though they are based on different principles than MCDM methods they allow ranking of evaluated units according to their efficiency or super-efficiency scores. The paper analyzes both methodological approaches and compares their results.


Data envelopment analysis, MCDM, Happy Planet Index, efficiency.

Reference index:

Josef Jablonsky, (2013), RE-CALCULATION OF HAPPY PLANET INDEX USING DEA MODELS, Multiple Criteria Decision Making (8), pp. 56-66

Full text:


Scopus citations in 1 paper(s):
  1. Rojas-Gualdrón, D. F. (2017). Inter-regional metric disadvantages when comparing country happiness on a global scale. A rasch-based consequential validity analysis. International Journal of Psychological Research, 10(2), 26-33. doi:10.21500/20112084.2995