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The Colombian Multidimensional Poverty Index: Measuring Poverty in a Public Policy Context

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Abstract

Previous multidimensional indices for the Colombian context, such as the Unmet Basic Needs Index or the Living Conditions Index, have lost their public policy relevance and arguably have become poor instruments for poverty measurement. This paper presents the Colombian Multidimensional Poverty Index (CMPI), a synthetic indicator that overcomes the methodological problems from previous multidimensional indices and has a broad public policy scope of use. The CMPI is based on the methodology of Alkire and Foster (J Public Econ 95:476–478, 2011a) and is composed of five dimensions (education of household members, childhood and youth conditions, health, employment and access to household utilities and living conditions). Additionally, it uses a nested weighting structure, where each dimension is equally weighted, as is each indicator within each dimension. This paper proposes the CMPI for tracking multiple deprivations across the national territory, to monitor public policies by sector and to design poverty reduction goals, among other public policy uses. Analysis of the results demonstrates that multidimensional poverty in Colombia decreased between 1997 and 2010 in both urban and rural areas, but imbalances remain.

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Notes

  1. The National Planning Department (NPD) is a technical entity that promotes the implementation of the strategic vision of the country in the social, economic and environmental sectors through the design, orientation and evaluation of public policies in Colombia; the management and allocation of public investments; and the realization of said plans, programs and government projects (see http://www.dnp.gov.co/).

  2. Although the term household is not equivalent to the term family, in Colombia approximately 82 % of households are made up of members of the same family, 60 % of households correspond to nuclear families and 22 % to extended families.

  3. The coefficient of variation \((cv)\) is defined as the ratio of the standard deviation obtained from sample to the mean \(cv=\sigma /\mu\). This measure is also known as the relative standard deviation and shows the extent of variation of a measure in relation to the population mean. According to 2008 DANE guidelines, the cv “measures the ...variability of the estimator’s sampling distribution, that is, it indicates the accuracy with which universe characteristics are being estimated.” For the LSMS case, DANE considers that an estimate is accurate if the \(cv <7\,\%\), has acceptable accuracy if \(7\,\%<cv<15\,\%\), has regular accuracy if \(15\,\% \le ve\le 20\,\%\), and finally, the estimate is inaccurate if \(cv>20\,\%\).

  4. The cut-off point was determined according to the Sector Plan for Education 2006–2007, presented by the National Ministry of Education, and the basic competencies acquired by an individual in primary school (1st–5th grades) and secondary school (6th–9th grades) that are required to have a decent job.

  5. A child is considered under the care of a responsible adult if (1) he/she remains at home under the care of father or mother, (2) is under the care of a relative, (3) is under the care of a nanny or maid, or (4) is under the care of neighbours or friends. The last two categories of care were defined as responsible adult because there is no evidence that indicates inadequate care in those cases. Being under the care of a nanny is considered adequate, and since it is not possible to separate the responsibilities of the maid from those of a nanny, the whole option is considered adequate. On the other hand, the ages of friends and neighbours are unknown is not sufficient to determine deprivation. A child that (1) is taken to work by a parent, (2) remains home alone, or (3) remains under the care of other minors younger than him is considered to be under inadequate care.

  6. Due to a lack of information, it is assumed that children under the care of a responsible adult receive adequate nutrition.

  7. See ILO convention No. 138 on the minimum age for admission to employments and work and ILO convention No. 182 on the worst forms of child labour, 1999.

  8. The definition of hazardous work varies from country to country, as well as among sectors within countries. According to the World Health Organization, for example, what makes child labour hazardous is the presence of hazards and risks at the workplace (such as the presence of chemicals, noise, ergonomic risks like lifting heavy loads, etc.) and working conditions (long hours, night work, harassment).

  9. The economically active population in this case is made by household members 12 years old and over who are either employed or actively seeking employment (unemployed).

  10. It is a contradiction to determine that a child is deprived when employed and at the same time that he/she is deprived if unemployed or actively seeking employment. The objective of the policy for elimination of child labour is for children to be excluded from the job market and, therefore, not classified as employed or unemployed.

  11. It includes any type of health insurance regime, namely contributory regime, subsidized regime or special regimes. Contributory Regime: for those with sufficient income and/or are formally employed, whose affiliation is subject to a monthly contribution of 12.5 % of their income. Subsidized Regime: for the poor population without payment capacity, identified with SISBEN instrument. Special Regimes: for people who have or had a labour relation with ECOPETROL (national petroleum company), the armed forces, the national police, the National Teaching Fund and public universities.

  12. Weights are rearranged according to the number of indicators within each dimension.

  13. Due to differences between the information available in the LSMS and the Census, some of the indicators used to calculate the CMPI at the municipal level were adapted according to Census data 2005: (1) the long-term unemployment indicator is replaced by the economic dependence rate, (2) a proxy for adequate nutrition is constructed for the childcare indicator, which considers a household in deprivation if the child did not receive any of the three basic meals one or more days of the previous week due to lack of money, and (3) access to healthcare services refers to the previous 12 months.

  14. At a company or hired individual’s location, at a rented or own location, at home, in someone else’s home, on the street, in a kiosk or stand, door to door, in a vehicle (taxi, car, bus, motorboat, boat), in a mine or quarry, in a construction site, in a farm or land, owned, rented or crop shared, somewhere else (ocean or river).

References

  • Alkire, S., & Foster, J. (2011a). Counting and multidimensional poverty measurement. Journal of Public Economics, 95, 476–478.

    Article  Google Scholar 

  • Alkire, S., & Foster, J. (2011b). Understandings and misunderstandings of multidimensional poverty measurement. The Journal of Economic Inequality, 9(2), 289–314.

    Article  Google Scholar 

  • Alkire, S., & Santos, M. (2010). Acute multidimensional poverty: A new index for developing countries. UNPD, Human Development Research Paper.

  • Atkinson, A. B. (2003). Multidimensional deprivation: Contrasting social welfare and counting approaches. The Journal of Economic Inequality, 1(1), 51–65.

    Article  Google Scholar 

  • Battiston, D. et al. (2009). Income and beyond: Multidimensional poverty in six Latin American countries. OPHI Working Paper, 17.

  • Bourguignon, F., & Chakravarty, S. R. (2003). The measurement of multidimensional poverty. The Journal of Economic Inequality, 1(1), 25–49.

    Article  Google Scholar 

  • Castano, E., Deutsch, R., & Velez, C. (1999). Una interpretación económica del sistema de focalización de programas sociales: El caso sisben en colombia. Revista Coyuntura Social, Fedesarrollo, 21.

  • CMEPSP. (2009). Report of commission on the measurement of economic performance and social progress. Technical report, National Planing Department, Colombia.

  • Conpes. (2012). Metodologías oficiales y arreglos institucionales para la medición de la pobreza en colombia. Technical report, Consejo Nacional de Política Económica y Social, República de Colombia, Departamento Nacional de Planeación. Documento Conpes Social No 150.

  • Cortés, D., Gamboa, L., & González, J. (1999a). Icv: Hacia una medida de estándar de vida. Revista Coyuntura Social, Fedesarrollo, 21.

  • Cortés, D., Gamboa, L., & González, J. (1999b). Un marco teórico para un indicador tipo sisben. Reporte técnico, Fondo Financiero de Proyectos de Desarrollo (FONADE) y Universidad del Rosario, Bogotá, Colombia.

  • Cortés, D., Gamboa, L., & González, J. (2000). Algunas consideraciones analíticas sobre el estándar de vida. Revista de Economía de la Universidad del Rosario, III.

  • Decancq, K., & Lugo, M. A. (2013). Weights in multidimensional indices of wellbeing: An overview. Econometric Reviews, 32(1), 7–34.

    Article  Google Scholar 

  • DNP, PNUD, ICBF, and MS (2002). Familias Colombianas: Estrategias Frente al Riesgo. Departamento Nacional de Planeación (DNP), Programa de las Naciones Unidas para el Desarrollo (PNUD), Instituto Colombiano de Bienestar Familiar (ICBF), Misión Social (MS). Alfa Omega, Bogota.

  • Florez, C., Sanchez, L., Espinosa, F., & Angulo, R. (2011). El indice sisben iii.

  • Foster, J., Greer, J., & Thorbecke, E. (1984). A class of decomposable poverty measures. Econometrica, 52, 761–766.

    Article  Google Scholar 

  • González, J., & Sarmiento, A. (1998). Algunos aspectos conceptuales del índice de condiciones de vida. Coyuntura Social, 19, 67–88.

    Google Scholar 

  • López Calva, L. F., & Ortiz Juárez, E. (2009). Medición multidimensional de la pobreza en méxico: Significancia estadística en la inclusión de dimensiones no monetarias. Reporte técnico, Estudios Económicos.

  • Muñoz, M. (1995). Los indicadores de necesidades básicas insatisfechas (nbi). Boletín de Estadística DANE, 507.

  • Pattanaik, P., & Xu, Y. (1990). On ranking opportunity sets in terms of freedoms of choice. Recherches Economiques de Louvain, 507.

  • PNUD, UNICEF, & DANE. (1987). Magnitud de la pobreza en colombia, primer informe del proyecto de indicadores de pobreza. Boletín de Estadística DANE 411, Departamento Nacional de Planeación y Ministerio de Agricultura.

  • Santos, M. E., Lugo, M. A., López-Calva, L. F., Cruces, G., & Battistón, D. (2010). Refining the basic needs approach: A multidimensional analysis of poverty in Latin America. In J. Bishop (Ed.), Studies in applied welfare analysis: Papers from the third ECINEQ meeting. Research on economic inequality Vol. 18 (pp. 1–29).

  • Sen, A. K. (1976). Poverty: An ordinal approach to measurement. Econometrica: Journal of the Econometric Society, 44(2), 219–231.

  • Sen, A. K. (1979). Issues in the measurement of poverty. The Scandinavian Journal of Economics, 81(2), 285–307.

  • Tsui, K.-Y. (2002). Multidimensional poverty indices. Social Choice and Welfare, 19(1), 69–93.

    Article  Google Scholar 

  • Vélez, C., Azevedo, J., & Posso, C. (2010). Oportunidades para los Niños Colombianos: Cuánto Avanzamos en esta Década. Banco Mundial, Banco de la República, DNP, Colombia.

  • WHO & UNICEF. (2010). Progress on sanitation and drinking-water: 2010 Update. World Health Organization (WHO) and the United Nations International Children’s Emergency Fund (UNICEF).

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Acknowledgments

This work was undertaken while the authors were working for the National Planning Department of Colombia (NPD); the project is an initiative of the National Planning Department, and it was funded in full by the NPD. We would like to thank Esteban Piedrahíta and Juan Mauricio Ramírez for taking the initiative to design a CMPI. We also thank James Foster (George Washington University) and Sabina Alkire, José Manuel Roche and Diego Zavaleta, from the Oxford Poverty and Human Development Initiative (OPHI) for their encouragement and critical comments during the design and development of the indicator. We thank Jorge Ivan González, Jairo Nuñez, Hugo López, Raquel Bernal, Ximena Peña and Alfredo Sarmiento for their clever and thoughtful comments, and we thank Yolanda Riveros for her careful work as a research assistant. Also, thanks to the Social Development and Urban Development Divisions at the National Planning Department for the advice on choosing indicators consistent with the priorities of public policy. Finally, we would like to thank Hernando José Gómez and José Fernando Arias for promoting the use of the CMPI in the design and orientation of public policy in Colombia. This version of the paper has benefited from the insights and suggestions of the anonymous referee and Maria Iacovou (University of Cambridge).

Conflict of interest

We (Roberto Angulo, Yadira Díaz and Renata Pardo) declare that we do not have any conflict of interest for the publication of this original research article.

Compliance with ethical standards

We, Roberto Angulo, Yadira Díaz and Renata Pardo, authors of the article ‘The Colombian multidimensional poverty index: measuring poverty in a public policy context”, certify that we comply in full the ethical responsibilities of authors of the journal Social Indicators Research outlined in the journal’s website (http://www.springer.com/social+sciences/journal/11205) accessed on the 23rd of February of 2015. For this purpose, we follow acknowledging the funding upon this work was developed, and disclosing no potential conflicts of interest for the publication of this manuscript as an original research article.

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Authors and Affiliations

  1. Bogotá, Colombia

    Roberto Angulo

  2. Institute of Social and Economic Research (ISER), University of Essex, Wivenhoe Park, Colchester, UK

    Yadira Díaz

  3. Universidad de los Andes, Bogotá, Colombia

    Renata Pardo

Authors
  1. Roberto Angulo
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  2. Yadira Díaz
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  3. Renata Pardo
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Corresponding author

Correspondence to Yadira Díaz.

Appendix

Appendix

See Figs. 8, 9, 10, 11 and Tables 8, 9.

Fig. 8
figure 8

Proportion of deprived population across the CMPI considered indicators, 1997–2010 Raw headcount ratios. Source: LSMS

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Fig. 9
figure 9

Multidimensional poverty headcount ratio \(H\) for different values of \(k\), urban and rural areas.

Source: LSMS

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Fig. 10
figure 10

Average deprivation rate suffered among the poor population \((A)\) for different values of \(k\), urban and rural areas.

Source: LSMS

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Fig. 11
figure 11

Adjusted multidimensional headcount poverty ratio \((M0)\) for different values of \(k\), urban and rural areas.

Source: LSMS

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Table 8 Indicators’ redefinition for calculating the adjusted gap in each dimension in which poor households are deprived
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Table 9 CMPI association with NDP sector goals
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Angulo, R., Díaz, Y. & Pardo, R. The Colombian Multidimensional Poverty Index: Measuring Poverty in a Public Policy Context. Soc Indic Res 127, 1–38 (2016). https://doi.org/10.1007/s11205-015-0964-z

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