Alkire Foster Research Articles

Social Policy and Programs Focused on Children in Peru (2010-2014): An Evaluation Based on the Multidimensional Poverty Index

During the first decade of the new Millennium, the economic growth of Peru was impressive. According to the official statistics, the monetary index decreased dramatically. However, in 2011 a new government was elected because the gains of the economic boom was not tangible for the poorest and it was necessary a more inclusive approach of the economic and social policy. In this context, the government allocated US$3 mm dollars per year of public budget to social programs focused on children. This paper is an evaluation of the Peruvian government social expenditure focused on children. This issue is studied from two perspectives. On the one hand, the Multidimensional Poverty Index, based on Alkire Foster (2007) methodology has been applied to the LSMS (2010-14) taking into consideration the different age groups of children, ethnic groups and geographical dominium. On the other hand, the social public expenditure focused on the main 6 government programs targeted on children has been analyzed based on data from the Integrated Financial Web System hosted by the Ministry of Economics and Finance. The primary findings of the paper draw the attention that the Peruvian public policy has implemented a regressive approach of the public social expenditure focused on children. Meanwhile many of the new law and policy instruments (2010-14) followed children rights approach, the public management allocated resources not taking into consideration of multidimensional poverty, vulnerability of ethnic groups and level of rurality. Moreover, a comparison of the monetary and multidimensional poverty indexes in Peru (2010-14) focused on children showed critical gaps of size of children population group. This gap might explain the fact that important part of the under-18 year old population was non-visible for the policymakers and economic managers. Thus, the lack of proper measurement of the real level of poverty of children could be misleading the allocation and use of public resources in Peru (2010-14). As a result, social conflicts at sub-national level in Peru could be nurturing.

Education Poverty in Pakistan: A Spatial Analysis at District Level

This study aims, first to construct an education poverty index (EPI) for Pakistan using household data; second, to investigate the spatial differences of education poverty (EP) at district level; and third to find the socio-economic determinants of EP. Four different dimensions are used to construct EPI using the Alkire Foster (AF) method. The results show that 26 per cent households are below the poverty cut-off in Pakistan. The ratio is high in rural area of Pakistan (33 per cent) as compared to urban areas of Pakistan (12 per cent). Similar trend has been observed across all provinces. The majority of the households are deprived in terms of cost of education. Empirical analysis shows that various socio-economic variables such as income, regional variation and awareness play very important role in explaining EP. To eradicate education deprivation, area- and dimension-specific policies are required to make efficient use of scarce resources.

STUDI KOMPARASI KEMISKINAN DI INDONESIA: MULTIDIMENSIONAL POVERTY DAN MONETARY POVERTY

Research on poverty has long been done by various methods and approaches. Approach to identifying the poor in general by calculating consumption expenditure or income reveneu. The calculation is then known as monetary poverty. Indonesia also use and implemented that approach. However, some experts believe that monetary poverty approach does not capture the whole cause of poverty because the indicator calculation not enough. Though poverty is a multidimensional phenomenon that involves not only the economic aspects but involves other aspects. Using secondary data from Indonesian family Life survey, this study proposes to calculate the multidimensional poverty index and estimates the poor based on two approaches, multidimensional poverty and monetary poverty. Calculating the poverty by alkire foster method, whereas to estimate multidimensional poverty and Monetary Poverty using logistic regression. The Results for Alkire-Foter calculation method show that identify of poor by multidimensional poverty greater than the monetary poverty. Generally, the standard of living dimension contributes most to the multidimensional poverty index. Standar living dimention was believed to be the dimension that explains the nature of households that are directly related to the everyday household behavior. Meanwhile, estimation of monetary poverty show that variable consumption per capita, the head of the household sector employment, hours of work, household size and household asset ownership affects the identification of poverty. Only education variable is not significant effect on the identification of poverty. Base on those finding, education has two possibilities to affect poverty one significant affect multidimensional poverty, while for monetery hasn't affect.Keywords: Multidimensional poverty, Monetary Poverty, Alkire-Foster Method, Logistic Regression

Considering the Extremely Poor: Multidimensional Poverty Measurement for Germany

This paper applies the Alkire and Foster (J Public Econ 95:476–487, 2011) index of multidimensional poverty to German data. This is done with respect to the politically most important dimensions of poverty mentioned in the German Federal Government’s report on poverty and wealth. Additionally, a modification of the identification step of the Alkire–Foster index is proposed to guarantee that individuals, who are extremely poor in only few dimensions, are not omitted by the index.

The breadth and depth of multidimensional child poverty in China

This study analysed the multidimensional child poverty status in China between 1989 and 2009, using the China Health and Nutrition survey data. Based on the Alkire–Foster method for measuring poverty, a multidimensional poverty index was calculated and further decomposed into seven deprivation dimensions: nutrition, water, sanitation, health, education, shelter and information. The study has four main findings: (1) The multidimensional child poverty rate in China declined gradually where the sanitation facility was most severely deprived; (2) The poverty gap between rich and poor provinces remained over the years; (3) The urban–rural disparity was reduced in all seven dimensions; (4) The poorest of the poor climbed out of ultra‐poverty and became the moderately poor or even the non‐poor.

Multidimensional Poverty in Crisis: Lessons from Zimbabwe

Zimbabwe experienced an acute social, political, and economic crisis from 2001 to 2008 and is now on a recovery path. This paper explores changes in poverty between 2001, 2007, and 2011–2012 using an Alkire–Foster multidimensional poverty index. Results indicate a large increase in poverty across multiple dimensions of household wellbeing between 2001 and 2007 (the start of the crisis peak), followed by a decrease in poverty between 2007 and 2011–2012, during the recovery period. Decomposition of the index shows significantly different trends in poverty dimensions over time with implications for short- and long-term social assistance policies.

A multidimensional child poverty index in China

This paper analyses the multidimensional child poverty status and its dynamic changes in China from 1989 to 2009 using the China Health and Nutrition survey data. Built on the Alkire–Foster methodology, the adjusted child poverty headcount ratio is calculated which measures not only the traditional headcount ratio of child poverty but also the average deprivation intensity among poor children. The overall poverty rates declined over years from 1989 to 2009 in national wide and among provinces, where the key driver was the reduction of the poverty headcount ratio. With the property of decomposition for the adjusted headcount ratio, this study also examines the provincial and regional contribution to the national poverty reduction. Provinces in the middle region of China received the biggest reduction of child poverty rate, and the regional gap of child poverty has been narrowed down, but more effort of poverty reduction should be made to the poorest provinces and rural areas.

The effect of political decentralisation and affirmative action on Multidimensional Poverty Index: evidence from Indian States

This essay examines the impact of decentralisation and political reservation for disadvantaged groups on Multidimensional Poverty Index (MPI) across states and disadvantaged minorities in India. The time variation in the implementation of the 73rd constitutional amendment across states has been exploited to analyse the impact of the amendment on multidimensional deprivation. National MPI*, similar to the standard international computed MPIs (using Alkire–Foster Methodology), has been decomposed across states and disadvantaged groups, and the effect of time variation in implementation of the amendment has then been seen on these indices. States implementing the amendment prior to 1997–1998 were found to have lower multidimensional deprivation in the year 2005, as compared to their counterparts which either implemented the amendment after 1998 or did not implement it at all. A similar impact of early implementation was seen on MPI* (of year 2005) of the disadvantaged groups that were given additional political representation under the 73rd constitutional amendment. The hypotheses, therefore, that decentralisation has a positive impact on general living standards, and that political reservation for certain classes improves the welfare indicators of members of the groups they represent, are verified by this study.

Child Poverty in Rural China: Multidimensional Perspective

This paper describes a pilot study on child multidimensional poverty in rural China by introducing the Alkire–Foster method based on survey data collected from five provinces/autonomous regions. Results showed that the headcount ratio of child multidimensional poverty was 14.29%. On average, multidimensionally poor children were deprived in 37.62% of all the dimensions, and their adjusted headcount ratio (multidimensional poverty) index was 0.054. Health was the most deprived dimension, followed by the subsistence and participation dimensions. Disabled children, children influenced by HIV/AIDS, and ethnic minority children were severely deprived. This study not only adds to the current literature on child poverty in China, but also provides policy suggestions for future action plans.

A Different Perspective on Poverty in Lao PDR: Multidimensional Poverty in Lao PDR for the Years 2002/2003 and 2007/2008

This paper presents an indicator for measuring multidimensional poverty in the Lao People’s Democratic Republic applying the Alkire–Foster methodology to the Lao Expenditure and Consumption Survey 2002/2003 and 2007/2008. We calculated a multidimensional poverty index (MPI) that includes three dimensions: education, health, and standard of living. Making use of the MPI’s decomposability, we analyse how much each of the different dimensions and its respective indicators contribute to the overall MPI. We find a marked reduction in the multidimensional poverty headcount ratio over the study period, regardless of how the indicators are weighted or how the deprivation and poverty cut-offs are set. This reduction is based on improvements regarding all indicators except cooking fuel and nutrition. We observe no significant reduction in the intensity of poverty, however; there are wide disparities between the country’s regions and between urban and rural areas. The proportion of poor people in rural areas is more than twice as high as that in urban areas. By complementing the traditional income-based poverty measure, we hope to provide useful information that can support knowledge-based decision-making for poverty alleviation.

A Multidimensional Approach to Measuring Rural Poverty in Kewet District, North Shoa, Ethiopia

This article analyses the multidimensional aspect of rural poverty in Kewetdistrict, Ethiopia using the Alkire Foster method of multidimensional povertyanalysis and Logit model. We collected primary data from 245 householdsselected through stratified and proportional random sampling procedures.Findings reveal that the poverty headcount is 0. 812 whereas the intensity andmultidimensional poverty index stand at 0.50 and 0.41, respectively. Findingsforther indicate that the greatest contribution to multidimensional poverty comesfrom deprivation in years if schooling (21. 8%) followed by deprivation in childenrollment (11. 3%) and child mortality (1 0. 5%). Thus policies aimed at targetingpoverty should consider its multidimensionality.Key words: Multidimensional poverty, deprivation, MPL Ethiopia

PHS128 - Correlation Between Multidimensional Poverty Index, Inequity In Health And Social Inequality Variables In Colombia, 2005

It was performed a diagnosis of the correlation among Multidimensional Poverty Index (MPI) (Colombian Adaptation) with quality of health services proxy variables, and inequality and poverty variables(2005). An ecological study was performed: the MPI was adapted by the Colombian government using the Alkire Foster Method of the Oxford Poverty and Human Development Initiative. The Unsatisfied Basic Needs indicator (UBNI), Gini coefficient (GC) and poverty line (PL) were obtained from National Statistics Department´s (DANE) databases. Maternal Mortality Rate (MMR) and Neonatal Mortality Rate (NMR) were estimated and standardized by age and sex, respectively. We estimated the Incidence of congenital syphilis (ICS). The Attributable Fraction (AF) was calculated as inequality indicator for these three variables: (AFMMR), (AFNMR) and (AFICS). We estimated Acute Myocardial Infarction Age-Standarized Rate (AMIASR) for each health regime. The Inequity in Health Index (IHI) was estimated. These data were estimated for each Colombian region for the year 2005, because MPI was specified in the same way for the same period. Normality was tested using the Shapiro-Wilks test. Sperman’s rho and Pearson’s rho were used according to normality. It was defined as correlated if p≤0.005, after Bonferroni adjustment. We found correlation between MPI and PL (Pearson r=-0.7748, p=0.0000); and UBNI (Spearman rho=0.8286, p=0.0000); there was not correlation with GC (Pearson r=-0.1785, p=0.4041); AFMMR (Spearman rho=0.3553, p=0.054); AFNMR (Spearman rho=0.3386, p=0.0539); AFICS (Spearman rho=–0.0543, p=0.7757); AMIASR subsidized regime, (Spearman rho=0.3032, p=0.0917), AMIASR, contributory regime, (Pearson r=0.31, p=0.1084). IHI: Spearman rho=0.3081, p=0.0811). We found correlation between MPI, PL and UBNI. There were not correlation with proxy variables in health, which suggests that MPI’s health dimension was not well adjusted for the Colombian case.

Conditions for the most robust multidimensional poverty comparisons using counting measures and ordinal variables

A natural concern with multivariate poverty measures, as well as with other composite indices, is the robustness of their ordinal comparisons to changes in the indices’ parameter values. Applying multivariate stochastic dominance techniques, this paper derives the distributional conditions under which a multidimensional poverty comparison based on the popular counting measures, and ordinal variables, is fully robust to any values of the indices’ parameters. As the paper shows, the conditions are relevant to most of the multidimensional poverty indices in the literature, including the Alkire–Foster family, upon which the UNDP’s “Multidimensional Poverty Index” (MPI) is based. The conditions are illustrated with an example from the EU-SILC data set.

Multidimensional Poverty: Measurement, Estimation, and Inference

Multidimensional poverty measures give rise to a host of statistical hypotheses that are of interest to applied economists and policy-makers alike. In the specific context of the generalized Alkire–Foster (Alkire and Foster, 2008) class of measures, we show that many of these hypotheses can be treated in a unified manner and also tested simultaneously using a minimum p-value approach. When applied to study the relative state of poverty among Hindus and Muslims in India, these tests reveal novel insights into the plight of the poor which are not otherwise captured by traditional univariate approaches.

Implementing a Multidimensional Poverty Measure Using Mixed Methods and a Participatory Framework

Recently, there have been advances in the development of multidimensional poverty measures. Work is needed however on how to implement such measures. This paper deals with the process of selecting dimensions and setting weights in multidimensional poverty measurement using qualitative and quantitative methods in a participatory framework. We estimate the multidimensional poverty measures developed by Alkire and Foster for a particular group: persons with psychiatric diagnoses in the United States. To select relevant dimensions and their relative ordering, two discussion groups are convened: one consisting of persons with lived-experience expertise and the other consisting of people with mental health service provision or research expertise. Several methods are used to convert dimension rankings into weights. The selection and ordering of dimensions differed between the two discussion groups, as did the resulting poverty measures. For instance, the poverty headcount using the dimensions and weights of the ‘lived experience’ group ranged from 20.61% to 26.96% as compared to a range of 18.62% to 33.19% using those of the ‘provider/researcher’ group. One of the main results of this study is that the Alkire Foster method is sensitive to the selection of dimensions and the methods used to derive rankings and weights. It points toward the limitation of relying exclusively on small scale qualitative methods for the selection and ranking of dimensions. In addition, the participatory framework used in this study was found to be essential in interpreting results, in particular with respect to the limitations of the data set in measuring relevant dimensions.

Implementing a Multidimensional Poverty Measure Using Mixed Methods and a Participatory Framework

Recently, there have been advances in the development of multidimensional poverty measures. Work is needed however on how to implement such measures. This paper deals with the process of selecting dimensions and setting weights in multidimensional poverty measurement using qualitative and quantitative methods in a participatory framework. We estimate the multidimensional poverty measures developed by Alkire and Foster for a particular group: persons with psychiatric diagnoses in the United States. To select relevant dimensions and their relative ordering, two discussion groups are convened: one consisting of persons with lived-experience expertise and the other consisting of people with mental health service provision or research expertise. Several methods are used to convert dimension rankings into weights. The selection and ordering of dimensions differed between the two discussion groups, as did the resulting poverty measures. For instance, the poverty headcount using the dimensions and weights of the ‘lived experience’ group ranged from 20.61 to 26.96% as compared to a range of 18.62–33.19% using those of the ‘provider/researcher’ group. One of the main results of this study is that the Alkire Foster method is sensitive to the selection of dimensions and the methods used to derive rankings and weights. It points toward the limitation of relying exclusively on small scale qualitative methods for the selection and ranking of dimensions. In addition, the participatory framework used in this study was found to be essential in interpreting results, in particular with respect to the limitations of the data set in measuring relevant dimensions.

A comment on multidimensional poverty indices

The three papers on multidimensional poverty published in the 2011 June issue of the Journal of Economic Inequality [1–3] present strong cases in favor of their respective methodologies to capture and measure well-being and poverty. Ultimately the choice of preferred indicators, whether unidimensional or multidimensional (and, in the latter case, which dimensions to incorporate in such indicators), depends ultimately on the purposes they should serve. Money-metric (income or consumption based) poverty measures have been useful to the World Bank in estimating approximately the magnitude of global poverty as well as individual regions’ and countries’ progress towards the reduction of poverty. The Human Development Index has provided the development community with a broader measure of well-being—adding health and educational dimensions to income—and demonstrating that the correlation between the monetary and non-monetary dimensions of poverty within and across countries was far from perfect. Finally, multidimensional indicators such as the Alkire-Foster (A-F) measure respond to an effective demand for scalar estimates of poverty that could be used by policymakers in the allocation of funds to reduce poverty in an efficient and equitable way. Hence, notwithstanding their shortcomings, each of these indicators fulfills somewhat different yet important functions. A strong feature of the A-F methodology is that it is anchored on the joint distribution of the various dimensions of well-being and the resulting deprivations that poor people experience. It is therefore essential that all data come from the same household survey. It should be noted that this means that any given household information is available not only on possible deprivations in some dimensions but also on possible surpluses over and above the deprivation thresholds in other dimensions. This immediately raises the issue of possible trade-offs among dimensions.

Measuring Multidimensional Poverty in India: A New Proposal

This paper focuses on the methodology by which India’s 2002 Below the Poverty Line (BPL) census data identify the poor and construct a BPL headcount. Using the BPL 2002 methodology and NFHS (National Family Health Survey) data, it identifies which rural families would have been considered BPL were NFHS (National Family Health Survey) data used. It compares these to poor families that would be identified using the same variables with the Alkire Foster multidimensional poverty methodology. It finds that up to 12 per cent of the poor sample population and 33 per cent of the extreme poor could be misclassified as non-poor by the pseudo-BPL method. The paper also develops a sample Index of Deprivation that responds to criticisms regarding BPL data. We compare these results with income poverty and with pseudo-BPL status for sample respondents and disaggregate the index by state and break it down by dimension.

Poor, Multidimensionally Speaking: Evidence from South Africa

There is an expanding literature on multidimensional poverty measurement. Even though the theoretical foundations of the field are well developed, there are only a few empirical papers on developing countries, especially on the comparison of different measures. This paper applies a decomposable multidimensional measure developed by Alkire and Foster (2007) to a cross-sectional dataset on South Africa. This measure allows for decomposition of final outcome into the dimensions used. Furthermore, South Africa provides an interesting case study as the country is renowned for its high income-inequality rate. The contribution of the paper is to draw significant policy implications when a decomposable multidimensional measure is used as opposed to measures that are either multidimensional but not dimensionally decomposable or unidimensional. Specifically, it evaluates the current policy-making mechanism in South Africa at the provincial level and suggests alternative revenue-allocation schemes by using the Alkire–Foster measure.