Category Archives: Publications

Does Aid Reduce Poverty?

Fifty years of literature on aid effectiveness has so far proven inconclusive. Two main challenges still require some attention. The first is to properly identify the causal effect of aid on poverty alleviation. To address it, I exploit differences in the number of years countries have been temporary members of the United Nations Security Council as an instrument for the average amount of economic aid disbursed by the United States. The second is to obtain reliable data on poverty, which I confront by using multidimensional poverty data from the Oxford Poverty and Human Development Initiative (OPHI). For a sample of 64 developing countries, I estimate a significant relationship between higher amounts of aid received during the period 1946–1999 and lower Multidimensional Poverty Index (MPI) between 2000 and 2014. On the contrary, the relationship does not seem to be significant when poverty is measured from an income perspective. Alternative measures of poverty could help improve the understanding of the relationship between development aid and poverty alleviation and might also contribute to improved targeting for aid disbursements.

Citation: Milovich, J. Y. (2018). ‘Does aid reduce poverty?’, OPHI Working Paper 122, University of Oxford.

Assessing Deprivation with Ordinal Variables: Depth Sensitivity and Poverty Aversion

The challenges associated with poverty measurement within an axiomatic framework, especially with cardinal variables, have received due attention during the last four decades. However, there is a dearth of literature studying how to meaningfully assess poverty with ordinal variables, capturing the depth of deprivations. In this paper, we first propose a class of additively decomposable ordinal poverty measures and provide an axiomatic characterisation using a set of basic foundational properties. Then, in a novel effort, we introduce a set of properties operationalising prioritarianism in the form of different degrees of poverty aversion in the ordinal context, and characterise relevant subclasses. We demonstrate the efficacy of our methods using an empirical illustration studying sanitation deprivation in Bangladesh. We further develop related stochastic dominance conditions for all our characterised classes and subclasses of measures. Finally, we elucidate how our ordinal measurement framework is related to the burgeoning literature on multidimensional poverty measurement.

Citation: Seth, S. and Yalonetzky, G. (2018). ‘Assessing deprivation with ordinal variables: depth sensitivity and poverty aversion’, OPHI Working Paper 123, University of Oxford.

Multidimensional Poverty Reduction in India 2005/6–2015/16: Still a Long Way to Go but the Poorest Are Catching Up

This paper assesses the change in multidimensional poverty in India from 2005/6 to 2015/16 using data from the NFHS-3 and NFHS-4 surveys. Estimates of changes are disaggregated by age cohort, state and by socio-economic group-level, and broken down by indicator; sampling errors are considered throughout. Multidimensional poverty is defined using the global Multidimensional Poverty Index 2018 (Alkire and Jahan 2018).  The paper finds a very strong reduction, indeed a halving of the MPI during that decade. Furthermore, subnational patterns of poverty reduction are strongly pro-poor, whereas from 1998/9 to 2005/6 they had been regressive. The reductions of MPI are hardly correlated with state level growth in GDP, making this a rich terrain for future research. District level analyses in 2015/16 only document extensive ongoing intra and interstate variation. These explorations confirm that at the end of the decade under study, at least 271 million fewer persons were living in multidimensional poverty – a magnitude of change rivalling the numbers exiting monetary poverty in China.

Citation: Alkire, S., Oldiges, C. and Kanagaratnam, U. (2018). ‘Multidimensional poverty reduction in India 2005/6–2015/16: still a long way to go but the poorest are catching up’, OPHI Research in Progress 54a, University of Oxford.

Towards a Global Assets Indicator: Re-assessing the Assets Indicator in the Global Multidimensional Poverty Index

This paper explains the revision of the assets indicator of the updated global Multidimensional Poverty Index (global MPI), which was launched just before the 73rd Session of the United Nations General Assembly in September 2018. The joint decision of the United Nations Development Programme (UNDP) and the Oxford Poverty and Human Development Initiative (OPHI) to revise the global MPI in 2018 to align it with the Sustainable Development Goals and to best monitor progress towards “leaving no one behind” provided the opportunity to assess the statistical validities of the assets indicator contained in the Original MPI, jointly designed by OPHI and UNDP Human Development Report Office (HDRO) in 2010, and an assets indicator included in an Innovative MPI, which was developed by UNDP HDRO in 2014. Further, considering the improvements in many Demographic and Health Surveys, Multiple Indicators Cluster Surveys and selected national surveys in recent years, from which the global MPI is constructed, the revision also offered an occasion to assess whether the inclusion of additional assets would add value to a revised asset index for the updated global MPI 2018. Taking into account a blend of inputs, including statistical test results, public consultations, normative reasoning and substantive trial measures of possible asset indices as outlined in detail in this paper, the revised assets indicator maintained the structure of the Original MPI, but added computer and animal cart as additional items. Here we explain the reasons and delineate the many decisions that were taken along the way.

Citation: Vollmer, F. and Alkire, S. (2018). ‘Towards a global asset indicator: re-assessing the asset indicator in the global Multidimensional Poverty Index’, OPHI Research in Progress 53a, Oxford Poverty and Human Development Initiative, University of Oxford.

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The New Global MPI 2018: Aligning with the Sustainable Development Goals

Early in 2018, the United Nations Development Program’s Human Development Report Office (HDRO) and the Oxford Poverty and Human Development Initiative (OPHI) agreed to adjust and unify their methodologies on poverty measurement and consider indicator improvements, in order to better monitor the Sustainable Development Goals (SDGs).

This paper sets out the specifications of a joint global Multidimensional Poverty Index first published in 2018, which is an internationally comparable measure of acute poverty that captures the multiple deprivations poor people experience with respect to health, education and living standards.  It builds on the original MPI launched in 2010, and an innovative MPI launched in 2014. The best features of both of these are subsumed in the joint global MPI 2018, which also reflects new data possibilities to better align the global MPI to the Sustainable Development Goals.

Because the objective of revising the MPI to create a more credible and legitimate measure of multidimensional poverty that enables comparisons across countries using existing data was challenging to realize, the paper first sets out five key principles for a global poverty measure related to data coverage, communicability, comparability, disaggregation, and robustness.

Drawing on expert interventions, a global consultation, empirical trials, and these principles, the paper then explains conceptually the motivation and nature of adjustments that were made to five of the ten included indicators. It also recognizes desirable changes that could not be made due to data constraints – for example including data on the environment, work, and security, or on intrahousehold inequalities. And it identifies key issues for future research related to household composition and the use of land and livestock variables.

Citation: Alkire, S. and Jahan, S. (2018). The New Global MPI 2018: aligning with the Sustainable Development Goals’, OPHI Working Paper 121, University of Oxford.

On Data Availability for Assessing Monetary and Multidimensional Poverty

Data availability plays a crucial role in the fight against poverty. Yet, it lags behind the data available on most other economic phenomena. We catalogue and review existing data availability aiming to break the cycle of outdated poverty data. We identify countries that generate and analyse frequent and accurate poverty data to highlight potential improvements. Results show, data for both monetary and multidimensional poverty dramatically increased since 1980. Sixty countries now produce annual datasets, while internationally comparable short surveys and regional harmonised variable definitions are being implemented. These existing resources and experiences can inform much-needed efforts to expand data availability.

Citation: Alkire, S. and Robson, M. (2018). ‘On data availability for assessing monetary and multidimensional poverty’, OPHI Research in Progress 52a, University of Oxford.

Evaluating the Effects of Housing Interventions on Multidimensional Poverty: The Case of TECHO-Argentina

The objective of this paper is to evaluate the effect of the NGO TECHO’s emergency housing programme on multidimensional poverty. It employs a quasi-experimental ‘pipeline’ evaluation design and is based on household survey data from 34 informal settlements in Buenos Aires, Argentina. The aim is to demonstrate the additional insights that can be gained from using a multidimensional framework based on the Alkire and Foster (2011) method to evaluate a programme’s impact. The results indicate that the programme reduces both the incidence and the intensity of poverty and causes the multidimensional poverty measure to fall by more than half. The magnitude of the effect is greater for the households that initially were the poorest. Privacy, interpersonal relations and psychological health are the dimensions that contribute the most to explaining the decline in multidimensional deprivation.

Citation: Mitchell, A. and Macció, J. (2018). ‘Evaluating the effects of housing interventions on multi­dimensional poverty: the case of TECHO-Argentina’, OPHI Working Paper 120, University of Oxford.

The Research Agenda on Multidimensional Poverty Measurement: Important and As-yet Unanswered Questions

The application of multidimensional poverty measures is proliferating, in part due to the emphasis in Goal 1 of the Sustainable Development Goals (SDGs) on ending poverty in all its forms and dimensions.  This paper first traces the emergence of a priority for non-monetary poverty measures in key texts that consid­ered then set out the SDGs. It then outlines some vital and feasible research questions on a sub-set of fascinating empirical topics on counting-based multidimensional measures. The topics covered here relate to the SDGs’ focus on measuring the multidimensional poverty of men, women, and children. Building on the existing literature, fascinating questions remain in terms of measurement design (the selection of dimensions, indicators, cutoffs, and weights), the analysis of multidimensional poverty measures, their application to child poverty and their implementation using gendered data. In each of these areas, it is expected that significant breakthroughs are possible.

Citation: Alkire, S. (2018). ‘The research agenda on multidimensional poverty measurement: important and as-yet unanswered questions’, OPHI Working Paper 119, University of Oxford.

Multidimensional Poverty Measures as Relevant Policy Tools

Poverty measurement is strewn with imperfection. And yet, even understanding limitations such as data quality and coverage, measures of multidimensional poverty have proven to be relevant policy tools. This paper first situates muldimensional poverty measures in the Sustainable Development Goals, which seek to End Poverty in all its forms and dimensions (italics added). It then explains a key distinguishing feature between multidimensional and monetary poverty measures, namely, that multidimensional poverty measures have an associated ‘information platform’ which provides the deprivations in each indicator, as well as the headcount ratio or poverty rate, and the intensity of poverty overall, and does so both nationally and for all groups by which the dataset can be disaggregated. Furthermore, multiple poverty lines are often set and reported. Bearing this informational richness in mind, the paper then canvasses the main ways that policy actors are using multidimensional poverty indices (MPIs) and their associated informational platform to shape policy. For example, a permanent official MPI complements the national monetary poverty measure, often drawing attention to different groups of poor persons. Also, the MPI design often includes participatory exercises and expert consultations, thus catalysing a national conversation about what is poverty. Like any national statistic, the MPI is used to monitor change and show the trend in a phenomenon of public importance. Further, the MPI, with its disaggregation by group and breakdown by indicator, is often used as part of the budget allocation formulae, for example, across subnational regions. The MPI is also used for targeting in two senses: targeting the poorest areas or social groups, and also (using a different dataset), targeting households that are eligible to benefit from certain schemes. One of the most powerful roles of the MPI is to support policy coordination which – in line with the SDG emphasis – facilitates integrated multisectoral policies that can be more cost-effective and high-impact methods for addressing interconnected deprivations and managing change. Finally, for many countries, the MPI is part of a new emphasis on the transparency and accountability of statistics, for example by posting data tables, or even datasets and computer algorithms online so students and researchers can fruitfully join the intellectual task of finding better ways to confront human disadvantage and suffering. The paper closes by referring to some new research areas that might further enrich this unfolding discipline.

Citation: Alkire, S. (2018). ‘Multidimensional poverty measures as relevant policy tools’, OPHI Working Paper 118, University of Oxford.

Statistical Note: Disaggregating Bhutan’s MPI 2017 by Disability Status

Since 2010, Bhutan has used a Multidimensional Poverty Index (MPI) alongside consumption poverty to measure and fight poverty in all its forms and dimensions. Bhutan’s National MPI was updated on 2012 and 2017 using the Bhutan Living Standards Survey (BLSS). In 2017, the BLSS questionnaire included questions on disability status. This statistical note shows different ways by which the MPI can be disaggregated using the available information. Each way is implemented, and the results analysed. Thus, by presenting worked out empirical examples, we hope to contribute to the evolving methodological discussions of how best to disaggregate poverty measures including the MPI by disability status. In addition, we hope to contribute to robust and detailed understanding in Bhutan of the relationship between poverty and disability status, hence to inform policies that seek to address both. However, survey data are limited, and so, very importantly, we also advise re-running these results with the 2017 census data for a more precise picture. It is hoped this note will provide some structure for a census-based analysis.

Citation: Pinilla-Roncancio, M. and Alkire, S. (2018). ‘Statistical note: disaggregating Bhutan’s MPI 2017 by disability status’, OPHI Research in Progress 51a, University of Oxford.