Measuring well-being in Colombian departments. The role of geography and demography☆
Section snippets
Introduction and motivation
Society's interest in well-being has rocketed in the last few years. A quick search in Google Scholar yields 2,260,000 results only for the last decade. There are several reasons underlying this trend. One of the most important is rooted in the limitations of GDP per capita as an appropriate well-being measure [[1], [2], [3]]. In response, some projects have tried to provide more comprehensive well-being measures, considering information on other dimensions of well-being beyond income. A
Well-being in Colombia: background
Regional disparities in Colombia are large and persistent, as documented in several reports by international institutions (e.g., Refs. [24,25]). The wide gaps across departments are reflected in critical indicators such as poverty, which shows values ranging from the relatively low levels of Santander (8%) and Cundinamarca (7.3%) to the much higher ones corresponding to Cauca (50.7%) and Chocó (59.3%), according to World Bank calculations in several rounds of the GEIH (Gran Encuesta Integrada
Computing a composite well-being indicator
The computation of composite indicators is grounded in data reduction techniques which enable the researcher to summarise the information contained in a set of variables relating to a given subject, e.g., well-being, into a single figure. The OECD [36] provides a comprehensive review of methodologies and guidelines to building composite indicators, with the issue of aggregation being one of the main challenges faced by researchers in the field. The use of equal weightings, i.e., assigning the
Data, sources and descriptive statistics
As commented in the introduction, our well-being benchmark is that defined by the OECD BLI, which includes 10 objective well-being dimensions and a subjective one, measured as self-reported life satisfaction. In this research, we focus on objective well-being, although not all 10 objective well-being BLI dimensions can be computed at the subnational level in Colombia, in our case the 33 Colombian departments. In particular, for the dimensions of work-life balance and community, no indicators
Results and discussion
In this section we analyse observed well-being disparities across Colombian departments using the composite indicators computed with our DEA-SBM-MCDM approach and the data described in Section 4. It is our hope that this analysis will allow a better understanding of the Colombian regional reality, which goes much beyond purely economic issues. Additionally, we attempt to unravel how conditioning factors shape the patterns of well-being. In particular, we take into account the role of spatial
Conclusions and prospects for future research
This paper builds a composite indicator of objective well-being for the 33 Colombian departments for the year 2016, taking the widely-accepted Better Life Index developed by the OECD as the benchmark. To that end, state-of-the-art techniques in the composite indicators literature, including Data Envelopment Analysis and Multi-Criteria-Decision-Making are employed. This combined approach provides a satisfactory solution to the aggregation problem that affects the construction of composite
Author statement
None of the authors holds any Conflict of Interest.
The database used in this research is available on request.
Jesús Peiró-Palomino. Associate Professor of Economics. PhD in Economics (University Jaume I, Spain, 2014). His research interests are social capital and institutions and their role in the economic sphere, especially innovation processes and development at the regional level. He is also interested in well-being, its spatial distribution and evolution over time. He has published several papers on these topics in specialized international journals.
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Cited by (0)
Jesús Peiró-Palomino. Associate Professor of Economics. PhD in Economics (University Jaume I, Spain, 2014). His research interests are social capital and institutions and their role in the economic sphere, especially innovation processes and development at the regional level. He is also interested in well-being, its spatial distribution and evolution over time. He has published several papers on these topics in specialized international journals.
Andrés J. Picazo-Tadeo. Full Professor of Economics. PhD in Economics (University of Valencia, Spain, 1994), MSc in Economics (London School of Economics and Political Science, United Kingdom, 1991). His main areas of research include environmental economics and the measurement of efficiency and productivity, in which he has published nearly a hundred papers.
Emili Tortosa-Ausina. Full Professor of Economics. Graduated in Economics and Business Studies from the Universitat de València and obtained his PhD with special honors from the Universitat Jaume I in Castellón, where he is Professor in Applied Economics. He has published various books in collaboration with others, and his articles have appeared in specialized journals and he has participated in and organized numerous national and international congresses and scientific meetings. His fields of research include economic measurement, in particular, the analysis of efficiency and productivity.
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We thank the participants at the XLV International Conference on Regional Science (2019) for helpful comments and suggestions—particularly those by Vicente Royuela—which contributed to an overall improvement of the paper. The comments from two referees have also contributed to a much improved research. We also acknowledge the financial support of the European Regional Development Fund and the Spanish Ministerio de Economía y Competitividad (ECO2016-75237-R and ECO2017-85746-P), Generalitat Valenciana (PROMETEO/2018/102) and Universitat Jaume I (UJI-B2017-33). The usual disclaimer applies.