Abstract
The aim of this chapter is to discuss and measure the impact on results of three main methodological assumptions in the construction of multidimensional indexes of poverty and well-being – namely, the transformation function, the aggregation procedure and the weighting system chosen. The empirical analysis is based on Jordan DHS (2002, 2007) datasets and integrated by a fieldwork conducted on a sample of students and development experts for eliciting information related to the relative weights attached to several well-being domains considered (education, health, housing, employment and personal security). A robustness analysis has been conducted quantifying the relative and global impact of different combinations of these three methodological choices on poverty estimates both at national and sub-national level.
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- 1.
An intensive debate has developed at the European institutional level in the last 2 years on how to measure progress and well-being, and many national and international initiatives have been promoted with this regard. See, in particular, the Equality of Human Rights Commission’s work in Britain and its recent report on developing a set of indicators for measuring equality (EHRC 2009), the 2009 French Report of the Stiglitz-Sen-Fitoussi Commission (2009) (http://www.stiglitz-sen-fitoussi.fr) and the initiative “Beyond GDP” promoted by the European Commission and OECD countries (www.beyond-gdp.eu). See also UNDP and the new series of indexes of human development introduced in the 2010 Human Development Report (UNDP 2010).
- 2.
On Millennium Development Goals, see the most recent Global Monitoring Report (World Bank 2010), while about EU indicators see Atkinson et al. (2002) and European Commission (2008). A most recent list of indicators has been adopted by the European Union at the end of 2009 for monitoring what is defined as the social Open Method of Coordination (OMC). For a general discussion on indicators of poverty and social exclusion at a global level, see also Marlier and Atkinson (2010).
- 3.
For a wide, even if non-exhaustive, overview of some of the most widespread well-being indices, see http://composite-indicators.jrc.ec.europa.eu. See also Ravaillon (2010a, b, 2011) for a critical discussion of some prominent composite indexes.
- 4.
These are defined by Ravaillon as “a composite index for which the producer is only constrained by the availability of data in choosing what variables to include and their weights” (Ravaillon 2010a, p. 3).
- 5.
At the best of our knowledge, there are no recent or regular empirical analyses on multidimensional deprivation in Jordan (at least, not in English) even if National Development Plans include poverty reduction and improvement in human development in their political agenda. See also the National Human Development Report (2004). A recent contribution aimed to investigate horizontal inequalities in Jordan with a special attention to Palestinian Refugees is Nimeh (2012).
- 6.
Other aggregation methods that do not allow compensability at all, such as the multi-criteria approach (MCA), are discussed in the OECD-JRC Handbook (2008). One of the innovations of the Human Development Index in the last 2010 Report is the switch from an arithmetic to a geometric mean. Critical comments on the current HDI structure have been raised by Ravaillon (2010a, b); for an intensive debate on this, see also the HDR forum “Let’s talk HD” http://hdr.undp.org/en/humandev/lets-talk-hd/
- 7.
It has been outlined, however, that an unbalanced structure in the composite index can arise if equal weights are given to each single variable when a different number of variables is being considered and subsequently grouped into different dimensions. See, among others, OECD-JRC (2008).
- 8.
There are other preliminary and fundamental choices in the construction of a composite index, such as the selection of a set of dimensions and related variables that we do not discuss in detail here for space reasons (but see Sect. 3 about the selection criteria adopted in our empirical analysis). Some theoretical frameworks, such as the capability approach, devote special attention to the selection of relevant domains to be considered (Robeyns 2003; Nussbaum 2003; Sen 2004), but as a matter of fact, in most cases, these choices are largely constrained by the availability of data.
- 9.
- 10.
The analysis presented here is part of a broader research project aimed to investigate multidimensional poverty at national and regional level from a jointly human rights and human development perspective. For that project, we referred to both national household surveys (1996, 2003) as well as to DHS micro-data (1997, 2002, 2007). Although coming from different sources, the design of a composite indicator for a large span of time has been possible because of the relatively good comparability of these five datasets.
- 11.
A Jordan 2009 DHS has recently been released but reports a smaller set of variables not sufficient to cover in an appropriate manner our chosen dimensions, while for the 2 years here considered, the datasets are more complete and perfectly comparable in terms of variables definition and sampling.
- 12.
governorates are first-level sub-national administrative units. There are 12 governorates in Jordan equally distributed in the Northern, Central and Southern regions of the country.
- 13.
The distribution of observations among the 12 governorates is consistent throughout the 2 years even if a slight over-representation of rural areas occurs in 2007. In general, the surveys design in the last 15 years registered an increase of the number of households interviewed and a higher representation of rural areas.
- 14.
There are different reasons that require making a direct connection between individual and household well-being. On one hand, the household remains the major source of social relations, decision-making and risk pooling. Moreover, some variables, like for instance those related to housing conditions, are collected at the household level.
- 15.
For similar reasons, we have not included asset indexes in the construction of our composite measures.
- 16.
For employment and health indicators, we refer to the narrow concept of family because for these indicators only parents and children are considered as unit of analysis.
- 17.
According to the high level of preoccupation that concerns unemployment in Jordan, our assumption is that a higher participation to the labour market contributes to a higher well-being. The participation of women to the labour market is very low in Jordan, around 15–20%. The woman usually does not work due to higher fertility rates and also because of cultural reasons. Therefore, a situation where only the woman works could represent a very extreme situation of poverty, when her participation to the labour market goes against cultural beliefs. Indeed, one could argue that this situation is worse than one where no one works. However, data confirm that women working enjoy more decisional power in the family, and one source of earning guarantees more protection against poverty than no source at all. Thus, we consider those families where no one is working as those with maximum deprivation.
- 18.
The two elementary indicators HOU1 and HOU5 have been aggregated using an arithmetic mean, but results are robust against other aggregation methods tested. See Table A.4 in the Annex for details.
- 19.
Among the few exceptions – according to our knowledge – there are the Vulnerability and Poverty Assessments surveys run in the Maldives Republic in 1997 and 2004 by the Minister of Planning and National Development (MPND) with the UNDP collaboration. These surveys provide a wide range of information regarding living conditions and socio-economic characteristics at both household and individual level, allowing the performance of multidimensional poverty and well-being assessments. Moreover, the surveys gather information on the importance attached to a predefined list of living standard dimensions by both individuals and the Island Communities – the latter being represented by Island Development Committees and Women’s Development Committees. These datasets are freely downloadable on the MPND website (www.frdp-maldives.gov.mv/hies/VPA.htm). See also de Kruijk and Rutten (2007).
- 20.
In order to facilitate the complete freedom of expression of the students, the questionnaire has been translated and submitted in Arabic. The total sample of 987 units included students, coming from the faculties of law (197), business (256), medicine (129), education (198) and architecture (207). The questionnaires have been distributed by a team of four people during the week of 21st–25th of February 2010. Arabic speakers have introduced the aim of the research to each class that has been visited and have given important support in explaining the questionnaire to the students and in replying to questions and doubts. Although the sample of interviewed citizens is not representative of the Jordan population, the significance of the collected opinions may be considered equally relevant, as current university students are likely to be part of the “leading group” of Jordan’s future.
- 21.
The sample included: the Jordanian Government (Ministry of Planning, Ministry of Social Affairs, National Aid Fund), Jordanian NGOs, semi-governmental organizations such as the Higher Council for Human Rights, International and Bilateral Organizations (UNDP, UNICEF, USAID) and academic experts of the University of Jordan. The importance of involving policymakers or citizens for determining weights has been outlined by many scholars, including McGillivray and Noorbakhsh (2006) and Ravaillon (2010a).
- 22.
- 23.
We follow here Esposito et al.’s methodology adopted for measuring different aspects related to literacy in Mozambique (see Esposito et al. 2011).
- 24.
Despite the fact that experts’ and students’ samples are not directly comparable, this exercise highlights major differences in perception and preference for weights assignment among the different dimensions.
- 25.
There are also some slight gender differences: male students give more importance to housing and personal security while female students worry more about health.
- 26.
The application of this methodology to the measurement of multidimensional poverty and well-being is not new even though it probably remains not sufficiently exploited. See, among other, Cerioli and Zani (1990), Cheli and Lemmi (1995), Chiappero-Martinetti (1996, 2000), Addabbo et al. (2004), Baliamoune (2004), Berenger and Verider-Chouchane (2007), Lelli (2001), Roche (2008).
- 27.
With this specification, the membership degree can also be seen as the individual poverty gap with respect to each specific domain.
- 28.
- 29.
In case of qualitative variables, the implicit assumption is that there is equidistance between modalities of the variables. For example, passing from illiteracy to primary schooling has exactly the same value as passing from a bachelor degree to a master degree.
- 30.
See Cheli and Lemmi (1995).
- 31.
- 32.
See Table A.7 in the Annex for a glossary of the multidimensional indexes corresponding to the different methodological choices.
- 33.
The FGT parametric class of poverty measures, formulated by Foster et al. (1984) may be written as follows:\(FGT=\frac{1}{n}{\left(\frac{z-{y}_{j}}{z}\right)}^{\alpha }\)with α ≥ 0; α = 0 corresponds to the head-count ratio, α = 1 to the Poverty Gap Index and α = 2 to the Squared Poverty Gap.
- 34.
- 35.
Worst and best performers are identified by the average ranking deriving from all ranking positions calculated by different multidimensional indexes for the PGI Index 2007 (values reported in Table A.9 in the Annex). Best and worst performers are held constant for all methodological comparisons.
- 36.
For reason of simplicity, we do not distinguish here between students’ and experts’ weights that however, as discussed in Sect. 3 are not so remarkably different.
- 37.
However, looking at a wider span time, such as from 1996 to 2007 (see footnote 9), poverty in Jordan has in overall decreased in a rather substantial manner. Improvements have mainly occurred in education and health while for employment and housing the Jordan performance appears to be rather stagnant. Security is a dimension where poverty appears to have increased, yet.
- 38.
It has already been remarked that the FUA indicators assume the value of the least favourable of the five considered dimensions while FIA indicators assume the value of the most favourable of the considered dimensions.
- 39.
For Fig. 5.5, all poverty estimates except those deriving from fuzzy indicators have been used. Results do not change in substance if fuzzy indicators are included, however: they tend to enter as outliers for each governatorate and therefore just make the distributional analysis of poverty estimates less clear.
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Acknowledgements
This paper has been developed within the Research Project on Human Rights and Human Development funded by the Italian Ministry of Higher Education and Research (FIRB RBIN06ZFSE). We would like to thank Ekhlas Sweis and the students of the master in human rights of the University of Jordan (UJ) for their kind support during the fieldwork conducted at the UJ in Amman and Zina Nimeh and Zaid Eyadat for their help in selecting and contacting experts and for the support provided during the interviews. Special thanks go to Lucio Esposito for his suggestions during the preparation of the questionnaires and to Achin Chakraborty for precious comments. We are very grateful to the STAT-TEAM (Alberto Cardaci, Francesca Gatti, Toa Giroletti and Francesco Maffoni) for the precious research assistance on data analysis. Helpful comments have been received by the participants at the 2010 HDCA Conference in Amman.
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Variable map for the composite multidimensional poverty index
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Chiappero-Martinetti, E., von Jacobi, N. (2012). Light and Shade of Multidimensional Indexes. In: Maggino, F., Nuvolati, G. (eds) Quality of life in Italy. Social Indicators Research Series, vol 48. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-3898-0_5
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