Abstract
Objective: Existing well-being measures differ in terms of number and format of items, factors being measured, aggregation methods, and are not comparable. A well-being measure involves combining n- number of indicators and quality of the measure depends on properties of combining procedures adopted. The paper proposes two assumption-free aggregation methods to satisfy the desired properties of an index Methods: The paper proposes two indices of well-being in terms of cosine similarity and Geometric mean (GM) avoiding problems associated with scaling of raw data and choosing of weights. Empirical illustration is provided on application of the proposed measures. Results: The proposed indices give better admissibility of operations and satisfy properties like time-reversal test, formation of chain indices, computation of group mean and statistical tests for comparison across time and space. The preferred index can be constructed even for skewed longitudinal data and helps to reflect path of improvement registered by a country/region over time. Conclusions: The index based on GM is preferred due to wider application areas. The index can further be used for classification of countries, sub-groups and even individuals with morbidity in terms of overall wellbeing values. Future studies suggested.
Highlights
Wellbeing Index (WBI) attempts to assess in quantitative terms —how people are doing
Major uses of WBI are (i) comparisons among persons or countries/regions/societies across time and space (ii) ranking and classifying the units (iii) identifying contribution of each domain/indicator to WBI (iv) identifying critical areas for policy changes towards individual and societal goals (v) drawing path of improvement of WBI over time for a unit and making inter-country or inter-regional comparisons with respect to such paths (vi) computing mean WBI for a group of units (Global WBI)
If the base period data is replaced by the targets, WBIc,Sustainable Development Goals (SDG) will indicate how far a country is from the SDG goals at the C-th period
Summary
Wellbeing Index (WBI) attempts to assess in quantitative terms —how people are doing. A wellbeing measure is a Composite Index (CI) combining measures of multidimensional aspects of wellbeing such as economy, physical health, psychological wellbeing, environment, social/cultural capital, satisfaction of basic needs, time use, etc. Social and psychological data are usually ordinal and discrete. Combining such data with continuous data in interval/ratio scale is problematic. Major uses of WBI are (i) comparisons among persons or countries/regions/societies across time and space (ii) ranking and classifying the units (iii) identifying contribution of each domain/indicator to WBI (iv) identifying critical areas for policy changes towards individual and societal goals (v) drawing path of improvement of WBI over time for a unit and making inter-country or inter-regional comparisons with respect to such paths (vi) computing mean WBI for a group of units (Global WBI). Methodologically sound WBI is needed to facilitate all such uses
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