OPHI Summer School 2021: Multidimensional Poverty Measurement & Analysis
Organised by the Oxford Poverty and Human Development Initiative (OPHI), University of Oxford, held from 9th to 21st August 2021.
*** This year, the OPHI Summer School was organised online. ***
The Summer School was aimed at those who were working on, or actively interested in gaining skills in multidimensional poverty measurement, particularly professional staff of national offices of statistics and government ministries that deal with poverty reduction, professionals from international development institutions, academics, and doctoral students. The Summer School was led by OPHI Director Sabina Alkire and the OPHI team, including researchers and academics with extensive experience of developing Multidimensional Poverty Indices (MPIs), and policy evaluation.
The purpose of this intensive Summer School was to provide a technical introduction, to multidimensional poverty measurement using the Alkire-Foster method, and to share examples of its practical applications. Upon completing the course, students had gained the skills required to construct and analyse a multidimensional poverty measure and to describe its policy relevance and usefulness for analytical purposes. Drawing on Amartya Sen’s capability approach and empirical examples of national and global Multidimensional Poverty Indices, the conceptual and empirical motivation for measuring multidimensional poverty was presented, as well as the full suite of measurement tools.
The following topics were covered:
- Unidimensional poverty measures;
- Multidimensional poverty measures and methodologies;
- The Alkire-Foster methodology of multidimensional poverty measurement;
- Measurement design – purpose, unit of measure, dimensions, indicators, cut-offs and weights;
- Estimation of multidimensional poverty and interpretation of the results;
- Subgroup decomposition and dimensional break-down;
- Multidimensional poverty changes over time;
- Interpretation and analysis of multidimensional poverty.
Course format
The Summer School consisted of two weeks of instruction and working group sessions, taught in English. Each participant needed access to a computer or laptop with Stata, and a stable and good internet connection to be part of the programme. Throughout the Summer School, participants were actively involved in discussions worked through problem sets in small groups (5 participants). They had the opportunity to attend live lectures and Q&A sessions with OPHI director Sabina Alkire, Professor James Foster, and OPHI researchers.
Dates and location
The course ran from Monday 9th August 2021 to Saturday 21st August 2021, online. Live lectures and working groups took place from Monday to Saturday, between 1.30 pm to 4.30 pm (BST).
We also offered a non-compulsory exam. Passing the exam provided a course certificate acknowledging participation and completion of the OPHI Summer School.
Costs
The course fees were as follows:
£600 GBP (students and developing country researchers)
£1,400 GBP (developing country professionals)
£2,000 GBP (developed country professionals)
In addition, participants needed to purchase their own Stata licence if they do not already have access to it.
Course Application Information
| Audience | The Summer School was aimed at those who are working on, or actively interested in gaining skills in, multidimensional poverty measurement, particularly professional staff of national offices of statistics and government ministries that deal with poverty reduction, professionals from international development institutions, academics, and doctoral students. Applicants who were currently pursuing work on measurement were also welcome. Other applicants having a demonstrated research interest in empirical analysis in these topics were considered on the basis of their experience and our capacity. |
| Prerequisites | – A demonstrable knowledge of Stata was an essential pre-requisite for attending the course. This was assessed as part of the application process. In addition, every participant needed to have Stata installed on their laptop. The software was not be provided by the Summer School. – A strong knowledge in quantitative methods and a strong interest in poverty measurement and analysis were highly desirable. – The Summer School was delivered through English so a high level of English language ability was necessary. – The Summer School was delivered online via Canvas and Zoom. Participants needed the following internet and system requirements to run these platforms: Canvas system requirements Zoom system requirements Internet speed test |
| Financial Support | Limited financial support was available. Competition for any financial support was very strong. However, well-qualified and committed applicants with financial needs were strongly encouraged to apply. Applicants were also highly encouraged to seek support from their local governments and institutions. We were happy to provide support letters for these funding applications to accepted candidates. |
| Application Form | To apply, this online application form was completed, which required you to submit a current curriculum vitae, sample Stata .do file, and a sample of written work. The application deadline for the Summer School 2020 was 30 June 2021. The application process was competitive and slots were limited; applicants were evaluated on the basis of the information provided in their application. |
| Questions? | More information at ophi-summerschool@qeh.ox.ac.uk |
In the week following OPHI’s 2021 Summer School, we offered OPHI’s inaugural Executive Education Leaders Programme: Using the MPI as a Policy Tool. This five-day online course provided top-level policymakers experience and evidence-based insights into how to use a Multidimensional Poverty Index (MPI) to guide successful poverty reduction. Through lectures, panels, and working groups, conducted by senior expert practitioners, the course leveraged candid discussions and high-level networking with fellow policymakers from around the world to share the successes and challenges of leading multidimensional poverty reduction.