Multidimensional measuring poverty for policymaking: a decision support perspective
Vivien Kana1, Alexis Tsoukiàs2 et Blaise Somé1
(1) Laboratoire d’Analyse Numérique, Informatique et BIOmathématiques (LANIBIO), Université de Ouagadougou, UFR/SEA, Département de Mathématiques et Informatique, 03 BP 7021 Ouagadougou 03, Burkina Faso, Tél : + 226 76 68 57 86 / +226 70 25 31 21,
E-mail : vizkana@yahoo.fr, some@univ-ouaga.bf
(2) Laboratoire d’Analyse et Modélisation de Systèmes pour l’Aide à la Décision (LAMSADE) CNRS, Université Paris-Dauphine, 75775 Paris Cedex 16, France, Tel: +33144054401, fax: +33144054091 Email : tsoukias@lamsade.dauphine.fr
Responding to the unequal progression of the durable development, the persistence of poverty and suffering, 189 countries adopted eight Millennium Development Goals (MDGs). The first of the eight MDGs invites to reduce by half the proportion of people living in extreme poverty by 2015 [9]. Thus, to achieve this goal, poverty must be defined, studied, be measured, simulated and be followed. The multiple facets of poverty and the complexity of its dimensions oppose a logical resistance to the various strategies of fight against poverty adopted, which, up to now, are based primarily on measurements whose uncertainty and unrealism are fragrant. The concept of poverty can be explained in sociology, but the traditional mathematical tools cannot apprehend the real range of this phenomenon. Indeed, the multidimensional aspect of poverty, its fuzzy character and possible substitutions between its various forms, return the research and the monitoring of explanatory factors more complex. According to Amartya SEN, "poverty is a complex world, multiform, which requires a precise analysis of all its many dimension" [8]. It is then indicated to take an operational step which has the role to take into account the whole of these aspects for better referring to reality [7].
Fighting against poverty (see [2] and [4]) implies to measure the phenomenon and to determine the main causes of them to propose the adequate policies. The modelling of poverty raises many questions: How one apprehends poverty? How is necessary it to evaluate the "wellbeing" of the citizens to decide which is poor? How to evaluate the "wellbeing" of a group of individuals to decide on a policy of reduction of poverty adapted to the targeted group. A household survey always provides reliable indications? Which measurement must be used to aggregate the data on
"well-being" of citizens? Its choice imports it? Empirical research (see literature on the management tools [1]) and theoretical research (see literature on the theory of measuring [3]) shows that the indicators are, at the same time, models of a reality and tools for implementation of a policy. The use of indicators affects and transforms our daily life, and contributes to the justification of policies led by organizations as well public as private. Their study thus requires at the same time a theoretical and empirical analysis, related to their installation with the service of a policy [6]. It is thus a question of improving our methodological knowledge on the way of building and of using indicators of poverty within the framework of the policies of development, in particular in Africa. Face to the complexity of the phenomenon of poverty, requiring a fine and flexible approach to build multiple dimensions model and taking in account the fuzzy character of problem, there exist several method of decision-making.
We present in this paper a multidimensional approach of identification of target sub-groups in a rural or perish-urban community for a suitable taking action and in particular, the assignment of subsidies in the framework of a reducing poverty program. Indeed, assuming that the criteria have been identified by the researchers and validated in participative ways by several groups of
actors (including the recipients), one should lead to build scales of poverty to which different categories of citizens would be affected (different levels of poverty). Each category representing, for the actor or the actors in charge to put a program or project, one or several targets for which it would be necessary to apply a policy or specific actions aiming to improve the living conditions of citizens or households belonging to the sub-groups or categories considered. To measure poverty will mean, in this approach, to measure the degree of need of households according to the requirements of the programme/project, being understood that in the majority of the projects, a contribution of the recipients is rather often required. Finally, it will be necessary to build:
¾ The concordance indices: who expresses how much the assertion "X belongs to a target/category A" agrees with the reality represented by the evaluations of X on the validated criteria attributes and the policy/strategic which is associated to him in the framework of the implementation of the program.
¾ The discordance indices: who expresses how much the assertion "X doesn’t belongs to a target/category A" agrees with the reality represented by the evaluations of X on the validated criteria attributes and the policy/strategic which is associated to him in the framework of the implementation of the program.
To associate individuals and/or households to the categories permit on the one hand to better describe the precise framework of the target of a certain policy and to measure its effectiveness in times and on the other hand, to advance alternative assertions of actions if the model appears very distant compared to reality observed and the needs from the actor. Otherwise, our approach wants to propose a methodology of measurement which is meaning for some policy/strategic action applied to the assignment of the subsidies in the reducing poverty programs.
Keywords: Multiple criteria method, poverty, subsidy, target group, indicators.
[1] Bouyssou Denis, Marchant T., Pilot M., Tsoukias A. and Vincke P. « Evaluation and Decision Models: a critical perspective ». Kluwer Academic Publishers,
Boston/London/Dordrecht, 2000.
[2] Coudouel A., Jesko S. Hentschel, and Quentin T. Wodon. « Poverty Measurement and Analysis ». World Bank, Washington, D.C. Volume 1, Chapter 1, April 25, 2002.
[3] Fred S. Roberts. «Measurement Theory with Applications to Decisionmaking, Utility, and the Social Sciences», Addison-Wesley Publishing Company, 1979, Massachusetts.
[4] Giovanna Prennushi, Gloria Rubio, and Kalanidhi Subbarao. « Monitoring and Evaluation».
World Bank, Washington, D.C. Volume 1, Chapter 3, 2002.
[5] Kana Vivien, Tsoukiàs Alexis. « Mesuring poverty and taking action », ORSSA/ORPA 2007 Conference, 10-14 september 2007, Capetown, South Africa.
[6] Kana Vivien, Tsoukiàs A. and Somé, B. “Theory of indicators and Measurement of Poverty for Policy Making, International Conference on Mathematic Modeling and Numerical Simulation in Environment, 11-16 june 2007, Ouagadougou, Burkina Faso.
[7] Kana Vivien, Tsoukiàs A., Somé B. and Ulungu B., “Analysis of poverty : a multicriteria approach”, SADA 2007, International Conference on Applied Statistics for Development in Africa, 26 fev.-02 march 2007, Cotonou, Bénin.
[8] Quesada Charo. « Amartya Sen et les mille visages de la pauvreté ». Publication de la banque interaméricaine de développement, juillet 2001.
[9] voir http://www.unmillenniumproject.org/goals/gti.htm.
