ABELL, N., D. W. SPRINGER and A. KAMATA (2009) Developing and
validating rapid assessment instruments, New York ; Oxford, Oxford
Brown, T. A. (2006) Confirmatory factor analysis for applied research,
New York, NY ; London, New York, NY ; London : Guilford Press.
(Chapter 2: The common Factor Model and Exploratory Factor Analysis)
CHIAPPERO-MARTINETTI, E. and J. M. ROCHE (2009) “Operationalization of
the capability approach, from theory to practice: a review of
techniques and empirical applications” in CHIAPPERO-MARTINETTI, E.
(Ed.) Debating Global Society: Reach and Limits of the Capability
Approach. Milan, Fondazione Feltrinelli.
Gallo, Cesar and J.M. Roche (2011) ‘Multidimensional Poverty in
Venezuela during 1997 – 2010: A proposal of a national adapted measure
for monitoring purposes’ in Serie Documentos de Trabajo, Banco Central
HAMILTON, L. C. (2009) Statistics with Stata : updated for version 10,
Belmont, CA, Brooks/Cole. (Chapter 12: Principal Components, Factor,
and Cluster Analysis)
HEATH, A. and J. MARTIN (1997) Chapter 3: Why Are There so Few Formal
Measuring Instruments in Social and Political Research? IN LYBERG, L.
(Ed.) Survey measurement and process quality. New York ; Chichester,
Klasen, S. (2000). Measuring Poverty and Deprivation in South Africa.
Review of Income and Wealth. Vol. 46, pp. 33-58.
Roche, J.M. (2008). Monitoring Inequality among Social Groups: A
Methodology Combining Fuzzy Set Theory and Principal Component
Analysis. Journal of Human Development. Vol. 9 (3)
Rutstein, S. and K. Johnson, 2004. The DHS Wealth Index, DHS
Comparative Reports No. 6, Calverton, MD: ORC Macro.
The list below is not comprehensive, but covers some of the key research issues that have been identified by OPHI researchers. Please watchPart 2 of the video to get a further explanation by Sabina Alkire.
Research Issues: Data for MPI
Can we improve international data for MPI calculations?
Should we ‘call for’ a survey having a specific set of dimensions and indicators? And which?
Research Issues: General data
Data Constraints: Most criticisms address these (why don’t you include _____?).
58:55 Question asked to reflect on your own multidimensional poverty measure
60:17 Link between MPI and the capability approach, and a discussion on the practical implementation of the capability approach – how the AF methodology allows for diversity with valued functionings (a k cut-off larger than union)
66:21 The capability approach’s relation to human development (and the HDR), they have the same objective
70:14 The capability approach’s relation to other conceptual framworks (MDGs, human rights, human security, happiness)
03:10 Introduction to the components of MPI: surveys used, dimensions and weights chosen, and data restrictions on international comparable survey data
05:20 Explanation of the health dimension – variables and deprivation cut-offs
06:37 Explanation of the educational dimension – variables and deprivation cut-offs
07:58 Explanation of the living standard dimension – variables and deprivation cut-offs
11:54 Data constraints, a call for better data, and a note that MPI is not appropriate for national policy
15:46 Explanation of the equally (nested) weights in MPI – same as HDI, pasted robustness check, (most importantly) they are easy to communicate (Atkinson)
18:35 Identification (z-cut and k-cut offs); the debate/choice of the poverty cut-off (k).
21:48 Aggregation and limitation to the adjusted headcount (M0), as MPI is based on ordinal data.
23:10 Examples from qualitative work done on the global MPI.
26:10 Present the MPI 2010 results, comparison to $1.25/day, introduction to the many research questions relating to construction of a multidimensional poverty measure and MPI work within the topic (see lecture on Ongoing Debates and Research Topics).
A national Multidimensional Poverty Index is a country-specific poverty measure tailored to each country’s unique situation. Such measures generally take the dimensions of health, education and living standards as their starting point, and supplement with different dimensions measured by locally appropriate indicators.