August 23–27, 2021, from 13:30 to 16:30 BST | Online
“To turn a corner on poverty, commitments at the highest levels are essential.”
Sabina Alkire, Director of OPHI & Juan Manuel Santos, Nobel Peace Prize Laureate and Former President of Colombia – Project Syndicate, July 29, 2020
This inaugural OPHI Executive Education Programme focuses on providing senior government officials and high-level policymakers with practical knowledge and direct access to the world’s leading experts on multidimensional poverty reduction, to deepen their understanding of the MPI as a policy tool and many of its potential uses, as well as their driving strategies.
Through 15 hours of interactive lectures, workshops, conversations with global leaders, and practitioners’ panels, the 5-day programme will leverage open discussions and high-level networking with fellow policy makers from around the world. Discussions will be guided by practical cases that require analysis and presenting solutions to real-world problems. Participants will also have the opportunity to meet with leading experts during office hours outside the programme schedule to discuss topics of mutual interest.
By the end of the programme, participants will be able to:
We are delighted to be joined by:
The Leaders Programme is aimed at senior professionals with a strong interest in multidimensional poverty and a capacity for influencing public policy priorities at an international, national, subnational, and institutional levels. This includes decision makers in the highest levels of a ministry, secretariat, agency, commission, or multilateral organization, in roles such as minister, deputy minister, permanent secretary, director general, secretary general, executive director, department head, or equivalent.
The programme will be delivered in English, via Canvas and Zoom. Please see below the system requirements to run these platforms:
Canvas system requirements
Zoom system requirements
£1,500
The first cohort of the programme will receive a special rate of 1,500 GBP per person that considers the context of COVID-19 and financial constraints for countries and institutions.
The programme fee covers registration and programme tuition, all academic materials, continuous support throughout the programme, and upon successful completion, a digital Certificate of Completion from OPHI and Oxford’s Department of International Development.
Limited financial support will be available.
The application deadline for the Leaders Programme 2021 is 30 July 2021. Slots are limited and applicants will be evaluated on the basis of the information provided in their application.
OPHI Executive Education focuses on the policy uses of the MPI and implementation of the measure. Those wishing to delve deeper into the technical side of measurement and learn how to construct and analyse the MPI are invited to apply for the OPHI Summer School.
For questions or further information, please contact us: ophi-exed@qeh.ox.ac.uk
Multidimensional Poverty Measurement and Analysis is a book from OPHI (published in June 2015) that provides an in-depth account of multidimensional poverty comparison methodologies, with a particular focus on the Alkire-Foster Method. E-chapters available now.
An Introduction to the Human Development and Capability Approach ~ Freedom and Agency OPHI supported the development of this new textbook aimed at students in the social sciences and development practitioners. It provides an introduction to Amartya Sen’s human development and capability approach. Download as a free e-textbook from IDRC website. Link to the PDF is also here.
Health emergencies pose serious threats to human lives and livelihoods, including immediate threats to health, survival, the economy and social life. WHO and OPHI have been collaborating to explore how the global Multidimensional Poverty Index (global MPI) and national Multidimensional Poverty or Vulnerability Indices (MPIs or MVIs) – could be or are already being used in health emergencies and to address health components of humanitarian crises.
This Research Brief provides an overview of their use, with the goal of sharing insights and lessons learned, as well as informing further exploration, based on how MPIs and MVIs have been used in Afghanistan, Colombia, Honduras, Iraq and the South Asia region during the COVID-19 pandemic. MPIs and MVIs capture the overlapping deprivations that people experience. They identify who is particularly disadvantaged or vulnerable by integrating information on the many dimensions of human development into a more holistic overall assessment, going beyond income or consumption. In particular, four ways of using multidimensional measures for health emergency preparedness, response and recovery are presented. (1) Constructing MVIs that capture overlapping vulnerabilities and provide information that identifies the most vulnerable and the main indicators increasing their vulnerability; (2) Using existing MPIs to inform the preparation for, response to and recovery from health emergencies; (3) Merging MPIs or MVIs with aggregate-level data to associate multidimensional measures with other indicators relevant in the context of health emergencies; (4) Microsimulating how people’s vulnerabilities or deprivations might be impacted by shocks, such as those associated with a health emergency. The use of multidimensional measures in the context of health emergencies is new. It is a field that invites further study, discussion and exploration.
Citation: WHO (2021). Using multidimensional poverty and vulnerability indices to inform equitable policies and interventions in health emergencies. Research brief. World Health Organization.
Also available on WHO website.
Empirically, official multidimensional measures of poverty often show children to be the poorest age group. Such poverty measures and their analysis can be used to directly inform policies to reduce children’s multiple deprivations. This paper introduces methods to produce official national statistics on multidimensional poverty that inform child-focused anti-poverty policies. In doing so, it recognises the importance of parsimonious, consistent measures, given practical constraints such as policy makers’ time. The paper does not recommend constructing several disjoint poverty measures which cannot be straightforwardly interpreted and used alongside one another, as these may create confusion or dilute policy attention. To create a compact and high-information measurement platform, the paper introduces four measurement strategies that have been used to directly uncover policy-relevant data on children’s experience of multidimensional poverty, and that are consistent with official population-level statistics. The four are as follows: (1) Include children’s deprivations as indicators of multidimensional poverty in national measures. (2) Disaggregate multidimensional poverty indices and their associated information platform to compare children and adults. (3) Analyse individual child deprivations and explore gendered and intra-household inequalities. (4) Construct an individual measure of child multidimensional poverty that is directly linked to the official national measure, but contains additional indicators across the life course of children. The paper illustrates these four strategies and the child-relevant statistics they yield, using examples from official poverty measures and previous research. It discusses the strengths and challenges of each method from conceptual, policy, and technical perspectives, and examines how they can be used for descriptive and prescriptive purposes in line with the Sustainable Development Goals.
Citation: Dirksen, J. and Alkire, S. (2021). ‘Children and multidimensional poverty: Four measurement strategies’, OPHI Working Paper 138, Oxford Poverty and Human Development Initiative (OPHI), University of Oxford.
This paper has been published in Sustainability, vol. 13, issue 16, article number 9108. It is published under an open access Creative Common CC BY license; any part of the article may be reused without permission provided that the original article is cited.
This 51st Methodological Note presents the methodology and technical decisions behind the global Multidimensional Poverty Index (MPI) 2021 and the results presented in global MPI 2021 Data Tables 1–8. This document is part of OPHI’s Methodological Notes series. A Methodological Note is published for every release of the global MPI. The global MPI 2021 covers the computation of MPI and its partial indices for 109 developing countries. The estimates are further disaggregated by age groups, rural/urban areas, and subnational regions. A new element in this 2021 round is that we have disaggregated by gender of household head (female and male). In addition, harmonised over time estimates are produced for 84 of the 109 countries. 56 of these countries have harmonised estimates for over two time periods, while 28 countries have harmonised estimates for over three time periods.
Citation: Alkire, S., Kanagaratnam, U., and Suppa, N. (2021). ‘The global Multidimensional Poverty Index (MPI) 2021’, OPHI MPI Methodological Note 51, Oxford Poverty and Human Development Initiative, University of Oxford.
The joint OPHI and UNDP global MPI report, Global Multidimensional Poverty Index 2021 – Unmasking disparities by ethnicity, caste and gender, presents the key findings of the global MPI 2021. The analyses:
Citation: UNDP and OPHI (2021). Global Multidimensional Poverty Index 2021 – Unmasking disparities by ethnicity, caste and gender. United Nations Development Programme and Oxford Poverty and Human Development Initiative.
Download the ethnicity tables ‘Multidimensional Poverty Index results by ethnic group 2021’.
MPI Methodological Note 49 for Tables 1–5 and MPI Methodological Note 50 for Table 6 define the statistics presented in the tables, explain the MPI indicator construction, and have entries detailing any specific data considerations for each country updated in 2020.
The do-files are the computational files that were used to create the MPI from each dataset in Stata.
| Afghanistan (AFG) | Ghana (GHA) | Nigeria (NGA) |
| Albania (ALB) | Guatemala (GTM) | North Macedonia (MKD) |
| Algeria (DZA) | Guinea (GIN) | Pakistan (PAK) |
| Angola (AGO) | Guinea-Bissau (GNB) | Palestine, State of (PSE) |
| Armenia (ARM) | Guyana (GUY) | Papua New Guinea (PNG) |
| Bangladesh (BGD) | Haiti (HTI) | Paraguay (PRY) |
| Barbados (BRB) | Honduras (HND) | Peru (PER) |
| Belize (BLZ) | India (IND) | Philippines (PHL) |
| Benin (BEN) | Indonesia (IDN) | Rwanda (RWA) |
| Bhutan (BTN) | Iraq (IRQ) | Saint Lucia (LCA) |
| Bolivia (BOL) | Jamaica (JAM) | Sao Tome and Principe (STP) |
| Bosnia & Herzegovina (BIH) | Jordan (JOR) | Senegal (SEN) |
| Botswana (BWA) | Kazakhstan (KAZ) | Serbia (SRB) |
| Brazil (BRA) | Kenya (KEN) | Seychelles (SYC) |
| Burkina Faso (BFA) | Kiribati (KIR) | Sierra Leone (SLE) |
| Burundi (BDI) | Kyrgyzstan (KGZ) | South Africa (ZAF) |
| Cambodia (KHM) | Lao PDR (LAO) | South Sudan (SSD) |
| Cameroon (CMR) | Lesotho (LSO) | Sri Lanka (LKA) |
| Central African Rep. (CAF) | Liberia (LBR) | Sudan (SDN) |
| Chad (TCD) | Libya (LBY) | Suriname (SUR) |
| China (CHN) | Madagascar (MDG) | Syria (SYR) |
| Colombia (COL) | Malawi (MWI) | Tajikistan (TJK) |
| Comoros (COM) | Maldives (MDV) | Tanzania (TZA) |
| Congo (COG) | Mali (MLI) | Thailand (THA) |
| Congo, DR (COD) | Mauritania (MRT) | Timor-Leste (TLS) |
| Côte d’Ivoire (CIV) | Mexico (MEX) | Togo (TGO) |
| Cuba (CUB) | Moldova (MDA) | Trinidad and Tobago (TTO) |
| Dominican Republic (DOM) | Mongolia (MNG) | Tunisia (TUN) |
| Ecuador (ECU) | Montenegro (MNE) | Turkmenistan (TKM) |
| Egypt (EGY) | Morocco (MAR) | Uganda (UGA) |
| El Salvador (SLV) | Mozambique (MOZ) | Ukraine (UKR) |
| eSwatini (SWZ) | Myanmar (MMR) | Vietnam (VNM) |
| Ethiopia (ETH) | Namibia (NAM) | Yemen (YEM) |
| Gabon (GAB) | Nepal (NPL) | Zambia (ZMB) |
| Gambia (GMB) | Nicaragua (NIC) | Zimbabwe (ZWE) |
| Georgia (GEO) | Niger (NER) | |
The global MPI Country Briefings present the country-specific results for the 107 countries in this year’s global MPI.
Each profile includes:
Of the countries analysed, 98 have poverty data at the subnational level, covering 1,279 regions, and this information is shared and mapped.
| Afghanistan (AFG) | Ghana (GHA) | Nigeria (NGA) |
| Albania (ALB) | Guatemala (GTM) | North Macedonia (MKD) |
| Algeria (DZA) | Guinea (GIN) | Pakistan (PAK) |
| Angola (AGO) | Guinea-Bissau (GNB) | Palestine, State of (PSE) |
| Armenia (ARM) | Guyana (GUY) | Papua New Guinea (PNG) |
| Bangladesh (BGD) | Haiti (HTI) | Paraguay (PRY) |
| Barbados (BRB) | Honduras (HND) | Peru (PER) |
| Belize (BLZ) | India (IND) | Philippines (PHL) |
| Benin (BEN) | Indonesia (IDN) | Rwanda (RWA) |
| Bhutan (BTN) | Iraq (IRQ) | Saint Lucia (LCA) |
| Bolivia (BOL) | Jamaica (JAM) | Sao Tome and Principe (STP) |
| Bosnia & Herzegovina (BIH) | Jordan (JOR) | Senegal (SEN) |
| Botswana (BWA) | Kazakhstan (KAZ) | Serbia (SRB) |
| Brazil (BRA) | Kenya (KEN) | Seychelles (SYC) |
| Burkina Faso (BFA) | Kiribati (KIR) | Sierra Leone (SLE) |
| Burundi (BDI) | Kyrgyzstan (KGZ) | South Africa (ZAF) |
| Cambodia (KHM) | Lao PDR (LAO) | South Sudan (SSD) |
| Cameroon (CMR) | Lesotho (LSO) | Sri Lanka (LKA) |
| Central African Rep. (CAF) | Liberia (LBR) | Sudan (SDN) |
| Chad (TCD) | Libya (LBY) | Suriname (SUR) |
| China (CHN) | Madagascar (MDG) | Syria (SYR) |
| Colombia (COL) | Malawi (MWI) | Tajikistan (TJK) |
| Comoros (COM) | Maldives (MDV) | Tanzania (TZA) |
| Congo (COG) | Mali (MLI) | Thailand (THA) |
| Congo, DR (COD) | Mauritania (MRT) | Timor-Leste (TLS) |
| Côte d’Ivoire (CIV) | Mexico (MEX) | Togo (TGO) |
| Cuba (CUB) | Moldova (MDA) | Trinidad and Tobago (TTO) |
| Dominican Republic (DOM) | Mongolia (MNG) | Tunisia (TUN) |
| Ecuador (ECU) | Montenegro (MNE) | Turkmenistan (TKM) |
| Egypt (EGY) | Morocco (MAR) | Uganda (UGA) |
| El Salvador (SLV) | Mozambique (MOZ) | Ukraine (UKR) |
| eSwatini (SWZ) | Myanmar (MMR) | Vietnam (VNM) |
| Ethiopia (ETH) | Namibia (NAM) | Yemen (YEM) |
| Gabon (GAB) | Nepal (NPL) | Zambia (ZMB) |
| Gambia (GMB) | Nicaragua (NIC) | Zimbabwe (ZWE) |
| Georgia (GEO) | Niger (NER) |
For the first time we offer a second series of Country Briefings on the study of poverty trends for the countries included in the Changes over Time analysis.
These briefings explore harmonized trends (indicated by MPIT) in poverty between two time points studied in each country. They cover 80 countries within the global MPI. Detailed results are presented in Table 6 and defined in the MPI Methodological Note 50.
Each profile includes:
This is the first global analysis of trends in multidimensional poverty covering five billion people. Find out more about the Changes over Time analysis in the MPI Methodological Note 50.
Please cite this document as:Oxford Poverty and Human Development Initiative (OPHI), (2020). ‘[Name of country] Country Briefing’, Multidimensional Poverty Index Data Bank. Oxford Poverty and Human Development Initiative, University of Oxford.
| Afghanistan (AFG) | Guyana (GUY) | Nigeria (NGA) |
| Albania (ALB) | Haiti (HTI) | North Macedonia (MKD) |
| Armenia (ARM) | Honduras (HND) | Pakistan (PAK) |
| Bangladesh (BGD) | India (IND) | Palestine, State of (PSE) |
| Belize (BLZ) | Indonesia (IDN) | Peru (PER) |
| Benin (BEN) | Iraq (IRQ) | Philippines (PHL) |
| Bolivia (BOL) | Jamaica (JAM) | Rwanda (RWA) |
| Bosnia & Herzegovina (BIH) | Jordan (JOR) | Sao Tome and Principe (STP) |
| Burkina Faso (BFA) | Kazakhstan (KAZ) | Senegal (SEN) |
| Burundi (BDI) | Kenya (KEN) | Serbia (SRB) |
| Cambodia (KHM) | Kyrgyzstan (KGZ) | Sierra Leone (SLE) |
| Cameroon (CMR) | Lao PDR (LAO) | Sudan (SDN) |
| Central African Rep. (CAF) | Lesotho (LSO) | Suriname (SUR) |
| Chad (TCD) | Liberia (LBR) | Tajikistan (TJK) |
| China (CHN) | Madagascar (MDG) | Tanzania (TZA) |
| Colombia (COL) | Malawi (MWI) | Thailand (THA) |
| Congo (COG) | Mali (MLI) | Timor-Leste (TLS) |
| Congo, DR (COD) | Mauritania (MRT) | Togo (TGO) |
| Côte d’Ivoire (CIV) | Mexico (MEX) | Trinidad and Tobago (TTO) |
| Dominican Republic (DOM) | Moldova (MDA) | Turkmenistan (TKM) |
| Egypt (EGY) | Mongolia (MNG) | Uganda (UGA) |
| eSwatini (SWZ) | Montenegro (MNE) | Ukraine (UKR) |
| Ethiopia (ETH) | Mozambique (MOZ) | Vietnam (VNM) |
| Gabon (GAB) | Namibia (NAM) | Yemen (YEM) |
| Gambia (GMB) | Nepal (NPL) | Zambia (ZMB) |
| Ghana (GHA) | Nicaragua (NIC) | Zimbabwe (ZWE) |
| Guinea (GIN) | Niger (NER) |
The following seminars will be given at 3pm on Mondays and will take place online.
Details and registration details will be published on talks.ox.ac.uk.
These seminars are organised jointly with the Institute for International Economic Policy at George Washington University and the UNDP Human Development Report Office. They will be hosted by Professor James Foster, GWU.
Series organisers: Dr Sabina Alkire (University of Oxford) , Professor James Foster (Georges Washington University) , Pedro Conceição (UNDP HDRO)
Dr Nicolai Suppa, CED, OPHI
18 January: ‘Sensitivity analyses in poverty measurement: The case of the global Multidimensional Poverty Index’.
Professor Sabina Alkire, OPHI
25 Jan: ‘Changes over time in the global Multidimensional Poverty Index’.
Dr Elina Scheja, Sida
1 Feb: ‘Moderate internationally comparable MPI’.
Mr Jakob Dirksen, OPHI
8 Feb: ‘Multidimensional poverty indices and children: Four measurement strategies’.
Dr Cecilia Calderon, UNDP HDRO
15 Feb: ‘Multidimensional Deprivation Index: an experimental measure for European developed countries’.
Dr Rizwan Ul Haq, PIDE
22 Feb: ‘Analysing individual deprivations alongside household poverty: Possibilities for gendered, intrahousehold, and multidimensional analyses’.
Dr Maria Emma Santos, CONICET, OPHI
1 Mar: ‘Inequality among the multidimensionally poor in over 100 countries’.
Dr Suman Seth, University of Leeds, OPHI
8 Mar: ‘Growth elasticity of multidimensional poverty in India between 2005/06 and 2015/16’
Job title: Executive Assistant and Project Administrator
Email: nteranya.sanginga@qeh.ox.ac.uk
Nteranya recently graduated from the University of Oxford’s MPhil in Development Studies. Prior to this, he was based in Minnesota, USA, where he completed his undergraduate degree in Political Science at Macalester College. He has served as the Director of Programs for Future Africa, an organisation redesigning political, economic and social discourse in Africa by bridging the gap between public policy leaders and proven approaches to address current and future development needs on the continent. He has also served as the Content Director for CongoExcellence, a facilitative platform for young Congolese around the world to elevate national economic growth and standard of living, while simultaneously sustaining this growth for future generations to come.
MPhil Development Studies, University of Oxford
BA Political Science, Macalester College
International development; post-conflict reconciliation; arts and culture; dance; dance mediation; poverty and conflict.
Alkire and Foster’s 2011 paper “Counting and Multidimensional Poverty Measurement” is posted by the Journal of Public Economics as their most cited article. The paper proposes a new methodology for multidimensional poverty measurement, and uses examples from the US and Indonesia to illustrate.
To read the article, click here.