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Dasho Karma Ura

Job title: Visiting Fellow
Email:  Please contact ophi@qeh.ox.ac.uk

Biography

Dasho Karma Ura has been the Executive President of The Centre for Bhutan Studies since 2008. From 1989 to 1998, he worked in the Planning Commission of Bhutan before joining the Centre for Bhutan and GNH Studies. He is a member of several international boards and working groups including the Advisory Board of the Wellbeing Research Centre at the University of Oxford, the Earth Trusteeship Working Group (ETWG), the Global Happiness Council in the UAE, and the World Happiness Report.

Education 

BA in Politics, Philosophy and Economics, Magdalen College, University of Oxford, UK.
MPhil in Economics, University of Edinburgh, UK.
PhD, Nagoya University, Japan.

Research interests 

Development policies; GNH (Gross National Happiness); wellbeing policy indicators; Buddhist iconographic painting and designs.

Selected publications

Books

Ura, K. (2022). The Unremembered Nation – Bhutan, Community and Livelihood, Vol. 1 Oxford: OUP (forthcoming in July 2022).

Ura, K. (2022). The Unremembered Nation – Bhutan, Art and Ideals, Vol 2. Oxford: OUP (forthcoming in July 2022).

Ura, K. (1995). The hero with a thousand Eyes: A historical novel. Thimphu: Karma Ura.

Ura, K., Alkire, S., Zangmo, T., and Wangdi, K. (2012). An extensive Analysis of GNH. Thimphu: Centre for Bhutan Studies & GNH Research.

Ura, K. and Thinley, J. (Trans). (2020) Discourse on the legal decree of Precious Palden Drukpa, victorious in all directions. Thimphu: Centre for Bhutan and GNH Studies.

Book chapters 

Ura, K. (2019). In Mearman, A., Berger, S., and Guizza, D. (Eds.). What is heterodox economics? Conversation with leadings economists (pp. 82–93). Routledge.

Ura, K. (2016). Longchen’s forests of poetry and rivers of composition: Introduction and translation of “The illuminating map – titled as forest park of flower garden – of Bumthang, the divine hidden land” by Longchen Ramjam (1308-1363). Thimphu: Centre for Bhutan and GNH Studies.

Ura, K. (2016). Gross National Happiness, values education and schooling for sustainability in Bhutan. In Gorana, R. N. and Kanaujia, P. R. (Eds.), Reorienting educational efforts for sustainable development: Experiences from South Asia, pp. 71­–88. Netherlands: Springer. Ura, K. (2017). Bhutan’s Indian rupee shortage: Macroeconomic causes and cures. In Mitra, S., and Jeong, H. Y. (Eds.), Bhutan: New pathways to growth. New Delhi: ADB and Oxford University Press.

Ura, K. (2017). The experience of Gross National Happiness as a development framework. In Mitra, S., and Jeong, H. Y. (Eds.), Bhutan: New pathways to growth. New Delhi: ADB and Oxford University Press.

Ura, K. (2016). Balancing GDP with GNH. In Thomas, S. T. (Ed.), Globalization and development: In search of new development paradigm (Vol. III), pp. 3–38. London and New York: Routledge.

Ura, K. (2013). Destiny of Nations. In Redeveloping America. UK/US: McMillan.

Ura, K. (1997). Development and tradition. In Schickgruber, C. and Pommaret, F. (Eds.), Mountain fortress of the gods, pp. 239–252. London: Serindia Publications.

Ura, K. (1994). Development and decentralization in medieval and modern Bhutan. In Aris, M., and Hutt, M. (Eds.), Bhutan: Aspects of culture and development. Scotland: Paul Strachan – Kiscadale Ltd.

Ura, K., Stringer, R., and Bulte, E. (2009). Wildlife and Human Conflicts in Bhutan. In Lipper, L., Sakuyama, T., Stringer, R., and Zilberman, D. (Eds.), Payment for environmental services in agricultural landscapes. Natural Resource Management and Policy, (Vol. XXXI). New York: Springer.

Articles

Ura, K. (1993). The nomads’ gamble: Pastoralists of northern Bhutan. In South Asia Research (Vol. XIII), pp. 81–101. School of Oriental and African Studies.

Ura, K. and Pablos, P. O. d. (Eds.). (2012). Advancing technologies for Asian business and economics: Information management developments. US: Information Science Reference, IGI Global.

Ura, K and Santos, E. (2008). Multidimensional Poverty Measurement of Poverty in Bhutan. Journal of Bhutan Studies, 18 (1). pp. 1–50.

IsDBI–OPHI Brief No. 4 ‘Exploring multidimensional poverty across IsDB Member Countries in Asia using the global MPI’

This brief, focusing on the Asia region, moves away from standard income poverty assessments and explores multidimensional poverty in seven IsDB Member Countries for which data are available. It brings to light multidimensional poverty as experienced at the national and subnational levels, providing a basis by which IsDB country programmes and government policies can be crafted.

The brief highlights the nuances of countries’ multidimensional poverty situations through a systematic analytical framework, bringing out, for example, variations across sub-regions, between urban and rural populations, and across age groups. This brief also tracks and highlights success stories, such as in Bangladesh, which made exemplary progress in reducing multidimensional poverty.

Citation: OPHI and IsDBI (2021). ‘Exploring multidimensional poverty across IsDB Member Countries in Asia using the global MPI’, IsDBI–OPHI Brief No. 4, Oxford Poverty and Human Development Initiative (OPHI) and IsDBI (Islamic Development Bank Institute), Oxford, UK.

Download IsDBI–OPHI Brief No. 4 (2021), ‘Exploring multidimensional poverty across IsDB Member Countries in Asia using the global MPI’.

IsDBI–OPHI Brief No. 2 ‘Exploring multidimensional poverty across IsDB Member Countries in MENA and Europe using the global MPI’

This brief, focusing on the Mid­dle East and North Africa (MENA) and Europe regions, moves away from standard income poverty assess­ments and explores multidimensional poverty of 15 IsDB Member Countries for which data are available. It brings to light multidimensional poverty as experienced at the national and subnational levels, providing a basis by which IsDB country programmes and government poli­cies can be crafted.

The brief highlights the nuances of countries’ multidimensional poverty situations through a systematic analytical framework, bringing out, for exam­ple, variations across sub-regions, between urban and rural populations, and across age groups. This brief also tracks and highlights success stories, such as in Mauritania, which made exemplary progress in reducing multidimensional poverty.

Citation: OPHI and IsDBI (2021). ‘Exploring multidimensional poverty across IsDB Member Countries in MENA and Europe using the global MPI’, IsDBI–OPHI Brief No. 2, Oxford Poverty and Human Development Initiative (OPHI) and IsDBI (Islamic Development Bank Institute), Oxford, UK.

Download IsDBI–OPHI Brief No. 2 (2021), ‘Exploring multidimensional poverty across IsDB Member Countries in MENA and Europe using the global MPI’.

IsDBI–OPHI Brief No. 1 ‘Exploring multidimensional poverty across IsDB Member Countries using the global MPI’

This brief moves away from standard income poverty assessments and explores multidimensional poverty in 42 IsDB Member Countries for which data are available. It brings to light multidimensional poverty as experienced at the national and subnational levels, providing a basis by which IsDB country programmes and government policies can be crafted.

The brief highlights the nuances of countries’ multidimensional poverty situations through a systematic analytical framework, bringing out, for example, variations across sub-regions, between urban and rural populations, and across age groups. This brief also tracks and highlights success stories, such as in Bangladesh, Gambia, Mauritania, and Sierra Leone, which made exemplary progress in reducing multidimensional poverty.

Citation: OPHI and IsDBI (2021). ‘Exploring multidimensional poverty across IsDB Member Countries using the global MPI’, IsDBI–OPHI Brief No. 1. Oxford Poverty and Human Development Initiative (OPHI) and IsDBI (Islamic Development Bank Institute), Oxford, UK.

Download IsDBI–OPHI Brief No. 1 (2021) ”Exploring multidimensional poverty across IsDB Member Countries using the global MPI’.

2021 – Summer School

OPHI Summer School 2021: Multidimensional Poverty Measurement and 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 was 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
AudienceThe 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 SupportLimited 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 FormTo 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.  

Global MPI Data Tables and Do-Files 2020 – archive

Global MPI data tables 2020

Table 1National Results MPI 2020 [download]
Table 2Other k Values MPI 2020 [download]
Table 3Age Results MPI 2020 [download]
Table 4Rural/Urban Area Results MPI 2020 [download]
Table 5Subnational Results MPI 2020 [download]
Table 6Changes over Time (incl. subnational, rural/urban and age disaggregation)[download]
Table 7All MPI Data 2010–2020 [download]

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.

Global MPI do-files 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)

Country Briefings 2020 – archive

Global MPI Country Briefings 2020

The global MPI Country Briefings present the country-specific results for the 107 countries in this year’s global MPI.

Each profile includes:

  • the level of multidimensional poverty, its incidence and intensity;
  • comparisons of the global MPI incidence with $1.90 a day and national monetary measures;
  • breakdowns by indicators;
  • disaggregation by urban/rural areas and subnational regions; and
  • studies of the distribution of deprivation scores that together make up the intensity of poverty across multidimensionally poor people.

Of the countries analysed, 98 have poverty data at the subnational level, covering 1,279 regions, and this information is shared and mapped.

Country Briefings 2020

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)

Changes over Time Country Briefings 2020

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:

  • the change in the MPIT, incidence, and intensity of multidimensional poverty;
  • changes in censored headcount ratios for each indicators;
  • absolute and relative changes in MPIT and incidence across subnational regions;
  • absolute reduction in MPIT across subnational regions;
  • absolute reduction in MPIT across age groups; and
  • the contribution of each indicator to MPIT in national, urban, and rural areas across the years.

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.

CoT briefings 2020

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)

Ayush Patel

Job title: Researcher
Email: Please contact ophi@qeh.ox.ac.uk

Biography

Ayush works with OPHI creating data visualization outputs and dashboards related to Multidimensional Poverty Indices (MPI). He also works on creating a guide for coding MPI using R.

His previous work involves research on rights-based laws in India and working with elected representatives and state governments for the implementation and monitoring of welfare programmes in Maharashtra, India.

Ayush is a RStudio certified tidyverse instructor and enjoys teaching data analysis skills using R.

Education

Postgraduate Diploma in Business Analytics, University of Mumbai
Postgraduate Diploma in Economics and Finance, University of Mumbai
Bachelor of Engineering, Gujarat Technological University

Research Interests

Development Economics; Multidimensional Poverty; Rights-Based Laws

Curriculum vitae

Ayush Patel’s CV (PDF)