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The multi-dimensionality of an index of human development, of poverty, or of any other social phenomenon, is always a welcome approach, since it takes into account factors that affect the well-being of the population. The High Commission for Planning (HCP), itself, developed in 2008 a multidimensional approach of poverty, remaining convinced, however, that the choices that such approaches imply remain debatable (see Annex 1). The HCP Standard of Living Index ( INV), developed by the High Commission for Planning on the basis of a data base collected via surveys on households’ standard of living and consumption (see annex). The INV measures multidimensional poverty. It covers access to education, health (medical-health coverage and consultation), healthy and balanced nutrition (drinking water availability, decent nutrition (according to the WHO-FAO standards) and sustainable self-protection from food poverty), housing conditions (decent housing, equipped with electricity, liquid sanitation, refrigerator, bath/shower, kitchen, toilet and stove), vocational integration represented by the economic activity of the household’s members and employment opportunities for young people, social equity and gender equality, respectively measured by the position in the social ladder of the standard of living and gender equality in terms of education- training, health care, and access to means of communication and transportation (see www.omdh.hcp.ma). As for Oxford Poverty and Human Development Initiative Center (OPHI), it has developed a multidimensional poverty index (MPI) published in a report entitled "Acute Multidimensional Poverty a new index for developing countries (see Annex 2). This work was authored by Sabina Alkire and Maria Emma Santos of the OPHI Research Centre, on the basis of an approach designed in 2007 by James Foster and Sabina Alkire. Tailored on the basis of demography and health surveys (DHS), aiming to analyze health situation rather than the extent of poverty, the OPHI index is constrained by data limitations, as admitted by its own authors (page 7 of the Report), and faces, according to WB experts (www.oxfamblogs.org), empirical and analytical limitations (see Appendix 5). It raises the following comments: 1. The dimensions included in the calculation of the Multidimensional Poverty Index are, by their multiplicity, certainly advantageous. Still, they do not cover all socio-economic priorities, including those that develop the capability of individuals to self-protect themselves from poverty. They are limited to ten indicators pertaining to health (infant mortality and nutrition), basic education and access to electricity, drinking water, sanitation, and some household durables (see Annex 2). Their choice was dictated by constraints linked much more to the nature of data collected by the Demography and Health Surveys than to the priorities and aspirations of the population. Besides, only output indicators are identified by this index. The input indicators that measure the ability of the population to be self-sustained are all excluded. This applies to income factors such as employment, social security insurance or access to road network and financing means. 2. The variables on which the measurement of the Multidimensional Poverty Index is based become problematic when poverty is put in a dynamic approach. For example, a malnourished child contributes with 1.67 to the value of the household deprivations. If this child is aged between 6 and 14 years and has never attended school, the value of household deprivation shall increase by 1.67. Thus, it amounts to a total of 3.34 (1.67 + 1.67). The approach does not assign this value (3.34) to the child alone but to all those who live with him under the same roof. Since this value (3.34) exceeds the poverty line, the value of which is arbitrarily fixed at 3, the child and the rest of the household members are all classified as poor, regardless the resources they have. Furthermore, when this child is 15 years old, he shall no longer be concerned by the variable of "Education of children between 6 and 14 years." That is to say that his non-education is no longer sanctioned by an increase, of 1.67, of the value of the household deprivation. This value is then reduced to 1.67 (3.34 - 1.67), below the poverty line, and, therefore, the whole household shall no longer be classified as poor. Such approach does not allow us, in any case, to understand the dynamics of poverty, nor to analyze its determinants. 3. Like all multidimensional approaches, the measurement of poverty according to the Multidimensional Poverty Index is based on a subjective threshold and does not take into consideration, therefore, comparisons with the monetary approach, the threshold of which is determined objectively. In addition to the aforesaid limitations, there is the subjective nature of the poverty line, arbitrarily set at 30%, admitted by the MPI authors themselves. This makes groundless any comparison of poverty rates according to the MPI with those based on monetary approaches. Indeed, 23 among the 55 countries, better ranked than Morocco, have a poverty rate of U.S. $ 2 PPP significantly higher than the Moroccan poverty rate. Similarly, 18 countries better ranked than Morocco have a level of inequality higher than Morocco’s. 4. Data reference periods range from 2000 to 2008, making the classification of countries according to the Multidimensional Poverty Index groundless. The reference years of surveys/data sources differ from one country to another and do not, in any way, classify countries according to this index level. For instance, the adopted classification compares Morocco in 2004 to Egypt in 2008 and Jordan in 2007. All efforts made by Morocco, between 2004 and 2008, in terms of human, economic and social development and also in terms of production of current statistics are thus omitted for the simple reason that the last Demography and Health Survey conducted in Morocco is dated 2004. The 2009 MDG national report provides recent data on the basic dimensions of the Multidimensional Poverty Index. It underlines that the new data sources available in Morocco (the Demographic Survey of 2009 and the survey on the standard of living 2007) allow to update this index. In terms of data availability, only 61 among the 104 countries concerned have data on the 10 used indicators. For the remaining countries, the missing indicators are replaced by the, lower or higher, bounds of variables or their proxies. 5. The application, itself, of the OPHI multidimensional poverty approach to Moroccan data gives similar results to those calculated by the HCP approach (see table in Annex 3). The OPHI approach applied to Moroccan survey data shows that poverty declined from 28.5% in 2004 to 11.1% in 2007. According to the HCP multidimensional approach, poverty declined from 23.9% in 2001 to 12.1% in 2007. This means that the decline in poverty rates is confirmed by both approaches. Oxford Poverty Human Development Initiative relies on data collected in 2004 instead of that relative to 2007, which means that the results of the OPHI approach do not reflect the current level of poverty in Morocco. Measured by the monetary approach according to the national threshold (U.S. $ 2.15 PPP), poverty also declined from 15.3% in 2001 to 8.9% in 2007. In short, the lack of variables and data on which the OPHI poverty approach is based proves that it cannot substitute objective approaches of international institutions. It is less relevant than the HCP’s approach. In any case, it cannot be used in the ranking of developing countries, unless it is based on the same reference period and unless it is subject to discussions and debate within the ECOSOC’s Statistical Commission, the sole UN body in charge of validating data and statistical methodology, as recommended by the UN Panel on human development indicator. ANNEXES Annex 1: HCP multidimensional poverty approach The measurement of Standard of Living in Morocco is based on dimensional monetary indicators. These indicators measure the consumption and/or income per capita and highlight only financial resources available to households. Other factors determine well-being, in addition to these resources. They are also related to the development of human capabilities (education and health) and sustainable self-protection vis-à-vis social hardships, and to the quality of life represented by housing conditions, environment, security, social equity, gender equality, etc. The multidimensional approach of the standard of living, based on the monetary and non-monetary attributes of the conditions of life, could be considered as an alternative to the monetary approach; since it takes into account the different quantitative and qualitative dimensions of well-being, and prioritizes those related to the population’s basic needs. The High Commission for Planning refers to the poverty multidimensional approach precisely in order to remedy to the analytical shortcomings of the one-dimensional monetary indicators. This approach is based on the factorial analysis of the multiple correspondences (ACM) -optimal coding option- to construct a composite index of the standard of living. Aggregating a series of welfare indicators, this index is a multidimensional measurement of the standard of living and multidimensional poverty. Methodology and data sources The most appropriate statistical method to calculate the weight of the variables that define a composite index of standard of living is the factorial analysis of the multiple correspondences (ACM) - optimal coding option. It also has the advantage of giving each household a coefficient depending on its position in the first factorial axis (more than 63% of the total inertia). The functional form of this coefficient is defined as follows considering m : index of a given household and cm : its own value : Where K : number of categorical indicators; Jk : number of modalities of the indicator K; : weight of the category Jk; : binary variable taking the value 1 when the unit (household) has the category Jk and 0 otherwise. Selection of modalities relative to the key variables of the composite index of the standard of living is based on the ACM applied to the samples in a 'cross section' of consumption surveys in 2001 and the standard of living of households in 1991 and 2007, realized by the High Commission for Planning on representative samples at the national, urban and rural scales. Results The main obtained applying ACM are related to the dimensions of multidimensional poverty in Morocco and the evolution of the composite index of the standard of living. Multidimensional poverty dimensions The multiple correspondences’ analysis provided the parameters based on the selection of variables involved in the construction of the composite index of the standard of living. The main criterion used to reduce the number of variables without losing the overall substantial consistency is the criterion of the ordinal explicative power of the first factorial axis. The variables that have this property are those that comply with the rule according to which well-being deteriorates from a position of wealth to a situation of poverty throughout this axis. This axis opposes two household profiles defined by the index of the standard of living: the first one includes the poorest households in terms of the standard of living, including households whose heads of family are illiterate, more than three quarters of their members have no educational abilities, deprived from access to health care and have no medical-health insurance, their children suffer from stunted growth, live in precarious housing units, with no connection to drinking water, electricity and liquid sanitation and equipped with neither basic comfort elements nor household durables, live in poverty in general and suffer from food poverty in particular. On the other hand, households with the highest composite index of the standard of living are lead by a literate person, their members have access to education and training and have a medical-health insurance, they live in villas, connected to water and electricity networks, have comfort elements and household durables and spend on food alone the equivalent of four times the poverty line. We conclude that households’ budgetary resources are only one component of the standard of living in Morocco and that the condition of being of the population is the result of non-monetary, quantitative and qualitative, factors. Given the available data and ACM parameters, any composite measurement of the standard of living is more appropriate in the Moroccan context that incorporates the following dimensions , namely: 1. Knowledge: education, training and literacy of the general population and younger generations in particular; 2. health measured by the health and medical coverage and consultation following an illness; 3. healthy and balanced nutrition: supply of drinking water, decent nutrition (according to WHO/FAO standards) for children and adults, and sustainable self-protection from nutrition poverty; 4. ensuring viable environment characterized by living in decent housing units equipped with electricity, liquid sanitation, refrigerator, bath / shower, kitchen, toilet, cooker, etc.; 5. vocational integration: economic activity of households’ members and employment opportunities for young people in particular; 6. social equity and gender equality, measured by the position in the social scale and gender equality in terms of education, training and health care; 7. communication means (TV, mobile phone...) and means of transportation. In short, only indicators adopted within the framework of MDGs are analytically similar to the Standard of Living Index (INV). This index introduces new dimensions in the evaluation of well-being conditions of. Still, it leaves little other binding or widely distributed dimensions (the case of vaccination). It can be used in all quantitative and qualitative analysis of the living standard, knowing that the level at which it is established (between 8 and 12% in 2007), does not matter vis-à-vis the trend it registers, particularly because of the subjectivity of poverty lines and changes that intervene in the value of the dimensions that make this type of poverty approaches. Annex 2: Presentation of Oxford Poverty and Human Development Initiative’s multidimensional poverty approach Methodology: The index is composed of 10 indicators representing three human development dimensions. Thus, a household is considered to be in deprivation; • in terms of education: 1. if none of its members completed five years of education. 2. if one of its children in school age does not attend school from the first to 8th grade • in terms of health 1. if one of its children is deceased 2. if one of its members is malnourished. • in terms of the standard of living 1. if the household has no electricity. 2. if it does not have access to clean water within 30 minutes of walk from home. 3. if it has no toilet or has a shared toilet. 4. if the floor of its house is dirty, with sand or manure. 5. if it cooks using wood, coal or manure. 6. If it has no car or tractor and does not have at least two of the following items: radio, television, telephone, bicycle, or motorcycle. Health and education indicators have a weight of 1/6 each and 1/18 for those relative to the standard of living. Thus, each dimension of the three dimensions has a weight of 1/3. Definitions • A household is considered poor if the weight of the indicators from which it is deprived exceeds 30%. • The intensity of poverty is the average number of deprivations. • The index of multidimensional poverty is the product of poverty rates by intensity. Results This methodology has been applied to 104 developing countries for which data exist and came up with a total number of poor people in these countries of 1.7 billion instead of 1.3 calculated by the WB approach, based on $ 1.25 per day. As far as Morocco is concerned, this approach was applied to the available data of the Demography Health Survey realized among a sample of 12,000 households by the Ministry of Health in 2003/2004 (field collection lasted from October 2003 to February 2004). Annex 3: Poverty rates of the different multidimensional approaches according to the residence area In% Year HCP Approach Oxford Approach Environment Urban Rural National Urban Rural National 1991 -/- 1992 10,4 55,7 36,5 25,8 84,3 58,3 2001 -/- 2003-04 9,4 42,3 23,9 -- -- 28,5 2006/07 7,4 18,3 12,1 2,8 21,9 11,1 NB: Calculations based on data collected from the national surveys on the standard of living in 1991/92 and 2006/07, the national survey on households’ consumption expenditure in 2000/01, and 2003/04 survey on the demography and health. Annex 4: The objectives of the Demography and Health Survey (2004) The National Survey on Population and Family Health (EPSF) conducted in Morocco in 2003-2004 aimed mainly to:  collect data to calculate demographic rates, particularly rates of fertility and infant and child mortality according to the residence area; urban/rural, and by region;  collect data on vaccination coverage among children and the coverage of supervised births according to the residence area; urban/rural, and by region;  measure the rates of contraceptive use by method and according to the residence area; urban/rural, and by region;  collect data on fertility preferences, including unmet needs regarding to contraception;  collect data on women’s chronic diseases, family health and reproductive health;  collect data on the prevalence and treatment of diarrhea and other diseases among children under five years. Annex 5: Criticisms of the OPHI approach expressed by World Bank’s experts The MPI is a composite of indicators selected for consistency with the UNDP’s famous Human Development Index (HDI). The HDI uses aggregate country-level data, while the MPI uses household-level data, which is then aggregated to country level. The index has ten components; two represent health (malnutrition, and child mortality), two are educational achievements (years of schooling and school enrolment), and six aim to capture “living standards” (including both access to services and proxies for household wealth). The three broad categories–health, education, and living standards–are weighted equally (one-third each) to form the composite index. The MPI’s six “living standard” indicators are likely to be correlated with consumption or income, but they are unlikely to be very responsive to economic fluctuations. The MPI would probably not capture well the impacts on poor people of economic downturns (such as the Global Financial Crisis) or rapid upswings in macro-economic performance. The precise indicators used in the MPI were not in fact chosen because they are the best available data on each dimension of poverty. Rather they were chosen because the methodology used by the MPI requires that the analyst has all the indicators for exactly the same sampled household. So they must all come from one survey. There is much better data available on virtually all of the components of the MPI, but these better data can’t be used in the MPI since they are only available from different surveys. This aspect of their methodology greatly constrains the exercise. There is a deeper concern about the MPI, which holds even if the best data all came from just one survey. The index is essentially adding up “apples and oranges” without knowing their relative price. When one measures aggregate consumption, one relies on economic theory, which says that (under certain conditions) market prices provide the correct weights for aggregation. We have no such theory for an index like the MPI. A decision has to be taken, and no consensus exists on how the multiple dimensions should be weighted to form the composite index. As the HDI, the weights chosen by the analyst may be challenged, and may be unacceptable to many people. How can one contend (as the MPI does implicitly) that the death of a child is equivalent to having a dirt floor, cooking with wood, and not having a radio, TV, telephone, bike or car? Or that attaining these material conditions is equivalent to an extra year of schooling (such that someone has at least 5 years) or to not having any malnourished family member? These are highly questionable value judgments. Sometimes such judgments are needed in policy making at country level, but we would not want to have them buried in some aggregate index. Rather, they should be brought out explicitly in the specific country and policy context, which will determine what trade off is considered appropriate; any given dimension of poverty will have higher priority in some countries and for some policy problems than others. Poverty is indeed multidimensional. But it is not obvious how a composite multidimensional poverty index such as the MPI contributes to better thinking about poverty, or better policies for fighting poverty. Being multidimensional about poverty is not about adding up fundamentally different things in arbitrary ways. Rather it is about explicitly recognizing that there are important aspects of welfare that cannot be captured in a single index.”